Hematopathology: Genomic Mechanisms of Neoplastic Diseases

Molecular and Translational Medicine

Series Editors William B. Coleman Gregory J. Tsongalis

For further volumes: http://www.springer.com/series/8176

Domnita Crisan Editor

Hematopathology Genomic Mechanisms of Neoplastic Diseases

Editor Domnita Crisan William Beaumont Hospital Department of Clinical Pathology Molecular Pathology Lab 3601 West 13 Mile Road 48073-6769 Royal Oak, Michigan USA [email protected]

ISBN 978-1-60761-261-2 e-ISBN 978-1-60761-262-9 DOI 10.1007/978-1-60761-262-9 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2010931434 © Springer Science+Business Media, LLC 2010 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Humana Press, c/o Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Humana Press is part of Springer Science+Business Media (www.springer.com)

I dedicate this book to my mother who gave me her gene for optimism, to my brave father who lost his life fighting communists, and to my husband, Dan, who offered his loving support, with patience and enthusiasm during work on this book and my entire professional career

Preface

Hematopathology: Genomic Mechanisms of Neoplastic Diseases in the book series Molecular and Translational Medicine addresses our current knowledge of genomics as applied to the pathogenesis, diagnosis, prognosis, monitoring, and targeted therapy of hematologic malignancies. Hematology has been at the vanguard of the application of molecular technologies in diagnosis, classification, risk stratification, and use of molecularly defined therapeutic targets. These advances in molecular technologies, diagnostics, and gene-related therapy have seen an extraordinary rapid pace since the completion of the Human Genome Project. Hematology has integrated the discoveries of genomic lesions underlying hematologic malignancies and applied the tools of molecular pathology, making them essential in clinical practice. The scope of this book is to keep pathologists and clinicians abreast of the rapid and complex changes in genomic medicine, as exemplified by the molecular pathology of leukemias and lymphomas. This is a timely opportunity to not only update physicians on the complexity of genomic abnormalities but also offer an integrated framework encompassing molecular diagnostics, the new WHO (World Health Organization) classification of hematologic neoplasms with focus on molecular pathology, prognostic value of molecular tests, and molecular monitoring of response to gene-targeted therapy. The rapid pace of discovery, the explosion in genomic information, and the ever changing molecular technologies make it necessary to constantly update our knowledge and I hope that the readers will use this book as a practical resource and place it next to their microscope, in their laboratories or clinical offices. The first two chapters should be helpful for practicing pathologists and for clinicians, providing overviews of molecular techniques and cytogenetics, both well established and new, as used in molecular hematology. Chapter 3 is a concise review of the new 2008 WHO classification, which integrates molecular abnormalities in the diagnosis of hematologic neoplasms. The following chapters offer comprehensive discussions of the molecular pathology of lymphoid and myeloid acute leukemias, the mature B-cell and T-cell lymphomas, the myeloproliferation neoplasms, chronic lymphocytic leukemia, overall representing the major diagnostic entities in neoplastic hematology.

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The new fields of targeted therapy in hematologic malignancies and microRNAs as applied in hematologic malignancies are reviewed in the last two chapters and offer comprehensive discussions of the current state of these novel approaches. I am extremely grateful to all the authors for their excellent contributions to this book; each chapter is an in-depth and thought-provoking update, as well as easily readable and practical. In a specialty as exciting and rapidly evolving as Molecular Hematology, it is my hope that this will be just the first of many editions of this book. It will be interesting and challenging to see the progress in genomics in the next years and ask the question, Quo Vadis Hematology? Royal Oak, Michigan

Domnita Crisan

Contents

1 Molecular Techniques in Hematopathology . . . . . . . . . . . . . Bobby L. Boyanton Jr. and Jennifer R. Rushton

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2 Classical and Molecular Cytogenetic Analysis of Hematolymphoid Disorders . . . . . . . . . . . . . . . . . . . . Mark A. Micale

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3 Using Cytogenetic and Molecular Tests in Diagnostic Workups with the WHO Classification – 2008 . . . . . . . . . . . Clarence C. Whitcomb

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4 Update on the Molecular Pathology of Precursor Lymphoid Leukemias . . . . . . . . . . . . . . . . . Robert B. Lorsbach

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5 Molecular Pathology of Acute Myeloid Leukemias . . . . . . . . . Karen P. Mann and Debra F. Saxe

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6 Molecular Pathology of Mature B-Cell and T-Cell Lymphomas . . Sophia L. Yohe, David W. Bahler, and Marsha C. Kinney

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7 Molecular Pathology of Myeloproliferative Neoplasms . . . . . . David S. Bosler

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8 Molecular Pathology of Chronic Lymphocytic Leukemia . . . . . Daniela Hoehn, L. Jeffrey Medeiros, and Sergej Konoplev

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9 Targeted Therapy in Hematologic Malignancies . . . . . . . . . . Barbara Zehnbauer and Mona Nasser

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10 Micro-RNAs in Hematologic Malignancies . . . . . . . . . . . . . Muller Fabbri and George A. Calin

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Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors

David W. Bahler, MD, PhD Department of Pathology, University of Utah, Salt Lake City, UT, USA David S. Bosler, MD Department of Clinical Pathology, Cleveland Clinic, Cleveland, OH, USA Bobby L. Boyanton Jr, MD Department of Clinical Pathology, Beaumont Hospitals, Royal Oak, MI, USA George A. Calin, MD, PhD Departments of Experimental Therapeutics and Cancer Genetics, University of Texas, M.D. Anderson Cancer Center, Houston, TX, USA Muller Fabbri, MD Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA Daniela Hoehn, MD Department of Hematopathology, M.D. Anderson Cancer Center, Houston, TX, USA Marsha C. Kinney, MD Division of Hematopathology, University of Texas Health Sciences Center, San Antonio, TX, USA Sergej Konoplev, MD, PhD Department of Hematopathology, M.D. Anderson Cancer Center, Houston, TX, USA Robert B. Lorsbach, MD, PhD Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, AR, USA Karen P. Mann, MD, PhD Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA L. Jeffrey Medeiros, MD Department of Hematopathology, M.D. Anderson Cancer Center, Houston, TX, USA Mark A. Micale, PhD Beaumont Laboratory, Department of Anatomic Pathology, Beaumont Hospitals, Royal Oak, MI, USA

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Mona Nasser, MD Department of Clinical Chemistry, School of Medicine, Beni Suef University, Beni Suef, Egypt Jennifer R. Rushton, MD Department of Pathology, Baylor College of Medicine – BCM 315, Houston, TX, USA Debra F. Saxe, PhD Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA Clarence C. Whitcomb, MD Department of Pathology, Miller School of Medicine, University of Miami, Miami, FL, USA Sophia L. Yohe, MD Department of Laboratory Medicine and Pathology, University of Minnesota Medical Center, Minneapolis, MN, USA Barbara Zehnbauer, PhD Division of Laboratory Systems, Laboratory Practice Evaluation and Genomics Branch, Centers for Disease Control and Prevention, Atlanta, GA, USA

Chapter 1

Molecular Techniques in Hematopathology Bobby L. Boyanton Jr. and Jennifer R. Rushton

Keywords DNA · RNA · Specimen collection · Specimen handling · Specimen processing · Cell enrichment · Nucleic acid · Stability · Storage · Spectrophotometric · Fluorometric · Absorbance · Asymmetric PCR · Clonality · Immunoglobulin · T-cell receptor · Antigen receptor · Gene · Hematology · Hematolymphoid · Hematopathology · Paraffin · Formalin · Fixative · Extraction · Purification · Phenol–chloroform · Chaotropic salt · Silica column · Ethidium bromide · SYBR green · Gel electrophoresis · Capillary electrophoresis · Agarose · Polyacrylamide · Restriction enzyme · Sanger sequencing · Chain termination · Pyrosequencing · Sequencing by synthesis · Nextgeneration sequencing · High-throughput sequencing · Automation · Polymerase chain reaction · PCR · Reverse transcriptase PCR · Allele-specific PCR · Nested PCR · Real-time PCR · Quantitative PCR · Methylation PCR · FRET · TaqMan · Probe · Hydrolysis · Hybridization

Introduction The discipline of hematopathology traditionally relies upon morphologic evaluation, cytochemical stains, immunohistochemistry, flow cytometry, and karyotypic analysis to classify hematolymphoid neoplasms. Although these time-honored methods still comprise the primary diagnostic arsenal of the pathologist, the last few decades have borne witness to the widespread acceptance of molecular techniques to classify these neoplasms. No longer considered ancillary, molecular analyses have led to a greater understanding of the biological and clinical heterogeneity of hematolymphoid neoplasms, and now form the primary diagnostic criteria for many diagnoses as set forth by the World Health Organization [1]. They also provide extremely sensitive and specific methods for prognostic marker detection and minimal residual disease monitoring. These techniques have evolved rapidly over the last B.L. Boyanton Jr. (B) Department of Clinical Pathology, Beaumont Hospitals, 3601 W. Thirteen Mile Rd, Royal Oak, MI 48073, USA e-mail: [email protected]

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_1, 

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decade from Southern blot and hybridization assays to polymerase chain reaction and its variants to gene expression profiling and single-nucleotide polymorphism analysis, and more recently to microarray technology and whole-genome analysis. Despite technological advancements, molecular techniques are critically dependent upon the nature of nucleic acids retrieved from the specimen. Results cannot be correctly interpreted if the quantity and/or the integrity of nucleic acids are not optimal for the desired molecular application. As such, the purpose of this chapter is twofold. First, issues pertaining to specimen collection, handling and processing, and nucleic acid extraction, stability, and storage are reviewed. Second, molecular techniques commonly utilized in hematopathology are reviewed. Cytogenetics, fluorescent in situ hybridization (FISH), and microarray techniques are discussed in Chapter 2.

Part I: Specimen Collection and Processing Standard Precautions and Safety The collection, processing, and storage of biological samples pose risks to the handler for the acquisition of a variety of infectious agents. All personnel handling biological samples should follow “standard precautions”; guidelines are available from the US Centers for Disease Control and Prevention (www.cdc.gov). Additionally, the Clinical and Laboratory Standards Institute (www.clsi.org) publishes literature pertaining to laboratory safety [2] and the protection of laboratory workers from occupationally acquired infections [3].

Patient Identification and Labeling Specimen labeling and tracking throughout the entire testing process is paramount to ensure valid test results. Unique patient identifiers should be utilized (i.e., full name, date of birth, medical record number). In addition, the test requisition should also include (1) date and time of specimen collection, (2) specimen type and source, (3) ordering physician and contact information, (4) billing information, and (5) pertinent clinical and laboratory information. A copy of the pathology report should be included with tissue specimens to ensure accurate specimen identification and the ability to correlate molecular-based test results with the histopathologic diagnosis. Every attempt should be made to obtain stained slides for review. This will ensure that the correct tissue is submitted and that the tissue is representative of the intended test, and will allow for the qualitative assessment of cellularity. Compliance with regulations protecting personal health information as set forth by the US Department of Health & Human Services (www.hhs.gov/ocr/hippa) is of paramount importance and must be adhered to at all times.

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Cell Enrichment and Selection Techniques The ability to selectively obtain desired cell populations increases the sensitivity and specificity of molecular-based testing and facilitates the removal of potential contaminating substances that may be inhibitory to amplification-based methods, such as polymerase chain reaction (PCR). This becomes vitally important with minimal residual disease (MRD) testing, where it is not uncommon for residual malignant cells to represent a minor fraction of the cellular milieu. Basic techniques of cell selection and enrichment are discussed in this section. The isolation of DNA or RNA from select cell populations within liquid specimens (i.e., whole blood, marrow aspirates, body fluids) can be accomplished by several techniques. Perhaps the most basic approach to obtain leukocytes involves the preparation of a leukocyte-rich layer [4]. Following centrifugation (3,300–3,500×g for 10–15 min), the specimen will partition into three distinct layers: an upper aqueous layer, a middle leukocyte-rich layer (buffy coat), and a lower layer (erythrocytes). The “buffy coat” is easily recovered following removal of the upper layer. Another approach is selective erythrocyte lysis with hypotonic buffer (e.g., ammonium chloride) [5]. After centrifugation, the released hemoglobin will partition into the upper aqueous layer, while the nucleic acid of interest is retained within the leukocyte pellet at the bottom of the tube. Following decanting of the aqueous layer, the leukocyte pellet is washed several times with isotonic buffer to remove any residual aqueous layer. Alternatively, density-gradient centrifugation facilitates the selective recovery of lymphocytes and monocytes from other cellular constituents [6]. Several commercial products incorporating FicollHypaque or other density-gradient media into evacuated collection tubes specifically for molecular-based testing are available – Vacutainer CPT Mononuclear Cell Preparation Tube (Becton–Dickinson, Franklin Lakes, NJ). A more recent approach uses antibody-coated magnetic beads to obtain desired cell populations from liquid specimens. After incubation of the liquid specimen with the magnetic beads, a magnetic field is applied, allowing unwanted cellular constituents to be removed by decanting. Magnetic bead-bound cells of interest are then washed with isotonic buffer. Cells of interest are released from the magnetic beads by either enzymatic cleavage or competitive displacement using high-affinity monoclonal antibodies [7]. Alternatively, fluorescent antibody cell sorting (FACS) is also useful for capturing selected cell populations. Fluorescent, differentially labeled antibodies bind to desired cellular constituents. Using a modified flow cytometer, cells of interest are routed to separate collection chambers based upon their fluorescence profile. The cells of interest are thusly obtained and ready for nucleic acid extraction. Laser capture microdissection is a common technique that facilitates the selection of desired cell populations from tissue sections. In short, tissue is mounted on a glass slide and covered with a translucent coating. Using a microscope, cells of interest are located, followed by user-defined infrared or UV laser activation that melts the translucent coating containing the cell(s) of interest from the slide. The selected regions of dissected film are removed, followed by routine nucleic acid extraction protocols [7]. Commercial systems are available from Arcturus/MDS Analytical

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Technologies (Mountain View, CA), Carl Zeiss (Thornwood, NY), Molecular Machines and Industries (Knoxville, TN), and PALM Microlaser Technologies (Bernried, Germany).

Source-Specific Requirements to Ensure Nucleic Acid Integrity The ability to reliably detect and/or quantify results for molecular-based testing relies predominantly upon decisions made at the time of specimen collection. This is of paramount importance in dealing with hematolymphoid disorders where highly labile messenger RNA (mRNA) transcripts are commonly the intended targets for molecular-based testing. The following subsections provide general guidelines for the collection and handling of specimens pertaining to hematolymphoid disorders arising in various locations.

Bone Marrow Aspirates, Whole Blood, and Body Fluids Ethylenediaminetetraacetic acid (EDTA) is the most commonly used anticoagulant for molecular-based testing of hematolymphoid disorders, although acid–citrate– dextrose (ACD) is an acceptable alternative. Heparin should be avoided as it interferes with the polymerase chain reaction [8–10], if not completely removed during subsequent extraction and purification processes. In general, body fluids are not collected in an anticoagulant container but are commonly contaminated with erythrocytes. Prior to DNA extraction, specimens may be temporarily stored at room or refrigerated temperature (2–8◦ C) for up to 24 or 72 h, respectively, without significant DNA degradation [7]. If delays in testing are unavoidable, erythrocytes should be removed prior to storage at –20◦ C [7], as hemoglobin is inhibitory to PCR [11] and is readily released from erythrocytes upon thawing frozen marrow aspirates or whole blood. For RNA analysis, marrow aspirates and whole blood should be collected directly into tubes containing an RNA stabilization agent. The PAXgene series of RNA stabilization tubes [PreAnalytiX; joint venture, Qiagen (Valencia, CA) and Becton–Dickinson (Franklin Lake, NJ)] is widely used and has been shown to reliably maintain RNA integrity [12–16]. Other collection systems are available from Ambion (Austin, TX), Applied Biosystems (Foster City, CA), Promega (Madison, WI), Invitrogen (Carlsbad, CA), Zymo Research (Orange, CA), and Gentra Systems (Plymouth, MN). If specialized collection tubes are not utilized, EDTA-anticoagulated specimens and body fluids should be placed on wet ice and immediately transported to the laboratory. RNA extraction should take place no longer than 4 h after collection. As with DNA, if RNA extraction cannot occur in a timely manner, the erythrocytes should be removed and then the sample frozen at –20◦ C or lower [7]. Failure to comply with these recommendations may lead to erroneous test results due to either RNA degradation or altered regulation of gene expression [13].

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Dried Blood Spots (Guthrie Cards) Dried blood spots, which are routinely collected for newborn screening programs, are an invaluable source of material for retrospective epidemiological and diagnostic studies. They have been pivotal in confirming the prenatal origin of leukemia in infants and young children [17–20]. To reliably obtain nucleic acid from dried blood spots, the specimen must be thoroughly air-dried and placed in a desiccantcontaining sealed bag to prevent moisture accumulation and microbial growth. Samples must be placed in separate sealed bags to prevent cross-contamination [7]. Dried blood spots should be maintained at –20◦ C to maintain optimal nucleic acid recovery and integrity [21]. Fresh Tissue It is commonplace for laboratories to receive fresh tissue following or during surgical procedures. This facilitates the pathologist’s ability to assess the surgical specimen and appropriately direct intra-operative patient management, and is a pivotal point from which fresh tissue can be triaged for molecular-based testing. Because one cannot always predict the future downstream testing methodologies, it is prudent to handle all fresh tissue with the mindset that RNA studies will be required. In that regard, fresh tissue should be “snap frozen” in liquid nitrogen prior to storage at –70◦ C [7]. If unavailable, the sample should be placed immediately on wet ice and/or in an RNA stabilization buffer, with RNA extraction taking place within 4 h of collection [7]. Snap frozen fresh tissue should be maintained on dry ice during transportation to the processing facility. Gloves should be worn at all times when handling specimens, reagents, and equipment as RNases, and to a lesser extent DNases, are ubiquitous and readily present on skin. Furthermore, reagents and equipment should be chemically treated to destroy RNase activity. Fixed, Paraffin-Embedded Tissue Tissue fixation and embedding has profound effects on the quality and yield of nucleic acids that can be recovered from tissue. The extent of nucleic acid degradation that invariably results from fixation depends on the type of fixative, the duration of fixation, the size of the specimen and its permeability to the fixative, the degree of tissue hypoxia as determined by the time between surgical removal and fixation, and the length of storage in paraffin blocks. Degradation of nucleic acids in fixed tissues is primarily due to the cross-linking of proteins and DNA, especially for formalin-based fixatives [22–24]. This two-step process consists of an initial, reversible reaction whereby formaldehyde induces hydroxymethylation of the amino and imino groups of nucleic acid bases; the second step involves methylene bridge formation between bases over the course of several days. Both reactions are temperature dependent. Hydrogen bond disruption between base pairs is proportional to temperature so that at denaturing temperatures (>90◦ C), ssDNA predominates. Formaldehyde reacts quickly with ssDNA via hydroxymethylation, preventing reannealing when the temperature is subsequently lowered. Due to the

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high temperatures reached during the paraffin-embedding process, ssDNA would be present in formalin-fixed, paraffin-embedded tissue that would impair restriction endonuclease recognition sites. The chemical-induced protein-to-nucleic-acid cross-linking is more pronounced with extended fixation time, making it necessary to prolong the proteinase K digestion step when dealing with formalin-fixed tissues. Acid depurination of DNA is an additional mechanism of DNA degradation, if neutralization of formaldehyde is insufficient or if unbuffered formalin is used. Despite these limitations, neutral buffered formalin (NBF) still remains the best formalin-based fixative for DNA extraction and has the advantage of preserving DNA methylation patterns. Compared to NBF, extensive DNA degradation is seen with fixatives containing heavy metals, such as mercuric chloride and formalin (B-5), and dichromate and acetic acid (Zenker’s, pH 2.0) [22, 23]. Other acid fixatives, such as Bouin’s and Hollande’s also result in extensive nucleic acid degradation due to acid depurination [24, 25]. The chemical effects of mercury in B-5 and chromium in Zenker’s are due to the formation of nucleoprotein complexes with phosphoric acid residues and thiol groups. In fixed tissue, these complexes promote resistance to digestion, and the inability to obtain extracted DNA of sufficient quality. Use of other cross-linking fixatives (i.e., glutaraldehyde and paraformaldehyde) also results in variable degrees of DNA degradation [26, 27]. Utilization of acidic decalcifying solutions for bone and bone marrow core biopsies also promotes nucleic acid degradation. In contrast, precipitation fixatives (i.e., ethanol, methanol, acetone) preserve nucleic acids quite well and allow the extraction of good-quality DNA and RNA [23, 24, 28–32]. New commercially available, non-formalin-based fixatives include Histochoice (Amersco, Inc., Solon, OH), HOPE (DCS Innovative, Hamburg, Germany), UMFIX (Sakura FineTek USA, Inc., Torrance, CA), Prefer (Anatech LTD, Battle Creek, MI), and FineFix (Milestone, Bergamo, Italy). These fixatives, with the exception of Prefer [33], appear to produce good-quality nucleic acid extracts [34–40]. The duration of formalin fixation is critical for the quality and yield of nucleic acid extracts, with 12–24 h generally considered the optimal fixation time. Prolonged fixation leads to poor-quality nucleic acid extracts [22, 24, 41, 42]. In contrast, alcohol-based fixatives allow for good-quality nucleic acid extracts, irrespective of the duration of fixation. The effect of prolonged storage of archival fixed paraffin-embedded tissues on the quality and quantity of nucleic acid extracts is less well defined, but it appears that the molecular weight of extracted DNA decreases with storage beyond 2 years; however, DNA has been successfully extracted from archival paraffin blocks greater than 20 years old [43].

Part II: Nucleic Acid Extraction, Purification, and Storage Overview Prior to molecular-based testing, nucleic acids must be retrieved from the clinical specimen, by any number of manual and automated methodologies. In general, the

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first step of this process involves cell lysis, which is usually accomplished with detergents (e.g., Tween 20, sodium dodecyl sulfate) [22, 24]. The initial step should be modified based upon the specimen type. Tissues (fresh, frozen, cultured cells) have a supporting connective tissue stroma, which requires proteolytic digestion to facilitate cell lysis. Paraffin-embedded tissue should be deparaffinized prior to digestion, which can be accomplished by heat and/or a combination of solvent-based reagents (alcohol and xylene) [22, 24]. The next step involves removal of proteins from the lysate either by enzymatic digestion or by selective precipitation by adjusting the salt concentration of the lysate. Enzymatic digestion is commonly performed with proteinase K at 56◦ C – the optimal temperature for enzymatic activity [24]. The length of proteinase K incubation depends upon the amount of tissue being digested and the pH of the buffering solution, although overnight incubation is usually sufficient. After tissue digestion, proteinase K should be inactivated by heating the solution to 95◦ C for 10–15 min. The next step involves the selective extraction of nucleic acids from the cellular lysate via a number of organic or chaotropic salt– silica column-based methods. Finally, the purified nucleic acid is precipitated into a salt buffer (e.g., Tris–EDTA) prior to analysis or storage.

Extraction Techniques Organic (Phenol–Chloroform) This gold standard nucleic acid extraction method involves the hazardous hydrocarbon phenol–chloroform. In brief, the chemical properties of nucleic acids and proteins promote differential migration into the aqueous and organic phases, respectively [22, 44]. The pH of this biphasic solution is critical and maintenance within the narrow range of 7.0–8.0 is of paramount importance. Within this pH range, nucleic acids remain in the aqueous phase, while other non-essential molecules (i.e., proteins, detergents, etc.) remain in the organic phase [22, 44]. If the solution is slightly acidified, the negatively charged phosphate groups of DNA will be preferentially neutralized by excess hydrogen ions, facilitating DNA migration into the organic phase and thusly the selective extraction of RNA from the aqueous phase [44]. The addition of isoamyl alcohol to the solution also facilitates the retention of RNA with long poly-A tracts in the aqueous phase [22]. A crucial step in organic extraction is adequate mixing of the organic and aqueous phases to allow appropriate partitioning of the suspended molecules. The organic phase should be removed with a sterile pipette and appropriately discarded into an organic solvent disposal system. Extraction should be repeated by adding fresh phenol–chloroform, followed by thorough mixing until all visible protein is removed from the organic–aqueous interface [22]. The final steps involve nucleic acid precipitation from the aqueous solution, using cold ethanol and monovalent cations at 0◦ C [22]. The aqueous solution should be cautiously removed with a sterile pipette to avoid disrupting the nucleic acid precipitate. Nucleic acid should be judiciously exposed to air to facilitate complete evaporation of the ethanol. The nucleic acid pellet should be resuspended in an appropriate buffer (e.g., Tris–EDTA).

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If RNA is desired, special considerations must be followed throughout the extraction process. Gloves should be worn at all times, since skin is a common source of RNases. All equipment and reagents must be treated with diethylpyrocarbonate (DEPC) to degrade all nuclease activity. Additionally, equipment and reagents and the designated workstation should be dedicated solely for RNA extraction. DEPCtreated reagents and equipment should be autoclaved to inactivate the DEPC to prevent the carboxymethylation of nucleic acid [22]. A modified version of the phenol–chloroform method involves the addition of guanidine isothiocyanate – soR (Invitrogen, Carlsbad, CA). Guanidine isothiocyanate (GITC) called TRIzol-LS is a powerful protein denaturant and is extremely effective at eliminating RNase activity. Inorganic (Chaotropic Salt–Silica Column) Inorganic extraction is a great alternative to organic extraction, circumventing the need to handle and dispose of hazardous chemicals. Additional advantages include commercial availability, enhanced reagent stability, and reduced waste. Commercial kits employ the principles of anion-exchange chromatography, salt precipitation, and silica adsorption [22]. Perhaps the most popular format, because of its ease of use and extraction efficiency, is the chaotropic salt–silica column. GITC, a chaotropic salt, not only inactivates nucleases but also facilitates nucleic acid binding to the silica column. The silica-bound nucleic acid is purified by several washing steps that remove contaminating proteins, lipids, and other non-essential molecules. Finally, nucleic acid is eluted from the column with a low salt concentration buffer [22]. Stability of DNA in Storage Depending upon the temporal relationship between purification and analysis, the choice of diluent may dramatically impact the integrity of the DNA sample. Distilled water will promote spontaneous separation of dsDNA and concomitant degradation via residual nuclease activity [45]. Tris–EDTA buffer is the most commonly utilized storage diluent for several reasons. First, EDTA chelates divalent cations, which are necessary for nuclease activity. Second, the ionic concentration of the sodium salt facilitates DNA helix stabilization and prevents spontaneous strand separation [45]. Purified DNA can be safely stored in Tris–EDTA for up to 26 weeks at room temperature, at least for 1 year at refrigerated temperature (2 to 8◦ C) [7], and at least for 7 years at –20◦ C or lower [7, 46, 47]. The choice of storage tube is also critical as standard polypropylene and polyethylene tubes bind DNA [7], therefore, specifically engineered polypropylene tubes (polyallomer) should be utilized [7]. Stability of RNA in Storage RNA is extremely labile and degradation and/or altered gene expression begins immediately following specimen collection [13]; therefore, prudent oversight of

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tissue handling and processing (as previously described) is of paramount importance. Once purified, RNA should be stored as an ethanol precipitate at –70◦ C or lower [7, 45], since RNases still retain activity at –20◦ C [7]. Tubes and diluents for RNA storage should be nuclease free, and gloves should be worn at all times to prevent RNA degradation due to RNases [45].

Considerations for Long-Term Storage To maintain the integrity of purified nucleic acid during long-term storage, samples must be stored in an appropriate buffer and at the correct temperature. Repeated freeze–thaw cycles will compromise nucleic acid integrity and should be avoided or minimized [7, 24, 45]. Storage freezers should not be “frost free” to prevent repeated freeze–thaw cycles [7]. The work of Schaudien et al. [48] has demonstrated that realtime PCR performed on purified DNA stored in 50% glycerol retains reproducible results even after 16 freeze–thaw cycles, an observation that supports glycerol as an alternative method to preserve nucleic acid integrity.

Part III: Assessment of Nucleic Acid Quality and Quantity Nucleic acid quantity and purity may be assessed using spectrophotometric or fluorometric methods. Spectrophotometers measure the absorbance of ultraviolet (UV) light. The absorbance maximum of nucleic acid and protein is 260 nm (A260 ) and 280 nm (A280 ), respectively. Quantifying nucleic acids in solution can be accomplished by obtaining the A260 measurement. The purity of the solution may be inferred by calculating the A260 :A280 ratio. Pure DNA has an A260 :A280 ratio of 1.8, while pure RNA has an A260 :A280 ratio of 2.0 [44]. An A260 :A280 ratio lower than 1.8 indicates the presence of contaminants [44], which may interfere with downstream applications. The accuracy of the A260 :A280 ratio is dependent on the pH and the ionic strength of the solution. With increasing pH, the A280 decreases, while the A260 remains unaffected, causing a spuriously increased A260 :A280 ratio [49]. Water is mildly acidic, which results in spurious lowering of the A260 :A280 ratio. As a result, buffered solutions with slightly alkaline pH (e.g., Tris–EDTA, pH 8.0) should be used as diluents and serve as a blank for spectrophotometric measurements. Fluorometric methods, on the other hand, use fluorescent dyes that intercalate into dsDNA, are relatively insensitive to non-nucleic acid contaminants [50, 51], and provide more accurate quantitation as compared to spectrophotometric methods, especially with lower nucleic acid concentrations. When dealing with very low quantities, neither spectrophotometric nor fluorometric methods can accurately quantify nucleic acids. Other methods, such as elemental analysis and traceable phosphorus, have circumvented this issue and are discussed elsewhere [52–54]. Commercially available systems for routine clinical work, developed by Nanodrop Technologies (Wilmington, DE), offer the ability to quantify nucleic acid using only 1 μL of purified sample. The ND-1000 and ND-8000 spectrophotometers facilitate

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the testing of one and eight samples, respectively, at a time and can accurately quantify nucleic acid in the nanogram per microliter range. The fluorometric ND-3300 is a more sensitive, low-throughput option that can quantify nucleic acids down to the picogram per microliter range. The previously discussed methodologies can quantify and assess nucleic acid purity; however, they are unable to assess quality in terms of molecular weight. A basic option is the electrophoresis of purified nucleic acid in an ethidium bromidestained agarose gel. High-quality, non-fragmented DNA will form a solitary band near the application well, while degraded DNA will appear as a smear throughout the lane. RNA integrity may be assessed by the electrophoresis of RNA on a denaturing ethidium bromide-stained agarose gel. Two distinct bands should be visualized, corresponding to 28S and 18S ribosomal RNA. The 28S rRNA band should be about twice the intensity of the 18S rRNA band. As RNA degrades, the intensity of the 28S and 18S rRNA bands will correspondingly decrease and, analogous to DNA, appear as a smear throughout the lane (see Fig. 1.1). Intercalating dyes (i.e., SYBR Green, PicoGreen) are replacing ethidium bromide due to its hazardous and mutagenic properties. Novel methods like the Agilent 2100 bioanalyzer (Agilent Technologies, Santa Clara, CA) use a combination of fluorescent dyes, capillary electrophoresis, and microfluidics technology to simultaneously assess the concentration and integrity of nucleic acids. In short, purified nucleic acids migrate through a microfluidics chip and bind to intercalating dyes, with the fluorescence signal being measured as each molecule passes through the detection system. The outcome is a summary of variously sized molecules and their corresponding peak heights, reflecting nucleic acid integrity and concentration, respectively [55].

Part IV: Selected Techniques Electrophoresis Electrophoresis is the process by which molecules under the influence of an electrical field are differentially separated within a liquid or a solid matrix. The differential separation of molecules is based upon many factors, including the size of each molecule and its three-dimensional conformation, the net charge of the molecule (as dictated by pH), the pore size of the matrix being utilized, and the amount of electrical current utilized [56]. Because nucleic acids are negatively charged, they will migrate toward the positive electrode (anode). The degree of migration toward the anode is based largely upon the size of the nucleic acid molecules and the matrix pore size, while the speed at which migration occurs is primarily reflected by the amount of electrical current applied and the matrix pore size. The composition and concentration of the matrix dictates the pore size; the mobility of nucleic acids within the matrix is inversely proportional to the log of the pore size [44]. Therefore, large molecules will demonstrate limited migration and will remain closer to the

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Fig. 1.1 Qualitative assessment of nucleic acid integrity by gel electrophoresis. Ethidium bromide stained, 2% agarose gel following electrophoresis. (Lanes 1 and 6) intentionally left blank; (lane 2) molecular weight size markers (100, 200, 300, 400, 500, 525, 700, 1,000 bp); (lane 3) genomic DNA (lambda phage DNA – Catalog # 25250-010, Invitrogen, Carlsbad, CA), demonstrating a single band (approximately 48,500 bp) near the application well, signifying the recovery of intact, high molecular weight DNA following extraction; (lane 4) human RNA, demonstrating two distinct bands (28S and 18S ribosomal RNA), signifying the recovery of intact RNA following extraction; (lane 5) degraded human RNA, demonstrating residual 28S and 18S bands and “smearing” of degraded RNA throughout the entire lane, representing variously sized RNA fragments. Degraded DNA would demonstrate a similar “smearing” pattern throughout the lane

negative electrode (cathode), while smaller molecules will migrate further to the positive electrode (anode). Agarose gel is the primary matrix utilized in clinical molecular laboratories for the electrophoretic separation of nucleic acids, and is formed by dissolving agarose gel powder into boiling electrophoresis buffer solution, followed by pouring into a casting tray for solidification. Ethidium bromide (EtBr), an intercalating dye used to facilitate nucleic acid visualization following ultraviolet light exposure, is usually added prior to pouring the liquid solution into the casting tray. Alternatively after electrophoresis, agarose gels can be submerged into a solution of EtBr to accomplish the same end result. Agarose gels with concentrations around 1% are typically

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utilized to resolve nucleic acid fragments in the range of 1–20 kb because of the relatively large pore size created. Higher concentrations of agarose (2–3%) decrease the pore size and are able to accurately resolve nucleic acid fragments between 100 and 2,000 bp. Polyacrylamide gels consist of polymerized acrylamide monomers that form small pores, facilitating the resolution of nucleic acid fragments in the range of 100–1,000 bp. Polyacrylamide gels are less commonly utilized due to their fragile nature and serious risks to laboratory personnel – acrylamide monomers are respiratory irritants and neurotoxic. Capillary electrophoresis (CE) is a separation technique whereby proteins, nucleic acids, and other analytes are differentially separated and analyzed in the interior of a small caliber capillary. Commercially available CE systems are readily available with varying configurations to accommodate the various needs of molecular diagnostic laboratories. In contrast to conventional electrophoresis, CE offers numerous advantages, including standardized protocols, ease of use, increased efficiency of workforce utilization, error reduction, increased throughput, and automation. In brief, CE separates analytes (i.e., nucleic acids, proteins, etc.) within a lowviscosity, electrolyte-containing liquid polymer that functions as a sieving matrix and facilitates current conduction within the capillary. Capillary tubes range from 25 to 100 cm in length and are approximately 50 μm in diameter [44]. Capillaries are constructed of glass (silica) and externally coated with a polymer for stability. The internal capillary wall consists of neutral silanol (Si–OH) groups that must be ionized to negatively charged silanolate (Si–O– ) groups prior to use. This is usually accomplished by first priming the capillary with a basic solution of sodium hydroxide or potassium hydroxide. When the low-viscosity liquid polymer is injected into the capillary and electrical current applied, electrolytes within the liquid polymer flow from the injection site to the opposing end where signal detection occurs. The sample is electrokinetically injected into the capillary, whereby the concentration of the low-viscosity polymer establishes the sieving matrix and differentially sized molecules are electrophoretically separated as they too move from injection site to the detection end. At the detection end of the capillary, a small portion of the external stability polymer is absent – so-called detection window. The detection window is optically aligned between a laser source (argon or diode) and a charge-coupled device (CCD) camera or filter wheel and photomultiplier tube (PMT). As analytes electrophoretically separate within the capillary, they are temporally detected as they pass by the detection window. In contrast to conventional gel electrophoresis, CE is more sensitive to DNA concentration and contaminants. When relatively large quantities of DNA of a particular molecular weight pass through the detection window, the signal intensity can overwhelm the detection system and generate a high-amplitude primary peak and a second adjacent lower amplitude peak (usually 1 bp greater in size) – so-called “shadow peak.” Additionally, high-amplitude peaks may be spuriously detected in more than one of the detection channels due to failure of the color compensation system to completely eliminate spectral overlap from the various fluorescent dyes that are incorporated into the DNA fragments. Other unwanted charged species that enter

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into the capillary can interfere with the electrophoretic mobility of nucleic acids and/or alter the intensity of the fluorescent signal. It is therefore commonplace to include a post-amplification purification step prior to electrokinetic injection. The purification step not only reduces contaminants but also incorporates formamide into the loading buffer that stabilizes DNA and optimizes capillary electrophoretic resolution. In the clinical molecular laboratory, CE is primarily utilized for DNA sequencing and DNA fragment sizing; however it may be used for quantitative purposes since the detected signal intensity is directly proportional to the amount of each fragment passing by the detection window. Current applications of CE to the practice of hematopathology include dideoxynucleotide chain termination DNA sequencing [57], evaluation of immunoglobulin heavy chain and T-cell receptor gene rearrangements for clonality assessment [58], fragment size analysis for the detection of small gene insertions and duplications, such as those characteristic of NPM1 and FLT3 genes in acute myeloid leukemia (AML) [59], and BCR–ABL fusion transcript size analysis for the discrimination of the three common fusion transcripts encountered in chronic myeloid leukemia (CML) [60].

Restriction Enzymes Restriction endonucleases (REs) are enzymes that cleave double-stranded DNA (dsDNA) at specific nucleotide recognition sites or restriction sites. These enzymes are ubiquitous in bacteria and are thought to have evolved as a defense mechanism facilitating the degradation of foreign DNA [61]. Specific methyltransferase enzymes chemically modify, via a process termed methylation, recognition sites, thereby protecting microbial DNA from its own degradation. REs are generally categorized into three classes based upon their target sequence, enzyme cofactor requirements, and the position of their DNA cleavage site relative to the target sequence. The majority of REs utilized in clinical molecular laboratories are class II and detailed discussion of these classes is beyond the scope of this chapter. In brief, class II REs require only the presence of magnesium (Mg2+ ), are usually palindromic in nature, recognize very small DNA lengths (usually 4–8 bases), and cleave dsDNA at or near the restriction site resulting in “blunt” or “sticky” ends [56]. Since their discovery in the early 1970s, thousands of REs have been characterized and a plethora of these are commercially available [62]. REs were crucial in the development of recombinant DNA technology, including the mass production of proinsulin [63], and have been widely adopted into the clinical molecular laboratory due to their unique ability to confirm the presence of desired PCR amplification products by knowing the predicted size of individual DNA fragments following digestion. These unique recognition sites occur at variable frequency throughout a given DNA sequence. Therefore, DNA digestion using different restriction enzymes will result in a unique pattern of DNA fragments upon separation. Furthermore, a change in restriction enzyme digestion pattern may result if mutations or polymorphisms occur at these recognition sites. A recognition site may be created or destroyed as a result

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of such a sequence variation. The creation of a new recognition site results in two smaller fragments in a sample with a mutation, whereas the destruction of a recognition site results in a larger DNA fragment in a sample with a mutation. These size differences can be detected by standard gel electrophoresis or CE. These changes in fragment pattern have been utilized in neoplastic hematopathology for the detection of a variety of point mutations, including FLT3 D835 mutation in AML and JAK2 V617F mutation in myeloproliferative neoplasms (MPN) [64, 65].

DNA Sequencing Sequencing refers to a set of analytical methods to determine the sequence or the order of nucleotide bases (adenine, guanine, cytosine, thymine) within a DNA molecule. In 1977, two independent research groups published ground-breaking technological developments that facilitated the ability to determine the sequence of DNA. In brief, Maxam and Gilbert [66] used chemicals to fragment radiolabeled DNA at specific bases, while Sanger and colleagues [67] used radiolabeled chainterminating inhibitors. The work of Sanger et al. [67] was acknowledged with a Nobel Prize in Chemistry in 1980 and established the fundamental sequencing technique utilized for the Human Genome Project and clinical molecular laboratories. Over the last two decades, modifications of Sanger sequencing as well as alternative DNA sequencing strategies have occurred. Subsequent sections on DNA sequencing will focus upon Sanger chain termination methods and modifications thereof, pyrosequencing or sequencing by synthesis, and next-generation sequencing. Sanger Sequencing Sanger sequencing is a multistep process that begins with PCR-based amplification of target DNA, followed by removal of excess deoxynucleotide triphosphates (dNTPs) and PCR primers. The next few steps involve denaturation of the dsDNA to facilitate the annealing of a sequencing primer to the 5 -end of the desired region of DNA to be sequenced and the addition of a thermostable DNA polymerase and a mixture of dNTPs and dideoxynucleotide triphosphates (ddNTPs). During repeated thermal cycling, the DNA polymerase recognizes the annealed sequencing primer at the 5 -end of the region of interest and in a 5 - to 3 -direction creates a new strand of DNA (complementary to the template DNA) as the dNTPs and ddNTPs are incorporated. ddNTPs retain a 5 -hydroxyl group which allows for their incorporation into the newly synthesized DNA strand; however, ddNTPs lack a 3 -hydroxyl group which prevents the subsequent incorporation of additional dNTPs or ddNTPs by DNA polymerase. Consequently, incorporated ddNTPs terminate the ability of the DNA polymerase to further extend the newly synthesized DNA strand. The rate of ddNTP incorporation is dependent upon the molar ratio of dNTPs to ddNTPs and the ability of the DNA polymerase to recognize and insert them into the growing DNA strand. In the initial paper by Sanger et al. [67], four separate sequencing reactions were required, each containing identical reagents, chain-terminating ddNTPs (ddATP, ddGTP, ddTTP, ddCTP), and a

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radiolabeled dNTP, usually [35 S]dATP or [32 P]dATP. Following thermal cycling, each reaction consisted of a pool of DNA fragments of varying lengths corresponding to when each respective chain-terminating ddNTP was incorporated. The DNA fragments underwent high-resolution electrophoresis with each sequencing reaction occupying an individual lane in a polyacrylamide gel. Exposure of the gel to X-ray film allowed visualization of the variously sized DNA fragments due to the incorporation of the radiolabeled dATP. The DNA sequence was obtained by reading the “staggered stair step” banding pattern in reverse order (anode to cathode) corresponding to smallest to largest DNA fragments. Although Sanger sequencing was an important milestone in molecular biology, the technique was labor intensive, time consuming, exposed personnel to radioactive materials and X-rays, and was not adaptable to automation. Modifications of Sanger sequencing emerged in the mid-1980s, whereby sequencing primers were differentially labeled with fluorescence dyes – so-called dye-primer chemistry [68, 69]. Similar to the original Sanger method, four separate sequencing reactions were required; however, the completed reactions could be pooled and DNA fragments resolved within a single lane on a polyacrylamide gel that was coupled to a laser-induced multi-wavelength fluorescence detection system. Not long thereafter, fluorescence dye-primer chemistry was replaced with fluorescence dye-terminator chemistry. This technological advancement paved the way for complete automation of the DNA sequencing process by eliminating the need for four separate sequencing reactions, utilizing a single sequencing primer, and the ability to resolve the DNA fragments to a single base pair with gel or capillary electrophoretic techniques, each coupled with laser-induced multi-wavelength fluorescence detection systems. The most commonly employed fluorescent dyes were carboxyfluorescein (FAM), carboxy-4 , 5 -dichloro-2 , 7 -dimethoxyfluorescein (JOE), carboxy-X-rhodamine (ROX), and carboxytetramethylrhodamine (TAMRA) because their emission wavelengths are spaced such that there is minimal spectral overlap, facilitating accurate detection and base pair resolution. The adaptation of fluorescence resonance energy transfer (FRET) technology to DNA sequencing was introduced in the mid-1990s using labeled sequencing primers [70], and shortly thereafter to labeled chain terminator ddNTPs [71]. FRET-labeled dye-terminator chemistry for the most part is the most commonly employed Sanger-based sequencing technology and is marR R by Applied Biosystems (Foster City, CA). BigDye chemistry keted as BigDye yields superb signal strength, is easily adapted to automated DNA-sequencing platforms, and produces little if any differential mobility of DNA during electrophoretic separation [56, 72, 73]. Although Sanger-based sequencing technologies provide high-quality sequence information in the range of several hundred to thousand bases, there are still practical limitations that need to be considered. Despite automation, Sanger-based sequencing is still relatively labor intensive, time consuming, expensive, and requires specialized equipment. It also has limited sensitivity for detecting point mutations, approximately 20% mutant DNA within a wild-type background [74–76]. Despite these drawbacks, Sanger-based sequencing is an invaluable tool for the clinical molecular laboratory and is becoming more commonplace over time.

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Pyrosequencing Pyrosequencing, or sequencing by synthesis, was conceptualized in 1985 [77]. The principle underwent modifications over the following decade [78, 79] and in the late 1990s was shown to be a rapid, cost-effective alternative to Sanger sequencing [80, 81]. It differs from Sanger sequencing by relying upon the detection of released pyrophosphate upon dNTP incorporation, rather than chain-terminating ddNTP incorporation. In brief, purified PCR amplicons are denatured to single-stranded DNA (ssDNA) templates and immobilized onto streptavidin-coated magnetic beads. The next series of steps involve four enzymes (Klenow fragment of DNA polymerase I [82] sulfurylase [83], luciferase [84], apyrase [85]), enzyme substrates (adenosine phosphosulfate, D-luciferin), the sequencing template with annealed sequencing primer, and dNTPs (dATP, dCTP, dGTP, dTTP). Each dNTP is dispensed one at a time in a repetitious cyclic manner, initiating an enzymatic cascade. For each dNTP incorporated into the newly synthesized DNA strand by DNA polymerase I, a molecule of inorganic pyrophosphate (PPi) is released which becomes the substrate for ATP generation by ATP sulfurylase. The generated ATP is utilized by luciferase to emit a bioluminescent signal. Unincorporated dNTPs and excess ATP are continuously degraded prior to the subsequent dispensation of dNTPs. Due to the stoichiometric relationship of substrates to products within this enzymatic cascade, the intensity of the generated signal is directly proportional to the number of each dNTP incorporated. The bioluminescent signal is detected and analyzed by the instrument in real time with the resultant generation of a pyrogram which consists of a series of peaks whose temporal relationship and height reflect the DNA sequence [86]. Detailed textual and pictorial descriptions of pyrosequencing are available [81, 87] but are beyond the scope of this chapter. Important properties of pyrosequencing include the ability to obtain highquality, semi-quantitative sequence data of 20–40 bases in real time and the ability to control the dNTP dispensation order. These unique properties make pyrosequencing advantageous for detecting mutations within short segments of DNA and the analysis of single-nucleotide polymorphisms (SNPs) [88]. The semi-quantitative nature of pyrosequencing facilitates determining the allelic ratio in hematopoietic chimerism or mixed clonality/heterogeneous tissue samples, the latter of which is characteristic of myeloproliferative neoplasms (MPNs) [76]. Dilution experiments demonstrate the ability of pyrosequencing to obtain assay sensitivity as low as 5% mutant allele within a wild-type background [89, 90]. More recently, pyrosequencing demonstrated utility in following patients with CML to detect changes in the relative proportion of mutant clones conferring dasatinib resistance or intolerance [91]. The ability of pyrosequencing to detect epigenetic changes (i.e., DNA methylation patterns) has also been described with applications to various hematolymphoid malignancies [92–94]. Analytical drawbacks of pyrosequencing include limited base read length and “plus and minus” frameshift, all of which have been improved by the addition of E. coli single-stranded binding protein (SSB). “Plus and minus” frameshifts are caused by insufficient activity of apyrase and DNA polymerase I (Klenow

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fragment), respectively. The addition of SSB stabilizes ssDNA and protects it from degradation and conformation changes during the pyrosequencing reaction, and through various mechanisms minimizes the effect of “plus and minus” frameshift, detailed mechanistic descriptions of which are discussed elsewhere [87]. Pyrosequencing technology was originally commercialized by Pyrosequencing AB (Uppsala, Sweden), later renamed Biotage (Uppsala, Sweden) in 2003 and was recently acquired by Qiagen (Gaithersburg, MD) in 2008. Pyrosequencing technology was also licensed to 454 Life Sciences that notably developed the first large-scale, high-throughput DNA-sequencing platform, thereby laying the foundation for next-generation sequencing. 454 Life Sciences has recently been acquired by Roche Diagnostics. Next-Generation Sequencing (NGS) Sanger-based sequencing has dominated the molecular biology landscape over the last three decades, primarily due to the desire of the international community to sequence the entire human genome. As a result, Sanger-based sequencing was quickly adapted to large-scale, high-throughput automation allowing parallel sequencing of DNA in up to 384 capillaries at a time. The industrialization of Sanger-based sequencing, primarily undertaken by Applied Biosystems, Inc. (Forster City, CA), facilitated the sequencing of the human genome in 2003. As the molecular biology community sought to expedite the sequencing of the human genome and that of other species, it became readily apparent that other technologies would be required. Over the last two decades, considerable resources were invested to the development of alternative sequencing strategies, and as recently as 2005 their utility was demonstrated. These novel sequencing strategies ushered in the new era of high-throughput sequencing and hence next-generation sequencing (NGS) was born. NGS provides numerous advantages over automated Sanger-based methods, including high speed and throughput, full automation, expense reduction, and the determination of sequence data from amplified single DNA fragments, negating the need for the in vitro cloning of DNA fragments. The high-throughput nature and decreased expense of NGS cannot be overemphasized. For perspective, Sangerbased sequencing of the entire human genome took 13 years with an estimated cost approaching $3 billion. In comparison, NGS technology sequenced the entire human genome in 5 months at a cost of $1.5 million [95, 96]. Despite these advantages, NGS does have drawbacks. Instrumentation is extremely expensive (range $500,000 to over $1 million), with individual sequencing runs costing over $5,000. With this being said, it is still several orders of magnitude less expensive than Sanger-based sequencing on a cost per base basis [97]. NGS is slightly more prone to sequencing errors due to non-uniform confidence in base calling, especially when dealing with homopolymeric tracts, and some technologies suffer from short read lengths. Furthermore, the quantity of sequence information generated per sequencing reaction (range 80 Mb–3 Gb) [98] creates an enormous amount of data (range 15 GB–15 TB) [95], which require unique information technology solutions for data storage and analysis.

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All NGS platforms have a common technological feature – the ability for highthroughput sequencing of clonally amplified or single DNA molecules which are spatially separated in a flow cell. Sequencing is performed by iterated cycles of either polymerase-mediated dNTP extension or oligonucleotide ligation [95]. Descriptions of the various technological strategies employed with NGS along with their advantages and disadvantages are beyond the scope of this chapter but have been thoroughly reviewed [95, 97, 99, 100]. Since 2005, numerous NGS technologies have emerged and are commercially available from Roche Applied Science (454 GenomeSequencer FLX), Illumina (Illumina/Solexa Genome Analyzer), Applied Biosystems (Supported Oligonucleotide Ligation and Detection system, SOLiD), and Helicos BioSciences (HeliScope). Other NGS platforms in the developmental phase are from VisiGen Biotechnologies and Pacific Biosciences. Although NGS was initially developed as a high-throughput means of genomic sequencing, novel applications of this technology are beginning to emerge. Examples include personalized medicine with detailed analysis of selected portions of the human genome, transcriptome analysis or the analysis of RNA transcript expression, the identification of selected regions of DNA that interact with gene expression regulatory elements, and the genome-wide characterization of mRNAs, chromatin structure, and DNA methylation patterns [97, 101]. To date, the literature is sparse in regard to applying NGS to hematolymphoid neoplasms, but this should be temporary. A recent review by Neff et al. [102] shed light on the application of NGS to study epigenetic changes in leukemia. Furthermore, the ability of NGS to characterize the genome-wide transcriptome profile of normal and cancerous tissues under controlled conditions (e.g., presence of selected anti-neoplastic drugs) should shed light on mechanisms of differential RNA expression, paving the way for the rapid development and employment of new anti-neoplastic agents [103–105].

Polymerase Chain Reaction Polymerase chain reaction (PCR) is an in vitro, DNA polymerase-dependent method for the exponential amplification of nucleic acid. From its inception in the midto-late 1980s, this invention [106] has revolutionized the direction of molecular diagnostic testing and is without question one of the most important milestones in the field of molecular testing. Compared to older technologies used to analyze DNA, such as the Southern blot, PCR is much more rapid, provides superior specificity and sensitivity, is less technically challenging, and allows for much higher throughput. For these reasons, PCR has become an indispensable tool in the practice of hematopathology. PCR is dependent on thermal cycling, i.e., iterative cycles of heating and cooling to allow for melting and annealing of DNA sequences, respectively. A standard PCR requires a target DNA template, two oligonucleotide primers, which are complementary to opposite strands of denatured target DNA, a thermostable DNA polymerase such as Taq, all four deoxynucleotide triphosphates (dNTPs), magnesium as a cofactor to Taq, and a buffer solution. There are three main temperature-dependent steps in the PCR. First, the target DNA is denatured at 94–98◦ C for 10–60 s. The high temperature disrupts the hydrogen bonds between

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complementary strands of DNA, resulting in single-stranded DNA. In the second step, the temperature is lowered to 50–70◦ C for 10–60 s to allow annealing of primers to the denatured target DNA. The primer sequences must be highly complementary to the target DNA for stable annealing to occur. Primer extension occurs in the third step at an intermediate temperature of 65–75◦ C. The DNA polymerase synthesizes a strand of DNA complementary to the target DNA by adding the appropriate dNTPs to the 3 -ends of the primers. This PCR cycle is then repeated 25–40 times. A programmable thermal cycler is used to automatically change the reaction temperature at the appropriate times. The thermostability of the polymerase eliminates the need to replace the enzyme after each cycle [107]. In subsequent PCR cycles, the amplification products can serve as templates, resulting in the doubling of target DNA during each cycle of PCR. This exponential amplification of template DNA is followed by a slowing of the reaction and eventual plateau as reagents are consumed and the activity of the polymerase is diminished. As mentioned above, PCR is a highly sensitive and specific target amplification method. The sensitivity of the reaction is due to the exponential amplification of template DNA, which allows for the amplification of even minute amounts of DNA. Because amplification products can serve as templates in subsequent cycles of PCR, these reactions are also highly sensitive to contamination by amplicons from previous reactions, which may result in false-positive results. Thoughtful laboratory design, including the separation of pre-PCR and post-PCR areas, as well as clean laboratory practices, can help prevent contamination by PCR amplicon or other extraneous DNA. On the other hand, the specificity of the reaction is primarily conferred by the two PCR primers, which anneal to the target DNA only if there is a degree of sequence complementarity and only at an appropriate temperature. The optimal annealing temperature is dependent on the length of the primer as well as the guanosine–cytosine (GC) content of the primer. The specificity of hybridization can be controlled by varying the annealing temperature or the magnesium concentration. Increasing the temperature or decreasing the magnesium concentration results in a more stringent hybridization, while lowering the temperature or increasing the magnesium concentration will lower the stringency of the reaction. Furthermore, extension of a PCR primer occurs only if there is perfect complementarity at the 3 -end of the primer due to the sensitivity of Taq polymerase to mismatches at this location. To prevent the generation of nonspecific amplification products, Taq polymerase activity may be inhibited early in the reaction by waiting to add Taq to the reaction mix until denaturation begins, by separating Taq from the reaction mix using a barrier, or by using specialized systems incorporating Taq inhibitors that dissociate at a high temperature. This variation on PCR is known as hot-start PCR. The specificity of conventional PCR must be confirmed by visualization of the PCR product. The size of the PCR product can be determined by standard gel electrophoresis or CE. Alternatively, or in addition to fragment size analysis, the PCR product can also be sequenced to ensure the specificity of the reaction. A variety of organic and inorganic compounds may inhibit PCR, including hemoglobin and urea. Consideration of possible inhibitors is important in the interpretation of a negative PCR result, as is the inclusion of an internal amplification control to confirm that amplification was not inhibited. Current clinical applications of conventional PCR

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to the practice of hematopathology include the amplification of DNA for subsequent assessment of clonality and for the detection of recurrent genetic abnormalities including point mutations by sequencing or fragment size analysis as mentioned above. Multiple primer sets can be included in a single PCR to amplify multiple targets from a single specimen in a variation on PCR called multiplex PCR. Effective primer design is critical for the success of multiplex PCR, and the reaction must be optimized to ensure functionality of the multiple primer sets in a single reaction. Many other variations on the conventional PCR have been developed and have current applications to the field of hematopathology.

Reverse Transcription PCR (RT-PCR) Reverse transcription PCR (RT-PCR) is a ribonucleic acid (RNA)-based PCR, which utilizes reverse transcriptase, an RNA-dependent DNA polymerase, capable of DNA polymerization using RNA as a template. The resulting complementary DNA (cDNA) strand is much more stable than the RNA target and can be used as a template in any subsequent PCR application. A single reverse transcription (RT) reaction allows for subsequent PCR analysis of multiple targets from the resultant cDNA. RT using random hexamer primers results in cDNA complementary to total RNA, whereas the use of specific oligo-dT primers results in cDNA complementary to mRNA only. Alternatively, gene-specific primers can be used to produce cDNA complementary to the gene of interest only. The availability of enzymes capable of using both RNA and DNA as templates for DNA polymerization has eliminated the need for an extra enzymatic step and increased the efficiency of RT-PCR [108]. As mentioned above, RNA is highly susceptible to degradation by ubiquitous RNases, and care is needed when handling RNA to prevent excessive loss or fragmentation. There are numerous applications of RT-PCR in hematopathology, including the detection of various fusion transcripts. The length of genomic DNA spanning chromosomal translocations usually prohibits their detection by PCR. However, since introns are removed from mRNA, these translocations can be more readily detected in the form of fusion mRNA transcripts. Some of the fusion transcripts currently evaluated by RT-PCR include BCR–ABL1 in CML and acute lymphoblastic leukemia (ALL), ETV6–RUNX1 and E2A–PBX1 in ALL, PML– RARA, RUNX1–ETO, CBFB–MYH11, RUNX1–RUNX1T1, and DEK–NUP214 in AML, NPM–ALK in anaplastic large-cell lymphoma, and BCL2–IGH in follicular lymphoma. Detection of these chromosomal translocations by RT-PCR is useful at the time of diagnosis both for risk stratification and treatment determination as well as following therapy for monitoring the presence of minimal residual disease.

Allele-Specific PCR Allele-specific PCR is used primarily for the detection of point mutations and single-nucleotide polymorphisms (SNPs). Whereas in conventional PCR, primers

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are designed to be complementary to an invariant region of the target DNA, allele-specific PCR utilizes a primer whose 3 -end includes the mutated site. Allele-specific PCR is also referred to as allele-specific oligonucleotide PCR and amplification refractory mutation system (ARMS) [109]. As mentioned above, there must be perfect sequence complementarity at the 3 -end of a primer and the target DNA for amplification to occur. Under stringent conditions, any mismatch at this location will prevent amplification from occurring. ARMS consists of two separate amplification reactions, one utilizing a wild-type allele-specific primer and one utilizing a mutant allele-specific primer. The second primer is common to both reactions. If amplification occurs only in the mutant reaction, a homozygous mutation is present. If amplification occurs in both reactions, a heterozygous mutation is present. If amplification occurs only in the wild-type reaction, no mutation is present. One caveat of ARMS is that a polymorphism or an unsuspected mutation at the 3 -end of the primers will prevent amplification and may lead to misinterpretation of results. Furthermore, amplification controls should be included in the reactions to exclude the possibility of PCR inhibition. Current clinical applications of ARMS–PCR include the identification of JAK2 V617F mutations in MPN [110] and ABL kinase domain mutations in imatinib resistance [111].

Nested PCR Nested PCR is a variation of PCR with increased sensitivity and specificity [112]. Nested PCR involves the use of two successive rounds of PCR using two primer pairs, one of which is located internally to the other. First, the outer primer set is used to amplify the target sequence. The PCR products are then amplified using the inner primer set, resulting in final PCR products that are shorter than the initial products. Nested PCR is highly specific since the second primer pair is complementary to sequences within the amplicons produced in the first reaction. Each PCR consists of approximately 25 cycles, resulting in approximately 50 total cycles of PCR. This high total cycle number is responsible for the high sensitivity of nested PCR. In addition, the smaller products obtained from the first PCR are more readily denatured in the second reaction, resulting in abundant template DNA. However, because the initial PCR product is manipulated during transfer to the second PCR tube, there is a high risk of amplicon contamination. Due to its exquisite sensitivity, nested PCR has been used to monitor the presence of minimal residual disease after therapy for acute and chronic leukemias [113, 114].

Real-Time PCR Real-time PCR involves the visualization of amplicon generation in real time using fluorescence detection during the exponential phase of PCR [115, 116]. In other words, target amplification and detection occur simultaneously in a single tube using a special thermal cycler, which monitors fluorescence emission and generates an amplification curve. The amount of fluorescence detected is directly proportional to

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the amount of PCR product, which is directly proportional to the amount of starting target DNA. Therefore, real-time PCR can be used to quantify the amount of target DNA present in a clinical sample. A real-time PCR growth curve is composed of a baseline or lag phase, a log-linear or exponential amplification phase, and a plateau phase. During the lag phase, the specific fluorescent signal is less than the background nonspecific fluorescence or autofluorescence. The crossing point or cycle threshold (Ct) is the point at which the growth curve enters the log-linear phase. The Ct is indirectly proportional to the amount of starting template such that a lower Ct value implies a larger amount of initial template. During the plateau phase, amplicon accumulation slows as reagents become rate limiting and the efficiency of the DNA polymerase declines. Real-time PCR holds several advantages over conventional end-point PCR, including faster turnaround time, higher reproducibility, wider dynamic range, and lower risk of amplicon contamination. Since real-time PCR is monitored in real time, there is no need for post-amplification analysis, such as electrophoresis. The elimination of post-amplification manipulation of the PCR products greatly reduces the risk of carryover contamination and the time required to complete the analysis. Melting curve analysis can increase the specificity of real-time PCR by confirming that amplification of the appropriate target has occurred. Melting curve analysis involves increasing the temperature of the reaction until the double-stranded amplicon is denatured [117]. This melting results in a decrease in fluorescence and a characteristic melting peak. The melting peak of an amplicon is based on its melting temperature, which will be distinct from the melting temperatures of nonspecific PCR products. Melting curve analysis is currently used in the practice of hematopathology for the detection of JAK2 V617F mutations. The specificity of real-time PCR can also be increased by incorporating hybridization probes into the reaction. A variety of methods can be used to generate a fluorescent signal, including nonspecific intercalating dyes and fluorescently labeled primers and probes.

Signal Detection Options SYBR Green and ethidium bromide are nonspecific intercalating dyes that fluoresce when bound to dsDNA. Nonspecific dyes simply indicate the presence of dsDNA, including nonspecific PCR products and primer dimers. Sequence-specific probes, on the other hand, indicate the generation of a specific amplicon. The amount of fluorescence is directly proportional to the amount of specific product generated. Many sequence-specific fluorescent probes utilize the phenomenon of fluorescent resonance energy transfer (FRET). FRET occurs when a donor dye is excited by an external light source. Instead of emitting light, the donor transfers this energy to an acceptor dye when the donor and acceptor are in close proximity. When energy transfer occurs, the acceptor molecule quenches the fluorescence of the donor molecule. The acceptor dye then emits light in an amount proportional to the amount of PCR product present.

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TaqMan probes are complementary to a PCR product at a location between the two primer-binding sites. TaqMan probes contain a 5 reporter donor and a 3 acceptor that quenches the reporter. When the probe is intact, the acceptor quenches the reporter, and no fluorescence is generated. However, upon primer extension, the probe is cleaved by the 5 to 3 exonuclease activity of Taq polymerase, which releases the reporter from the quenching activity of the acceptor [118]. The resulting fluorescent signal is proportional to the amount of amplicon generated. Since the probe is hydrolyzed, it is unavailable for future reactions and precludes the ability to utilize melting curve analysis. TaqMan probes have found widespread use in neoplastic hematopathology, including the detection of various fusion transcripts. As opposed to hydrolysis probes, hybridization probes remain intact throughout the reaction. A simple hybridization probe system consists of two fluorescently labeled probes, one donor and one reporter acceptor. The probes are complementary to adjacent sequences of the PCR product between the two primer-binding sequences. Upon annealing to amplicon, the donor and the acceptor are placed into close proximity, and a fluorescent signal is generated. In contrast to hydrolysis probes, Taq polymerase simply displaces hybridization probes, which remain intact and available for the next amplification cycle as well as subsequent melting curve analysis. Variations of hybridization probes include molecular beacons and scorpion probes, characterized by a hairpin loop structure. Molecular beacons are single probes with a 5 reporter and a 3 quencher [119]. When unbound, the probe forms a hairpin loop structure, and the reporter is quenched. During the annealing step, the hairpin loop unfolds, and the probe hybridizes to a complementary sequence in the amplicon. This annealing of probe to product separates the reporter from the quencher, and a fluorescent signal is generated. Similarly, a scorpion probe utilizes a hairpin loop structure to bring the reporter and the quencher into proximity. However, scorpions contain a primer covalently linked to the probe [120]. To date, molecular beacon probes and scorpion probes have found clinical applications primarily in the molecular microbiology lab for pathogen detection. However, this technology has the potential for clinical applicability in hematopathology, especially for the sensitive detection and quantification of point mutations, such as JAK2 V617F [121], and for monitoring minimal residual disease [122].

Quantitative Real-Time PCR Quantitative real-time PCR (Q-PCR) is currently the most accurate method for quantifying DNA or RNA. Because real-time PCR analysis occurs in the early log phase of amplification, this method is less sensitive to differences in PCR efficiency between reactions. In Q-PCR, a standard curve is generated using samples of known template concentration. The concentrations of unknown samples can then be extrapolated from the standard curve (Fig. 1.2). Q-PCR is currently utilized in hematopathology to monitor minimal residual disease post-therapy, especially for ALL, AML, and CML. The amount of minimal residual disease may be used clinically to assess the efficacy of therapy, to determine further treatment type

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Fig. 1.2 Quantitative real-time RT-PCR. Real-time PCR amplification curves (top) and standard curve (bottom) generated from a 10-fold dilution series of a known standard. Graphical data obtained from a quantitative real-time RT-PCR assay for BCR–ABL (Ipsogen, Inc., Stamford, CT) using the LightCycler 1.2 (Roche Applied Science, Indianapolis, IN)

and timing, as well as for prognostic information [123]. Q-PCR is also used to quantify the allelic burden of JAK2 V617F in patients with a myeloproliferative neoplasm [124].

Methylation-Specific PCR DNA methylation is an epigenetic phenomenon critical for transcriptional regulation and is an essential process in human development. In humans, DNA is methylated at CpG islands, i.e., cytosines located 5 to guanosines. CpG islands are present in the 5 regulatory regions of many human genes. Aberrant hypermethylation has been demonstrated to be an important mechanism for transcriptional dysregulation in neoplasia and may contribute to the development of leukemias and lymphomas. Methylation-specific PCR is one way to distinguish methylated from unmethylated DNA [125]. Treatment of DNA with sodium bisulfite converts unmethylated cytosine to uracil while leaving methylated cytosine intact. Following sodium bisulfite treatment, methylation-specific PCR amplifies DNA using primers specific for either methylated or unmethylated DNA. The primer sets for methylated

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and unmethylated sequences are identical except at CpG islands, where one primer pair recognizes cytosine in methylated DNA and the other primer pair recognizes uracil in unmethylated DNA. The PCR products can then be analyzed by standard gel electrophoresis or CE to identify methylated or unmethylated target sequences or both. While a variety of differentially methylated genes have been described in hematolymphoid neoplasia, no applications have been implemented in the clinical laboratory to date.

Restriction Site PCR Restriction site-generating PCR generates an artificial RE recognition site. Briefly, a PCR primer is designed to have a mismatch with the template adjacent to the mutation of interest. The mismatched base creates a restriction site in either the wild-type or the mutant amplicon. The RE digestion pattern can then be analyzed by standard gel electrophoresis or CE. This method can be theoretically used in hematopathology for the detection of mutations which do not result in the creation or loss of an RE recognition site. However, this variation on PCR has not gained widespread clinical use to date.

Asymmetric PCR Asymmetric PCR is a variation on PCR which preferentially amplifies one strand of target DNA over the other. This outcome is typically accomplished by using excess amounts of the primer complementary to the desired single-stranded product. Upon depletion of the limiting primer during the exponential phase, amplification of the desired strand occurs in a linear fashion. For this reason, asymmetric PCR requires additional cycles of PCR and at times may be inefficient and difficult to optimize. Linear-after-the-exponential PCR (LATE-PCR) is a specific type of asymmetric PCR with increased efficiency due to the use of a limiting primer with a higher melting temperature than the excess primer. While asymmetric PCR may be used for the detection of a variety of mutations in hematolymphoid neoplasia, clinical applications of LATE-PCR are not yet widespread in the practice of hematopathology.

Clonality Assessment Overview The majority of hematolymphoid disorders can be characterized as malignant or reactive/benign by clinical history, morphology, and immunophenotyping using ancillary studies (i.e., immunohistochemistry, flow cytometry). However, up to 10% of cases may remain elusive [126]. As such, clonality assessment is an invaluable

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tool to further characterize these cases. In principle, all cells comprising a malignant process are monoclonal because they arise, via the process of clonal expansion, from a common malignant cell; likewise, reactive/benign conditions are polyclonal as they are composed of numerous unique cell populations. Clonality assessment relies upon the techniques of Southern blotting and PCR to analyze the immunoglobulin and T-cell receptor genes. Immunoglobulin (Ig) and T-cell receptors (TCRs) are encoded by gene segment clusters that undergo genetic (somatic) recombination during the development and maturation of B and T cells in the bone marrow and thymus, respectively. This recombination essentially involves the splicing and fusion of one of numerous variable (V), diversity (D), joining (J), and constant (C) regions. Diversity (D) regions are not present within Ig kappa, Ig lambda, TCR alpha, and TCR gamma chains. The recombination process is sequential in that one gene segment from each of the D (if applicable) and J regions rearrange first, followed by V to DJ rearrangement. The assembled V–J or V–D–J segments will subsequently be joined to a distinct constant (C) region to create a unique coding sequence capable of being translated into a functional antigen receptor protein [127, 128]. Immune cells yielding non-functional antigen receptors undergo programmed cell death via the process of apoptosis. In regard to immature B cells, the Ig heavy (IGH) chain is the first to undergo somatic recombination. If the first allele is non-functional, the second allele will rearrange to produce a function gene. Therefore, a single B cell can have two different IGH rearrangements, one functional and one non-functional. Rearrangement of the kappa (κ) light chain is next and occurs only if the IGH rearrangement was successful. The lambda (λ) light chain will undergo somatic recombination only if both alleles from the kappa light chain are non-productive, in which case the non-functional kappa light chain gene segments will be deleted. The end result is an intact coding sequence which facilitates the creation of a functional immunoglobulin protein receptor. In regard to T cells, the T-cell receptor gamma (TCRγ) and delta (TCRδ) loci begin the somatic recombination process. Approximately 10% of T cells will express a functional heterodimeric gamma–delta T-cell receptor (TCRγδ). The majority (90%) of T cells will encode a non-functional TCRγδ (gamma delta) antigen receptor and thus will rely upon the TCR alpha (α) and TCR beta (β) loci to generate a functional, heterodimeric T-cell receptor (TCRαβ) (alpha beta). It is imperative to understand that the majority of mature T cells expressing a TCRαβ (alpha beta) phenotype still retain the non-functional γδ (gamma delta) gene rearrangement – a unique feature that can be exploited with molecular-based testing for clonality assessment. The immune system requires an enormous repertoire of antigen receptors to facilitate the recognition of an almost infinite number of antigens. Immunoglobulin and T-cell receptor antigen diversity is primarily derived from the numerous genetic segments available within the V, D, and J regions that are randomly chosen to undergo somatic recombination (Table 1.1). As a result, the number of combinatorial possibilities is significant, at approximately 2 × 106 , 3 × 106 , and 5 × 103 for the Ig, TCRαβ (alpha beta), and TCRγδ (gamma delta),

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respectively [126]. Additional diversity is facilitated by two mechanisms: (1) imperfection in junction site splicing and (2) the enzymatic action of terminal deoxynucleotidyl transferase (TdT), which adds or deletes individual nucleotides and/or small oligonucleotide sequences at the V–D–J splice sites (Fig. 1.3). Following Table 1.1 General characteristics of the immunoglobulin (Ig) and T-cell receptor (TCR) genes. Standardized nomenclature, chromosomal location of individual genes, and approximate number of gene segments contained within the variable, diversity, joining, and constant regions are provided. Compiled from multiple sources [126, 138, 139] Antigen receptor Ig

TCR

Gene

Gene location

Variable (V) Diversity (D)

Joining (J)

Heavy (H) Kappa (κ) Lambda (λ) Alpha (α) Beta (β) Gamma (γ) Delta (δ)

14q32 2p11–12 22q11 14q11 7q34 7p15 14q11

>100 50–100 20–70 50–100 75–100 14 10

9 5

30 0 0 0 2 0 3

Constant (C)

11 1 7 J–C clusters 50–100 1 13 2 5 2 3 1

Fig. 1.3 Schematic of immunoglobulin heavy chain (IGH) receptor gene. Basic process of somatic recombination at the IGH locus occurring within developing B cells. Random selection and rearrangement of first diversity (DH ) and joining (JH ) gene segments, followed next by a variable (VH ) gene segment completes the primary V–D–J coding sequence. Antigen diversity is derived from the unique nucleotide sequences of the randomly selected gene segments. Further diversity stems from terminal deoxynucleotidyl transferase (TdT) which inserts a random number of “nontemplate”-derived nucleotides (designated “n”) at the variable, diversity, and joining junction sites. The finished V–D–J segment is then joined with a constant (CH ) region to complete the final IGHcoding sequence for protein synthesis. The IGH variable region (VH ) is further divided into three framework regions (FRs) and three complementarity-determining regions (CDRs). Due to the high degree of sequence homology with the framework regions, PCR-based assays can utilize differentially labeled fluorescent forward (FR1, FR2, FR3) and non-labeled reverse (FR4) primers to generate fluorescently labeled amplicons that can subsequently undergo capillary electrophoretic resolution

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successful rearrangement, the immunoglobulin genes within mature B cells may undergo additional genetic alterations to “fine-tune” their antigen receptor via the processes of isotype switching and somatic hypermutation within the germinal center.

Techniques Molecular laboratories generally rely upon the molecular techniques of Southern blotting and PCR-based methods for clonality assessment and focus on IGH, TCRγ (gamma), and TCRβ (beta) gene rearrangements. Although still considered by many to be the gold standard, Southern blot analysis is performed only by a few laboratories because of slow turnaround time (usually 5–7 days), expense, and labor-intensive nature and inherent technical challenges of this methodology. Southern blotting requires microgram or greater quantities of intact, high molecular weight DNA which can be obtained only from fresh tissue, not fixed or fixed paraffin-embedded tissue. Additionally, the sensitivity of this method is around 10%, meaning that approximately 10% of the clonal population must be represented in the tissue submitted for analysis to be reliably detected by this methodology [126]. In brief, clonality assessment by Southern blot involves subjecting high molecular weight DNA to RE digestion, whereby clonal gene rearrangements will yield a different restriction fragment length pattern as compared to the germ line configuration. Radiolabeled probes are hybridized to the digested DNA fragments and visualized. For B-cell clonality, probes are usually directed toward the joining (J) regions of the IGH chain or the Ig kappa light chains [126]. For T-cell clonality, probes are generally directed toward the constant (C) or joining (J) regions of the TCRβ (beta) gene. Southern blot analysis generally fails to detect monoclonal populations when targeting the TCRγ (gamma) gene. Due to the inherent challenges of Southern blot analysis, the majority of molecular laboratories rely upon PCR-based methods for clonality assessment. Because PCR-based methods amplify relatively short distances (usually <1,000 bp) of DNA, this approach is advantageous for formalin-fixed, paraffin-embedded tissue, where DNA fragmentation is universally encountered. Furthermore, the sensitivity of PCRbased method approaches 1% (i.e., 1 clonal cell in a background of 99 polyclonal cells), especially when coupled with capillary electrophoresis, an important tool from the viewpoint of initial diagnosis and minimal residual disease monitoring. In general, these methods employ multiple primer sets (i.e., consensus primers) that target conserved gene segments within variable (V) and joining (J) regions of the antigen receptor genes that have undergone somatic recombination, due to the close proximity of the V–J or V–D–J coding sequence. These consensus primers will amplify both clonal and polyclonal (background) cell populations, the latter of which is depicted as a smear on gel-based detection platforms. Using fluorescently labeled primers, which are incorporated into the amplified products, background cell populations will appear as a Gaussian distribution of peaks when resolved by capillary electrophoresis (Fig. 1.4).

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Fig. 1.4 Electropherogram of IGH gene rearrangement following three separate PCR-based amplification reactions using differentially labeled fluorescent primers. Each PCR reaction utilized the same consensus joining (JH ) region reverse primer targeting the framework 4 (FR4) region and separate consensus forward primers targeting the framework 1 (FR1, top panel), framework 2 (FR2, middle panel), and framework 3 (FR3, bottom panel) regions of the IGH gene. Each panel clearly indicates the presence of a distinct, monoclonal peak. Top and bottom panels also demonstrate the concomitant presence of normal cell populations as indicated by the Gaussian distribution of polyclonal B cells

PCR-based analysis of the IGH gene is perhaps the most commonly employed method of clonality assessment. The V–D–J rearrangement created after somatic recombination can be further subdivided into discrete functional units, entitled framework regions (FRs), and complementarity-determining regions (CDRs) (Fig. 1.3). The three framework regions (FR1, FR2, FR3) within the VH region have a high degree of sequence similarity allowing for the creation of forward consensus primers. The fourth framework region (FR4) is located in the JH region and allows for the creation of a universal reverse primer. In contrast, the complementaritydetermining regions (CDR1, CDR2, CDR3) play an integral part in antigen receptor diversity and as such contain tremendous sequence diversity. Assays employing FR3 and JH consensus primers will detect 60–70% of malignant B-cell neoplasms [126]. This detection rate can exceed 80% by the addition of consensus primer sets targeting the FR1 and FR2 regions [126, 129] and has been further increased by using more extensive primer sets as reported by the BIOMED-2 consortium project [130, 131]. Because the FR1 and JH consensus primers generate the largest amplicons (range, 350–450 bp), there is a higher chance of false-negative results if significant DNA degradation is present. It is therefore imperative to incorporate amplicon size-matched internal controls to assess the degree of DNA degradation for each sample analyzed. PCR-based methods will not detect all clonal B-cell populations. False-negative results are commonly encountered with post-germinal center B-cell malignancies (i.e., chronic lymphocytic leukemia, follicular lymphoma, plasma cell malignancies) due to somatic hypermutation. This process

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normally occurs within the germinal center and facilitates additional alterations of the V–D–J coding sequence of the IGH genes within cells. This process facilitates “fine-tuning” of the antigen recognition sites of the Ig receptor, however, alters the DNA sequence within the VH and JH regions such that PCR consensus primers no longer anneal to the template DNA, thereby severely reducing or preventing amplification. PCR-based clonality assessment of the TCR is usually performed on the TCRγ (gamma) and/or TCRβ (beta) chain; however, due to the complexity of the TCRβ (beta) locus (i.e., 75–100 V segments, 2 D segments, 13 J segments) and the requirement for a large number of amplification primers, most laboratories analyze only TCRγ (gamma). In comparison, the TCRγ (gamma) locus is considerably simple containing only 14 V segments and 5 J segments, with the former divided into four discrete families (Vγ1–8, Vγ9, Vγ10, and Vγ11). As such PCR analysis requires relatively few consensus primer sets to amplify the corresponding V–J coding sequence following somatic recombination. The vast majority (>90%) of T-cell malignancies will be detected with this approach [132–134].

Limitations Limitations of molecular-based methods of antigen receptor clonality assessment consist of DNA degradation, lineage infidelity, detection of clonal populations within reactive/benign processes, oligoclonality/clonal evolution, and primerbinding site mutations due to somatic hypermutation. DNA degradation is a common limitation and is generally due to formalin fixation as previously discussed. It is prudent to include amplicon size-matched internal controls to assess the degree of DNA degradation with each sample to be tested. However, it should be noted that false-negative results may still occur if the quantity of DNA to be amplified for clonality assessment is disproportionally less than the amount of DNA to be amplified for the internal controls. Lineage infidelity is a phenomenon whereby discordance exists between the detected clonal antigen receptor rearrangement and the immunophenotype of the cell [i.e., detecting a TCRγ (gamma) gene rearrangement in a B-cell lymphoma]. This commonly occurs with precursor B-cell malignancies (i.e., precursor B-cell acute lymphoblastic leukemia) and is uncommonly encountered (<10%) with mature B-cell malignancies. Although this process is not entirely understood, it is thought that immature B cells may rearrange their TCR genes prior to receiving appropriate cues from the cellular milieu (i.e., bone marrow) to direct their commitment to the B-cell lineage. Once committed to the B-cell lineage, the appropriate IGH and IGκ (kappa) or IGH and IGλ (lambda) gene rearrangements occur as previously discussed; however, the rearranged TCR gene is not deleted and can be detected. This concept is important to understand and as such, the use of molecularbased methods for clonality assessment should be discouraged to assign cellular lineage.

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The ability to detect a clonal cell population does not always equate to malignancy, as small B-cell clones may be detected in benign/reactive lymphoid hyperplasia without supporting morphologic or immunophenotypic (immunohistochemical and/or flow cytometric) evidence of neoplasia [135–137]. This situation may occur in the setting of autoimmune disease, immunodeficiency states, and certain infections. As such it is prudent to correlate molecular test results with other clinical, morphologic, and immunophenotypic data. Another limitation of PCR-based methods of clonality assessment is oligoclonality and clonal evolution. By definition, an oligoclonal pattern indicates the presence of more than two bands following PCR and electrophoretic resolution. This type of pattern is commonly seen in reactive processes where there are fewer distinct cellular populations (i.e., expansion of several cell clones, no longer polyclonal) as would be expected to facilitate a focused cellular response to the pathologic process. This pattern is also seen in immunocompromised individuals who have a reduced cellular repertoire and in paucicellular specimens. The latter situation is commonly encountered with diminutive skin specimens (i.e., punch and shave biopsies), and as such it is imperative to review the histologic preparations of the corresponding material submitted for molecular analysis. It is also possible for an individual to have two separate, simultaneous monoclonal processes. Prior to entertaining this remote possibility, correlation of the molecular testing results with other morphologic and immunophenotypic information is warranted. Lastly, clonal evolution is the process whereby during the course of the disease process, additional genetic alterations occur within the antigen receptor genes. This will lead to either an alteration of the so-called tumor-specific signature (i.e., unique size of the monoclonal peak) or primer annealing site mutations such that the so-called signature peak of the tumor is no longer detected. When the latter situation occurs, patient monitoring should be performed with either flow cytometric analysis and/or an alternative antigen receptor rearrangement assay [i.e., IGκ (kappa), IGλ (lambda)] if informative.

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118. Holland PM, Abramson RD, Watson R, et al. Detection of specific polymerase chain reaction product by utilizing the 5 -3 exonuclease activity of Thermus aquaticus DNA polymerase. Proc Natl Acad Sci USA. 1991;88:7276–7280. 119. Tyagi S, Bratu DP, Kramer FR. Multicolor molecular beacons for allele discrimination. Nat Biotechnol. 1998;16:49–53. 120. Thelwell N, Millington S, Solinas A, et al. Mode of action and application of Scorpion primers to mutation detection. Nucleic Acids Res. 2000;28:3752–3761. 121. Sidon P, Heimann P, Lambert F, et al. Combined locked nucleic acid and molecular beacon technologies for sensitive detection of the JAK2V617F somatic single-base sequence variant. Clin Chem. 2006;52:1436–1438. 122. Martinez-Lopez J, Lahuerta JJ, Salama P, et al. The use of fluorescent molecular beacons in real time PCR of IgH gene rearrangements for quantitative evaluation of multiple myeloma. Clin Lab Haematol. 2004;26:31–35. 123. van der Velden VH, Hochhaus A, Cazzaniga G, et al. Detection of minimal residual disease in hematologic malignancies by real-time quantitative PCR: principles, approaches, and laboratory aspects. Leukemia. 2003;17:1013–1034. 124. Lucia E, Martino B, Mammi C, et al. The incidence of JAK2 V617F mutation in bcr/abl-negative chronic myeloproliferative disorders: assessment by two different detection methods. Leuk Lymphoma. 2008;49:1907–1915. 125. Herman JG, Graff JR, Myohanen S, et al. Methylation-specific PCR: a novel PCR assay for methylation status of CpG islands. Proc Natl Acad Sci USA. 1996;93: 9821–9826. 126. Mariappan MR AD. Molecular diagnostics in hematopathology. In: Pfeifer JD, ed. Molecular Genetic Testing in Surgical Pathology. 1st ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2006. pp. 250–274. 127. Bassing CH, Swat W, Alt FW. The mechanism and regulation of chromosomal V(D)J recombination. Cell. 2002;109:S45–S55. 128. Macintyre EA, Delabesse E. Molecular approaches to the diagnosis and evaluation of lymphoid malignancies. Semin Hematol. 1999;36:373–389. 129. Bagg A, Braziel RM, Arber DA, et al. Immunoglobulin heavy chain gene analysis in lymphomas: a multi-center study demonstrating the heterogeneity of performance of polymerase chain reaction assays. J Mol Diagn. 2002;4:81–89. 130. van Dongen JJ, Langerak AW, Bruggemann M, et al. Design and standardization of PCR primers and protocols for detection of clonal immunoglobulin and T-cell receptor gene recombinations in suspect lymphoproliferations: report of the BIOMED-2 Concerted Action BMH4-CT98-3936. Leukemia. 2003;17:2257–2317. 131. van Krieken JH, Langerak AW, San Miguel JF, et al. Clonality analysis for antigen receptor genes: preliminary results from the Biomed-2 concerted action PL 96-3936. Hum Pathol. 2003;34:359–361. 132. Greiner TC, Raffeld M, Lutz C, et al. Analysis of T cell receptor-gamma gene rearrangements by denaturing gradient gel electrophoresis of GC-clamped polymerase chain reaction products. Correlation with tumor-specific sequences. Am J Pathol. 1995;146:46–55. 133. Greiner TC, Rubocki RJ. Effectiveness of capillary electrophoresis using fluorescent-labeled primers in detecting T-cell receptor gamma gene rearrangements. J Mol Diagn. 2002;4: 137–143. 134. Theodorou I, Bigorgne C, Delfau MH, et al. VJ rearrangements of the TCR gamma locus in peripheral T-cell lymphomas: analysis by polymerase chain reaction and denaturing gradient gel electrophoresis. J Pathol. 1996;178:303–310. 135. Elenitoba-Johnson KS, Bohling SD, Mitchell RS, et al. PCR analysis of the immunoglobulin heavy chain gene in polyclonal processes can yield pseudoclonal bands as an artifact of low B cell number. J Mol Diagn. 2000;2:92–96. 136. Lee SC, Berg KD, Racke FK, et al. Pseudo-spikes are common in histologically benign lymphoid tissues. J Mol Diagn. 2000;2:145–152.

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137. Nihal M, Mikkola D, Wood GS. Detection of clonally restricted immunoglobulin heavy chain gene rearrangements in normal and lesional skin: analysis of the B cell component of the skin-associated lymphoid tissue and implications for the molecular diagnosis of cutaneous B cell lymphomas. J Mol Diagn. 2000;2:5–10. 138. Pan L CE, Knowles DM. Antigen receptor genes: structure, function, and genetic analysis of their rearrangements. In: Knowles DM, ed. Neoplastic Hematopathology. Philadelphia, PA: Lippincott Williams & Wilkins; 2001. pp. 307–328. 139. Viswanatha DS, Larson RS. Molecular diagnosis of hematopoietic neoplasms. In: McPherson RA, Pincus MR, eds. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 21st ed. Philadelphia, PA: Saunders Elsevier; 2007. pp. 1295–1322.

Chapter 2

Classical and Molecular Cytogenetic Analysis of Hematolymphoid Disorders Mark A. Micale

Keywords Myelodysplastic/myeloproliferative disorders · Leukemia · Lymphoma · Fluorescence in situ hybridization · Array comparative genomic hybridization (array CGH) · WHO Classification of Tumors of Hematopoietic and Lymphoid Tissues · Hematolymphoid neoplasms · Philadelphia chromosome · Chronic myelogenous leukemia (CML) · Burkitt lymphoma · BCR/ABL · PML/RARA · Acute promyelocytic leukemia · Chromosome microarray analysis · International System of Human Cytogenetic Nomenclature (2009) · Illegitimate V(D)J or switch recombination · ALU sequences · LINE elements · Error-prone non-homologous end joining · Translin-binding consensus sequences · Scaffold-associated regions · Centromere enumeration probes (CEPs) · Locus-specific identifier (LSI) probes · Whole-chromosome paint (WCP) probes · Dual-color · dual-fusion (DCDF) LSI probes · Interphase FISH · Paraffin FISH · Myeloproliferative neoplasms (MPNs) · JAK2 V617F mutation · FIP1L1-PDGFRA · ASS gene · Imatinib mesylate (Gleevec) · Postpolycythemic myelofibrosis · Essential thrombocythemia · Primary myelofibrosis · HMGA2 gene · Chronic neutrophilic leukemia · Normal karyotype · Chronic eosinophilic leukemia/idiopathic hypereosinophilic syndrome · Myeloid and lymphoid neoplasms with PDGFRA rearrangements · Polycythemia vera · Hypereosinophilia · CHIC2 gene · Myelodysplastic syndrome · Chromosome 5q deletion · MDS associated with isolated del(5q) · Loss of the Y chromosome · MDS-FISH panel · Monosomy 5/del(5q) · Monosomy 7/del(7q) · Chromosome 11q deletion · Chromosome 13q deletion · Acute myeloid leukemia (AML) · Therapy-related- or t-AML · AML with t(8;21)(q22;q22) – RUNX1/RUNX1T1 · AML (promyelocytic) with t(15;17)(q22;q12) – PML/RARα · ZBTB16/RARα · NPM1/RARα · NUMA1/RARα · RARα gene · All-trans-retinoic acid (ATRA) · AML with t(9;11)(p22;q23) – MLLT3/MLL · MLL (myeloid lymphoid lineage or mixed lineage leukemia)

M.A. Micale (B) Beaumont Laboratory, Department of Anatomic Pathology, Beaumont Hospitals, 3601 W. Thirteen Mile Rd, Royal Oak, MI 48073, USA e-mail: [email protected]

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_2, 

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gene · t(9;11)(p21;q23) · t(11;19)(q23;p13.1) · t(11;19)(q23;p13.3) · MLL gene break-apart probe · AML with inv(16)(p13q22) or t(16;16)(p13;q22) – CBFβ/MYH · acute myelomonocytic leukemia (AMML) · Core binding factor beta subunit (CBFβ) · AML with t(6;9)(p23;q34) – DEK/NUP214 · Multilineage dysplasia · FLT3-ITD · AML with inv(3)(q21q26.2) or t(3;3)(q21;q26.2) – RPN1/EVI1 · AML (megakaryoblastic) with t(1;22)(p13;q13) – RBM15-MKL1 · Acute myeloid leukemia with myelodysplasia-related changes · Therapy-related myeloid neoplasms · Alkylating agent · Topoisomerase II inhibitor therapy · Acute myeloid leukemia · not otherwise specified · Acute myeloid leukemia with minimal differentiation · Acute myeloid leukemia without maturation · Acute myeloid leukemia with maturation · Acute myelomonocytic leukemia · Acute monoblastic and monocytic leukemia · Acute erythroid leukemia · Acute megakaryoblastic leukemia · Acute basophilic leukemia · Acute panmyelosis with myelofibrosis · B-lymphoblastic leukemia/lymphoma with recurrent genetic abnormalities · Acute lymphoblastic leukemia (ALL) · Childhood ALL · B-lymphoblastic leukemia/lymphoma with hyperdiploidy · Hyperdiploid ALL · Hypodiploid ALL · B-lymphoblastic leukemia/lymphoma with hypodiploidy · B-lymphoblastic leukemia/lymphoma with t(12;21)(p13;q22) · TEL/AML1 (ETV6/RUNX1) · TEL (ETV6) gene · AML1 (CBFA2 or RUNX1) gene · B-lymphoblastic leukemia/lymphoma with t(9;22)(q34;q11.2) · BCR/ABL · B-lymphoblastic leukemia/lymphoma with t(v;11q23) · MLL rearranged · B-lymphoblastic leukemia/lymphoma with t(1;19)(q23;p13.3) · ETA/PBX1 (TCF3/PBX1) · B-lymphoblastic leukemia/lymphoma with t(5;14)(q31;q32) · IL3/IGH · Children’s Oncology Group (COG) · T-lymphoblastic leukemia/lymphoma · T-cell receptor (TCR) genes · chronic lymphocytic leukemia/small lymphocytic lymphoma · MYB gene · ATM gene D13S319 locus · LAMP1 gene · p53 gene · CLL FISH panel · Plasmacell myeloma · IgH gene rearrangements · Monoclonal gammopathy of undetermined significance · plasma cell leukemia · Monosomy 13/del(13q), t(11;14)(q13;q32), t(4;14)(p16.3;q32), t(14;16)(q32;q23) · FGFR3/IgH · MAF/IgH · C-MYC gene · IgH/CCND1 · CCND1 gene · Plasma cell myeloma FISH panel · Non-Hodgkin lymphoma · API2MALT1 · MALT lymphoma · Burkitt lymphoma · t(8;14)(q24;q32) · Mantle cell lymphoma v t(11;14)(q13;q32) · Diffuse large B-cell lymphoma · Complex karyotype · Follicular lymphoma · t(14;18)(q32;q21) · BCL2 gene · IgH gene · BCL6 gene · t(2;8)(p12;q24), t(8;22)(q24;q11) · Splenic marginal zone lymphoma · Extranodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue · Anaplastic large-cell lymphoma · t(2;5)(p23;q35) · Anaplastic lymphoma kinase (ALK) gene

Cytogenetic Analysis in the Diagnosis of Hematolymphoid Disorders Non-random chromosomal abnormalities are a common feature of many hematolymphoid disorders and are a key component of their pathogenesis. As such,

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routine chromosome analysis is critical in the laboratory workup of most known or suspected myelodysplastic/myeloproliferative disorders, leukemias, and lymphomas. Such studies can provide (1) diagnostic confirmation; (2) information useful for classification, staging, and prognostication; (3) information to guide appropriate choice of therapy; and (4) evidence of remission or relapse. In lymph node evaluation, cytogenetics can differentiate a reactive process from a malignant condition. With the continued evolution of genetic laboratory methodologies, highly sensitive techniques have become commonplace in the laboratory workup of hematolymphoid disorders, including fluorescence in situ hybridization (FISH) and polymerase chain reaction (PCR). These technologies do not, however, provide the genome-wide coverage afforded by classical cytogenetics. Array comparative genomic hybridization (array CGH) promises the opportunity to study these malignancies in a genome-wide fashion and at a level of resolution not previously achievable by conventional cytogenetics. Using cytogenetic and molecular data, along with morphology and immunophenotype, hematolymphoid neoplasms can now be classified into clinically relevant categories that greatly improve tumor classification. While earlier disease classification schemes included primarily clinical features, morphology, and immunophenotype, the recent advances in cytogenetic and molecular genetic analysis have greatly refined this process. Earlier attempts to classify myeloid and lymphoid neoplasms into meaningful subgroups resulted in the French–American–British (FAB) scheme proposed in 1976, which was based primarily on tissue morphology. Later revisions of the FAB system took into account immunocytochemical reactions of neoplastic cells; however, bone marrow morphology continued to be the backbone of classification. The “Revised European–American Classification of Lymphoid Neoplasms” (REAL) in 1994 extended the basis for classifying lymphoid neoplasms to include morphologic, immunologic, and genetic features; clinical presentations and disease course; and postulated normal cellular counterpart [1]. In 1997, the World Health Organization (WHO) released its first edition of a classification scheme developed jointly by pathologists, hematologists, and oncologists for hematologic malignancies [2]. This classification recognized specific disease entities based on a combination of morphologic and cytogenetic features. More recent editions of the WHO Classification of Tumors of Hematopoietic and Lymphoid Tissues have included information about immunophenotype and molecular abnormalities. The latest edition (4th edition) published in 2008 [3] categorizes hematolymphoid neoplasms based on clinical and biological features, morphology, immunophenotype, cytogenetic abnormalities, and molecular genetic mutations. While certain conditions have specific immunophenotypic, cytogenetic, and/or molecular features, some myeloid and many lymphoid disorders demonstrate chromosomal abnormalities that may be observed in a number of entities. Nevertheless, these “non-specific” abnormalities can still provide important prognostic information that may guide choice of treatment. In addition, the classification of hematolymphoid neoplasms based on the multiple criteria described above has led to elucidation of involved genes and pathways, which has been critical for the development of “molecularly targeted” therapeutics.

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Classical Cytogenetic Analysis of Bone Marrow and Leukemic Blood Historical Perspectives Despite the original description of chromosomes by Professor Walther Flemming in 1876 [4], it would be some 80 years later before the correct number of human chromosomes in a cell (46) was elucidated by Tjio and Levan [5]. Since then, the field of cytogenetics has witnessed several eras that have ushered in new and exciting discoveries that have dramatically improved the diagnostic capabilities of cytogenetics laboratories and made it an important specialty of medical genetics. The first cytogenetic abnormality associated with a specific type of malignancy was described by Nowell and Hungerford in 1960 [6]. The marker chromosome, named the Philadelphia chromosome for the city where it was identified, was associated with chronic myelogenous leukemia (CML). Utilizing better banding techniques, Janet Rowley at the University of Chicago later identified this marker as a derivative chromosome 22 originating from a reciprocal translocation between chromosomes 9 and 22 [t(9;22)(q34;q11.2)] [7]. Burkitt lymphoma was the first lymphoid neoplasm in which a characteristic chromosomal abnormality [t(8;14)(q24;q32)] was identified [8]. The “banding era” of the late 1960s and 1970s resulted in improved visualization of the human chromosome complement through the formation of unique banding patterns for each chromosome. The development of quinacrine banding, Giemsa banding, C-banding using barium hydroxide and reverse banding using acridine orange permitted delineation of individual chromosomes which improved the capability of cytogenetics laboratories to more accurately define numerical and structural chromosomal abnormalities. The introduction of in situ hybridization methodologies in cytogenetics utilized DNA probes labeled with biotin and detected by sequential hybridizations with streptavidin–horseradish peroxidase and diaminobenzidine followed by visualization using standard bright-field microscopy. A slight modification of this enzymatic ISH procedure, known as chromogenic in situ hybridization (CISH), utilized fluorescently labeled DNA probes. This technique, known as fluorescence in situ hybridization (FISH), initially used single-fluorophore DNA probes and applied them to standard chromosome preparations for chromosome enumeration. As more single-copy FISH probes became commercially available, the diagnostic utility of FISH in the clinical cytogenetics laboratory increased. This technique became even more powerful as multicolor FISH probes became commonplace, permitting the identification of characteristic hematolymphoid chromosomal rearrangements such as the BCR/ABL fusion gene associated with the t(9;22)(q34;q11.2) in CML and the PML/RARA fusion gene associated with the t(15;17)(q22;q12) in acute promyelocytic leukemia. Additionally, because FISH did not require dividing cells, chromosomal abnormalities could be identified in non-dividing cells, including those in paraffin sections where tissue architecture is retained. As time went

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on, more sophisticated molecular cytogenetic techniques were developed. These included comparative genomic hybridization (CGH) [9], spectral karyotyping [10], and Fiber FISH [11]. While these techniques extended the diagnostic capabilities of FISH, their technical complexity precluded their routine implementation in many cytogenetics laboratories. With the approach of the 21st century, clinical cytogenetics found itself at yet another crossroads, defined by a powerful new diagnostic assay that truly blurs the line of demarcation between molecular genetic and cytogenetic analysis. Chromosome microarray analysis, or microarray CGH, is akin to a multiplex FISH experiment utilizing thousands of individual DNA probes arrayed to a glass slide. The “microarray era” has witnessed a substantial improvement in the diagnostic capability for identifying small (less than 5 Mb) unbalanced constitutional chromosomal rearrangements and has found great utility in the workup of children with developmental delay, mental retardation, autism/autism spectrum disorder, and multiple congenital anomalies [12, 13]. Recent literature has also demonstrated that this technology (using SNP arrays) will have a significant impact on the cytogenetic workup of hematolymphoid disorders, permitting detection of molecular mechanisms of tumorigenesis such as copy-number neutral loss of heterozygosity that cannot be identified using other cytogenetic methodologies [14, 15].

Specimen Collection and Storage Bone marrow is the tissue of choice for chromosome analysis in most hematological disorders including myeloproliferative neoplasms, myelodysplastic syndrome, chronic lymphocytic leukemia, and acute leukemias. Collection of 1–2 ml of bone marrow aspirate is adequate in most cases; however, a smaller sample may be acceptable if the marrow is hypercellular. If a bone marrow aspirate cannot be obtained, a bone core biopsy can be processed; however, the success rate for obtaining cytogenetic data on such a specimen is lower than that for a marrow aspirate. In patients with a white blood cell count greater than 10,000 billion/l and at least 10% circulating blast cells, a peripheral blood specimen cultured without phytohemagglutinin (PHA) can be studied. PHA will stimulate division of nonmalignant cells which can potentially interfere with the analysis of spontaneously dividing neoplastic cells. For lymphoma, sampling an involved lymph node is the method of choice. Cytogenetic analysis of bone marrow in lymphoid malignancies will yield positive results only if the bone marrow is involved as well; however, lymphoid-associated chromosomal abnormalities can sometimes be identified in bone marrow specimens without any overt morphological evidence of lymphoma involvement. Immediate heparinization of a newly obtained bone marrow aspirate is critical, as clotting can make it difficult to process the specimen and may, in extreme cases, render the sample useless for cytogenetic study. Processing a clotted bone marrow specimen involves mechanical disaggregation of the clot and overnight treatment with 0.1 ml of heparin (stock solution 1,000 U/ml). In our experience, this procedure has proved successful in obtaining enough cells for tissue culture in most cases, with

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more limited success in older bone marrow specimens. The newly obtained bone marrow aspirate should be transported in a sterile container containing preservativefree sodium heparin, tissue culture medium such as RPMI 1640 supplemented with heparin, or Hank’s balanced salt solution (HBSS) containing heparin. A small sample of lymph node should be placed in sterile tissue culture medium or HBSS and transported to the cytogenetics lab as soon as possible. Every attempt should be made to transport the specimen to the lab without delay so that cultures can be initiated. If any delay in transport is expected, the specimens should be placed in sterile tissue culture medium to maintain cell viability. Samples can be stored at 4◦ C overnight and for no longer than 3 days. An important concern is the overgrowth of normal cells in specimens that have been subjected to delay prior to culture initiation. Thus, with longer delays comes an increased chance of a false-negative result. Specimens with high white blood cell counts and acute lymphoblastic leukemia specimens are particularly vulnerable and should be processed without delay.

Specimen Processing and Tissue Culture Successful tissue culture of bone marrow specimens requires an optimal cell density, which for a bone marrow culture is approximately 106 cells. Extremely low and extremely high cell densities can compromise tissue culture outcomes. To determine the proper dilution of the original bone marrow suspension to ensure optimal cell density, two common methods are utilized. A hemocytometer can be used to perform a cell count on the original specimen, with the results used to determine the proper dilution of the original sample to 106 cells/ml per culture. The second method is cruder and utilizes the patient’s white blood cell count to determine the number of drops of bone marrow suspension to add to 10 ml of tissue culture medium. An experienced cancer cytogenetics laboratory will more often than not identify one or more chromosomal abnormalities, either by conventional analysis or FISH, in a bone marrow specimen with abnormal morphology. One exception to this rule are the chronic myeloproliferative neoplasms such as polycythemia vera, which are often characterized by molecular genetic changes such as the JAK2 V617F mutation. Success in obtaining positive cytogenetic results is highly dependent on choosing the appropriate culture conditions for the bone marrow, leukemic blood, and lymph node specimen. Providing clinical information and a suspected diagnosis (if possible) can aid greatly in determining the type and number of cultures to be established. Table 2.1 provides an overview of various culture regimens. While a short-term culture of 24–48 h is initiated in most studies along with additional cultures as described above (given an adequate specimen volume), a direct method is also used in some laboratories. In this method, cells are treated with Colcemid for 1 h followed by incubation in a warm hypotonic solution (0.075 M KCl) for 15 min and fixation with 3:1 methanol:glacial acetic acid. The direct method often yields suitable metaphase cells for analysis and can provide a result within 24 h; however, short-term (24 h) cultures have two major advantages over direct preparations. First, the metaphase quality obtained with the direct preparation is not as good as that obtained in a short-term culture. Second, in some cases, clonal

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Table 2.1 Culture conditions used for hematolymphoid disorders Clinical findings/suspected diagnosis

Types of cultures to be initiated

Myelodysplastic syndrome and myeloproliferative neoplasms Acute myeloid leukemia Anemia Bicytopenia Chronic myelogenous leukemiaa Eosinophilia Pancytopenia Thrombocytosis Leukopenia or neutropenia

ST + CM

B-cell lymphocytic leukemia B-cell lymphoma Chronic lymphocytic leukemiab Hairy cell leukemia Lymphadenopathy Lymphocytosis Lymphoma Lymphoproliferative disorders Mantle cell lymphoma Monoclonal gammopathy Non-Hodgkin lymphoma Plasmacytoma Plasma cell leukemia Plasma cell myeloma T-cell leukemia/lymphoma

ST + CM

ST + CM (adult) ST + GCT (child) ST + GCT + LPS + PWM (if adequate specimen volume)

ST + GCT + PHA

ST – short-term culture (unstimulated 24-h culture) CM – conditioned medium (48–72-h culture). Preparation: 1 ml supernatant from HTB-9 ladder carcinoma cell line culture (obtained from ATCC) added to 9 ml complete medium GCT – giant cell tumor culture supplement (48–72-h culture). Preparation: 1 ml supernatant from TIB-223 human lung histiocytoma cell line culture (obtained from ATCC) added to 9 ml complete medium. LPS – lipopolysaccharide (3–4-day culture) PHA – phytohemagglutinin PWM – pokeweed mitogen (3–4-day culture) a For peripheral blood, if WBC <50.0, set up buffy coat; if WBC>50.0, set up whole blood b If peripheral blood, LPS + PWM only; if post bone marrow transplant, ST + GCT

rearrangements are detectable only in cultured preparations, such as the diagnostic t(15;17) in acute promyelocytic leukemia. If the specimen is extremely limited in quantity, it may be necessary to initiate only one culture, which is usually a short-term unstimulated culture. The protocol for studying peripheral blood is similar; however, transport medium should not be added to the blood sample. Transport in a sodium heparin vacutainer (alternatively lithium heparin) is necessary. The culture conditions described above would also be appropriate for peripheral blood samples. Mitogens are added to stimulate the growth of B or T cells as clinically indicated (Table 2.1).

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Culture Harvesting, Slide Preparation, and Staining Specimen harvesting involves incubating the culture in a mitotic spindle inhibitor, such as Colcemid (0.05 μg/ml) to collect metaphases, then adding a hypotonic solution (0.075 M KCl), and incubating at 37◦ C for 10–15 min. This is followed by several fixation steps using chilled 3:1 methanol:glacial acetic acid. With each successive fixation, the cell pellet is being “cleaned up,” ensuring an optimal cell suspension with little or no background when slides are prepared. After 4–5 fixation steps, the cells are resuspended in fixative and can be stored at –20◦ C. Preparing slides is as much an art as it is a science, and each lab will have slight variations on their technique. The overall goal is to prepare slides with wellspread chromosomes that can be recognized as individual “metaphase spreads.” Precleaning microscope slides with 95% ethanol can facilitate uniformity of chromosome spreading and enhance the quality of metaphase preparations. Optimal humidity (45–55% ) and ambient temperature (70–75◦ F) are also important, necessitating in some cases the use of an environmentally controlled chamber for slide preparation. In the metaphase stage of the cell cycle, chromosomes are condensed such that individual chromosome morphology can be recognized. Chromosome morphology is characterized by size, centromere position, and banding pattern. The bands observed in metaphase chromosomes are prepared by processing slides using various different methodologies and staining solutions, including quinacrine mustard and fluorescence microscopy (Q banding), Giemsa or an equivalent stain (G banding), hot alkali followed by staining with Giemsa or acridine orange (R banding), chromosome denaturation prior to Giemsa staining (C banding) to visualize heterochromatic DNA, and staining with silver nitrate (AgNOR banding) to visualize nucleolar organizing regions in the short arm of acrocentric chromosomes.

Guidelines for Microscopic Analysis of Bone Marrow and Leukemic Blood In most cases, normal and neoplastic cells will coexist in the specimen. The goal, therefore, is to identify those neoplastic cells that potentially carry one or more chromosomal abnormalities. Care should be exercised when making any clinical predictions based on the proportion of normal to abnormal cells in a given specimen, as this can be influenced by cell culture conditions as well as sampling error. The microscopists performing the cytogenetic examination must be aware that in some conditions, particularly ALL, it is those metaphases with poorer morphology that may be representative of the neoplastic clone. Care should, therefore, always be taken to examine a variety of metaphase cells of differing quality. In addition, a case which is found to be cytogenetically normal may still harbor significant molecular abnormalities. Approximately 40–50% of AML cases demonstrate a normal karyotype but possess one or more acquired mutational changes [14] or have

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submicroscopic abnormalities detectable by higher resolution techniques such as array comparative genomic hybridization [16]. The typical oncology chromosome study requires the examination of 20 metaphase cells. A clonal abnormality as defined in ISCN 2009 [17] consists of two or more cells with the same chromosome gain or structural rearrangement, or three cells with the same chromosome loss. If a single-cell abnormality is identified, the process cannot be defined as clonal; however, if it is a characteristic abnormality associated with a specific hematolymphoid disorder or is observed in a patient that demonstrated it as part of an abnormal clone in a previous study, an extended workup is indicated. Sometimes, an apparently balanced rearrangement not known to be associated with any hematolymphoid disorder will be observed. This observation necessitates the examination of a PHA-stimulated peripheral blood culture to determine if the abnormality is constitutional in nature.

The Karyotype and Cytogenetic Nomenclature The karyotype is a pictorial representation of the 46 chromosomes present in each cell (Fig. 2.1). They are classified by their size and centromere position into seven groups. Within each of these groups, individual chromosome homologues are paired with each other based on their similar banding pattern generated by G, Q, or R banding.

Fig. 2.1 A normal G-banded bone marrow karyotype

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The development and refinement of a specific and descriptive way to describe karyotype abnormalities has been integral in the growth of cytogenetics over the last 30 years. The original attempt to achieve standardization of chromosome nomenclature was the document A Proposed Standard System of Nomenclature of Human Mitotic Chromosomes presented at the Denver Conference in 1960, while the newest revision of An International System of Human Cytogenetic Nomenclature (2009) has just been published [17]. Each revision in between has addressed the enhanced methodologies for studying chromosomes that were developed since the previous release. Techniques such as high-resolution banding, FISH, and most recently array CGH have resulted in a refinement of chromosome morphology, necessitating an expansion of chromosome nomenclature in each revision. The reader is referred to ISCN 2009 [17] for an in depth description of human chromosome nomenclature. Only a few basic features will be presented here. Chromosomal abnormalities are of two types, numerical and structural. The normal modal chromosome number is 46, designated as a diploid cell. If more or less than 46 chromosomes are present, the cell is referred to as being aneuploid. If more than 46 chromosomes are present, the cell is hyperdiploid; if less than 45 chromosomes, the cell is hypodiploid. Gain of a chromosome is referred to as trisomy, while loss of a chromosome is referred to as monosomy. These are described in the karyotype designation by a “+” or “–,” respectively. Structural abnormalities are designated by the type of abnormality present and the breakpoints involved. The breakpoints will lie either within a chromosome band or at the junction between two chromosome bands. A chromosome band is a portion of a chromosome clearly distinguishable from adjacent segments which may be lighter or darker depending on the banding technique. There are specific “landmark” bands that help to distinguish one chromosome from another. Each band is, at successively higher levels of resolution, further divided into subbands. The bands and subbands are numbered outward from the centromere. Descriptions of structural rearrangements commonly observed in neoplastic disorders are provided in Table 2.2. Table 2.3 lists several examples of common chromosomal abnormalities and their description using ISCN 2009 nomenclature.

The Molecular Mechanisms Responsible for Chromosomal Rearrangements in Neoplasia Many cancers are associated with specific chromosomal abnormalities that disrupt normal cellular processes leading to malignant transformation. Much work has focused on the molecular mechanisms that lead to the visible chromosomal rearrangements observed in a variety of human constitutional chromosome disorders [18]. The mechanisms that underlie those pathogenetic rearrangements observed in various hematolymphoid disorders may not be dissimilar. A chromosome translocation appears to be initiated by a DNA double-strand break

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Table 2.2 Overview of structural chromosomal rearrangements observed in neoplasia Type of structural chromosomal abnormality Translocation

Derivative

Inversion

Deletion

Isochromosome Isodicentric chromosome Ring Marker Double minutes Homogenously staining region Add

Morphological change observed Exchange of two chromosomal segments distal to the designated breakpoints in two chromosomes; can be balanced or unbalanced A structurally rearranged chromosome generated from events involving two or more chromosomes or multiple events within a single chromosome 180◦ inversion of chromosome segment between two designated breakpoints Pericentric – breakpoints are in p and q arms Paracentric – both breakpoints in same arm Loss of chromosome segment Terminal – Loss of segment distal to single breakpoint Interstitial – Loss of segment between two breakpoints Chromosome arms are identical with a single centromere A mirror-image chromosome with two centromeres Chromosome with one breakpoint in each arm followed by reunion of two ends Chromosome that appears to be mitotically stable but cannot be classified by conventional banding studies Acentric chromosome fragments often in multiple copies Chromosome region that stains uniformly (Both are cytogenetic manifestations of gene amplification) Chromosome with “additional” material of unknown origin attached to the long or short arm

Table 2.3 Common hematolymphoid chromosomal abnormalities and their description using ISCN nomenclature t(9;22)(q34;q11.2) t – denotes translocation (9;22) – translocation between chromosomes 9 and 22 (q34;q11.2) – breakpoints are in the long arm of both chromosomes at bands 9q34 and 22q11.2 der(22)t(9;22)(q34;q11.2) der(22) – denotes derivative chromosome 22 originating from the t(9;22)(q34;q11.2) inv(16)(p13q22) inv – denotes inversion (16) – inversion involves chromosome 16 (p13q22) – the inverted segment lies between the breakpoints 16p13 (in the p arm) and 16q22 (in the q arm); the segment between the two breakpoints rotates 180◦ del(5)(q13q33) del – denotes deletion (5) – deletion involves chromosome 5 (q13q33) – deleted segment is interstitial between bands 5q13 and 5q33 in the long arm i(17)(q10) i – denotes isochromosome (17) – isochromosome involves chromosome 17 (q10) – chromosome arms are composed of two identical complete chromosome 17 long arms

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followed by “misrepair.” Proposed mechanisms that result in recurrent, balanced translocations in hematolymphoid disorders include the following: (1) illegitimate V(D)J or switch recombination, (2) presence of repetitive sequences such as ALU sequences or LINE elements at “broken” ends, and (3) error-prone non-homologous end joining [19]. The joining of the two “broken” ends appears to be facilitated by the presence of specific DNA sequences at these breaks, including ALU sequences, translin-binding consensus sequences, and scaffold-associated regions [20]. In addition, the formation of recurrent translocations also requires a clustering within the nucleus of the two involved chromosomes. This has been demonstrated for the BCR and ABL1 genes associated with chronic myelogenous leukemia and the BCL6 and MYC genes that rearrange with IGH in B-cell disorders [19]. The mechanism(s) that facilitate this clustering within the nucleus are not known. Finally, the identification of recurrent hematolymphoid translocations including the t(9;22)(q34;q11.2), t(15;17)(q22;q12), and t(14;18)(q32;q21) rearrangements by the polymerase chain reaction (PCR) in apparently healthy individuals raises the possibility that the mechanisms required for malignant transformation may be far more involved than what is currently appreciated [21].

Molecular Cytogenetic (FISH) Analysis of Bone Marrow and Leukemic Blood Basic Principles of Fluorescence In Situ Hybridization Conventional cytogenetic analysis of bone marrow or leukemic blood cultures permits a genome-wide assessment of chromosomal abnormalities; however, it is sometimes hampered by low mitotic index, poor chromosome morphology, considerable karyotypic complexity, and normal karyotypes. Fluorescence in situ hybridization (FISH) can overcome these problems by targeting specific nucleic acid sequences in a highly sensitive and rapid manner. The powerful diagnostic capabilities of FISH are rooted in its relative ease of use in the clinical laboratory, enhanced sensitivity over conventional banding studies, and ability to probe for one or more specific genomic regions of interest in either dividing or non-dividing cells, as well as in in situ tissue preparations permitting identification of cytogenetic changes in a specific cell lineage. By utilizing fluorescently labeled DNA probes to detect genetic aberrations that are generally beyond the resolution of conventional chromosome banding studies, FISH in a sense merges conventional cytogenetic analysis with molecular genetics. FISH is based on the principle that a single-stranded DNA molecule will recognize and bind to its complementary sequence on a metaphase chromosome or in an interphase nucleus. The overall hybridization is similar to in situ hybridization using radioisotope-labeled probes. The major advantage of FISH, however, is the utilization of a DNA probe labeled with a fluorescent dye, which results in a

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highly sensitive, simple, and rapid assay. Both the probe and the target DNA are treated with heated formamide solution to denature double-stranded DNA, followed by probe application to target DNA and incubation at 37◦ C. During the incubation process, annealing of the probe to the target sequence occurs through complementary base pairing. A fluorescence microscope equipped with appropriate filters is then used to detect the hybridized probe on the target material, appearing as brightcolored signals. Multiple probes labeled with different colored fluorescent tags can be applied simultaneously on the same target to detect one or more specific regions of the genome. FISH analysis can be performed on either metaphase chromosomes derived from cultured cells or non-dividing cells, allowing identification of chromosomal aberrations irrespective of cell cycle stage. This latter technique, known as interphase FISH, is a powerful cytogenetic tool that can be applied to a wide variety of clinical specimens to enumerate chromosomes and identify chromosomal rearrangements. When viable specimens are not available, interphase FISH can be performed on a bone marrow or a blood smear, disaggregated cells from a paraffin block, touch preparation from a lymph node, or cytospin cells fixed on a microscope slide. FISH can also be performed on a paraffin-embedded tissue section. While this technique has the advantage of maintaining tissue architecture, its inherent disadvantages include nuclear truncation artifact and overlapping cells that may make analysis difficult.

Clinical Indications for FISH Testing in Hematolymphoid Disorders Common indications for FISH testing in hematolymphoid malignancies include the following: (1) confirmation of chromosomal abnormalities detected by conventional cytogenetics and establishment of FISH signal pattern for follow-up study, (2) detection of chromosomal abnormalities when clinical and morphologic findings are suggestive of a specific chromosomal abnormality [e.g., t(11;14) in mantle cell lymphoma], (3) characterization of genetic aberrations using a panel of disease-specific FISH probes for risk stratification and therapeutic management, such as in acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), and plasma cell myeloma (PCM), (4) detection of cryptic or masked translocations when chromosome analysis is inconclusive or yields a normal karyotype [such as the t(12;21) in ALL or t(4;14) in myeloma], (5) detection of lymphoma-associated translocations in paraffin-embedded tissue sections, (6) quantitation of minimal residual disease and detection of cytogenetic remission and relapse through analysis of a large number of both dividing and non-dividing cells, (7) monitoring cross-sex bone marrow transplantation patients for engraftment status (chimerism), and (8) rapid detection of PML/RARA gene fusion in acute promyelocytic leukemia, where quick diagnosis is required for prompt treatment.

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Types of FISH Probes Routinely Used in Hematological Disorders There are primarily three types of probes used in clinical FISH testing: centromere enumeration probes (CEPs), locus-specific identifier (LSI) probes, and whole-chromosome paint (WCP) probes (Fig. 2.2). The CEPs recognize a highly repetitive alpha-satellite DNA sequence located at the centromere of each chromosome. These probes are labeled in one color and give a large, bright signal, useful for chromosome enumeration in both interphase and metaphase cells. The LSI probes hybridize to single-copy DNA sequences in a specific chromosomal region or gene. These probes can identify fusion gene products generated from a reciprocal translocation, chromosome inversions, and gene deletion or amplification. On metaphase cells, the LSI probes give two small, discrete signals per chromosome. The gain of LSI signals within a nucleus is consistent with duplications or amplifications, while the loss of LSI signal indicates a deletion. The design of LSI probes targeting specific translocations has evolved considerably, minimizing the false-positive and false-negative rates. Dual-color, dual-fusion (DCDF) LSI probes are designed to span both sides of the breakpoints in two different chromosome regions/genes involved in a reciprocal translocation, resulting

Fig. 2.2 Examples of FISH probe designs commonly used in hematolymphoid disorders and their resulting hybridization patterns (reproduced with permission from [58])

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in remarkably improved specificity. To assess the rearrangement of a gene that may be associated with multiple translocation partners, a dual-color break-apart (DCBA) LSI probe has been designed. The DCBA probe is a combination of two differently labeled probes that bind to sequences that flank the 5 - and 3 -ends of the breakpoint within the involved chromosome region. The separation of the two colors is indicative of rearrangement. WCP probes are cocktails of unique sequence DNA probes derived from flow-sorted chromosomes, chromosome-specific libraries, or chromosome-microdissected regions that recognize specific sequences spanning the length of a chromosome. In normal metaphase preparations, this gives the effect that both chromosome homologues are “painted.” WCP probes are useful to identify marker chromosomes and to detect cryptic translocations; however, their utility in interphase nuclei is limited. An overview of commercially available FISH probes useful to characterize hematolymphoid disorders is provided in Table 2.4. Table 2.4 Commercially available FISH probes used to characterize hematolymphoid disorders Disease

Chromosomal abnormality

CML

t(9;22)(q34;q11.2)

AML

AML-M3 (APL) MDS

MPN

B-ALL

Gene(s) involved

ABL, BCR ASS t(8;21)(q22;q22) RUNX1T1 (ETO), RUNX1 (AML1) inv(16)(p13q22)/t(16;16) MYH11, CBFβ

t(v;11)(v;q23), del 11q23 Monosomy 5/del 5q33-34 Monosomy 5/del 5q31 Monosomy 7/del 7q del 20q Trisomy 8 t(15;17)(q22;q12) t(v;17)(v;q12) Monosomy 5/del 5q33-34 Monosomy 5/del 5q31 Monosomy 7/del 7q del 20q Trisomy 8 del(11)(q23) del(13)(q14) Trisomy 8 Trisomy 9 del(4)(q12q12) del 20q Trisomy 4, 10, 17 t(12;21)(p13;q22) t(v;11)(v;q23) t (9;22)(q34;q11.2)

MLL CSF1R EGR1

PML, RARA CSF1R EGR1

MLL RB1

CHIC2 PDGFRA/FIP1L1

ETV6 (TEL), RUNX1 (AML1) MLL ABL, BCR

FISH probe(s) BCR/ABL fusion BCR/ABL fusion + 9q34 RUNX1T1/RUNX1 fusion CBFβ or MYH11 break apart MYH11/CBFβ fusion MLL break apart CSF1R/5p EGR1/5p D7S522/CEP7 D20S108 CEP8 PML/RARA fusion, RARA break apart CSF1R/5p EGR1/5p D7S522/CEP7 D20S108 CEP 8 MLL break apart RB1/13q14 D13S319/13q14 CEP 8 CEP 9 CHIC2/ 4qter PDGFRA/FIP1L1 fusion D20S108 CEP 4, 10, 17 TEL/AML1 ES fusion MLL break apart BCR/ABL fusion

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Disease T-ALL

CLL

PCM

NHL MCL FL BL

DLBCL

MALT ALCL

Chromosomal abnormality

Gene(s) involved

t(1;19), t(17;19) t(5;14)(q35;q32) del(9)(p21) 7q35 rearrangement 7p14-15 rearrangement 14q11.2 rearrangement

TLX3 (HOX11L2) p16 TCRbeta TCRgamma TCRalpha/delta

del(11)(q22.3) Trisomy 12 del (13)(q14.3) del(17)(p13) del(6)(q23) Monosomy 13/del(13)(q14) Trisomy 5,9,15,19 del(17)(p13) t(11;14)(q13;q32) t(4;14)(p16.3;q32) t(14;16)(q32;q23) t(V;8)(V;q24) t(V;14)(V;q32) t(11;14)(q13;q32) t(14;18)(q32;q21) t(8;14)(q24;q32) t(2;8)(p12;q24) t(8;22)(q24;q11.1) t(3;14)(q27;q32), t(2;3)(p12;q27), t(3;22)(q27;q11.2) t(11;18)(q21;q21), t(14;18)(q32;q21) t(2;5)(p23;q35), t(V;5)(V;q35)

ATM Micro-RNA genes (miR-16-1,miR-15a) TP53 MYB

TP53 CCND1, IGH FGFR3, IGH IGH, MAF MYC IGH CCND1, IGH IGH, BCL2 MYC, IGH MYC, IGK MYC, IGL BCL6, IGH IGK, BCL6 BCL6, IGL API2, MALT IGH, MALT ALK, NPM

FISH probe(s) E2A TC3F/PBX1 fusion TLX3 break apart p16/D9Z3 TCRbeta break apart TCRgamma break apart TCRalpha/delta break apart ATM CEP 12 D13S319/13q14 RB1/13q14 TP53 MYB D13S319/LAMP1 RB1/LAMP1 CEP 5, 9, 15, 19 TP53 CCND1/IGH fusion FGFR3/IGH fusion MAF/IGH fusion MYC break apart IGH break apart CCND1/IGH fusion BCL2/IGH fusion IGH/MYC,CEP8 MYC break apart BCL6 break apart

API2/MALT1 fusion MALT1 break apart ALK break apart

CML, Chronic myelogenous leukemia; AML, acute myelogenous leukemia; APL, acute promyelocytic leukemia; MDS, myelodysplastic syndrome; MPD, myeloproliferative disorder; ALL, acute lymphoid leukemia (B or T cell); CLL, chronic lymphocytic leukemia; PCM, plasma cell myeloma; NHL, non-Hodgkin lymphoma; MCL, mantle cell lymphoma; FL, follicular lymphoma; BL, Burkitt lymphoma; DLCL, diffuse large-cell lymphoma; MALT, extranodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue; ALCL, anaplastic large-cell lymphoma; BMT, bone marrow transplantation

Advantages and Disadvantages of FISH FISH analysis has both advantages and disadvantages over conventional cytogenetic analysis. FISH can (1) be performed on metaphase cells or interphase nuclei

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(non-dividing cells) and on fresh or fixed tissue samples, (2) target genetic aberrations that pinpoint candidate genes involved in leukemogenesis, (3) simultaneously assess chromosomal aberrations, cellular phenotype, and tissue morphology utilizing paraffin-embedded tissue sections (paraffin FISH), (4) provide in a rapid fashion highly specific, sensitive, and reproducible results that are interpreted objectively, (5) simultaneously assess multiple genomic targets, (6) provide superior resolution (interphase FISH > 20 kb, metaphase FISH > 100 kb) compared with standard karyotyping (>10 Mb), and (7) detect specific cryptic chromosomal abnormalities. Limitations of FISH include the following: (1) its inability to provide a genomewide assessment of chromosomes; (2) the necessity for clinical information or a differential diagnosis to guide the appropriate choice of probes to be used, and (3) the requirement for a high-quality fluorescence microscope with multiple filters, a CCD camera that can detect low-level light emission, and sophisticated imaging software.

Diagnostic and Prognostic Cytogenetic Markers in Myeloid Disorders Myeloproliferative Neoplasms (MPN) Most MPNs are not characterized by a unique cytogenetic abnormality but instead demonstrate molecular mutations in genes that code for cytoplasmic or receptor protein tyrosine kinases. As such, these mutations such as the JAK2 V617F and FIP1L1–PDGFRA fusion gene do not affect differentiation but instead convey a proliferative advantage [22]. Those cytogenetic abnormalities that are identified are found in a variety of myeloid neoplasms, precluding their use as a marker to subclassify the disease process. Despite the relatively low frequency of karyotypic abnormalities at diagnosis in these disorders, cytogenetic analysis is still important. It can distinguish a clonal process from a reactive myeloproliferation, it can exclude chronic myelogenous leukemia characterized by the Philadelphia (Ph) chromosome, and it can be used throughout the course of the disease to identify cytogenetic progression associated with disease progression and an increased risk of leukemic transformation. In addition, identification of a complex karyotype in the diagnostic bone marrow is associated with a poorer prognosis. Chronic myelogenous leukemia, BCR/ABL1 positive. CML was the first hematological disorder to be associated with a specific chromosomal abnormality, the t(9;22)(q34;q11.2) which generates the Philadelphia chromosome (truncated chromosome 22) (Fig. 2.3). The molecular consequence of this translocation is fusion of the 3 segment of the Abelson (ABL1) proto-oncogene on chromosome 9q34 to the 5 segment of the BCR gene on chromosome 22q11.2, producing a chimeric 210-kDa BCR/ABL fusion gene product that has constitutive tyrosine kinase activity. At diagnosis, over 90% of CML patients will demonstrate the t(9;22)(q34;q11.2) by conventional cytogenetic

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Fig. 2.3 An abnormal female karyotype demonstrating the t(9;22)(q34;q11.2) which generates the Philadelphia chromosome [der(22) chromosome]

analysis. The remaining cases present either a submicroscopic rearrangement or a variant t(v;9;22) translocation. In these cases, FISH analysis can readily detect the BCR/ABL1 fusion, and failure to do so would suggest that another MPN, such as chronic neutrophilic leukemia, should be considered. The dual-color, dual-fusion FISH (D-FISH) assay utilizing the BCR/ABL1 probe (Fig. 2.4a) not only will detect translocations occurring at the typical major breakpoint cluster region (M-BCR) that generates the p210 product but will also identify a breakpoint in the micro breakpoint cluster region (μ-BCR) which produces a larger fusion protein (p230) rarely observed in CML, as well as a breakpoint in the minor breakpoint cluster region (m-BCR) producing the shorter fusion product (p190) most often observed in Ph+ ALL. Deletion of DNA sequences proximal to the 9q34 breakpoint, which includes the ASS gene, has been observed in approximately 10–30% of CML patients at diagnosis. These deletions have been associated in some studies with a shortened chronic phase and decreased overall survival; however, other studies have reported no significant difference in those patients with a der(9) deletion with regard to response rate or overall survival [23]. Effective treatments for CML including imatinib mesylate (Gleevec), α-interferon, and allogeneic stem cell transplantation result in a decrease in the percentage of Ph+ neoplastic cells. BCR/ABL1 FISH can accurately quantify cytogenetic response to therapy, determine remission status, and identify relapse. With

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Fig. 2.4 Common cytogenetic abnormalities in MPNs. (a) A BCR/ABL1 fusion in CML is demonstrated utilizing the dual-color, dual-fusion FISH assay. The BCR/ABL1-positive nuclei (with two fusion signals) are at 3 and 6 o’clock. The nucleus in the bottom left corner is negative for BCR/ABL1 fusion (two red, two green signals). The metaphase cell in the center is also positive for fusion [arrows identify the der(9) and der(22) chromosomes]. Deletion of chromosomes 20q (b) and 11q (c) is a relatively common abnormality in MPNs

successful treatment, the D-FISH assay can monitor regression of the clone down to 1%. Much has been written about the use of BCR/ABL1 FISH analysis of peripheral blood specimens. This is a common practice for routinely monitoring CML patients, as it can be performed at regular intervals without the need for an invasive bone marrow aspiration, even for patients in complete cytogenetic remission. Some studies have suggested a similar performance of the BCR/ABL1 quantitative FISH assay in peripheral blood versus bone marrow for detection of minimal residual disease; however, other studies have suggested that measuring BCR/ABL1 positivity in peripheral blood may underestimate the tumor burden [23]. Nevertheless, it is generally acknowledged that FISH analysis of peripheral blood utilizing D-FISH is adequate for CML disease monitoring. Of the three diagnostic modalities (karyotyping, FISH, and RT-PCR), only conventional cytogenetics provides a genome-wide assessment that permits identification of clonal evolution including acquisition of abnormalities such as trisomy 8, isochromosome 17q, trisomy 19, and an additional copy of the der(22) chromosome. These abnormalities herald the onset of accelerated phase or blast phase CML which would necessitate modifications of the treatment plan. Thus, neither RT-PCR nor BCR/ABL1 FISH negate the importance of bone marrow cytogenetic analysis as an important management tool in CML. Polycythemia vera. The most common cytogenetic markers identified in PV in decreasing frequency are del(20q) (Fig. 2.4b), +8, +9, 9p rearrangement, gains of 1q, and del(13q). These abnormalities are observed in 15–25% of cases. Trisomy 8 may be the sole change or may be found in combination with trisomy 9. A clone with

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trisomies 8 and 9 may persist for several decades without clonal evolution or transformation to acute leukemia. As PV evolves to postpolycythemic myelofibrosis or acute leukemia, additional cytogenetic abnormalities are acquired [23]. This cytogenetic evolution is apparent when comparing follow-up bone marrow biopsies with the baseline karyotype performed on the diagnostic bone marrow specimen. The identification of unfavorable prognostic markers [any aberration other than del(13q) or del(20q)] appears to be the strongest predictor of a poor prognosis in secondary myelofibrosis [24]. Essential thrombocythemia. Less than 10% of ET cases demonstrate cytogenetic abnormalities, and none are specific for this disorder. Like other MPNs, deletions of chromosomes 5q, 13q, and 20q, along with +8, +9, and gains of 1q are commonly observed. One important prognostic cytogenetic marker in ET is the presence of abnormalities involving chromosomes 7 and 17, which appear to be associated with a higher risk of leukemic transformation. Since none of these abnormalities are specific for ET, the greatest benefit of cytogenetic testing in this disorder is to exclude the presence of the Ph chromosome as a cause of thrombocytosis [22]. Primary myelofibrosis. Chromosomal abnormalities are found in 40–50% of cases and are found in greater numbers with disease progression. The presence of either del(13)(q12–22) or der(6)t(1;6)(q21–23;p21.3) is strongly suggestive but not diagnostic for PMF. Non-random abnormalities are similar to those found in PV, including trisomy for chromosomes 8, 9, and 21 as well as del(13q) and del(20q) chromosomes. As the disease progresses, structural abnormalities become more common, including gain of 1q, chromosome 7q abnormalities, and del(17p). The chromosome 7q abnormalities along with chromosome 5q deletions may be therapy-related changes related to cytotoxic therapy used to treat the myeloproliferative process. The HMGA2 (high-mobility group protein A2) is disrupted by a recurrent breakpoint at chromosome band 12q14 in some cases [3, 22]. Chronic neutrophilic leukemia. Most patients with CNL demonstrate a normal karyotype; however, +8, +9, +21, del(11q) (Fig. 2.4c), del(12p), and del(20q) have been reported as clonal aberrations. As the disease progresses, clonal cytogenetic abnormalities may emerge [3]. Chronic eosinophilic leukemia/idiopathic hypereosinophilic syndrome. CEL/ HES belongs to the WHO subgroup of Myeloid and Lymphoid Neoplasms with PDGFRA Rearrangement. These disorders are characterized by a persistent unexplained hypereosinophilia and rearrangement of the PDGFRA gene. The most common rearrangement of PDGFRA involves formation of a hybrid fusion tyrosine kinase between the 5 -portion of the FIP1L1 gene and the 3 -portion of the PDGFRA gene through a cryptic 800-kb interstitial deletion within chromosome band 4q12 [25, 26]. This event can be identified in 40–60% of CEL patients and can be readily demonstrated by FISH utilizing a probe for the CHIC2 gene, which lies between the FIP1L1 and PDGFRA genes and is deleted when the fusion event occurs. Recently, a FISH probe which recognizes the PDGFRA/FIP1L1 fusion gene has become available. A subset of patients with CES have benefited from treatment with imatinib mesylate, which appears to target FIP1L1/PDGFRA [25].

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Myelodysplastic Syndromes (MDS) Bone marrow cytogenetic analysis is a standard practice in the evaluation of a patient with suspected MDS and is considered an independent predictor of clinical outcome, overall survival, and progression to acute leukemia. The extent and nature of cytogenetic abnormalities is one of the three parameters in the International Prognostic Scoring System (IPSS), along with degree of peripheral cytopenia and bone marrow blast cell percentage that separates patients into one of the four prognostic groups (good, intermediate-1, intermediate-2, and poor) with regard to both survival and AML evolution [27]. As the disease becomes more severe, the frequency of cytogenetic abnormalities increases. Cytogenetic analysis can also distinguish a monoclonal proliferation from a reactive process in a morphologically unremarkable bone marrow and can, through serial cytogenetic studies, identify clonal evolution which accompanies progression of disease. Conventional cytogenetic analysis can identify chromosomal abnormalities in 40–70% of de novo MDS cases and in almost 95% of t-MDS at diagnosis [28], with none specific for a particular MDS subtype except for the chromosome 5q deletion [WHO classification: MDS associated with isolated del(5q)]. Recurrent chromosome changes in MDS include loss of chromosome 5 or 7, deletions of chromosome 5q or 7q, trisomy 8, and chromosome 20q deletion. Loss of the Y chromosome is also relatively common in MDS, but this may be an age-related artifact in many patients. The identification of trisomy 8 and/or del(20q) in the absence of morphological evidence does not provide a definitive diagnosis of MDS. Close clinical and laboratory follow-up of such patients is necessary to identify emerging evidence of myelodysplasia [3]. Less frequently, structural rearrangements involving chromosomes 3q; deletion of chromosomes 11q, 13q, and 17p; and trisomies 9 and 21 are observed. Many of these chromosomal changes are also observed in AML, a finding indicative of the pathobiologic similarity between the two diseases. Complex karyotypes are often associated with advanced disease and a greater likelihood of leukemic transformation (Fig. 2.5). The primary utility of FISH analysis in MDS is based on the finding that 15–20% of MDS patients demonstrate a normal karyotype, yet possess one or more clonal abnormalities of prognostic and/or therapeutic significance when analyzed by FISH [28, 29]. These patients will often demonstrate an increase in bone marrow blasts, an increase in rate of leukemic transformation, and a poorer prognosis [29]. Based on this and other studies, most advocate the use of an MDS-FISH panel on the diagnostic specimen. The MDS-FISH panel utilized in many laboratories includes probes to detect monosomy 5/del(5q), monosomy 7/del(7q), trisomy 8, chromosome 20q deletion, chromosome 11q deletion, and chromosome 13q deletion [28].

Acute Myeloid Leukemia Acute myeloid leukemia (AML) is characterized by excessive accumulation of myeloid blasts (>20%) in bone marrow, peripheral blood, and other tissues. AML can be de novo or can occur following exposure to cytotoxic agents including

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Fig. 2.5 An abnormal cytogenetic clone presenting this complex karyotype was identified in an 83-year-old female with pancytopenia. Her history is positive for right breast infiltrating ductal carcinoma in 2002 with chemotherapy and radiation therapy. Bone marrow examination revealed refractory anemia with excess blasts, type 1. Abnormalities are identified by arrows and include the myeloid markers del(5q) and monosomy 7 which are consistent with secondary (therapy-related) myelodysplasia

chemotherapy and radiotherapy (therapy-related- or t-AML). Some 10–15% of AML cases are related to such previous cytotoxic exposure. The identification of specific cytogenetic abnormalities is diagnostic for specific AML subtypes and can be powerful predictors of prognosis and response to therapy. Overall, cytogenetic abnormalities are identified in approximately 55% of adults at diagnosis, with a range of 50–80% [28]; however, only a subset of these chromosome changes are associated with clinical, morphological, and immunophenotypic specificity for a particular AML subtype. In the current WHO classification scheme, the following AMLs are characterized by a recurrent cytogenetic abnormality associated with a specific molecular rearrangement (Fig. 2.6a–d): • AML with t(8;21)(q22;q22) – RUNX1/RUNX1T1: Identified in 5–12% cases of AML with maturation [FAB classification: AML-M2] and in 40–50% of karyotypically abnormal cases of AML with maturation. • AML (promyelocytic) with t(15;17)(q22;q12) – PML/RARα (Fig. 2.6a): Acute promyelocytic leukemia (APL) [FAB classification: AML-M3], a disease

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Fig. 2.6 (a–c) Common rearrangements identified in acute myeloid leukemia (arrows point to derivative chromosomes). (d) FISH detection of chromosome 16 inversion using a break-apart probe for CBFβ in an interphase nucleus and metaphase spread (arrow indicates break-apart signal)

primarily observed in young adults, is characterized by the presence of abnormal hypergranular promyelocytes. All AML cases with the t(15;17)(q22;q12) are diagnosed as APL; however, not all cases of APL will present the classic t(15;17)(q22;q12) due to the presence of (1) a complex karyotype involving both chromosomes 15 and 17 with additional cytogenetic changes, (2) a submicroscopic event leading to insertion of the retinoic acid receptor alpha (RARα) gene into the promyelocytic leukemia (PML) gene, or (3) a variant translocation such as t(11;17)(q23;q12) with ZBTB16/RARα fusion, t(5;17)(q35;q12) with NPM1/RARα fusion, or t(11;17)(q13;q12) with NUMA1/RARα fusion. The t(15;17) and variant translocations all have in common disruption of the RARα gene, with the typical t(15;17) giving rise to the PML/RARα gene fusion product which causes a block in differentiation at the promyelocyte stage [3]. The identification of the t(15;17) and the genes involved in this rearrangement has led to a successful treatment for APL utilizing all-trans-retinoic acid (ATRA), which acts as a differentiating agent [28]. Identification of variant translocations is important, as some APL variants such as t(11;17)(q23;q12) are resistant to this drug. • AML with t(9;11)(p22;q23) – MLLT3/MLL (Fig. 2.6b): Acute myeloid leukemia with chromosome 11q23 abnormalities generally presents with monocytic features and involves disruption of the MLL (myeloid lymphoid lineage or mixed lineage leukemia) gene. Abnormalities of 11q23 are identified in 5–6% of AML cases occurring at any age; however, it is more common in childhood AML. The two AML subgroups that demonstrate 11q23 rearrangement most often are AML in infants and therapy-related AML (following topoisomerase II therapy). The most common translocations in childhood AML include t(9;11)(p21;q23) and t(11;19)(q23;p13.1) or t(11;19)(q23;p13.3). The MLL gene is very promiscuous, as it is known to be involved in 73 recurrent translocations and partner with 54 partner genes in all acute leukemias [3, 30]. Because of this, the most effective method to detect MLL gene rearrangement is to utilize an MLL gene break-apart probe that can detect involvement of MLL regardless of which partner chromosome band/gene is involved [3].

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• AML with inv(16)(p13q22) or t(16;16)(p13;q22) – CBFβ/MYH11 (Fig. 2.6c): Acute myelomonocytic leukemia (AMML) [FAB classification: AML-M4eo] accounts for approximately 10% of all AML cases and is characterized by an increase in myeloid and monocytic cell lines with a characteristically abnormal eosinophil component in bone marrow. The genetic basis for AML-M4eo is the fusion of the core binding factor beta subunit (CBFβ) gene at chromosome 16q22 to the smooth muscle myosin heavy chain gene (MYH11) at chromosome 16p13 through either the inv(16) or the t(16;16). • AML with t(6;9)(p23;q34) – DEK/NUP214: AML with or without monocytic features that is often associated with basophilia and multilineage dysplasia. The t(6;9) is the sole abnormality in most cases, although it can sometimes be part of a complex karyotype. The concurrent identification of the FLT3-ITD mutation occurs in 69% of pediatric cases and 78% of adult cases [3]. • AML with inv(3)(q21q26.2) or t(3;3)(q21;q26.2) – RPN1/EVI1: AML with increased atypical bone marrow megakaryocytes and associated multilineage dysplasia. Patients may present de novo or have a prior MDS phase [3]. • AML (megakaryoblastic) with t(1;22)(p13;q13) – RBM15/MKL1: A rare AML (<1% of cases) that demonstrates small and large megakaryoblasts. This disease is de novo in most cases and almost exclusively seen in infants and young children [3].

Of these AMLs, the rearrangements considered to be favorable with regard to response to chemotherapy, high remission rate, and long-term survival include t(8;21)(q22;q22), inv(16)(p13q22) or t(16;16)(p13;q22), and t(15;17)(q22;q12) treated with all-trans-retinoic acid. The (9;11)(p22;q23) is associated with an intermediate prognosis, while the t(6;9)(p23;q34), inv(3)(q21q26.2), and t(3;3)(q21;q26.2) are associated with a poor prognostic outcome [3]. In addition to the cytogenetically characterized myeloid leukemias described above, several additional AML groups are recognized. Acute myeloid leukemia with myelodysplasia-related changes often present with severe pancytopenia. More often observed in the elderly, this disease is characterized by chromosomal abnormalities similar to those found in MDS. These include monosomy 5/del(5q) and monosomy 7/del(7q), often as part of a complex karyotype [3]. The latency period for development of therapy-related myeloid neoplasms varies with the type of chemotherapeutic agents used. Therapy-related AML (t-AML) associated with alkylating agent chemotherapy or radiation therapy is often preceded by MDS and can develop after a period of 2–7 years, while topoisomerase II inhibitor therapy-associated AML develops after a shorter latency period and is not associated with a preceding myelodysplastic phase [31]. Alkylating agent t-AML is characterized by deletions involving chromosomes 5 and 7, often as part of a complex karyotype (Fig. 2.7). Topoisomerase-associated t-AML is associated with disruptions of the MLL gene at 11q23, often through a balanced translocation. While in general the outcome of t-AML/t-MDS is poor, certain cytogenetic results including inv(16), t(8;21), and t(15;17) are associated with a better prognosis (comparable to de novo AML with favorable cytogenetics).

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Fig. 2.7 This complex karyotype was identified in a patient who had undergone multiple rounds of chemotherapy and radiation for persistent follicular lymphoma over many years. The concurrent bone marrow examination demonstrated marked erythroid hyperplasia and megakaryocytic hyperplasia along with erythroid and megakaryocytic dyspoiesis and ringed sideroblasts. t-MDS was favored, given her therapy history. This karyotype confirms t-MDS with abnormalities of chromosomes 5 and 7. A little over 1 month later, this patient presented with acute myeloid leukemia (t-AML), not surprising given the complexity of this karyotype

Those AMLs subtyped in the WHO classification as acute myeloid leukemia, not otherwise specified include acute myeloid leukemia with minimal differentiation, acute myeloid leukemia without maturation, acute myeloid leukemia with maturation, acute myelomonocytic leukemia, acute monoblastic and monocytic leukemia, acute erythroid leukemia, acute megakaryoblastic leukemia, acute basophilic leukemia, and acute panmyelosis with myelofibrosis. These diseases are not associated with a specific cytogenetic abnormality but instead demonstrate abnormalities that are best classified as “myeloid cytogenetic markers.” These include monosomy 5/del(5q), monosomy 7/del(7q), +8, del(11q), del(20q). Complex karyotypes are often observed as well [3].

Diagnostic and Prognostic Cytogenetic Markers in Lymphoid Disorders B-Lymphoblastic Leukemia/Lymphoma with Recurrent Genetic Abnormalities This new WHO classification defines a group of diseases characterized by recurrent numerical and structural chromosomal abnormalities. In childhood ALL, the identification of recurrent chromosomal aberrations as prognostic markers has had a major

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impact on efforts to cure this disease, as they have permitted effective stratification of patients into appropriate treatment regimens. Approximately 80% of ALL cases demonstrate clonal chromosomal abnormalities, while the remaining cases either present a normal karyotype or cannot be analyzed due to a variety of factors such as poor chromosome morphology and the apoptotic tendency of ALL blasts in culture. For this reason, FISH has become an important tool for the assessment of genetic aberrations in ALL [32]. High hyperdiploidy, defined as >50 chromosomes per karyotype, occurs in approximately 25% of ALL cases (B-lymphoblastic leukemia/lymphoma with hyperdiploidy) and constitutes a distinct subset characterized by a favorable prognosis (Fig. 2.8). The gains are non-random, with chromosomes 4, 6, 10, 14, 17, 18, 21, and X accounting for close to 80% [32]. More specifically, hyperdiploid ALL with simultaneous trisomy of chromosomes 4, 10, and 17 has the least treatment failure and the greatest clinical outcome [33]. Enumeration of chromosomes 4, 10, and 17 by FISH (triple trisomy FISH) can identify these numerical changes (Fig. 2.9), providing important prognostic information when chromosome analysis is unsuccessful or when a normal karyotype is identified by banding studies. In contrast, hypodiploid ALL (B-lymphoblastic leukemia/lymphoma with hypodiploidy) defines a subgroup characterized by <45 chromosomes per karyotype. This is observed in both adults and children; however, near-haploid ALL (with 23–29 chromosomes) is identified almost exclusively in children. Hypodiploid ALL is associated with a poor prognosis [3]. Care should be exercised when a high

Fig. 2.8 Pediatric bone marrow with precursor B-cell ALL demonstrating a hyperdiploid karyotype. Note trisomy for chromosomes 4 and 17 (see text)

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Fig. 2.9 Pediatric B-cell ALL demonstrating trisomy of chromosomes 4, 10, and 17 by FISH

hyperdiploid/near-triploid karyotype is identified to examine the pattern of chromosome gain, as duplication of a near-haploid/hypodiploid karyotype can appear as a hyperdiploid karyotype, yet will be associated with the poor prognosis characteristic of hypodiploid ALL. In the non-hyperdiploid ALL subgroup, four major translocations have been observed. B-lymphoblastic leukemia/lymphoma with t(12;21)(p13;q22); TEL/AML1 (ETV6/RUNX1) is recognized in up to 30% of childhood B-precursor ALL; however, this translocation is rare or absent in infants and in adults with ALL. The t(12;21) translocation fuses the TEL (ETV6) and AML1 (CBFA2 or RUNX1) genes, normally localized to 12p13 and 21q22, respectively. Many studies have demonstrated that ALL patients with TEL/AML1 fusion do extremely well. This translocation cannot be detected by conventional cytogenetics due to its cryptic nature, therefore necessitating the use of a TEL/AML1 fusion FISH probe for detection [3]. B-lymphoblastic leukemia/lymphoma with t(9;22)(q34;q11.2); BCR/ABL1 is observed in approximately 5% of children but up to 25% of adults with ALL. The resulting BCR/ABL1 hybrid gene product is a 190-kDa protein that, as in CML, possesses dysregulated tyrosine kinase activity and is responsible for leukemic transformation. Ph+ALL is one of the most difficult childhood leukemias to treat and is generally associated with a poor prognosis [3]. Any of the BCR/ABL1 FISH probe formats utilized in CML will also detect the fusion gene associated with breakpoints within the minor breakpoint region in ALL. B-lymphoblastic leukemia/lymphoma with t(v;11q23); MLL rearranged constitutes a subgroup characterized by translocations of chromosome band 11q23

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causing rearrangements of the MLL gene. This is seen in 80% of infant leukemia and in secondary leukemia that arises in patients treated with topoisomerase II inhibitors. Leukemic cells containing 11q23/MLL rearrangement are usually non-hyperdiploid, have an early pre-B-cell immunophenotype, and coexpress myeloid antigens except for CD10. Generally, ALL that involves MLL gene rearrangement is a clinically aggressive disease with a poor prognosis. Greater than 50 translocation partners with 11q23 have been described in ALL, suggesting that disruption or destabilization of MLL function underlies leukemogenesis in these cases. As these leukemias have been observed in very young infants, it has been theorized that MLL gene rearrangement may occur in utero. The most common translocations are t(4;11) followed by t(11;19) and t(9;11). As many different variant t(v;11q23) translocations exist, the most sensitive method for detecting MLL gene rearrangement is to utilize an MLL gene rearrangement probe [3, 30]. B-lymphoblastic leukemia/lymphoma with t(1;19)(q23;p13.3); E2A/PBX1 (TCF3/PBX1) is seen in approximately 5% of adult and childhood ALLs and encodes the fusion protein E2A/PBX1. This was previously thought to represent a poor prognostic marker, but intensification of therapy in pediatric patients has overcome its effects on outcome. This translocation can be detected utilizing an E2A gene break-apart FISH probe [3]. B-lymphoblastic leukemia/lymphoma with t(5;14)(q31;q32); IL3/IGH is a rare entity accounting for less than 1% of all cases of ALL. Seen in both children and adults, the prognostic significance of this translocation is not firmly established. Conventional cytogenetic analysis can usually identify this abnormality [3]. FISH has become an invaluable tool for identifying the major genetic aberrations in ALL and for risk-stratifying patients with this disease. In one large study, FISH screening using probes for TEL/AML1, BCR/ABL1, and MLL gene rearrangements along with selected centromeric probes increased the success rate to 91% and the detection rate of genetic aberrations to 89% [34]. Many clinical trials, including those established by the Children’s Oncology Group (COG), require all newly diagnosed ALL cases to undergo both conventional cytogenetic testing and molecular cytogenetic characterization for risk stratification utilizing a panel to identify TEL/AML1and BCR/ABL1 fusion; MLL rearrangement; and chromosomes 4, 10, and 17 triple trisomy.

T-Lymphoblastic Leukemia/Lymphoma T-lymphoblastic leukemia/lymphoma is a malignancy of lymphoblasts committed to the T-cell lineage. T-cell acute lymphoblastic leukemia (T-ALL) comprises about 15% of all childhood ALL cases. It is more commonly found in older than younger children and more often in males than females. In adults, T-ALL comprises about 25% of all ALL cases. T-cell lymphoblastic lymphoma (T-LBL) is found in all age groups and makes up approximately 90–95% of all lymphoblastic lymphomas. Both T-ALL and T-LBL demonstrate clonal rearrangements of the T-cell receptor (TCR) genes including the alpha/delta TCR loci at 14q11.2, the beta locus at 7q35, and

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the gamma locus at 7p14-15. These genes rearrange with various partner genes including MYC, HOX11 (TLX1), HOX11L2 (TLX3), and TAL1 and lead to dysregulation of the partner gene when it juxtaposes next to one of the TCR gene promoter regions. While an abnormal karyotype is identified in 50–70% of cases, FISH breakapart probes to detect rearrangement of the TCR alpha/delta, TCR beta, and TCR gamma loci (Table 2.4) are available [3].

Chronic Lymphocytic Leukemia/Small Lymphocytic Leukemia Low proliferation activity of leukemic B cells in culture and overgrowth of normal cells preclude the routine detection of chromosomal abnormalities by conventional cytogenetic analysis in chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). For this reason, FISH utilizing a panel of DNA probes that interrogate the MYB gene at 6q23, ATM gene at 11q22.3, chromosome 12 alpha-satellite region, D13S319 locus at 13q14.3, LAMP1 gene at 13q34, and p53 gene at 17p13.1 is a useful adjunct to conventional analysis in the workup of a newly diagnosed CLL/SLL case. G banding reveals a clonal chromosomal abnormality in approximately 40% of CLL/SLL cases (with trisomy 12 being the most frequent), while FISH identifies genetic aberrations in over 80% of CLL/SLL cases. With FISH, the most common single chromosomal abnormality is a deletion of 13q14 found in 55–65% of cases followed by trisomy 12 in 15–25%, deletion of 11q22/ATM in 11–18%, deletion of 17p13/p53 in 7–8%, and deletion of 6q in 5–6% [35–37]. Identification of these abnormalities is of prognostic value, with isolated 13q deletion or a normal karyotype predicting a better prognosis, while del(6q), del(11q), and del(17p) characterize a group with a poorer prognosis. Trisomy 12 carries a high risk of disease progression, but unlike patients with del(17p) and del(11q), patients with trisomy 12 respond to therapy with better survival [35]. Follow-up FISH studies are also clinically useful, as demonstrated by one study which showed that 27% of CLL patients acquired new chromosomal aberrations during the course of their disease, and in one-third of these patients, the newly detected abnormalities changed their disease status from low risk to high risk [38].

Plasma Cell Myeloma Identification of recurrent chromosomal abnormalities by conventional analysis in plasma cell myeloma (PCM) has been hindered by patchy bone marrow infiltration, low mitotic index of malignant plasma cells in vitro, the poor quality of metaphase chromosomes, and the cryptic nature of some IgH gene rearrangements observed in this disease. An abnormal karyotype is found in 30–40% of cases, more often in advanced stages than in newly diagnosed patients. Highly complex karyotypes are also common, mostly in later stage disease [39–42]. Three distinct cytogenetic groups are recognized: (1) a hyperdiploid group with 47 or more chromosomes observed in 30–50% of cases with a lower frequency

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of IgH/14q32 rearrangement and monosomy 13/del(13q), (2) a hypodiploid group accounting for 20–35% of cases with a higher frequency of IgH/14q32 rearrangement and monosomy 13/del(13q), and (3) a pseudodiploid group in 20–35% of cases characterized by IgH/14q32 rearrangement [41]. Clinically, this cytogenetic classification is valuable, since hyperdiploid PCM patients seem to have a better outcome than do non-hyperdiploid patients. FISH analysis has demonstrated that chromosomal aberrations can be found in the majority of PCM cases, despite the relatively high incidence of a normal karyotype identified by conventional banding studies. In a Mayo Clinic study, Dewald et al. [42] identified one or more abnormalities by FISH in 86% of newly diagnosed PCM cases using a panel of FISH probes to detect t(4;14), t(11;14), t(14;16), 17p13 deletion, and monosomy 13/del(13q). Identification of monosomy 13/del(13q) by FISH is the most common abnormality detected in PCM. FISH studies have revealed that monosomy 13/del(13q) occurs in all stages of plasma cell neoplasms including monoclonal gammopathy of undetermined significance (MGUS), PCM, and plasma cell leukemia (PCL); however, the net effect of monosomy 13/del(13q) on prognosis is stronger when monosomy 13/del(13q) is detected by karyotype than when it is observed by FISH [42]. This is because the observation of abnormal metaphases indicates a larger tumor burden with a highly proliferative malignant plasma cell component. While monosomy 13/del(13q) has been associated with shorter survival and lower response rates to treatment, some recent studies have suggested that it may not, as the sole abnormality, be as important a prognostic marker. Instead, its close association with other poor prognostic markers such as t(4;14), t(14;16), and p53 gene deletion may contribute to the perception that monosomy 13/del(13q) predicts an adverse outcome. At present, the prognostic significance of chromosome 13 abnormalities in PCM is not completely clear [41]. The IgH/14q32 translocation is detected in more than 50% of PCM cases and is strongly associated with the non-hyperdiploid group [43]. This rearrangement is mediated mostly by errors in immunoglobulin class switch recombination [44] and is believed to be an early, possibly pathogenic event in many cases [45]. Three major specific IgH translocations t(11;14)(q13;q32), t(4;14)(p16.3;q32), and t(14;16)(q32;q23) are identified in PCM. The t(4;14) and t(14;16) are cryptic translocations found in less than 15 and 5% of patients, respectively. They can only be detected accurately utilizing the FGFR3/IgH and MAF/IgH FISH dual-fusion FISH probes. Both t(4;14) and t(14;16) are associated with hypodiploidy, an adverse disease outcome with shorter survival, and aggressive clinical features. Less common translocations involving IgH have also been described involving partner genes such as IRF4, IRTA1/IRTA2, and C-MYC [41]. Secondary IgH translocations that dysregulate the C-MYCproto-oncogene are found in 5% of PCM cases [40]. Those types of translocations are considered late progression events and are likely to have a negative impact on overall prognosis. The t(11;14) is the most common translocation observed in PCM, being seen in 15–20% of cases. While it can be detected easily by G banding, the IgH/CCND1 FISH probe is useful to examine metaphase cells with a complex karyotype or poor

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morphology, and to asses interphase nuclei in cases that yield normal metaphases. The t(11;14) results in upregulation of CCND1and is associated with a favorable prognosis. Other cyclin genes such as CCND2 and CCND3 have also been found to be upregulated in both MGUS and PCM. It appears that almost all cases of MGUS and PCM tumors upregulate at least one cyclin gene, sometimes as a consequence of an IgH translocation [45]. Some have proposed that a classification system for PCM based on the type of cyclin gene expressed together with the karyotypic profile may generate useful biological and clinical subgroups. Deletion of 17p13/p53 gene using a locus-specific p53 gene FISH probe is detected in 9–30% of PCM cases. This abnormality is identified more often in nonhyperdiploid PCM (26%) than in the hyperdiploid group (1%) [40]. Deletion of 17p13 is associated with a poor prognosis in PCM. It is clear that identification of cytogenetic abnormalities by both conventional karyotyping and FISH studies provides important diagnostic and prognostic information in PCM. The FISH panel utilized by most cytogenetics laboratories in newly diagnosed PCM cases includes enumeration probes for chromosomes 3, 9, and 15 to screen for ploidy (gain of chromosomes 3, 9, and 15 is found in >90% of hyperdiploid cases) as well as probes to detect monosomy 13/13q deletion (RB1/LAMP1), p53 gene deletion, and common IgH translocations (Fig. 2.10). This methodology yields significant prognostic information for risk assessment and treatment stratification in patients with PCM. In order to increase the sensitivity of FISH in PCM, some labs are now employing techniques that enrich

Fig. 2.10 Plasma cell myeloma FISH panel demonstrates the following: (a, b) loss of the D13S319 and RB1 loci (one orange signal) with retention of the LAMP1 locus at 13q34 (two green signals) [this differentiates a chromosome 13q deletion from monosomy 13] and (c) loss of the p53 gene (one orange signal indicated by arrows)

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for the plasma cell component in either whole-nuclei preparations or paraffinembedded tissue sections. Originally described by Ahmann and colleagues [46], simultaneous FISH and cytoplasmic immunoglobulin staining permits analysis of only cells that express a plasma cell phenotype. Other techniques including May-Grunwald Giemsa (MGG) staining and FISH (target FISH or T-FISH) [47], FICTION (fluorescence immunophenotyping and interphase cytogenetics as a tool for the investigation of neoplasms) [48], and SNP microarrays combined with FISH [49] have been used to enrich for the malignant component in FISH analysis of plasma cell disorders.

Non-Hodgkin Lymphoma The majority of non-Hodgkin lymphomas (NHLs) demonstrate clonal chromosomal abnormalities. The primary aberrations are commonly translocations that cause relocation of oncogenes to the vicinity of highly active promoter/enhancer elements of immunoglobulin or T-cell receptor genes in B-cell or T-cell lymphoma, respectively, resulting in gene deregulation [50]. Unlike most of the translocations in acute and chronic leukemias that result in a hybrid fusion gene with altered activity, the translocations in B-cell lymphoma mostly result in juxtaposition (not fusion) of the oncogene to an immunoglobulin gene regulatory sequence. One exception is the API2–MALT1 fusion gene generated by the t(11;18)(q21;q21) in MALT lymphoma. In some B-lineage lymphomas such as Burkitt lymphoma [t(8;14)(q24;q32) and its variants] or mantle cell lymphoma [t(11;14)(q13;q32)], one or a few specific IgH rearrangements are identified in the majority of cases and are thus considered pathognomonic for the disease; however, in other B-cell neoplasms such as diffuse large B-cell lymphoma, IgH rearrangements are detectable in a smaller number of cases and are translocated with a wide variety of partner genes. In general, few translocations identified in B-cell neoplasms are characteristic of a specific lymphoma subtype [41]. Cytogenetic and molecular studies have provided evidence that the process of oncogenesis in many lymphomas follows a multistep process similar to that originally described for colorectal cancer. It appears that the primary genetic event of a tumor clone initiates the lymphoid malignancy. These genetic alterations thus serve as diagnostic markers for the malignancy; however, additional changes would appear to be necessary for sustained lymphomagenesis. One line of evidence to support this notion is the molecular identification in apparently healthy individuals of genetic alterations such as the t(14;18) or the t(11;14). Whether these individuals are at higher risk for subsequent development of malignancy is not clear, but it seems that one or more additional genetic alterations are necessary for the development of frank malignancy. These secondary genetic changes are often identified along with the defined primary change in the diagnostic specimen. These, and further genetic changes, result in increasing complexity of the karyotype and are associated with transformation of an indolent lymphoma to one with more aggressive biological behavior. Thus, identification of complex karyotypes in the

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diagnostic lymphoma specimen, or cytogenetic evolution with increasing karyotypic complexity, is associated with a poorer prognosis [41]. Conventional cytogenetic analysis is not always possible in lymphomas due to the lack of fresh tissue and small biopsy specimens. FISH can be used to establish the diagnosis in viable and fixed tissue and to assess the involvement of bone marrow by lymphoid tumor. As unfixed tissue may not be available, FISH on paraffin-embedded tissue sections can be an invaluable technique to identify genetic aberrations in lymphoid malignancies, as can FISH analysis of touch imprint specimens [51]. Studies have shown that the sensitivity of FISH for detecting lymphoma-associated chromosome translocations is higher and more specific than PCR owing, in part, to the large genomic region over which some of the translocation breakpoints are spread. This can preclude their detection by molecular methods in a highly sensitive fashion. In mantle cell lymphoma, for instance, FISH was found to be superior to PCR with a 95–100% detection rate of IgH/CCND1 gene fusion as compared with a detection rate of 35–40% by PCR [52]. Follicular lymphoma. The most frequent translocation in B-cell NHL, t(14;18)(q32;q21), juxtaposes the BCL2 proto-oncogene at 18q21 next to the IgH gene locus at 14q32 (Fig. 2.11). This translocation is identified in 80–90% of follicular lymphoma (FL) cases and to a lesser extent in diffuse large B-cell lymphoma (20–30%). The translocated BCL2 gene encodes an aberrant protein that inhibits apoptosis. Only in 10% of cases is the t(14;18) the sole abnormality. A number of non-random secondary changes are documented, the most common of which is an additional copy of the derivative chromosome 18 originating from the t(14;18) [der(18)t(14;18)(q32;q21)]. Low-grade FL can progress to high-grade FL or transform to diffuse large B-cell lymphoma (DLBCL) through acquisition of additional cytogenetic changes, an event associated with a poorer prognosis [41]. Another recurrent primary abnormality in FL is rearrangement of the BCL6 gene at band 3q27. This rearrangement occurs through a variety of chromosomal abnormalities involving various partner genes. In fact, BCL6 rearrangement appears to be an extremely common event in a variety of B-cell disorders, in particular DLBCL. Rearrangements of BCL6 result in dysregulation through its interaction

Fig. 2.11 (a) A patient with follicular lymphoma demonstrates the t(14;18) by conventional cytogenetic analysis. (b) FISH analysis utilizing a dual-color, dual-fusion probe reveals one red, one green, and two fusion signals (solid arrows) indicating fusion of IGH and BCL2genes. The hatched arrow indicates a nucleus with a normal signal pattern

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with gene regulatory sequences of the partner gene in the translocation. High-grade FL with BCL6 rearrangement but without the t(14;18) often progresses to DLBCL as well [41]. Diffuse large B-cell lymphoma. No chromosomal abnormality is specific for diffuse large B-cell lymphoma. Many of the chromosomal abnormalities observed in other B-cell lymphomas can be observed in this disease as well. These abnormalities include BCL6 gene disruption (20–40% of cases); translocations of 14q32 involving the IgH locus (20–40%); gain of chromosomes X, 3, 7, 12, and 18; and loss of chromosomes Y, 6, 13, 15, and 17. There is at present conflicting evidence regarding the prognostic significance of either BCL6 rearrangement or t(14;18), the most commonly observed translocation of 14q32 being observed in DLBCL. However, like in other lymphomas, del(17p) involving the p53 gene as well as karyotypic complexity indicates disease progression and a poorer prognosis [41]. Of interest is the finding that t(14;18) can occur concurrently with chromosome 8q24/MYC gene translocation in a number of B-cell neoplasms, including DLBCL. These neoplasms are of high grade and are associated with a poorer prognosis [53]. Burkitt lymphoma. The Burkitt lymphoma (BL)-associated translocations include t(8;14)(q24;q32), t(2;8)(p12;q24), and t(8;22)(q24;q11). The t(8;14) is observed in 75–85% of all BL patients (Fig. 2.12), while the remaining 15–25% of patients present one of the variant translocations, with the t(8;22) seen twice as frequently as

Fig. 2.12 This karyotype from a patient with Burkitt lymphoma demonstrates the t(8;14) (q24;q32) (solid arrows). An add (19q) chromosome is also present (open arrow)

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the t(2;8). These translocations juxtapose the C-MYC proto-oncogene at 8q24 next to the promoter for the Ig heavy chain gene at 14q32, Ig kappa locus at 2p12, or Ig lambda locus at 22q11. This repositioning of the MYC gene disrupts its regulation and results in its constitutive overexpression leading to malignant transformation. Activation of MYC takes place on the der(14) in the t(8;14) and on the der(8) in the t(2;8) and t(8;22). Molecular analysis of the breakpoints in sporadic, endemic, and immunodeficiency-associated BL demonstrates different clustering on the der(8) and the der(14), suggesting that different pathogenetic mechanisms may generate the t(8;14) in different disease settings. A characteristic feature of BL is that one of the three characteristic translocations is generally part of a relatively simple karyotype, with karyotypic complexity indicating disease progression. Among secondary chromosomal abnormalities, the most common is structural rearrangement of chromosome 1, especially the long arm, as well as trisomy 7 and trisomy 12 [41]. Mantle cell lymphoma. The t(11;14)(q13;q32) is present in virtually all cases of mantle cell lymphoma (MCL). In 20% of cases, it is part of a more complex karyotype, sometimes associated with loss of the der(11) chromosome. Chromosome numbers are generally in the diploid or the hyperdiploid range, except in the blastic variants where polyploidy is often observed. The t(11;14) involves a breakpoint within the BCL1 gene locus at 11q13 that results in relocation of the CCND1 gene (which is positioned downstream from BCL1) next to the promoter for the IgH gene. This results in the overexpression of CCND1. Identification of the t(11;14) is important as it can differentiate MCL from other low-grade lymphomas, especially if immunophenotyping is inconclusive [41]. Splenic marginal zone lymphoma. Up to 40% of splenic marginal zone lymphomas present a del(7q) chromosome. The t(11;14)(q13;q32) has also been reported; however, it is unclear whether these cases may have been MCL [41]. Extranodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT type). Three recurrent translocations are observed in MALT lymphomas. These include t(11;18)(q21;q21), t(14;18)(q32;q21), and t(1;14)(p22;q32). Trisomies 3 and 18 are observed in translocation-negative MALT lymphomas. Like other lymphomas, as MALT lymphomas progress, they acquire additional secondary chromosomal changes including MYC gene translocations (8q24), del(17p) with loss of p53 and del(9p) with loss of the CDKN2A locus. The presence of the t(11;18) and possibly the t(1;14) is associated with a low probability of cure by antibiotic therapy that targets Helicobacter pylori, the infectious agent responsible for the development of gastric MALT lymphoma [41]. Anaplastic large-cell lymphoma. The t(2;5)(p23;q35), which fuses the nucleophosmin (NPM) gene at 5q35 with the anaplastic lymphoma kinase (ALK) gene at 2p23, is the most common translocation observed in anaplastic large-cell lymphoma (ALCL). Tumors with this translocation are generally of high grade and express the CD30 (Ki-1) antigen. The t(2;5) leads to the formation of a chimeric fusion protein with constitutive tyrosine kinase activity. Other translocations which fuse ALK to other partner genes have been identified in ALCL as well [41].

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Hodgkin Lymphoma Chromosome analysis in classical Hodgkin lymphoma (HL) often reveals normal karyotypes due to the abundance of nonmalignant cells in the lesion; however, cytogenetic studies by classical and FISH methods combined with CD-30 immunofluorescence staining have revealed highly complex karyotypes with cytogenetic instability, triploid/tetraploid metaphases, and multiple aneuploidies in the neoplastic Reed–Sternberg cells. In nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL), abnormalities involving the BCL6 gene at 3q27 are identified in up to 50% of cases, not surprising given that NLPHL shares many features with DLBCL, and may in fact be a non-Hodgkin lymphoma rather than a HL [41].

Array-Based Genomic Profiling of Hematolymphoid Disorders The newest generation of hematolymphoid molecular analysis is based on the simultaneous examination of thousands of small genomic segments utilizing arrays containing either oligonucleotides (60-mers) or single-nucleotide polymorphisms (SNPs). SNP analysis appears to be better suited for studying neoplasia as it can detect gene-dosage changes at a higher level of resolution than can oligos and can also detect copy-number neutral loss of heterozygosity (acquired uniparental disomy). From a few hundred thousand to over one million individual loci can be interrogated in a single assay depending on the type of SNP array used. Two technologies currently available involve the spotting of individual SNPs onto gene chips (Affymetrix SNP Array) or adsorbed on microbeads (Illumina Infinium HD BeadChip). Some have referred to this technology as “molecular allelokaryotyping” [54, 55]. One significant disadvantage of array-based studies is that present platforms cannot detect balanced chromosomal rearrangements, a common feature of many hematolymphoid disorders. SNP arrays appear to provide concordant results when compared with FISH analysis using disease-specific panels; however, SNP analysis may not be as sensitive as FISH for detecting low-level mosaicism. Sargent et al. [56] studied 100 CLL samples utilizing both a typical CLL FISH panel and a 44 K oligonucleotide array and demonstrated a high degree of concordance between FISH and array CGH, although low-level mosaicism (<25% of nuclei positive for a chromosomal abnormality) was often not detected by array CGH. Studies utilizing SNP array technology to genomically profile hematolymphoid neoplasms are becoming more numerous in the literature. These studies have revealed clinically significant information previously unattainable by classical cytogenetic and FISH analysis. Lehmann et al. performed SNP chip analysis on 56 patients with early stage untreated CLL and identified not only abnormalities that were detected by simultaneous FISH analysis but also additional abnormalities including deletions of chromosomes 5q, 6q, and Xp. Whole-chromosome 13 uniparental disomy (UPD) was also identified and appears to be a common finding in early stage CLL [54]. Kawamata et al. performed SNP chip analysis on 14

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ALL samples at diagnosis, remission, and relapse. All cases demonstrated genomic abnormalities at relapse, with 10 samples acquiring additional changes not observed in the diagnostic specimen. These changes included deletion of the INK4A/ARF and NF2 genes. Also at relapse, uniparental disomy of chromosomes originally presenting in the diagnostic specimen as trisomy was identified, along with UPD of chromosome region 16p12.3-pter. Interestingly, this SNP chip study also revealed disappearance of deletions at relapse, possibly indicating that some of the clones identified at relapse were present but not identified at initial diagnosis [55]. SNP chip analysis of AML/MDS samples reported by Akagi et al. [57] identified genomic abnormalities including uniparental disomy in 49% of samples previously found to have a normal karyotype. These and other studies clearly demonstrate the power of SNP array-based genetic analysis; however, for the foreseeable future, a combination of conventional cytogenetics, FISH, and SNP array analysis will likely be the best approach to studying hematolymphoid disorders.

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Chapter 3

Using Cytogenetic and Molecular Tests in Diagnostic Workups with the WHO Classification – 2008 Clarence C. Whitcomb

Keywords WHO classification of hematopoietic neoplasms · Cytogenetic testing · Molecular tests · Immunohistochemical staining · Flow cytometry · Karyotype · DNA and DNA testing, Chronic myeloproliferative neoplasms · DNA sequencing · Comparative genomic hybridization · Gene expression profiles · Chronic myelogenous leukemia · BCR–ABL1 · Polycythemia vera · Essential thrombocythemia · Primary myelofibrosis · Chronic neutrophilic leukemia · Myeloid and lymphoid neoplasms with eosinophilia · PDGFRA · PDGFRB · FGFR1 · Chronic eosinophilic leukemia · Chronic myelomonocytic leukemia · Atypical chronic myeloid leukemia · Juvenile myelomonocytic leukemia · Myelodysplastic/myeloproliferative neoplasm · Myelodysplastic syndrome · Refractory cytopenia with unilineage dysplasia · Refractory anemia with excess blasts · Refractory anemia with ring sideroblasts · Refractory cytopenia with multilineage dysplasia · Childhood myelodysplastic syndrome · Acute promyelocytic leukemia · B-cell ALL · AML with minimal differentiation · AML without maturation · AML with maturation · Acute myelomonocytic leukemia · Acute monoblastic leukemia · Acute erythroid leukemia · Acute megakaryoblastic leukemia · Acute basophilic leukemia · Acute panmyelosis with myelofibrosis · Malignant lymphomas · Chronic lymphocytic leukemia · Follicular lymphoma · Mantle cell lymphoma · Marginal zone B-cell lymphoma · Diffuse large B-cell lymphoma · Burkitt lymphoma · T-cell lymphoma · Anaplastic large-cell lymphoma · NK lymphoma · Hodgkin lymphoma · Mast cell neoplasms A critical review of the neoplastic disorders of hematopoietic cells has been conducted by panels of expert clinicians and pathologists under the sponsorship of the World Health Organization (WHO), and from this effort a comprehensive classification for these disorders has been developed. Clinical features, phenotypic characteristics of the cellular proliferations, and, in many instances, genotypic features of the abnormal cells are all used in characterizing these disorders. Detailed C.C. Whitcomb (B) Department of Pathology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA e-mail: [email protected] D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_3, 

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descriptions and discussions of diagnostically important features for the entities defined within this classification have been summarized and published in a monograph – WHO Classification of Tumors of Haematopoietic and Lymphoid Tissues [1] – which represents the consensus of the many experts who have contributed to the WHO project. Findings from cytogenetic and molecular test procedures are included as important diagnostic criteria for many of the entities. Because this classification is used almost universally today, cytogenetic and molecular testing of blood, bone marrow, or tissue has become an integral component in the diagnostic workups for patients in whom these disorders are suspected. The following is a summary of the use of such tests in diagnostic workups, following the guidelines of the WHO classification. Particular emphasis is focused on entities and situations for which cytogenetic and molecular testing is required or can be very effectively used today. Detailed discussions of clinical, morphological, phenotypic, and genetic features of the hematopoietic neoplasms as well as specific criteria for diagnosing these disorders are presented in the WHO monograph cited above [1]. The discussion here is more general in focus, and this chapter is intended only as a guide to the WHO monograph, which should serve in practice today as the “working manual” for hematopathologists. The disorders are discussed in the sequence in which they are presented in the WHO monograph and the nomenclature used also follows the style of that work. An extensive list of references pertinent to the specific disorders is included in the WHO monograph. Selected references of a more general nature or which relate to practical issues arising during actual diagnostic workups are included here.

Diagnostic Workups Cytogenetic and molecular tests are technically specialized procedures that are often performed in regional facilities. Multiple individuals, at the “primary” site of care as well as in separate reference laboratories, may be involved in the generation of data from which a final diagnostic interpretation is formulated. Coordination of the many and varied activities involved in receiving, preparing, and distributing materials for testing, correlating test results with observations from traditional morphological studies and integration of the data from all of the procedures into a comprehensive summary are responsibilities of the hematopathologist. Careful case management during the workup is essential, and this is a non-trivial task. A diagnostic workup is a multi-step process. Procedures are used in a sequential manner to refine an evolving diagnostic impression. Evaluation of stained smears and tissue sections serves as the first step in a workup, for traditional morphological observations still provide a firm basis upon which at least a working differential diagnosis can be formulated [2]. An initial diagnostic impression is refined by more detailed phenotypic characterization of cells from the lesional tissue. Flow cytometry analysis of cells from the tissue is widely used for this purpose, and this technique is very effective in workups of the leukemic disorders [3].

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Immunohistochemical staining procedures are widely used in the workups of tissue tumors. The information generated by these “first-stage” activities may suffice for a working diagnosis, but often important issues will not have been completely addressed by the initial procedures. Cytogenetic and molecular tests are then used as “second-stage” studies to provide additional critical information. The specialized molecular and cytogenetic procedures can also be very helpful in the first stages of a workup, however – particularly in workups of tissue tumors – where they can help resolve “basic” diagnostic question such as whether a cellular proliferation is neoplastic at all or whether it represents a “benign” reactive process [4–6]. Immunohistochemical staining is a basic tool in the practice of pathology today [7]. The technique is rapid and inexpensive, but its application is limited to fixed cells and tissues, and the antibody reagents used must be reactive with these materials. A wider repertoire of antibodies can be used in flow cytometry analysis of cells in suspensions and that technique has greater analytic sensitivity. However, flow cytometry analysis requires fresh tissue, and, for useful information to be derived, sufficient viable cells must be isolated from the specimen. It also does not afford easy correlation of analytic results with histomorphology. Cytogenetic tests provide information related to the cell genome. Conventional karyotyping can detect deletions and amplifications of individual chromosomes as well as a wide range of structural alterations, such as translocations of segments within and among the chromosomes. A karyotype provides a comprehensive view of the genome at a relatively “gross” level, but it also requires fresh cells and is timeconsuming and expensive. In addition, not all diagnostically important structural abnormalities will be detected by this technique. Fluorescent in situ hybridization analysis (FISH) can target specific chromosomal segments or genes, and FISH procedures are rapid and can be performed with non-dividing cells in smears or histologic sections [8, 9]. In addition, FISH procedures can detect some structural alterations not discernable by routine karyotype analysis. When performed in situ, these cytogenetic procedures also facilitate correlation of cytogenetic and morphologic findings. Analyses of DNA or RNA provide information at a molecular level. When used to evaluate the antigen receptor genes (ARG) of B cells or T cells, these analyses are very useful for demonstrating the presence of a clonal lymphoid cell population within a background of “normal” cells. A clonal population is detected by virtue of the component cells having a similar ARG rearrangement, which is demonstrated in the analysis as a distinct “monoclonal” signal that is distinguished from “polyclonal” readings produced by the background cells. Tests for clonal ARG rearrangements are frequently used to assess whether a cellular proliferation is neoplastic or reactive – a “positive” finding of a monoclonal T- or B-cell population being considered as evidence supporting an interpretation of neoplasia [10]. Molecular tests do not provide information of a “gross” nature such as gains or losses of whole chromosomes or chromosomal segments, but they are excellent tools for detecting specific structural abnormalities. Molecular techniques can be used as an alternative to FISH procedures for detecting chromosome translocations in many instances. Molecular tests provide the greatest analytic sensitivity, and they

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are very useful in evaluating specimens for residual disease detection [11]. However, due to variations in the structural rearrangements that can alter the chromosomes, some important translocations may not be detected. In these cases FISH analysis can be diagnostically more sensitive and should be used if molecular testing yields a “negative” finding. Molecular tests are performed using DNA and RNA extracted from cells. Careful tissue handling is required to obtain high-quality material for molecular testing. Expeditious processing is particularly required to obtain material suitable for RNA analysis. In the most direct approach a portion of fresh tissue can be submitted for molecular analysis in the first stage of the workup. If molecular testing will be deferred to a later stage, the tissue aliquot may be preserved by freezing, preferably at –70◦ C. Alternatively, for DNA analyses using polymerase chain reaction techniques, material for analysis can be extracted from fixed tissue that has been embedded in paraffin blocks. The latter approach is very useful when the amount of diagnostic tissue is limited, and it facilitates correlation of molecular and morphological findings. Highly technical cytogenetic and molecular procedures such as comparative genomic hybridization (CGH) [12], sequencing of DNA, and generation of gene expression profiles (GEP) by array analyses [13] – among other techniques – have been used widely in investigational studies. These studies have contributed immensely to the current understanding of pathogenetic mechanisms involved in the neoplastic hematopoietic disorders, and findings from some studies have been translated into new approaches in diagnosis and clinical management. These more technically demanding procedures are not used in the routine diagnostic setting at this time, and they will not be discussed further here, except in the context of possible future applications.

Chronic Myeloproliferative Disorders The following sections summarize information that is presented in great detail in the WHO monograph cited above. Most of the factual assertions and recommendations made in the following comments are taken from that monograph [1]. A very useful summary of the cytogenetic and molecular findings used in defining the myeloid disorders has been also recently published [14]. The myeloproliferative neoplasms (MPN) include chronic myelogenous leukemia, BCR–ABL1 positive, polycythemia vera, essential thrombocythemia, and primary myelofibrosis, as well as entities designated chronic neutrophilic leukemia, myeloid and lymphoid neoplasms with eosinophilia and abnormalities of PDGFRA, PDGFRB, or FGFR1, chronic eosinophilic leukemia, NOS, and myeloproliferative neoplasm, unclassifiable. Each of these entities is characterized by the presence of a clonal proliferation of myeloid – i.e., granulocytic, erythroid, and megakaryocytic – cells. Cytogenetic and molecular tests are essential in the workups of these disorders. Indeed, the use of such tests in the diagnosis and treatment of patients with chronic myelogenous leukemia (CML) is a paradigm for how such testing may

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Table 3.1 Molecular and cytogenetic findings in myeloproliferative neoplasms WHO category

Required findings

Chronic myelogenous leukemia, BCR–ABL1 positive Chronic neutrophilic leukemia Polycythemia vera Primary myelofibrosis Essential thrombocythemia Myeloid and lymphoid neoplasms with eosinophilia and abnormalities of PDGFRA, PDGFRB, or FGFR1 Chronic eosinophilic leukemia, NOS Myeloproliferative neoplasm, unclassifiable

BCR–ABL1 POS See text BCR–ABL1 NEG BCR–ABL1 NEG BCR–ABL1 NEG BCR–ABL1 NEG BCR–ABL1 NEG Variable translocations involving PDGFA (4q12), PDGFB(5q31-33), or FGFR1(8p11-12) may be found BCR–ABL1 NEG; PDGFA, PDGFB, and FGFR1 NEG BCR–ABL1 NEG; PDGFA, PDGFB, and FGFR1 NEG

Useful but not required

JAK2 POS – occasional cases JAK2 POS – most cases JAK2 POS – 50% of cases JAK2 POS – 40–50%

JAK2 POS – occasional cases JAK2 POS – occasional cases

be used in the management of hematopoietic neoplasms. Table 3.1 summarizes findings of relevant cytogenetic and molecular tests for the disorders of the MPN group. Abnormalities of genes encoding proteins involved in intracellular signaling pathways are pathogenetically associated with the MPN disorders. Tests to demonstrate these abnormalities are useful in diagnostic workups. Demonstration of the characteristic “Philadelphia chromosome,” which results from a reciprocal translocation of material between chromosomes 9 and 22 – designated in cytogenetic terminology as t[9;22](q34;q11.2) – has long been used for the diagnosis of CML. The translocation juxtaposes portions of the ABL1 gene on chromosome 9 (9q34) and the BCR locus on chromosome 22 (22q11.2) to create an abnormal “fusion gene” BCR–ABL1. A “positive” finding of an abnormal BCR–ABL1 gene is a sine qua non for the diagnosis of CML. A positive test for BCR–ABL1 will be found in more than 90% of patients with CML. This abnormality can be detected by karyotyping, FISH analysis, or molecular procedures. Different BCR–ABL1 fusion genes can be formed depending upon the site(s) of breakage and recombination within the involved chromosomes. The usual translocation seen in CML results in a fusion gene that encodes a 210 kD protein. Breaks at other sites can result in fusion genes and gene products of different molecular sizes (e.g., p190 or p230 kD). A variant translocation that may not be detected by routine karyotyping can also occur. Therefore, other analytic techniques should be used when a “negative” result is found by karyotyping in a clinically suspicious case. Quantitative molecular tests for BCR–ABL1 have been developed, and these are now used to monitor the effects of therapy and to provide guidance for management decisions such as the timing of bone marrow transplantation [15].

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All of the other MPN disorders lack the distinctive BCR–ABL1 abnormality, but mutations of the JAK2 gene are associated with several of these entities. The most common mutation of JAK2 is designated as V617F [16]. A mutated JAK2 gene is not specific for any particular BCR–ABL1-negative MPN, and JAK2 mutations may be seen in rare cases of CML as well, but a “positive” molecular test finding is very useful for distinguishing a BCR–ABL1-negative myeloproliferative neoplasm from a reactive hyperplasia of myeloid cells [17]. The well-recognized BCR–ABL1-negative myeloproliferative neoplasms include the following: 1. Chronic neutrophilic leukemia: This rare disorder can resemble CML morphologically, but it is characterized by a predominance of mature neutrophils. Distinction from reactive neutrophilia is very difficult. A positive test for a JAK2 mutation will help resolve this problem. Rare cases of CML with a neutrophilia similar to that of chronic neutrophilic leukemia do occur, but the presence of a BCR–ABL1 fusion gene should distinguish these cases. The fusion gene in such cases of CML is often the result of a translocation producing a p230 kD protein. 2. Polycythemia vera: The JAK2 V617F mutation can be demonstrated in almost all cases. A positive finding for a JAK2 mutation is now a major criterion for the diagnosis of this disorder. 3. Primary myelofibrosis: Characteristic morphological features in bone marrow core biopsies are the primary features used for diagnosis. A JAK2 mutation can be found in about half of cases, however, and a positive finding is very useful in morphologically equivocal cases. 4. Essential thrombocythemia: JAK2 mutation can be demonstrated in about half of the cases. A positive test finding is helpful in differentiating this disorder from a reactive thrombocytosis. Other BCR–ABL1-negative disorders in the MPN group include the following: 5. Myeloid and lymphoid neoplasms with eosinophilia and abnormalities of PDGFRA, PDGFRB, or FGFR1: This diagnosis may be used if a translocation involving one of the genes PDGFRA(4q12), PDGFRB(5q31-33), or FGFR1(8p11-12) can be demonstrated. Abnormalities of these genes have been found in several neoplastic disorders in which eosinophilia is a conspicuous feature, and, because of these associations, this new entity has been added to the WHO classification in its most recent edition of 2008. Rare cases of CML with eosinophilia can be seen, but the presence of a BCR–ABL1 fusion gene should distinguish these cases. Therefore, tests for BCR–ABL1 should be used in conjunction with tests for these translocations when eosinophilia is a conspicuous feature. 6. Chronic eosinophilic leukemia, NOS: This diagnosis is appropriate only when an absence of eosinophilia-associated translocations has been demonstrated. 7. Myeloproliferative neoplasm, unclassifiable: This diagnostic category is appropriate only for cases which are BCR–ABL1 negative, have no demonstrable abnormalities of PDGFRA, PDGFRB, or FGFR1, and which have no

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morphological features that would support a diagnosis of one of the other BCR– ABL1-negative categories. Some of the “unclassifiable” cases may be JAK2 positive.

Myelodysplastic Disorders Two groups of entities designated as myelodysplastic/myeloproliferative neoplasms (MDS/MPN) and myelodysplastic syndromes (MDS) are included in the WHO classification. These groups include a complex assortment of disorders characterized by dysplastic morphological features involving mature and immature granulocytes, erythroid precursors, and/or megakaryocytes. The MDS/MPN group includes the following: Chronic myelomonocytic leukemia Atypical chronic myeloid leukemia, BCR–ABL1 negative Juvenile myelomonocytic leukemia Myelodysplastic/myeloproliferative neoplasm, unclassifiable Refractory anemia with ring sideroblasts (RARS) associated with marked thrombocytosis (provisional entity) The MDS/MPN disorders typically present with clinical and morphological features that are more like those of the myeloproliferative neoplasms, i.e., they are more “proliferative” in nature. Dysplastic features are often present, but may be rather minimal in these disorders. The MDS group includes the following entities: Refractory cytopenia with unilineage dysplasia Refractory anemia with ring sideroblasts Refractory cytopenia with multilineage dysplasia Refractory anemia with excess blasts Myelodysplastic syndrome with isolated del(5q) Myelodysplastic syndrome, unclassifiable Childhood myelodysplastic syndrome Refractory cytopenia of childhood (provisional entity) The MDS disorders usually present clinically with “cytopenic” features suggesting ineffective hematopoiesis. Morphological findings of dyserythropoiesis, dysgranulopoiesis, and/or dysmegakaryopoiesis are a hallmark of these disorders, and an accurate blast cell count is needed for diagnosis of these entities. Careful evaluation of a peripheral blood smear and adequately cellular bone marrow aspirate smears by microscopy is essential, particularly for determination of the “blast count.” Flow cytometry should not be substituted for morphological analysis for this purpose.

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The BCR–ABL1 abnormality that characterizes CML is not found in any of the MDS/MPN or MDS disorders, but a variety of non-specific cytogenetic abnormalities are common. Deletions of segments from chromosome 7 or 5 or deletions of the entire chromosomes – del(5) or del(7) – are frequently found, and multiple abnormalities are often present. A list of cytogenetic abnormalities that are typically seen in these disorders is included in the WHO monograph [1]. Although these cytogenetic abnormalities are not completely specific for the MDS disorders, they are used as “signature” features, and a diagnosis of a disorder from the MDS group can be made even in the absence of conspicuous morphological dysplasia if such cytogenetic abnormalities are present. Because no specific abnormality can be predicted from the initial morphological findings, however, a full karyotype study is recommended for diagnosis of these disorders. The genetic abnormalities found in the MDS/MPN and MDS disorders are not associated directly with the same intracellular signaling pathways involved in the MPN disorders, e.g., the JAK–STAT pathway. In some of the MDS/MPN entities, e.g., Juvenile myelomonocytic leukemia, mutations in the PTPN11, NRAS, KRAS, or NF1 genes that encode components of the RAS pathway are found. A JAK2 mutation may be seen in some cases of myelodysplasia, but this finding should not supersede the other genetic abnormalities associated with MDS as a diagnostic criterion. A finding of a 5q deletion as the only cytogenetic abnormality characterizes the entity designated myelodysplastic syndrome with isolated del(5q). A few patients with this rare disorder may also have a JAK2 mutation. Patients with the entity designated refractory anemia with ring sideroblasts (RARS) may have a marked thrombocytosis, and for these patients tests for JAK2 V617F should be obtained. If tests for JAK2 mutations are negative, studies of the MPL gene mutations W515K/L are recommended as well. Finally, a diagnosis of any of the entities in the MDS/MPN and MDS groups should not be made without demonstrating “negative” findings in tests for BCR–ABL1 and also for translocations involving PDGFRA, PDGFRB, or FGFR1 if eosinophilia is a prominent feature.

Acute Leukemias A diagnosis of acute leukemia is made when blasts constitute more than 20% of the nucleated cells in a cellular bone marrow aspirate smear. The initial diagnosis is usually made easily by morphological examination of peripheral blood and bone marrow materials. Microscopic examination of an adequately cellular bone marrow aspirate smear – including a “differential count” of at least 500 nucleated cells – is still the recommended technique for establishing a diagnosis of acute leukemia. The critical blast cell “count” should be determined by microscopy; quantitation by flow cytometry is not recommended. The blast cells may be of either myeloid or lymphoid lineage. Characterization of the blasts to distinguish acute myeloid leukemia (AML) from acute lymphoblastic leukemia (ALL) and, more specifically, to identify B-lineage acute lymphoblastic leukemia (B-ALL) or T-lineage acute lymphoblastic leukemia (T-ALL) is a

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necessary “first-stage” activity in the workup of an acute leukemia. Flow cytometry analysis is the preferred tool for determining the lineage of the blast cells, and this is usually readily accomplished when specimens containing sufficient blast cells are available. If sufficient cells cannot be obtained for analysis, morphologic techniques using immunostaining can be used. In some cases features of both myeloid and lymphoid lineages may be demonstrable. Despite the fact that a clonal rearrangement of a lymphoid antigen receptor gene – IGH for B cells or one of the T-cell receptor (TCR) genes for T cells – can be demonstrated in most cases of ALL, and that these same genes are usually in germline configuration in most cases of AML, tests for lymphoid ARG rearrangements are usually not needed in a workup of an acute leukemia. Because rearrangements of both an IGH and a TCR gene may be found in either B-ALL or T-ALL, these tests are not helpful for lineage determination. Rare cases of AML have been reported in which a clonal lymphoid ARG rearrangement was present as well. However, tests for a clonal T-lineage ARG rearrangement are useful for distinguishing NK cells, which do not have rearranged TCR genes, from true T cells, and tests for a clonal IGH rearrangement can help differentiate leukemic blasts of B-ALL from immature but polyclonal B cells (hematogones) that are often seen in regenerating bone marrow specimens post chemotherapy. Subtypes of AML and B-ALL are distinguished by the presence of specific cytogenetic translocations. These are designated as individual entities within the current WHO classification. The defining cytogenetic abnormality must be demonstrated for diagnosis of an individual case as one of these specific subtypes. No subclassification of T-ALL based on cytogenetic abnormalities is part of the current WHO schema. Other non-specific cytogenetic abnormalities as well as mutations in FLT or KIT genes may be found in any of the specific subtypes of acute leukemia, but only the designated abnormality is used as the “defining” criterion for classification. The cytogenetically defined subtypes of acute leukemia identify patients for which predictable differences in the clinical course have been well demonstrated [18]. Recognition of these specific subtypes of acute leukemia is helpful for clinical assessment of risk of relapse, and specific abnormalities can also serve as target “markers” in follow-up testing for residual or recurrent disease [19]. With the exception of acute promyelocytic leukemia (discussed below) complete cytogenetic characterization for most cases can be completed as “second-stage” procedures in the workup, but materials for these studies must have been taken and distributed appropriately from the materials initially received. The genetically defined subtypes of acute leukemia are listed in Table 3.2. The complete WHO terminology for these subtypes includes a formal designation of the defining translocation and the names of the genes involved, but for clarity in Table 3.2 the entities are listed with only the gene names. The associated cytogenetic abnormality – the required finding – is listed in the following column. The entity “acute promyelocytic leukemia with PML-RARA” is characterized by a specific cytogenetic translocation t(15;17) involving the retinoic acid receptor gene (RARA). This particular subtype of AML responds well to therapy that is designed to overcome the aberrant intracellular signaling that results from the aberration of

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C.C. Whitcomb Table 3.2 Cytogenetic findings in AML and ALL with recurrent genetic abnormalities

WHO category

Required findings

AML with RUNX1-RUNX1T1 AML with CBFB-MYH11 Acute promyelocytic leukemia with PML-RARA AML with MLLT3-MLL AML with DEK-NUP214 AML with RPN1-EVI1 AML with RBM15-MKL1 AML with mutated NPM1 AML with mutated CEBPA B-ALL with BCR–ABL1 B-ALL with MLL rearranged B-ALL with TEL-AML1 (ETV6-RUNX1) B-ALL with hyperdiploidy B-ALL with hypodiploidy B-ALL with IL3-IGH B-lymphoblastic leukemia/lymphoma with E2A-PBX1 (TCF3-PBX1) Mixed phenotype acute leukemia with BCR–ABL1 Mixed phenotype acute leukemia with MLL rearranged

t(8;21)(q22;q22) inv(16)(p13.1;q22) or t(16;16)(p13.1;q22) t(15;17)(q22;q12) t(9;11)(p22;q23) t(6;9)(p23;q34) inv(3)(q21;26.2) or t(3;3)(q21;q26.2) t(1;22)(p13;q13)

t(9;22)(q34;q11.2) t(v;11q23) t(12;21)(p13;q22)

t(5;14)(q31;q32) t(1;19)(q23;p13.3) t(9;22)q34;q11.2) A rearrangement involving MLL (11q23) must be present; t(4;11) is common

the RARA gene. Recognition of this subtype of AML with its unique pathophysiology is essential for optimal patient care. Some cases have distinctive morphological features (e.g., multiple Auer rods), and a finding of decreased or absent expression of HLADR by flow cytometry analysis is also very suggestive for this subtype. Definitive diagnosis requires demonstration of a translocation involving the RARA gene, however. Cytogenetic confirmation of such can be accomplished rapidly with FISH or molecular studies. The entity “B-ALL with [9;22](q34;q11.2); BCR–ABL1” is characterized by the presence of a BCR–ABL1 fusion gene. Tests for this signature abnormality should be capable of detecting the common variant translocations of BCR–ABL1. The p190 variant is found in most cases of ALL in childhood, while only about half of adult patients will have this form, the others having the p210 variant which is typically seen in CML. Other “leukemia-associated” cytogenetic abnormalities may occur in association with the BCR–ABL1 in these cases, but the BCR–ABL1 abnormality is the defining abnormality for classification. A variety of partner genes can participate in translocations with the MLL gene (11q23) in acute leukemia. Demonstration of a translocation involving the MLL gene is a requirement for diagnosis of a case as “B-ALL with MLL rearranged.” Karyotypic analysis may be required to detect these variable chromosomal abnormalities. Hyperploidy can be detected by karyotyping, by FISH analysis, or by a DNA index calculation from flow cytometric DNA ploidy analysis. When present,

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trisomies of chromosome 4, 10, and 17 are particularly significant, and a “triple” combination of all three trisomies is a particularly favorable cytogenetic finding. Eosinophilia may be seen in some cases of B-ALL, and this may be associated particularly with a t(5;14)(q31;q32) translocation. Two additional subcategories of acute leukemia designated “AML with mutated NPM1” and “AML with mutated CEBPA” are included in the WHO classification as “provisional” diagnostic categories. These are defined by the presence of mutations. The karyotype is usually unremarkable in these cases. The special tests for the defining mutations may not be widely available.

Acute Leukemias with No Specific Cytogenetic Findings A substantial number of cases of AML will not have any of the specific genetic abnormalities. Cases of AML with no defining abnormalities are designated “acute myeloid leukemia, NOS”. In such cases, the following diagnostic categories – defined entirely by morphological criteria – may be used. AML with minimal differentiation AML without maturation AML with maturation Acute myelomonocytic leukemia Acute monoblastic and monocytic leukemia Acute erythroid leukemia Acute megakaryoblastic leukemia Acute basophilic leukemia Acute panmyelosis with myelofibrosis Testing to establish the absence of any of the specific cytogenetic abnormalities is essential when these diagnostic categories are used. They should not be used for cases in which no testing has been performed. Studies for mutations of NPM1, CEBPA, and FLT3 may be recommended in cases of “cytogenetically normal” AML, but these special tests are not required for classification. For cases in which the morphological features suggest the rare entity acute basophilic leukemia, cytogenetic tests to establish the absence of a BCR–ABL1 fusion gene, and also the absence of t(6;9)(p23;q34), should be undertaken. Acute myeloid leukemia may arise in patients who have had a well-documented preexisting myelodysplastic disorder or in whom one or more of the “MDSassociated” cytogenetic abnormalities is demonstrable. Such cases may be diagnosed as AML with myelodysplasia-related changes. However, if any of the cytogenetic abnormalities specific for one of the genetically defined subtypes is present, the case should be classified within that specific subgroup. A separate group of entities designated acute leukemias of ambiguous lineage includes several diagnostically challenging disorders. Phenotypic studies using flow

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cytometry and immunohistochemical staining will demonstrate features of multiple lineages for the blasts in these cases, and designation of any single lineage for classification is equivocal. Various cytogenetic abnormalities may be found in these cases. If abnormalities involving the BCR–ABL1 or the MLL genes are present, the cases may be classified as either mixed phenotype acute leukemia with t(9;22)q34;q11.2); BCR–ABL1 or mixed phenotype acute leukemia with t(v;11q23); MLL rearranged.

Malignant Lymphomas Neoplasms of mature lymphoid cells presenting as tissue tumors constitute the malignant lymphomas (non-Hodgkin lymphomas) and Hodgkin’s disease (now called Hodgkin lymphoma). The WHO classification separates the mature B-cell and T-cell neoplasms into two large groups, each containing numerous specific entities that are differentiated by their morphological, phenotypic, and clinical features. Cytogenetic studies are not used for subclassification of the tissue tumors as they are for acute leukemia. However, such studies can be useful in resolving some differential diagnostic issues. Table 3.3 lists malignant lymphomas in which specific cytogenetic abnormalities can provide useful information. Brief discussions of some of the specific types of lymphoma are given below. Chronic lymphocytic leukemia (CLL), hairy cell leukemia, and some other “leukemic” disorders are grouped with the tumorous disorders in the WHO classification. The “leukemic” cells in these disorders are mature B or T cells, just as are the Table 3.3 Cytogenetic abnormalities in non-Hodgkin lymphomas WHO category

Potentially significant or useful findings

Follicular lymphoma Mantle cell lymphoma

t(14;18)(q32;q21) and BCL2 t(11;14)(q13;q32) Rare variants may be negative t(11;18)(q21;q21), t(14;18)(q32;q21), or t(3;14)(p14.1;q32)

Extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue (MALT lymphoma) Nodal marginal zone lymphoma Splenic marginal zone lymphoma Primary cutaneous follicle center lymphoma Diffuse large B-cell lymphoma (DLBCL), NOS Burkitt lymphoma B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and Burkitt lymphoma Primary cutaneous DLBCL, leg type Primary DLBCL of the CNS ALK-positive large B-cell lymphoma

Absence of t(11;18), t(14;18), or t(3;14) Absence of t(11;18) t(14;18)(q32;q21) and BCL2 Rearrangements of MYC may be seen in 10% A translocation involving MYC is strongly recommended A translocation involving MYC should be demonstrated, but an additional translocation involving BCL2 may be present as well Absence of t(14;18) t(14;18) and t(8;14) are seen only rarely t(2;5)(p23;q35) or t(2;17)(p23;q23) or variants

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cells of the disorders that present as primary tissue tumors. A distinction between “leukemia” and “lymphoma” can be arbitrary in some instances. Patients with CLL frequently have lymphadenopathy and splenomegaly, while patients presenting with tissue tumors can have a demonstrable “leukemic” component. Phenotyping of the leukemic cells is usually easily accomplished by flow cytometry for the “leukemic” disorders. No specific cytogenetic studies are required for the diagnosis of these “chronic” leukemias, but a general characterization of ploidy or karyotype may be useful, particularly in the management of patients with CLL. Molecular studies are often helpful in the first stages of a diagnostic workup of lymphoid proliferations in tissue. Molecular testing for clonal ARG rearrangements can be very helpful in distinguishing a neoplastic lymphoid cell proliferation from a reactive cellular infiltrate. A clonal IGH rearrangement can be found in virtually all of the B-cell lymphomas, and a clonal rearrangement of a TCR gene (usually TRB, TRG) can be demonstrated in most cases of T-cell lymphoma. The rare NK-cell lymphomas do not exhibit rearrangements of the T- and B-lineage antigen receptor genes. Because of the morphologic similarity between T cells and NK cells, molecular testing for TCR rearrangements is essential for distinguishing the neoplasms of these two lineages. Once a diagnosis of neoplasia has been established, further classification is based on the phenotype. In some cases, molecular techniques targeting specific genetic abnormalities may be helpful for resolving issues of classification.

Some Diagnostic Problems When small lymphocytic cells predominate or are admixed in significant numbers with larger lymphoid cells, the distinction of a neoplastic proliferation from a reactive / inflammatory lymphoid cell infiltrate can be very difficult. Restricted expression of immunoglobulin light chains by B cells can be used as an indicator of a clonal B-cell population, but demonstration of light chain expression is often difficult in sections of fixed and paraffin-embedded tissue. Flow cytometry analysis can demonstrate immunoglobulin light chain restriction if an adequate aliquot of unfixed cells is available, but this is frequently not possible with small endoscopic biopsies or needle core biopsies. In addition, neither morphologic nor flow cytometric techniques can demonstrate the presence of a clonal T-cell population. Because of these limitations molecular tests to demonstrate a clonal IGH or TCR rearrangement are often useful. Material from paraffin-embedded biopsy tissue can be used for these molecular studies if PCR-DNA techniques are used. However, clonality does not by itself imply neoplasia. A “positive” finding of a clonal ARG rearrangement in a morphologically suspicious lesion provides strong support for an interpretation of a B-cell lymphoid neoplasm. Contrariwise, a “negative” finding should foster caution in proceeding with such an interpretation. However, the occurrence of clonal B-cell populations in lymphoid tissue containing hyperplastic follicles has been well-documented [20, 21], and there are also numerous reports of findings of “monoclonal” T-cell or B-cell populations in biopsies interpreted with due consideration as morphologically

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benign [22–24]. Therefore, a positive molecular test finding should not be interpreted as prima facie evidence for neoplasia. Correlation of the molecular test findings with the histomorphologic features in the tissue from which the analytic material was derived is essential. “False-positive” molecular test findings may reflect physiologic expansions of non-neoplastic lymphoid clones, but technical aberrations may also produce findings that can be discordant with morphology [25–30]. Interpretation of the analytic data from PCR procedures can be challenging, particularly in specimens in which only a small number of cells are available. In such cases the findings may be reported as indicating “oligoclonal” or “pseudoclonal” populations [31]. Molecular test reports should include some discussion of the limitations of the analytic data when this occurs [32].

Follicular Lymphoma (FL) Follicular lymphoma is characterized by a t(14;18)(q32;q21) chromosome translocation that juxtaposes the BCL2 gene (18q21) and the IGH gene (14q32). Rare cases of FL can have a t(8;14) translocation in addition to t(14;18). The t(14;18) translocation is not specific for follicular lymphoma, and it can be seen in other types of mature B-cell lymphoma. In addition, a “positive” finding for a BCL2 translocation alone cannot be taken as an absolute indicator of clinical neoplasia, for abnormalities involving BCL2 have been reported in “normal” individuals [33, 34]. Despite these limitations, cytogenetic tests for a t(14;18) translocation can be useful in separating follicular lymphoma from atypical follicular hyperplasia, and they can serve as an adjunct to tests for ARG rearrangements in ambiguous cases. Due to variations in the sites of the chromosomal breakages and recombination, molecular tests may not be as diagnostically sensitive as FISH analysis.

Mantle Cell Lymphoma (MCL) This mature B-cell lymphoma is characterized by a t(11;14)(q13;q32) translocation that juxtaposes the CCND1 gene (11q13) and the IGH (14q32). The translocation results in deregulation of the BCL1 gene and consequent over-expression of cyclin-D1. Demonstration of cyclin-D1 by immunohistochemical staining is usually employed as the primary criterion for a diagnosis of MCL. When expression of cyclin-D1 cannot be demonstrated, however, cytogenetic tests for a t(11;14) translocation can be useful [35]. The t(11;14) translocation is specific for mantle cell lymphoma. In rare cases in which neither cyclin-D1 nor t(11;14) can be demonstrated – and in which no abnormalities characteristic of other subtypes of lymphoma are present – tests for other cyclins (e.g., cyclin-D2 or cyclin-D3) are recommended to support a diagnosis of MCL. Tests for t(11;14) may be useful for monitoring patients for residual or recurrent disease as well.

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Marginal Zone B-Cell Lymphoma (MZL) The lymphomas of marginal zone B-cell type occur in extranodal sites as well as lymph nodes [36]. Extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue (MALT lymphoma) is a relatively common “low-grade” lymphoid neoplasm of the gastrointestinal tract, and morphologically similar lymphomas occur in other “mucosa-associated” sites, such as the bronchial tree and ocular adnexa. Translocations involving the BCL2 gene may be seen in MZL, but genes other than IGH are often associated as “partners” in these chromosomal abnormalities. Different translocations may be seen preferentially in lesions from different sites. For example, a t(11;18)(q21;q21) translocation is most frequently found in gastric or pulmonary tumors, while a t(14;18)(q32;q21) translocation is more likely to be found in neoplasms involving ocular adnexa or salivary gland. A t(3;14)(p14.1;q32) translocation may occur in tumors of the thyroid, ocular adnexa, or skin. Distinguishing MZL from MCL (mantle cell lymphoma) can be challenging, and demonstration of a BCL2 translocation – in the absence of a translocation involving CCND1 – can be helpful in resolving this differential diagnostic problem. Biopsy specimens from extranodal lesions are frequently very small, and diagnosis by morphological examination can be very difficult. Tests for clonal ARG rearrangements are often needed to address the initial diagnostic question as to whether the lymphoid cell population is a neoplastic proliferation or simply a reactive infiltrate. As discussed previously, a “positive” molecular finding in a small biopsy specimen must be considered carefully. Correlation with morphological – and imaging findings – is essential to avoid “over-interpretation” [37]. Demonstration of a cytogenetic abnormality in these situations may help resolve uncertainty in the significance of a “positive” ARG rearrangement. In addition, cytogenetic testing for the t(11;18)(q21;q21) translocation can be helpful in the workup of gastric biopsies in patients with Helicobacter pylori infection. The presence of a t(11;18) gene rearrangement may be predictive of a lack of response to antibiotic therapy for H. pylori infection.

Diffuse Large B-Cell Lymphoma (DLBCL) Diagnosis of a large-cell lymphoma of B-cell lineage, in any of several morphological variants, is often relatively easy from the histomorphological features and the cellular phenotype as demonstrated by immunohistochemical staining. Tests for clonal IGH rearrangements will be “positive” in virtually all cases, and in many cases molecular testing is not really needed. Cytogenetic studies, if performed, will frequently demonstrate translocations involving the BCL6 or the BCL2 genes, but cytogenetic findings are not used as primary criteria for diagnosis or classification of these neoplasms. Investigations using array-based techniques to evaluate the expression of multiple genes within the tissue cell populations (gene expression profiling – GEP) have demonstrated that the large B-cell lymphomas can be subdivided into at least two

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groups – one in which the cells exhibit an expression profile similar to that of follicle B cells (germinal center-like B-cell lymphomas) and the other in which the profile is more like that of activated “non-follicle” B cells (activated B-cell lymphoma) [38]. Clinical studies have demonstrated significant differences in the behavior of tumors with these different gene expression profiles. The technically demanding GEP procedures are not suitable for routine diagnostic use at this time, but results from these studies have led to refinements in immunohistochemical profiling of the DLBCL. An algorithm incorporating the results of immunohistochemical stains for CD10, BCL6, and MUM1 has been used to sub-classify cases of DLBCL. An expanded discriminator incorporating findings for BCL2, BCL6, LMO2, FN1, CCND2, and SCYA3 has been proposed more recently [39].

Burkitt Lymphoma (BL) A diagnosis of “Burkitt lymphoma” is usually suggested by the histologic appearance of the tumor, but in many cases the morphology is “atypical” and distinction of BL from DLBCL can be problematic [40]. Cytogenetic tests may provide some guidance in resolving this diagnostic problem. Translocations involving the MYC gene on chromosome 8 with various “partner” genes are characteristic of true BL. Translocations with IGH, IGK, or IGL as partners – e.g., t(8;14), t(8;22), or t(2;8) respectively – are common variants. Tests to detect these translocations are recommended for confirmation of a diagnosis of BL in both classic and problematic cases. The translocations involving MYC are not specific for BL, however, and they may be found in some cases of DLBCL as well. A finding of a MYC translocation as the only abnormality provides strong support for classification of a case as BL. In contrast, findings of other abnormalities (e.g., translocations involving BCL6 or BCL2) along with a MYC translocation would favor a diagnosis of DLBCL. The diagnostic problem in separating BL from DLBCL is recognized in the WHO classification by inclusion of a separate category designated “ML with features intermediate between BL and DLBCL,” which can be used for cases in which the difficulties cannot be resolved. Cytogenetic tests may be helpful in the diagnosis of some other large-cell B-cell lymphomas as well. The t(14;18) translocation is typically not seen in “Primary cutaneous DLBCL, leg type” and it is also quite rare in “Primary DLBCL of the CNS.” Therefore, demonstrating an absence of this abnormality may help indirectly in properly classifying these particular lymphomas. In addition, the presence of a BCL2 translocation is used as an indicator of poor prognosis in DLBCL, and testing for this abnormality during and after treatment may assist in monitoring therapeutic response and detection of minimal residual disease or recurrent lymphoma.

Plasma Cell Neoplasms (PCN) Neoplastic proliferations of plasma cells present in several clinicopathologic forms. These neoplasms are distinguished by biochemical characteristics of the

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immunoglobulins produced by the neoplastic plasma cells as well as by clinical features. In most cases a plasma cell neoplasm is easily diagnosed by morphologic studies. Evidence of clonality is provided by demonstrating restricted expression of immunoglobulin light chains in the cytoplasm of the plasma cells. Either immunohistochemical stains or flow cytometry can be used for this purpose. Molecular tests are seldom needed for demonstration of a clonal population. Chromosomal abnormalities are commonly found in the PCN disorders, but cytogenetic tests are not needed for primary diagnosis. Recent investigational studies using gene expression profiling have led to a proposal for a subclassification of plasma cell myeloma based on gene expression patterns in association with the expression of cyclins-D1, -D2, and -D3, but this refinement is not included in the current WHO classification [41].

T-Cell Lymphomas The neoplasms of mature T cells form a large and diverse group of entities. As discussed previously, tests for clonal TCR rearrangements are very useful in the primary stages of a workup to establish the neoplastic nature of a T-cell proliferation. The subtypes of the T-cell neoplasms are distinguished primarily on the basis of morphological, phenotypic, and clinical features. Molecular and cytogenetic test findings are not used as primary diagnostic criteria for the recognized subtypes. The antigen receptor expressed at the cell surface in T cells may be composed of either alpha/beta or gamma/delta chains. Designation of a T-cell tumor as a gamma/delta T-cell neoplasm or an alpha/beta T-cell neoplasm is based on the antigen receptor expressed at the cell membrane. Tests for rearrangements of the underlying TCR genes usually target either the TCG (gamma chain) or TCB (beta chain) gene. The gene rearrangement(s) demonstrable by molecular testing may not necessarily correlate with the antigen receptor actually expressed at the cell membrane, however, and in some cases molecular testing will demonstrate rearrangements of both genes. Therefore immunohistochemical staining of the surface receptor molecule is the preferred technique for definitive lineage assignment within the T-cell neoplasms. The entity designated “T-cell lymphoma AILD like” is a noteworthy subtype of the T-cell lymphomas [42–44]. Clonal populations of B cells may develop in these tumors in addition to the dominant clonal T-cell population. Molecular testing may demonstrate both T-cell and B-cell clonality in such instances. Clonal T-cell populations, presumably arising as a “secondary” phenomenon, have been described in patients with plasma cell myeloma also [45, 46].

Anaplastic Large-Cell Lymphomas (ALCL) This morphologically distinctive lymphoid neoplasm is characterized by expression of CD30. The cells in many tumors express protein markers of T-cell lineage, and molecular tests for ARG rearrangements will demonstrate a clonal TCR rearrangement in many cases. The cells may also express a cytoplasmic protein ALK

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(anaplastic lymphoma kinase), which can serve as an additional useful diagnostic feature. Cases of ALCL are phenotypically and genotypically heterogeneous, however, and can present diagnostic difficulties. Some cases may not express markers of T-cell lineage, but may have a “positive” finding for a clonal TCR gene rearrangement. Other cases may have “negative” tests for ARG rearrangements, and not all cases express ALK protein. Expression of ALK in ALCL is often associated with a t(2;5)(p23;q35) translocation involving the ALK gene of chromosome 2. Cytogenetic tests demonstrating a translocation involving ALK may be helpful in problematic cases. Molecular tests for the ALK–NPM fusion gene created by the t(2;5) translocation are available, but PCR-based tests may occasionally be negative in cases of variant translocation.

NK-Cell Lymphomas An initial impression of a possible T-cell neoplasm often arises in the workup of a disorder of NK cells because of “positive” immunostaining for CD3. Clinical features can be very helpful in suggesting the NK-cell nature of the proliferation, however. The CD3 “positivity” in these cases reflects the presence of CD3-epislon within the cytoplasm of the NK cells rather than a complete CD3 molecule at the cell membrane – a finding that typifies true T cells. A discordant “negative” result for CD3 will be obtained from concurrent flow cytometric analysis that assesses membrane-associated CD3. Application of a comprehensive staining panel for antigens associated with NK cells, including CD56 and cytotoxic enzymes TIA1, granzyme, and perforin, should be used to document the NK-cell lineage of the abnormal cells in these cases. Demonstration of EB viral material within tumor cells is also useful in diagnosing some of the NK-cell entities. Molecular tests to demonstrate an absence of a clonal TCR rearrangement will be confirmatory and should be performed. Neoplasms of mature B and T lymphoid cells for which no specific cytogenetic abnormalities or molecular test findings have been found to date are included in the WHO classification. Diagnosis of these entities requires consideration of multiple features including the following: Histopathologic features: Plasmablastic lymphoma T-cell/histiocyte-rich large B-cell lymphoma Intravascular large B-cell lymphoma Peripheral T-cell lymphoma, NOS (including angioimmunoblastic T-cell lymphoma) Anaplastic large-cell lymphoma (C-ALCL) Clinical presentation: Splenic marginal zone lymphoma Primary mediastinal large B-cell lymphoma

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Primary effusion lymphoma Enteropathy-associated T-cell lymphoma Hepatosplenic T-cell lymphoma Cutaneous T-cell lymphomas (multiple subtypes) Subcutaneous panniculitis-like T-cell lymphoma) Presence of specific pathogenetic viruses: Adult T-cell leukemia/lymphoma (HTLV-1 associated) Large B-cell lymphoma arising in HHV8-associated multicentric Castleman disease EBV-positive T-cell lymphoproliferative diseases of childhood

Tests for Viruses Are Useful in Diagnosis of Hematolymphoid Neoplasms Tests for EB virus (EBV) are useful in the diagnosis of several entities within the WHO classification [47]. Burkitt lymphoma, DLBCL involving the CNS, primary effusion lymphoma, plasmablastic lymphoma, and some of the NK-cell neoplasms are associated with EB virus. Demonstration of the presence of viral materials in the cells of these proliferations can be useful for diagnosis of these entities. Demonstration of viral material within abnormal cells themselves is the diagnostically most important finding, and procedures that afford correlation with histopathology are recommended. Immunohistochemical staining for viral proteins and in situ hybridization procedures are generally used to demonstrate EB virus. Molecular tests targeting episomal EB viral DNA can be used to demonstrate clonal populations of infected cells as well, but such highly technical techniques are not readily available. Molecular tests (e.g., PCR) for EB viral material within CSF are useful in the workups of patients with CNS lesions that are suspicious for lymphoma when diagnostic tissue cannot be easily obtained. It is also reasonable to consider using tests for EBV in any situation in which immunocompromise is likely. Expression of EBV in Hodgkin lymphoma is also of current interest. Other viruses such as HIV, HTLV1, HHV6, HHV8, and HCV have also been implicated as cofactors in the pathogenesis of some lymphomas, and tests to document the presence of these agents may be useful in selected cases as well. Therapy designed to eliminate the viral agent may be a rational adjunctive therapeutic approach in those lesions associated with infection.

Hodgkin Lymphoma The tumors of Hodgkin lymphoma contain only a minor population of abnormal cells within a background of “normal” – presumably reactive – lymphoid cells, histiocytes, and granulocytic cells. The abnormal cells (Hodgkin and Reed–Sternberg cells) are indeed clonal lymphoid cells (usually of B-cell lineage), but, because

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of their scarcity, testing of whole (aggregate) tumor tissue for clonal ARG rearrangements often yields “negative” results. The clonal nature of the abnormal cells has been demonstrated by micro-dissecting them from tumor tissue and analyzing the minute quantities of DNA extracted therefrom. Such techniques are impractical for routine use at the present time. A diagnosis of HL is based entirely on the histomorphological features of the tumors. Cells with morphological features similar to Hodgkin or Reed–Sternberg cells can be found in some cases of mature T- or B-cell lymphoma. A “positive” finding for a clonal B-cell population by molecular testing will not distinguish HL from a B-cell lymphoma with “Hodgkin-like” features, but demonstration of a clonal T-cell population by molecular techniques can be helpful in differentiating HL from a Tcell lymphoma. Although cases of HL of T-cell lineage have been reported, a finding of a clonal T-cell population in conjunction with an “atypical” (i.e., “not classic for HL”) immunophenotype in the abnormal cells, would strongly suggest that the tumor is a T-cell lymphoma rather than HL. Diagnostic difficulties in separating HL from DLBCL are recognized in the WHO classification by inclusion of a category designated “ML with features intermediate between HL and DLBCL” [48–50]. This category can be used for cases in which the diagnostic difficulties are intractable with current testing modalities.

Other Hematolymphoid Neoplasms The WHO monograph includes detailed discussions of clinical and pathological features for tumors of mast cells, immature granulocytic cells (myeloid sarcomas), dendritic cells, and histiocytes. Proliferations associated with immunodeficiency are also discussed. With the exception of the neoplastic proliferations of mast cells, in which KIT mutations may be demonstrable, no specific cytogenetic or molecular findings are associated with these other proliferations, and diagnosis is based on morphological findings. Neoplasms of mast cells have been grouped with the clonal “myeloid” disorders of the MPN group in the 2008 WHO classification. Molecular testing for KIT mutation may be helpful for diagnosis in cases where morphological and phenotypic findings are equivocal and is important for prognosis since it results in relative resistance to tyrosine kinase inhibitor (imatinib) therapy.

Summary The goal of a diagnostic workup should be a concise and clinically useful report that summarizes the information generated from the various procedures used and states a final diagnostic interpretation using current terminology [51]. The report should particularly emphasize those attributes that support the diagnosis. When critical information is unavailable or when discordant findings arise during the workup, concise explanatory statements and recommendations for additional procedures will be helpful to the clinical user. Such a report will provide clear documentation for current and future management.

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The WHO classification includes some diagnostic categories intended for cases that are “unclassifiable” or which can only be classified in a general manner, e.g., as “not otherwise specified.” A discussion of the use of these diagnostic categories can be found in Chapter 2 of the WHO monograph. Although the particular comments in that chapter are directed to the use of the “unclassified” descriptor in connection with myeloproliferative neoplasms, the discussion can be generalized for application to other situations in which an adequate workup fails to provide sufficient diagnostic information. To quote from that discussion: “In such cases it is often preferable to describe the morphological findings, and to suggest additional clinical and laboratory procedures that are needed to further classify the process. The report should summarize the reason for the difficulty in reaching a more specific diagnosis, and, if possible, specify which [entities] can be excluded from consideration” [1]. Diagnostic difficulties do remain for a number of the entities in the current WHO classification, but it should be anticipated that ongoing studies will generate findings that may suggest new approaches to these difficulties [52–54]. In addition, continuing studies, particularly of the cytogenetically “normal” acute leukemias and of both “large-cell” and “small-cell” lymphomas, may very well lead to the recognition of new entities with clinically distinctive features. Since its original publication in 2001, the WHO classification has undergone continual review by panels of expert editors and consultants. In its most recent fourth edition, published in 2008, significantly increased emphasis was placed on cytogenetic and molecular testing. As members of the expert groups continue to review the classification, it should be anticipated that further revisions to diagnostic criteria, almost certainly incorporating additional findings from cytogenetic and molecular testing, will be forthcoming.

References 1. Swerdlow SH, Campo E, Harris NL, Jatte ES, Pileri SA, Stein H, Thiele J, Vardiman JW, eds. WHO Tumours of Haematopoietic and Lymphoid Tissues. International Agency for research on Cancer. Lyon, France: IARC; 2008. pp. 439. 2. Jaffe ES, Harris NL, Stein H, Isaacson PG. Classification of lymphoid neoplasms: the microscope as a tool for disease discovery. Blood. 2008;112:4384–4399. 3. Dunphy CH. Applications of flow cytometry and immunohistochemistry to diagnostic hematopathology. Arch Pathol Lab Med. 2004;128:1004–1022. 4. Arber DA. Review: molecular diagnostic approach to non-Hodgkin’s lymphoma. J Mol Diagn. 2000;2:178–190. 5. Bench AJ, Erber WN, Scott MA. Molecular genetic analysis of haematological malignancies: I. Acute leukaemias and myeloproliferative disorders. Clin Lab Haem. 2005;27:148–171. 6. Bench AJ, Erber WN, Follows GA, Scott MA. Molecular genetic analysis of haematological malignancies II: mature lymphoid neoplasms. Int J Lab Hem. 2007;29:229–260. 7. Garcia F MD, Swerdlow SH. Best practices in contemporary diagnostic immunohistochemistry panel approach to hematolymphoid proliferations. Arch Pathol Lab Med. 2009;133: 756–765. 8. Wolff DJ, Bagg A, Cooley LD, et al. Guidance for fluorescence in situ hybridization testing in hematologic disorders. J Mol Diagn. 2007;9:134–143.

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9. Ventura RA, Martin-Subero JI, Jones M, et al. Review: FISH analysis for the detection of lymphoma-associated chromosomal abnormalities in routine paraffin-embedded tissue. J Mol Diagn. 2006;8:141–151. 10. van Krieken JH, Langerak AW, Macintyre EA, et al. Improved reliability of lymphoma diagnostics via PCR-based clonality testing. Leukemia. 2007;21:201–206. 11. van der Velden VHJ, Hochhaus A, Cazzaniga G, et al. Detection of minimal residual disease in hematologic malignancies by real-time quantitative PCR: principles, approaches, and laboratory aspects. Leukemia. 2003;17:1013–1034. 12. Bejjani BA, Shaffer LG. Review: application of array-based comparative genomic hybridization to clinical diagnostics. J Mol Diagn. 2006;8:528–533. 13. Dunphy CH. Gene expression profiling data in lymphoma and leukemia: review of the literature and extrapolation of pertinent clinical applications. Arch Pathol Lab Med. 2006;130: 483–520. 14. Vardiman JW, Thiele J, Arber DA, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114:937–951. 15. Hughes T, Deininger M, Hochhaus A, et al. Monitoring CML patients responding to treatment with tyrosine kinase inhibitors: review and recommendations for harmonizing current methodology for detecting BCR-ABL transcripts and kinase domain mutations and for expressing results. Blood. 2006;108:28–37. 16. Tefferi A, Gilliland G. The JAK2V617F tyrosine kinase mutation in myeloproliferative disorders: status report and immediate implications for disease classification and diagnosis. Mayo Clin Proc. 2005;80:947–958. 17. Lay M, Mariappan R, Gotlib J, et al. Detection of the JAK2 V617F mutation by LightCycler PCR and Probe Dissociation Analysis. J Mol Diagn. 2006;8:330–334. 18. Arber DA, Stein AS, Carter NH, et al. Prognostic impact of acute myeloid leukemia classification: importance of detection of recurring cytogenetic abnormalities and multilineage dysplasia on survival. Am J Clin Pathol. 2003;119:672–680. 19. van der Reijden BA, Simons A, Luiten E, et al. Minimal residual disease quantification in patients with acute myeloid leukaemia and inv(16)/CBFB-MYH11 gene fusion. Acute myeloid leukaemia. Br J Haematol. 2002;118:411–418. 20. Iijima T, Inadome Y, Noguch Mi. Clonal proliferation of b lymphocytes in the germinal centers of human reactive lymph nodes: possibility of overdiagnosis of b cell clonal proliferation. Diagn Mol Pathol. 2000;9:132–136. 21. Nam-Cha SH, San-Millan´ B, Mollejo M, et al. Light-chain-restricted germinal centres in reactive lymphadenitis: report of eight cases. Histopathology. 2008;52:436–444. 22. Dippel E, Klemke CD, Hummel M, et al. T-cell clonality of undetermined significance. Blood. 2001;98:247–248. 23. Rawstron AC, Green MJ, Kuzmicki A, et al. Monoclonal B lymphocytes with the characteristics of ‘indolent’ chronic lymphocytic leukemia are present in 3.5% of adults with normal blood counts. Blood. 2002;100:635–639. 24. Dong L, Masaki Y, Takegami T, et al. Clonality analysis of lymphoproliferative disorders in patients with Sjogren’s syndrome. Clin Exp Immunol. 2007;150:279–284. 25. Zhou XG, Sandvej K, Gregersen N, et al. Detection of clonal B cells in microdissected reactive lymphoproliferations: possible diagnostic pitfalls in PCR analysis of immunoglobulin heavy chain gene rearrangement. J Clin Pathol. 1999;52:104–110. 26. Elenitoba-Johnson KS, Bohling SD, Mitchell RS, et al. PCR analysis of the immunoglobulin heavy chain gene in polyclonal processes can yield pseudoclonal bands as an artifact of low B cell number. J Mol Diagn. 2000;2:92–96. 27. Langerak AW, Molina TJ, Lavender FL, et al. Polymerase chain reaction-based clonality testing in tissue samples with reactive lymphoproliferations: usefulness and pitfalls. A report of the BIOMED-2 Concerted Action BMH4-CT98-3936. Leukemia. 2007;21:222–229.

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28. Murphy KM, Berg KD, Geiger T, et al. Consultations in molecular diagnostics: capillary electrophoresis artifact due to eosin: implications for the interpretation of molecular diagnostic assays. J Mol Diagn. 2005;7:143–148. 29. Kojo S, Elenitoba-Johnson J, Bohling SD, et al. PCR analysis of the immunoglobulin heavy chain gene in polyclonal processes can yield pseudoclonal bands as an artifact of low B cell number. J Mol Diagn. 2000;2:92–96. 30. Ahrens K, Braylan R, Almasri N, et al. IgH PCR of zinc formalin-fixed, paraffin-embedded non-lymphomatous gastric samples produces artifactual “Clonal” bands not observed in paired tissues unexposed to zinc formalin. J Mol Diagn. 2002;4:159–163. 31. Bagg A. Commentary: immunoglobulin and t-cell receptor gene rearrangements: minding your B’s and T’s in assessing lineage and clonality in neoplastic lymphoproliferative disorders. J Mol Diagn. 2006;8:426–429. 32. Gulley ML, Braziel RM, Halling KC, et al. Clinical laboratory reports in molecular pathology. Arch Pathol Lab Med. 2007;131:852–863. 33. Limpens J, Stad R, Vos C, et al. Lymphoma-associated translocation t(14;18) in blood B cells of normal individuals. Blood. 1995;85:2528–2536. 34. Summers KE, Goff LK, Wilson AG, et al. Frequency of the Bcl-2/IGH rearrangement in normal individuals: implications for the monitoring of disease in patients with follicular lymphoma. J Clin Oncol. 2001;19:420–424. 35. Wohlschlaeger C, Lange K, Merz H, et al. Aberrant immunophenotypes of mantle cell lymphomas. Leuk Lymphoma. 2003;44:269–273. 36. Rao DS, Said JW. Small lymphoid proliferations in extranodal locations. Arch Pathol Lab Med. 2007;131:383–396. 37. Hummel M, Oeschger S, Barth TF, et al. Wotherspoon criteria combined with B cell clonality analysis by advanced polymerase chain reaction technology discriminates covert gastric marginal zone lymphoma from chronic gastritis. Gut. 2006;55:782–787. 38. Alizadeh AA, Eisen MB, Davis RE, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403:503–511. 39. Lossos IS, Czerwinski DK, Alizadeh AA, et al. Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. N Engl J Med. 2004;350:1828–1837. 40. Haralambieva E, Boerma E-J, van Imhoff GW, et al. Clinical, immunophenotypic, and genetic analysis of adult lymphomas with morphologic features of Burkitt lymphoma. Am J Surg Pathol. 2005;29:1086–1094. 41. Kuehl WM, Bergsagel PL. Early genetic events provide the basis for a clinical classification of multiple myeloma. Am Soc Hematology. 2005;346–352. 42. Zettl A, Lee SS, Rudiger T, et al. Epstein-Barr virus-associated B-cell lymphoproliferative disorders in angioimmunoblastic T-cell lymphoma and peripheral T-cell lymphoma, unspecified. Am J Clin Pathol. 2002;117:368–379. 43. Luzzatto F, Pruneri G, Benini E, et al. Angioimmunoblastic T-cell lymphoma with hyperplastic germinal centres and a high content of EBV-infected large B-cells carrying IgH chain gene monoclonal rearrangement. Histopathology. 2005;46:464–466. 44. Tan BT, Warnke RA, Arber DA. The frequency of B and T cell gene rearrangements and EBV in T-cell lymphomas: a comparison between angioimmunoblastic T-cell lymphoma and peripheral T-cell lymphoma, unspecified, with and without associated B cell proliferations. J Mol Diagn. 2006;8:466–475. 45. Lim SH, Badros A, Lue C, et al. Distinct T-cell clonal expansion in the vicinity of tumor cells in plasmacytoma. Cancer. 2001;91:900–8. 46. Sze DM. Clonality detection of expanded T-cell populations in patients with multiple myeloma. Methods Mol Med. 2005;113:257–267. 47. Gulley ML, Tang W. Review: laboratory assays for Epstein-Barr virus-related disease. J Mol Diagn. 2008;10:279–292. 48. Poppema S, Kluiver JL, Atayar C, et al. Report: workshop on mediastinal grey zone lymphoma. Eur J Haematol. 2005;75(Suppl 66):45–52.

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Chapter 4

Update on the Molecular Pathology of Precursor Lymphoid Leukemias Robert B. Lorsbach

Keywords Acute lymphoblastic leukemia · Lymphoblastic lymphoma · Precursor B-lymphoblastic leukemia · Precursor T-lymphoblastic leukemia · Precursor lymphoid malignancy · World Health Organization · BCR–ABL1 · Philadelphia chromosome · IKAROS · IKZF1 · Micro-RNA · miR-230 · Chronic myelogenous leukemia · Down syndrome · GATA1 · Acute megakaryoblastic leukemia · JAK2 · JAK2 R683 mutation · Janus kinase · CRLF2 · IL-7 alpha receptor · Leukemia predisposition · ARID5B · Cancer stem cell · Leukemia stem cell · NOD/SCID mouse · NOTCH1 · Delta-like ligand · Gammasecretase · Gamma-secretase inhibitor · FBXW7 · PTEN (phosphatase and tensin analog) · PI3K (phosphatidylinositol 3-kinase) · HES1 (hairy and enhancer-of-split analog 1) · AKT · mTOR · Corticosteroids · Flow cytometry · Early T-cell precursor

Introduction The precursor lymphoid malignancies are a group of neoplasms derived from either hematopoietic stem cells (HSCs) or committed lymphoid progenitor cells, depending upon the underlying genetic lesion. Because the malignant cells in these tumors share many of the genetic (e.g., ongoing rearrangement of antigen receptor genes), and immunophenotypic (e.g., expression of progenitor markers such as CD34 and terminal deoxynucleotidyl transferase) properties of normal lymphoid progenitors, they are categorized under the World Health Organization (WHO) classification as “precursor lymphoid malignancies” [1]. These neoplasms include precursor B-lymphoblastic leukemia (B-ALL), precursor B-lymphoblastic lymphoma (B-LBL), precursor T-lymphoblastic leukemia (T-ALL), and precursor T-lymphoblastic lymphoma (T-LBL). B-ALL is significantly more common than T-lineage disease, with the latter comprising only 10–15% and 25% of ALL in children and adults, respectively. Although they may develop at any age, the precursor R.B. Lorsbach (B) Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA e-mail: [email protected]

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_4, 

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lymphoid malignancies arise most frequently in children, in whom ALL is the most common malignancy. The lineage of the malignant lymphoblasts, most commonly determined by flow cytometry-based immunophenotyping, greatly influences the likelihood of lymphomatous versus leukemic presentation [2]. With B-lineage disease, a leukemic presentation is much more common, whereas T-lymphoblastic malignancies manifest more frequently as a lymphoma most often an anterior mediastinal thymic mass. Historically, the precursor lymphoid malignancies have been classified according to their morphologic, cytochemical, or immunophenotypic properties. However, a wide array of cytogenetic and molecular lesions have been detected in these malignancies, which in many instances have been shown to have a profound impact on their biologic behavior and ultimately on clinical outcome. Thus, these underlying genetic lesions are now acknowledged as critical determinants in the classification and prognostication of the precursor lymphoid neoplasms, particularly for B-ALL/LBL. This is reflected in the recently published WHO classification, where several cytogenetically or molecularly defined subtypes of precursor ALL/LBL are now recognized as diagnostic entities. In this chapter, we will briefly review the classification of the precursor lymphoid malignancies and discuss briefly some general aspects of their pathogenesis. However, the main focus of discussion will be on recent advances in our understanding of the molecular pathogenesis of the precursor lymphoid malignancies.

WHO Classification of Precursor Lymphoid Malignancies The classification of the precursor lymphoid malignancies has been revised and included as part of the 2008 WHO classification of hematopoietic and lymphoid malignancies (Table 4.1) [1]. An important feature of this revised classification is its delineation as diagnostic entities of several cytogenetically or molecularly defined subtypes of ALL/LBL. In particular, the WHO classification includes several subtypes of B-ALL/LBL, each containing a critical genetic lesion (either a translocation or a numerical chromosomal abnormality) that has been extensively characterized Table 4.1 2008 World health organization classification of precursor lymphoid neoplasms B-lymphoblastic leukemia/lymphoma, not otherwise specified B-lymphoblastic leukemia/lymphoma with recurrent genetic abnormalities B-lymphoblastic leukemia/lymphoma with t(9;22)(q34;q11.2); BCR–ABL1 B-lymphoblastic leukemia/lymphoma with t(v;11q23); MLL rearranged B-lymphoblastic leukemia/lymphoma with t(12;21)(p13;q22); ETV6-RUNX1 B-lymphoblastic leukemia/lymphoma with hyperdiploidy B-lymphoblastic leukemia/lymphoma with hypodiploidy B-lymphoblastic leukemia/lymphoma with t(5;14)(q31;q32); IL3-IGH B-lymphoblastic leukemia/lymphoma with t(1;19)(q23;p13.3); TCF3-PBX1 T-lymphoblastic leukemia/lymphoma

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and shown to delineate a distinct tumor type. Particularly in the pediatric population, these subtypes of B-ALL/LBL are often associated with distinctive clinical behavior and are of prognostic importance. No subtypes of T-ALL/LBL are recognized for diagnostic purposes under WHO criteria. This is due, in part, to the fact that although several genetic lesions have been identified in T-ALL/LBL, their prognostic importance is not as well defined as the genetic abnormalities in B-lineage tumors. However, the recent identification in T-ALL/LBL of genetic abnormalities which represent potential therapeutic targets will likely prompt the recognition of these abnormalities in future WHO classification schemes. A practical and obvious implication of the 2008 WHO classification for the routine practice of diagnostic hematopathology is the requirement for cytogenetic or molecular characterization for final diagnosis of a precursor lymphoid neoplasm. The ongoing application of genome-wide, high-throughput genetic techniques to the analysis of the precursor ALL/LBL has revealed several novel genetic abnormalities in these malignancies, a subset of which appears to significantly impact on their clinical behavior. Thus, the classification of these malignancies will undoubtedly be further refined to better reflect advances in our understanding of their underlying molecular pathogenesis as well as to better define more homogenous leukemia subtypes that might be amenable to molecularly targeted therapeutics.

Overview of Cytogenetic and Molecular Lesions in Precursor Lymphoblastic Malignancies Numerous genetic lesions in ALL/LBL have been identified and extensively characterized, a comprehensive discussion of which is beyond the scope of this chapter. Therefore, in this section only general aspects of leukemogenesis will be addressed before proceeding to detailed discussion of several select topics on ALL pathogenesis. For a more general discussion of the molecular genetics of the precursor lymphoid leukemias/lymphomas, the reader is referred to several excellent reviews [3–6]. The precursor lymphoid malignancies include two major types in which there is immunophenotypic and genetic evidence of either B- or T-lineage lymphoid differentiation. The major genetic lesions found in B-ALL versus T-ALL are almost mutually exclusive. Rarely, one of these genetic abnormalities may be detected in both B-ALL and T-ALL, for example, the exceptional case of T-ALL expressing BCR–ABL1, a fusion almost invariably associated with B-ALL. This tight association between genetic lesion and disease type reflects the lineage-restricted expression and/or function of many of the gene products targeted by these genetic abnormalities. As alluded to above, the major cytogenetic/molecular subtypes of B-ALL have been incorporated into the current WHO classification (Table 4.1); these prominently include several chromosomal translocations and also subtypes in which there are numerical chromosomal abnormalities. The principal genetic lesions detected in T-ALL are indicated in Table 4.2; similar to B-ALL, these include not

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R.B. Lorsbach Table 4.2 Genetic lesions in T-ALL

Genetic lesion

Frequency

Target gene(s)

Translocations targeting TCR genes at 7q34 (TCRB & TCRG) and 14q11 (TCRA & TCRD) Aberrant expression due to 1p32 rearrangements Fusion oncogene formation

35%

TAL1, TAL2, TLX1 (HOX11), TLX3 (HOX11L2), LYL1, LMO1, LMO2, LCK, NOTCH1, OLIG2, CCND2 STIL-TAL1

Deletion of 9p21 and 6q Activating gene mutations

20% 10% ∼5% ∼5% Rare 65%, del(9p) 20–30%, del(6q) 50–60% 10–15% pediatric T-ALLs ∼10%

PICALM-MLLT10 (CALM-AF10) MLL fusions ABL1 fusions NUP98 fusions P15, P16 Unidentified loci NOTCH1 FLT3 NRAS, KRAS

only translocations but also other chromosomal rearrangements, as well as point mutations. The majority of these lesions target genes encoding transcription factors that are critically involved in normal B- and T-cell lymphopoiesis. In some instances, a chromosomal translocation targeting a transcription factor gene results in formation of a fusion oncoprotein that aberrantly activates or represses the expression of downstream transcriptional targets (e.g., ETV6-RUNX1), whereas other chromosomal rearrangements result in overexpression of a transcription factor with perturbation of downstream gene expression (e.g., rearrangements targeting the HOX genes in T-ALL). In contrast to AML and other myeloid disorders, few genetic lesions in ALL directly target tyrosine kinases, most notably BCR–ABL1 a constitutively activated tyrosine kinase resulting from the t(9;22). Finally, recent investigation has identified several genetic lesions important in the pathogenesis of ALL which may be detected in several molecular subtypes (Table 4.2). The most notable of these are activating mutations in NOTCH1 which are detected in more than half of T-ALL cases. Given this, some investigators have proposed defining as a “type A mutation” those genetic lesions which define specific ALL subtypes (e.g., the TCF3–PBX1 fusion oncogene resulting from the t(1;19) detected in a subset of B-ALL) and using “type B mutation” to denote those abnormalities which may be detected in two or more ALL subtypes (e.g., the aforementioned NOTCH1 mutations) [4]. In general, these genetic aberrations disrupt the normal ontogenetic program of the lymphoid progenitors in which they occur. This is achieved through the perturbation of several key cell signaling pathways in lymphoid progenitors, inducing variable degrees of dysregulated proliferation and cell cycle regulation, increased resistance to apoptosis, blocked differentiation, and ultimately the development of acute leukemia.

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B-lymphoblastic Leukemia with t(9;22)(q34;q11.2) The t(9;22)(q34;q11.2), or Philadelphia (Ph) chromosome, was the first described recurrent genetic lesion in a human malignancy and is by definition present in chronic myelogenous leukemia (CML) [7, 8]. This translocation targets the BCR and ABL1 genes located on chromosomes 22 and 9, respectively, and results in the expression of a BCR–ABL1 fusion mRNA transcript and ultimately the BCR– ABL1 fusion oncoprotein [9, 10]. While the chromosomal breakpoint at 9q34 occurs within a relatively restricted region of the ABL1 gene, within the intron preceding exon 2 (a2), there is much greater variability in the BCR breakpoints. In virtually all cases of CML and a minority of Ph+ adult and pediatric B-ALLs, the breakpoint in BCR occurs within the so-called major breakpoint cluster region (M-bcr) after either exon 13 (e13 or b2) or exon 14 (e14 or b3), resulting in the expression of a p210 fusion protein. However, in most cases of B-ALL, the minor breakpoint cluster region (m-bcr), located between exons 1 and 2 of BCR, is utilized. Because it contains significantly less BCR coding sequence, utilization of the m-bcr results in expression of the smaller p190 isoform of BCR–ABL1. Although not expressed in B-ALL, a p230 isoform of BCR–ABL1 is expressed in rare cases of CML in which the BCR breakpoint occurs within intron 19 [11–13]. The molecular genetics of the BCR–ABL1 rearrangements are detailed in several recent reviews [14, 15] and in Chapter 7. The leukemogenic effects of BCR–ABL1 are largely attributable to dysregulated protein tyrosine kinase activity, recently reviewed by Goldman and Melo [14]. Homodimerization of BCR–ABL1 is effected through motifs derived from BCR. This results in constitutive protein tyrosine kinase activation due to phosphorylation of critical tyrosine residues within the activation loop of the ABL-derived kinase domain. The dysregulated signaling induced by BCR–ABL1 is effected through several critical signaling pathways, including RAS, signal transducers and activators of transcription (STATs), phosphatidylinositol 3-kinase, mitogen-activated protein (MAP) kinases, and MYC. Thus, BCR–ABL1 signaling within a leukemic cell results in growth factor-independent proliferation, resistance to pro-apoptotic stimuli, and reduced cell adhesion. In addition to its pathogenetic role in CML, the t(9;22) with expression of BCR–ABL1 defines a subset of de novo B-ALL, so-called Ph+ B-ALL, accounting for 25% and approximately 3% of B-ALL in adults and children, respectively. Clinically, Ph+ B-ALL is an aggressive disease, and even in children it is associated with lower rates of complete remission and significantly lower rates of overall survival than most other molecular/cytogenetic subtypes of ALL [16, 17], although clinical outcome may be improved by addition of imatinib [18]. The mechanisms responsible for the poor outcome of Ph+ B-ALL are poorly understood; however, a better understanding of the genetic lesions that cooperate with BCR–ABL1 may permit the development of more effective, targeted therapies which would have a significant impact on clinical outcome, particularly in adult B-ALL. A major advance in our understanding of the pathogenesis of Ph+ B-ALL came with the recent demonstration that most Ph+ ALLs harbor deletions in the IKZF1

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Fig. 4.1 Genomic organization of the IKZF1 gene. IKZF1 encodes the B-cell transcription factor IKAROS. Exons are indicated by blue boxes; the first exon is noncoding. Those segments encoding zinc finger motifs within the N-terminal portion and the C-terminus are indicated by gray bars. As denoted, the N-terminal zinc fingers mediate DNA binding, whereas those located within the C-terminus are responsible for IKAROS dimerization

gene, which encodes the highly conserved transcription factor IKAROS [19–21]. IKAROS is expressed in hematopoietic progenitors and mature lymphoid cells. Mice deficient in Ikaros have major defects in lymphoid development as manifested by an absence of mature B cells and their progenitors, a marked deficiency of mature T cells and their progenitors, and an absence of NK cells [22]. Like most transcription factors, IKAROS is a modular protein (Fig. 4.1). Multiple zinc finger domains are located in the amino one-half of IKAROS and are responsible for DNA-binding and nuclear localization. Near the carboxy terminus, additional zinc finger motifs are present which mediate protein–protein interaction, including the homodimerization of IKAROS. In addition, this C-terminal domain mediates the interaction of IKAROS with other proteins, such as the histone deacetylases, that mediate chromatin remodeling. Using high-density single-nucleotide polymorphism (SNP) array analysis with whole-genome coverage, 60–80% of Ph+ B-ALLs from adult and pediatric patients IKZF1 were found to harbor IKZF1 mutations, nearly all of which were heterozygous [20, 21, 23]. The most common of these were deletions encompassing exons 3–6 (3–6). The resulting truncated transcript is predicted to encode an IKAROS isoform lacking the DNA-binding domain; this 3–6 mutant manifests aberrant subcellular localization, being localized in the cytoplasm [20]. Furthermore, the 3–6 mutant forms non-functional heterodimers with wild-type IKAROS and thus functions in a dominant-negative manner [24]. Less commonly, deletions of exons 1–6 were identified, deleting all but the last coding exon; other less common deletions of IKZF1 were also detected. Interestingly, earlier studies had identified multiple different IKZF1 transcripts in normal B cells as well as Ph+ B-ALL and in both instances were believed to be generated solely through alternative splicing [25, 26]. These more recent findings indicate that the variant transcripts in Ph+ BALL are due, in part, to intragenic deletions in IKZF1. Importantly, these mutations in IKZF1 are not observed in chronic-phase CML but are detected commensurate with transformation of CML to lymphoid blast crisis but not myeloid blast crisis, suggesting that the leukemogenic potential of these IKZF1 mutations is context specific for B-lymphoblastic malignancy [20, 23]. Recent studies provide insight into the basis for this association between BCR–ABL1 signaling and altered IKAROS function. Following ligation of the preB-cell receptor complex, signaling mediated by phosphorylated STAT5 and the SRC family of tyrosine kinases induces cell proliferation through the activation of NF-κB

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and ultimately upregulation of MYC and CCND2 [27]. This pro-proliferative signaling of the pre-B-cell receptor complex is counteracted by signaling through the linker proteins SYK and SLP65 which inhibits STAT5 and upregulates expression of IKAROS, subsequently inducing cell cycle arrest through IKAROS-dependent expression of p27 [28–30]. Elegant studies from Muschen and colleagues indicate that in the presence of IKAROS, BCR–ABL1 tyrosine kinase activity is diverted away from SRC signaling and toward that of SYK and SLP65, which would result in net growth inhibition [31]. Indeed, expression of wild-type IKAROS in BCR–ABL1+ B lymphoblasts induces cell cycle arrest, even though these cells do not express a functional pre-B-cell receptor complex. By contrast, in the absence of IKAROS, BCR–ABL1 downstream signaling occurs mainly through SRC-mediated pathways resulting in dysregulated proliferation. Thus, IKAROS appears to function as a tumor suppressor in the specific context of B-cell progenitors expressing BCR–ABL. The mechanism by which IKAROS “redirects” the downstream signaling effected by BCR–ABL1 remains to be determined. Nevertheless, these observations account for the high incidence of IKAROS mutations in BCR–ABL1+ B-ALL. Although not detected in AML or in most subtypes of ALL, IKZF1 mutations have also been detected in a subset of clinically aggressive ALL lacking BCR–ABL1 expression [32, 33]. Interestingly, these cases have gene expression profiles that are quite similar to that of Ph+ B-ALL. These observations suggest that BCR–ABL– B-ALLs with IKZF1 mutations may harbor occult mutations in an as yet unidentified tyrosine kinase. Indeed, activating mutations in the Janus family kinases have been described in a subset of high-risk B-ALLs, 70% of which also harbor IKZF1 mutations [34]. Finally, these findings indicate that the tumor suppressor function of IKAROS is not strictly limited to Ph+ ALL. Micro-RNAs (miRNAs) are short, noncoding RNAs that silence target gene expression through direct degradation of mRNA transcripts or indirectly through repression of translation. miRNAs regulate several important biologic processes, including cell proliferation, differentiation, and apoptosis [35]. Recent studies demonstrate that expression of BCR–ABL1, as well as that of native ABL1, is subject to miRNA-mediated epigenetic regulation [36]. Comparative genomic hybridization analysis of mouse leukemias expressing BCR–ABL1 identified loss of heterozygosity on chromosome 12, a region of the mouse genome which is particularly enriched in genes encoding miRNAs. Further analysis of this region revealed that the promoter of one gene, miR-230, had undergone extensive CpG hypermethylation. The syntenic region of the human genome containing miR-230 is located on chromosome 14q32, a region that is deleted with progression to blast phase in CML [37]. Importantly, such epigenetic silencing of miR-230 was also detected in primary human Ph+ leukemic cells, and it was specific for leukemic cells expressing BCR–ABL1, as it was not observed in BCR–ABL– cells. Reexpression of miR230 markedly inhibited proliferation of BCR–ABL1+ cell lines. These results have several important implications. First, they indicate that miR-230 is an important tumor suppressor in BCR–ABL1+ leukemias. Perhaps more importantly, they suggest that restoration of miR-230 expression in BCR–ABL+ leukemic cells may be

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therapeutically useful, an approach that could be achieved through the administration of demethylating drugs such as decitabine. While certainly preliminary, manipulation of miR-230 expression may represent an important new avenue for therapeutic intervention in BCR–ABL1+ leukemias.

Down Syndrome-Associated ALL Children with Down syndrome (DS) have a markedly increased risk of developing acute leukemia, including both AML and ALL, with a 20-fold higher risk for ALL than the general pediatric population [38]. A significant advance in our understanding of DS-associated acute leukemia resulted from the demonstration that mutations in GATA1, which encodes a megakaryocyte- and erythroid-specific transcription factor, are present in nearly all cases of transient myeloproliferative disorder and acute megakaryoblastic leukemia (AMKL) occurring in the setting of DS (Fig. 4.2). These mutations result in the expression of a truncated form of GATA1 which is believed to result in dysregulated proliferation of megakaryocytic progenitors, which may in the case of AMKL progress to overt acute leukemia [39]. Cytogenetic analyses have demonstrated distinct differences between DSassociated ALL (DS-ALL) and ALL occurring in children without DS [40]. For example, ALL with the t(9;22) or 11q23 rearrangements are distinctly uncommon in DS-ALL, compared to non-DS-ALL. By contrast, trisomy of chromosome X, del(9p), and the t(8;14)(q11;q32) are significantly more common in DS-ALL. While these cytogenetic findings suggest differences in the pathogenesis of DSALL, the pathogenesis of ALL in children with DS has remained poorly understood until recently. The Janus kinases are protein tyrosine kinases and include three family members, JAK1, JAK2, and JAK3 [41]. The demonstration that mutations in JAK2, primarily the V617F mutation, are detected at a high frequency in several myeloproliferative neoplasms, including polycythemia vera, essential thrombocythemia, and primary myelofibrosis, has spawned considerable investigation into the role of altered JAK signaling in leukemogenesis. The Janus kinases physically associate with the cytoplasmic tails of several cytokine receptors, including those for erythropoietin, IL-3, and GM-CSF, and effect signal transduction upon engagement of the receptor by its cognate ligand through the phosphorylation of critical downstream signaling molecules, including the signal transducer and activator of transcription (STAT) proteins, mitogen-activated protein kinases (MAPK), and phosphatidylinositol-3kinase (PI3K) signaling pathways. In contrast to wild-type JAK2, which is activated only upon ligand binding, the V617F mutation endows JAK2 with constitutive signaling activity [42]. Although there were scattered isolated reports describing mutations or translocations targeting JAK2, the first definitive evidence for a broader pathogenetic role of perturbed JAK signaling in DS-ALL came from the identification of JAK2 mutations in approximately 20% of analyzed cases of DS-ALL, nearly all of which were

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Fig. 4.2 Pathogenesis of Down syndrome-associated acute leukemia. DS is associated with significantly increased risk for the development of acute leukemia including both AML, particularly AMKL, and ALL. A critical early genetic lesion in the evolution of DS-associated megakaryocytic disorders is acquisition of mutations in GATA1 (top portion of figure), which is thought to result in dysregulated proliferation in megakaryocyte lineage-committed hematopoietic progenitors. GATA1 mutations are detected in nearly all TMDs; progression to overt AMKL presumably reflects the acquisition of additional cooperating mutations (indicated by an asterisk), the identity of which are largely unknown. Recent studies implicate aberrant overexpression of CRLF2 in the pathogenesis of DS-associated ALL (bottom portion of figure). Together with IL7-Rα, CRLF2 forms a high-affinity receptor for the cytokine thymic stromal lymphopoietin (TSLP). The mechanism by which CRLF2 overexpression contributes to leukemogenesis is presently unknown. However, acquisition of mutations in tyrosine kinases, such as the JAK R683 mutant which possesses constitutive kinase activity, appears to cooperate with CRLF2 to induce ALL. In both DS-associated ALL and AMKL, the identity of those genes on chromosome 21 which cooperate with these mutations is currently unknown

heterozygous [43]. In contrast to the V617F mutation characteristic of myeloproliferative neoplasms, the JAK2 mutations identified in DS-ALL primarily targeted a conserved arginine residue at position 683 (R683). Subsequent analyses by other investigators have similarly detected JAK2 R683 mutations in 18–28% of DS-ALL cases [44, 45]. Similar to the V617F, transduction of JAK2 R683 mutants into cytokine-dependent cell lines conferred cytokine-independent growth and activated downstream signaling pathways [43, 44]. Like V617, the R683 residue is located within the pseudokinase domain of JAK2. Molecular modeling predicts that R683 is located within the very highly conserved binding pocket of the JAK2 pseudokinase

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domain [43]; thus, this mutation may alter the substrate binding of JAK2. The fact that the mutations targeting V617 and R683 are thought to be on different surfaces of the pseudokinase domain may account for the distinct disease associations observed with each of these JAK2 mutations. The JAK2 R683 mutation does not appear to have any significant prognostic impact [43, 45]. Deregulated expression of cytokine receptor-like factor 2, or CRLF2, has very recently been implicated in the pathogenesis of DS-ALL [46, 47]. CRLF2 is expressed by early B- and T-cell progenitors, mast cells, and dendritic cells [48]. Together with the IL-7 receptor α chain, CRLF2 forms a high-affinity, heterodimeric receptor for thymic stromal-derived lymphopoietin (TSLP), a cytokine that shares homology with IL-7 [49, 50]. As suggested by its name, TSLP is primarily expressed by epithelial cells, keratinocytes, and stromal cells [51, 52]. It potently activates dendritic cells and plays a critical role in the regulation of inflammatory and allergic responses, although it appears to be dispensable for B-cell development [53–58]. The CRLF2 gene resides within a pseudoautosomal region, PAR1, of the X and Y sex chromosomes [59]. Dysregulation of CRLF2 expression has been demonstrated in both pediatric and adult B-ALL. This may occur secondary to a chromosomal translocation involving 14q32, either the t(X;14)(p22;q32) or the t(Y;14)(p11;q32), bringing CRLF2 into close juxtaposition with the immunoglobulin heavy chain enhancer, resulting in its overexpression [46]. Alternatively, an interstitial deletion within PAR1, either del(X)(p22.33p22.33) or del(Y)(p11.32p11.32), juxtaposes the P2RY8 and CRLF2 genes, yielding an in-frame fusion of a noncoding exon of P2RY8 to the entire coding region of CRLF2, resulting in dysregulated expression of CRLF2 driven by P2RY8 promoter elements [47]. The PAR1 deletion appears to be more common in pediatric ALL, whereas both genomic rearrangements are detected with comparable frequency in adult ALL. Notably, the deletion is frequently present in 42–53% of DS with ALL, in contrast to typical pediatric ALL in which a PAR1 deletion is detected in only 2–3% of cases [47]. Furthermore, mutations in JAK2 are present in approximately 45% of cases with alterations affecting CRLF2. These include primarily the R683 mutations discussed above, but also JAK2 kinase domain mutations and rarely JAK1 pseudokinase domain mutations. In vitro analyses confirmed constitutive JAK2 signaling in cells harboring these mutations. Importantly, cell lines overexpressing CRLF2 together with a constitutively active JAK2 R683 mutant manifest cytokine-independent growth in vitro. While the underlying leukemogenic mechanism is as yet unknown, it is likely that CRLF2 overexpression plays an important role in DS-ALL pathogenesis, given that these cases generally lack the genetic lesions characteristic of typical pediatric ALL, including the t(12;21), t(1;19), t(9;22), and translocations targeting MLL as well as the typical numerical chromosomal abnormalities, e.g., high hyperdiploidy, hypodiploidy [47]. Although not restricted to DS-ALL, the detection of genomic alterations resulting in dysregulated CRLF2 expression in nearly half of DS-ALL cases suggests that the oncogenic potential of CRLF2 is enhanced or influenced by a coexisting trisomy 21. Interestingly, in both DS-associated AMKL and ALL, the identified recurrent genetic lesions target genes (GATA1 and CRLF2, respectively) do not reside on chromosome 21. This suggests that in the context of DS, leukemogenesis

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requires cooperation between the aberrant signaling induced by these mutations and the altered expression of an as yet unidentified gene residing in the DS critical region which has been mapped to chromosome 21q22 [60, 61].

Genetic Factors Predisposing to Precursor Lymphoblastic Leukemia/Lymphoma While several genetic disorders are well known to predispose to lymphoblastic leukemia, including Down syndrome, Bloom syndrome, neurofibromatosis, and ataxia telangiectasia [62–66], patients with these disorders collectively account for fewer than 5% of cases of ALL. Consequently, the existence and identity of predisposing genetic factors in the preponderance of patients with ALL remains largely undefined. The analysis of twins to gain insight into whether there exists a genetic propensity for the development of ALL is complicated by the fact that a significant subset of pediatric ALLs develops in utero with the attendant risk for transplacental leukemic “metastasis” [67]. Recent whole-genome association analyses have provided some initial insights [68, 69]. Using high-density singlenucleotide polymorphism (SNP)-based analysis, several germline polymorphisms have been identified which appear to confer an increased risk for the development of ALL. In two independent studies, SNPs located on chromosome 7p12.2 and mapping to or near the IKZF1 locus were the most strongly associated with risk for ALL. Both groups also identified SNPs mapping to the ARID5B gene (AT-rich interactive domain 5B). Interestingly, both studies found associations between certain SNPs and specific ALL subtypes. For example, ARID5B polymorphisms were specifically associated with hyperdiploid B-ALL, whereas another SNP mapping to ORC2C3 was associated with ETV6-RUNX1+ B-ALLs [69]. In addition, population studies indicate increased risk for ALL development in children harboring polymorphisms in gene products involved in DNA mismatch repair, P-glycoprotein-mediated drug efflux, and folate metabolism [70–72]. As with most SNP disease association studies of this type, the underlying mechanisms by which the identified alleles actually predispose to ALL leukemogenesis are incompletely understood. Collectively, however, these data indicate that the in utero and childhood development of ALL is likely multifactorial and in a subset of patients may be attributable to inherited abnormalities that directly predispose to leukemia due to dysregulated lymphoid progenitor development and proliferation as well as genetic lesions that indirectly contribute to leukemogenesis through altered xenobiotic and micronutrient metabolism.

Cancer Stem Cells in Precursor B-ALL: Definitions and Controversies It is now well accepted that pluripotent stem cells exist in virtually all normal tissues. Such stem cells possess two essential biologic properties, namely a capacity

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for self-renewal and the ability to generate differentiated progeny. With recognition of the existence of stem cells in normal tissues, considerable effort in recent years has focused on determination of whether a similar hierarchy of differentiation exists within tumors and specifically whether a pluripotent cell analogous to the aforementioned normal tissue stem cells, the so-called cancer stem cell (CSC), likewise exists. Our current concept of a CSC derives from the pioneering work of John Dick and colleagues who first showed that the capacity to generate disease upon transfer to immunocompromised NOD/SCID murine recipients was largely restricted to cells present in the CD34+ CD38– fraction of human AMLs [73, 74]. Subsequent analysis of a wide array of tumors typically coupled with sophisticated cell-sorting approaches has revealed that within a given cancer, individual tumor cells vary considerably in their capacity to subsequently give rise to tumors when, for example, transplanted to immunocompromised murine recipients [75]. Thus, CSCs appear to be present in many, if not all, types of malignancies. Like its normal counterpart, a CSC is defined by its possession of self-renewal properties as well as the capacity to generate more differentiated cellular progeny. In addition, CSCs are quiescent and are thought to express high levels of several drug transporters, which would render them relatively resistant to chemotherapy, similar to their benign counterparts [76]. Given this, it is presently thought that our failure to eradicate many human malignancies with currently available chemotherapeutics is attributable, at least in part, to this relative intrinsic resistance of CSCs to chemotherapy when compared to their more differentiated tumor cell progeny. Thus, it is hoped that enhanced understanding of cancer stem cell biology will facilitate the development of more effective therapeutic approaches that specifically target CSCs. Before turning to leukemia stem cells (LSCs), a few salient comments regarding the analysis of stem cells are in order. Given the intrinsic properties of stem cell biology, analysis of any candidate CSC population requires ultimately a biologic readout, most stringently one in which the properties of the putative CSC population are assessed in vivo. For example, transplantation of tumor cell populations into immunodeficient murine recipients is a commonly used technique to assay for CSCs. However, several factors can impact quantitatively and qualitatively on the outcome of in vivo analyses of CSCs, including differences in how the recipient mice are manipulated prior to transplantation (e.g., irradiation, other “conditioning” regimens), the route by which experimental cells are actually administered to recipient animals (e.g., subcutaneous injection versus intravenous injection versus intramedullary injection in the case of LSCs), and whether experimental cells are administered alone or together with normal “carrier” cells. Thus, it is important to be cognizant of not only the inherent variability of any biologic assay but also the fact that subtle technical differences among these techniques have the potential to impact significantly on the experimental readout. In addition to these variables related to experimental technique, it is helpful to remember that while they share some biologic properties with normal stem cells

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by definition, CSCs are neoplastic, and their biologic behavior may differ significantly in other regards from that of their benign counterparts. For example, a leukemia-initiating genetic lesion (e.g., a chromosomal translocation resulting in expression of a fusion oncoprotein) may in fact occur in a more differentiated or lineage-committed cell type, and it could impart “stemness” to this otherwise differentiated cell by altered gene expression or epigenetic events resulting directly from the initial leukemogenic mutation. In addition, the degree to which a CSC niche is recapitulated in recipient animals used in transplant assays has significant potential to influence findings. If such niches are not present due to deficient cytokine signaling or lack of stromal interactions (including both inappropriate expression of critical molecules and attenuated or absent molecular interaction across species), then the “stemness” of a candidate cell population would not be detected. Finally, xenotransplantation may select for a small subset of cancer cells that can surmount the biologic obstacles posed by these assays, thus artificially imparting a “stemness” to a cell population that does not actually exist in a human host, an interpretation for which supporting experimental data exist [77]. The nuances and variables of assessing the biologic properties of putative CSCs have recently been addressed [78, 79]. Let us now turn to LSCs. Since the characterization of CD34+ /CD38− LSCs in AML by Dick and colleagues [73], considerable work has been undertaken to identify and characterize LSCs in ALL [80]. In these studies, the isolation of various leukemic blast populations has exploited the differential and temporally regulated expression of several cell surface antigens during the various stages of normal B-cell ontogeny (Fig. 4.3). It should also be noted that leukemic blasts coexpress CD34 and CD38 in more than 95% of cases of B-ALL [81]. While several studies clearly indicate that acquisition of the primary leukemogenic mutation occurs within a progenitor cell, studies published to date have yielded conflicting findings. For example, some FISH analyses of sorted cell populations from patients with t(12;21) B-ALL have failed to identify this translocation in the CD34+ CD19− cell fraction, which presumably contains normal totipotent HSCs [82, 83]. However, other investigators have shown that only cells within either the CD34+ CD19− or the CD34+ CD10− fraction, and not CD34+ cells coexpressing CD19 or CD10, could generate leukemia in NOD/SCID recipient animals, suggesting that the t(12;21) is acquired in a cell more immature than a committed B-cell progenitor. The picture is also somewhat muddled with regard to Ph+ ALL. Recent analyses of Ph+ ALL suggest that the t(9;22) occurs in a committed B-cell progenitor [82, 84]. However, the exact phenotype of this progenitor is uncertain as contradictory findings have been published. Hotfilder et al. demonstrated that the t(9;22) was detectable by FISH in approximately 50% of flow-sorted CD34+ CD10− cells versus over 90% of CD34+ CD19+ cells [84]. By contrast, Castor et al. found that the t(9;22) was present in CD34+ CD38− CD19− cells only in cases expressing the p210 BCR−ABL1 isoform but not those expressing p190 [82]. Despite these differences, progenitors containing the t(9;22) manifested essentially no capacity for myeloid/erythroid differentiation when assayed either in vitro or in vivo. These

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Fig. 4.3 Temporal acquisition of cell surface protein expression during B-cell ontogeny. The development and maturation of human B cells is characterized by the tightly regulated expression of several cell surface markers. As indicated, the expression of certain markers is evanescent, e.g., CD34, whereas other cell surface proteins such as CD19 are expressed throughout much of B-cell ontogeny at a relatively uniform level. This temporally regulated marker expression has been exploited to define the indicated stages of B-cell maturation. It should be pointed out that leukemic B lymphoblasts not infrequently manifest patterns or levels of antigen expression that deviate from those of normal B-cell progenitors

results appear to contradict the findings of older studies of BCR–ABL+ ALLs with p190 expression where the t(9;22) was detected in normal hematopoietic lineages in addition to the leukemic blasts, suggesting its presence in a multipotential HSC compartment [81, 85]. A recent study from Vormoor et al. further confounds the picture [86]. These investigators fractionated leukemic bone marrow samples into CD34+ CD19– , CD34+ CD19+ , and CD34− CD19+ populations and surprisingly found significant leukemic engraftment in NOD/SCID recipients for all three cell fractions. Furthermore, they showed that transplant of CD19+ cells coexpressing CD20, a marker expressed relatively late in normal B-cell ontogeny (Fig. 4.3), could likewise yield leukemic engraftment in recipient mice. The basis for these seemingly contradictory results is uncertain at present, but may be attributable to subtle differences between the experimental approaches used by these investigators. For example, Vormoor et al. [86] used intrafemoral injection of their stem cell preparations, whereas the other studies employed intravenous injection. Technical differences in the cell-sorting strategies employed as well as the utilization of different cell surface marker combinations may also be confounding these analyses. With few exceptions, most of the studies indicate that there are significant differences in the capacity of various sorted ALL to generate leukemia in recipient immunodeficient mice, indicative of the existence of LSCs in B-ALL. However, the apparently contradictory findings of some studies highlight the need for a standardized approach to the isolation and analysis of LSCs.

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Altered NOTCH Signaling in T-ALL NOTCH1 encodes a heterodimeric receptor that critically regulates cell fate decisions by multipotent progenitors during development. As such, NOTCH1 plays an important role in regulating proliferation, apoptosis, and differentiation in these cells. Within the hematopoietic system, NOTCH1 critically influences the generation of T-cells at multiple steps in their ontogeny [87, 88]. The commitment of hematopoietic progenitors to the T-cell lineage is dependent on NOTCH1 signaling. Loss of NOTCH1 within hematopoietic cells results in a block in T-cell development at an early CD4/CD8 double-negative stage and the aberrant development of B-cells within the thymus. NOTCH1 signaling also regulates subsequent stages of T-cell development including transition of thymocytes from CD4/CD8 double-negative to double-positive cells, as well as influencing the choice between αβ and γδ T-cell differentiation. NOTCH signaling is rather complex, due in part to the existence of multiple ligands [including Delta-like (DLL) 1, 3, and 4 as well as Jagged 1 and 2] as well as multiple NOTCH receptors (NOTCH1, 2, 3, and 4) [87]; for the sake of brevity and relevance, our discussion will be limited to NOTCH1. Both NOTCH1 and DLLs are type I transmembrane proteins. The mature NOTCH1 receptor is generated by cleavage of the nascent NOTCH1 protein by a furin-like protein, forming a heterodimer receptor complex comprised of an extracellular component and a transmembrane/intracellular subunit. Upon binding ligand, the latter undergoes proteolytic cleavage mediated in part by γ-secretase with release of ICN, the intracellular portion of NOTCH1. ICN then translocates to the nucleus where it forms a multimeric transcription complex with several other cofactors, including the DNA-binding protein CSL, to induce the expression of NOTCH1 target genes [89]. The first indication of a role for NOTCH1 in T-ALL leukemogenesis came from the observation that NOTCH1 was the chromosomal target of the t(7;9)(q34;q34.3) [90]. Given the rarity of this translocation, which is detected in less than 1% of cases, the broader pathogenetic relevance of altered NOTCH1 signaling in T-ALL was not appreciated until recently when mutations in NOTCH1 were demonstrated in approximately 60% of cases [91–93]. These mutations target the extracellular heterodimerization domain (HD) and the C-terminal inhibitory PEST domain of NOTCH1. The HD mutations induce NOTCH1 cleavage independent of its binding to extracellular ligand, whereas mutations in the PEST domain inhibit the proteasomal degradation of ICN1. Thus, both types of mutations result in the amplification or aberrant activation of NOTCH1 signaling and expression of critical downstream targets, such as HES1 and MYC, resulting in leukemic development (Fig. 4.4) [94–97]. The leukemogenic effect of perturbed NOTCH1 signaling appears to be restricted to T-cell progenitors, as NOTCH1 mutations have not been reported in B-ALL. With the identification of NOTCH1 mutations in the majority of T-ALLs, there has been considerable interest in exploiting the resulting aberrant NOTCH1 signaling for therapeutic purposes. An obvious candidate is γ-secretase, an enzyme required for NOTCH1 proteolysis. γ-secretase inhibitors (GSIs) were readily available, as they had been developed and used therapeutically for Alzheimer

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Fig. 4.4 Role of aberrant NOTCH1 and PI3K/AKT signaling in T-cell ALL. Upon ligand binding, NOTCH1 undergoes two proteolytic cleavages, the latter catalyzed by γ-secretase. This releases the intracellular portion (ICN) which then translocates to the nucleus where it forms multimeric complexes with CSL and other transcriptional coactivators on the promoters of NOTCH-responsive genes resulting in their transcriptional activation (upper left). Mutations in NOTCH1 are among the commonest in T-ALL and result in constitutive NOTCH1 signaling which directly and indirectly through PI3K/AKT enhances cell growth and survival. The γ-secretase inhibitors (GSIs) block the proteolytic processing of NOTCH1, thereby inhibiting NOTCH signaling (upper right). However, resistance to GSIs is present in a significant subset of T-ALL cases at diagnosis and relapse (lower left). Recent studies indicate that this resistance is due to deletion of PTEN, an indirect NOTCH1 transcriptional target and central regulator of PI3K/AKT signaling. This loss of PTEN expression in leukemic T lymphoblasts results in a shift from their dependency on aberrant NOTCH1 signaling to dysregulated PI3K/AKT activity, resulting in continued leukemic proliferation even in the face of GSI therapy (lower right). Modified from [114]

disease, where they function to block synthesis of amyloidogenic β-amyloid peptides. Unfortunately, despite their apparent efficacy in inhibiting the growth of cell lines in vitro, clinical trials with GSIs have been disappointing due to a modest antileukemic effect and significant toxicity in vivo. Given their potent lymphotoxicity, corticosteroids are a key component of most multiagent chemotherapeutic regimens for ALL. Interestingly, recent studies indicate that GSIs and corticosteroids may act synergistically to exert a more significant anti-leukemic effect by restoring corticosteroid sensitivity in resistant cell lines [98]. In addition, glucocorticoids may block the goblet cell metaplasia and intestinal toxicity resulting from the GSI-induced inhibition of NOTCH1 signaling. While these findings clearly need to be confirmed

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in primary leukemic samples and in preclinical models, they suggest that GSIs may exert clinically meaningful anti-leukemic effect when administered as a component of combination chemotherapy. More recently, mutations have also been detected in FBXW7, an E3 ligase that ubiquitinates NOTCH1 as well as MYC, targeting them for proteasomal degradation, and thereby acting as a negative regulator of NOTCH1 signaling [28]. Mutations in FBXW7 have been detected in 11–24% of adult and pediatric T-ALL/LBL [28, 91, 99, 100]. The prognostic significance of mutations that impact on NOTCH1-mediated signaling, including FBXW7 mutations, is currently unresolved as some studies have shown that such mutations confer a good prognosis [91, 101, 102], whereas others have shown that NOTCH signaling pathway mutations lack prognostic significance or even negatively impact on prognosis [100, 103]. The basis for these discrepant findings is currently uncertain, but is presumably attributable to differences in therapy.

Role of PTEN and PI3K in Pathogenesis of T-ALL PTEN (phosphatase and tensin analog) negatively regulates the phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathway. Upon activation of PI3K by extracellular stimuli, phosphatidylinositol-3, 4, 5 trisphosphate (PIP3) is generated which then recruits AKT, a serine–threonine kinase, to the plasma membrane where it subsequently undergoes phosphorylation-dependent activation, effected by 3-phosphoinositide-dependent kinase-1. AKT then phosphorylates several key downstream molecules, including TSC2, MDM2, and FOXO, which enhance cell growth, survival, and proliferation [104]. Through its dephosphorylation of PIP3 to phosphatidylinositol-4,5 bisphosphate (PIP2), PTEN functions as a central, critical negative regulator of PI3K signaling. NOTCH1 represses PTEN expression in both normal thymocytes and T-ALL cells [105]. This effect is mediated indirectly through the induction of HES1 (hairy and enhancer-of-split analog-1). Thus, the abrogation of NOTCH1 signaling by GSIs blocks HES1 expression, resulting in the upregulation of PTEN expression and consequently inhibition of PI3K-AKT signaling (Fig. 4.4). As alluded to above, GSIs have only a modest anti-leukemic effect in vivo, presumably due at least in part to acquisition of resistance. In support of this notion, GSI-resistant T-ALL cell lines but not GSI-sensitive ones harbor homozygous deletions or biallelic mutations in PTEN, resulting in complete loss or marked down regulation of PTEN expression [105]. PTEN mutations have likewise been detected in primary T-ALL leukemic samples at initial diagnosis in 6–9% of cases [105–107]. Loss of PTEN in GSIresistant cells is accompanied by markedly increased levels of phosphorylated AKT, indicating constitutive activation of the PI3K-AKT signaling pathway [105]. Hyperactivation of PI3K-AKT signaling appears to play a critical oncogenic role in GSI-resistant T-ALL cells, since an AKT inhibitor markedly inhibited their growth and viability, but not that of GSI-sensitive cells. Thus, acquisition of PTEN mutations obviates the need for ongoing NOTCH1 signaling, inducing instead a

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critical need, or “oncogene addiction” for constitutive PI3K-AKT signaling. A more recent analysis using array-based comparative genomic hybridization similarly showed that DNA gains or deletions encompassing genes encoding activators [e.g., MAP kinase interacting serine/threonine kinase 2, insulin-like growth factor 2 (IGF2), IGF2 receptor), and inhibitors (PTEN, FOXO3A) of PI3K-AKT signaling are present in approximately 30% of pediatric T-ALL cases, indicating that perturbations of this signaling pathway have an important pathogenetic role in T-ALL [107]. An obvious and important implication of these studies is that effective therapy for T-ALL likely requires inhibition of both the NOTCH1 and the PI3K-AKT signaling pathways. Inhibitors targeting various components of PI3K-AKT signaling are currently under development and preclinical evaluation [108, 109]. mTOR (mammalian target of rapamycin) is an important downstream target of PI3K-AKT. Several recent studies indicate that inhibition of multiple downstream signaling targets of NOTCH1 and PI3K-AKT, including mTOR, may work synergistically to induce cell cycle arrest and apoptosis in T-cell lymphoblasts in in vitro and in vivo murine models [110–112].

Integration of Whole-Genome Analyses with Other Analytic Approaches to Identify Novel ALL Subtypes The integration of high-throughput methodologies, detailed knowledge of the biology of lymphoid precursors, and traditional immunophenotypic analytical methods holds promise for defining novel, clinically relevant subtypes of precursor lymphoid malignancies. A recent analysis of T-ALL has demonstrated the power of such an approach. Early T-cell precursors (ETPs) represent a small minority of thymocytes which have recently emigrated from the bone marrow to the thymus and have been well characterized immunophenotypically. Through the analysis of T-ALLs to detect those cases which have a gene expression profile most closely resembling that of normal ETPs, Campana et al. were able to identify a distinctive subset of T-ALLs [113]. In addition to having a cell surface immunophenotype, similar to that of normal ETPs, this subset of T-ALLs manifests increased genomic instability. Clinically, children with ETP-like T-ALL tend to be younger, respond more poorly to induction chemotherapy with frequently detectable minimal residual disease, and most importantly have a higher rate of hematologic relapse than typical T-ALL patients. This study demonstrates the power of integrating different analytical approaches to define novel ALL subsets which may possibly share a common molecular pathogenesis. Importantly, such approaches may permit the prospective identification of patients who would benefit from more intensive chemotherapy or molecularly targeted therapeutics.

Conclusion During the past four decades, tremendous progress has been made in elucidating the pathogenetic mechanisms underlying precursor ALL/LBL and in the development

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of improved therapeutics for these malignancies, which has resulted in marked improvement in clinical outcome and survival, particularly in the pediatric population. However, the prognosis of adults with ALL/LBL remains poor, and while effective in children, the currently available therapies are highly toxic with many significant and long-lasting side effects. Improvements in the therapy for the precursor lymphoblastic malignancies and in the survival of patients afflicted by them will undoubtedly be predicated on continued advances in our understanding of their molecular pathogenesis, a goal that should be attainable with the ongoing application of whole-genome analytic techniques to the investigation of these malignancies and the development of molecularly targeted therapeutics.

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Chapter 5

Molecular Pathology of Acute Myeloid Leukemias Karen P. Mann and Debra F. Saxe

Keywords AML · Acute myeloid leukemia · APL · Acute promyelocytic leukemia · Myeloid · RQ-PCR · RT-PCR · PCR · Capillary electrophoresis · Electropherogram · Sequencing · DNA · RNA · Translocation · Point mutation · Insertions · Deletions · Gene expression · Prognosis · FLT3 · NPM1 · PML · RARA · RUNX1 · RUNXT1 · MYH11 · CBFB · MLL · Double fusion probe · Breakapart probe · Chromosome enumeration probe · FISH · WT1 · CEBPA · ERG · BAALC · Myelodysplasia · Myelodysplastic syndrome · Myeloproliferative neoplasm · BCR-ABL1 · JAK2 · MPL · Exon · Intron · Breakpoints · Primers · MRD · Minimal residual disease · WHO classification · Karyotyping · Allele-specific PCR · Melt-curve · AML with recurrent genetic abnormalities · AML with balanced translocations · AML with gene mutations · inv(16) · t(16;16) · t(8;21) · t(15;17) · t(5;17) · t(11;17) · PML– RARA · RUNXI-RUNXITI · CBFB-MYH11 · MLL-X · MLL-PTD · Partial tandem duplication · NRMI · NUMA · PLZF · PLZF-RARA · NPM1-RARA · NUMA-RARA · ATRA · Core binding factor AML · CBF-AML · KIT · RUNX2 · RUNX1 · class I · class II · Fusion protein · ETO · MLLT3-MLL1 · t(9;11) · Pediatric AML · Prognosis · AF9 · AF10 · ELL · AF6 · ENL · AF17 · SEPT6 · AML-MDS · AML with myelodysplasia-related changes · Therapy-related AML · t(6;9) · DEKNUP214I · inv(3) · t(3;3) · RPN1-EVI1 · t(1;22) · RBM15-MKL1 · AML with mutated NPM1 · AML with mutated CEBPA · NK-AML · Normal karyotype AML · FLT3-LM · FLT3-TKD · D835 · CCAAT/enhancer-binding protein alpha · Chromosome 5 · Chromosome 7 · 5q- · 7q- · Monosomy · CTNNAI · RPS14 · DIAPH1 · Egr1/Krox20 · Alpha-catenin · MLL5 · APS · CUTL1 · 7q22 · D7S486 · D7S498 · D7S505 · 7q31-4 · t(5;11) · t(2;11) · t(11;16) · Tyrosine kinase · Allelic ratio · Wilms tumor 1 · Homozygous · Heterozygous

K.P. Mann (B) Department of Pathology and Laboratory Medicine, Emory University, F143c Emory University Hospital, 1364 Clifton Rd NE, Atlanta, GA 30322, USA e-mail: [email protected]

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_5, 

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Introduction Acute myeloid leukemia (AML) is a family of hematopoietic neoplasms characterized by proliferation of myeloid-lineage blast cells in the bone marrow, peripheral blood, and/or extramedullary sites. Appropriate classification and subclassification of these neoplasms is necessary to ensure appropriate therapy. This classification is increasingly based upon the underlying genetic abnormalities of these diseases, and evaluation for these abnormalities has become standard of care in the diagnosis and treatment of acute leukemias. The current WHO classification incorporates a combination of clinical features, morphologic features, immunophenotype, karyotype, and molecular testing to precisely subclassify these diseases [1]. This is considered a work in progress, and, as more abnormalities are identified, they will be incorporated into novel diagnostic and prognostic subgroups. In addition, at least some of these mutations are being incorporated into minimal residual disease testing and some are targeted for directed therapy. A variety of types of mutations have been described requiring a variety of diagnostic modalities. These include balanced translocations [e.g., t(15;17)(q22;q21)], insertions (e.g., NPM1), deletions [e.g., del(5q)], point mutations (e.g., FLT 3D835), and duplications (e.g., MLL-PTD). Some of these mutations define specific subtypes of disease, whereas others provide prognostic information and/or guide therapy. A variety of detection techniques can be used, depending on the specific abnormalities. This may include FISH and conventional karyotyping, sequencing, PCR, RT-PCR, and RQ-PCR, each of which has unique advantages and disadvantages. Conventional karyotyping provides broad overview of all of the patient’s abnormalities. It will not, however, detect small abnormalities (<3–5 Mb) or masked translocations and has low analytic sensitivity as typically only 20 cells are evaluated. FISH increases the sensitivity by approximately 10-fold and is excellent at detecting masked translocations that are not picked up by chromosome analysis. Since the probes cover large areas of DNA (100 kb–1.5 Mb), polymorphisms or mutations do not interfere with their ability to bind. In addition, FISH excels in situations where a given gene has multiple translocation partners (e.g., MLL). Using proper probe design, one can demonstrate that a given gene has been involved in a translocation without needing probes for every possible gene partner. Many laboratories have devised specific FISH probes panels in addition to standard karyotyping to identify recurring prognostic cytogenetic abnormalities in AML. These panels may vary among laboratories but most often include combinations of the following probes: 5q– /– 5, 7q– /– 7, t(8;21), inv(16), MLL, t(15;17), and t(9;22). Although most of these abnormalities can be detected readily by chromosome analysis, the addition of FISH can resolve complex karyotypes involving rearrangement of the many chromosomes included in the panels and are very informative in preparations with few dividing cells. Once specific abnormalities have been identified by FISH, the patient may then be followed by FISH alone for the appropriate abnormalities. When disease progression is suspected, the entire panel and standard cytogenetics are warranted to look for additional abnormalities.

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Amplification-based techniques (PCR, RT-PCR, and RQ-PCR) have the highest analytic sensitivity and can be used both at diagnosis and for minimal residual disease (MRD) testing. Point mutations can be detected by sequencing (considered the gold standard), but can also be identified by allele-specific PCR, PCR with meltcurve analysis, and in specific cases PCR followed by restriction enzyme digestion and fragment analysis. In this chapter, we will review the molecular abnormalities in AML with a focus upon those that are considered standard of care in diagnosis, treatment monitoring, and MRD assessment. In addition, we will describe the testing modalities used to demonstrate the abnormalities, discuss the appropriate utilization of these tests, and describe the pros and cons of specific types of testing. A brief review of future diagnostic possibilities will also be discussed.

Acute Myeloid Leukemia AML is divided into subcategories based in large part upon underlying genetic abnormalities (Table 5.1) [1]. Many of these abnormalities are balanced translocations which were originally identified by conventional karyotyping. Subsequently, FISH and PCR techniques have been developed to detect the more common of these. Detection of these abnormalities has become standard of care in treatment of patients with AML. In addition, mutations with significant prognostic implications have been and are being identified (Table 5.1). Their usage is increasing as diagnostic tests and targeted therapies are developed. In specific settings, minimal residual disease testing is becoming increasingly used as well to monitor response to therapy and detect early relapse.

Table 5.1 AML-associated mutations AML with recurrent genetic abnormalities

Balanced translocations

Gene mutations Other significant gene mutations in AML

t(8;21)(q22;q22); RUNX1-RUNX1T1 inv(16)(p13.1q22) or t(16;16)(p13;q22); CBFB-MYH11 t(15;17)(q22;q12); (PML–RARA) t(9;11)(q22;q23); MLLT3-MLL t(6;9)(p23;q34); DEK-NUP214 inv(3)(q21q26.2); RPN1-EVI1 t(1;22)(p13;q13); RBM15-MKL1 Mutated NPM1 (provisional entity) Mutated CEBPA (provisional entity) FLT3-ITD FLT3-D835 KIT exon 8 or 17 mutations WT1 MLL translocations [other than t(9;11)] MLL partial tandem duplications

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AML with Recurrent Genetic Abnormalities AML with Balanced Translocations/Inversions Acute Promyelocytic Leukemia with t(15;17)(q22;q21); PML–RARA (APL) Demonstration of the t(15;17)(q22;q21) PML–RARA, or more rarely one of several alternative translocations (X-RARA), is required for diagnosis of APL [1, 2]. The translocation results in creation of a fusion protein involving the two genes: PML on chromosome 15q22 and RARA on chromosome 17q21 [3]. The PML protein product is believed to be involved in a number of cellular functions including apoptosis, tumor suppression, and senescence [4]. The retinoic acid receptor alpha is a ligand-dependent nuclear receptor which controls expression of genes involved in hematopoietic differentiation and growth [3]. The PML–RARA fusion gene joins the nuclear localization signal and dimerization domains of the PML gene to the DNA-binding and ligand-binding domains of RARA [3, 4]. Detection of the PML–RARA translocation can be performed using conventional karyotyping, FISH, RT-PCR, or RQ-PCR each of which has advantages and disadvantages as described above. Since patients with APL have a high risk of disseminated intravascular coagulopathy, rapid diagnosis followed by institution of specific therapy [all-trans retinoic acid (ATRA) along with cytotoxic chemotherapy] is essential. In order to assess response to therapy and likelihood of relapse, RT-PCR testing is routinely performed [2, 5, 6]. FISH probes are commercially available to detect this translocation. The two most common strategies are dual color, dual fusion probes to detect PML/RARA, and breakapart probe directed at RARA (Fig. 5.1). In the dual fusion probe design each gene is labeled with a different fluorochrome, typically spectrum orange and spectrum green, each of which spans the breakpoint of the respective genes. When the t(15;17) occurs, the distal portion of each gene is translocated to the other chromosome (Fig. 5.1b). The two translocated chromosomes then each contain a fusion signal (yellow) consisting of half a red and half a green signal. The normal homologs appear as single red and green signals (2F1R1G). Normal cells contain two red and two green signals (2R2G) (Fig. 5.1a). This strategy will also identify t(15;17) variants such as complex 3-way translocations. Alternatively, the RARA breakapart probe set spans the gene with the distal portion or 3’ end in one color and the proximal region or 5’ end in another color (fusion/yellow, F). If there is a translocation involving RARA, the break occurs between the two colors, separating the red and green signals (Fig. 5.1d). A translocation in RARA appears as one fusion signal, one red signal, and one green signal (1F1R1G). This probe demonstrates that a rearrangement in the RARA gene has occurred, but does not designate the partner chromosome. RARA rearrangements with PML and rare related genes such as NRMI (5q32), NUMA (11q13), PLZF (11q23), and others all show the same breakapart pattern, 1F1R1G. The presence of the fusion transcript can also be demonstrated by RT-PCR or RQ-PCR. Although the breakpoint in the RARA gene consistently occurs in intron 2, there are three distinct breakpoints in the PML gene, bcr1 (50–60%), bcr2 (5%),

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Fig. 5.1 Sample FISH results from patient with APL. Interphase cells hybridized with PML/RARA dual color, dual fusion probe set, with normal cells showing 2R2G (a) and t(15;17) cells showing 2F1R1G signal patterns (b). Interphase cells hybridized with RARA breakapart probe set, with normal cells showing 2F (b) and t(?;17) cells showing 1F1R1G signal patterns (d). Signal patterns shown in (c) and (d) could likewise represent a breakapart probe such as is used for AML with inv(16). In this case, normal pattern would show 2F (d) and the abnormal pattern would show 1F1R1G

and bcr3 (35–45%) resulting in the L (long), V (variable), or S (short forms, respectively) shown in Fig. 5.2 [3, 4, 7]. Therefore, multiple primers that bind to appropriate loci in the PML gene are necessary in order to detect all possible transcripts. Consensus primers and probes for a RQ-PCR assay have been designed by Gabert et al. [8] and validated in a multi-institutional study supported by a Europe against Cancer Program (Fig. 5.3). Many other laboratories have also developed assays, reviewed by Grimwade and Lo Coco [2]. Demonstration of this translocation by RQ-PCR at diagnosis is helpful not only to establish the diagnosis (which may also be established by FISH or cytogenetics) but also to ensure that the primer sets work for the individual patients for minimal residual disease testing. In addition, it allows determination of the change in disease burden with treatment for minimal residual disease testing. In addition to the common translocation above, alternative rearrangements have been described including t(11;17)(q23q21) PLZF-RARA, t(5;17)(q32;q21)

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Fig. 5.2 Exon–intron structure of PML (yellow boxes) and RARA (blue boxes). Breakpoints are indicated by arrows. Three alternative fusion products are shown (L, V, and S)

Fig. 5.3 RQ-PCR results from two samples from patients with APL with different levels of fusion transcript burden (PML–RARA). Primers based upon Gabert et al. (8). Results are compared to the reference gene ABL

NPM1-RARA, t(11;17)(q13q21) NUMA-RARA, and others [1–3, 6]. Although rare, they are clinically significant as APL with t(11;17)(q23;q21) does not respond to ATRA, whereas APL with t(5;17)(q32;q21) or t(11;17)(q13q21) do [6, 9, 10]. Detection of these alternative translocations is typically performed by conventional karyotyping, although they will be detected by both RARA breakapart probes and some FISH probes designed primarily to detect the PML–RARA fusion. If appropriately designed, the double fusion probe can demonstrate that an alternative translocation involving RARA occurred even though it will not detect the specific fusion partner. In these cases, instead of showing the typical double fusion pattern seen in Fig. 5.1b, an extra RARA signal will be seen (2R3G PML/RARA). RT-PCR

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or RQ-PCR directed at PML–RARA will not detect the alternative translocations and the majority of clinical laboratories have not validated RT-PCR/RQ-PCR to detect these rare translocations. Molecular minimal residual disease testing has become standard of care in APL. This is typically performed by RT-PCR or RQ-PCR. The persistence of the pml– rara fusion transcript during induction is a well-recognized phenomenon and does not indicate failed therapy [6, 11, 12]. A major therapeutic goal is for the fusion transcript to be undetectable in a bone marrow aspirate sample post-consolidation. Persistence at this time point is associated with an increased rate of relapse [2, 6, 11, 12]. If a patient is in molecular remission post-consolidation and the transcript recurs, this is likewise associated with increased risk of relapse [2, 12]. A recent international consensus document has been published on behalf of European LeukemiaNet [6]. This document reiterates that PCR positivity postinduction should not alter therapy. In addition, they recommend molecular monitoring for PML–RARA every 3 months following consolidation with bone marrow aspirate material as the preferred sample. This monitoring should be continued for 3 years. If transcript returns, they recommend early repeat testing to confirm positivity. In this setting positivity indicates that these patients will relapse if not given additional therapy. Core Binding Factor AML The core binding factor (CBF) AMLs (CBF-AML) are comprised of acute leukemias with recurrent translocations that involve a gene of the CBF complex. They comprise 10–25% of AML [1, 13]. These are so-called good prognosis AML as the majority of patients go into complete remission with standard therapy. The most common of the CBF-AML are AML with t(8;21)(q22;q22) RUNX1[CBFA2]RUNX1T1 [AML t(8;21)] and AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 [AML inv(16)]. Of note, these translocations are not sufficient for development of leukemia. Ongoing studies have identified a variety of complementary mutations all of which involve constitutive activation of protein kinases, reviewed by Mrozek et al. [14]. Mutations in the KIT gene in particular have been described in 12–44% of all CBF-AML [14–19] and at least some groups have shown that these mutations have prognostic significance (see below). The normal CBF complex is composed of alpha and beta subunits which heterodimerize and is involved in transcriptional regulation of a host of genes. RUNX1 is involved in regulation of normal hematopoietic establishment and differentiation, whereas other members of the RUNX family (RUNX2, RUNX3) are involved in transcriptional regulation of other genes [13]. The translocations seen in CBF-AML result in fusion proteins that are believed to act as dominant negative inhibitors of normal transcription. AML with t(8;21)(q22;q22) RUNX1-RUNX1T1 AML t(8;21) is one of the two common CBF-AML. This translocation occurs in 4–12% of adult AML and 12–30% of pediatric AML [1, 20]. It represents 5–15%

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of all AML [1, 13, 21]. This abnormality is considered to be a good prognosis with the majority of patients going into CR with standard therapy. Although AML t(8;21) has typical morphologic and immunophenotypic features, diagnosis requires demonstration of this unique translocation by conventional cytogenetics, FISH, or RQ-PCR. The use of quantitative RQ-PCR for minimal disease testing is becoming standard of care and is described below. A typical FISH strategy is a dual color, dual fusion probe using a strategy similar to that described above for APL (Fig. 5.1a, b). Primers and probes have been developed by a number of groups including the Europe Against Cancer Consortium [8, 22–25]. RUNX1 (also known as AML1 and CBFA2) is a member of the core binding factor complex which includes RUNX1 and RUNX1T1 [20, 21, 26]. RUNX1 contains a runt homology DNA-binding domain that binds to control elements upstream of genes involved in hematopoiesis. Binding is enhanced by heterodimerization with CBFB. Its fusion partner RUNX1T1 [ETO1] has a zinc finger domain as well as Nervy homology regions [20, 21, 26]. It acts to inhibit CEBPB. The fusion gene contains the runt homology (i.e., the DNA binding) domain of RUNX1, but lacks its transactivation domain [26, 27]. This is replaced by almost the entire coding region of RUNX1T1 (Fig. 5.4). The fusion protein acts in a dominant negative fashion suppressing function of the normal CBF complex. Although, AML t(8;21) is generally considered a good prognosis acute leukemia, many patients (30–40%) relapse after completing therapy, and there has been an ongoing attempt to identify additional genetic abnormalities that predict relapse [21, 28]. As mentioned above, a subset of patients with CBF-AML harbor KIT gene mutations [15–18]. KIT is a type 3 tyrosine kinase receptor. The most common mutations have been identified in exons 8 and 17 and include the D816 and other mutations in exon 17 [15–20, 29], exon 8 insertions and deletions, and less commonly internal tandem duplications in exon 11 [18]. KIT mutations are associated with early relapse and worse overall survival [15, 16, 18, 19, 29, 30]. Identification of these abnormalities is typically performed at diagnosis in these patients by sequencing of the appropriate exons of the KIT gene prior to initiating therapy. Other methodologies including allele-specific PCR and PCR followed by high-resolution melt-curve analysis can also be used.

Fig. 5.4 Exon–intron structure of RUNX1 (pink boxes) and RUNX1T1 (blue boxes). Breakpoint regions are indicated by arrow or bracket. Fusion product shown below

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AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 [AML inv(16)] is another “good prognosis” CBF-AML. This mutation is identified in 8– 12% of patients with AML [13, 20, 31]. It is typically associated with AML with atypical eosinophils with mixed basophilic and eosinophilic granules as well as at least partial monocytic differentiation. The genes involved are the CBFB gene involved in the CBF complex as well as the smooth muscle myosin heavy chain gene MYH11 [32–35]. Identification of this translocation can be done by conventional karyotyping, FISH, or RT-PCR. Of note, both the inv(16) and the t(16;16) can be difficult to identify by conventional karyotyping and can be easily missed by inexperienced readers. FISH probes are typically designed as a breakapart probe set, which yields the same pattern of 1F1R1G for both the inversion and the translocated 16 (see Fig. 5.1c, d). Because of variations in the breakpoints in MYH11 (see below), careful design of primers and probes is essential. RQ-PCR for minimal residual disease testing is discussed below. CBFB contains a single domain, the heterodimerization domain, which binds to RUNX1 and stabilizes binding of the CBF complex to DNA [32, 34]. CBFB does not directly bind DNA. Breakpoints for the fusion transcript are almost always scattered in exon 5, a 15 kb exon of this gene [13, 32, 34, 35]. A single report of an exon 6 breakpoint in CBFB was recently made [36]. MYH11 is a complex gene with 42 coding exons which encode a protein of close to 2000 amino acids [37]. There are multiple MYH11 breakpoints that occur in AML inv(16), and at least 11 fusion transcripts have been described to date [8, 31, 33, 36]. Breakpoints found in multiple different exons and in the cDNA span greater than 1000 base pair length of sequence. Therefore detection requires the use of multiple primer pairs. The most common fusion transcripts are A (88%), D (5%), and E (5%) (Fig. 5.5). The other alternative transcripts are rare and each one is detected in fewer than 1% of cases [8, 33, 36, 38, 39]. The fusion in all cases, however, results in the heterodimerization domain of the CBFB being joined to the multimerization C-terminal domain of MYH11 [34]. The resulting fusion transcript has a dominant negative effect on transcription [33]. Of note, in addition to the variation of fusion transcript size determined by MYH11 breakpoint, RUNX1 can have alternative splicing which results in a fusion protein with only 133 amino acids from CBFB [34]. KIT mutations are likewise seen in a subset of these patients [15–18]. However, the prognostic significance is less clear. Paschka et al. [16] and Care et al. [15] demonstrated increased relapse rates in patients with AML inv(16) with KIT mutations, and Paschka et al. [16] additionally demonstrated decreased overall survival in these patients. Boissel et al. [17] and Cairoli et al. [18] did not find any differences in overall or relapse-free survival based upon KIT mutation status. Additionally, Paschka et al. [16] only found significant changes in patients with exon 17 mutation, whereas Care et al. [15] found changes in patients with exon 8 mutations.

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Fig. 5.5 Exon–intron structure of CBFB (green boxes) and MYH11 (purple boxes). Breakpoint regions indicated by arrows. Most frequent fusion products are shown (a, d, and e)

MRD by RQ-PCR in CBF-AML The significance of molecular monitoring to evaluate MRD in CBF-AML has been investigated by a number of investigators and reviewed by Marcucci et al. [28] and Mrozek et al. [40]. Initial studies using qualitative RT-PCR and competitive RT-PCR gave variable results as to the persistence of detectable fusion transcripts and the significance of their presence or absence during therapy. More recently, investigators have used RQ-PCR to look at fusion transcript levels at diagnosis, after induction therapy, after consolidation therapy, and at continued follow-up [41–49]. Although each study was designed differently and had somewhat different findings, all demonstrated that monitoring of molecularly determined MRD is of value in CBF-AML. Multiple investigators demonstrated a wide variation of transcript burden between patients at diagnosis (1–3 log variation) which could not be explained purely by blast count or number of positive interphase cells by FISH [43–45, 47]. Patients with higher transcript levels were found to have worse overall and eventfree survival [44] and increased rate of relapse [45]. This type of variation is unlike what has been observed in detection of BCR-ABL1 in chronic-phase CML and is worth noting as many laboratories compare BCR-ABL1 levels to a normalized level of an average patient in order to determine log decrease or percentage level of transcript [50]. This would not work in CBF-AML where levels at diagnosis vary so widely. Two investigators found a high concordance between levels of MRD in peripheral blood and bone marrow and proposed that peripheral blood could be used for monitoring in both CBF-AML subtypes [46] or specifically in AML t(8;21) [45].

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Other findings include the following: Leroy et al. [45] determined that a >3 log decrease post-induction or a level >10−5 post-consolidation was associated with decreased risk of relapse. Weisser et al. [48] used a median level of transcript after induction and post-consolidation. At both time points patients with a level greater than median showed increased cumulative incidence of relapse and decreased overall survival and event-free survival. They found a cutoff level of 0.003 (the median in their study) or a reduction to 0.01% (4 log) could be similarly used. Other proposed cutoff levels include greater than 10 copies as compared to a standard curve at end of treatment [47], less than 2 log decrease post-induction [46], greater than 1 log increase after complete remission [49], and greater than 2 log reduction [43]. Schnittger et al. [44] proposed a score which looked at transcript level at two time points, diagnosis and during the first 3–4 months of therapy. He found that patients who had a level at diagnosis greater than the 75 percentile (as compared to other patients) and a level at the 3–4 month time point greater than the median (which corresponded to <3 log decrease) are at high risk for treatment failure. Although these results are promising and indicate the value of MRD detection in CBF-AML, more work needs to be done, including standardization of RQ-PCR techniques, standardization of methods of reporting, and development of an international standard for quantification, before specific cutoffs can guide therapy. Other Recurrent Translocations Additional recurrent translocations are included in the WHO classification [1] and are shown in Table 5.1. All of these are rare and vary from representing <1–2% of adult AML depending on the specific translocation. AML with t(9;11)(p22q23); MLLT3-MLL and Other MLL Abnormalities Although AML with t(9;11)(p22q23); MLLT3-MLL [AML t(9;11)] is distinct from the other MLL abnormalities in the WHO classification, all MLL abnormalities will be summarized in this section. At least 104 distinct MLL rearrangements have been identified. Of these 64 fusion partners have been characterized at the molecular level [51]. In addition both partial tandem duplication (AML-PTD) and MLL amplifications have been described [52–57]. Translocations involving the MLL gene occur in 3–4% of adult AML, 14–20% cases of pediatric AML, and 65% of infant AML [58–60]). These translocations are frequent in treatment-related AML, specifically those treated with topoisomerase II inhibitors. MLL-PTD is relatively frequent in adults (5–10%), but occurs in fewer than 1% of pediatric AML patients [51, 56, 61]. Although the majority of MLL translocations are associated with a poor prognosis, at least some studies have demonstrated that AML t(9;11) is somewhat unique and is associated with an intermediate prognosis in AML [62–66]. Other studies have not replicated this finding [57, 60]. In addition, studies have demonstrated poor prognosis [67] for t(6;11)(q27;q23) and good prognosis for t(9;11) in childhood AML [64]. The MLL gene contains 37 exons and covers over 100 kb [59, 68–72]. The protein consists of 3969 amino acids and contains several significant

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Fig. 5.6 Exon–intron structure of MLL (yellow boxes). Gene X (green boxes) indicates any known fusion partners. Fusion transcript and MLL-PTD shown with protein domains: AT (AT hooks), SNL (nuclear localization signal), DMT (dimerization domain), PHD (PHD finger domain), TAD (transactivation domain), and SET (domain involved in histone methylation)

domains including AT hooks, a nuclear localization domain, repressor domains, and PHD domains [68–72]. The breakpoint cluster region (Fig. 5.6) covers over 8 kb and breakpoints can occur in introns 5–11 [59, 73]. MLL is involved in a multiprotein complex that is present in the nucleus and involved in remodeling of the nucleosome. It has histone methyltransferase activity and is involved in methylation, acetylation, and nucleosome remodeling [72]. Its role in HOX gene regulation is essential for normal hematopoiesis. Although there are numerous translocation partners, the majority of MLL translocations in AML involve the following genes: AF9, AF10, ELL, AF6, ENL, AF17, and SEPT [51]. Translocations fall into two types: class I mutations involving fusion to a nuclear protein and class II mutations which result in cytoplasmic localization [56, 72]. It is important to note that patients with acute leukemia with translocations involving MLL may fall into a number of different categories including AML with recurrent translocations, AML with myelodysplasia-related changes (AML-MDS), and therapy-related AML. Appropriate classification of these cases requires a combination of clinical history as well as identification of specific translocations (see below). In cases with MLL translocations that do not have a translocation that falls under AML-MDS the specific abnormality is listed in the diagnosis [1]. Although it is theoretically possible to develop RQ-PCR testing to detect all of these translocations, it is impractical for the clinical laboratory. Therefore, MLL translocations are typically detected by a combination of karyotyping and FISH using a breakapart probe (Fig. 5.1c, d). FISH using a breakapart probe has the advantage of detecting cryptic translocations as well as MLL-PTD and amplifications. It does not, however, demonstrate the translocation partner. MRD in AML with MLL Abnormalities Although MRD detection by RQ-PCR is difficult due to the multiple translocation partners, some studies have demonstrated clinical significance to MRD detection

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[51, 55, 74]. Therefore, laboratories should at least consider whether RT-PCR analysis detecting specific translocations is appropriate in their clinical setting. Conventional karyotyping will, however, detect the majority of these. Of note, MLLPTD is detectable in up to 100% of healthy adults [56] and in 93% of cord blood samples when high-sensitivity techniques are used. The level is typically 4 log lower than is seen in AML with MLL-PTD. Rare Subtypes of AML In addition to the commonly seen subtypes of AML described above, rare yet recurrent translocations are also incorporated into the new WHO classification, specifically: AML with t(6;9)(p23;q34); DEK-NUP214, AML with inv(3)(q21q26.2) or t(3;3)(q21;q26.2); RPN1-EVI1, and AML with t(1;22)(p13;q13); RBM15-MKL1. Taken together they comprise approximately 2–4% of AML [1]. These mutations are typically detected by conventional karyotyping instead of RQ-PCR due to their rarity. AML with t(6;9) occurs in adults and children. Patients have a poor prognosis with short survival. There is often multilineage dysplasia (especially in the erythroid and granulocytic series) as well as an absolute basophilia. Like the other AML with recurrent translocations, a diagnosis of AML with t(6;9) can be made even if blasts comprise fewer than 20% of cells. The translocation is amenable to detection by both Southern blot and RQ-PCR [75–77]. AML with inv(3) or t(3;3) is also a poor prognosis AML. It occurs both as a therapy-related AML and de novo. There is often multilineage dysplasia with megakaryocytic dysplasia often with micromegakaryocytes with unilobated or bilobed nuclei. A subset of cases show marked thrombocytosis at diagnosis [1]. Fusion transcripts can be evaluated by RT-PCR [78]; however, these studies are not routinely performed in the majority of clinical laboratories. AML with t(1;22) is very rare (<1% of AML) and is typically seen in infants [1, 79, 80]. A single case report exists describing an adult patient [81]. AML with Gene Mutations In addition to the balanced translocations described above, numerous gene mutations have been described and continue to be described associated with AML. These can be divided into class I mutations (involved in proliferation and apoptosis) and class II mutations (associated with differentiation). Many of these are felt to be cooperating mutations and are found in a number of different subtypes of AML, whereas others may represent novel AML subtypes defined by gene mutations. Two of these are identified as provisional entities in the WHO classification [1]. AML with Mutated Nucleophosmin 1 (NPM1) (Provisional Entity) Mutation of NPMI is the most common mutation in AML and occurs in approximately 30% of all AML and 50–60% of normal karyotype AML (NK-AML) [1, 61,

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82]. It occurs in both pediatric and adult AML, but is significantly rarer in children, 4% of all pediatric AML [83]. In NK-AML, the presence of the NPM1 mutation in the absence of an accompanying FLT3-LM is associated with a good prognosis [61, 84–88]. NPM1 encodes a shuttling protein that is typically located in the nucleolus of the cell. Mutations typically involve 4–5 base pair insertions in exon 12 but rare alternative translocations have been identified in exons 9 [89] and 11 [90, 91] (Fig. 5.7). At least 40 unique mutations have been identified to date. The most common mutations are A, B, and D with A occurring in up to 80% of cases [92, 93]. All result in abnormal localization from the nucleus into the cytoplasm due to creation of a nuclear export signal. Detection of NPM1 can be performed by PCR using primers flanking the site of insertion (Fig. 5.8), followed by fragment analysis [94]. This should be performed at the time of diagnosis in NK-AML and should be paired with evaluation for FLT3-LM (see below) for appropriate assessment of prognosis. The mutation

Fig. 5.7 Exon–intron structure of NPM1. Major mutation site is indicated by arrow. Rare mutations sites are indicated by double-headed arrow

Fig. 5.8 Electropherogram demonstrating the presence of an NPM1 exon 12 insertion mutation by PCR with fragment analysis by capillary electrophoresis. Unmutated and mutated genes indicated by arrows

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occurs in a single allele and therefore both the mutated and the unmutated genes will be detected. This approach also has the advantage that it should detect any mutation within the coding sequence flanked by the primer set. More recently a variety of groups have developed RQ-PCR assays using either specific primer sets targeting common mutations [95] or multiple primer sets that detect multiple different mutations [92, 93, 96]. A typical strategy is to utilize a consensus forward or reverse primer paired with mutant-specific reverse or forward primers, respectively. Consensus probes are used [92, 93, 96]. NPM1 is an attractive target of MRD testing as it is believed to occur early in oncogenesis and the majority of authors find it stable at relapse [92, 93, 96]. There are reports of clonal evolution at relapse [87, 95], but these appear to be the exception and not the rule. Using a RQ-PCR assay, both Gorello et al. [92] and Chou et al. [96] were able to monitor disease level in these patients and in some cases predict relapse. More recently Schnittger et al. [93] described RQ-PCR assays which were able to define 17 different NPM1 mutations in 252 patients. They additionally found that monitoring of mutant transcript level during treatment could predict likelihood of complete clinical response as well as likelihood of relapse.

AML with Mutated CCAAT/Enhancer-Binding Protein Alpha (CEBPA) (Provisional Entity) CEBPA is a member of the CCAAT/enhancer-binding protein family with a role in proliferation and differentiation in myelopoiesis [97, 98]. Down-regulation of CEBPA is associated with CBF-AML and APL [98]. Mutations in CEBPA are seen in 10–15% of AML [97] and in approximately 15% of NK-AML [61]. They are seen in 7% of pediatric AML [83]. Patients with mutated CEBPA have a good prognosis similar to that seen in the CBF-AML and APL [97, 99]. CEBPA is encoded on chromosome 19q13.1. It encodes multiple domains including several transactivation domains as well as a leucine zipper, DNA-binding and dimerization domain [97, 98]. Mutations cluster in several regions and biallelic mutations are common [100]. Mutations in the N-terminal region are typically out-of-frame insertions or deletions. They result in increase in an alternative isoform which acts in a dominant negative fashion to inactivate the unmutated gene. Alternatively mutations occur in the C-terminal DNA-binding domain and interfere with normal transcription activation of myeloid genes involved in differentiation. Although studies are limited, the mutations are not detected at the time of CR; however, if patients relapse, the initial mutations are once more detectable [101]. To the best of our knowledge, development of novel CEBPA mutations at relapse has not been described. Given the variation in mutations seen in this gene (i.e., mutations occur over the entire coding sequence of the gene), routine testing in the clinical laboratory has not been adopted; however, multiplex or multiple PCR reactions in conjunction with fragment analysis can be used as a screening technique to identify these mutations [102, 103].

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AML with Myelodysplasia-Related Changes Diagnosis of this entity can be made by using a combination of clinical history (prior MDS and absence of prior cytotoxic therapy), morphologic/cytologic findings of dyspoiesis, absence of recurring genetic abnormality not associated with MDS, and the presence of specific abnormalities associated with MDS [1]. Diagnosis, therefore, depends in part upon demonstrating the presence of MDS-associated abnormalities by FISH and/or conventional cytogenetics. Specific alterations have been described that will fulfill the criteria for AML with MDS-related changes, summarized in Table 5.2 [1]. Unbalanced abnormalities of chromosome 5 and 7 are the most common abnormalities in this group. These abnormalities result in loss of all of chromosomes 5 and 7 (monosomy) or loss of portions of the long arm (Fig 5.9). Although the breakpoints vary with both 5q and 7q rearrangements, the commonly deleted regions (CDR) are 5q31-32, 7q22, and 7q32-34 [104, 105]. The CDR on chromosome 5 contains over 40 genes, several of which have been implicated in the pathogenesis of myeloid malignancies. These candidate genes include CTNNAI [106], RPS14 [107], DIAPH1, Egr1/Krox20, and alpha-catenin [108–111]. Such genes as MLL5,APS, and CUTL1 at 7q22 and regions D7S486, D7S498, and D7S505 at 7q31-4 have been suggested to be involved in myeloid disease within the two commonly deleted regions on 7q [112–116].

Table 5.2 AML-MDS-related cytogenetic abnormalities Complex (>3 abnormalities) –5 or del(5q) –7 or del(7q) i(17q) or t(17p) –13 or del(13q) del(11q) del(12p) or t(12p) del(9q) idic(X)q13 t(1;3)(p36.3;q21.1) t(11;16)(q23;p13.3) t(2;11)(p21;q23) t(3;21)(q26.2;q22.1) t(3;5)(q25;q34) t(5;10)(q33;q21) t(5;12)(q33;p12) t(5;17)(q33;p13) t(5;7)(q33;q11.2)

Although the majority of MLL translocations are categorized under AML with recurrent translocations (see above), two specific translocations fall in this category t(2;11)(p21;q23) and t(11;16)(q23;p13.3) if the patient does not have prior history of chemotherapy.

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Fig. 5.9 FISH images using enumeration probe set for chromosome 5 with the Cri-du-Chat region at 5p15.2 labeled in green and the EGR1 region at 5q31 in red. (a) Metaphase and interphase FISH demonstrate normal pattern of this probe (2G2R). (b) FISH pattern showing deletion/monosomy of chromosome 5 (1G1R). (f ) FISH pattern showing interstitial deletion 5q (2G1R)

Other Gene Mutations in AML with Prognostic Significance FLT3-LM and FLT3-TKD Activating mutations in the type 3 receptor tyrosine kinase FLT3 gene were first identified by Nakao et al. [117] and subsequently have been described in 25–30% of AML patients and in 40% in NK-AML [61, 118, 119]. These mutations are rarer in pediatric AML and are seen in approximately 10–15% of patients [83, 119]. When activated, mutated FLT3 acts on downstream pathways including the PI3 kinase/AKT pathway, RAS/MAP kinase pathway, and STAT5 pathway [120]. The gene is, therefore, involved in a number of normal cellular processes including apoptosis, proliferation, and differentiation. FLT3 mutations in AML constitutively activate the receptor by two distinct types of mutations: in-frame length mutations (LM) in a regulatory juxtamembrane domain and point mutations (either at D835 or at I836) in the tyrosine kinase domain (TKD) as shown in Fig. 5.10 [1, 119]. The former has been shown to predict poor

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Fig. 5.10 Structure of FLT3 gene with protein domains indicated. IGG (immunoglobulin like domains), JM (juxtamembrane), TK1, and TK2 (tyrosine kinase domains). Sites of LM (length mutations) and TKD (tyrosine kinase domain point mutations) are indicated

prognosis in NK-AML [61, 119]. The significance of the point mutation, however, is less well established. Some studies have shown that the TKD mutations also confer a poorer prognosis [118, 121], whereas others either do not show prognostic significance or must be analyzed in conjunction with other mutations [122]. Specifically, they found that TKD mutation in NK-AML does not demonstrate prognostic significance; TKD mutations along with FLT3-LM, PML–RARA, or MLL-PTD mutations confer a poor prognosis, and TKD mutations along with NPM1 or CEBPA mutations show improved prognosis [122]. FLT3 mutations are common in APL and are seen in approximately 35% of patients [118, 123]. They do not seem to impart the same poor prognosis in this group. Of note, FLT3 mutations can be lost at time of relapse, may arise at relapse, or the size of the FLT3-LM may change during the disease course [74, 124–127]. Testing for FLT3-LM can be performed by PCR followed by fragment analysis as shown in Fig. 5.11 [94, 128]. The size of the LM varies widely ranging from 3 to > 400 base pair and in some patients multiple different size insertions can be found [123, 124]. In the majority of patients, this is a heterozygous mutation, i.e.,

Fig. 5.11 Electropherogram demonstrating detection of the FLT3-LM as performed by PCR followed by capillary electrophoresis with fragment analysis. Both the unmutated allele (FLT3) and the mutated allele (FLT3-LM) are indicated

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the normal gene is still identified, but in a subset only mutated alleles are detected. In addition, some patients have both the LM and the TKD. D835 mutation evaluation can be performed by PCR followed by restriction enzyme digestion, allele-specific PCR, or sequencing. The allelic ratio of the LM to the normal allele has been shown to be of prognostic significance. In general, higher ratios correlate with worsening prognosis [129]. Low levels of allele burden have not been shown to impart the negative prognosis of this mutation. Specific levels of allele burden have been identified in the literature below which the prognosis is no longer poor, < 0.4 in children [130] or < 0.78 in adults [118]. It is difficult to know, however, how to apply this in the clinical laboratory as independent standards are not available to confirm that allelic ratios are consistent from laboratory to laboratory. Of note, allelic ratio comparisons have been performed between laboratories participating in specific Children’s Oncology Group (COG) trials. Given that this testing is typically performed using end point PCR and the size of the LM can vary from 3 to > 400 base pair, it is naïve to assume that the amplification efficiency of the mutated allele will be identical to the unmutated gene regardless of insert size. Therefore the establishment of a strict cutoff for allelic burden may not be appropriate unless testing is performed in a more quantitative manner. As mentioned above, FLT3 mutations have been known to disappear during the disease course [126, 127]. Therefore detection of this mutation may not be a reliable target for MRD testing. FLT3 inhibitors are in early use and show some promise. Wilms Tumor 1 (WT1) WT1 is mutated in 10–15% of AML [131–134] and in approximately 6% cases of pediatric AML [83]. Two large series specifically analyzed NK-AML and found mutations in approximately 10% of NK-AML [133, 134]. Mutations tend to cluster in exons 7 and 9 [131–134], but other exons are rarely involved [131]. The role of the WT1 protein in hematopoiesis is not fully understood at this time; however, it is known to contain transcription regulatory domains as well as DNA-binding zinc finger domains. Mutations include small insertions and deletions primarily in exon 7 and point mutations primarily in exon 9 [131–134]. In the majority of patients it is a heterozygous mutation, but in some cases only the mutant allele is identified most likely caused by copy number neutral loss of heterozygosity (acquired uniparental disomy). Mutations result in either loss of all or a portion of the DNAbinding domain or missense mutations. Multiple WT1 mutations are also found in a subset of patients [131–134]. Of note, WT1 mutations are associated with poor prognosis and, therefore, may help stratify patients with NK-AML [83, 132–134]. Numerous papers have been written describing the use of WT1 expression levels by RT-PCR in monitoring AML. Gene Expression and Prognosis in NK-AML Attempts to further stratify prognosis in NK-AML are underway looking at levels of gene expression and their effects on prognosis. High expression of the

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following genes has been shown to help further stratify these patients: brain and acute leukemia, cytoplasmic (BAALC), meningioma 1 (MN1), and ETS-related gene (ERG). BAALC is a highly conserved gene normally expressed in mesodermal cells and in normal hematopoietic precursors [135–137]. Its expression is not seen in normal peripheral blood leukocytes and is only seen at low levels in normal bone marrow cells due to the relative paucity of the CD34+ stem cell compartment. Multiple protein isoforms are expressed secondary to alternative splicing [135]. Overexpression of BAALC has been shown to be associated with poor prognosis in NK-AML by multiple groups [135, 138–140]. In addition, when evaluated in concert with FLT3LM mutation status, and allele burden for FLT-LM (when positive), it allowed further stratification of both mutation-positive and mutation-negative patients [139, 140]. High levels of expression of this gene are associated with other poor prognostic factors, including the presence of FLT3-LM, unmutated NPM1, mutated CEBPA, MLL-PTD, and high ERG expression [140]. The MN1 gene was first identified in a patient with meningioma [141]. It was subsequently found to be involved in rare translocations seen in myeloid neoplasms [142]. High levels of expression of the MN1 gene have been shown to be associated with unmutated NPM1 and to be an independent indicator of poor prognosis in NK-AML [143, 144]. High expression of ERG has likewise been shown to be an independent indicator of poor prognosis in NK-AML [145, 146]. The authors propose that level of expression of ERG can be used in addition to mutation status for FLT3-LM and NPM1 in patients with NK-AML. Although expression of these three genes has been shown to have prognostic significance in the studies referenced above, it is premature to incorporate them into routine clinical testing. In order to use gene expression levels to guide therapy outside of clinical trials a number of hurdles will need to be overcome. Testing will have to be performed and reported in a uniform manner from laboratory to laboratory, and an international standard will need to be available to ensure that different laboratories are performing the test accurately and that the results are comparative from lab to lab. In addition, large, prospective, multicenter studies will need to be performed to define appropriate cutoffs to predict good versus poor prognosis.

Mutations and Translocations Associated with Other Myeloid Neoplasms Mutations and translocations primarily associated with myeloproliferative neoplasms or myelodysplastic disorders can also be seen in de novo AML. This includes BCR/ABL1, JAK2, and MPL. Some of these cases may represent blast transformation of previously undiagnosed myeloid neoplasms; however, others appear to represent de novo disease [1, 147–152]. Molecular detection of these abnormalities is described in the chapter on myeloproliferative neoplasms.

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Future Directions As our knowledge and understanding of the underlying pathobiology of AML continues to improve, so will the need for new molecular testing to identify and monitor these abnormalities. Many of these tests will begin as laboratory-developed tests, whereas others may evolve as companion diagnostics as new drugs are developed for targeted therapies. Although some suggested diagnostic algorithms have been proposed [14, 153], substantial work needs to be done in developing guidelines for appropriate sensitivity, guidelines for therapy based upon a complex mixture of prognostic markers, and uniformity in reporting and quantitation. Widely available, well-characterized positive controls and quantitation standards are needed to ensure quality and consistency from laboratory to laboratory. These are non-trivial problems and attempts to solve them are ongoing. In addition, the technology continues to evolve and in many cases become substantially cheaper. Techniques including gene expression arrays, whole genome sequencing, and studies involving SNP arrays, epigenetic analysis, microRNAs, and proteomics are ongoing.

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Chapter 6

Molecular Pathology of Mature B-Cell and T-Cell Lymphomas Sophia L. Yohe, David W. Bahler, and Marsha C. Kinney

Keywords B-cell maturation · Immunoglobulin heavy chain (IgH) gene rearrangement · Kappa immunoglobulin light chain gene rearrangement · Lambda immunoglobulin light chain gene rearrangement · Class (isotype) switch · Somatic hypermutation · Clonality testing · B-cell · Follicular lymphoma · B-cell lymphoma/CLL 2 (BCL2) translocation –t(14;18) · Mantle cell lymphoma · Cyclin D1 translocation –t(11;14) · Diffuse large B-cell lymphoma (DLBCL) · Germinal center type · Activated B-cell type · B-cell lymphoma/CLL 6 (BCL6) · Marginal zone lymphoma · Mucosal associated · t(11;18) · Nodal marginal zone lymphoma · Splenic marginal zone lymphoma · Burkitt lymphoma · MYC breakpoints · t(8:14) · Lymphomas intermediate between Burkitt and DLBCL · Lymphoplasmacytic lymphoma · T-cell maturation · T-cell receptor (TCR) alpha gene rearrangement · T-cell receptor (TCR) beta gene rearrangement · T-cell receptor (TCR) delta gene rearrangement · T-cell receptor (TCR) gamma gene rearrangement · Clonality testing · T-cell · Clonal peak height · Flow cytometry · Vbeta · Anaplastic large cell lymphoma · ALKNPM translocation –t(2;5) · ALK signaling pathway · Angioimmunoblastic T-cell lymphoma · Mycosis fungoides · Sezary syndrome · Hepatosplenic T-cell lymphoma · Enteropathy associated T-cell lymphoma · Extranodal NK/T-cell lymphoma · Peripheral T-cell lymphoma NOS · Nodular lymphocyte predominant Hodgkin lymphoma · Aberrant somatic hypermutation · Classical Hodgkin lymphoma · Southern blot · Polymerase chain reaction (PCR) – Fluorescent in-situ hybridization (FISH) · Immunohistochemical stains · Comparative genomic hybridization · Gene expression profiling

S.L. Yohe (B) Department of Laboratory Medicine and Pathology, University of Minnesota Medical Center, Fairview, Mayo Room D219-7, 420 Delaware St. SE, Minneapolis, MN 55455, USA e-mail: [email protected]

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_6, 

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Introduction Over the last two decades, molecular genetic testing has assumed a prominent role in the diagnosis, classification, and clinical management of lymphoma [1]. In some lymphoid and more so in myeloid tumors, a specific genetic abnormality may be the defining feature. More often genetic abnormalities are characteristic of one type of disease but may be present in other tumors and contribute to their pathogenesis. In addition to the standard assays for receptor gene rearrangements and specific genetic lesions (particularly translocations) used in clinical practice, sophisticated assays such as expression microarray, array comparative genomic hybridization (CGH), microRNA analysis, and epigenetic testing are more readily available; data derived from these complex analyses are continuously being translated into clinically pertinent information regarding pathogenesis, diagnosis, prognosis, and targeted therapy for lymphoma. This chapter will focus on the molecular pathogenesis of lymphoma and discuss current clinical molecular diagnostic testing and its limitations and emphasize interpretation of molecular results in the context of clinical features, morphology, or other studies.

Molecular Testing for B-Cell Non-Hodgkin Lymphoma (B-NHL) B-Cell Biology and Maturation Events that occur during B-cell development play an important role in molecular testing for B-cell lymphomas. Furthermore, many B-NHLs correspond to different stages of B-cell development; therefore an understanding of B-cell development is critical in the diagnosis of B-NHL (Table 6.1). B cells are part of the adaptive immune system, producing antibodies against various antigens. Given the large number of antigens and unpredictable exposure in different individuals, mechanisms must be in place to create a wide range of antibodies (an antibody repertoire) from a limited number of genes. The first step in creating this diversity is rearrangement of the heavy- and light-chain immunoglobulin genes, which occurs in B lymphoblasts residing in the bone marrow. Rearrangement of the immunoglobulin heavy-chain gene (IGH or H) occurs first followed by rearrangement of the kappa (κ) and lambda (λ) immunoglobulin light-chain genes (L). Additional diversity is created by the addition and subtraction of nucleotides at the sites of rearrangement, pairing of different heavy and light chains, and somatic hypermutation. These differences are responsible for the polyclonal population of B cells in normal individuals. The IGH gene on chromosome 14q32 is composed of 40–52 functional variable (V), 25 diversity (D), six joining (J), and five constant (C) segments [2, 3] as shown in Fig. 6.1.

Rearranged surface Rearranged surface Rearranged surface

GC B cell Centroblast GC B cell

Plasma cell

Memory B cell Post-follicular B cell

High Ongoing High and aberrant High High

Germline (60–85%) or low Ongoing

Rearranged surface High Rearranged surface and High cytoplasmic Rearranged cytoplasmic High Class switch

GC or post-GC B cell Rearranged surface Activated peripheral Rearranged surface B cell

Rearranged surface

Centrocyte

Germinal center

Postgerminal center

Rearranged sIgM/sIgD

Mantle zone Naïve B cell

Rearranged surface Rearranged surface and cytoplasmic Rearranged cytoplasmic

Rearranged surface Rearranged surface

Rearranged surface Rearranged surface Rearranged surface Rearranged surface

CD138, CD38, MUM1

No CD5 or CD10 No CD5 or CD10

CD10, BCL6, CD19, CD20 CD30, CD15, CD19, CD20, BCL6 CD10, BCL6, CD19, CD20 CD10, high Ki67 MUM1 No CD10

Rearranged

PCN

MZL LPL

BL DLBCL (ABC type)

CHL NLPHL DLBCL (GC type)

FL

MCL CLL/SLL

CD19, CD20, BCL2

Rearranged

Neoplastic counterpart

Molecular Pathology of Mature B-Cell and T-Cell Lymphomas

The cell of origin and its neoplastic counterpart are notated. Several lymphomas may arise from more than one cell of origin. ALL, acute lymphoblastic lymphoma; MCL, mantle cell lymphoma; FL: follicular lymphoma; CHL, classical Hodgkin lymphoma; NLPHL, nodular lymphocyte-predominant Hodgkin lymphoma; DLBCL, diffuse large B-cell lymphoma; BL, Burkitt lymphoma; MZL, marginal-zone lymphoma; LPL, lymphoplasmacytic lymphoma; PCN, plasma cell neoplasm

Lymphoid tissue

Immature B cell

Germline VL –JL

Germline VH –DH JH Rearranged Germline intracellular μ Rearranged surface IgM Germline

Late pro-B cell Pre-B cell

Immunophenotype TdT, CD34, CD10, ALL CD19, CD38 TdT, CD10, CD19, CD38 ALL CD19, CD20, CD38, Less ALL TdT, variable CD20 CD19, CD20

Germline

Germline

DH –JH

Early pro-B cell

κ/λ

Bone marrow

SHM

Cell

Location

IgH

Table 6.1 Overview of B-cell development showing the timing of immunoglobulin gene rearrangement and somatic hypermutation (SHM)

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Fig. 6.1 Immunoglobulin heavy-chain gene rearrangement. DH –JH rearrangement occurs first followed by VH –DH JH rearrangement. There are 40–52 functional VH regions. Non-template (N) and palindromic (P) nucleotides are added at the joins by terminal deoxynucleotidyl transferase (TdT) and recombination-activating gene (RAG) proteins, respectively. After rearrangement a single V, D, and J region is present. PCR primers are directed toward the framework regions (FRs) which are more conserved between V regions than the complementarity-determining regions (CDRs). Forward primers are directed toward FR I, FR II, and/or FR III in the VH segment, while the reverse primer is directed toward FR IV in the JH segment. L refers to a leader sequence

Ultimately a single V, D, J, and C regions are joined to each other with the intervening gene sequences removed. Not all recombinations create a functional protein as a stop codon may be created or rearrangement may occur with a pseudogene (especially in the variable region). Rearrangement starts on the IGH gene in early pro-B cells with a DH to JH segment joining [2]. This rearrangement occurs on both alleles and is usually successful (rarely produces a stop codon) due to the makeup of the DH segment [2]. The next step is VH to DH JH rearrangement in late pro-B cells (Fig. 6.1). Recombination at this step is less often successful and occurs in one allele at a time [2]. The second allele will rearrange only if recombination is unsuccessful on the first and both alleles can join different remaining VH segments. Despite the option of multiple rearrangements on one allele and subsequently on the other, at least 45% of pro-B cells do not successfully complete this step and are lost [2]. Pro-B cells that complete this step produce mu (μ) heavy chains and become pre-B cells. Successful rearrangement is signaled by a receptor composed of the newly formed mu heavy chain, CD79A, CD79B, and surrogate light chains encoded by non-rearranged genes [2]. Theoretically VH –DH –JH rearrangements can lead to ∼6,000 different combinations in the heavy-chain gene [2]. Additional diversity is created by the addition and subtraction of nucleotides at the sites of recombination by the action of terminal deoxynucleotidyl transferase (TdT) and various other enzymes. TdT, which is highly expressed in pro-B cells, adds up to 20 random or non-template nucleotides (N nucleotides) at the DH –JH and VH -DH

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joins [2]. Palindromic sequences of nucleotides (P nucleotides) are added by the recombination-activating gene (RAG) proteins [2]. Various DNA repair enzymes are responsible for the removal of nucleotides. The IGH gene now has a VDJ composed of four framework regions (FRs) and three complementarity-determining regions (CDRs) as shown in Fig. 6.1. FR I, FR II, and FR III are located in the VH region, while FR IV is in the JH region. FRs are similar in all VH segments and undergo less somatic hypermutation than do CDRs. CDRs are the antigen-binding areas, are variable from one VH segment to another, and are prone to somatic hypermutation. Pre-B cells proliferate prior to recombining their light-chain genes, therefore several cells with the same IGH rearrangement will pair with different kappa or lambda light chains. The light-chain genes lack a diversity segment and have N nucleotides added only about 25% of the time due to lower expression of TdT in pre-B cells [2] as shown in Fig. 6.2a. The kappa light-chain gene (IGK) on chromosome 2p11 rearranges first >90–95% of the time (Fig. 6.2a). One of the variable segments recombines with one of the joining segments. If this rearrangement is unsuccessful, remaining V and J segments can recombine and if one allele is completely unsuccessful, the second allele will undergo recombination. If both alleles are unsuccessful, then the second light chain, lambda (IGL) on chromosome 22q11, will undergo rearrangement in the same manner (Fig. 6.2b). The kappa a

b

Fig. 6.2 Kappa and lambda light-chain gene rearrangement. (a) Kappa light-chain gene rearrangement. Vκ –Jκ rearrangement occurs if unsuccessful subsequent Vκ –Jκ rearrangements can occur with any of the remaining Vκ and Jκ segments until there are no remaining segments. Non-template (N) nucleotides are only added to the join approximately 25% of the time. A kappa-deleting element (Kde) segment can rearrange with a variable segment or the intron between Jκ and Cκ (intron-RSS) leading to inactivation of the allele. (b) Lambda light-chain gene rearrangement. Rearrangement is similar to kappa light-chain gene rearrangement, except that there is no analog to Kde. N nucleotides are only added to the join approximately 25% of the time

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immunoglobulin light-chain gene has a unique area called the kappa-deleting element (Kde) (Fig. 6.2a). The Kde area can recombine with a variable segment or an area in the intron between Jκ and Cκ (intron-RSS) (Fig. 6.2a). Both possible Kde recombinations delete the constant region and recombination with the variable region also deletes the junctional region leading to inactivation and inhibition of somatic hypermutation of that allele. Rearrangement of the light-chain genes theoretically results in 320 different combinations and 1.92 × 106 different combinations are theoretically possible with a heavy chain paired to a light chain [2]. Diversity is increased to about 5 × 1013 by the addition of N and P nucleotides and subtraction of nucleotides in the areas of rearrangement [2]. Successful light-chain rearrangement results in the expression of surface IgM and the cell becomes an immature B cell. Immature B cells leave the bone marrow (unless they react to self-antigens) and travel to the peripheral lymphoid tissues such as spleen and lymph node where they are now considered mature B cells. Mature B cells enter in the interfollicular areas and move through the germinal center where they are exposed to foreign antigens to become plasma cells and memory B cells. Antigen-naïve B cells in the mantle zone have not switched the CH region and express IgM or IgD using alternative transcription or splicing [4]. These cells compete for entry into the germinal center where proliferation, class (isotype) switching, and somatic hypermutation take place. Class switch to IgG, IgA, or IgE occurs upon presentation to antigen and is dependent on signals from the microenvironment, including helper T cells and dendritic cells [4, 5]. Activation-induced cytidine deaminase (AID) is important for both class switching and somatic hypermutation by converting cytosine to uracil [4]. Uracil is removed by base excision repair leading to a single-stranded (ss) DNA break [4]. The resulting gap is usually repaired by DNA polymerase which replaces the missing nucleotide based on reading the opposing DNA strand. However, for class switch to occur, DNA polymerase fails to correct the problem. Instead, the mismatch repair (MMR) system excises the nucleotides near an ssDNA break on one allele and an ssDNA break on the other allele leading to a double-stranded DNA break [4]. In some cases, two uracils on opposing DNA strands will be close enough to form a double-stranded break without the action of MMR. Doublestranded breaks formed by either of these methods are cleaned up to form blunt ends. A blunt end in a donor switch (S) region is then recombined with a blunt end in an acceptor S region via non-homologous end joining [5] as shown in Fig. 6.3. Somatic hypermutation starts in the dark zone of the germinal center in centroblasts and continues as the cell traverses the germinal center and becomes a centrocyte. Studies have shown mutation-active periods and mutation-silent periods during which antigen selection takes place [6]. A cell that has a good fit with a presented antigen goes on to the next round of somatic hypermutation, while a cell that does not fit is targeted for apoptosis. Somatic hypermutation functions in antigen selection by producing point mutations of the V segment of the heavy- and/or light-chain genes which may lead to a single amino acid change during cell division. Over several cell divisions, multiple mutations accumulate. Still these mutations usually lead to only subtle changes in affinity to antigen compared to the original

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Fig. 6.3 Class switch of the immunoglobulin heavy-chain gene. Activation-induced cytosine deaminase (AID) changes cytosine to uracil in the switch regions ultimately leading to doublestranded DNA breaks and recombination between two different switch regions. In this example, there is class switching to IgG2

parent-naïve B cell. AID converts cytosine to uracil which is repaired, sometimes incorrectly resulting in a point mutation. Studies have shown that AID is active in non-immunoglobulin regions of the genome and may play a role in immunoglobulin translocations with other genes [7]. The effects of AID outside of the immunoglobulin loci are repaired at a high rate, whereas repair in the immunoglobulin regions is error prone, leading to mutations in 1 per 1,000 nucleotides per cell division [8]. This mechanism seems to involve the V region promoter, since somatic hypermutation occurs over a limited area downstream from the promoter and the rate of mutation is proportional to the distance from the promoter [8]. Errors in these normal physiologic B-cell processes can lead to genetic alterations that are lymphomagenic or leukemogenic. The double-stranded breaks that occur during VDJ recombination and class switching can lead to translocations involving the immunoglobulin genes such as t(14;18), t(11;14), and t(8;14). Aberrant somatic hypermutation can occur in areas of the genome other than the immunoglobulin genes leading to multiple point mutations or translocations. Testing for aberrant somatic hypermutation is not generally available; however, testing for pathologic rearrangements and physiologic VDJ rearrangements is widely used and helpful for determining clonality, supporting a diagnosis of malignancy, lymphoma subclassification, and minimal residual disease evaluation.

B-Cell Clonality Testing Clonality testing takes advantage of the fact that once a B cell has rearranged its immunoglobulin genes, every daughter cell will have the same rearrangement. Indications for gene rearrangement clonality testing include evaluation of B-cell proliferations when morphology and immunophenotype are inconclusive for malignancy, lymphoproliferations in immunosuppressed individuals (including post-transplant patients), evaluation of minimal residual disease, and comparison of

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two lymphoid malignancies for a clonal relationship. Gene rearrangement testing is not lineage specific and should not be used to establish lineage. IGH rearrangement has been detected in 4–18% of AML, 8–16% of mature T-cell lymphomas, and approximately 22% of T-lymphoblastic leukemia (T-ALL), especially CD3-negative or γδ (gamma delta) T-ALL, although lineage infidelity with IGH is less frequent than with T-cell receptor (TCR) gene rearrangements [3, 9–11]. Southern blot, once the gold standard for detecting clonal populations, is less commonly performed than PCR because it is time consuming, labor intensive, technically demanding, and requires large amounts of high-quality DNA (fresh tissue). Additionally it has a lower sensitivity than PCR, requiring the presence of 5–10% tumor cells for detection. Southern blot relies on the detection of non-germline (i.e., rearranged) DNA fragments after restriction enzyme digest. Testing of IGH and IGK is more common because these genes not only have a simple gene structure allowing the use of one to two probes but also have a large repertoire. False positives are rare and related to incomplete enzyme digestion or polymorphisms of restriction enzyme sites. False negatives are also rare as long as the DNA quality is good and adequate (5–10%) tumor cells are present. PCR has several advantages over Southern blot: it is quicker, less labor intensive, requires smaller amounts of DNA, can tolerate lower quality DNA (such as DNA obtained from fixed tissue), and has a better sensitivity. However, PCR is more prone to false positives and false negatives (especially in germinal center or post-germinal center-derived malignancies). PCR testing takes advantage of the length differences created during VDJ rearrangement, especially from the addition of N and P nucleotides and the subtraction of nucleotides. In normal or reactive B-cell populations, PCR product sizes will show a Gaussian distribution, often referred to as a polyclonal background (Fig. 6.4). A clonal B-cell population has the same immunoglobulin rearrangement in all cells and that PCR product size will predominate with or without a polyclonal background (Fig. 6.4). PCR testing usually targets the VH –JH region with consensus or family primers to at least two of FR I, II, and III and consensus primers to FR IV (Fig. 6.1);

Fig. 6.4 Example of PCR with capillary electrophoresis gene scanning using primers to FR III. The top panel shows a clonal peak. The bottom panel demonstrates a polyclonal population having a bell-shaped curve distribution of sizes in the expected range for the primer set used (71–150 bp)

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however, testing of other segments can increase diagnostic sensitivity. Testing with a single FR yields sensitivities from 50–75% depending on the primer used [12–14]. Testing with multiple FR primers increases sensitivity to approximately 80% [12–14]. Addition of primers to evaluate kappa immunoglobulin light-chain gene rearrangement increases sensitivity further to approximately 90% [12, 13, 15]. The BIOMED-2 primers target FR I, II, and III, as well as incomplete DH –JH rearrangement, IGK, and IGL. Testing of DH –JH rearrangement targets the incompletely rearranged, non-coding allele and increases the yield in germinal center/postgerminal center malignancies as an incompletely rearranged allele does not undergo somatic hypermutation [3]. BIOMED-2 primers for IGK include evaluation of Vκ –Jκ as well as rearrangements with Kde. Many studies have shown good sensitivity and specificity for detecting clonality in B-cell neoplasms versus reactive conditions when using a combination of BIOMED2 primer sets (tubes). Generally using both κ (kappa) tubes (Vκ–Jκ and Vκ/intron-RSS-Kde) with some combination of the FR I, II, or III tubes gives a sensitivity from 91 to 98%, with good DNA quality (>300–400 base pairs) [12, 13]. The DH –JH primer set may be useful in clonality detection in plasma cell neoplasms which are positive in about 60% of cases and in improving detection of marginal-zone lymphoma to >90% [12, 13]. Detection of clonality in lymphoplasmacytic lymphoma is also increased slightly with the use of the DH –JH primer set [16]. Use of a lambda primer set does not provide significant additional information [12, 13]. Because of its high sensitivity, false positives are often seen with PCR testing. These pseudoclonal or often oligoclonal populations result from the amplification of a limited benign population or repertoire. Amplification of a few B cells (for example, hypocellular samples after chemotherapy or with aplastic anemia) can lead to an apparent clonal gene rearrangement. Oligoclonal/pseudoclonal populations due to limited numbers of cells will amplify different peaks on different runs. Therefore, running a sample in duplicate (done in most laboratories) or retesting an apparently clonal population avoids this complication [12, 13]. A limited repertoire can be seen in immunosuppressed patients (including transplant patients) and in reactive lymph nodes because of the presence of antigen-selected clones. False negatives most often occur due to poor annealing of primers; therefore, primer design is very important. However, even with good primer design, somatic hypermutation can affect the primer-binding sites and lead to false negatives. As expected, false negatives are more common in B-cell malignancies that have undergone somatic hypermutation (germinal center or post-germinal center malignancies), although targeting the kappa gene rearrangements mentioned above greatly improves detection [12, 13]. Degraded poor-quality DNA and the presence of PCR inhibitors can lead to falsely negative results. Both of these occur more often when using fixed and paraffin-embedded tissue [3]. Both the type of fixative and the age of the specimen can affect PCR success. Degradation of DNA can be assessed by measuring the size of DNA fragments. Fragments less than 200 base pairs lead to extremely poor detection rates by PCR (16%), while fragments at least 300 base pairs in size lead to reasonable rates of amplification (>76–96%) [3, 12].

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Somatic Hypermutation Testing In the research setting, somatic hypermutation status of the IGH variable region (VH ) may be used to help distinguish the cell of origin of B-cell neoplasms. However, in the clinical setting, testing is usually performed to determine the VH mutational status of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) and splenic marginal-zone lymphoma. Testing for somatic hypermutation involves sequencing the VH segment of a clonal population and comparing the resulting sequence to a database of germline sequences of the different VH segments. Significant differences from the most homologous VH segment sequence indicate that the population has undergone somatic hypermutation. A difference of ≥2% is considered mutated, whereas >98% homology is considered unmutated. In CLL/SLL, unmutated VH is associated with a worse prognosis. Ongoing somatic hypermutation is indicated by detecting several different sequences from the clonal population as opposed to a single sequence. The presence of a single sequence indicates that a cell has been exposed to antigen within the germinal center and completed somatic hypermutation prior to clonal expansion and therefore is either a late germinal center or a post-germinal center B cell. The presence of ongoing somatic hypermutation suggests a cell of origin of a germinal center B cell at the stage of antigen presentation, although a more mature B-cell stage that has failed to shut off or has re-initiated somatic hypermutation is another possibility.

Follicular Lymphoma Follicular lymphoma is derived from germinal center B cells (centrocytes and centroblasts) which have rearranged heavy- and light-chain genes and have ongoing somatic hypermutation. Morphology and immunophenotype typically reflect this origin with a follicular growth pattern and expression of germinal center markers CD10 and BCL6. Rearrangement of immunoglobulin genes can be detected by PCR, although somatic hypermutation decreases the detection rate to approximately 60% by VH –JH testing. Targeting the incomplete DH –JH rearrangement and kappa light chain can increase the detection rate to > 90% [12, 13]. Follicular lymphoma is characterized by t(14;18) or variant B-cell CLL/lymphoma 2 (BCL2) rearrangements such as t(2;18) and t(18;22) which are found in up to 90% of follicular lymphomas.

Follicular Lymphoma and BCL2 t(14;18) Normal BCL2 protein plays a role in mitochondrial permeability and has an antiapoptotic effect. The BCL2 breakpoints are in the untranslated region and therefore the translated portion of BCL2 is fused to the 3 immunoglobulin gene which brings BCL2 under the influence of the immunoglobulin promoter leading to overexpression of a functional protein and decreased apoptosis. Approximately 65–70% of

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the rearrangements occur in the major breakpoint region (MBR) which is located in the untranslated region of the last exon (exon 3) and another 10% occur in the minor cluster region (mcr) which is about 30 kb outside of the BCL2 gene (Fig. 6.5). Approximately 20% occur either at the 3 -end of the BCL2 gene or 5 to the mcr and in some patients the breakpoint is unknown [17, 18]. The IGH breakpoint consistently occurs in the junctional region. Although some studies have noted different clinical characteristics associated with the location of the BCL2 breakpoint, other studies have failed to confirm those findings [17, 18]. Testing for the BCL2 rearrangement is indicated if there is a suspicion of follicular lymphoma, but clonality cannot be demonstrated by immunoglobulin gene rearrangement studies and when follicular lymphoma is in the differential of another small B-cell lymphoma displaying a nodular pattern, such as marginal-zone lymphoma with colonization of the germinal center. Testing can be done by conventional cytogenetics, FISH, or PCR. Immunohistochemical staining of BCL2 does not indicate the presence of the BCL2 translocation as other mechanisms can cause BCL2 expression and staining is positive in most small B-cell lymphomas and some normal B cells, such as mantle zone cells, and normal T cells. Conventional cytogenetics detects most cases of t(14;18) and its variants as well as other abnormalities; however, fresh tissue is not always available and there are cryptic rearrangements that require additional testing to detect. Most PCR assays have primers to only the MBR and mcr, and the detection rate of t(14;18) is about 60% [3]. Some assays have been designed with additional primers to the 5 mcr and 3 MBR breakpoint regions, but the detection rate still reaches only 60–88% [3, 19, 20]. FISH detects >90% of t(14;18) and, depending on the probe strategy,

Fig. 6.5 BCL2/IGH rearrangement at the major breakpoint region (MBR). The IGH breakpoint is consistently in the joining region. The BCL2 breakpoints are variable and include the following: the major breakpoint region (MBR) within the 3 non-coding portion of exon 3; the minor cluster region (mcr), located 20–30 kb 3 to the MBR; and additional breakpoints/clusters between the MBR and the mcr [3 BCL2, 3 MBR, intermediate cluster region (icr), and 5 mcr] in most of the remaining cases

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will usually detect variant cases; therefore, FISH is generally preferred over PCR for diagnosis [20, 21]. Positivity of BCL2 by PCR requires correlation with other information, as the t(14;18) can occur in other lymphomas, particularly diffuse large B-cell lymphomas, and can occur in the peripheral blood of healthy blood donors and in hyperplastic lymphoid tissue [22, 23]. False-negative PCR results occur with alternate breakpoints or mutations of the primer-binding sites. About 10% of nodal follicular lymphomas are t(14;18) negative by current testing methods; however, absence of a BCL2 translocation is the rule for pediatric follicular lymphoma and primary cutaneous follicle center cell lymphoma. A small subset of t(14;18)-negative follicular lymphomas have an alternate mechanism of increasing BCL2 expression, such as +18q [24]. Translocations of BCL2 are less common in grade 3B follicular lymphoma with <15% of cases positive compared to >80% positivity in grades 1 and 2 and >70% positivity in grade 3A [19]. Grade 3B follicular lymphomas frequently have alterations in BCL6 on 3q27 and other cytogenetic abnormalities similar to DLBCL [19].

Other Genetic Abnormalities in Follicular Lymphoma Since t(14;18) can be found in the blood and hyperplastic lymphoid tissues of healthy individuals, additional abnormalities are likely required for follicular lymphoma to develop [22, 23, 25]. The translocation is thought to be an early event in B-cell development leading to a prolonged life span of the B cell, giving ample time to develop other genetic defects. In fact, follicular lymphoma usually has at least one additional abnormality by routine cytogenetics such as gains of 1q, 2p, 7, 8q, 12q, 18q, and X and losses of 1p, 6q, 10q, 13q, and 17p [25]. Findings associated with a bad prognosis are thought to be late events and include gains of 1q, 12, and X and losses of 1p, 17p, and 17q [25]. Some of these same abnormalities are associated with large-cell transformation which occurs in 10–60% of follicular lymphomas (Table 6.2). Transformation to a higher grade lymphoma, usually diffuse large B-cell lymphoma, occurs in 25–35% of patients with follicular lymphoma [1]. Transformation has been associated with gains of 7, 12q, and X; losses of 4q, 13q, and 17p; inactivation of TP53 and CDKN2A; and MYC deregulation [25]. BCL6 rearrangements are common in grade 3B follicular lymphomas with a diffuse large B-cell component but are rare in lower grade follicular lymphomas and grade 3B follicular lymphomas with a pure follicular pattern [26]. Follicular lymphoma rarely has a t(8;14) which is associated with a particularly aggressive course [27]. CGH has shown chromosomal gains similar to conventional cytogenetics but also found gains in 18p and 12p in over 10% of the cases, although the significant gene(s) affected are not known [28]. Deletions by CGH include those seen by conventional cytogenetics, as well as deletions of 9p, 3q, and 11q [28]. The deletion of 9q often involves the CDKN2A and CDKN2B loci and is associated with worse overall survival [28]. The deletion of 3q involves the LIM domain containing preferred translocation partner in lipoma (LPP) gene approximately half

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Table 6.2 Genetic changes associated with higher grade (grade 3B) follicular lymphoma (FL), a poor prognosis, and transformation Grade 3B FL

Poor prognosis/transformation

Less frequent t(14;18) 3q27 abnormalities including BCL6 rearrangementsa

del 6q23-26 del 17p TP53 mutations/inactivation –1p, +12, +18p, +Xp MYC rearrangements Inactivation p16INK4A

In general these are all associated with more complex karyotypes and an increased number of abnormalities a When diffuse growth is present

of the time [28]. Deletions of 5p and 6q were also associated with a worse overall survival [28]. Prognosis in follicular lymphoma has also been linked to gene expression profiling (GEP) of the background cells, which shows two distinct signatures termed immune response 1 (IR1) and immune response 2 (IR2). IR1 displays increased expression of T-cell genes and the macrophage genes TNFSF13B and ACTN1 and has a favorable prognosis. IR2 shows increased expression of follicular dendritic cell genes and other macrophage genes and has an unfavorable prognosis [25].

Mantle Cell Lymphoma Mantle cell lymphomas (MCLs) originate from the small CD5-positive B cells that reside in the mantle zone areas surrounding germinal centers [29]. Most are thought to be derived from naïve pre-germinal center cells, while the minority with mutated immunoglobulin genes may arise from post-germinal center memory B cells [29, 30]. Virtually all MCLs have a characteristic translocation, the t(11;14)(q13;q32), that brings the CCND1 gene at 11q13 encoding cyclin D1 under control of the immunoglobulin heavy-chain locus at 14q32 [1, 29]. The net result is constitutive expression of cyclin D1 which is normally not expressed by B cells. In addition, levels of cyclin D1 are often further increased in MCL by deletions and point mutations that result in the removal of destabilization elements in the cyclin D1 mRNA leading to truncated transcripts with an increased halflife [31]. Increased levels of cyclin D1 cause deregulation of cell cycle control at the G1–S phase checkpoint by mitigating the suppressor effects of the retinoblastoma protein and the cyclin-dependent kinase inhibitors p27kip1 and p21 [29, 32]. The t(11;14)(q13;q32) is thought to occur as a mistake during the immunoglobulin gene rearrangement process in early B-cell development and is necessary but not sufficient for the subsequent development of MCL [29].

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Detection of Cyclin D1 Dysregulation The diagnosis of MCL usually requires direct or indirect demonstration of an t(11;14)(q13;q32) [1]. Only very rare cases of MCL lack t(11;14)(q13;q32) and as a result are difficult to diagnose with certainty using standard techniques [1, 33]. The few cases of MCL that do not have t(11;14)(q13;q32) typically show abnormal expression of cyclin D2 or cyclin D3 [1, 33]. Testing for t(11;14)(q13;q32) should generally be performed on all CD5+ small B-cell neoplasms that do not have the characteristic phenotypic and morphologic features of CLL/SLL. In addition, t(11;14)(q13;q32) testing is also appropriate for B-cell neoplasms that do not fit into other diagnostic categories since MCL may occasionally lack CD5 and/or have other unusual features [1]. In most cases, indirect testing for t(11;14)(q13;q32) by immunohistochemical staining paraffin-fixed tissue section for cyclin D1 that has histologic evidence of lymphoma is sufficient for diagnosis [1]. Although other small B-cell neoplasms should be negative, cases of hairy cell leukemia as well as the proliferation centers of CLL/SLL may sometimes show increased reactivity for cyclin D1, creating a potential diagnostic pitfall [34, 35]. In addition, histiocytes and endothelial cells which can be admixed with lymphoma cells may normally express cyclin D1. Also, approximately 20% of plasma cell myeloma cases can express elevated levels of cyclin D1 secondary to having a t(11;14)(q13;q32) and often have a more lymphoid cytologic appearance than do typical plasma cells [36]. In suspected cases of MCL that have equivocal cyclin D1 staining results and/or other unusual features, testing for t(11;14)(q13;q32) by FISH is the method of choice. FISH testing for t(11;14)(q13;q32) can be reliably performed using standard paraffin-embedded fixed tissue biopsies and has a sensitivity of over 95% for MCL [37, 38]. Because of the variability in t(11;14)(q13;q32) breakpoints, molecular PCR-based testing is informative in only approximately 40–50% of cases [38, 39]. Classical cytogenetics and Southern blot analysis can also be used for detection of t(11;14)(q13;q32), but both methods require fresh non-fixed tissue or cells, are relatively expensive and time consuming, and are only about 70% sensitive [40].

Other Genetic Abnormalities in MCL Most MCLs also have large numbers of other detectable genetic abnormalities including gains, losses, and high copy amplification of particular chromosomal regions [29, 32, 41]. In particular, gains of 3q25-qter have been reported in 30–50% of cases, 7p21–22 gains and 8q21-qter gains in 15–35%, and gains of 18q11–23 in 16% of cases [1, 29]. Frequent areas of chromosome loss include 1p13–31 in 30–50% of cases, 6q23–27 in 20–40%, 9p21–22 in 20–30%, 9q21-qter in 20–30%, 11q22–23 in 20–60%, 13q11–13 in 25–55%, 13q14–34 in 40–50%, and 17p13-pter in 20–45% of cases [1, 29]. In addition to the above listed structural abnormalities, inactivating mutations of the ATM gene at 11q22–23 appear to be present in 40–75% of MCL cases [42]. Abnormalities of the 8q24 locus that contains the MYC gene are not common but have been reported in very aggressive MCL [43].

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Clinical Implications Most MCLs are aggressive with patients typically experiencing only short responses to current treatments and having median survivals of only 3–4 years [1, 29]. However, small numbers of MCL patients have been identified with very indolent clinical courses, even without receiving treatment, indicating that the clinical behavior of MCL can be highly variable [29, 44, 45]. Recent studies have suggested that MCL in patients who experience indolent disease may have relatively few if any identifiable genetic abnormalities other than the t(11;14)(q13;q32), unlike the majority of MCL [29, 46]. Gene expression array profiling of large numbers of MCL cases has identified a proliferation signature using 20 genes that can divide patients into four prognostic groups with median survivals ranging between 10 months (most aggressive group) and 6.7 years (least aggressive group) [47]. As might be expected, given these findings, more routinely used measures of cell proliferation such as the mitotic index or percentage of Ki-67 positively stained cells have also been negatively correlated with survival [48]. The negative survival impact of 3q region gains, or 9p, 9q, and 17p region losses which are often present in clinically aggressive cases, appears to be independent of the array-based proliferation score [29], indicating that multiple measures of prognosis may need to be considered to optimize treatment decisions for MCL patients. Although clinical tests for many of the cytogenetic abnormalities frequently seen in MCL are not readily available, quantitative PCR assays for copy number and other MCL alterations have been reported that may become suitable for more routine prognostic stratification [49]. Unlike CLL/SLL, the mutational status of the expressed immunoglobulin heavy-chain variable gene segments (VH) does not appear to have prognostic value [45, 50]. However, MCLs appear to show preferential use of certain VH gene segments relative to normal CD5+ B cells, indicating that direct antigen receptor stimulation may be playing a positive role in lymphoma cell development and growth [50, 51]. Moreover, the use of particular VH gene segments such as V3–21 has been associated with increased survival and fewer genetic alterations [46, 50, 51].

Diffuse Large B-Cell Lymphoma Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity, the minority of which falls into defined categories (Tables 6.3 and 6.4) with specific morphologic, immunophenotypic, and molecular features, and the majority are referred to as DLBCL, not otherwise specified. These are a heterogeneous group of tumors that can be subtyped by different gene expression profiling signatures. Subtyping of DLBCL by comparing signatures to normal B cells has identified two distinct signatures: germinal center B-cell (GC) type, which has a profile similar to germinal center B cells, and the post-germinal center or activated B-cell (ABC) type, which has a profile like activated peripheral B cells, although some cases do not display either signature [52]. Alternative clustering methods have been used to divide DLBCL based on potential

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S.L. Yohe et al. Table 6.3 Genetic alterations in specific diffuse large B-cell subtypes

Entity

Recurrent abnormalities

T-cell-rich, 4q and 19p anomalies histiocyte-rich only seen by CGH DLBCL Primary DLBCL BCL6 rearrangements of CNS Biased use of VH 4/34 PIM-1, MYC, RhoH/TTFn, and PAX5 6q del and gains of 12q and 22q Gains of 18q21 and copy number increase in BCL2 and MALT-1 Deletions at 9p21 affect CDKN2A/p16INK4A array CGH 6p21.3 (HLA region) No t(14;18) Similar to DLBCB, NOS Primary BCL-6, MYC, and IgH cutaneous rearrangements DLBCL, leg High-level amplifications type of 18q21.31–q21.33 including BCL-2 and MALT1 del of 9p21.3 (CDKN2A and CDKN2B) No t(14;18) EBV+ DLBCL None reported of the elderly

Immunoglobulin gene SHM Rearranged Ongoing SHM Rearranged Ongoing SHM (< 27%)

Gene expression profiling

Cell of origin

Host immune- GC B cell response profile Activated (late) GC B cell

Rearranged Ongoing SHM (some cases)

ABC type

Peripheral post-GC B cells

Rearranged

Unknown

Mature B cell transformed by EBV

DLBCL, diffuse large B-cell lymphoma; SHM, somatic hypermutation; GC, germinal center; CNS, central nervous system; NOS, not otherwise specified; ABC, activated B cell; EBV, Epstein–Barr virus

pathogenetic mechanisms into three groups: oxidative phosphorylation, BCR(Bcell receptor)/proliferation, and host response [53]. Although the prognosis in these groups is similar, identification of such groups provides insight into pathogenesis and may help guide research for targeted therapy [53].

BCL6 Alterations in DLBCL The B-cell CLL/lymphoma 6 (BCL6) gene, located on chromosome 3q27, encodes a zinc finger protein that is a transcriptional repressor normally expressed in germinal

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Table 6.4 Genetic alterations in other lymphomas of large B cells Entity

Recurrent abnormalities

Primary mediastinal (thymic) +9p24, +2p15, large B-cell lymphoma +Xp11.4–21, +Xq24–26 Intravascular large B-cell Unknown lymphoma DLBCL associated with chronic inflammation Lymphomatoid None granulomatosis ALK-positive DLBCL t(2;17) (CLTC-ALK) t(2;5) less common Plasmablastic lymphoma None Large B-cell lymphoma arising in HHV-8-associated multicentric Castleman disease Primary effusion lymphoma

Gene expression profiling

Other

Similar to classical Hodgkin lymphoma

Negative

Unknown

Negative

Distinct profile

EBV positive

Unknown

EBV positive

Unknown

Negative

Unknown

EBV positive 60–75% EBV negative HHV8 positive

Unknown

Unknown

None

Distinct profile

EBV positive HHV8 positive

DLBCL, diffuse large B-cell lymphoma; EBV, Epstein–Barr virus; HHV, human herpes virus

center B cells but downregulated with maturation into plasma cells. Expression of BCL6 appears to block differentiation to memory B cells and inhibit apoptosis. BCL6 translocations are the most common translocation found in DLBCL but other abnormalities, such as gains/amplifications or mutations, involving BCL6 also occur [54]. Approximately 40% of DLBCLs show some alteration of BCL6 which is more common in the ABC type than the GC type [54, 55]. These genetic changes do not have a uniform effect on BCL6. Although constitutive activation of BCL6 is a frequent outcome, not all cases display protein overexpression [54, 56]. Differential binding of BCL6 protein to its normal target genes has been described and may explain the variability in protein expression [56]. Increased BCL6 protein expression has been associated with a better prognosis [54, 57]. Changes in BCL6 are not limited to DLBCL and are seen in other lymphomas, as well as non-hematologic malignancies. BCL6 translocations occur more commonly with ABC-type DLBCL and partner with IGH about half the time [54]. The translocations generally bring BCL6 under the effect of a new promoter [25]. BCL6 translocations have also been found in primary mediastinal DLBCL [54], cutaneous diffuse large B-cell lymphoma, leg type [58], follicular lymphoma, and nodular lymphocyte-predominant Hodgkin lymphomas [59, 60]. The breakpoint on BCL6 is most commonly in the major breakpoint region (MBR) which spans the non-coding exon 1 and 5 region of the first

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intron, but a few cases occur at an alternative breakpoint region [61]. As would be expected with alternate breakpoints and multiple translocation partners, PCR testing for BCL6 translocations has a poor detection rate and FISH with a break-apart probe for BCL6 is the preferred method of testing for BCL6 translocations. A BCL6 translocation is not specific for DLBCL, and there is no clear association with prognosis; therefore, routine clinical testing for BCL6 translocation is not recommended currently. Mutations of BCL6 are common in DLBCL and involve exon 1 and the 5 region of intron 1. Multiple mutations are often present suggesting aberrant somatic hypermutation. The study by Iqbal et al. [54] detected higher messenger RNA (mRNA) levels and a trend toward higher protein levels in DLBCL cases with BCL6 mutations.

Other Genetic Alterations in DLBCL Many other genetic alterations have been found in DLBCL, including other translocations, amplifications, aberrant somatic hypermutation, deletions, and inactivation. Genetic alterations vary with the type of DLBCL. GC-type DLBCL is more frequently associated with t(14;18), amplification of REL on chromosome 2p, and gain of 12q [25]. BCL2 translocations, such as the t(14;18) seen in follicular lymphoma, occur in 20–30% of the GC-type DLBCL [25]. REL is a transcription factor in the nuclear factor kappa B (NF-κB) family. The NF-κB pathway is also altered in the ABC-type DLBCL, with constitutive activation of NF-κB being described. Other changes seen primarily in the ABC type are gains of 3q and 18q, loss of 6q (including PRDM1), and inactivating mutations of PRDM1 [25]. MYC rearrangements occur in up to 10% of DLBCLs and are associated with a worse prognosis even in rituximab-treated patients and often, but not always, a high proliferative rate at >90% by Ki67 [1, 25, 62, 63]. MYC-positive DLBCLs are often indistinguishable from DLBCLs without MYC translocations [62]. The partner of the rearranged MYC is an immunoglobulin gene in 60% of cases [1]. Aberrant somatic hypermutations in genes, such as PIM1 (a protooncogene), MYC, RHOH (a RAS family GTPase), and PAX5, occur in more than 50% of DLBCLs [25]. Immunohistochemical stains can be used to categorize DLBCL into germinal center like or ABC type, although the correlation with gene expression profiling is not perfect. Cases that are CD10 positive or BCL6 positive and MUM1 negative are germinal center like and all other staining patterns are the ABC type [64, 65]. Different chromosomal abnormalities are found in these two entities as well with BCL2 rearrangements and gains of 12q12 occurring in the germinal center-type DLBCL, while 3q27 abnormalities, gains of 18q21–q22, and losses of 6q21–q22 occur more often in the ABC-type DLBCL. As a group, DLBCL shows rearrangement of the immunoglobulin genes and somatic hypermutation in the variable regions. As expected, only the GC type of DLBCL has ongoing somatic hypermutation [1]. Early studies showed the GC subtype to have a better prognosis with a

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50–60% 5-year survival, compared to 15–30% 5-year survival for the ABC subtype. More recent studies, with rituximab as a part of standard therapy, have had conflicting results. A gene expression profiling study by Lenz et al. confirmed a better overall and progression-free survival in the GC type of DLBCL; however, other studies showed no survival difference between the GC and ABC subtypes as identified by immunohistochemistry [66–68]. Gene expression profiling of the nonmalignant background cells has shown two distinct signatures that are associated with outcome. One signature, referred to as stromal 1, has expression of genes that encode extracellular matrix components and remodeling proteins and macrophage genes and is associated with a better prognosis [66]. A second signature, referred to as stromal 2, has expression of endothelial genes and genes associated with angiogenesis and is associated with a poorer prognosis [66]. Both the stromal 1 and stromal 2 gene expression profiles were seen in GC and ABC types of DLBCL [66]. Expression of BCL2 protein by immunohistochemical staining has been associated with prognosis. In general, BCL2 positivity is associated with a worse prognosis, although studies vary as to whether the prognostic difference occurs in the GC type or non-GC type of DLBCL [65, 69]. Prognosis is also affected by the presence of histologic and molecular bone marrow involvement. Patients with histologic marrow involvement have the poorest 5-year survival of 12% [70]. However, patients without histologic involvement but a positive gene rearrangement study have a 5-year survival of 37% compared to 66% for patients who lack both [70].

Marginal-Zone Lymphomas Extranodal marginal-zone lymphomas of mucosa-associated lymphoid tissue (MALT lymphomas) represent the majority of lymphomas that arise outside of primary hematopoietic tissues (lymph node, spleen, bone marrow) [1]. The cell of origin is thought to be a post-germinal center memory B cell which normally resides in the marginal zones that surround follicular mantles. As would be expected based on the cell of origin, the vast majority of MALT lymphomas lack expression of CD5 and CD10 [1]. MALT lymphomas develop at sites that do not normally have lymphoid tissue but where lymphoid tissue has been acquired in response to a chronic infection or an autoimmune disease [71]. The most common site of MALT lymphoma development is the stomach, where Helicobacter pylori is the infectious agent causing acquisition of the reactive precursor MALT [72, 73]. MALT lymphomas that develop in the salivary gland or thyroid are preceded by reactive infiltrates related to the autoimmune diseases Sjögren’s syndrome and Hashimoto’s thyroiditis, respectively [1]. The highly restricted use of certain VH gene segments by salivary gland lymphomas implicates direct antigen stimulation mediated through the immunoglobulin receptor complex as playing an important role in lymphoma development [74], while in the stomach the importance of H. pylori-specific

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T cells to lymphoma cell growth and survival highlights the complementary role of indirect antigen stimulation [75]. With continued antigenic stimulation, clonal B-cell populations sometimes develop in the acquired infiltrates with molecular and genetic abnormalities that give rise to lymphomas [76, 77].

Genetic Abnormalities in MALT Lymphomas Four recurrent balanced translocations have been reported in MALT lymphomas, t(11;18)(q21;q21), t(14;18)(q32;q21), t(1;14)(p22;q32), and t(3;14)(p14.1;q32) [76, 77]. The t(11;18)(q21;q21) fuses the amino end of API2 at 11q21 to the carboxyl terminal of MALT1 at 18q21, generating a chimeric fusion protein that activates NF-κB. The t(14;18)(q32;q21) and the t(1;14)(p22;q32) result in deregulation of MALT1 and BCL10 at 1p22 by bringing them under the control of the immunoglobulin heavy-chain (IgH) locus at 14q32, which also result in the activation of the NF-κB pathway. The more recently identified t(3;14)(p14.1;q32) results in the deregulation of FOXP1 (forkhead box protein P1). The incidence of these four translocations varies greatly depending on the lymphoma site (Table 6.5), with t(11;18)(q21;q21) being more common in gastric, intestinal, and lung MALT lymphomas, while the t(14;18)(q32;q21) and t(3;14)(p14.1;q32) more often identified in salivary gland, and ocular MALT lymphomas [78–80]. These observations suggest that MALT lymphomagenesis has location-specific features that may in turn depend on the type of antigenic stimulation triggering the precursor-reactive infiltrates. The concept of site-dependent factors affecting MALT lymphoma development is further supported by these translocations being mutually exclusive [78]. In addition, the frequency of MALT lymphoma-associated translocations may also vary with geographical region, in that European-based studies have found higher incidences of t(11;18)(q21;q21) in gastric MALT lymphomas relative to North American-based studies, while t(3;14)(p14.1;q32), identified in 10% of European MALT lymphoma Table 6.5 Frequencies (%) of MALT lymphoma translocations and trisomies

Site Stomach Intestine Lung Salivary gland Ocular adnexa Thyroid a Left

t(11;18)a API2– MALT1

t(14;18)a IgH– MALT1

t(1;14)a IgH– BCL10

t(3;14)a IgH– FOXP1

Trisomy 3b

Trisomy 18b

5, 24 42, 12 31, 53 0, 1

5, 1 0, 0 10, 7 0, 12

0, 0 0, 12 2, 7 0, 2

0, 0 0, 0 0, 0 0, 0

11 75 20 55

6 25 7 19

0, 1

0, 24

0, 0

0, 20

38

14

0, 17

0, 0

0, 0

0, 50

17

0

most data is from North American study of Remstein et al. [78] and right most data is from European studies of Streubel et al. [79, 80] b Data from Streubel et al. [79]

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cases, was not detected in a large North American study (Table 6.5) [78–80]. In addition to the translocations noted above, trisomies of chromosomes 3 and 18 are also common, being present in 25–40% of cases (Table 6.5) [78, 79]. The presence of trisomies often occurs in cases that do not show evidence of translocations, indicating that testing for both types of genetic abnormalities is advisable [78].

Detection of MALT Lymphoma Translocations A definitive diagnosis of MALT lymphoma can often be difficult to render because of the presence of the precursor-reactive infiltrate in many biopsy specimens. IGH rearrangement studies can be used to detect clonal B-cell populations. Detection of one of the MALT lymphoma-associated translocations or trisomies would have a more significant diagnostic impact, especially with equivocal histologic and/or immunophenotypic findings, and strongly favor a diagnosis of MALT lymphoma. Clinical testing for t(11;18)(q21;q21) is often done by RT-PCR, which works well for small tissue specimens typically obtained from endoscopic procedures. Moreover, it is also well suited for fixed paraffin-embedded specimens typically used for histology, being able to detect 96% of t(11;18)(q21;q21) with only three primer sets. FISH is also used by many labs for detection of t(11;18)(q21;q21), although perhaps being slightly less sensitive than PCR in some cases. Clinical testing for detection of t(14;18)(q32;q21) as well as for trisomies 18 and 3 is also widely available and usually done by FISH. Tests for detection of the less frequently encountered t(1;14)(p22;q32), and t(3;14)(p14.1;q32) are presently limited to research laboratories.

Clinical Implications Besides having diagnostic importance, the presence of t(11;18)(q21;q21) also has prognostic and treatment-related significance. MALT lymphomas with t(11;18)(q21;q21) are much more likely to be present in regional lymph nodes and other distal sites at diagnosis, and are less likely to undergo transformation to large-cell lymphomas [71–81]. Moreover, gastric MALT lymphomas that harbor t(11;18)(q21;q21) generally do not respond to antibiotic treatments that eliminate H. pylori, while complete responses can be obtained with this approach in 70% or more of other gastric MALT lymphomas [76, 82].

Other Marginal-Zone Lymphomas Nodal marginal-zone lymphomas (MZLs) resemble other types of marginal-zone lymphomas but differ by originating from lymph node-based marginal-zone B cells and do not show evidence of extranodal or splenic involvement [1]. The four

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translocations associated with MALT lymphomas described above are not found in nodal MZLs [83]. Splenic MZLs originate from spleen-based marginal-zone B cells that phenotypically differ from other marginal-zone B cells in frequently expressing IgD along with IgM [1]. MALT-associated translocations are also not seen, but approximately 40% of cases show allelic loss of 7q31–32 which is also associated with more aggressive disease [84]. Similar to CLL/SLL, about half of splenic MZL cases have mutated VH genes and about half have unmutated VH genes, and those cases with unmutated VH genes have a more aggressive clinical course [85]. However, the VH gene mutational status may not be independent of the effect of 7q31–32 loss, which occurs primarily in those cases with unmutated VH genes. More recently, gene expression profiling has suggested that survival of splenic MZL patients is negatively associated with the expression of CD38 and genes associated with the NF-κB pathway [86]. Both mutated and unmutated splenic MZLs also show biased use of the VH1–2 segment, which may be expressed by approximately 40% of cases [85, 87], further supporting a role for direct antigen receptor stimulation in splenic MZL development. Splenic MZL has a unique transcriptional profile compared to other small B-cell lymphomas with expression of genes involved in the AKT1 signaling pathway [88].

Burkitt Lymphoma Burkitt lymphoma (BL) is an aggressive, rapidly proliferating tumor characterized morphologically by medium-sized monotonous cells with many mitoses and apoptotic cells. Macrophages with apoptotic debris are scattered throughout the tumor giving the classic “starry sky” pattern. The cells have an immunophenotype of germinal center B cells and express B-cell markers, CD10, and BCL6 but are negative for BCL2. The high rate of proliferation is demonstrated by staining with Ki67 which is nearly 100% positive in the tumor cells. Translocations of MYC are present in about 95% of cases, with t(8;14) being present 80% of the time and t(2;14) or t(14;22) comprising the remainder of cases [1]. Rearrangement is more common with the kappa light-chain gene than with the lambda light-chain gene. There are three main types of BL which differ in their epidemiology, clinical characteristics, EBV involvement, and MYC and immunoglobulin breakpoints (Table 6.6).

Burkitt Lymphoma and MYC MYC [v-myc myelocytomatosis viral oncogene homolog (avian), also known as C-MYC] on chromosome 8q24 encodes a nuclear phosphoprotein that functions as a transcription factor and plays a role in cell cycle progression, apoptosis, and cellular transformation. Two isoforms exist that result from alternate translational start signals. Synthesis of the longer isoform is suppressed in BL. Endemic and EBV-positive BLs have the MYC breakpoint far 5 from the MYC gene (class III

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Table 6.6 Differences between endemic, sporadic, and immunodeficient Burkitt lymphomas (BLs)

Geographic distribution Anatomic predilection EBV+ IGH breakpoint MYC breakpoint Other

Endemic BL

Sporadic BL

Immunodeficient BL

Equatorial Africa, Papua, New Guinea Jaws, facial bones (50%) ∼100% VDJ Class III

Worldwide

Worldwide

Abdominal

Nodal

∼30% Cμ switch region Classes I and II

25–40% VDJ Class III HIV+

breakpoint) and the IGH breakpoint in the VDJ region suggesting occurrence during somatic hypermutation and show a high rate of somatic hypermutation without ongoing mutation, suggesting a post-germinal center B-cell or memory B-cell origin [6, 89, 90]. Sporadic and EBV-negative BLs have an IGH breakpoint in the class switch region and the MYC breakpoint occurs in exon 1 or intron 1 (class I breakpoints) or close 5 from the MYC gene (class II breakpoints) as shown in Fig. 6.6, and have a low rate of somatic hypermutation, suggesting an early germinal center B-cell origin such as a centroblast [6, 89, 90].

Fig. 6.6 MYC/IGH rearrangement in endemic (eBL) and sporadic (sBL) Burkitt lymphoma. In eBL, the IGH breakpoint is in the DH JH region and the MYC breakpoint is far 5 from exon 1 of MYC (class III). In sBL, the IGH breakpoint is in the switch region of CH and the MYC breakpoint is either in exon or intron 1 (class I) or toward the 5 -end but close to exon 1 (class II)

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Testing for MYC translocation is done to confirm a diagnosis of classic BL and may be helpful in cases that are atypical for BL; however, some cases of DLBCL and cases intermediate between BL and DLBCL have MYC translocations [62, 63, 91]. A final diagnosis in these cases must take into account the genetic changes with morphology and immunophenotype. Conventional cytogenetics can detect many cases of t(8;14) and its variants as well as other abnormalities; however, there are cryptic rearrangements that require additional testing to detect. The breakpoints occur over too large a region to be amplified by standard PCR; however, long-range PCR techniques have reported detection rates up to 87% in cases of sporadic BL with t(8;14) [92, 93]. The breakpoint in endemic BL yields too large a product to be detected even with long-range PCR and this method does not detect translocations with kappa or lambda immunoglobulin light-chain genes, making the overall detection of MYC translocations lower. Long-range PCR assays generally use the MYC/04 primer to exon 2 of the MYC gene and primers to JH , Cμ, Cγ, and Cα and yield PCR products ranging in size from 1.5 to 12 kb [93, 94]. The sensitivity for detection is 1 in 1,000 to 1 in 10,000 cells; therefore it can be used to monitor minimal residual disease [93, 94]. FISH detects about 90% of t(8;14) and, depending on the probe strategy, will usually detect variant translocations; therefore, FISH is generally preferred over PCR for diagnosis [95]. The presence of t(8;14), t(2;8), or t(8;22) is not synonymous with a diagnosis of Burkitt lymphoma as it can be present in DLBCL and rarely in transformed follicular lymphoma [1].

Other Genetic Abnormalities in Burkitt Lymphoma Additional genetic events can occur in BL and commonly involve the CDKN2A (p14ARF and p16INK4a )–MDM2–p53 pathway and the BCL2 family of proteins through BIM which binds and inactivates BCL2. Mutations of TP53 occur in about 30% of BL, whereas inactivation of CDKN2A (p14ARF) and overexpression of MDM2 are less common but represent alternative mechanisms to inhibit p53 [96]. CDKN2A produces several proteins, including p16INK4a and p14ARF, through alternate transcription. MDM2 blocks the transactivation domain and exports p53 to the cytoplasm for degradation, while p14ARF inhibits MDM2. Therefore both overexpression of MDM2 and inactivation of p14ARF lead to decreased expression of p53 [96]. Inactivation of CDKN2A (p16INK4a) by promoter methylation occurs in a substantial number of cases and affects the retinoblastoma (Rb) protein by preventing phosphorylation. Other mechanisms of inactivating CDKN2A, such as deletions and point mutations, occur but less commonly [96]. Chromosome abnormalities in addition to MYC translocations are common occurring in 92% of pediatric cases; gains of 1q and 7q have been seen and are associated with a poor outcome [25, 97, 98]. However, most cases have a relatively simple karyotype with only a few additional abnormalities [25]. Presence of t(14;18) is associated with an aggressive clinical course and a poor prognosis [91, 99]. Lymphomas with features of both BL and DLBCL tend to have a more complex karyotype than does BL, and although 35–50% have MYC translocations, the

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partner is often not an immunoglobulin gene [1, 100]. It is more common to have BCL2 or BCL6 translocations with a MYC translocation (a double-hit lymphoma) in these indeterminant lymphomas rather than in either BL or DLBCL and a complex karyotype with MYC rearrangement by CGH with > 6 abnormalities) [1, 100–102] (Table 6.7). Gene expression profiling shows a signature for BL that is distinct from DLBCL and can categorize some of these cases; however, even with this technique, intermediate cases are found [100, 103]. Table 6.7 Genetic differences between Burkitt lymphoma (BL), diffuse large B-cell lymphoma (DLBCL), and lymphomas intermediate between BL and DLBCL Genetic features

BL

Intermediate BL/DLBCL

DLBCL

MYC rearrangement IG-MYCa Non-IG-MYCa BCL2 without MYC rearrangement BCL6 without MYC rearrangement Double hitb MYC-simple karyotypec MYC-complex karyotypec

Yes (95%) Yes No No No No Yes Rare

Common ∼30% ∼20% Rare Rare ∼50% Rare Common

Rare Rare Rare 20–30% 30–40% Rare Rare Rare

a IG-MYC

includes translocation with immunoglobulin heavy- or light-chain genes lymphomas contain either a BCL2 or a BCL6 rearrangement in addition to an MYC rearrangement c Complex karyotype by array CGH has more than six abnormalities, while a simple karyotype shows no or only a few cytogenetic or CGH abnormalities in addition to the MYC rearrangement b Double-hit

Lymphoplasmacytic Lymphoma Lymphoplasmacytic lymphoma (LPL) is thought to originate from post-follicular center B cells that show some capacity to differentiate into plasma cells. Most cases of LPL express IgM and those showing bone marrow involvement and an IgM paraprotein of any concentration meet criteria for the entity termed Waldenström’s macroglobulinemia [1]. The diagnosis of LPL is one of exclusion and can often be difficult to differentiate from marginal-zone lymphoma using only histology and immunohistochemical staining [1]. However, LPL has no specific recurrent chromosomal or molecular abnormalities; so detecting molecular changes associated with marginal-zone or other lymphomas can help rule out LPL. Contrary to earlier reports, the t(9;14) translocation, which brings PAX5 on chromosome 9 under regulation of the IgH gene on chromosome 14, is only occasionally found in well-characterized LPL [104]. Deletion of 6q may be present in up to 50% of bone marrow-based LPL but is not specific for LPL and is rarely reported in tissue-based LPL [105, 106]. However, those cases with 6q deletions have been reported to have more aggressive disease and worse prognoses [107]. Trisomies of

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chromosome 4 have been reported in approximately 20% of cases of Waldenström’s macroglobulinemia [108].

Molecular Testing for T-Cell Non-Hodgkin lymphoma (T-NHL) T-Cell Biology and Maturation As with B cells, knowledge of the developing T-cell and T-cell receptor (TCR) rearrangement is important for understanding molecular clonality testing. Most αβ (alpha beta) T cells are part of the adaptive immune system, responding to a variety of antigens. T-cell receptors recognize antigens that are presented by major histocompatibility complex (MHC) class I and II proteins on other cells. Given the large number and unpredictable makeup of antigens, mechanisms must be in place to create a wide range of T-cell receptors (repertoire) with a limited number of genes. The first step in creating this diversity is rearrangement of the individual T-cell receptor genes, which occurs in T cells in the thymus. Additional diversity is created by addition and subtraction of nucleotides at the sites of rearrangement and pairing of different chains. These differences are responsible for the polyclonal population of T cells in normal individuals. Rearrangement of the TCR genes is similar to rearrangement of the immunoglobulin genes. TCR beta (TRB) and TCR delta (TRD) are similar to IGH and have variable, diversity, and joining regions. TCR alpha (TRA) and TCR gamma (TRG) lack the diversity region similar to the immunoglobulin light-chain genes. T-cell receptors differ from immunoglobulins in that TRB only pairs with TRA and TRD only pairs with TRG defining two subsets of T cells: alpha beta (αβ) T cells and gamma delta (γδ) T cells. Furthermore, TRD is unique because it is entirely located within the TRA gene locus and is therefore deleted when TRA rearrangement takes place (Fig. 6.7). Lymphoid progenitors migrate from the bone marrow to the thymus, where they are triggered to become T cells and undergo TCR rearrangement. The earliest T cells

Fig. 6.7 The TRA locus contains 70–80 variable (V) regions and 61 joining (J) regions. TRD has eight V regions interspersed with TRA but can also rearrange with TRA V regions. The three D and four J regions of TRD are located between the shared variable region and the remainder of TRA and are deleted with rearrangement of TRA

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are CD3-negative and CD4- and CD8-negative (double-negative) thymocytes. TRD on chromosome 14q12 rearranges first followed by TRG on chromosome 7p15. If no further rearrangement takes place, the cells become γδ (gamma delta) T cells which remain negative for CD4 and CD8. However, cells that become αβ (alpha beta) T cells will rearrange TRB on chromosome 7q32. Successful rearrangement of TRB leads to expression of CD4 and CD8 (double-positive thymocytes), proliferation, and subsequent rearrangement of TRA on chromosome 14q12. Several different T cells with the same TRB will have different TRA rearrangements increasing diversity, which approximates 5.8 × 106 for TRB and TRA combinations. Addition and subtraction of nucleotides adds about 2 × 1011 possibilities for a total of about 1018 αβ (alpha beta) T-cell repertoire [2]. Mature αβ (alpha beta) T cells express either CD4 or CD8. The majority of T cells are αβ (alpha beta) T cells and both TRA and TRB have much greater diversity than do TRG and TRD. TRB is a highly complex gene with 52 V regions of which 39–47 are functional and two different sets of D and J regions [2, 3] (Fig. 6.8).

Fig. 6.8 The TRB locus contains 52 variable (V) regions (39–47 are functional), a diversity (D) region with six associated joining (J) regions and a constant region (Cβ1), and a second D region with seven associated J regions and a constant region (Cβ2). Because of the two separate D and J regions, it is possible to have two Dβ–Jβ rearrangements on a single allele

Because of the latter there may be two different DB –JB rearrangements present on one allele. The first DB region has six corresponding JB regions, while the second DB region has seven JB regions. TRA with 70–80 functional V regions and 61 J regions is also a complex gene [2, 3] (Fig. 6.7). The TRD V regions are interspersed with the TRA V regions, while the TRD D, J, and C regions are located between the shared V region and the TRA J region (Fig. 6.7). Therefore, when TRA undergoes rearrangement of the VA and JA segments, the TRD regions are lost. The TRD and TRG loci have less diversity and a more limited repertoire (Figs. 6.7 and 6.9). Although TRG rearrangement is present in both αβ (alpha beta) and γδ (gamma delta) T cells, the TRG gene has 14 variable regions of which only 10 are functional, 5 J segments, 2 C segments, and a limited number of N and P nucleotides; therefore, not only is there less diversity but the length differences between different rearrangements are only 20–30 base pairs versus about 60 base pairs for IGH [2]. TRD has three D and four J regions located between the shared V segments and the TRA J region. TRD has eight V regions, but it can also use some of the TRA V regions [2]. Both the TRG and the TRD loci show preferential rearrangement of

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Fig. 6.9 The TRG locus contains 14 variable (V) regions of which only 10 are functional and undergo rearrangement, 5 joining (J) regions, and 2 constant regions (C). Primers are generally designed against V1–V8, V9, V10, and V11 (forward arrows) with multiple primers against the J regions (reverse arrows). JP1, T-cell receptor gamma joining P1; JP, T-cell receptor gamma joining P; J1, T-cell receptor gamma joining 1; JP2, T-cell receptor gamma joining P2; J2, T-cell receptor gamma joining 2

the variable regions at particular anatomic sites after birth. For example, most γδ (gamma delta) T cells in the intestines and the spleen express region Vδ1, Vδ2 is preferred in the skin, and Vγ9/Vδ2 predominates in peripheral blood γδ (gamma delta) T cells in adults [3]. Unlike the immunoglobulin genes, the TCR genes are not commonly involved in translocations in T-cell leukemias or lymphomas. The exception is T-cell prolymphocytic leukemia (T-PLL), where about 90% of cases have activation of TCL1A and TCL1B on 14q32 by inv(14q11–q32) or t(14;14)(q11;q32) and placement next to TRA [1].

T-Cell Clonality Testing Clonality testing takes advantage of the fact that once a T cell has rearranged its TCR genes, every daughter cell will have the same rearrangement. Indications for gene rearrangement clonality testing include evaluation of suspicious T-cell proliferations, lymphoproliferations in immunosuppressed individuals (including post-transplant patients), evaluation for minimal residual disease, and comparison of two lymphoid malignancies for a clonal relationship. Gene rearrangement testing is not lineage specific and should not be used to establish lineage. TCR rearrangement occurs in 40–70% of B-ALL, 4–14% of AML, and 2–10% of mature B-cell malignancies [3, 9, 109, 110]. Southern blot testing usually targets TCRβ because this gene not only allows the use of one to two probes but also has a large repertoire of possible rearrangements. Southern blot depends on the detection of non-germline (i.e., rearranged) DNA fragments after restriction enzyme digest. TRB gene rearrangement is present in virtually all αβ (alpha beta) T-cell lymphomas, 95% of CD3-positive T-ALL, and 80% of CD3-negative T-ALL [3]. Limitations and the occurrence of false positives and false negatives are the same as for testing IGH (see B-cell Clonality Testing section).

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PCR for TCR gene rearrangement generally targets TRG because primer design is simpler, (Fig. 6.9) although BIOMED-2 primers also target TRB and TRD. The TRA gene is so complex that analysis of it is generally not attempted. TRG gene rearrangements are detected overall in approximately 80%-90% of T-cell lymphomas with the incidence varying between subtypes and techniques [8]. TRG detection rates are better (>90%) for T-lymphoblastic leukemia (T-ALL), T-LGL, and T-PLL [3]. Improved overall detection rates of approximately 95% have been seen with the BIOMED-2 primer sets for both TRG and TRB [9, 111, 112]. Testing with the full BIOMED-2 set of primers against TRG, TRB, and TRD has a sensitivity of 98% and specificity of 93% for T-cell neoplasms, as long as good quality DNA (>300–400 base pairs) is used [9]. There are many different primer designs for detecting T-cell receptor gamma gene rearrangements. Primers are generally designed against VG 1–8, VG 9, VG 10, and VG 11 regions with multiple primers against the JG regions (Fig. 6.9). Approximately 60%-70% of clones occur in the VG 1–8 primer set [11]. Using multiple primers against the variable and joining regions increases detection rates to over 80% [8, 113]. Some PCR methods use PCR primers only against T-cell receptor gamma joining regions 1 and 2, however, better results are obtained if primers against the other joining regions are also employed [3, 8, 113]. The joining region primers may be labeled with different fluorescent dyes and multiplexed to decrease the number of tubes and to assist in comparing a peak to the polyclonal background [114]. The limited TRG repertoire and more limited size of rearrangements means that a small clonal population that has a common rearrangement may blend in with the background and not be detectable or may look clonal. Furthermore, canonical rearrangements such as those that occur in γδ (gamma delta) T cells may look clonal because these cells preferentially rearrange the same V-J segments and limited N nucleotides are added. Most TRG clones have one or two rearrangements present; however, approximately 10%-15% have more than two rearrangements suggesting a second minor clone or oligoclones, genomic instability, or aneuploidy [112]. These peaks may be present in a polyclonal background and it may be difficult to determine if the peaks represent a clonal population or a pseudoclonal population. Clonal peaks should be significantly higher than the polyclonal background; however, what the exact cutoff should be to call a clonal peak is debated. Several methods have been proposed that compare a predominant peak to the polyclonal background. A commonly used method is to compare the relative peak heights. One study suggested that if the predominant peak is at least three times the height of the polyclonal background, it should be considered a clonal peak, whereas peaks 1.5–3 times the height of the background may be clonal and require further evaluation [115]. However, reactive T-cell lesions may display clonal peaks even using strict criteria. The TRD locus has more diversity than its partner; however, it is deleted with rearrangement of TRA on the same allele, and therefore TRD rearrangement is present only in about 35% of αβ (alpha beta) T cells. Furthermore, TRD has a more restricted repertoire and can lead to false-positive clones and should be interpreted

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in the context of concomitant TRG and TRB analyses. In the BIOMED-2 studies, TRD did not significantly add to detection, although it could be considered for use in known γδ (gamma delta) T-cell neoplasms, such as hepatosplenic lymphoma or cutaneous γδ (gamma delta) T-cell lymphoma [112]. False-positive and false-negative results occur for the same reasons that they occur with immunoglobulin gene rearrangement (see B-cell Clonality Testing section). Additionally false-positive clones are more common with PCR of TRG because of its more limited repertoire and preferential rearrangement [3]. As mentioned previously, running samples in duplicate or retesting apparently clonal populations will help to differentiate oligoclonal/pseudoclonal populations by amplifying different peaks on different runs [3, 12]. Clonal T-cell populations can occur in approximately 5–10% of ostensibly reactive T-cell proliferations and should prompt careful review of histopathology, close follow-up, and additional testing to include re-biopsy of another site particularly in cutaneous lesions [111]. Finding identical peaks at two different sites or on two separate runs is strong evidence for a true clonal process. Another method to assess clonality of a T-cell population is to perform flow cytometric immunophenotyping with antibodies to the variable region of TRB (Vβ (beta) ). Commercial antibodies against class-specific sequences of Vβ (beta) are available and cover approximately 70% of the Vβ (beta) repertoire [116]. The normal distribution of T-cell expression of these Vβ (beta) classes is well defined and substantially increased numbers of T cells expressing a single Vβ (beta) class suggest a clonal T-cell population [117]. This method can be used to assess a subpopulation of T cells identified by other surface markers or an entire T-cell population (such as CD8-positive T cells). Sensitivities of >90% and a specificity of 80% are achieved when evaluating some disorders such as T-cell large granular lymphocyte leukemia and Vβ (beta) analysis may help when evaluating pseudoclonal TRG PCR results [116, 118]. However, Vβ (beta) analysis by flow cytometry is more prone to false negatives when small numbers of neoplastic cells are present [118].

Anaplastic Large-Cell Lymphoma (ALCL) Anaplastic large-cell lymphoma (ALCL) is defined by cohesive clusters and sheets of large dysplastic CD4+ T cells that invade the paracortex and sinuses of lymph nodes and strongly express the activation antigen CD30 in a membrane and Golgi pattern in virtually every cell [119]. Approximately 30% of systemic ALCL involve extranodal sites such as skin, bone, soft tissue, liver, and lung. Systemic ALCL is divided into two categories based on the expression of anaplastic lymphoma kinase (ALK), a type II transmembrane receptor tyrosine kinase belonging to the insulin receptor superfamily [119–121]. ALK– ALCL is morphologically indistinguishable from ALK+ ALCL and is separated from peripheral T-cell lymphoma, not otherwise specified (NOS) based on its strong expression of CD30 in virtually every cell. At the molecular level, ALK– ALCL appears to have a distinct genetic profile, although

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with some overlapping features with ALK+ ALCL and PTCL-NOS [121]. A third entity limited to the skin, primary cutaneous ALCL, is ALK negative (with very rare exceptions), clinically indolent, and will not be discussed in detail [122]. ALK (on chromosome 2p23) is highly conserved across species, is expressed in embryonic neural tissue, and is involved in midgut and neural tissue development [123]. Midkine and pleiotrophin are the putative normal ALK ligands. ALK is not normally expressed in lymphoid tissue, but as a result of translocation with other genes, a fusion protein is created that forms homodimers or heterodimers (as is the case with NPM–ALK) resulting in transphosphorylation and activation of the ALK signaling pathway. NPM (5q35), a gene involved in ribosome biogenesis and shuttling between the cytoplasm and the nucleolus, is the most frequent ALK partner (70–85% of cases), but approximately eight other partner genes have been described in ALCL (Table 6.8). The genomic breakpoints in ALK are almost invariably located in the intron flanked by exons 16 and 17 with exons 17–26 encoding the intracytoplasmic domain. The fusion gene is composed of the 5 -end partner fused to the ALK tyrosine kinase domain at the 3 -end (Fig. 6.10). The subcellular compartmentalization of the fusion protein and particular signaling pathway activated are fusion gene dependent (Table 6.8). The interaction of NPM–ALK with wild-type NPM in the centrosome protein complex may explain the frequent numerical chromosome aberrations in ALCL through deregulated phosphorylation of cell-division regulators [124]. Activation of the ALK signaling pathway leads to proliferation, prolonged tumor cell survival, and cytoskeletal rearrangement and cell migration, reviewed

Table 6.8 ALK translocations seen in anaplastic large-cell lymphoma Cytogenetic abnormality

ALK partner gene

t(2;5)(p23;q35)

NPM

t(1;2)(q25;p23)

TPM3

Inv(2)(p23q35) t(2;3)(p23;q21) t(2;17)(p23;q23) t(2;17)(p23;q35) t(2;19)(p23;p13.1) t(2;22)(p23;q11.2) t(2;X)(p23;q11–12)

ATIC TFGa CLTC ALO17 TPM4 MYH9 MSN

a Three

ALK staining pattern Nuclear, diffuse cytoplasmic Diffuse cytoplasmic with membrane accentuation Diffuse cytoplasmic Diffuse cytoplasmic Granular cytoplasmic Diffuse cytoplasmic Diffuse cytoplasmic Diffuse cytoplasmic Membrane staining

Approximate percentage of cases 80 10–15 <5 <5 <5 <1 <1 <1 <1

variants based on different fusion protein lengths NPM, nucleophosmin gene; TPM3 and TPM4, non-muscular tropomyosin gene; ATIC, aminoterminus of 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase gene; TFG, TRK-fused gene; CLTC, clathrin heavy polypeptide gene; ALO17, ALK lymphoma oligomerization partner on chromosome 17; MYH9, myosin heavy-chain 9 gene; MSN, moesin gene

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Fig. 6.10 Simplified schematic of the molecular structure of ALK, NPM, and ALK fusion genes. With the exception of MSN (moesin)–ALK and MYH9 (myosin heavy chain)–ALK, all ALK fusion proteins contain the entire intracytoplasmic portion (amino acids 1,058–1,620) of ALK. Homodimerization of the fusion protein or heterodimerization with NPM mimics ligand-mediated aggregation of full-length wild-type ALK, resulting in constitutive activation of the ALK signaling pathway. X, other variant fusion partners (Table 6.8); arrows indicate breakpoint; numbers indicate the amino acid

by Chiarle et al. [125]. Proliferative effects are primarily the result of activation of cyclins and enhanced expression of genes such as FOS, JUN, and MYC. NPM–ALK acts as a docking molecule for downstream adaptors [IRS1 (insulin receptor substrate), SRC (sarcoma), SHC (SH2 domain-containing transforming protein), and PLCγ (phospholipase C gamma)] that activate the RAS–ERK (extracellular signalrelated kinase) pathway. One of the key steps in lymphomagenesis appears to be interaction of the SHP2/GRB2 (growth factor receptor-bound protein 2) complex with ALK through SHC to enhance phosphorylation of ERK1/2 through SRC and SOS (son of sevenless) [126]. Recent evidence suggests that IGF-1R (type 1 insulinlike growth factor receptor) tyrosine kinase interacts with NPM–ALK to potentiate its effects and may function as an extracellular domain to maintain the phosphorylation status of NPM–ALK [127]. The effect of ALK on survival is mediated through the JAK–STAT pathway (particularly STAT3) that regulates downstream molecules such as BCL-2, BCLXL , C/EBPβ (CCAAT/enhancer binding protein beta), survivin,

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MCL1 (myeloid cell leukemia sequence 1) and through the PI3K (phosphatidylinositol 3-kinase)–AKT pathway with inhibition of FOXO3A (forkhead box O3A) and BAD (BCL-2 agonist of cell death). Interestingly ALK’s effect on the ERK1/2 pathway (increased JUNB expression) and STAT3 also enhance transcription of CD30. Changes in actin filament depolymerization and loss of cell-matrix adhesion result from ALK activation of the Rho family GTPases through phosphorylation of members of the VAV family of guanine nucleotide exchange factors (GEFs) and may contribute to the unusual sinus growth pattern of this lymphoma [128]. Deregulated expression of full-length or ALK fusion protein has been described in non-lymphoid tumor cell lines and tumors from multiple tissue types including tumors of neural origin (retinoblastoma, neuroblastoma, glioblastoma) or solid tumors such as melanoma, breast carcinoma, and rhabdomyosarcoma [125–131]. Approximately 50% of inflammatory myofibroblastic tumors express ALK fusions with tropomyosin genes TPM3 and TPM4 and less frequently RANBP2 (RANbinding protein 2), CARS (cysteinyl-tRNA synthetase), and SEC31A (SEC-like 1) [125, 132]. Recent evaluation of genes located near the t(2;5) breakpoints such as the oncogenic AP-1 transcription factor FRA2 (on 2p23) and the HLH protein inhibitor of differentiation ID2 (2p25) and the tyrosine kinase CSF-1 receptor (5q33.1) has shown upregulation of these genes in both ALK+ and ALK– ALCL [133], suggesting that aberrant expression of these genes through unknown mechanisms may contribute to lymphomagenesis, precede the t(2;5), and create conditions favorable for translocations to occur.

Detection of ALK Dysregulation The t(2;5)(p23;q35) and other variant translocations can be detected on routine cytogenetics, but fresh tissue is often not available. RT-PCR methods to detect NPM–ALK fusion transcripts are only rarely used in routine diagnosis due the inability to detect other partners and the more time-consuming technique. In addition, NPM–ALK translocations have been detected in normal individuals in peripheral blood and lymph nodes using sensitive RT-PCR techniques [134–136]. Real-time quantitative (RQ)-RT-RCR can potentially be used to detect bone marrow involvement, minimal residual disease, and early relapse in ALCL but has not been evaluated in a large number of patients [136, 137]. Immunohistochemical detection using the ALK-1 antibody is the routine method of detecting ALK protein (CD256). The pattern of staining reflects the nature of the fusion protein (and cytogenetic lesion), with diffuse staining in the nucleus (due to heterodimerization of wild-type NPM with oncogenic NPM–ALK fusion protein) and cytoplasm with NPM–ALK and diffuse or granular cytoplasmic or membrane staining with other partners (Table 6.8). Caution should be taken in interpreting immunostaining as other tumors (inflammatory myofibroblastic tumors, rhabdomyosarcoma, and others) may express ALK.

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FISH break-apart rearrangement probes targeting sequences on either side of the ALK gene breakpoint are routinely used to detect the t(2;5) and variant translocations and numerical abnormalities. Additional copies of 2p23 or 2p have been reported in ALK– ALCL suggesting other mechanisms of ALK dysregulation in a subset of ALCL [138–140]. A rare t(11; 22) type 2 (EWS exon 7/FLI exon 5) typical for Ewing sarcoma has been detected by PCR in a ALK+ ALCL with expression of CD99 [141]. Rare three-way translocations of ALK and NPM with chromosome 3p21 and 13q14 have been described particularly in the small-cell variant [142].

Other Genetic Abnormalities in ALCL Secondary chromosomal imbalances have been detected by conventional CGH analysis in approximately 60–90% of ALK+ and ALK– ALCL, with the specific chromosomal abnormalities being somewhat variable in the limited number of cases investigated [139, 140, 143]. Loss of 11q or 13q has been reported in ALK+ and ALK– ALCL in approximately 15–30% of cases. Losses of chromosomes 4 [140] and 9p and 10p [139] in ALK+ ALCL and of 6q and 16p in ALK– ALCL [139, 140, 143] are reported. Gains of 7p and 6p [139] and 17p and 17q [140] in ALK+ ALCL and of 1q, 3p, 6p, or 8q in approximately 20–50% of ALK– ALCL [140, 143] have been reported. Although loss of 13q and gain of 17q are commonly present in other T-cell lymphomas, other numerical abnormalities such as loss of 9p21-pter, 5q21, or 12q21–22 seen in approximately 30% of PTCL-NOS were detected in less than 5% of ALK– or ALK+ ALCL. Sub-megabase resolution tiling (SMRT) array CGH performed on ALCL cell lines DEL and SR-786 revealed gains of 5p15.32–p14.3, 20p12.3–q13.11, and 20q13.2–q13.32 and losses of 18q21.32–18q23 [144]. A limited number of gene expression microarray profiling (GEP) studies have been performed. Thompson et al. [145] found that ALK+ ALCL overexpresses genes encoding signal transduction molecules such as SYK, LYN, CDC37 and underexpresses transcription factors such as HOXC6 and HOXA3, and both ALK+ and ALK– ALCL highly express kinase genes (LCK, protein kinase C, VAV2, and NKIAMRE). GEP of nodal peripheral T-cell lymphoma distinguished ALCL from other peripheral T-cell lymphomas [146]. Analysis of 25 ALK+ ALCL and 7 ALK– ALCL found that BCL-6, PTPN12 (tyrosine phosphatase), C/EBPβ, and SERPINA1 (alpha-1 antitrypsin) genes were differentially expressed in ALK+ ALCL and CCR7, CNTFR, IL22, and IL21 in ALK– ALCL [147]. Further gene ontology (GO) analysis (association of gene products with regard to their biologic processes, cellular components, and molecular functions) has shown that the ALK+ ALCL profile was related to immune response, the IkB kinase/NFκB cascade, and transendothelial migration pathways. The ALK+ tumors showed different expression profiles based on variant morphology (common versus small cell), in particular ALCL with variant morphology overexpressed genes involved in the cell cycle regulation and proliferation and genes encoding proteins involved

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in adhesion and migration. The variant histology group also had upregulation of biochemical pathways reflecting a hyperactive metabolic state. GEP performed on microdissected tumor cells and compared to normal T-cell and NK-cell subsets has confirmed the upregulation of NF-κB target genes and an activated T-cell phenotype with loss of T-cell-specific signaling and differentiation molecules [148]. Interestingly, the number of genes differentially expressed between ALK+ and ALK– ALCL were few and seem to be related to genes activated by ALK signaling, suggesting that these two tumors are closely related. This study also showed that few genes were differentially expressed between systemic and primary cutaneous ALCL, suggesting that the different clinical behavior may be influenced by the microenvironment, particularly increased numbers of T-regulatory cells in systemic ALCL.

Angioimmunoblastic T-Cell Lymphoma (AITL) Angioimmunoblastic T-cell lymphoma (AITL) is a tumor of CD4+ T cells with a follicular helper phenotype (CD10+, BCL-6+, CXCL13+, PD-1+) [149]. The tumor is heterogeneous with admixed plasma cells, eosinophils, and histiocytes and an EBV+ large B-cell population being almost invariably present. Other characteristic features include vascular proliferation and expanded follicular dendritic cell meshwork. Due to the polymorphous nature of the infiltrate resembling a reactive process, clonality studies are important in confirming the presence of a neoplastic population. Clonal TCR rearrangement is detected in 75–90% of cases; 25–30% have clonal IGH as well [150–152]. In a small subset, an EBV+ DLBCL may develop as a composite lymphoma or at relapse [153].

Genetic Abnormalities in AITL The most frequent recurrent cytogenetic abnormalities include +3, +5, and +X [154, 155]. Recurrent breakpoints have been reported at 1p31–32; 3p24–25; 4p13; 9q21–22; 12q13; 14q11; 14q32. Compared to PTCL-NOS and ALCL, AITL has fewer structural abnormalities and lacks polyploidy or gains of chromosome 7 seen in approximately 20% of PTCL-NOS and rarely in ALCL [156]. Comparative genomic hybridization studies in AITL are limited. In one series, complete or partial chromosome gains (the majority being the result of trisomic events, particularly 5q31q35 in 55% or 21 in 41%) or losses (most commonly 6q in 23%) have been identified in 91 and 36% of AITL, respectively [143]. The +21 was consistently associated with a gain of 5. 5q31–32 appears to be distinctive, and growth factor and growth factor receptor genes (such as IL-3, PDGFRB) localize to this area. In another study, Thorns et al. failed to detect significant gains of chromosomes 3 or 5 or 21 but showed recurrent gains of 22q, 19, and 11q13 and losses of 13q [157].

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Gene expression profiling has confirmed the CD4+ follicular helper T-cell origin of AITL with overexpression of such genes as CXCL13 [chemokine (C–X–C motif) ligand 13], BCL6, PDCD1 (programmed cell death 1), CD40L (CD40 ligand), NFATC1 (nuclear factor of activated T-cell cytoplasmic, calcineurin-dependent 1) [158]. In addition, there appears to be a strong microenvironmental component with overexpression of B-cell and follicular dendritic cell-related genes, chemokines, and genes related to the extracellular matrix and vascular biology. A set of eight genes has been identified that may accurately separate AITL from PTCL-NOS [158]. In one study, approximately 75% of AITL have elevated levels of c-MAF (cellular homologue of the transforming gene of the avian retrovirus AS42), a transcription factor on 16q23 belonging to the AP1 superfamily detected by RT-PCR [159].

Mycosis Fungoides (MF) Mycosis fungoides is a tumor composed of skin homing CD4+ T cells with dysplastic cerebriform nuclei that infiltrate the epidermis [160]. The clinical appearance varies as the tumor progresses from patches to infiltrative plaques and tumors and correlates with the number of cells present and the depth of invasion into the dermis. Several clinical/morphologic variants have been described but as of yet do not have characteristic recurrent cytogenetic or molecular genetic abnormalities. The immunophenotype often shows little loss of pan T-cell antigens except CD7, which can be seen in reactive lymphoid infiltrates. Early lesions of MF often resemble benign dermatoses, and the diagnosis is problematic relying on the detection of a T-cell clone in the appropriate clinical and morphologic context [161, 162]. Rearrangements of TRG and TRB are detected by PCR in approximately 70–90% of MF using the BIOMED-2 primers and other PCR techniques [163, 164] and are highest in patients with tumors versus patches/plaques. PCR analysis for TCR gamma rearrangement with denaturing gradient gel electrophoresis (DGGE) (or related techniques such as PCR temperature gradient gel electrophoresis or PCR/single-stranded conformational polymorphism analysis) with thresholds of detection of 1% increases the sensitivity of clonality detection up to approximately 90% [165, 166]. PCR amplification followed by ribonuclease protection analysis has a detection rate of 1/100,000 cells but is too sensitive for routine diagnosis as a clone may be detected in microscopically normal blood, bone marrow, on lymph nodes in patients with patch stage MF who never develop involvement of these sites and have a normal life expectancy [166]. Using these more sensitive techniques, clonal T-cell populations have been detected in reactive lymphoproliferations including skin infiltrates (approximately 2–11% of cases) [163–165, 167, 168]. These clonal dermatoses may in fact represent a “falsepositive” precursor lesion with approximately 20% having a risk of later developing MF [166] or a cutaneous T-cell lymphoid dyscrasia [169]. The presence of a matching clone from a different site improves the specificity of the clone; however, this can occur in clonal dermatitis as well [164, 170].

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Molecular Staging of Mycosis Fungoides (MF) The detection of a T-cell clone in the peripheral blood should not be considered peripheral blood involvement by MF unless the clone is identical to that seen in the skin or other involved sites such as a lymph node [166, 171, 172]. The clones detected may represent benign oligoclonal or clonal cytotoxic T-cell large granular lymphocyte (LGL) expansions that are relatively common in the elderly [173, 174] or that represent a restricted LGL response to tumor cell antigens or a monoclonal T-cell dyscrasia of undetermined significance with or without erythroderma [175, 176]. PCR/DGGE is particularly useful in demonstrating clonal relatedness in that the separation of PCR products relies on nucleotide sequences and implies an identical product more than PCR alone. In addition, another consideration is that comparison of DNA from paraffin-embedded tissue versus DNA isolated from fresh lymphocytes in the blood may not be directly comparable, and there may be false-negative or false-positive results. Detection of a T-cell clone in histologically uninvolved lymph nodes from patients with MF is associated with a reduced probability of survival and appears to be useful in distinguishing tumor involvement from benign dermatopathic lymphadenopathy [177, 178]. However, the molecular detection of a clone by PCR in histologically uninvolved lymph nodes has not been demonstrated to be statistically significant in multivariate analysis [179]. Currently the International Society for Cutaneous Lymphomas (ISCL) and the European Organization of Research and Treatment of Cancer (EORTC) recommend that nodal rating still be based principally on histopathology with the recommendation that lymph nodes lacking architectural effacement (NCI/VA LN3 or Dutch grade 2) be divided into two groups, N2A (clone negative) and N2B (clone positive), based on TCR results to determine the prognostic significance between patients with N2B versus N3 (partial effacement of node architecture with many atypical cerebriform lymphocytes, NC1VA LN4) [180]. Detection of a T-cell clone in the bone marrow does not appear to provide additional prognostic value over examination of the peripheral blood [181].

Genetic Abnormalities in Mycosis Fungoides Genomic instability with numerous random and non-random structural chromosome abnormalities has been reported in up to 70% of MF by both conventional cytogenetics and more sophisticated studies. These structural abnormalities have primarily been detected in late-stage disease as it is more difficult to culture or isolate cells in early patch/plaque MF. Most frequent abnormalities involve chromosomes 1, 8, 9, 10, 11, 12, and 17, and include loss of chromosome material at 1p22 and 1p36, and 9p21, 10q, and 17p [182–184]. The involvement of regions containing the T-cell receptor subunits is observed rarely. Reciprocal translocation is very rare in MF; a t(3;9) has been reported in one case of the granulomatous slack skin variant of MF [185].

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Gene expression profiling comparing MF and inflammatory dermatosis has revealed upregulation of 10 genes involved in anti-apoptotic signaling with inhibition of proapoptotic pathways through tumor necrosis factor receptor 1 (TNFR1). Interleukin-2 signaling may also be critical in MF pathogenesis through activation of JAK2 and STAT4 and induction of oncogenes such as MYC, LYN, and HCK [186]. Unsupervised hierarchical clustering has revealed two major subclasses, one being more aggressive including tumoral-stage MF and the other less agressive (plaque stage). Six genes were identified that could be used as a prediction model to distinguish MF and inflammatory conditions in 97% of cases. Signatures associated with abnormal immunophenotypes and with tumoral-stage disease were also detected. Transcriptional profiling of MF at various clinical stages has revealed three clusters with distinct clinical and biologic characteristics: patients in cluster 1 had the worst prognosis/tumor stage disease and upregulation of genes involved in lymphocyte activation and the TNF pathway; patients in cluster 2 had less aggressive disease and upregulation of genes associated with epidermal development; and cluster 3 patients had more extensive disease, decreased event-free survival, and poor response to therapy and increased expression of genes involved in inflammation and benign epidermal hyperproliferation [187]. Conventional comparative genomic hybridization studies have shown chromosome imbalances in 56–94% of MF cases and corroborate some of the abnormalities detected on cytogenetic studies [188–190]. Chromosome imbalances are stage related with the highest incidence with large-cell transformation. DNA losses have been reported at 1p (38%), 10q (15%), 13q (<10%), 17p (21%), and 19 (15%) [189]. DNA gains involve 4q (18%), 18 (15%), and 17q (12%). 1p33–36 and 10q26 may represent regions of minimal recurrent deletion; on chromosome 1p, two regions of minimal common deletion at 1p36 (D1S228 marker) and 1p22 (D1S2766 marker) have been defined by allelotyping [189]. Loss of heterozygosity (LOH) studies has also identified abnormalities in 1p22 (putative tumor suppressor gene), 9p21 (p15/CDKN2B and p16/CDKN2A), 10q23 (PTEN), and 17p13 (TP53), the most common being in 10q23, particularly in tumor stage MF [191]. Alterations in p15 and p16/CDKN2A (allelic loss or promoter hypermethylation) have been identified in all stages of MF, being somewhat more frequent in tumor stage [192, 193]. In transformed MF, loss of 17p and gain of 17q can result from the formation of i(17q) with subsequent loss of TP53 and overexpression of genes on 17q such as STAT3 [188]. Evidence of widespread epigenetic instability, with promoter hypermethylation of multiple tumor suppressor genes, has been reported, again particularly in advanced stage disease [194]. Amplification of JUNB (19p13.2), a member of the AP-1 transcription factor complex, has been reported in MF, Sézary syndrome (SS), and ALCL [195]. A recent study of array CGH performed on tumor stage MF with evidence of large-cell transformation (>25% large cells) revealed gains of 7q36 and 7q21–7q22 and losses of 5q13 and 9p21 [196]. Integration of array CGH data with expression array from the same patients revealed that the most frequent copy number abnormality, gain of 7q36, is associated with increased expression of FASTK, a serine/threonine protein kinase that attenuates apoptosis. Loss of 9p21 is associated

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with diminished expression of p16/CDKN2A and 13q14 with decreased RB1 and hypermethylation of DLEU1; this region also contains miRNA15A and miRNA161 which also have tumor suppressor properties. Gain of 1q21–22 is associated with higher expression of MCL-1 (myeloid cell leukemia sequence 1) which modulates glucocorticoid resistance; glucocorticoid sensitivity can be restored by the mTOR inhibitor rapamycin suggesting another therapeutic modality for tumors with this abnormality. Loss of 9p21, gain of 8q24.3, or gain of 1q21–1q22 was associated with lower survival rates in this study. In a previous publication, the same authors found that SS is characterized by gain of 17q22–25 and 8q22–24 and loss of 17p13 and 10q25, with amplification of the MYC gene seen in 75% of SS patients [197] supporting the hypothesis that MF and SS are distinct diseases.

Sézary Syndrome (SS) Sézary syndrome is a rare disease defined by the presence of erythroderma (often associated with pruritus), generalized lymphadenopathy, and the presence of an identical T-cell clone in the involved tissues and blood. An absolute Sézary cell count of 1,000 or more cells per cubic millimeter, or a CD4/CD8 ratio of 10 or more, or loss of one or more pan T-cell antigens other than CD7 (CD2, CD3, CD4, and/or CD5) must be identified in the peripheral blood T cells. A monotonous cerebriform cell infiltrate in the skin is present, but epidermotropism may be absent or minimal. Bone marrow involvement may be sparse and predominantly interstitial. Patients with MF may rarely be erythrodermic but usually are distinguished from SS by slow onset with an antecedent history of patch or plaque-type lesions and fewer abnormal cells in the peripheral blood. Although SS and MF are considered distinct entities in the current WHO classification, there is no distinct pathogenetic marker in either, and there is some overlap in clinical and pathologic features as well as genetic abnormalities.

Genetic Abnormalities in Sézary Syndrome Similar to MF, complex karyotypes are seen with many numerical and structural abnormalities particularly involving deletions of portions of chromosomes 1p, 6q, 10q [particularly 10(q22.3–q26.13)], and 13q and additions of 17p and 19 [189, 198–200]. Unbalanced translocations between chromosomes 8 and 17 have been reported in a small number of patients [183, 198]. Gene expression profiling has not yielded entirely uniform and reproducible molecular signatures in SS but has confirmed some previous observations and identified novel molecular abnormalities. Sézary cells have a Th2 pattern of differentiation with suppression of Th1 differentiation through decreased STAT4 and increased GATA3 [201, 202]. Pro-survival and anti-apoptotic signaling is important. CGH has revealed aberrant high expression of the tyrosine kinase receptor EpHA4

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(phosphorylation of STAT3) and the transcription factor TWIST that prevents MYCinduced apoptosis by antagonizing TP53 [203]. Upregulation of molecules such as CD01 (cysteine dioxygenase, the rate-limiting step in the synthesis of taurine, which protects T cells from apoptosis through CD95 and is regulated by MYC) and DNM3 (regulated by TWIST1) appears to distinguish skin lesions of SS from MF [204]. RT-PCR assay for three upregulated genes (PLS3, DNM3, CD01) and one downregulated gene (STAT4) may potentially prove to be highly sensitive and specific for the diagnosis of SS [204, 205]. Array CGH and correlative quantitative PCR studies interpreted in the context of previous genetic studies suggest that at least three molecular mechanisms are involved in the pathogenesis of SS [197]. Dysregulation of MYC due to gain of MYC, loss of MYC antagonists MX11 (10q25) and MNT (17p13), or disturbances in MYC induced apoptosis with loss of BIM (2q12) or genetic lesions in TP53, TWIST, or CDKN2A, which have been previously described. In addition, FAS (10q24), which is a key regulator in mature T cells, can be lost. Potentiation of IL-2, IL-7, and IL-15 signaling resulting in STAT3/STAT5 phosphorylation and deletions of inhibitors of IL-2 (DUSP5 and TCF8) is seen in the majority of patients and leads to uncontrolled proliferation. The loss of chromosomal regions containing TP53 and genome maintenance genes (RPA1 impairs double-strand break repair and HICI leads to de-acetylation of TP53) likely contributes to the chromosomal instability seen in SS patients. Recurrent duplication of 17q11.2∼q12 (a region containing STAT5 and ERBB2, alias HER2/neu) has been identified in early stage MF and SS and suggested to be an early event in the pathogenesis of these neoplasms [206].

Hepatosplenic T-Cell lymphoma (HSTL) Hepatosplenic T-cell lymphoma is a rare, aggressive extranodal, cytotoxic, T-cell lymphoma with a predominantly CD4–, CD8–/+ gamma delta T-cell phenotype [207]. Patients are typically young males with hepatosplenomegaly, little or no adenopathy, and frequent bone marrow involvement. Approximately 20% of the tumors arise in chronically immunosuppressed patients. At the molecular level, HSTL shows biallelic rearrangement of the TRG genes. In the small number of HSTL with an alpha beta T-cell phenotype, the TRB genes are rearranged. Non-productive TRB gene rearrangements are seen in some gamma delta HSTL. It should be remembered that a T cell is designated as a gamma delta T cell based on the expression of the gamma delta T-cell receptor proteins, not on molecular receptor rearrangements. Isochromosome 7q is present in most cases but is not entirely pathognomonic as it can be seen in other lymphomas [156, 208, 209]. Multiple copies of isochromosome 7q can be seen with progression [210]. Other mechanisms of 7q amplification including ring chromosomes have been reported [211]. Trisomy 8 and loss of a sex chromosome may also be present.

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Gene expression profiling in a small number of cases has shown a signature different from AITL and gamma delta T-cell lymphomas arising at other sites [212]. Overexpressed genes included those related to natural killer cell-associated molecules such as killer cell immunoglobulin-like molecules (KIRs), CD16 (genes FCGR3B and FCGR3A), and KLRC4 (gene for protein NKG2F, a killer cell lectin). GO analysis revealed enriched molecules for cellular defense response, signal transduction, receptor activity, and IgG binding.

Enteropathy-Associated T-Cell Lymphoma (EATL) Enteropathy-associated T-cell lymphoma is uncommon in most parts of the world except in northern Europe, where celiac disease is more prevalent [213]. The tumor presents as mucosal masses, most commonly in the small intestine (jejunum). The tumor is composed of intraepithelial CD5–, predominantly alpha beta T cells and can be divided into two subtypes based on cell morphology and immunophenotype (classical EATL with variable sized, CD4–, CD8–/+, CD56– T cells in patients with celiac disease versus type II (monomorphic) EATL with small to medium monomorphic, CD4–, CD8+/–, CD56+ T cells). There is a strong association with the HLA-DQ2/DQ8 phenotype in classical EATL. Cytogenetic studies reveal that most tumors (classical and type II) have complex segmental amplifications of the 9q31.3-qter region or deletions of 16q12.1 [214–216]. The classical EATL has more frequent gains of 1q and 5q, while type II EATL has more 8q24 (MYC) amplifications. Patients with refractory celiac disease with gains of 1q and monoclonal TRG rearrangement and decreased expression of CD8 in T cells in the surrounding enteropathic mucosa likely have intraepithelial T-cell lymphoma or in situ EATL [217].

Extranodal Natural Killer-/T-Cell Lymphoma True natural killer (NK) cell malignancies are rare in the Western world and more prevalent in the Far East, Mexico, and South America [218]. Due to their infrequent nature and overlap in morphology and immunophenotype with cytotoxic T-cell neoplasms, their diagnosis is difficult. The prototypic NK-cell malignancy is the extranodal NK-/T-cell lymphoma, nasal type. As the name implies, the cell of origin is an activated NK cell or a cytotoxic T cell. Both NK cells and cytotoxic T cells express cytotoxic granule protein TIA-1, granzyme B, and perforin. There are currently no lineage-specific NK-cell markers; NK-cell lineage determination relies on the absence of T-cell receptor gene rearrangements and the lack of surface CD3, CD5, and T-cell receptor proteins alpha beta or gamma delta that would be expressed in cytotoxic T cells. Extranodal NK-/T-cell lymphoma, nasal type most commonly presents in the nose or paranasal sinuses but can involve the skin, soft tissue, gastrointestinal tract, and testis. Characteristic pathologic features include invasion and

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destruction of blood vessels by small, medium, or large tumor cells with areas of zonal necrosis. Tumor cells are CD4–, CD8–/+, CD16+, CD56+, express cytotoxic granule markers, and most are EBV+. Extranodal NK-/T-cell lymphoma (and other NK-cell malignancies) does not have specific recurrent translocations. Many cytogenetic abnormalities have been reported [219–221], the most frequent being del(6)(q21q25) or i(6)p10. As TCR rearrangements are not present in NK-cell malignancies, cytogenetic or molecular genetic abnormalities are the only tests available to demonstrate clonality in NK-cell malignancies and may be useful in distinguishing fulminant reactive proliferations of cytotoxic T cells or NK cells as seen in hemophagocytic lymphohistiocytosis. CGH and LOH studies of NK-cell malignancies in general have shown many abnormalities, some of which are recurrent, and include gain of 1q31.3-qter and other regions in 1q, 2q13–q14 and 2q31.1–q32.2, 7q11.2 and 7q31.1–q31.2, 17q21.1, and 20pter-qter and loss of 1p36.23–p36.33, several regions in 6q, 4q12, 5q34–q35.3, 7q21.3–q22.1, 9p21.3–p22.1, 11q22.3–q23.3, 13q14.11, 15q11.2–q14, and 17p13–p13.1 [222–224]. Nakashima et al. [223] have found that abnormal regions preferentially detected in extranodal NK-/T-cell lymphoma, nasal type include gains of 2q11.2–q37 and losses of 6q16.1–q27, 11q22.3–q23.3, and 4q31.3–q32.1 and in aggressive NK-cell leukemia gains of 1q23.1–q24.2 and 1q31.3–q44 and loss of 17p13.1. Several regions in 6q are deleted, the most common being 6q21. GEP has shown three genes in the 6q21 deleted region that have decreased expression; these include PRDM1 (PR domain zinc finger protein 1), Blimp-1 (B-lymphocyte induced maturation protein, a transcriptional repressor and master regulator of B-cell differentiation), ATG5 (autophagy 5, involved in IFN-γ-induced autophagic cell death), and AIM1 (absent in melanoma, tumor suppressor gene implicated in melanoma); highly methylated CpG islands 5 of PRDM1 and AIM1 correlate with their decreased expression [224]. Loss in the 9p22.1–p22.3 region includes tumor suppressor genes CDKN2B (p15INK4B) and CDKN2A (p16INK4A). Mutations in the 17p region may result in the loss of tumor suppressor genes other than TP53. Recent Northern blot and QT-PCR studies have shown that miRNA21 (located on 17q23) and miRNA155 (located on 21q21) are overexpressed in NK-cell lymphoma/leukemia and dysregulate AKT signaling via repression of PTEN (phosphatase and tensin homologue) and SHIP1 (SH2 domain containing inositol-5-phosphatase), respectively, as a possible mechanism for lymphomagenesis [225]. In other focused studies, partial deletion of FAS or mutation in TP53, beta-catenin, K-RAS or C-KIT, changes of unknown significance, have been identified in extranodal NK-/T-cell lymphoma, nasal type [226–228].

Peripheral T-Cell Lymphoma, Not Otherwise Specified (PTCL-NOS) Peripheral T-cell lymphoma not otherwise specified is a heterogeneous group of T-cell lymphomas that do not fit into well-defined categories. PTCL-NOS predominantly arises from a CD4+ T cell involving lymph nodes, but CD8+ tumors and

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extranodal disease are described. More than half of the cases have complex karyotypes without specific cytogenetic lesions. Recurrent losses of 4q, 5q, 6q, 13q, and 9p, 10p, 10q, and 12q and 13q and recurrent gains of 1q, 3p, 5p, 7q22-qter, 8q, 17q, and 22q are described with variable detection between series [139, 143, 157]. It should be noted that abnormalities in 1p36, 6q21, 7p15, 11q13, 14q11.2, 14q32, 16q22, 16q24, 17p13-q25, 19q13, 22q11.2, and 22q13 may be seen in PTCL-NOS, AITL, or ALCL. A recent study by Nelson et al. found that the most frequent abnormality is gain of 7q (minimal overlapping region [MR] 7q22q31) (33%) followed by losses on 6q (MR 6q22q24) (26%) and 10p (MR1013pter) (26%) [143]. Gains of 7q are present in several benign and malignant neoplasms and in apparently normal tissue and may be associated with disease progression. Loss of 6q is a common finding in non-Hodgkin lymphoma, including PTCL where the area clusters at 6q21. In PTCLNOS, the minimal region extends distally from 6q22–6q24 [143]. Translocations involving 14q11.2, the site of the TCR alpha/TCR delta locus, and 11q23 (MLL region) rearrangements are also found. GEP has shown deregulation of genes involved in proliferation, apoptosis, matrix remodeling, cell adhesion, and transcriptional regulation [146, 158, 229, 230]. Although PTCL-NOS in most cases is distinct from ALCL and AITL, there is overlap. It appears that a subset of CD30– PTCL-NOS may include some lymphomas derived from AITL or lymphomas with a follicular helper T-cell origin that have a pathogenesis distinct from AILT [158]. Molecular subgroups within PTCL-NOS do not correlate with a CD4+ helper or CD8+ suppressor phenotype [229]. A proliferation signature with expression of genes associated with the cell cycle [e.g., CCNA (cyclin A2), CCNB (cyclin B1), TOP2A topoisomerase DNA II alpha] and PCNA (proliferating cell nuclear antigen) correlates with a shorter survival and is inversely related to inflammatory response genes and genes regulating a T-cell-specific program [230]. Based on GEP and using a multi-class predictor, PTCL-NOS can be divided into three molecular subgroups: one with a poor outcome based on the expression of genes such as CCND2; another with overexpression of genes involved in T-cell activation and apoptosis, including NFK B1 and BCL-2; and lastly a group with overexpression of genes in the IFN/JAK/STAT pathway.

Hodgkin Lymphoma Hodgkin lymphomas typically present in young adults as lymphadenopathy, especially in the cervical region. Morphologically, the tumor cells are generally sparse and scattered within a background of non-neoplastic inflammatory cells. Molecular abnormalities are often masked by the prominent inflammatory background unless the neoplastic cells are isolated for testing (such as by microdissection). Two main disease entities are recognized: classical Hodgkin lymphoma (CHL) and nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL), which differ in their clinical, morphologic, and molecular features.

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Nodular Lymphocyte-Predominant Hodgkin Lymphoma (NLPHL) A diagnosis of NLPHL requires identification of the neoplastic lymphocytepredominant (LP) cells within an inflammatory background and with an at least partially nodular architecture. The folded or multilobate nuclei of LP cells, which give rise to the moniker “popcorn” cells, generally contain multiple nucleoli that are smaller than CHL Reed–Sternberg (RS) cells; however, occasionally LP cells can be morphologically indistinguishable from classic RS cells. The immunophenotype differs greatly as LP cells express CD45 and normal B-cell markers such as CD20 and CD79a and lack CD15 and CD30. The background shows a follicular dendritic meshwork with small B cells and CD3+, CD57+ T cells form rosettes around the LP cells. The T-cell immunophenotype resembles germinal center T cells with BCL6 and MUM1 expression. The neoplastic LP cells are thought to be derived from centroblastic germinal center B cells as they express BCL6, have rearranged immunoglobulin genes, and show evidence of ongoing somatic hypermutation. Aberrant somatic hypermutation is found in approximately 80% of cases, most commonly in PAX5 and to a lesser extent in PIM1, Rho/TTF, and MYC [231]. BCL6 rearrangements are present in about one-half of cases and have a variety of partners including immunoglobulin genes, IKAROS, and ABR [59, 60].

Classical Hodgkin lymphoma (CHL) Four subtypes of CHL are recognized which differ in morphology (especially the composition of the background cells), clinical characteristics, and frequency of EBV association; however, the neoplastic cells share the same immunophenotype and genetics. The neoplastic cells are composed of classic RS cells and mononuclear variants termed Hodgkin (H) cells. Despite the fact that the HRS cells are B cells in >98% of cases, they lack or have weak staining for many B-cell markers and are negative for CD45. CD79a is usually absent; CD20 shows variable staining of the neoplastic cells in 30–40% of cases. PAX5 almost always stains the neoplastic cells, but staining is often weaker than in normal B cells. The cells are classically positive for CD30 and CD15 in a membranous and Golgi pattern and also express MUM1. Immunoglobulin gene rearrangement is present in the HRS cells in >98% of cases and the VH region contains a high number of somatic mutations without evidence of ongoing mutation; therefore the cell of origin is thought to be a mature germinal center B cell in these cases [24]. Rare cases of CHL express T-cell markers and approximately 85% of these demonstrate clonal immunoglobulin gene rearrangement in the RS cells and are thought to be of B-cell origin with aberrant expression of T-cell markers [232, 233]. The remaining cases lack immunoglobulin gene rearrangement and instead show TRG rearrangement in the HRS cells supporting a rare T-cell origin [232, 233]. Although no recurrent cytogenetic abnormalities are described for CHL, aneuploid and hypertetraploid karyotypes are frequently found. Smaller gains and amplifications have been discovered on 2p, 9p, 12q, 4p16, and 4q23–q24 by CGH

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analysis of a few cases [234]. Using gene sequencing, aberrant somatic hypermutation is found in approximately 55% of cases, most commonly in MYC and to a lesser extent in PIM1, Rho/TTF, and PAX5 [231]. Gene expression profiling (GEP) of the background cells can differentiate CHL from T-cell-rich, histiocyte-rich DLBCL and shows a different signature for EBVpositive and EBV-negative cases of CHL [235]. EBV-positive cases express antiviral-related genes associated with activated T cells, especially Th1-positive cells, and macrophages [235]. Outcome has also been correlated with certain gene expression profile signatures. Expression of apoptotic genes and B-cell-related genes, such as BCL11A and CCL21, is correlated with a good outcome [235]. Conversely, expression of extracellular matrix and stromal remodeling genes, such as collagens, is associated with an unfavorable outcome [235]. Immunohistochemistry can be used as a surrogate for these expression profiles. Increased background cells staining with CD20 and BCL11A (indicating increased reactive B cells) and increased FOXP3-positive T-regulatory cells are associated with a good outcome, while increased TIA1-positive or topoisomerase IIa reactive background T cells are associated with an unfavorable outcome [235]. GEP of the HRS cells shows a distinct signature that is most similar to EBV-transformed B cells and ABC-type DLBCL and has upregulation of several genes including fascin. There is downregulation of several B-cell genes, such as CD19, CD20, CD52, and TNFRSF17 (BCMA), leading to the weak expression of classic B-cell markers [236]. Downregulation of CD19, CD79a, and IGH has been shown to be due to inhibition of transcription factor TCF3 (E2A) by Id2 and MSC (ABF-1) [237]. Furthermore, inhibition of TCF3 leads to upregulation of several T-cell and macrophage genes [237]. The overlap with ABCtype DLBCL included several genes (cyclinD2, IRF-4/MUM1, CCR7, IκBα, and cFLIP) that promote proliferation and inhibit apoptosis and are regulated by nuclear factor kappa B (NF-κB) and HRS cells show constitutive activation of NF-κB [237].

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175. Gniadecki R, Lukowsky A. Monoclonal T-cell dyscrasia of undetermined significance associated with recalcitrant erythroderma. Arch Dermatol. 2005;141:361–367. 176. Klemke CD, Poenitz N, Dippel E, Hummel M, Stein H, Goerdt S. T-cell clonality of undetermined significance. Arch Dermatol. 2006;142:393–394. 177. Assaf C, Hummel M, Steinhoff M, et al. Early TCR-beta and TCR-gamma PCR detection of T-cell clonality indicates minimal tumor disease in lymph nodes of cutaneous T-cell lymphoma: diagnostic and prognostic implications. Blood. 2005;105:503–510. 178. Fraser-Andrews EA, Mitchell T, Ferreira S, et al. Molecular staging of lymph nodes from 60 patients with mycosis fungoides and Sezary syndrome: correlation with histopathology and outcome suggests prognostic relevance in mycosis fungoides. Br J Dermatol. 2006;155: 756–762. 179. Juarez T, Isenhath SN, Polissar NL, et al. Analysis of T-cell receptor gene rearrangement for predicting clinical outcome in patients with cutaneous T-cell lymphoma: a comparison of Southern blot and polymerase chain reaction methods. Arch Dermatol. 2005;141: 1107–1113. 180. Olsen E, Vonderheid E, Pimpinelli N, et al. Revisions to the staging and classification of mycosis fungoides and Sezary syndrome: a proposal of the International Society for Cutaneous Lymphomas (ISCL) and the cutaneous lymphoma task force of the European Organization of Research and Treatment of Cancer (EORTC). Blood. 2007;110:1713–1722. 181. Sibaud V, Beylot-Barry M, Thiebaut R, et al. Bone marrow histopathologic and molecular staging in epidermotropic T-cell lymphomas. Am J Clin Pathol. 2003;119:414–423. 182. Scarisbrick JJ, Woolford AJ, Russell-Jones R, Whittaker SJ. Allelotyping in mycosis fungoides and Sezary syndrome: common regions of allelic loss identified on 9p, 10q, and 17p. J Invest Dermatol. 2001;117:663–670. 183. Thangavelu M, Finn WG, Yelavarthi KK, et al. Recurring structural chromosome abnormalities in peripheral blood lymphocytes of patients with mycosis fungoides/Sezary syndrome. Blood. 1997;89:3371–3377. 184. Karenko L, Sarna S, Kahkonen M, Ranki A. Chromosomal abnormalities in relation to clinical disease in patients with cutaneous T-cell lymphoma: a 5-year follow-up study. Br J Dermatol. 2003;148:55-64. 185. Ikonomou IM, Aamot HV, Heim S, Fossa A, Delabie J. Granulomatous slack skin with a translocation t(3;9)(q12;p24). Am J Surg Pathol. 2007;31:803-806. 186. Tracey L, Villuendas R, Dotor AM, et al. Mycosis fungoides shows concurrent deregulation of multiple genes involved in the TNF signaling pathway: an expression profile study. Blood. 2003;102:1042–1050. 187. Shin J, Monti S, Aires DJ, et al. Lesional gene expression profiling in cutaneous T-cell lymphoma reveals natural clusters associated with disease outcome. Blood. 2007;110: 3015–3027. 188. Prochazkova M, Chevret E, Mainhaguiet G, et al. Common chromosomal abnormalities in mycosis fungoides transformation. Genes Chromosomes Cancer. 2007;46:828–838. 189. Mao X, Lillington D, Scarisbrick JJ, et al. Molecular cytogenetic analysis of cutaneous T-cell lymphomas: identification of common genetic alterations in Sezary syndrome and mycosis fungoides. Br J Dermatol. 2002;147:464–475. 190. Fischer TC, Gellrich S, Muche JM, et al. Genomic aberrations and survival in cutaneous T cell lymphomas. J Invest Dermatol. 2004;122:579–586. 191. Katona TM, O’Malley DP, Cheng L, et al. Loss of heterozygosity analysis identifies genetic abnormalities in mycosis fungoides and specific loci associated with disease progression. Am J Surg Pathol. 2007;31:1552–1556. 192. Navas IC, Ortiz-Romero PL, Villuendas R, et al. p16(INK4a) gene alterations are frequent in lesions of mycosis fungoides. Am J Pathol. 2000;156:1565–1572. 193. Scarisbrick JJ, Woolford AJ, Calonje E, et al. Frequent abnormalities of the p15 and p16 genes in mycosis fungoides and sezary syndrome. J Invest Dermatol. 2002;118:493–499.

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194. van Doorn R, Zoutman WH, Dijkman R, et al. Epigenetic profiling of cutaneous T-cell lymphoma: promoter hypermethylation of multiple tumor suppressor genes including BCL7a, PTPRG, and p73. J Clin Oncol. 2005;23:3886–3896. 195. Mao X, Orchard G, Lillington DM, Russell-Jones R, Young BD, Whittaker SJ. Amplification and overexpression of JUNB is associated with primary cutaneous T-cell lymphomas. Blood. 2003;101:1513–1519. 196. van Doorn R, van Kester MS, Dijkman R, et al. Oncogenomic analysis of mycosis fungoides reveals major differences with Sezary syndrome. Blood. 2009;113:127–136. 197. Vermeer MH, van Doorn R, Dijkman R, et al. Novel and highly recurrent chromosomal alterations in Sezary syndrome. Cancer Res. 2008;68:2689–2698. 198. Batista DA, Vonderheid EC, Hawkins A, et al. Multicolor fluorescence in situ hybridization (SKY) in mycosis fungoides and Sezary syndrome: search for recurrent chromosome abnormalities. Genes Chromosomes Cancer. 2006;45:383–391. 199. Mao X, Lillington DM, Czepulkowski B, Russell-Jones R, Young BD, Whittaker S. Molecular cytogenetic characterization of Sezary syndrome. Genes Chromosomes Cancer. 2003;36:250–260. 200. Karenko L, Kahkonen M, Hyytinen ER, Lindlof M, Ranki A. Notable losses at specific regions of chromosomes 10q and 13q in the Sezary syndrome detected by comparative genomic hybridization. J Invest Dermatol. 1999;112:392–395. 201. Kari L, Loboda A, Nebozhyn M, et al. Classification and prediction of survival in patients with the leukemic phase of cutaneous T cell lymphoma. J Exp Med. 2003;197: 1477–1488. 202. Hahtola S, Tuomela S, Elo L, et al. Th1 response and cytotoxicity genes are down-regulated in cutaneous T-cell lymphoma. Clin Cancer Res. 2006;12:4812–4821. 203. van Doorn R, Dijkman R, Vermeer MH, et al. Aberrant expression of the tyrosine kinase receptor EphA4 and the transcription factor twist in Sezary syndrome identified by gene expression analysis. Cancer Res. 2004;64:5578–5586. 204. Booken N, Gratchev A, Utikal J, et al. Sezary syndrome is a unique cutaneous T-cell lymphoma as identified by an expanded gene signature including diagnostic marker molecules CDO1 and DNM3. Leukemia. 2008;22:393–399. 205. Nebozhyn M, Loboda A, Kari L, et al. Quantitative PCR on 5 genes reliably identifies CTCL patients with 5% to 99% circulating tumor cells with 90% accuracy. Blood. 2006;107: 3189–3196. 206. Barba G, Matteucci C, Girolomoni G, et al. Comparative genomic hybridization identifies 17q11.2 approximately q12 duplication as an early event in cutaneous T-cell lymphomas. Cancer Genet Cytogenet. 2008;184:48–51. 207. Gaulard P, Jaffe ES, Krenacs L, Macon WR. Hepatosplenic T-cell lymphoma. In: Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, Thiele J, Vardiman JW, eds. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissue. 4th ed. Lyon: IARC Press; 2008. pp. 292–293. 208. Alonsozana EL, Stamberg J, Kumar D, et al. Isochromosome 7q: the primary cytogenetic abnormality in hepatosplenic gammadelta T cell lymphoma. Leukemia. 1997;11: 1367–1372. 209. Feldman AL, Law M, Grogg KL, et al. Incidence of TCR and TCL1 gene translocations and isochromosome 7q in peripheral T-cell lymphomas using fluorescence in situ hybridization. Am J Clin Pathol. 2008;130:178–185. 210. Wlodarska I, Martin-Garcia N, Achten R, et al. Fluorescence in situ hybridization study of chromosome 7 aberrations in hepatosplenic T-cell lymphoma: isochromosome 7q as a common abnormality accumulating in forms with features of cytologic progression. Genes Chromosomes Cancer. 2002;33:243–251. 211. Tamaska J, Adam E, Kozma A, et al. Hepatosplenic gammadelta T-cell lymphoma with ring chromosome 7, an isochromosome 7q equivalent clonal chromosomal aberration. Virchows Arch. 2006;449:479–483.

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Chapter 7

Molecular Pathology of Myeloproliferative Neoplasms David S. Bosler

Keywords Introduction · Classification · Roles of molecular diagnostics · Chronic myelogenous leukemia (CML) · Philadelphia chromosome · t(9;22) · BCR– ABL1 discovery · Imatinib · CML · Clinical findings · Laboratory findings · Histology · CML blast phase · BCR–ABL1 structure · BCR– ABL1 breakpoints · M-BCR · m-BCR · p210 · p190 · p230 · BCR–ABL1 as chimeric protein · ABL1 tyrosine kinase · BCR–ABL1 pathogenesis · BCR–ABL1 domains · BCR–ABL1 diagnostic testing · cytogenetics · RT-PCR · BCR–ABL1 fluorescence in situ hybridization (FISH) · Multiplex PCR · CML disease monitoring · Hematologic response · Cytogenetic response · Imatinib · Major molecular response · CML disease monitoring · BCR–ABL1 transcript measurement · Quantitative RT-PCR · Normalized copy number · BCR–ABL1 control gene · BCR–ABL1 quantitative RT-PCR platforms · BCR–ABL1 reporting · Normalized copy number · BCR–ABL1 measurement standardization · BCR–ABL1 measurement optimization · Imatinib mechanism · Imatinib resistance · ABL1 kinase domain mutations · P-loop · T315I · ABL1 mutation testing methods · DNA sequencing · ABL1 mutation testing standardization · CML molecular diagnostic testing · BCR–ABL1-negative classic myeloproliferative neoplasms (MPNs) · JAK2 · MPL · BCR–ABL1-negative MPNs: epidemiology · Clinical findings · JAK2 V617F · Secondary erythrocytosis · JAK2 V617F as marker of clonality · JAK2 V617F pathogenesis · JAK2 exon 12 mutations · polycythemia vera JAK2 mutations · JAK2 allelic burden · JAK2 detection methods · JAK2 detection methods · JAK2 V617F detection · JAK2 detection methods · JAK2 exon 12 mutations · MPL · MPL W515 mutations · PDGFR · FGFR1 · Eosinophilia · Chronic eosinophilic leukemia · Hypereosinophilic syndrome · PDGFRA · CHIC2 deletion · FIP1L1–PDGFRA fusion · FIP1L1–PDGFRA fusion imatinib response · Eosinophilia · FIP1L1–PDGFRA detection · PDGFRB · ETV6–PDGFRB fusion · Chronic myelomonocytic leukemia · PDGFRB

D.S. Bosler (B) Department of Clinical Pathology, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195, USA e-mail: [email protected]

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_7, 

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abnormality detection · FGFR1 · 8p11 myeloproliferative syndrome · FGFR1 disease spectrum · FGFR1 fusion partners · FGFR1 imatinib resistance · FGFR1 abnormality detection · Mast cell disease · KIT D816V · KIT D816V tyrosine kinase inhibitor therapy · KIT D816V detection · KIT D816V detection methods · Mast cell disease differential diagnosis

Introduction As a group, myeloproliferative neoplasms affect an estimated 6–10 per 100,000 people [1]. Although many of the individual myeloproliferative neoplasms had been previously recognized clinical entities, it was Dameshek in 1950 that proposed the currently recognized concept of the myeloproliferative neoplasms as a group of similar entities united by poorly controlled proliferation of various hematopoietic elements [2]. With the exception of chronic myelogenous leukemia (CML), few additional advancements had been made, and other members of this group had largely continued to be defined by a combination of clinical and pathologic criteria until very recently. Continued advances in molecular diagnostic techniques and research into these entities have recently yielded additional insights into the pathobiology of the myeloproliferative neoplasms. Although much of the story remains to be told, these insights are now reflected in the way myeloproliferative neoplasms are diagnosed and classified. The 2008 WHO Classification [1] groups the myeloproliferative neoplasms largely according to their associated molecular abnormalities, many of which involve tyrosine kinases (see Table 7.1). CML is defined by the presence of the BCR–ABL1 fusion. The diagnosis of the other “classic” myeloproliferative neoplasms – polycythemia vera, essential thrombocythemia, and primary myelofibrosis – is greatly aided by the presence of JAK2 mutations or MPL mutations. Myeloproliferative neoplasms involving PDGFRA, PDGFRB, and FGFR1 have been defined as a group containing somewhat heterogeneous but also unifying clinicopathologic features. Diagnosis of mast cell disease is also sometimes aided by the presence of a common mutation in KIT. This classification system places molecular diagnostics in a central role in the diagnosis and classification of Table 7.1 Tyrosine kinases involved in myeloproliferative neoplasms Tyrosine kinase

Disease

Abl kinase Janus kinase 2 (JAK2)

Chronic myelogenous leukemia Polycythemia vera, essential thrombocythemia, primary myelofibrosis Myeloid and lymphoid neoplasms with eosinophilia and abnormalities of PDGFRA, PDGFRB, or FGFR1

Platelet-derived growth factor receptors (PDGFRA, PDGFRB) Fibroblast growth factor receptor 1 (FGFR1) KIT

Mast cell disease (also acute myeloid leukemia, gastrointestinal stromal tumor, melanoma)

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myeloproliferative neoplasms. Many of the recent changes in the classification system have largely been driven by the advent and widespread use of tyrosine kinase inhibitors such as imatinib mesylate, with part of the goal of classification being reliable prediction of which neoplasms will respond to this type of therapy. Additional roles for molecular diagnostics have also emerged, such as prognosis and disease monitoring. Although these potential roles are yet to be fully realized in many diseases, CML serves as an illustration of the various ways that molecular diagnostics can contribute to management of malignancy. This chapter is organized by disease groups within the myeloproliferative neoplasms as recognized by the WHO classification. This chapter will explain the basics of the abnormalities encountered in each group and show how they are identified. It will also illustrate additional roles of molecular diagnostics where applicable, and it will discuss some of the salient issues that challenge molecular diagnosticians today. A large portion of the chapter is devoted to chronic myelogenous leukemia, reflecting its importance from an historical perspective as well as the range of test applications and the complexity of issues confronting the contemporary molecular diagnostic lab related to this disease.

Chronic Myelogenous Leukemia Historical Perspective and Current Relevance The story of CML merits special attention in any comprehensive discussion of molecular diagnostics. It has particular relevance from an historical perspective, and it serves as an illustrative microcosm of the potential spectrum of molecular diagnostics’ applications in clinical oncology. From the early cytogenetics-based discovery of the Philadelphia chromosome and the discovery of BCR–ABL1, encoding one of the earliest known fusion proteins in neoplasia, to the more recent development of therapy targeted specifically to inhibit that fusion protein, CML has been the subject of many ground-breaking discoveries that have led the advance of the broader science and practice of hematology and oncology (Fig. 7.1). CML was first described as early as 1845 [3]. Relatively soon after Dameshek’s description of myeloproliferative neoplasms in 1950, a series of rapid advances in cytogenetics techniques resulted in numerous discoveries related to human chromosomes. One of these landmark discoveries was the Philadelphia chromosome in CML, the first described structural chromosome abnormality, by Nowell and Hungerford in 1960 [4]. Looking at karyotypes from normal individuals, acute leukemias, and chronic granulocytic leukemias, these researchers identified an abnormal minute chromosome present only in those with CML. Later dubbed the “Philadelphia chromosome,” there was understandably initially no idea how it was derived. Thirteen years later in 1973, Janet Rowley demonstrated using banding techniques that the Philadelphia chromosome resulted from a reciprocal translocation between chromosomes 9 and 22 by recognizing that, in cases with the

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1985: BCR-ABL fusion 1990: BCR-ABL as cause of CML

1960: Philadelphia chromosome

2001: Imatinib FDA Approval

1845: First description of CML

1845

1960 1970 1980 1990 2000

Fig. 7.1 Timeline of landmark developments from the first descriptions of CML to the use of targeted therapy

Philadelphia chromosome, chromosome 9 contained additional material similar in length and staining pattern to that lost from chromosome 22 [5]. Also a pioneering discovery, this was the first identified translocation in human chromosomes. Numerous studies and researchers in the 1980s contributed to the ultimate demonstration of the BCR–ABL1 fusion [6], including the localization of ABL1 to the long arm of chromosome 9 [7], mapping of the breakpoint regions on both chromosomes 9 and 22 showing proximity and/or involvement of ABL1 and BCR, respectively [8, 9], and demonstration that ABL1 is involved in the t(9;22) and other variant translocations of CML, but is not translocated in Philadelphia chromosome-negative cases [10]. The presence of the BCR–ABL1 fusion transcript in CML cells was ultimately demonstrated in 1985 by Shtivelman et al. [11], and introduction of BCR–ABL1 was shown to cause a CML-like disease in mice in 1990 [12]. A growing body of research furthered the notion that CML containing the t(9;22) or similar variants was a distinct entity from similar appearing neoplasms without such abnormalities. Based on evidence implicating the ABL1 tyrosine kinase activity within BCR– ABL1 in the leukemogenesis of CML, STI571 (later called imatinib) was developed as a specific inhibitor of BCR–ABL1’s tyrosine kinase activity. After demonstration of its clinical utility, imatinib was approved for use in 2001 for the treatment of CML and was the first molecular-targeted therapy approved for use in human cancer [13, 14]. The impact of molecular diagnostics on care for patients with CML has only grown with time, with integral facets of contemporary management including disease-defining diagnostic tests, providing prognostic information, guiding choice of therapy, monitoring of response to therapy through minimal residual disease testing, and testing for development of resistance to therapy.

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Epidemiology, Clinical, and Laboratory Features Chronic myelogenous leukemia accounts for 7–20% of leukemias, has an estimated incidence of one to two per 100,000 worldwide, and will be diagnosed in an estimated 5050 people in the United States in 2009 [15, 16]. The median age at diagnosis is in the fifth and sixth decades [1, 17]. At diagnosis, patients most often complain of fatigue, bleeding tendencies, weight loss, sweats, and symptoms related to splenomegaly such as left upper quadrant pain, sensation of a mass, abdominal fullness, and/or swelling [18, 19]. Less common manifestations include bone pain and infection. Twenty to 40% are asymptomatic, presenting incidentally with laboratory abnormalities [16, 18]. Seventy-five percent of patients have splenomegaly, and purpura is also a common finding [18]. The most common laboratory findings at presentation are granulocytic leukocytosis and anemia, with or without thrombocytosis. Average values range 174–225 × 109 /L for white blood cell count, 9.7–10.3 g/dL for hemoglobin, and 430–485 × 109 /L for platelets [18, 20]. There is generally a loose inverse relationship between the leukocyte count and the severity of anemia. The granulocytes are left-shifted in the peripheral blood, with full maturation to neutrophils, a prominence of myelocytes, and relatively few blasts compared to acute leukemias. Absolute basophilia is a virtually invariant feature, and absolute eosinophilia and monocytosis are present in the majority of cases. Although leukocytosis is the rule, exceptional cases may have normal white blood cell counts and present instead with markedly elevated platelet counts, myelofibrosis, or anemia [18, 20]. The bone marrow is markedly hypercellular with a marked predominance of granulocytes and thick paratrabecular cuffs of immature granulocytic precursors [19]. The granulocytes are left-shifted and show full maturation. Blasts account for less than 10% of cellularity in chronic phase and have morphology that cannot be distinguished from normal myeloid blasts [19, 21, 22]. Small hypolobated megakaryocytes are a frequent finding, as are bone marrow basophilia and eosinophilia [19, 22]. The natural history of CML is biphasic or triphasic. Most patients present in chronic phase, with untreated cases almost invariably progressing to blast phase, and about two-thirds of cases passing through a transitional accelerated phase [17]. While the overall survival at 3 years in imatinib-treated patients in chronic phase is 95%, progression to blast phase portends a much more aggressive course, with 10% survival at 3 years [21]. Although there has been debate regarding the criteria for diagnosis of accelerated phase and blast phase, the current WHO criteria for accelerated phase include persistent or worsening WBC count, thrombocytosis or splenomegaly unresponsive to therapy, thrombocytopenia, the appearance of additional clonal abnormalities, basophilia >20%, or blast count 10– 19%, while blast phase is defined as >20% blasts in the peripheral blood/marrow or extramedullary blast proliferation [1]. Chromosomal abnormalities in addition to the Philadelphia chromosome frequently accompany the onset of accelerated or blast phase, described in more detail below. Blastic transformation may be myeloid, lymphoid, or undifferentiated [17, 23].

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The Structure and Pathogenesis of BCR–ABL1 The Philadelphia chromosome is created by a reciprocal translocation of chromosomes 9 and 22, with the portions of these chromosomes telomeric to their respective breakpoints at 9q34 and 22q11 essentially trading places with each other [5] (Fig. 7.2). The “Philadelphia chromosome” is the abnormal chromosome 22 that is derived from this reciprocal translocation and is easily recognized by its small size [4]. The BCR–ABL1 fusion is on this newly derived chromosome 22, created by translocation of the 3 end of the ABL1 gene from chromosome 9 to chromosome 22, where it is juxtaposed to the 5 part of BCR. The t(9;22) is the most common mechanism of creating a BCR–ABL1 fusion and is present in over 90% of CML cases [10]. In the remaining cases, the BCR–ABL1 fusion is either created by a complex translocation involving chromosomes 9, 22, and one or two other chromosomes or is present but cannot be detected by cytogenetics [10, 24, 25]. Although the breakpoints in ABL1 vary over a relatively large 300 kb range of chromosome 9, these varied breakpoints most often ultimately result in the same portion of ABL1 being incorporated into the fusion [6, 24]. This homogeneity occurs because breakpoints in ABL1 span the regions of the gene including exons Ib and Ia, which are both ultimately spliced out of the mature BCR–ABL1 fusion transcript regardless of the breakpoint [25]. The end result is that exons 2 through 11 are the

(der)Chr 9

Chr 9 Chr 22

Ph Chr

BCR 22q11

BCR-ABL1

ABL1 9q34

e13 e14 e15 e19

5’ e1

p190

3’

BCR m-BCR

M-BCR

µ-BCR

p210

e1a2

e13a2 e14a2

5’ ABL1

1b

1a

a2 a3

a11 3’

p230 e19a2

Fig. 7.2 The Philadelphia chromosome results from a reciprocal translocation involving the long arms of chromosomes 9 and 22 – t(9;22)(q34;q11). The Philadelphia chromosome is the altered chromosome 22 that is derived from this translocation, and contains a fusion of the 5 end of BCR and the 3 end of ABL1. Varying BCR breakpoints result in transcripts and fusion proteins of various lengths, including the most common p210 fusion protein (containing breakpoints of e13a2 or e14a2), as well as the p190 (e1a2) and p230 (e19a2)

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most frequent portion of ABL1 that is incorporated into the fusion. Rarely, exon 2 of ABL1 is also excluded from the fusion transcript, resulting in incorporation of exons 3 through 11 of ABL1. These cases produce a similar fusion protein and have a clinical presentation without distinguishable differences [6, 24]. The breakpoints within BCR have a more limited and clustered distribution. Most commonly, BCR is disrupted in a 5.8 kb region known as M-BCR (major breakpoint cluster region) spanning exons 12–16 of the BCR gene [8, 24]. Breakpoints within the M-BCR yield a 210 kDa protein called the p210 protein that is present in most CML cases, with the most frequent fusions being b3a2 (exon 14 of BCR to exon 2 of ABL1) and b2a2 (exon 13 of BCR to exon 2 of ABL1). Some studies suggest that cases involving breakpoints within the more 3 end of this region are more likely to be associated with thrombocytosis or present as essential thrombocythemia like, but these findings are not well established [24]. At least two other breakpoint cluster regions are present on BCR, and although they occur rarely in CML, they are associated with unique phenotypes. BCR–ABL1 fusions involving m-BCR (minor breakpoint cluster region) are most often seen in acute lymphoblastic leukemia and are also rarely seen in CML. This region spans 55 kb of BCR between exons 1 and 2, so rearrangements involving this region include only the most 5 end of BCR (e1a2 – exon 1 of BCR to exon 2 of ABL1) [6, 24]. As might be expected, this fusion results in a smaller protein, the p190 fusion protein. Although rare in CML, this fusion has been associated with an increase in monocytes and phenotypic features overlapping with chronic myelomonocytic leukemia (CMML) and has been associated with inferior response to imatinib [24, 26]. Interestingly, very small amounts of the p190 fusion protein are frequently co-expressed in cases with M-BCR breakpoints and p210 as the major fusion protein. Rare cases of CML also involve the μ-BCR (micro breakpoint cluster region), which creates an e19a2 (exon 19 of BCR to exon 2 of ABL1) rearrangement that includes more of BCR, and results in the longer p230 fusion protein. These cases have been associated with a greater proportion of mature neutrophils within the neoplastic proliferation and show clinical and hematologic overlap with chronic neutrophilic leukemia [6, 24]. BCR–ABL1 rearrangements involving areas of BCR outside these three clustered regions have also been rarely reported, including intron 6, intron 8, and intron 10 [24]. The BCR–ABL1 fusion results in a chimeric protein that contains part BCR and part ABL1. This chimeric fusion is a different result from that of most translocations in lymphoma, which bring an intact oncogene under the regulation of a constitutively active gene, such as the immunoglobulin heavy chain gene in B-cell lymphomas. Despite its chimeric nature, the BCR–ABL1 fusion protein retains the non-receptor tyrosine kinase activity that is attributed to ABL1. Normal intact ABL1 is a member of a family of tyrosine kinases, which use a phosphate from adenosine triphosphate (ATP) to phosphorylate tyrosine amino acid residues within proteins [25]. This tyrosine phosphorylation serves as the mechanism of signal transduction that normal ABL1 uses to help regulate cytoskeleton structure and the cell cycle [6, 27]. The BCR–ABL1 fusion has deregulated and increased ABL1 kinase activity. Studies in mouse models have shown that the ABL1 tyrosine kinase activity of the BCR–ABL1 fusion protein is necessary for induction of

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CML-like disease and is most effective at inducing CML-like disease when introduced into hematopoietic stem cells [12, 27]. Although increased ABL1 kinase activity has some transformative properties, murine studies have also shown that ABL1 kinase activation alone is insufficient to reliably induce a CML-like disease. Other functional regions within the BCR–ABL1 fusion are also necessary for transformation, such as the BCR coiled-coil multimerization domain, the BCR GRB-2 binding site, the ABL1 SH2 domain, and various other tyrosine phosphorylation sites [27]. The coiled-coil multimerization domain acts to enhance the kinase activity of ABL1, while the SH2 domain facilitates activation of the RAS pathway, and the GRB-2 binding site participates in cell proliferation and survival signals through activation of RAS, SHP2 and PI3K-AKT pathways [27]. The downstream effects of BCR–ABL1 include induction of hematopoietic growth factors such as interleukin-3 (IL-3), granulocyte colony-stimulating factor (G-CSF), and granulocyte–macrophage colony-stimulating factor (GM-CSF). Altered apoptotic signaling pathways such as upregulation of BCL-2 also play a role. The result is uninhibited growth and proliferation that, combined with reduced apoptosis, produce the morphologic and clinical findings in CML. Taken together, these findings highlight the central role of BCR–ABL1 in the pathogenesis of CML. Induction of blast phase is associated with additional compounding genetic alterations. One study found additional abnormalities in 65 and 82% of blast-phase and accelerated-phase cases, respectively, with the most frequent additional abnormalities being a second Philadelphia chromosome, trisomy 8, and isochromosome 17q [23]. Other abnormalities associated with disease progression include mutations in p53, RB1, P16, c-MYC, and RAS; increased BCR–ABL1 transcript expression; and methylation abnormalities of ABL1 [28]. Silencing of various tumor suppressor genes may occur through a variety of mechanisms, including deletion, inactivating mutations, and promoter methylation.

Diagnostic Testing As CML is a disease defined by the presence of the BCR–ABL1 fusion, a reliable and sensitive method of detecting the fusion is critical to the diagnostic process whenever a diagnosis of CML is considered. Although cytogenetic karyotyping is a reliable method for detection of t(9;22) and complex translocations, a small percentage of cases are not detectable by this method and would be missed if cytogenetics were used as a sole method of molecular testing [24]. Additionally, the process of cytogenetic karyotyping takes a minimum of several days to complete, resulting in a delay in diagnosis that is unnecessary if other methods can provide an answer sooner. RT-PCR designed to detect the BCR–ABL1 transcript for the p210 fusion is a rapid and very analytically sensitive technique that is useful in diagnosing CML if positive, but a negative result does not completely exclude CML since a small percentage of cases have alternate fusion transcripts that would be missed by a primer set designed to detect a single fusion protein [29]. Additionally, rare deletions occurring in or near the primers may cause false-negative results by PCR even when the

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correct breakpoints are targeted [30]. Given the limitations of these methods, other techniques have been employed when necessary as adjuncts to provide the optimal clinical and analytical sensitivity. One method commonly used to detect the BCR–ABL1 fusion gene at diagnosis is fluorescence in situ hybridization (FISH). One of the most common forms of this method is the locus-specific identifier (LSI) BCR/ABL Dual Color, Dual Fusion Translocation Probe by Vysis (Downers Grove, IL). This probe set is a combination of LSI BCR probe (22q11.2) labeled with SpectrumGreen and LSI ABL1 probe (9q34) labeled with SpectrumOrange. Since the probe sets span and flank the breakpoints, the reciprocal translocation creates two fusion signals, one on the Philadelphia chromosome (derived chromosome 22) and the other on the altered chromosome 9. Since FISH can be performed on interphase cells, results are not dependent on cell culture, resulting in the ability to perform testing on a wider range of samples as well as a more rapid turn around time than can be achieved by the culture-dependent cytogenetic karyotyping [31]. Additionally, BCR–ABL1 fusions can be detected by FISH in rare Philadelphia chromosome-negative cases of CML [24, 31, 32]. Comprehensive multiplex PCR strategies have also been employed as a reliable and sensitive means of detecting BCR–ABL1 fusions. These methods often use RTPCR, since starting with messenger RNA means that the introns have been spliced out, allowing amplification of products with a variety of breakpoints using fewer primers. One published multiplex RT-PCR method using multiple labeled primers combined with capillary electrophoresis fragment size analysis detects transcripts with a wide array of breakpoints, including e1, e13, e14, e19 on BCR, as well as a2 and a3 on ABL1 [33]. Others have employed bead-array-based technology in the detection phase to distinguish products with various breakpoints. One advantage that these methods have over FISH is that they provide more detailed information about the breakpoints present in the fusion, which may have clinical implications and is important in identifying a target for detection of minimal residual disease. Other technologies such as protein-based flow cytometric immunobead assays have shown promising results in some studies and may ultimately provide another powerful and flexible option for detection [34].

Disease Monitoring/Response to Therapy As therapeutic options for CML have improved, methods for detecting smaller amounts of residual disease have become increasingly relevant (summarized in Table 7.2). Hematologic remission, or normalization of peripheral blood counts and spleen size, was an important indicator of control of disease when hydroxyurea was a mainstay of CML therapy [35, 36]. Cytogenetic response became important in the era of interferon-α (alpha) therapy, since it could induce complete cytogenetic response (loss of detection of the Philadelphia chromosome by cytogenetic methods), in 10–20% of patients, and detection of the level of cytogenetic response

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D.S. Bosler Table 7.2 Definition of various response types and equivalent estimated tumor burden

Response type

Hematologic

Cytogenetic

Molecular

Definition

Complete: normalization of peripheral blood counts and spleen size

Partial (major): <35% Ph+ cells detected Complete: no Ph+ cells detected

Approximate equivalent tumor burden (number of cells)

1010 –1012

Complete: 109 –1010

Major: 3 log reduction from standardized level at diagnosis Complete: no transcript detected (poorly reproduced level) Major: <109 Complete: ? 106

Reproduced and adapted with permission from Baccarani et al. [42].

was important because it was associated with both a longer duration of chronic phase and an improved survival compared with those that did not achieve this level of response [35, 36]. Patients could be stratified into prognostically significant groups based on whether they had a complete cytogenetic response, major cytogenetic response (<35% of cells with the Philadelphia chromosome), or no major cytogenetic response (>35%). The advent of imatinib mesylate therapy brought about major changes in the course and survival of CML patients as a group and required yet another level of detection sensitivity to provide adequate stratification of response to therapy. The superiority of imatinib was established in the landmark IRIS (International Randomized Study of Interferon versus STI571) clinical trial, in which 1106 subjects with newly diagnosed CML were randomized to receive either imatinib (STI571) or interferon-α plus cytarabine [37]. The rates of complete cytogenetic remission at 12 months were 69% for the imatinib group and 7% for the interferon-α group. The imatinib response rates were not only durable but also actually improved over time, with 87% of imatinib-treated subjects achieving complete cytogenetic response by 60 months [38]. Importantly, the cytogenetic response was highly predictive of a favorable outcome – of those subjects who achieved complete cytogenetic response at 12 months, 97% were progression free at 60 months, compared with 81% for those that had not achieved a major cytogenetic response [38]. Among subjects with a complete cytogenetic response, quantitative measurement of BCR– ABL1 transcript levels provided additional useful prognostic information. Subjects receiving imatinib achieved major molecular response (>3 log reduction from standardized baseline) faster and at a higher rate than those receiving interferon-α(37). Fifty-seven percent of imatinib-treated subjects with a complete cytogenetic remission achieved a major molecular response by 12 months (39% of all imatinib-treated subjects), and these subjects were 100% free from progression to accelerated-phase or blast-phase crisis at 60 months of follow-up [37, 38]. Failure to achieve at least a 2 log reduction of BCR–ABL1 transcripts by the time of complete cytogenetic

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response and failure to reach a 3 log reduction at any time have subsequently been associated with poorer progression-free survival [39]. Monitoring of BCR–ABL1 transcript levels early in treatment (4 weeks and 3 months) has also been shown to be predictive of eventual major cytogenetic response and progression-free survival [40]. Imatinib therapy has so changed the course of disease in CML that many prognostic factors recognized during previous eras of therapy are now superseded by response to imatinib [17, 38, 41]. As management of CML has evolved, it has become necessary to integrate the various methods of disease monitoring in the optimal way for measuring both initial response and maintenance of response to therapy. Recommendations from the European LeukemiaNet for CML disease monitoring are summarized in Table 7.3 [42]. The prioritized goals of treatment according to these recommendations are (in order) complete hematologic response, complete cytogenetic response, major molecular response, and “complete” molecular response. If these goals are achieved, they most often happen in order as imatinib therapy continues over time, and as Table 7.4 shows, the various goals are built into the evaluation of response to therapy Table 7.3 Samples and recommended frequencies for various types of response Hematologic response Sample Recommended frequency

Cytogenetic response

Peripheral blood (CBC) Bone marrow aspirate Every 2 weeks until Every 6 months until complete response; complete response; then every 3 months then every year

Molecular response Peripheral blood or marrow Every 3 months; mutational analysis as indicated

Reproduced and adapted with permission from Baccarani et al. [42]. Table 7.4 Criteria for lack of response Time after diagnosis

Failure

Suboptimal response

3 months

No response

6 months

1. Less than complete hematologic response 2. No cytogenetic response (Ph >95%) Less than partial cytogenetic response (Ph >35%) Less than complete cytogenetic response 1. Loss of complete hematologic response 2. Loss of complete cytogenetic response 3. Mutationa

Less than complete hematologic response Less than partial cytogenetic response (Ph >35%) Less than complete cytogenetic response Less than major molecular response 1. Additional cytogenetic abnormalities 2. Loss of major molecular response 3. Mutationa

12 months 18 months Anytime

a Mutation

should be one with known high level of insensitivity to imatinib in order to fulfill this criterion. Reproduced and adapted with permission from Baccarani et al. [42].

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in a time-dependent manner. If the goals are not achieved or are lost, evaluation for resistance to therapy is often warranted as described in more detail below. Since evaluations of hematologic response and molecular response can be performed on peripheral blood, only cytogenetic evaluation requires periodic bone marrow sampling. Although FISH testing may allow evaluation of cytogenetic response in peripheral blood due to its increased sensitivity, the panel did not recommend FISH for this purpose because outcome data had been based on cytogenetics, and because cytogenetics has the important advantage of detecting additional chromosomal abnormalities [42].

Quantitative RT-PCR in Disease Monitoring – Optimization, Control Genes, and Reporting As we have seen, the realization of widespread imatinib use necessitated widespread implementation of a sensitive and reliable test to monitor response to therapy. Since pivotal imatinib trials had used quantitative RT-PCR, this method was a logical initial choice [37, 38]. Modern quantitative PCR methods have many advantages that are important to BCR–ABL1 fusion monitoring, including high sensitivity, a closed system that reduces the possibility for contamination, comparatively good reproducibility and a wide dynamic range of 5–6 logs [29]. The basic steps involved in performing this assay include RNA extraction, reverse transcription, amplification with simultaneous detection of target cDNA using technology such as Taqman or FRET probes, and comparison to a calibration curve that converts the cycle number at detection (Ct) to a quantitative value (Fig. 7.3). The optimization and standardization of each of these steps has been the focus of extensive study and discussion [43,

Fig. 7.3 Quantitative RT-PCR is the established method used in molecular level disease monitoring of BCR–ABL1 transcripts in CML treated with tyrosine kinase inhibitors. Curves showing detection of both the BCR–ABL1 fusion at the M-BCR breakpoint and the control gene (in this case ABL1) are shown. Reporting the quantity of BCR–ABL1 relative to the quantity of ABL1 in the same sample (referred to as the normalized copy number) can help control for variability due to RNA degradation as the sample ages

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44]. The Europe Against Cancer (EAC) Program established a standardized protocol for minimal residual disease testing using quantitative RT-PCR with TaqMan detection technology in 26 laboratories across 10 countries, and their design and protocol for BCR–ABL1 transcript measurement have provided a reference standard against which other methods can be compared [44]. Quantitative RT-PCR has the advantages and disadvantages associated with messenger RNA as a starting material. As discussed earlier, one advantage is that introns have been spliced out, overcoming much of the variability of breakpoints in ABL1 and allowing the use of fewer primer sets. One disadvantage is that RNA is unstable and degrades over time, leading to quantitative variability depending on the time from draw to analysis unless appropriate compensatory mechanisms are in place. For this reason, a control gene must be incorporated into quantitative RTPCR assays. Reporting the BCR–ABL1 expression level (in copy number) as a ratio to the transcript copy number of an appropriate control gene, a relative value known as the normalized copy number (NCN), can help compensate for RNA degradation that occurs with aging of the specimen, as well as variability in the efficiency of the extraction and reverse transcription steps [43–45]. The ideal control gene would have a predictable, stable expression level and rate of degradation that is comparable to that of BCR–ABL1, yet its measurement would be unaffected by BCR–ABL1 levels [45, 46]. Beillard et al. extensively studied the appropriateness of 14 candidate control genes as part of the EAC effort and, based on stability, expression levels in various samples, and lack of pseudogene amplification, concluded that ABL1, beta-glucuronidase (GUSB), and beta-2-microglobulin (B2M) had the appropriate characteristics to potentially serve as control genes for quantitative minimal residual disease testing [45]. Ultimately, the authors selected ABL1 as the most appropriate based on comparatively consistent expression levels in different sample types and in both normal and leukemic samples (BCR was not evaluated). In practice, many different control genes are used, with BCR, ABL1, and GUSB being the most prevalent. BCR and ABL1 have both been established by use in high-profile studies, both have the advantage of convenience from an assay design standpoint, and ABL1 particularly has demonstrated similar stability to BCR–ABL1 [37, 43–46]. A potential limitation of ABL1 as a control gene is that, since its primers may also amplify BCR–ABL1 fusion transcripts, the control genes may be over-represented when BCR–ABL1 levels are high, resulting in underestimation of BCR–ABL1 when expressed as NCN [45, 47]. Since precise quantitation is most important when BCR– ABL1 levels are low rather than at high levels where the potential for skewed results is greatest however [48], this bias is of undetermined clinical relevance, and ABL1 remains in widespread use as a BCR–ABL1 assay control gene, along with BCR, GUSB, and others. Many acceptable platforms are available for BCR–ABL1 quantitative monitoring, with variable capacity for throughput available depending on anticipated testing volume. Silvy et al. compared seven different platforms using serial dilutions from a BCR–ABL1-positive cell line, plasmid standard curves, and results expressed as normalized copy number according to the EAC protocol and found the methods generally equivalent and within acceptable performance standards [49].

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Another issue confronting clinical laboratories performing quantitative BCR– ABL1 testing is how best to report the results. As described above, reporting BCR–ABL1 levels as copy number per microgram does not account for variability in age of the specimen or efficiency of the assay. While using normalized copy number corrects many of these issues, it does not account for variability between laboratories, and raw NCNs do not have well-established clinical relevance. For these reasons, most laboratories report BCR–ABL1 levels using the method first described by Hughes et al. for use in evaluating subjects on the IRIS trial [37]. In order to standardize results between laboratories, this group converted their normalized copy number results into a log reduction from a standardized median created from measurement of 30 newly diagnosed (baseline) patients at each laboratory. Using this method to report results has a few distinct advantages. First, since each lab creates a standard baseline using its own method, reporting the results relative to each lab’s baseline may correct some of the variability between laboratories. Second, since this reporting method was used in the pivotal IRIS trial, it has established clinical validity – a 3 log reduction from the standardized median baseline was the cutoff value shown to have clinical relevance, as described in more detail earlier [37]. In practice, many labs report both the NCN and the log reduction.

Quantitative RT-PCR in Disease Monitoring – Interlaboratory Standardization Efforts Despite the use of methods with high internal reproducibility and standardization by reporting log reduction from a standardized median, considerable variation between laboratories remains an issue. One sample sharing study of 38 laboratories found that results varied considerably from lab to lab, with log reduction ranges between laboratories spanning 2.5–3.0 logs for the same dilution [47]. These results emphasize the importance not only of careful optimization of methods but also the need for standardization between laboratories. Additional efforts at standardization that are currently underway include the application of an internationally standardized conversion factor analogous to the International Normalized Ratio (INR) used in monitoring anticoagulation with warfarin, and preparation and dissemination of stable standard reference and calibration materials. Proposals for an international standardization include use of standardized calibrators to produce conversion factors for laboratories that would allow normalization to two anchor points, with the median standard baseline equal to 100% and the 3 log reduction equal to 0.1% [48, 50]. In an international study comparing laboratory values, Branford et al. showed that application of such a laboratory-specific conversion factor can result in higher rates of concordance between laboratories [51]. Meanwhile, efforts at producing stable, standardized reference material are progressing. A lyophilized preparation of K562 cell line has been shown to have potential as a stable and reliable quality control reagent that could serve as an international standard [52]. Availability of such standards appears imminent and will significantly advance the efforts at inter-laboratory standardization.

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Resistance to Tyrosine Kinase Inhibitor Therapy A brief review of imatinib’s mechanism of action is warranted as preparation for a discussion regarding imatinib resistance. Originally known as signal transduction inhibitor 571 (STI 571), imatinib inhibits the tyrosine kinase activity of BCR–ABL1, platelet-derived growth factor receptors (PDGFRA and PDGFRB), and c-KIT, by competitively blocking the ATP binding site (Fig. 7.4). Imatinib achieves high affinity and specificity for BCR–ABL1 through specific binding to BCR–ABL1’s inactive form, which locks the tyrosine kinase in an inactive state [14, 53]. With the kinase in the inactive form and access to ATP blocked, substrate phosphorylation cannot take place, preventing the downstream cascade of events that drives transformation in CML (as described above in more detail). Indications for resistance testing include either signs indicating initial treatment failure or suboptimal response (see Table 7.4), or indications that response has been lost, such as accelerated- or blast-phase, clonal evolution, loss of cytogenetic or hematologic response, or increasing BCR–ABL1 transcript level [29, 42, 54]. A confirmed increase in BCR–ABL1 transcript levels of 5–10-fold or greater has been proposed as a threshold that would prompt evaluation for resistance [43, 54].

A.

Substrate BCR-ABL1 P P P

Substrate

Tyr

Tyr P

B.

Substrate BCR-ABL1 imatinib

Substrate

Tyr

P P P

Tyr

Fig. 7.4 (a) BCR–ABL1 acts as a constitutively active tyrosine kinase, using ATP as a phosphate source to phosphorylate substrate proteins at tyrosine residues, resulting in activation of downstream pathways. (b) Imatinib blocks the ATP binding site and binds BCR–ABL1 in its inactive conformation, preventing tyrosine phophorylation of substrates

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Resistance to imatinib therapy may be primary or secondary, and either BCR– ABL1 dependent or independent [29]. Initial therapy failure (primary resistance) is generally related to pharmacokinetic and/or pharmacodynamic properties of imatinib and the treated host including abnormal cellular drug transport [55]. Secondary resistance is more common, occurring at an annual rate of about 4%, and most commonly results from mutations in the ABL1 kinase domain that block or overcome imatinib’s activity [29, 55–57]. Approximately 30–50% of chronic-phase CML patients with signs of resistance have a detectable ABL1 kinase domain mutation, with higher rates in accelerated and blast phase [54, 58]. Other mechanisms of resistance include BCR–ABL1 amplification and/or overexpression and BCR–ABL1-independent mechanisms such as clonal evolution [42, 55]. Some studies have demonstrated LYN-mediated upregulation of BCL-2 as a mechanism of BCR–ABL1-independent resistance [59, 60]. ABL1 kinase domain mutations tend to occur in one of four functional regions: the P-loop, the imatinib binding site, the catalytic domain, and the activation loop [14, 54]. Although over 70 ABL1 kinase domain mutations have been reported, mutations within just eight codons (M244V, G250E, Y253F/H, E255K/V, T315I, M351T, F359V, H396R) represent up to 85% of resistance [54, 58]. Not all mutations are functionally equivalent, and the implications of detection may vary. For example, imatinib dose escalation may be a reasonable approach with mutations such as M351T that show mild resistance, while other mutations may prompt a switch to second-generation tyrosine kinase inhibitors, and yet others such as T315I may indicate resistance not only to imatinib but also to newer tyrosine kinase inhibitors [54]. Mutations within the P-loop (codons 248–256) and the T315I mutation typically confer the greatest level of resistance [54, 58]. Although newer and more potent tyrosine kinase inhibitors such as dasatinib and nilotinib serve as effective second-line therapies in patients who have failed imatinib [57], continued experience with these drugs has demonstrated that specific mutations are also associated with their use [54, 61]. In one study of subjects treated with dasatinib or nilotinib after imatinib failure, new mutations developed in 26% of cases [61]. Although new mutations during dasatinib or nilotinib therapy tended to occur at certain codons (e.g., 253, 317, 359), only the T315I mutation was associated with a higher level of resistance. The high level of resistance to available therapies found in T315I-mutated cases has prompted the development of newer potential therapies such as the aurora kinase inhibitors, many of which have shown promising clinical and/or laboratory activity against T315I, and are in early phase clinical trials [62]. Several questions regarding ABL1 kinase domain mutations and resistance remain unanswered. The number of ABL1 kinase domain mutations reported continues to grow, and the functional significance of many remains undetermined. It is not clear whether mutations occur after initiation of therapy or if they become apparent as a dominant mutated clone emerges under selective therapeutic pressure, although detection of low levels of mutation in treatment naïve subjects suggest the latter [63]. Additionally, detection of these low-level mutations was not associated with development of resistance or shortened survival [63], prompting questions about at what level a mutated clone becomes clinically relevant.

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Several methods have been implemented in detection of ABL1 kinase domain mutations, including denaturing HPLC, direct chain termination-based (Sanger) sequencing, pyrosequencing, allele-specific oligonucleotide (ASO) PCR, and liquid bead array [43, 54]. The currently recommended technique for mutation screening is Sanger sequencing [43, 54]. Although this method is less sensitive than others, it offers the advantages of comprehensive evaluation of the targeted area as well as bidirectional confirmation and is routinely available in most labs. Additionally, while methods such as ASO-PCR offer much greater sensitivity of detection, lowlevel detection of mutations does not appear to have clinical relevance at this time, and ASO-PCR assays are limited to detection of the specific mutations for which they are designed. One potential challenge with sequencing is detection of mutations with uncertain clinical significance. Although there is generally good correlation between in vitro resistance to tyrosine kinase inhibitors and clinical resistance [54, 61], new or recently reported mutations may not have been evaluated. Additionally, correlation of BCR–ABL1 transcript levels with levels of the ABL1mutated clone has shown that the presence of a mutation does not invariably account for clinical resistance [64]. To address some of the challenges associated with testing for ABL1 kinase domain mutations, the Association for Molecular Pathology convened an ABL Mutation Working Group. The resulting publication of laboratory practice guidelines [54] provides guidance on testing methods and recommendations for reporting and makes proposals for standardization, reference materials, proficiency testing, and development of a publicly available BCR–ABL1 kinase domain mutation database for use in interpreting the clinical significance of results.

Summary: Integration of Molecular Diagnostic Testing into CML Management Molecular diagnostic testing is an important component of many aspects of diagnosis and management of CML, including diagnosis itself, disease monitoring and prognosis, and response to therapy and resistance. At diagnosis, reliable and sensitive methods for detection of BCR–ABL1 fusion include fluorescence in situ hybridization and some comprehensive multiplex RT-PCR assays. Cytogenetic karyotyping and PCR for the p210 fusion also detect the vast majority of CML cases, but they miss cases that are cytogenetically cryptic or that involve rare variant fusions, respectively. Nonetheless, it remains important to perform these tests at diagnosis in order to get baseline information that will become important in disease monitoring. Assuming that a p210 BCR–ABL1 fusion is present at diagnosis, quantitative RT-PCR designed to detect the p210 fusion is the most sensitive method of monitoring residual disease, and the increased sensitivity of this method has been shown to be clinically relevant. Obtaining a baseline result for the RT-PCR p210 assay is helpful in order to ensure that cases that are subsequently negative for the BCR–ABL1 fusion during disease monitoring are negative because they have achieved complete molecular response rather than because they have a variant

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rearrangement that is not detected by the assay. Additionally, cytogenetic karyotyping remains an important method of detecting additional cytogenetic abnormalities, such as a second Philadelphia chromosome, trisomy 8, or isochromosome 17q, which may be harbingers of disease progression and are not detected by RT-PCR or FISH. When molecular disease monitoring, hematologic findings, or clinical course suggests loss of response to therapy, analysis of the ABL1 kinase for mutations that confer resistance to imatinib and/or other tyrosine kinase inhibitors helps to guide choice of subsequent therapy.

BCR–ABL1-Negative “Classic” Myeloproliferative Neoplasms Like CML, the BCR–ABL1-negative classic myeloproliferative neoplasms (MPNs) are long-established recognized clinical entities. Although some were known by different names, polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF) were all included along with CML in Dameshek’s first conceptual grouping of myeloproliferative neoplasms in 1951 [2]. Unlike the early advancements in pathogenesis and diagnostic markers seen in CML however, substantive discoveries regarding the BCR–ABL1-negative MPNs lagged and their diagnosis relied almost exclusively on clinicopathologic findings until very recently. The discovery of JAK2 mutations and, to a lesser extent, MPL mutations in the BCR–ABL1-negative classic MPNs have both advanced the knowledge of pathogenesis and provided much more robust markers of clonality that have greatly simplified their diagnosis, with much remaining to be explained.

Epidemiology, Clinical, and Laboratory Features As a group, PV, ET, and PMF occur with about three times the frequency of CML [65]. Estimated incidence rates of each vary by study, but it appears that ET may be slightly more common than the other two, with all having a peak incidence in the sixth and seventh decades [1, 65, 66]. These three closely related entities are united by the presence of unregulated proliferation of myeloid precursor cells. This proliferation involves varying combinations of erythroid, granulocytic, and/or megakaryocytic cell lines. Although there can be some overlap between them, PV generally shows predominant erythroid proliferation, while ET shows predominant megakaryocytic proliferation, and PMF shows predominant myelofibrosis [1, 67]. The clinicopathologic overlap intimates the underlying clonal stem cell abnormality that is present in each of these disorders. Patients present with splenomegaly and variable abnormalities of peripheral blood cell counts, including elevated red blood cell mass (PV) or platelets (ET), or combinations of elevated counts and cytopenias with a leukoerythroblastic blood picture indicating marrow replacement by fibrosis (PMF). Leukocytosis may also be present. Risk of thromboembolic events is significantly increased and is the leading etiology of morbidity

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and mortality in MPN patients [1, 68]. Bone marrow morphology can be normocellular to mildly hypercellular (ET), markedly hypercellular (PV), or have marked fibrosis (PMF). Marrow histology overlaps, with hyperplasia of various myeloid components, morphologically abnormal and clustered megakaryocytes, and reticulin fibrosis found to varying degrees in each entity. Dysplasia is not a prominent feature. The clinical course is indolent and variable, with risk of marrow failure due to progressive myelofibrosis, and progression to blast crisis in a minority. ET is the least likely to progress, with those affected most often showing an indolent course [1, 69, 70]. Although distinction between ET and PMF is of prognostic significance, the distinction based on morphologic grounds can be unreliable [71]. Despite the overlap of clinical and pathologic features, the heterogeneity indicates that there are likely varied pathophysiologic mechanisms at work, many of which remain unexplained.

JAK2 V617F’s Contribution to Diagnosis of MPNs Prior to the discovery of the JAK2 mutation, only about 20% of the BCR–ABL1negative classic MPNs had recognizable clonal abnormalities [1]. The combination of the lack of a marker of clonality in a majority of cases and significant overlap with non-neoplastic conditions resulted in a complicated diagnostic process that most often included an exhaustive exclusion of alternative explanations for signs and symptoms before a diagnosis of a myeloproliferative neoplasm could be made. For example, the differential diagnosis of erythrocytosis includes a wide variety of etiologies aside from polycythemia vera [72]. Congenital causes such as mutations in the VHL gene, activating mutations of EPO, or high oxygen affinity hemoglobin variants result in erythrocytosis. Additionally, a number of potentially more common causes of acquired erythrocytosis must be excluded, including those resulting from hypoxia such as tobacco smoking, chronic lung disease or high altitude, and paraneoplastic erythropoietin production from a variety of nonhematolymphoid neoplasms (e.g., renal, hepatocellular, uterine leiomyomas). Low erythropoietin (EPO) levels are seen in PV and can help to rule out many of the more common causes of secondary erythrocytosis. In addition to ruling out alternative causes, the evaluation for a myeloproliferative neoplasm most often also included the relatively cumbersome measurement of red cell mass in order to rule out apparent (relative) polycythemia [72]. Similarly, thrombocytosis has a wide variety of potential etiologies other than ET, such as iron deficiency anemia, infection, inflammation, other underlying malignancies (hematologic or other), or response to medications [73]. When present, the JAK2 V617F mutation provides a marker of clonality that dramatically simplifies the diagnostic process for BCR–ABL1-negative MPNs. Located on chromosome 9p24, the JAK2 gene encodes a non-receptor protein tyrosine kinase that associates with homodimeric growth factor receptors. The JAK2 V617F mutation’s presence in a majority of BCR–ABL1-negative MPNs was reported essentially simultaneously by four research groups in 2005 [74–77]. The mutation is found

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D.S. Bosler Table 7.5 JAK2 and MPL in BCR–ABL-negative MPNs Mutation

PV ET PMF

JAK2 V617F

JAK2 Exon 12

MPL W515

95% 50% 50%

∼ 5% – –

– 1–4% 5–11%

in about 95% of PV, roughly half of ET and PMF (Table 7.5), and in small percentages of other myeloid neoplasms including chronic myelomonocytic leukemia, atypical CML, acute myeloid leukemias, and refractory anemia with ring sideroblasts and thrombocytosis (RARS-T) [78–82]. The mutation consists of a single nucleotide substitution (G1849T) in exon 14 of JAK2 that results in a single amino acid change from valine to phenylalanine at position 617. This mutation within the JH2-negative regulatory domain results in phosphorylation and constitutive activation of JAK2, which facilitates ligand-independent activation at homodimeric growth factor receptors (such as the EPO receptor, thrombopoietin receptor, and GCSFR) and activation of STAT signaling proteins [83, 84]. Ultimately, there is unregulated (ligand independent) downstream activation of transcription factors involved in proliferation and survival via activation of the MAPK and PI3K pathways (Fig. 7.5) [81]. As this mutation is not detected at significant levels in normal subjects, it serves as a marker of clonality, precluding the need for exhaustive exclusion of potential alternative etiologies of signs and symptoms before a diagnosis can be made. It is important to remember that the JAK2 V617F mutation is not specific for any MPN, nor does its absence exclude the possibility of an MPN.

Other JAK2 Mutations in PV Investigation of some of the 5% of PV cases that are JAK2 V617F negative has revealed that most of these cases contain alternate JAK2 abnormalities. The first such investigation showed four novel mutations within exon 12 of JAK2, with detected abnormalities including the amino acid substitutions K539L and H538Q with K539L, as well as a small deletion, N542-E543del, and a deletion/insertion, F537K539delinsL [85]. Subsequent studies have confirmed these results and uncovered additional mutations within exon 12, most often occurring within the region containing amino acid residues 530–550 [86–88]. Overall, the N542-E543del is the most frequent abnormality [82]. These mutations appear to occur only in PV, and phenotype–genotype correlations suggest that these cases more often present with an isolated erythrocytosis. In contrast to the V617F mutation, most of the exon 12 mutated cases are heterozygous [82, 85–87]. One recent study screening 20,000 samples from patients with suspected MPNs suggests that alternative JAK2 mutations may occur over a much broader range of the gene than initially suggested [89].

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A.

235

B. Erythropoietin receptor

Erythropoietin receptor JAK2 V617F

JAK2 V617F

JAK2 P

JAK2

P

P

P

STAT

STAT

PI3K

Proliferation, Survival

MAPK

C. Thrombopoietin receptor (MPL) MPL W515L/K

JAK2

Proliferation, Survival

P

JAK2 P

STAT

Proliferation, Survival

Fig. 7.5 (a) Physiologic activation of the erythropoietin receptor and downstream pathways requires binding by erythropoietin, which results in JAK2 activation and phosphorylation, with recruitment and activation of STAT signaling proteins and downstream induction of proliferation and survival genes via the PI3K and MAPK pathways. (b) Mutated JAK2 protein results in constitutive activation of JAK2 and downstream pathways that is independent of erythropoietin binding. (c) Mutations in MPL (thrombopoietin receptor) result in activation of the same pathway due to ligand-independent constitutive activation of the receptor itself

Ma et al. confirmed the presence of mutations within the previously reported exon 12 hot spots but also reported mutations throughout exons 13–15 [89]. Although the functional significance of these new mutations and their association with disease are not established, the study suggests that a broader net be cast when testing for alternative mutations.

Effect of JAK2 Allelic Burden A growing body of literature is examining the relevance of the quantity of JAK2 V617F present in BCR–ABL1-negative classic MPNs. A subset of PV cases (25–30%) has a homozygous V617F mutation most often resulting from mitotic recombination (acquired uniparental disomy) rather than deletional loss of heterozygosity [76, 77, 90]. Homozygosity is more common in PV, occurring relatively rarely in ET and PMF [76, 77, 90]. Homozygous PV cases are associated with increased hematocrit and leukocyte counts, lower platelet counts, a greater degree

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of splenomegaly, and pruritus [90]. More recently, studies have focused on quantitative JAK2 V617F burden rather than zygosity, with mixed results. As might be expected, increasing allelic burden in PV correlates with the findings in homozygous cases, and ET and PMF cases with increased JAK2 V617F allelic burden tend to show similar findings such as increased hemoglobin and leukocyte count [91–94]. Although many studies have attempted to stratify prognosis and thrombotic risk according to allelic burden, results have been conflicting and likely reflect a more complex underlying pathobiology that remains to be more completely sorted out. A few studies have shown that low JAK2 V617F allele burden in PMF correlates with poor prognosis [93, 95].

JAK2 Mutation Detection Methods Numerous methods can be employed to detect the JAK2 V617F mutation. One recent study performed a head-to-head comparison of four methods, including commercial assays using PCR with enzyme digestion and fragment size analysis, PCR with differentially fluorescent allele-specific Taqman probes, and allele-specific oligonucleotide (ASO) PCR and a laboratory-developed test using PCR followed by melt curve analysis [96]. The quantitative ASO-PCR showed the greatest sensitivity (0.0098%), followed by the two semi-quantitative methods (PCR with Taqman probes and PCR with enzyme digestion and capillary electrophoresis), which both had a sensitivity of 1.25%. The PCR with melt curve analysis showed the least sensitivity, with a slight curve abnormality at 10%, and clearly visible peaks only present at the 20% and undiluted (100%) levels. Evaluation of 33 patients’ bone marrow and blood samples including a variety of MPNs as well as non-MPN malignancies and a variety of reactive conditions showed concordance between all four methods in 30 of 33 cases. Two of the three discordant cases were negative by the less sensitive melt curve analysis and positive by the other three methods [96]. Although the authors felt that the commercial assays had all performed well, the PCR followed by enzyme digestion and electrophoresis required more hands-on time and posed some interpretation difficulties with low-level positives (Fig. 7.6). The ASO-PCR technique has the added benefit that it can be used as a quantitative assay. Although the clinical relevance of JAK2 V617F quantitation is currently unclear, it may become more relevant in the future either as a prognostic tool if issues surrounding allele burden become clearer or as a disease monitoring tool if JAK2 inhibitors prove effective. One potential challenge encountered when using an assay with such high sensitivity is what to do with low-level positive results. Since low-level positives are seen in subjects without any evidence of MPNs (presumably normal), extensive study of normal populations is recommended to establish a normal range prior to implementation. Also, although one might be concerned about quantitative differences between blood and bone marrow samples, one relatively limited recent study using parallel ASO-PCR reactions for wild-type and V617F mutant JAK2 to evaluate peripheral blood and bone marrow samples in 11 untreated MPN subjects

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Fig. 7.6 Detection of JAK2 by PCR followed by melting curve analysis is accomplished by using flanking PCR primers that amplify both wild-type and mutated JAK2, with application of a FRET probe. In the following melting curve analysis, rising temperatures cause the probes to “melt” off of the amplified product to which they’ve hybridized, resulting in loss of fluorescence. The probe in this case is 100% homologous to the wild-type sequence, requiring a higher melting temperature to denature, while the partially mismatched mutated sequence denatures at a slightly lower temperature. Detection of wild-type and or mutated JAK2 is achieved by comparing the melting curves of the samples to controls. Although this method works well, it only detects sequence changes that occur under the probe, and may have limited sensitivity in detecting low levels of JAK2 V617F

showed good correlation between peripheral blood and bone marrow levels [97]. Besides the sample size, one limitation of this study was that no low-level samples were tested. Since the V617F mutation accounts for 95% of PV, analysis for other JAK2 mutations may remain largely limited to high-volume laboratories. A direct sequencing assay might be adequate to detect most of these mutations as long as they are present in high enough amounts (25–30%) to be detected by direct sequencing (e.g., at diagnosis). Strategies to increase sensitivity such as use of wild-type blocking oligonucleotides in targeted areas may be of benefit. Alternatively, mutation screening methods can be employed. One recent study reports successful screening of the entire coding region of JAK2 exons 11–15, incorporating all of the reported abnormalities, using a non-isotopic RNA cleavage assay [98]. Others have shown high sensitivity and specificity in detection of exon 12 and 14 mutations with high-resolution melting analysis [99].

JAK2 – Unresolved Issues Many issues surrounding JAK2 and MPNs remain incompletely resolved and are the subject of investigation, including whether JAK2 is the initiating event in MPNs, the role that heredity may play in susceptibility to acquiring JAK2 mutations, the mechanisms driving pathogenesis in JAK2- and MPL-negative ET and PMF cases, and the role of JAK2 inhibitor therapy [100]. Between 10 and 20 JAK2 inhibitors

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are in the development pipeline, with five in clinical trials. Although early results show improvement in signs and symptoms such as blood counts, splenomegaly, and constitutional symptoms, whether any will induce remission or alter disease course is yet to be determined [82, 100].

MPL Mutations in MPL have recently been discovered in a small percentage of JAK2negative ET and PMF cases. Located at chromosome 1p34, MPL encodes the thrombopoietin receptor, which stimulates global hematopoiesis as well as megakaryocyte growth and differentiation. When bound to its ligand, MPL acts in a fashion similar to the erythropoietin receptor, with activation of the JAK/STAT pathway and downstream stimulation of proliferation and survival signals via the MAPK and PI3K pathways [81]. MPL mutations in MPNs were first reported in 2006, when a group screening JAK2 V617F-negative MPNs for mutations reported a single nucleotide substitution (G1544T) resulting in a single amino acid change from tryptophan to leucine (W515L) in 4 of 45 evaluated PMF cases [101]. In vitro models showed that the mutation conferred thrombopoietin-independent growth and activation of downstream pathways (Fig. 7.3C), and mice transduced with the mutation-developed lethal MPNs with a short latency [101]. A subsequent larger study evaluated 1182 myeloid neoplasms for MPL mutations and found W515L or W515K (lysine substituted for tryptophan) mutations in 4 of 318 ET, 13 of 290 PMF, and 3 of 126 acute myeloid leukemia cases (the three positives were diagnosed as blast transformation of a pre-existing myeloproliferative neoplasm) and did not detect mutations in any of 242 PV cases, 206 other myeloid neoplasms, or 64 controls [102]. Six subjects had W515L and JAK V617F concurrently. More recent studies have found additional somatic mutations, including W515S and S505N, and report incidence rates of 1–4% of ET and 5–11% of PMF [82]. Compared with MPL wild-type MPN subjects, mutated cases are older, more anemic, and more likely to require transfusion support [103]. The primary clinical utility of MPL testing at this time is as a marker of clonality in cases of suspected MPN when JAK2 analysis and cytogenetics reveal no abnormalities. Since this utility impacts a relatively small number of cases, testing for MPL mutations is currently relegated to only a few laboratories, with the most common method used being reverse transcription, PCR, and direct sequencing of targeted areas of MPL.

PDGFR and FGFR1 Abnormalities This rare group of neoplasms was segregated into its own chapter in the 2008 WHO classification, with each of the three members in the group defined and classified according to its associated molecular abnormality. This change in classification has largely been driven by the recognition that some of these disorders can be

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successfully treated with tyrosine kinase inhibitors such as imatinib, underscoring the importance of recognizing them when present despite their rare incidence. Overlapping clinicopathologic features both within this group and with other myeloid and lymphoid neoplasms combine with varying responses to tyrosine kinase inhibitors to make molecular diagnostic techniques an indispensible part of the diagnostic process when the possibility of one of these entities is considered. Table 7.6 summarizes some of the salient features of neoplasms with PDGFRA, PDGFRB, and FGFR1 abnormalities (Table 7.6). Table 7.6 Key points for PDGFRA, PDGFRB, and FGFR1 abnormalities Gene

PDGFRA

PDGFRB

FGFR1

Locus Detection Common presentation TKI therapy

4q12 FISH CEL

5q31∼32 Karyotypea CMML

8p11 Karyotype CEL, AML, T-LBL

Sensitive

Sensitive

Not effective

a Molecular

confirmation recommended.

Spectrum of Eosinophilia-Related Disorders Before further exploring the PDGFR- and FGFR1-associated neoplasms, a brief discussion is warranted regarding the broader context of eosinophilia, one of their most common manifestations. Distinction of neoplastic processes involving eosinophils from reactive eosinophilias has historically been challenging [104]. Eosinophilia is most often a T-cell-mediated, cytokine-driven process resulting from a variety of non-neoplastic conditions including parasitic or other infections, allergy, connective tissue disease, certain pulmonary diseases, and drug reactions [104, 105]. Additionally, reactive eosinophilias can be induced by a variety of malignancies, including Hodgkin lymphoma, T-cell lymphomas, lymphoblastic leukemia/lymphomas, and mastocytosis. Less than 1% of eosinophilias are part of a clonal neoplastic process, and these more often occur as part of a variety of myeloid neoplasms other than chronic eosinophilic leukemia, including CML or other myeloproliferative neoplasms, myelodysplastic syndromes, and acute myeloid leukemias [20, 105, 106]. Clonal eosinophils can also be seen with lymphoblastic lymphoma and systemic mastocytosis. Chronic eosinophilic leukemia (CEL) is a comparatively rare eosinophil-predominant myeloid neoplasm with increased peripheral blood and bone marrow eosinophils and either evidence of clonality or increased blasts (<20%). Due to their potential responsiveness to tyrosine kinase inhibitors, PDGFR- and FGFR1-associated neoplasms presenting with the morphologic findings of CEL are specifically excluded from a diagnosis of CEL, not otherwise specified, and are instead classified according to their specific molecular abnormalities [1] as described in more detail below. Finally, hypereosinophilic syndrome (HES) is a diagnosis of exclusion in the setting of persistent unexplained

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eosinophilia and evidence of organ involvement. It is a process of incompletely explained etiology that, while often morphologically indistinguishable from CEL, has no demonstrable evidence of clonality, and potential underlying etiologies of reactive eosinophilia have been excluded [1, 106, 107]. Although clonal Tcell receptor gene rearrangements have been demonstrated in some subjects with an HES-like presentation [108], these cases are excluded from the diagnosis of HES, and generally regarded as aberrant T-cell populations with cytokine-induced eosinophilia rather than a myeloid neoplasm. Because of the potential for tissue damage (including potentially life-threatening cardiac pathology) resulting from eosinophil tissue infiltration and degranulation regardless of etiology, potential correctable etiologies for eosinophilia should be exhaustively explored and excluded before a diagnosis of hypereosinophilic syndrome is considered [105].

PDGFRA Platelet-derived growth factor receptor (PDGFR) alpha is a member of the type III family of receptor tyrosine kinases that also includes PDGFR beta and KIT [82]. Its gene, PDGFRA, resides at 4q12. Abnormalities involving this locus result in constitutive activation of the PDGFRA tyrosine kinase activity and have been demonstrated in neoplasms with a range of clinical and morphologic features. Although sporadic reports of abnormalities involving the PDGFRA locus had previously been reported in eosinophilic neoplasms, the most common abnormality of this locus was first reported by Cools et al. in 2003 [109]. Their strategy was to look for abnormalities in patients with HES that had responded to imatinib therapy, with attention focused on PDGFRA, PDGFRB, and KIT based on previous studies showing that their tyrosine kinase products are targets of imatinib. Part of their analysis included using FISH probes to more closely evaluate a translocation involving 4q12 in one subject, revealing a deletion at this locus involving the CHIC2 gene. Additional studies showed the presence of a fusion gene, FIP1L1–PDGFRA, which resulted not from the translocation but from an 800 kb interstitial deletion on 4q12. Many subjects without any cytogenetically evident abnormalities also had the deletion and fusion, with 9 of 16 evaluated HES subjects ultimately testing positive [109]. Further characterization of this entity has shown male predominance and a median age of onset in the fifth decade [110, 111]. Splenomegaly and cardiac involvement are frequent findings, as are elevated vitamin B12 and serum tryptase levels [110–112]. The FIP1L1–PDGFRA fusion was also subsequently demonstrated by Pardanani et al. in three of five evaluated subjects with systemic mastocytosis with eosinophilia and, in marked contrast to the morphologically similar systemic mastocytosis cases that had the KIT D816V mutation, those with the FIP1L1–PDGFRA fusion achieved sustained complete response with imatinib [113]. A subsequent study by the same group screened 89 subjects with eosinophilia for the FIP1L1–PDGFRA fusion and found that after exclusion of clearly reactive cases (all of which were negative for the fusion), 14% of primary eosinophilias harbored the fusion [112]. Although 10

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of 11 positive cases were categorized by this group as systemic mastocytosis with eosinophilia, 7 of these had originally been diagnosed clinically as HES and were reclassified after elevated serum tryptase levels were seen in some, and careful bone marrow histologic and immunophenotypic evaluation showed increased numbers of immunophenotypically aberrant mast cells. The FIP1L1–PDGFRA fusion has also been described in association with T-lymphoblastic lymphomas and acute myeloid leukemias with eosinophilia that responded to imatinib [114]. The positive responses to imatinib in this clinically and morphologically diverse group of entities with features that overlap significantly with diseases that do not respond to imatinib underscores the relevance of molecular diagnostic testing in these cases. When present, the FIP1L1–PDGFRA most often occurs as a sole abnormality [110]. Unlike the BCR–ABL1 fusion, the FIP1L1–PDGFRA fusion does not depend on its 5 component, FIP1L1, for its function [115]. The breakpoints in FIP1L1 significantly vary compared with the relatively stable breakpoint region in PDGFRA in exon 12 involving the autoinhibitory juxtamembrane region [82, 108]. Disruption of this autoinhibitory domain has been shown to be required for constitutive activation and transforming potential [115]. An important point for hematopathologists and molecular diagnosticians is that this 800 kb deletion is too small to be detected at the level of conventional cytogenetic karyotyping. As such, one must remember to order a specific diagnostic test when this entity is considered in the differential diagnosis. Although some have successfully used RT-PCR to confirm the presence of the fusion [108, 110], the varied breakpoints in FIP1L1 make FISH a practical strategy of detection for clinical use. Perhaps the most common FISH probe strategy uses three probes, including probes 5 to the FIP1L1 breakpoints, 3 to the PDGFRA breakpoints, and within the expected deleted region [104, 110]. With this strategy, the presence of three signals indicates lack of deletion, while absence of the middle signal (within the deleted region) indicates presence of the deletion (Fig. 7.7).

PDGFRB Myeloid neoplasms associated with PDGFRB abnormalities represent another rare set of neoplasms with a range of clinicopathologic findings unified by the aforementioned molecular abnormality as well as their general responsiveness to tyrosine kinase inhibitors. PDGFR beta, also a receptor tyrosine kinase, is encoded by the PDGFRB gene located at chromosome 5q31∼32. The most common PDGFRBassociated abnormality is the t(5;12) (q31∼33;p12∼13) translocation, which creates a ETV6–PDGFRB fusion that was first described by Golub et al. in 1994 in subjects with chronic myelomonocytic leukemia (CMML) [111, 116]. A host of other rare translocations involving alternative fusion partners have also been described, all of which have been detectable by conventional cytogenetic karyotyping [111]. Alternative fusion partners with known or likely response to imatinib described to date include WDR48, GPIAP1, TPM3, PDE4DIP, PRKG2, GOLGA4, HIP1, CCDC6, GIT2, NIN, KIAA1509, TP53BP1, NDE1, RABEP1, and SPECC1

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D.S. Bosler ~800 bp deletion

FIP1L1

B.

KI T

CH IC 2

A.

PDGFRA

C.

Fig. 7.7 (a) The FIP1L1–PDGFRA fusion occurs through deletion of an interstitial DNA segment of approximately 800 kb. FISH probes placed in regions flanking the genes of interest and within the deleted area can be used to detect the fusion via loss of the signal in the deleted region (orange in this case). (b) The image on the left shows a normal signal, with two copies of an intact segment of the locus of interest on chromosome 4q12 resulting in two signals containing all three probes. The image on the right is from a cell line that contains two copies of the deletion and one normal allele, resulting in two signals containing only aqua and green (with orange absent), and one normal signal with all three probes

[1, 111, 117]. Regardless of the fusion partner, the fusion with PDGFRB results in constitutive activation of the tyrosine kinase via ligand-independent dimerization, which has demonstrated transformative properties [118]. In addition to CMML, PDGFRB abnormalities have also been described in cases with the clinicopathologic features of atypical CML, juvenile myelomonocytic leukemia, and chronic eosinophilic leukemia [117, 119–121]. As is seen with PDGFRA-associated neoplasms, mast cells may be increased and have morphologic and immunophenotypic aberrancies [117]. Overall, responses to imatinib in these disorders have been rapid, complete and relatively durable [116]. One study following 12 subjects with PDGFRB-associated chronic myeloproliferative disorders treated with imatinib reported that all 12 had rapid response and 11 had complete normalization of peripheral blood counts [122]. Median overall survival since diagnosis was 65 months, with 10 of 12 subjects still alive at last follow-up.

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Although the PDGFRB abnormalities are detected by conventional cytogenetics, the 2008 WHO Classification recommends that for definitive diagnosis these abnormalities should be confirmed at the molecular level, because t(5;12) translocations that do not contain that ETV6–PDGFRB fusion can be cytogenetically indistinguishable from those that do [1]. Since there are numerous potential partners, a breakapart FISH probe strategy using probes surrounding PDGFRB would be a potentially practical approach for this confirmation. Multiplex RT-PCR strategies that detect most of the common ETV6–PDGFRB fusion have also been demonstrated [123]. Additionally, the dramatic responses to imatinib in PDGFRA- and PDGFRB-associated neoplasms raise the question of whether methods of disease monitoring analogous to those used in CML should be implemented. The comparative rarity of these neoplasms has prevented a thorough analysis of this question to date, however, and more detailed studies are needed before a consensus can be reached.

FGFR1 FGFR1-associated hematolymphoid neoplasms are quite rare, with only about 50 cases reported [1, 111]. The first cases reported in the 1990s were characterized as presenting with T-lymphoblastic lymphoma with eosinophilia, subsequently developing myeloid malignancies such as AML or myeloid sarcoma and showing a t(8;13) translocation most often involving 8p11 [124, 125]. Also known as the 8p11 myeloproliferative syndrome and 8p11 stem cell leukemia/lymphoma syndrome, the involvement of the FGFR1 gene on 8p11 in these neoplasms was first characterized in 1998 by Xiao et al., who localized the defect to the disruption of FGFR1 intron 8 and described a ZNF198-FGFR1 fusion in four patients with t(8;13) (p11;q12) translocation-associated malignancies [126]. This most common fusion involves the 5 end of ZNF198 on 13q12 and the 3 end of FGFR1 (including exon 9) on 8p11. Although the 3 end of the FGFR1 gene is invariantly involved, numerous alternative 5 fusion partners have been described, including CEP110, FGFR1OP1, BCR, TRIM24, MYO18A, HERVK, FGFR1OP2, and CPSF6 [1, 82, 111, 127]. Similar to PDGFRB fusions, the FGFR1 fusions result in constitutive activation of FGFR1’s tyrosine kinase activity via ligand-independent dimerization and have been shown to induce hematolymphoid neoplasms in murine models that are analogous to that seen in humans [82, 128–130]. The heterogeneous spectrum of clinicopathologic presentations seen in the FGFR1-associated hematolymphoid neoplasms reflects the presence of an underlying defect in pluripotent stem cells with the ability to differentiate into myeloid or lymphoid cells [111]. The neoplasms can present as a myeloproliferative neoplasm such as chronic eosinophilic leukemia or CML-like disease, as acute myeloid leukemia, or as lymphoblastic leukemia/lymphoma (T-cell more often than B-cell) [131]. Acute leukemias can also be of mixed myeloid and lymphoid phenotype. Despite this heterogeneous range of presentations, about 90% have peripheral blood and/or bone marrow eosinophilia at presentation. In those that present with chronic

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disease, transformation to one of the acute manifestations usually occurs rapidly within 1–2 years of diagnosis [131]. Presentation is often relatively early in life, the median age at diagnosis is 32 years, and there is a slight male predominance [131]. The disease most often behaves aggressively and is refractory to chemotherapeutic regimens, with most patients dying of persistent or relapsed disease within 1.5 years [125, 131]. Allogeneic stem cell transplant is currently the only chance for cure. Unlike the other members of this group, FGFR1-associated neoplasms are not sensitive to imatinib. A newer tyrosine kinase inhibitor, PKC412, has been shown to inhibit tyrosine kinase activity in transformed cell lines and prolong survival in murine models [130]. Although these researchers also reported that one human subject with a FGFR1-associated myeloproliferative neoplasm showed improvement in leukocytosis and reduction of lymphadenopathy and splenomegaly when treated with PKC412, much more work is needed to more definitively characterize the drug’s effectiveness in this disease. The lack of established therapeutic regimens that might require precise quantitation for disease monitoring and the lack of known genotype–phenotype correlations with prognostic relevance make the current role of the molecular diagnostician relatively limited for the FGFR1-associated hematolymphoid neoplasms. The laboratory’s main role is ensuring that this rare entity is recognized when present. Since all reported abnormalities to date have been detectable by cytogenetic karyotyping, this method should be adequate means of detection in most cases. In the rare instance where clinical suspicion is very high despite negative cytogenetics, or where material for cytogenetic analysis is not available, an alternative strategy such as breakapart FISH at the 8p11 locus may be of benefit if demonstration of the abnormality is required.

Mast Cell Disease Mastocytosis is a rare and clinically heterogeneous disease characterized by a neoplastic proliferation of abnormal, clonal mast cells. Manifestations can be either primarily cutaneous or systemic, with frequent sites of systemic involvement including the gastrointestinal tract, liver, spleen, bone marrow, and lymph nodes [1]. Affected patients have an increased risk of associated myeloid neoplasms. The diagnosis and classification process of mastocytosis contains complexities that are beyond the scope of this text, and interested readers are referred to the 2008 WHO Classification and/or one of many published reviews on the topic [1, 132–134]. In summary, the diagnosis relies on some combination of the clinical findings, the presence of morphologically and immunophenotypically abnormal clusters of mast cells at affected sites, elevated serum tryptase levels, and the presence of the KIT D816V mutation. Like the other myeloproliferative neoplasms, the central molecular abnormality in mastocytosis causes constitutive activation of a tyrosine kinase. Mastocytosis involves KIT, a receptor tyrosine kinase in the same family as PDGFRA and PDGFRB that binds stem cell factor as its ligand [135]. The gene for KIT resides in

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close proximity to PDGFRA at 4q12 and contains 21 exons. Like the other tyrosine kinases discussed in this chapter, the downstream effects of KIT activation include cell proliferation, maturation, differentiation, and prolonged survival and are mediated through several familiar pathways including PI3K, MAPK, JAK/STAT, and protein kinase C. KIT is normally expressed in a variety of cell types, including mast cells, hematopoietic stem cells, germ cells, melanocytes, and interstitial cells of Cajal present within the gastrointestinal stroma. Interestingly, this distribution reflects the types of tumors in which KIT mutations arise, including not only mastocytosis but also acute myeloid leukemias and lymphomas, germ cell tumors, melanomas, and gastrointestinal stromal tumors [135]. A single nucleotide substitution in exon 17 of KIT (A7176T) resulting in a single amino acid change from aspartic acid to valine (D816V) is present in over 90% of adult systemic mastocytosis cases [136]. This most common mutation occurs within the activation loop of the TK2 domain and results in destabilization of the inactive conformation of KIT and ligand-independent activation [135, 137]. The mutation is present in mast cells, with variable expression in other hematopoietic cells [136]. A significant subset of D816V-negative cases has other KIT mutations (Fig. 7.8), which tend to cluster within the TK2 activation loop near D816 (amino acids 815–839) and within the extracellular cleavage, transmembrane, and juxtamembrane regulatory domains (amino acids 419 and 509–560) [135]. The importance of distinguishing between these mutation sites is that, while the D816V and other activation loop mutations are by-and-large resistant to imatinib therapy, some mutations within the transmembrane and juxtamembrane domains show sensitivity to imatinib [82]. Some newer generation tyrosine kinase inhibitors such as dasatinib have shown limited activity against systemic mastocytosis with D816V mutations, and PKC412 has

KIT Domains: Extracellular

Imatinib

Transmembrane

e sitiv

Mastocytosis Hotspots

Juxtamembrane

sen

resistant

TK1 TK2

D816V

PI3K

MAPK

Tyrosine kinase

PKC

Fig. 7.8 This schematic representation of the KIT receptor highlights the various function domains and hot spots for mutations within KIT that are associated with mast cell disease. The most common mutation in mast cell disease, KIT D816V, occurs in the TK2 domain. As is true with D816V, mutations in this region tend to be resistant to imatinib, while rarer mutations in the transmembrane and juxtamembrane domains may show some imatinib sensitivity

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also shown activity against D816V cases in very limited clinical experience [82, 138, 139]. KIT testing in mastocytosis has potential clinical relevance for both diagnosis and choice of therapy. Detection of D816V is one of the diagnostic criteria for mastocytosis and can help to confirm the diagnosis in otherwise challenging cases. Additionally, knowledge of the D816V mutation’s presence in a given case will likely dissuade the use of imatinib given the established lack of benefit. By contrast, detecting one of the rare mutations with potential sensitivity to imatinib may be of substantial benefit in individual cases, although the rarity of these cases likely makes routine evaluation for these mutations impractical except in the highest volume reference laboratories. Although detection of a single nucleotide substitution such as the KIT D816V mutation should be easily achieved by a variety of methods, the relative paucity of cells harboring the mutation, particularly in peripheral blood, can pose a challenge for detecting D816V in mastocytosis. Peripheral blood samples may preferentially be positive for mastocytosis cases in which the underlying defect originates in a multipotent stem cell and is therefore present in a variety of hematopoietic cells rather than restricted solely to mast cells [137]. Higher detection rates are therefore typical when testing bone marrow or lesional tissue compared with peripheral blood. Enrichment for mast cells, such as with flow cytometric sorting based on CD25 expression, often has a higher diagnostic yield than testing of unsorted specimens. Additionally, analysis of mRNA via RT-PCR helps to compensate for the paucity of cells carrying the mutation, since these cells express KIT at a high level [137]. Numerous methods have been employed in the detection of D816V for clinical purposes, including RT-PCR followed by RFLP analysis or direct sequencing, allele-specific PCR, and peptide nucleic acid (PNA)-mediated polymerase chain reaction clamping of the wild-type allele combined with oligonucleotide hybridization probes [137, 140]. Allele-specific PCR offers the advantage of sensitivity that can overcome the small percentage of tumor cells. For example, a sensitivity of 1% has been reported using DNA from formalin-fixed, paraffin-embedded tissue using allele-specific PCR combined with a wild-type blocking oligonucleotide [141]. The disadvantage of allele-specific PCR is that, since it detects only the mutations for which it has been designed, alternative methods would be required to detect the rare non-D816V mutations. One final relevant point for mast cell disease is that, since abnormal mast cells and increased eosinophils can occur in both of the PDGFR-associated myeloid neoplasms and mastocytosis, evaluation for all of these entities should be considered when this overlapping presentation is encountered. Although rarely encountered, this distinction has particular clinical relevance due to striking differences in response to imatinib therapy.

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123. Curtis CE, Grand FH, Waghorn K, Sahoo TP, George J, Cross NC. A novel ETV6-PDGFRB fusion transcript missed by standard screening in a patient with an imatinib responsive chronic myeloproliferative disease. Leukemia. 2007;21:1839–1841. 124. Abruzzo LV, Jaffe ES, Cotelingam JD, Whang-Peng J, Del DV, Jr., Medeiros LJ. T-cell lymphoblastic lymphoma with eosinophilia associated with subsequent myeloid malignancy. Am J Surg Pathol. 1992;16:236–245. 125. Inhorn RC, Aster JC, Roach SA, et al. A syndrome of lymphoblastic lymphoma, eosinophilia, and myeloid hyperplasia/malignancy associated with t(8;13)(p11;q11): description of a distinctive clinicopathologic entity. Blood. 1995;85:1881–1887. 126. Xiao S, Nalabolu SR, Aster JC, et al. FGFR1 is fused with a novel zinc-finger gene, ZNF198, in the t(8;13) leukaemia/lymphoma syndrome. Nat Genet. 1998;18:84–87. 127. Hidalgo-Curtis C, Chase A, Drachenberg M, et al. The t(1;9)(p34;q34) and t(8;12)(p11;q15) fuse pre-mRNA processing proteins SFPQ (PSF) and CPSF6 to ABL and FGFR1. Genes Chromosomes Cancer. 2008;47:379–385. 128. Roumiantsev S, Krause DS, Neumann CA, et al. Distinct stem cell myeloproliferative/T lymphoma syndromes induced by ZNF198-FGFR1 and BCR-FGFR1 fusion genes from 8p11 translocations. Cancer Cell. 2004;5:287–298. 129. Guasch G, Delaval B, Arnoulet C, et al. FOP-FGFR1 tyrosine kinase, the product of a t(6;8) translocation, induces a fatal myeloproliferative disease in mice. Blood. 2004;103:309–312. 130. Chen J, DeAngelo DJ, Kutok JL, et al. PKC412 inhibits the zinc finger 198-fibroblast growth factor receptor 1 fusion tyrosine kinase and is active in treatment of stem cell myeloproliferative disorder. Proc Natl Acad Sci U S A. 2004;101:14479–14484. 131. Macdonald D, Reiter A, Cross NC. The 8p11 myeloproliferative syndrome: a distinct clinical entity caused by constitutive activation of FGFR1. Acta Haematol. 2002;107:101–107. 132. Horny HP, Sotlar K, Valent P. Mastocytosis: state of the art. Pathobiology. 2007;74:121–132. 133. Pardanani A, Akin C, Valent P. Pathogenesis, clinical features, and treatment advances in mastocytosis. Best Pract Res Clin Haematol. 2006;19:595–615. 134. Hungness SI, Akin C. Mastocytosis: advances in diagnosis and treatment. Curr Allergy Asthma Rep. 2007;7:248–254. 135. Orfao A, Garcia-Montero AC, Sanchez L, Escribano L. Recent advances in the understanding of mastocytosis: the role of KIT mutations. Br J Haematol. 2007;138:12–30. 136. Garcia-Montero AC, Jara-Acevedo M, Teodosio C, et al. KIT mutation in mast cells and other bone marrow hematopoietic cell lineages in systemic mast cell disorders: a prospective study of the Spanish Network on Mastocytosis (REMA) in a series of 113 patients. Blood. 2006;108:2366–2372. 137. Akin C. Molecular diagnosis of mast cell disorders: a paper from the 2005 William Beaumont Hospital Symposium on Molecular Pathology. J Mol Diagn. 2006;8:412–419. 138. Gleixner KV, Mayerhofer M, Sonneck K, et al. Synergistic growth-inhibitory effects of two tyrosine kinase inhibitors, dasatinib and PKC412, on neoplastic mast cells expressing the D816V-mutated oncogenic variant of KIT. Haematologica. 2007;92:1451–1459. 139. Gotlib J, Berube C, Growney JD, et al. Activity of the tyrosine kinase inhibitor PKC412 in a patient with mast cell leukemia with the D816V KIT mutation. Blood. 2005;106:2865–2870. 140. Sotlar K, Escribano L, Landt O, et al. One-step detection of c-kit point mutations using peptide nucleic acid-mediated polymerase chain reaction clamping and hybridization probes. Am J Pathol. 2003;162:737–746. 141. Corless CL, Harrell P, Lacouture M, et al. Allele-specific polymerase chain reaction for the imatinib-resistant KIT D816V and D816F mutations in mastocytosis and acute myelogenous leukemia. J Mol Diagn. 2006;8:604–612.

Chapter 8

Molecular Pathology of Chronic Lymphocytic Leukemia Daniela Hoehn, L. Jeffrey Medeiros, and Sergej Konoplev

Keywords Chronic lymphocytic leukemia (CLL) · Small lymphocytic lymphoma (SLL) · Genetic predisposition · Conventional cytogenetics · Fluorescence in situ hybridization (FISH) · 13q14 deletion · Retinoblastoma gene (RB1) · D13S25 · D13S319 · miR-15a · miR-16-1 · 11q22-q23 deletion · Ataxia telangiectasia mutated (ATM) · MLL · RDX · NPAT · CUL5 · PPP2R1B · Trisomy 12 · CDK2 · CDK4 · STAT6 · APAF-1 · MDM-2 · 17p13 deletion · miR-34a · p53 mutation · 6q deletion · 3q27 trisomy · BCL6 · 8q24 gain · MYC · t(14;19)(q32;q13) · BCL3 · BCL2 · t(2;14)(p16;q32) · DNA methylation · Denaturing high-performance liquid chromatography (DHPLC) · Comparative genomic hybridization (CGH) · Single nucleotide polymorphism arrays (SNP arrays) · Multiplex ligation-dependent probe amplification (MLPA) · Gene expression profiling · microRNA · B-cell receptor (BCR) · IgH variable region (IgHV) · ZAP-70 · CD38 · Activation-induced cytidine deaminase (AID) · Somatic hypermutation (SHM) · Class-switch recombination (CSR) · Stereotyped BCR · Pharmacological inhibition of BCR signaling · LYN · SYK · AKT · ERK · MCL-1 · BCLXL · Dasatinib · Apoptosis · Caspases · CD95 · TOSO · CD40 · Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) · TCL-1 · Survivin · IL-4 · Stromal cells · CCL22/MDC · CCL-17/TARC

Introduction Chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL) are mature B-cell lymphoid neoplasms with an identical immunophenotype that are currently thought to be very closely related if not identical. As a result, the current World Health Organization classification of hematolymphoid diseases S. Konoplev (B) Department of Hematopathology, M.D. Anderson Cancer Center, Box 72, 1515 Holcombe Boulevard, Houston, TX 7030, USA e-mail: [email protected]

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has designated this disease as chronic lymphocytic leukemia/small lymphocytic lymphoma. Patients who present as CLL have lymphocytosis and bone marrow involvement and usually also have tissue sites of disease (lymph nodes, spleen, other organs). In contrast, patients who present as SLL have lymphadenopathy and commonly have involvement of bone marrow and other tissue sites of disease, but lack lymphocytosis. This chapter will discuss the cytogenetic and molecular genetic findings in CLL/SLL, and most of the data are derived from patients with CLL. For simplicity, from this point forward CLL/SLL will be referred to as CLL. Chronic lymphocytic leukemia is the most common hematological neoplasm of adults in western countries with an incidence of approximately 2–6 cases per 100,000 per year, increasing to 12.8 cases per 100,000 per year in the seventh decade. CLL represents approximately 7% of all non-Hodgkin lymphomas. A genetic predisposition to CLL is thought likely. Familial clustering of CLL cases can be documented in 5–10% of patients (Swedish cancer database). In addition, CLL has marked geographic variation. Chronic lymphocytic leukemia is rare in Asian countries, and this low incidence is maintained in populations that migrate to western countries, further supporting a genetic predisposition.

Cytogenetic Abnormalities The identification and frequency of chromosomal abnormalities in CLL are highly dependent on the method employed. The two methods typically used are conventional cytogenetics and fluorescence in situ hybridization (FISH). Traditionally, FISH has been far more sensitive than conventional cytogenetic analysis. The observed false-negative rate of conventional cytogenetic analysis has been attributed to the low proliferation rate of CLL cells. Using conventional cytogenetic techniques, chromosomal abnormalities are identified in approximately 50% of CLL, whereas genetic abnormalities can be detected in up to 80% of CLL cases using FISH probes. Recently, stimulation of CLL cells with either CD40 ligandexpressing cells and IL-4 or a combination of CpG-oligodeoxynucleotides and IL-2 has led to an increased frequency of metaphase spreads for detailed chromosome analysis in CLL [1, 2]. In the initial report [1], this approach revealed translocations in 33 of 96 (34%) of CLL patients. The presence of these translocations also defined a new prognostic subgroup with significantly inferior overall survival and shorter treatment-free survival (Fig. 8.1). Later studies showed that most of these translocations are not balanced and are accompanied by DNA losses at the breakpoints. In another study, after stimulation with CpG-oligodeoxynucleotides and IL-2, the rate of detection of abnormalities in CLL was comparable to the rate of detection by parallel interphase FISH [2]. Conventional cytogenetics using stimulation with CpG-oligodeoxynucleotides and IL-2 also frequently detected balanced and unbalanced translocations. The studies also suggested that there is a higher frequency of complex aberrations (more than three aberrations) in CLL than was appreciated using traditional methods. In a recent, large update on the results of metaphase cytogenetics after stimulation

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Fig. 8.1 The median survival times for the groups with 17p deletion, 11q deletion, 12q trisomy, normal karyotype, and 13q deletion as the sole abnormality were 32, 79, 114, 111, and 133 months, respectively. (Reproduced with permission from [4])

in more than 506 patients with CLL [3], 500 (98.8%) cases yielded metaphases. Aberrations were detected in 415 (83.0%) cases by conventional banding and in 392 (78.4%) cases by FISH. Conventional karyotyping detected a total of 832 abnormalities compared with 502 by FISH. A subgroup of CLL cases with a complex karyotype (16.4%) was identified. In addition, deletion 13q, the most common abnormality in CLL, could be further subdivided on the basis of the presence of translocations or complex aberrations [3]. Due to economical restraints there is a tendency to combine several probes specific to most common cytogenetic abnormalities in a panel, which makes FISH testing more cost-effective. Examples of application of this technique are illustrated in Fig. 8.2.

Deletion 13q14 Deletion of band 13q14 is the most common chromosomal aberration in CLL, in 40–60% of cases assessed by FISH. This deletion is associated with a long interval between diagnosis and the need for treatment [4]. The 13q14 locus is thought

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Fig. 8.2 An example of a commercially available fluorescence in situ hybridization panel for CLL. (a) So-called R tube containing the spectrum orange probe specific for p53 gene at 17p13.1 and the spectrum green probe specific for ATM gene at 11q22.3. Two cells labeled 2G2R (one being in interphase and one being in mitotic spread) demonstrate two preserved copies of both genes. Cells labeled 1G2R demonstrate loss of one allele of the ATM gene; a cell labeled 2G1R demonstrates loss of one allele of p53 gene; a cell labeled 1G1R shows loss of both p53 and ATM genes. (b) So-called B tube containing the spectrum orange probe specific for the 13q13.4 locus, the spectrum green probe specific for the centromeric region of chromosome 12, and the spectrum cyanic probe specific for the 13q34 locus. Two cells labeled 2R2A2G (one being in interphase and one being in mitotic spread) demonstrate a normal pattern. A cell labeled 1R2A2G demonstrates deletion of 13q13.4 locus; a cell labeled 2R1A2G demonstrates loss of the 13q34 locus; a cell labeled 2R2A3G shows gain of chromosome 12 (trisomy 12). (Microphotographs were kindly provided by Lynne V. Abruzzo, M.D., Ph.D)

to be the site of a tumor suppressor gene. Since the retinoblastoma gene (RB1) is located at 13q14, and FISH has shown monoallelic loss of the RB1 in 30% of CLL patients, RB1 deletion has been implicated in pathogenesis. RB1 encodes for a nuclear phosphoprotein that is involved in cell cycle regulation and transcription control. Disruption of both RB1 alleles by deletion or mutation, however, is extremely rare. These findings raise questions about the hypothesized pathogenetic role of RB1 in CLL. Other studies have shown that the minimally deleted region at 13q14 is 1.6 cM telomeric to RB1. Additional loci, D13S25 and D13S319, located distal to band 13q14 and more frequently deleted in CLL have been identified suggesting a novel tumor suppressor gene located in these regions. High-resolution genomic maps of these critical regions revealed several new genes from this area. BCMS and BCMSUN are more commonly deleted and require further research as potential tumor suppressor genes. Deletion or downregulation of two micro-RNA genes, miR15 and miR16, also has been implicated in CLL pathogenesis [5]. miR-15a and miR-16-1 are located in the minimally deleted region of 13q13.4. A germline mutation of miR-16-1 and miR-15a was able to cause lower levels of micro-RNA expression and was associated with deletion of normal alleles. Deletion or downregulation of these miRNA genes has been shown in 70% of CLL cases (but not in CD5+ B lymphocytes obtained from healthy donors) [6]. Moreover, a mutation that reduces the expression of miRNA15a and miRNA16-1 has been associated with loss of the other allele in CLL cells. This would support the hypothesis that this miRNA cluster functions as a

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tumor suppressor gene [5]. The roles of miR-15a and miR-16-1 as tumor suppressor genes in CLL have been verified in multiple studies that elucidated an inverse correlation between miRNA expression and BCL2 gene expression. Furthermore this cluster directly targets and represses expression of BCL2 in leukemic cells [7]. Cell growth and cell cycle progression have been shown to be negatively regulated by miR-16-1 [8]. miRNA expression also has prognostic implications as CLL patients with monoallelic 13q14 deletion have slower lymphocyte growth kinetics than do CLL patients with biallelic 13q14 deletion [9].

Deletion 11q22-q23 Structural aberrations of chromosome 11 are reported in 12–25% of CLL cases. 11q deletions are clinically associated with younger patient age, advanced clinical stage, and a worse prognosis. FISH studies have identified a critical region around the neural cell adhesion molecule (NCAM) at 11q23. This region is deleted in many hematological neoplasms [10]. A minimal consensus-deleted region of 2–3 Mb in size in bands 11q22.3-q23.1 has been shown [11]. This area is rich in tumor suppressor and other genes including FDX, ataxia telangiectasia mutated (ATM), MLL, and RDX. The ATM gene is involved in DNA repair. The frequent observation of lymphoma development in ATM knockout mice supports the function of ATM as a tumor suppressor gene [12, 13]. The absence of ATM protein expression in CLL cases further supports ATM being involved in CLL pathogenesis. Inactivation of ATM by deletion and/or mutation has been shown in multiple studies. More than two-thirds of CLL cases have monoallelic loss of ATM, while the other nondeleted allele often bears point mutations, most frequently located in the PI-3 kinase domain. Chronic lymphocytic leukemia cells carrying 11q22.3 deletions often show upregulation of genes that control cell cycle progression and signaling pathways. ATM-mutant CLL cases exhibit a deficient ATM-dependent p21 response to gamma irradiation, fail to upregulate tumor necrosis factor-related apoptosisinducing ligand receptor 2 (TRAIL R2), and therefore have an inability to repair chromosomal breaks. ATM mutations are associated with genetic instability, clonal evolution, and disease progression. ATM-mutant CLL cases uniformly lack immunoglobulin variable region (IGHV) somatic hypermutation. This association indicates their crucial key role for ATM at the pregerminal center stage of B-cell maturation, subsequently contributing to development of CLL. ATM gene mutations have been shown in CLL patients with and without del 11q [14, 15]. In a study of 155 CLL patients [15], ATM mutations were shown in 12% of cases and were associated with poorer prognosis. Most CLL patients with ATM mutations were refractory to DNA damaging chemotherapeutic drugs, and it has been suggested that these patients might benefit from agents bypassing the classical DNA damage pathway [15]. Interestingly, ATM mutations are only found in about

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one-third of the cases with 11q deletion suggesting that more complex mechanisms underlie the poorer prognosis of patients with deletion 11q [16]. A hypothesized regulator of ATM expression is the miR34b/miR-34c cluster. This cluster is located at the deleted region 11q23, centromeric to ATM. Other candidate genes in the 11q22-23 region include NPAT (cell cycle regulation), CUL5 (ubiquitindependent apoptosis regulation), and PPP2R1B (component of the cell cycle and apoptosis regulating PP2A) which are all down-regulated in CLL cases with 11q deletion.

Trisomy 12 Trisomy 12 was one of the first recurrent aberrations described in CLL, in 10–25% of cases. Detailed assessment by FISH studies has shown a minimally gained region limited to bands 12q13-q15. The gene (genes) in this region are presumably amplified and hypothesized to be oncogenes. Genes of oncogenic potential that are localized in this region include CDK2, CDK4, STAT6, APAF-1, and MDM-2. Although these genes play critical roles in the regulation of oncogenesis, cell cycle control, and apoptosis, their role in the CLL pathogenesis is yet to be elucidated. DNA microchip technology employing matrix comparative genomic hybridization (CGH) has shown the smallest replicated genomic regions in bands 12q13-q21 in CLL [17, 18].

Deletion 17p13 Chromosomal deletion of 17p13 occurs in 10–15% of CLL cases [19]. 17p deletion is associated with more aggressive clinical behavior and worse prognosis. Many of these cases show numerous copy number changes, many recurrent, and a highly unstable genome [20]. Chromosome 17p13 is the location of the p53 gene. Various studies have shown a prevalence of p53 mutations in the range of 10% of all CLL cases and higher in patients with 17p13 deletions. p53 mutations have been found in 4–17% patients with early stage CLL and have been associated with poor prognosis in a number of studies [21–23]. However, the exact prognostic relevance of TP53 mutations has not been conclusively documented within prospective trials. There is growing evidence that functional testing of p53 may be used to predict prognosis [24]. Deletion of 17p/p53 mutation has been associated with downregulation of miR34a. MiR-34a is transcriptionally induced by p53 and directly targets CDK6, CCND1, CDK4, CCNE2, and MET [25] expression in patients with CLL [26]. Furthermore, there appears to be a common ancestry for the miR-15a/miR-16-1 and miR-34b/miR-34c clusters [27]. Investigators have analyzed the transcriptome induced by overexpression of miR-34 in CLL. The transcriptome is highly enriched for genes that regulate cell cycle progression, DNA repair, angiogenesis, and apoptosis [28]. Multiple studies have shown miR-34a to be proficient in inducing cell cycle

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arrest and subsequent caspase-dependent apoptosis via BCL2 and E2F3 repression [29, 30].

Deletion 6q Deletions of the long arm of chromosome 6 have been shown by conventional cytyogenetics in 4–6%, and by FISH in up to 9%, of CLL cases. 6q deletions are not specific for CLL. At least two independently deleted regions have been shown in various types of non-Hodgkin lymphoma: 6q21-23 and 6q25-q27 [31, 32]. A minimally deleted region in band 6q21 spanning 4–5 Mb has been identified [33], but the identity of candidate gene(s) in this areas is unknown. Deletions of 6q are often associated with high leukocyte counts, extensive lymphadenopathy, and splenomegaly. Cases of CLL with del(6q) commonly have atypical morphologic features, including cleaved lymphocytes and increased larger cells, either immunoblast-like or prolymphocytoid cells.

Trisomy 3q27 Trisomy 3q is a rare, recurrent abnormality in CLL. The distal arm of 3q contains a minimally duplicated region and this region includes 3q27 which carries the BCL6 gene. BCL6 is commonly involved in chromosomal translocations in several types of B-cell lymphoma. The BCL6 gene also can undergo point mutations, somatic hypermutations, and microdeletions. Translocations involving BCL6 occur in 3% of CLL cases. The partner genes in BCL6 translocations are most commonly the Ig heavy or light chain genes; however, other BCL6 partners include Ras homolog gene family member H (RHOH) in the t(3;4), histone H1F1 in the t(3;6), Oct binding factor 1 (OBF1) in the t(3;11), and lymphocyte cytosolic protein1(LCP1) in the t(3;13). In most translocations the first noncoding exon of the partner gene fuses with the second exon of BCL6, resulting in deregulated expression of normal BCL6 protein. BCL6 encodes for a 706 amino acid zinc finger transcription factor and contains an N-terminal POZ domain. The 5 portion of BCL6 encodes for the BTB/POZ domain (broad-complex/tramtrack/bric-a-brac/pox virus/zinc finger) and the 3 end encodes for six DNA binding zinc fingers. BCL6 protein acts as a sequence-specific repressor of transcription. BCL6 can bind to DNA in a sequence-specific fashion and repress transcription and can recruit a variety of other POZ-containing proteins that will function as transcription corepressors/protein repressors. The carboxy terminus of BCL6 is responsible for sequence-specific DNA binding through its six zinc fingers, mediated through the consensus sequence TTCCT(A/C)GAA. The protein– protein interactions on the other hand are mediated through the BTB/POZ domain. BCL6 protein is required for normal germinal center formation and antibody affinity maturation and is highly expressed in germinal center B cells.

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8q24 gain Gains in 8q occur in a small subset of CLL cases [34]. The 8q24 locus is the site of MYC (previously known as c-MYC) which belongs to the MYC family of transcription factors. MYC family transcription factors contain a basic helix-loophelix leucine zipper domain. MYC encodes a transcription factor that is involved in regulating the expression of a significant number of genes in major cellular pathways. MYC abnormalities arise via translocation, mutation, or amplification. These abnormalities lead to upregulation of MYC expression and therefore unregulated expression of many other genes. The MYC gene has three exons. Two promoters, P1 and P2, control transcription and the choice of promoter depends on the MYC protein level. The P2 promoter is considered as most active, generating a 2.25 kb transcript, whereas the P1 promoter generates a 2.4 kb transcript. Expression of MYC, which is among the earliest events following stimulation of the protein kinase signal transduction pathway, can be successfully induced in CLL cells [35]. MYC overexpression in CLL is a marker of resistance to apoptosis [36]. Although rare in CLL, MYC translocations are associated with a poor prognosis. Affected patients have shorter survival, commonly present with increased prolymphocytes in blood and bone marrow, and additional cytogenetic abnormalities are common [37]. A typical finding of a case with MYC rearrangement is illustrated in Fig. 8.3. A mouse model attests to the role MYC plays in a subset of CLL. MYC overexpression cooperates with the B-cell receptor to induce lymphomas. In mice with MYC overexpression, with constitutive B-cell receptor signaling the tumors resembled CLL. In contrast, with antigenic stimulation of the B-cell receptor the tumors resembled Burkitt lymphoma [38].

t(14;19)(q32;q13) t(14;19)(q32;q13) is rare in CLL accounting for approximately 1% of cases. This translocation involves the BCL3 gene at chromosome 19q13 and the IgH gene at chromosome 14q32 [39]. BCL3 and IgH are joined in a head-to-head configuration resulting in overexpression of BCL3. The BCL3 gene encodes a protein of the IκB family and is involved in regulating the NF-kappa B family of transcription factor proteins. Unlike other IκB proteins, BCL3 functions as a coactivator of transcription and it inhibits NF-kappa B. Originally identified by its involvement in the t(14:19), BCL3 expression has been reported in 12% of non-Hodgkin lymphomas, including a subset of CLL cases, and 41% of Hodgkin lymphomas. Patents with CLL associated with t(14;19) tend to be of younger age and often have rapid disease progression and poorer prognosis. These neoplasms often have atypical morphologic features manifested by a mixture of small and larger lymphocytes, – and cleaved/indented nuclei. Occasional prolymphocytes are seen in some cases, but never exceed 10% Trisomy 12 and other abnormalities of chromosome

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Fig. 8.3 CLL with MYC rearrangement. (a) The bone marrow aspirate smear shows increased prolymphocytes (Wright-Giemsa ×1000); (b) In lymph node a pseudofollicle contains larger cells with prominent nucleoli (H&E ×400); (c) Conventional cytogenetic analysis performed on a G-banded metaphase demonstrates t(8;14)(q24·1;q32); (d) FISH study performed on metaphase and interphase cells using probes to the MYC (red signal) and IGH (green signal) loci demonstrates that the neoplastic cells contain a reciprocal translocation between the two loci (yellow signals). (Reproduced with permission from [37])

19 are common in these tumors [40, 41]. Typical findings in a case of CLL with t(14;19) are illustrated in Fig. 8.4.

Chromosomal Translocations Involving BCL2 The BCL2 gene at chromosome 18q21 is rearranged in rare CLL cases. Rearrangement usually occurs as part of translocations with Ig genes, with t(2;18)(p11;q21)/Igkappa-BCL2 and t(18;22)(q21;q11)/Iglambda-BCL2 more common than t(14;18)(q32;q21)/IgH-BCL2. Although translocations are rare, BCL2 is upregulated in all cases of CLL, and by suppressing apoptosis contributes to the prolonged lifecycle of CLL cells. Upregulation of BCL2 is most commonly related to deletions of two genes, miRNA15a and miRNA16-1, located at 13q14. In 70% of CLL cases deletions of miRNA15a and miRNA16-1 lead to overexpression of BCL2.

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Fig. 8.4 CLL with t(14;19)(q32;q13). (a) Bone marrow aspirate smear showing atypical morphology of neoplastic cells with high nuclear:cytoplasmic ratio and nuclear indentations; WrightGiemsa, ×1000. (b) Many of the neoplastic cells show strong nuclear staining for bcl3 (× 400). (c) A representative karyogram demonstrates the t(14;19)(q32;q13) and +12. Trisomy 12 is often seen in cases of CLL with t(14;19)(q32;q13). (Reproduced with permission from [41])

The miRNA genes belong to a highly conserved noncoding gene family, whose transcripts inhibit gene expression by causing degradation of mRNA or by blocking transcription of mRNA. MiR-15a and miR-16-1 are major direct negative regulators of the BCL2 antiapoptotic protein and, in addition are indirect activators of the intrinsic apoptotic program. This in turn activates the apoptotic peptidase activating factor:1/caspase-9/poly(ADP-ribose) polymerase pathway. The downmodulation of these two miRNAs in CLL has been correlated with altered expression of other antiapoptotic proteins and miRNAs. For example miR-29b expression is known to be downregulated in patients with CLL having poor prognosis. This miRNA suppresses MCL1, an antiapoptotic member of the BCL2 family.

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t(2;14)(p13;q32) The t(2;14)(p16;q32) is a rare, recurrent abnormality in CLL. The t(2;14) juxtaposes the BCL11A gene at 2p13 with IgH at 14q32. The BCL11A gene is the human homolog of the mouse EVI9 gene [42, 43]. The t(2;14) presumably occurs in activated B cells in the course of T-cell-independent immune responses outside the germinal center. This can be supported by the fact that these translocations are mainly targeted to the switch regions of the IgG2 gene, without T-cell-dependent immune responses [43]. The t(2;14) in CLL has been associated with younger patient age (including children) and atypical morphologic features, including plasmacytoid differentiation, irregular nuclei, and increased prolymphocytes. These neoplasms commonly have unmutated IGVH genes and express ZAP70 and CD38 [44]. Typical findings in a case of CLL with t(2;14) are illustrated in Fig. 8.5.

Fig. 8.5 CLL with t(2;14). (a) The aspirate smear demonstrates that many of the cells are cytologically atypical, with irregular nuclear contours and increased prolymphocytes (WrightGiemsa, ×1,000). (b) Conventional cytogenetic analysis demonstrating the t(2;14)(p16;q32); (c) Fluorescence in situ hybridization analysis was performed on interphase cells using a dualcolor, dual-fusion probe to BCL11A at 2p16 and IgH at 14q32. Reciprocal translocation involving the BCL11A and IgH genes generates yellow fusion signals on both derivative chromosomes. The normal chromosome 14 shows a green signal, and the normal chromosome 2 shows a red signal. A cell that contains the translocation is on the left; a cell without the translocation is on the right. (Reproduced with permission from [44])

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Translocations Involving Chromosome 14q32 When all translocations involving chromosome 14q32/IgH are tabulated, they occur in a small percentage of cases of CLL. These translocations are currently best detected by FISH. In general, patients with CLL that carry translocations involving chromosome 14q32/IgH, regardless of the partner chromosome, more commonly have advanced stage disease, unmutated IgH variable region genes, express CD38 and ZAP70, and have a poorer prognosis [45].

Epigenetic Changes Gene methylation is another mechanism of gene inactivation, and the field focused on the study of this phenomenon is known as epigenetics. With the advent of new methods for assessing DNA methylation, the importance of epigenetic changes in human cancers is well recognized [46]. In CLL, global DNA hypomethylation was initially detected 16 years ago [47]. The genome-wide patterns of DNA methylation in CLL are rather specific for CLL cells and can be reproduced in different patients [48, 49] suggesting that DNA methylation plays a specific role in the pathogenesis of CLL. Aberrant methylation has been described for specific genes in CLL, for example, hypomethylation of BCL2 and TCL1 [50, 51]. Unbiased genome-wide screens of CLL have shown specific methylation of the promoter region of TWIST2 [52] and of DAPK1 kinase [53]. When DNA methylation analyses were performed on the promoter region of ZAP-70, a specific CpG was methylated in 51 of 53 ZAP70-negative CLL cases. By contrast, no methylation was found in 30 of 32 ZAP70-positive CLL cases [54]. Apart from their role in pathogenesis and their potential utility in diagnosis, epigenetic modifications are also an interesting target for therapy as epigenetic modifications are reversible (in contrast with genetic aberrations). Several compounds have been tested on cells in vitro and in clinical studies and shown to be biologically and clinically active. An inhibitor of histone deacetylases (depsipeptide FR901228) was shown to selectively target CLL cells in vitro as compared with normal blood B cells and BM-derived progenitors [55].

High-Throughput Molecular Methods to Assess CLL Sequence and Mutation Analysis The availability of high-throughput techniques for mutation screening, e.g., denaturing high-performance liquid chromatography (DHPLC) will allow using mutation detection in larger cohorts of patients and in a timely fashion. The technique allows the detection of point mutations and small deletions on the basis of heteroduplex formation and the different mobility of the homoduplex (no mutation) and heteroduplex strand (mutation).

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The systematic analysis of mutations of these and other tumor suppressors within clinical trials will help to further delineate the prognostic value and clinical use of mutation assessment for clinical decision making in the treatment of patients with CLL. Currently there is no consensus on which method is best used for mutation analysis but the choice will often depend on local expertise and equipment. In addition to DHPLC, mutation analysis can be performed by direct sequencing, DGGE, SSCP, and array-based mutation analysis. Array Comparative Genomic Hybridization Comparative genomic hybridization (including array-CGH) is a microarray platform-based test, in which genomic hybridization is compared to an array of defined DNA fragments. General principles of array-CGH are illustrated in Fig. 8.6.

Fig. 8.6 General principles of comparative genomic hybridization array (CGH-A) and single nucleotide polymorphism array (SNP-A) arrays. (a) In array-CGH, control DNA (oligo or bacterial artificial chromosome probes) is used as reference for the test DNA (putative tumor DNA). Decreased copy number in the tumor DNA results in decreased intensity of the signal for the test and increased signal for reference DNA. (b) In SNP array, hybridization of amplified and labeled DNA with probes corresponding to alleles for each locus results in a genotyping pattern allowing for determination of the heterozygosity or homozygosity for each allele. At the same time, intensity of the hybridization signals allows for determination of copy number changes. (Reproduced with permission from [192].)

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Fig. 8.7 An example of array-CGH technique applied to CLL cases and revealing frequent submicroscopic 22q11 deletions. (a) Monoallelic loss of 22q11 was observed in a total of 24 cases and (b) biallelic loss was observed in a total of four cases. One case with (c) monoallelic loss and one case with (d) biallelic loss also exhibited concomitant gains of whole chromosome 22. (e) Oligonucleotide array-CGH analysis of the twenty-eight 22q11 deletion cases identified by BAC array-CGH revealed a minimally deleted 340,279 bp region that contained the ZNF280A (SUHW1), ZNF280B (SUHW2), PRAME, and GGTLC2 (GGTL4) genes. One CLL case with a monoallelic 22q11 deletion is shown. The green and red dots represent the fluorescence ratios of individual oligonucleotide probes on the microarray. Red dots represent probes with positive fluorescence ratios and green dots represent probes with negative fluorescence ratios. The cluster of green probes significantly shifted to the left of zero at 22q11 represents a small deletion. The vertical green bar at the left of the figure and the green-shaded rectangle represent the deleted region at 22q11. (Reproduced with permission from [56])

Array-CGH has been proven to be a sensitive tool in detecting new recurrent cytogenetic abnormalities [18]. Comparing array-CGH to chromosomal CGH in a large series of CLL cases, Schwaenen and colleagues demonstrated that the spatial resolution of array-CGH was much better and allowed the detection of small-sized imbalanced regions [18]. In this study, array-CGH allowed detection of previously unrecognized recurrent genomic imbalances as a copy number gain of chromosome 19 and the MYCN oncogene on 2p24 [18]. Recently, Gunn and colleagues used BAC array-based CGH to detect genomic imbalances in 187 CLL cases and demonstrated submicroscopic deletions of chromosome 22q11 in 28 cases (15%) with the frequency of these deletions being second only to loss of the 13q14 region [56] (Fig. 8.7). Oligonucleotide-based array-CGH analysis showed that the 22q11 deletions ranged in size from 0.34 Mb up to 1 Mb. The minimally deleted region included the ZNF280A, ZNF280B, GGTLC2, and PRAME genes. Quantitative realtime PCR revealed that ZNF280A, ZNF280B, and PRAME mRNA expression was significantly lower in the 22q11 deletion cases compared with nondeleted cases (Fig. 8.7) [56]. Single Nucleotide Polymorphisms Arrays Single nucleotide polymorphisms arrays (SNP-arrays) have recently been used for genome-wide detection of copy number changes in CLL [57]. In addition,

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SNP-arrays allow for the detection of uniparental disomy, a potential cause of loss of heterozygosity (LOH) without copy number changes. Pfeifer and colleagues applied SNP arrays to a large series of CLL patients and detected chromosomal imbalances in up to 82% of cases [57]. This study observed that aberrations of prognostic importance were identified at expected frequency [57]. In addition, 24 large (>10 Mb) copy number neutral regions with LOH were identified in 14 cases. These abnormalities are not detectable by other methods and may harbor relevant genes or loss-of-function alleles which may be important for the pathogenesis of CLL [57]. Multiplex Ligation-Dependent Probe Amplification Multiplex ligation-dependent probe amplification (MLPA) is a novel PCR-based technique to detect genomic alterations, which allows the analysis of more than 40 different small (50 pb) DNA sequences in a single reaction [58]. This technique relies on the comparative quantitation of specifically bound probes that are amplified by polymerase chain reaction (PCR) with universal primers and allows simultaneous processing of multiple samples. Coll-Mulet and colleagues performed MLPA analysis in CLL patients with the simultaneous identification of 55 genomic CLL-specific targets, and compared the results of the analysis with FISH data [58]. Results showed a good correlation between MLPA and FISH, as most of the alterations were detected by both techniques [58]. Gene Expression Profiling Array-based gene expression studies in CLL have shown remarkable results. The initial studies were able to detect a small group of genes that could differentiate mutated from unmutated CLL cases after supervised clustering [59, 60] (Fig. 8.8). A number of these genes have been confirmed to distinguish prognostic subgroups in CLL including ZAP70. Further studies on the gene expression profile in CLL demonstrated several important findings such as a gene dosage effect of the chromosomal aberrations [61], a p53-dependent signature in response to fludarabine treatment [62], and a highly sophisticated temporal program following the stimulation of CLL cells by B-cell receptor cross-linking [63]. Recently, a gene profiling study demonstrated the relationship of clinical variability and the expression of two gene clusters, associated with B-cell receptor signaling and mitogen-activated protein kinase activation [64]. The expression of these clusters dramatically separated patients into three groups with treatment-free survival probabilities at 5 years of 83, 50, and 17% [64]. MicroRNA This approach is one of more recently developed technologies applied to the analysis of CLL and other lymphomas and leukemias. As this is specifically discussed in another chapter in this book, we have mentioned relevant aspects of microRNA biology in this chapter but refer the reader to the complete discussion elsewhere.

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Fig. 8.8 Relative gene expression levels in CLL. (a) Hierarchical clustering of gene expression data for 205 array elements representing approximately 175 genes that were differentially expressed between Ig-mutated and Ig-unmutated CLL samples (P < 0.001). (b) Hierarchical clustering of genes that most strongly discriminated between the CLL subtypes. Also shown for each gene is the ratio of mean expression of the gene in Ig-unmutated CLL samples versus mean expression in Ig-mutated (high) CLL samples, together with the P values (Student’s t test) that quantitate the significance of the difference in mean expression between the two CLL subtypes. (c) RT-PCR analysis of ZAP-70 expression. Shown are data from two Ig-unmutated and two Ig-mutated CLL cases, a T-cell line (Jurkat), various B-cell lines found by microarray analysis to express ZAP-70 (LILA, LK6, OCI-Ly2), and a B-cell line not expressing ZAP-70. The control lane represents a reaction in which the reverse transcriptase was omitted. (Reproduced with permission from [59])

B-Cell Receptor Most cases of CLL express surface monotypic Ig light chain, IgM, and IgD. Surface Igs are usually expressed at low density/dim intensity for, in large part, still unknown

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reasons [65]. The Ig genes are composed of variable and constant regions, and the variable regions can undergo mutations in the complementarity determining regions (CDR), thought to be induced by exposure to antigen. Physiologically, these mutations permit the development of more specific antigen-antibody binding [66–71]. The complex of Ig light and heavy chain genes and other molecules expressed on the cell surface of all B cells, and specifically CLL, comprises the B-cell receptor (BCR). The BCR is a key molecule for understanding the molecular mechanisms of CLL. For the remainder of this chapter, we attempt to place molecular genetic findings in the context of BCR signaling. Somatic Mutations of Ig Variable Region Genes A milestone in understanding of CLL was the observation that somatic mutations of the Ig variable region genes occur in a subset of CLL cases and that the absence or presence of these mutations correlates with clinical course [72, 73] (Fig. 8.9). Somatic mutations occur in both the IgH and Ig light chain genes, but IgH variable region (IGHV) analysis is easier and adequate for prognostic purposes. An arbitrary cutoff of 2% or more mutations divides CLL into two prognostic groups. Patients with CLL in which the IGHV genes show < 2% somatic mutations (unmutated CLL) have a poor clinical outcome. It appears that CLL cells in this subset receive continuous antiapoptotic and/or proliferating microenvironmental stimuli via the BCR leading to more aggressive disease. In contrast, CLL patients in which

Fig. 8.9 (a) Somatic hypermutation of the V region of the IgH/IgL loci. Mutations that are targeted to the V region can result in either silent or replacement mutations at the amino acid level. (b) Kaplan–Meier plot comparing survival based on the absence (unmutated) or presence (mutated) of significant numbers (<2%) of V gene mutations in 47 B-CLL cases. Median survival of unmutated group: 9 years; median survival of mutated group not reached; P = 0.0001; log-rank test). (a) Reproduced with permission from [193]. (b) Reproduced with permission from [72]

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the IGHV genes show ≥ 2% mutations (mutated CLL) have a clinically indolent course [72, 73]. A difference in outcome was also demonstrated in CLL patients receiving an autologous stem cell transplant (ASCT); all patients with unmutated IGHV genes relapsed and progressed after a 4-year follow-up, whereas most patients with mutated IGHV genes remained in molecular remission [74]. Initially it was thought that CLL cases with unmutated IGHV genes (U-CLL) were derived from naive B cells, and that CLL cases with mutated IGHV genes CLL (M-CLL) derived from antigen-experienced B cells. It is now known that all CLL cells bear the surface membrane immunophenotype of being antigen experienced (CD27) and activated (expression of CD23, CD25, CD69, and CD71). Gene expression profiling has shown that CLL cells have a profile similar to memory B cells irrespective of IGHV mutational status [59, 60]. These findings suggest that all cases of CLL have a common cellular origin and/or common mechanism of transformation [59] and a continued requirement for antigen after the transformational event [75]. Comparative analysis of U-CLL and M-CLL, however, suggests that the neoplastic cells, by differing in their IGHV genes, have different antigen encounter histories [75]. It also has been suggested that an antigen-driven process might be critical for determining clinical features and for modulating disease outcome, irrespective of mutation status in B-CLL [76]. Signaling downstream of the BCR in CLL is dominated by the kinases LYN and SYK, which transduce survival and antiapoptotic signals after antigen triggers the BCR [77]. Antiapoptotic BCR signaling has been associated with prolonged activation of the MEK/ERK and PI3K/AKT pathways and with AKT-induced elevated expression of antiapoptotic MCL-1, which leads to increased survival of CLL cells [78]. Signal transduction via LYN is regulated and amplified via CD19 and these signals are responsible for the establishment of baseline signaling thresholds in B cells before antigen-receptor ligation, in addition to augmenting tonic signaling following BCR engagement [79]. LYN was identified as a major contributor to antigen-independent BCR signaling, as it is strongly overexpressed, constitutively active and aberrantly present in the cytosol [77]. The recruitment and subsequent activation of SYK to immunoreceptor tyrosine-based activation motifs within the cytoplasmic tails of Igα and Igβ seems to be disturbed in CLL, as alternative transcripts of Ig have been described [80]. CLL clones with a proliferative response to BCR ligation have considerably higher Syk levels than nonresponsive ‘anergic’ CLL cells [81], and the tyrosine kinase ZAP-70 can partially restore BCR signaling when Syk is not expressed [82]. ZAP-70, which is involved in T-cell receptor signaling, is aberrantly expressed in some patients with CLL and shows partial, but not complete, overlap with the presence of unmutated IGHV genes [83, 84]. Currently, the detection of ZAP-70 in neoplastic cells can be performed both by flow cytometry immunophenotypic studies and by immunohistochemistry. An example of immunohistochemical analysis in bone marrow is illustrated in Fig. 8.10. High ZAP-70 expression in CLL cells is associated with more aggressive disease. While M-CLL cells are considered anergized, U-CLL cells seem to retain some capacity for competent BCR signaling, with an increased tendency to phosphorylate

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Fig. 8.10 Immunohistochemical study for ZAP70 expression using fixed, paraffin-embedded tissue of a bone marrow aspirate clot section. Note dim ZAP70 expression by CLL cells and brighter ZAP70 expression by intermixed reactive T cells. (a), ×200; (b), ×1000

SYK and to recruit and phosphorylate ZAP-70 [85]. The presence of ZAP-70 can enhance and prolong BCR signaling in CLL independent of its tyrosine kinase function, probably by acting as an adaptor protein [82]. CD38 is another potential modifier of BCR signaling that shows substantial overlap with ZAP70 expression and unmutated IGHV genes. CD38 is a molecule that affects proliferation and longevity of the neoplastic clone [86]. CD38 ligation by monoclonal antibodies results in proliferation and blastic transformation of a subset of CLL cells, and engagement of CD38 as a receptor is a Lyn-dependent process [87]. Dynamic localization to lipid rafts and lateral association of CD38 with the BCR, CD19, and CD81 was reported to be a prerequisite for CD38mediated signaling and both enhancement and refinement of BCR signaling [88]. Importantly, ZAP-70 represents a limiting factor in the CD38 signaling pathway, probably serving as a cross-point where BCR signals are enhanced and where migratory signals from chemokine receptors intersect with growth signals mediated via CD38 [89]. Activation-induced cytidine deaminase (AID), an enzyme involved in the somatic hypermutation (SHM) process and class-switch recombination (CSR) during normal B-cell differentiation [90], is upregulated in U-CLL cells [91] and is functional with generation of isotype-switched transcripts and mutations in the preswitch μ region [92, 93]. AID upregulation causes mutation in genes associated with aggressive disease (e.g., BCL6, PAX5, MYC, RHOH) [94, 95]. In addition, an association of AID expression with deletions in 11q- and loss of TP53 has been demonstrated [96]. A main determinant of BCR-mediated signaling in CLL may be the expression level of surface IgM, which is generally upregulated in U-CLL and downregulated to anergy in M-CLL [85]. Another possible explanation for anergy in M-CLL may be chronic exposure to soluble antigens in the absence of co-stimulatory signals [97] and of unresponsiveness to BCR signaling owing to receptor desensitization. It also has been shown that BCR translocation to lipid rafts differs in M-CLL compared with U-CLL. Constitutive exclusion of the BCR from lipid rafts was observed in

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M-CLL and could be responsible for impaired interactions between the BCR and the actin cytoskeleton [98]. This molecular signature of anergy in CLL is characterized by constitutive activation of MEK and ERK [99]. As anergy occurs primarily in M-CLL, this may explain why ERK phosphorylation defines CLL cases with a favorable prognosis [99]. Stereotypy Biased use of IGHV genes has been described in CLL. The VH1 gene family of the IgH gene and the VIIIb family of the Igkappa gene are used in the formation of Ig gene rearrangements more often than can be explained by chance alone. DNA sequence analysis of the variable (V), diversity (D), and joining (J) segments involved in IgH and Igkappa gene rearrangement has shown that a subset of CLL have somatic mutations [4, 100]. It has been demonstrated that unrelated and geographically distant patients with CLL share quasi-identical sequences of BCR. In one large series, 15 of 1,220 unrelated patients (1.3%) carried virtually identical unmutated IGHV created by rearrangement of the IGHV1-69, IGHD316, and IGHJ3 genes [101]. Several groups have reported CLL subsets carrying BCR characterized by non-random pairing of specific IGHV, highly homologous, or identical HCDR3 often associated with a restricted selection of IGVK or IGVL light chains (the so-called stereotyped BCR) [101–109]. These stereotyped BCR have been detected in more than 20% of CLL cases [102, 104, 105, 109]; the nonrandom composition of the expressed BCR on the CLL cells with IG binding has lead to the hypothesis of that similar/identical antigens are involved in pathogenesis [102, 104, 105, 110]. The frequency of stereotyped BCR is higher in U-CLL [107]. Most clusters are composed of U-CLL cases [102, 104–107, 109]. In particular, these clusters include CLL cases that express autoreactive and polyreactive BCR, allegedly derived from the B-cell compartment devoted to the production of natural antibodies [108, 110, 111]. Among “common” clusters, of particular clinical interest is a cluster composed by U-CLL cases with stereotyped BCR expressing genes from the IGHV1 gene family other than IGHV1-69 (IGHV1-2, IGHV1-18, IGHV1-3,IGHV1-46, IGHV74-1), homologous HCDR3 bearing the QWL amino acid motif, and IGKV1-39 light chains [102, 104, 105]. The prognosis of CLL patients whose neoplasms express this stereotyped BCR is poor, compared with all the other CLL patients or CLL patients in whom their tumor expresses the same IGHV genes but without the same stereotyped BCR [102, 105]. Among the few clusters of M-CLL cases there are two clusters, both expressing IgG, composed by cases expressing IGHV4-34 and IGHV4-39, respectively [102, 104, 105, 112, 113]. Specific cluster-biased genomic aberrations have been found; 13q has been associated with the IGHV4-34/IGKV2-30 cluster and trisomy 12 has been associated with the IGHV4-39/IGKV1-39 cluster [113]. The latter cluster has been associated with the development of large B-cell lymphoma (Richter syndrome) [114, 115]. Other clusters, mainly composed of M-CLL cases and expressing IGHV3 are less frequent and might be subjected to a geographical

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bias. Of particular interest is a group of IGHV3-21 CLL, composed of cases with either unmutated or mutated IGHV genes, that express a stereotyped BCR characterized by an unusually short and highly homologous HCDR3 associated with IGLV3-21 [103, 106, 116–118]. A significantly skewed representation of this particular cluster has been well documented in different European and non-European countries and even in different regions from the same country [103, 116–118]. It was clearly demonstrated that patients belonging to IGHV3-21/IGLV3-21 CLL cluster have shorter time to treatment compared with all M-CLL cases and with M-CLL cases that express IGHV3-21, but not included in this stereotyped cluster [103, 105, 116]. The molecular basis for a more aggressive clinical behavior of CLL belonging to the IGHV3-21/IGLV3-21 CLL cluster is also suggested by gene expression profiling and immunophenotypic analyses [103]. There are current proposals to use IGHV3-21 expression to drive clinical decisions in prospective trials [119, 120]. It also has been observed that cases expressing the IGHV3-23 gene are constantly absent from stereotyped BCR clusters [121], despite the fact that IGHV3-23 is frequently used, usually in cases of M-CLL [102, 103, 105]. A possible explanation justifying the absence of IGHV3-23 genes from clusters of stereotyped BCR is that IGHV3-23-expressing BCR might be selected through non-CDR-based recognition mechanisms, e.g., through interactions with superantigens, a general feature of BCR expressing IGHV3 subgroup genes [121–124]. IGHV3-23 expression has been identified as an independent negative prognosticator in the context of M-CLL [121]. Another example of the clinicobiological implications of BCR stereotypy is provided by cases that utilize the IGHV4-34 gene [102, 104]. This gene encodes antibodies that are intrinsically autoreactive by virtue of universal and largely light chain-independent recognition of the N-acetyllactosamine (NAL) antigenic determinant of the I/i blood group antigen [125, 126]. The IGHV4-34 gene is used at a high frequency in normal individuals; however, IGHV4-34 cells are censored at multiple checkpoints during B-cell development to alleviate their autoreactivity [127]. This finding explains why IGHV4-34 antibodies are virtually undetectable in healthy sera, despite the abundance of IGHV4-34 B cells in normal individuals. In contrast, IGHV4-34 antibodies are secreted at high levels in patients with systemic lupus erythematosus (SLE) and closely related to tissue damage and disease activity [127]. The IGHV4-34 gene is also frequently used in CLL and usually employed in M-CLL cases [102, 104, 128], perhaps reflecting the fact that IGHV4-34 sequences must undergo somatic hypermutation (SHM) in order to negate their autoreactivity and become sufficiently ‘safe’ to be allowed into the functioning Ig repertoire. Several groups have reported that a major subset of CLL cases expressing stereotyped IgG-switched, mutated BCRs employ the IGHV4-34 gene in association with the IGKV2-30 gene [102, 104, 107]. The IGHV4-34/IGKV2-30 stereotype (subset 4) is shared by greater than 1% of patients with CLL. As first shown by a Mediterranean group, subset 4 is also characterized by striking clinical similarities [102]. In particular, cases belonging to this subset were significantly younger at diagnosis and had indolent disease.

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The IGHV4-34/IGKV2-30 Ig stereotype of subset 4 cases is characterized by long, positively charged HCDR3, enriched in aromatic and positively charged amino acids, similar to pathogenic anti-DNA antibodies [129]. Furthermore, subset 4 VH and VK domains exhibit very distinctive SHM patterns, typified by the frequent introduction of acidic residues (especially aspartic and glutamic acid residues) [104]. All subset 4 IGHV4-34 sequences were also recently reported to carry intact NAL-binding motifs [104]: thus, in theory, these IGHV4-34-expressing CLL cells could still be bound (and stimulated for clonal expansion) by NAL-containing epitopes present in various auto- and exo-antigens. These superantigen-like interactions could provide the signals promoting survival, expansion, malignant transformation, and potentially clonal evolution. CLL cells often produce BCRs/mAbs (monoclonal antibodies) that bind autoantigens in a polyreactive manner [130–132], similar to ‘natural antibodies’ [133]. In recent studies using recombinantly expressed mAbs from CLL patients with both unmutated and mutated IGHV, about 80% of U-CLL mAbs and about 15% of M-CLL mAbs reacted in enzyme immunoassays with various self and foreign antigens in a polyreactive pattern [111]. Similarly, these mAbs reacted with fixed and permeabilized cells, as in a standard clinical anti-nuclear antibody assay that is used to define systemic autoimmune disorders. However, the reactivity of CLL mAbs with intracellular targets was primarily directed against cytoplasmic structures [111], unlike Abs from patients with autoimmune disorders like SLE that frequently, although not exclusively, react with molecules residing in the nucleus. In related studies, mAbs derived from Epstein–Barr virus (EBV)-immortalized CLL B cells and from soluble mAb elaborated by CLL cells stimulated in vitro with differentiating agents, reacted with tissue antigens of human tonsil and rat aortic smooth muscle [110]. As the monoreactivity of several of the M-CLL mAbs could be changed to polyreactivity by reverting the Ab amino acid structure to that of the germline gene, it appeared that most CLL B cells emanate from normal B lymphocytes with poly/autoreactive BCRs [111]. In an attempt to define the cytoplasmic, autoantigenic targets recognized by CLL cells, mAbs from subset 1 patients [102] were used to probe HEp-2 cell lysates in immunoprecipitation experiments [134]. The BCRs/mAbs of subset 1 patients are characterized by unmutated rearrangements involving IGHV1-69, IGHD3-16, and IGHJ3, with nearly identical HCDR3 sequences that are paired with unmutated IGKV3-20 having equally restricted KCDR3s [101, 102, 107]. These mAbs selectively isolated a molecule of 225 kDa, which upon amino acid sequencing was identified as nonmuscle myosin heavy chain IIA (MYHIIA) [134], a major molecular motor of normal cells. By using another member of this mAb subset in similar immunoprecipitation experiments, the identity of MYHIIA as the target of this group of CLL mAbs was corroborated. In addition, exposure of cells to reagents that alter MYHIIA amounts (specific siRNA) and cytoplasmic localization (blebbistatin) resulted in a corresponding change in binding to these mAbs, thereby confirming that MYHIIA was their intracellular target [134]. Similar studies were carried out with a mAb from a patient whose clone belonged to subset 8 that exhibits a stereotypic rearrangement of IGHV4-39, IGHD6-13, and IGHJ5 associated with

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an IGKL1-39 rearrangement containing an Arg at the IGKV–IGKJ junction. These studies revealed vimentin as a target for this subgroup of mAbs [B75]. Furthermore, these studies identified other cytoskeletal components as targets of CLL mAbs, e.g., filamin B and cofilin-1 [110].

Pharmacological Inhibition of BCR Signaling Pharmacological inhibition of BCR signaling could provide a twofold effect disrupting both tonic and antigen-ligation-dependent BCR signaling. Potential therapeutic targets for inhibition of BCR signaling in CLL are LYN and SYK [97]. Specific inhibition of LYN and SYK induces apoptosis of CLL cells in vitro, which indicates that these kinases primarily transmit prosurvival signals [97]. Inhibition of LYN might partially mimic an anergic state, as is present in M-CLL. Dasatinib, an ABL and SRC-kinase inhibitor, induces apoptosis in primary CLL cells in vitro, with a preference for the U-CLL or ZAP-70+ CLL subsets, at concentrations clinically achievable by oral administration [135]. Preliminary data from a currently ongoing phase II clinical trial of dasatinib in heavily pretreated patients with relapsed CLL demonstrated several patients with partial responses in lymph nodes and reductions of lymphocyte counts [136]. Decreased signaling via survival-signaling cascades involving AKT and ERK, reduced expression of antiapoptotic MCL-1 and BCL-XL, and increased p53 levels are also considered to be the basis of the antiproliferative and proapoptotic capacity of dasatinib [135]. Ex vivo, CLL lymph node samples display strong ERK activation and high levels of BCL-XL and MCL-1; this has been attributed to CD40-triggered events [137]. Protein kinase C (PKC) and phosphatidylinositol 3-kinase (PI3K)-mediated signaling pathways are centrally involved in controlling apoptosis and CLL survival [138]. Approaches that target several isoforms of PKC are under clinical investigation. Several PKC isoforms are constitutively active in CLL [139]. Some PKC isoforms are key mediators of BCR signaling (for example, PKCβII, which is overexpressed in CLL) [140], whereas other isoforms induce AKT activation independent of BCR ligation and PI3K in CLL cells [141]. PKCδ is permanently activated and downstream of the constitutively activated PI3K in CLL. Specific blockade of PKCδ by rottlerin induces apoptosis and synergizes with vincristine in CLL cells but not in normal B lymphocytes [142]. It is possible that the synergistic effect of rottlerin is sufficient to disrupt the balance between antagonizing PKCα and PKCδ isoforms [142, 143]. The PKC modulator, bryostatin 1, increases CD20 expression via MEK1/ERK signaling in a PKC-dependent manner in CLL cells and leads to a twofold increase in apoptosis induction by rituximab [144]. Rituximab achieves inhibition of the RAF/MEK/ERK signaling pathway, resulting in BclxL downregulation and chemosensitization [145]. Farnesyl transferase inhibitors, known to block RAS activity and ERK phosphorylation, have been shown to induce apoptosis in primary CLL cells refractory to standard therapy [146]. Inhibition of MEK significantly enhances cytotoxicity of purine analogs in a CLL cell line [147].

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Apoptosis It is of interest that MYHIIA and vimentin, and possibly other nucleic acid-binding intracellular molecules, transmigrate to the external surface of cells undergoing programmed cell death [148–150]. This finding is consistent with the observation that many U-CLL mAbs (about 60%) and some M-CLL mAbs (about 10%) react with the surfaces of apoptotic cells and not the same cells in the viable state [110, 151, 152]. Within the apoptosis-reactive CLL cases, those using IGHV1-69 were the most abundant, and mAbs from patients with mutated IGHV3-21 were less reactive, indicating that not all CLL mAbs encoded by IGHV genes associated with poor clinical outcome necessarily bind apoptotic targets. CLL blood cells typically undergo apoptosis when cultured in vitro, indicating that in vivo accumulation of leukemic lymphocytes is favored by other factors probably originating from the microenvironment. By studying cells at different times after the induction of apoptosis, it was found that some of the intracellular antigens bound by CLL cells translocated to the surface membrane and could be identified in apoptotic blebs [151, 152]. Animal studies indicate that some of the target antigens that appear during apoptosis represent chemical modifications of lipids, lipoproteins, or proteins[153]. These modifications are often the consequences of oxidation [154]. It was demonstrated that proteins or lipoproteins that were not normally recognized by CLL mAbs in their native state became targets of these mAbs after oxidative modification [110, 151]. Such modified molecules [e.g., bovine serum albumin (BSA) derivatized with malondialdehyde] inhibited the binding of certain CLL mAbs to apoptotic cells [110, 151], suggesting that at least some of the epitopes recognized on apoptotic cells by CLL mAbs were neoantigens created during the apoptotic process Antibodies reactive with neoepitopes created during apoptosis can also recognize phosphorylcholine (PC) a molecule hidden in cell membranes of mammalian and microbial cells but exposed during apoptosis [155]. It has been shown that CLL mAbs recognize PC and PC-substituted molecules [110, 151], suggesting that CLL mAbs reactive with autoantigens or neoantigens also bind bacterial cell wall components. These data confirm the observation that most U-CLL mAbs react with intact bacteria of multiple strains [156]. Apoptotic Pathway Multiple signals converge in CLL cells to influence cellular fate. Cell death is regulated by a network of cellular signaling cascades that are also influenced by intracellular sensor modules [157]. Upon ligation, these receptors create a platform for activation of initiator caspases that directly feed into a caspase cascade leading to cell death [158]. A number of death signaling components have been characterized in CLL. CLL cells express CD95 but are largely resistant to CD95 cross-linking [159]. Overexpression of the CD95 regulator TOSO in CLL might contribute to CD95 resistance [160]. Although CD40 signaling upregulates CD95, CLL cells commonly

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remain resistant to CD95 triggering [161]. IL-15 treatment also is able to sensitize CD40-stimulated CLL cells to CD95 cross-linking [162]. In addition, CD40Lstimulated CLL cells were rendered CD95 sensitive by XIAP (X-linked inhibitor of apoptosis protein) inhibition using non-SMAC (second mitochondria-derived activator of caspases) mimetic, synthetic compounds [163]. Also, CD40-activated CLL cells are effectively killed by genetically engineered effector cells expressing both the CD95 ligand (CD178) and TRAIL (tumor necrosis factor-related apoptosisinducing ligand [164]. The ex vivo phenotype of CLL is one of resistance to TRAIL [165]. However, two publications have shown that histone deacetylase inhibition sensitizes CLL cells to the effects of TRAIL, and that the TRAIL receptor DR4, but not DR5, is involved in cell killing [165, 166]. As mentioned above, CD40 has a prominent role in CLL pathogenesis. In terms of cell death regulation, CD40 signaling has been suggested to trigger major reprogramming along the BCL-2 governed pathway to cell death [167–169]. In parallel to a pattern observed in CLL from lymph node tissue, CD40L triggers upregulation of Mcl-1 and A1, as well as Bcl-xL antiapoptotic proteins [168]. BCR signaling has been reported to also regulate Mcl-1 [78]. This was suggested to be mediated via AKT signaling. AKT has also been shown to target BH3-only proteins BAD and BIM for deactivation by phosphorylation [170, 171]. Interestingly the Akt signal seems to be positively modified by TCL-1 overexpression, which is found in a relatively large proportion of CLL patients and has been proposed to be a consequence of dysregulation of the microRNAs, miR-29, and miR-181 [170, 172]. In addition, miR-15 and miR-16 have been proposed to be the basis of constitutive BCL-2 overexpression in CLL [7, 170, 173]. Another reported signal that modifies cell death machinery is IL-21, which mediates apoptosis through upregulation of BIM [174].

Role of the Microenvironment Chronic lymphocytic leukemia cells maintain their capacity to respond to selected external stimuli that confer a growth advantage and extended survival. In vitro, spontaneous apoptosis of CLL cells can be rescued by the co-culture with ‘nurselike cells’ or stromal cells [175–179]. Adherent nurse-like cells are able to protect leukemic cells from spontaneous apoptosis [180]. Activated autologous T cells co-cultured with CLL cells also prevent apoptosis [177, 178]; this action can be somehow replaced by T-cell derived cytokines (i.e. IL-4) and exposure to T-cellrelated molecules (i.e., sCD40L) [178, 181]. In addition to rescuing leukemic cells from apoptosis, CD40 stimulation can induce their proliferation [182, 183] and activation as shown by upregulation of cell surface molecules (e.g., CD80, CD95), as well induction of chemokine production (e.g., CCL-22/MDC, CCL-17/TARC) [184, 185] and apoptosis regulators (e.g., survivin) [182]. Normal activated T cells are numerous in tissues involved by CLL where they are mainly located in proliferation centers [184] and intermingled with leukemic cells that express activation molecules and have increased proliferative activity [184].

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These findings suggest that T-cell-mediated activation is also occurring in vivo, resembling a sort of immune reaction, and reinforce the concept of a sustained immune stimulation in CLL. The presence of prolymphocytes and paraimmunoblasts, the correlation between size and numbers of proliferation centers, and the lymphocyte doubling time [186] strongly indicate that proliferation centers are the reservoir of dividing leukemic cells. Therefore, the dogma that CLL is a static disease, resulting solely from an accumulation of apoptosis-resistant leukemic cells, needs to be reconsidered. Investigation of telomere length and telomerase activity [187, 188] as well as kinetics studies [189] indicate that CLL is a dynamic process composed of cells that proliferate and die, often at appreciable levels. It seems clear that most proliferating cells are found in tissues where CLL cells can exploit microenvironmental interactions in order to avoid apoptosis and acquire a growth advantage. Experimental findings suggest that CLL cells in tissues interact with activated T cells that influence leukemic cell proliferation and provide short-term antiapoptotic support, while stromal cells (and other accessory cells, e.g., nurse-like cells) provide long-term support that favors the extended survival and relentless CLL cell accumulation [177, 190]. These and other pieces of experimental evidence indicate that different microenvironmental components deliver fundamental and specific signals for the maintenance and expansion of leukemic B cells at different time points in the natural history of CLL. At the same time, CLL cells are active players in shaping the microenvironment according to their needs, thanks to the production of selected chemokines (i.e., CCL22/MDC and CCL-17/TARC) which recruit activated T lymphocytes that will ensure provision of signals (e.g., IL-4 and CD40 ligation) favoring malignant cell growth and survival. As CLL cells express CXCR4 [157], they can drift away from T cells toward the surrounding stromal cells which are the main producers of CXCL12/SDF-1 [191], the CXCR4-specific ligand, probably avoiding a T-cell-mediated limit to their expansion (e.g., via CD95–CD95L interactions) [161], and at the same time, taking advantage of the long-term support by stromal cells. All these data support the importance of the microenvironment in the natural history of CLL.

Conclusions Molecular characterization of the abnormalities in CLL has been and continues to be important for a number of reasons. From the scientific view point these studies help to identify the genes and the mechanisms involved in hematopoiesis and the pathogenesis of CLL. Further progress may help to identify targets for rational drug design or gene therapy. From a more immediate clinical perspective, information gleaned from these studies has improved the accuracy of diagnosis, helped to predict therapeutic response, provided criteria for selecting high-risk patient groups who may benefit from intensive but highly toxic chemotherapy protocols or bone marrow transplantation, and aids in the detection of minimal residual disease before clinical relapse.

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Chapter 9

Targeted Therapy in Hematologic Malignancies Barbara Zehnbauer and Mona Nasser

Keywords Tumor · Genetics · Therapy · Targeted · Chemotherapy · Molecular · Cancer · Therapies · Antibodies · Anti-cancer · Immune · Cytotoxicity · Cytotoxic · Tumor · Monoclonal · Antibodies · Human · Therapeutic · Chimeric · Resistant · Treatment · Trials · Kinase · Inhibitor · Kinase · Cancer · JAK2 · Activation · Molecule · Inhibitors · Imatinib · CML · Binding · Resistance · Mutation · Nilotinib · Dasatinib · ATRA · Retinoic · Repression · APL · AML · Mutations · Classification · Target · Angiogenesis · Thalidomide · Immunomodulatory · Apoptotic · Relapsed · Vaccine · Immune · Virus · Membrane · Targeted · Agents · Inhibitor · Antitumor

Introduction The utility of tumor-specific molecular genetic signatures in the clinical care of patients with cancer has been well documented. Many diagnostic criteria of disease categories and subtypes have been revised to include defining genetic signatures such as the BCR–ABL1 fusion protein produced as a result of the formation of the Philadelphia chromosome, a translocation between chromosomes 9 and 22. This is the hallmark diagnostic finding in more than 95% of patients with chronic myelogenous leukemia (CML). Genetic markers have also been recognized as prognostic indicators of likelihood of response to treatment or disease progression. BCR–ABL1 is an indicator of poor prognosis in some pediatric patients with ALL because this marker is associated with poor response to therapy and a poor duration of response. Studies from many clinical centers have also validated the utility of using these signatures to stratify patients to the most effective treatment regimens based on historic outcome-based studies. These therapies have ranged from chemotherapy and stem cell transplantation to immunotherapy and small molecule drugs. In addition, the B. Zehnbauer (B) Division of Laboratory Systems, Laboratory Practice Evaluation and Genomics Branch, Centers for Disease Control and Prevention, 1600 Clifton Road NE, Mail Stop G23, Atlanta, GA 30329, USA e-mail: [email protected] D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_9, 

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defining molecular signature may be used to track the efficacy of the treatment by monitoring levels of residual cancer cells throughout the course of treatment. Now anti-cancer therapies may specifically target the tumor-specific gene products within the cancer cells, bypassing normal cells of the same lineage. Only cancers that bear the genetic mutations will respond to these targeted therapies, requiring specific, sensitive, and timely molecular diagnostic tools to aid the oncologist in characterizing the cancers of patients who may be candidates for these genetically designed drugs. In this chapter we will review the categories of targeted therapies that are in use to treat hematologic malignancies including leukemia, lymphoma, and multiple myeloma.

Targeted Therapy: Definitions and Classification The concept of a “magic bullet” therapy to selectively target specific cells to cure disease was originally introduced by Paul Ehrlich for microbial infections in 1891. Nearly a century later, this concept was applied in the anti-cancer therapeutic field. Recent molecular and genetic advances have led to the identification of many of the molecules that are overexpressed in cancer cells, or involved in the process of transformation of normal cells into cancer cells (carcinogenesis) [1–3]. As a result, a new generation of anti-cancer drugs, called “targeted therapy,” has been developed to target and specifically act on these molecular targets. These strategies have been termed “molecular targeted therapy” and are integral components of current personalized medicine. These targeted treatments hold the promise of not only more effective anti-cancer action but also reduced toxicities and adverse side effects because normal cells are not targeted [4, 5]. Three definitions for targeted cancer therapies have generally been applied [6]. The first definition describes targeted therapy as the use of any drug that precisely focuses on a distinct molecular target and/or interferes with a specific signaling pathway resulting in the prevention of cancer growth and progression. The second usage expands the definition of targeted therapy to include antibodies joined with cytotoxic agents, cytotoxic radioisotopes, and cellular poisons to selectively target cancer cells. The third, adopted by the Food and Drug Administration (FDA), defines targeted therapy as a drug with an approved label that can be administered only after an approved diagnostic test has been performed to establish a patient’s eligibility for that drug. In other words, the label of the drug has a reference to the prerequisite of testing for a valid molecular biomarker. For example, patients with metastatic colorectal cancer are candidates for cetuximab if overexpression of EGFR (epithelial growth factor receptor) can be demonstrated with a diagnostic test required to qualify for the drug. Both the test and the drug are considered a combination product as they meet the following criterion outlined by the FDA: “Any investigational drug, device or biological product packaged separately that according to its proposed labeling is for use only with another individually specified

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investigational drug, device or biological product where both are required to achieve the intended use, indication or effect” [7]. Conventional cytotoxic chemotherapeutic agents act mainly on rapidly proliferating cells by inhibiting cell division or inducing damage to the DNA replicated in these cells. Inadequate specificity is the major drawback to this mechanism because rapid proliferation is a shared feature of both cancer and some normal cells. Thus, toxicity to actively dividing normal cells is a common side effect to this type of therapy. In contrast, targeted therapy achieves specificity by focusing on distinct characteristics and specific pathways of cancer cells [8, 9]. The main advantage of targeted therapy over traditional cancer therapies, such as chemotherapy and radiation, is the ability to specifically target cancer cells without harming or destroying normal cells [4]. The specificity requires a molecule that is critical to the malignant phenotype (expression) but at the same time is not expressed in vital organs or tissues. The availability of an analytical testing method for quantifying the molecular target of the cancer cells is an essential factor for identification of the population of patients who are eligible for this therapy based on the likelihood of a favorable response to treatment. Moreover, an ideal molecular target has a pivotal prognostic role; interfering with that target provides a significant and measurable impact on the clinical course of the disease [6]. The ideal target may be difficult to define; BCR–ABL1 tyrosine kinase has been the best example of a tumor-specific signature targeted by a specific small molecule inhibitor, imatinib mesylate. This hybrid protein in patients with chronic myeloid leukemia (CML) is crucial to the malignant process [10]. There are several methods to categorize targeted therapies in the literature. The National Cancer Institute classification is the one most commonly used [5]. It categorizes targeted therapeutic agents as follows: 1. 2. 3. 4. 5. 6.

Therapeutic monoclonal antibodies Small molecule drugs Angiogenesis inhibitors Apoptosis-inducing drugs Cancer vaccines Gene therapy

Small molecule drugs and therapeutic monoclonal antibodies are considered to be the main categories of targeted therapy for hematologic malignancies [9, 11]. However, there may be some overlap between different categories because some drugs may have more than one pharmacodynamic property. Medical care providers may view the third and fourth categories as subgroups of the first and second. For example, bevacizumab is considered to be a monoclonal antibody that has antiangiogenic properties, while bortezomib may be classified as a small molecule drug that induces apoptosis [4]. Some agents of targeted therapy have been approved by the FDA, while many others are still in preclinical testing or clinical trials [5, 8].

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Of 20 anti-cancer therapies approved by the FDA during 2000–2008, 15 have been targeted agents [9, 12].

Therapeutic Monoclonal Antibodies in Targeted Therapy Monoclonal antibodies (mABs) used in targeted anti-cancer therapy are antibodies produced by genetic engineering to be directed against specific antigens that are expressed primarily or solely by malignant cells [8]. They are water-soluble proteins of high molecular weight (150,000 Da) which are unable to penetrate cells; thus they target extracellular components of the cells, such as an extracellular binding domain of receptor protein molecules [9, 11]. Monoclonal antibodies are usually more efficient in targeting hematologic malignancies than solid tumors due to the ease of accessing hematopoietic cells and the low diffusion efficiency through solid tumor tissues to individual cells [1, 8, 11]. These agents are usually administered by intravenous injections to avoid denaturation of the protein content, which would occur in the gastrointestinal tract following oral intake [9]. The basic antibody molecule is composed of four immunoglobulin polypeptide chains: two identical light chains and two identical heavy chains. The light chains each have two regions – one constant region domain (CL) and one variable region domain (VL) – while the heavy chain has four regions – three constant region domains (CH1, CH2, CH3) and one variable region domain (VH). The variable region domains of the fragment antigen-binding (FAB) region have highly variable amino acid sequences and define the complementarity-determining regions (CDRs) which are responsible for antigen-binding specificity [11]. The fragment crystallizable region (Fc region) is derived from the constant domains and forms the tail part of an immunoglobulin protein [8]. The constant region has more conserved amino acid content and encodes the protein region responsible for the induction of an immune-mediated response upon binding of the Fc receptors in the effector cells to proteins of the complement complex [1, 9, 11, 13, 14]. Most therapeutic monoclonal antibodies with a human framework are of IgG1 subclass due to their long half-life and the capability to induce immune responses mediated through their Fc regions such as antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cell-mediated cytotoxicity (CDCC), and complement-dependent cytotoxicity (CDC) [1, 11]. Therapeutic mABs may execute their targeted anti-cancer action via three different approaches: direct inhibitory effect on the tumor, induction of immune-mediated mechanisms, and delivery of cytotoxic materials to the tumor cells [1, 9, 11, 15]. In the first approach, mABs act directly by binding to certain receptors or ligands, usually on the cell surface of the tumor, to inhibit signal transduction pathways that are crucial to cancer cell survival or proliferation. This direct antigen–antibody binding mechanism may exert its effect by blocking the binding site of the ligand, inhibiting receptor heterodimerization, or promoting receptor internalization [16, 17]. Inhibiting the molecular signaling cascade can lead to the arrest of the cell cycle, the reduction of angiogenesis [18], the inhibition of DNA repair [19],

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or the induction of apoptosis [11]. Monoclonal antibodies targeting proteins of the epithelial growth factor receptor (EGFR) family are considered the most effective signal transduction inhibitors [1]. In the second approach, mABs induce immune-mediated responses in which mABs tag the target tumor cells which the immune system components subsequently attack and destroy [8, 14]. Binding of a mAB to its target on the tumor cell surface leads to the interaction between the antibody Fc region and the Fc receptor on the immune effector cells (macrophages and natural killer cells).The effector cells mediate phagocytosis and lysis of the antibody-coated tumor cells via the so-called antibody-dependent cellular cytotoxicity (ADCC) mechanism [11]. Moreover, activation of the complement cascade can be initiated by binding mAB to the tumor cell. This cascade reaction either induces complement-dependent cytotoxicity (CDD) during which a membrane attack complex (MAC) leads to tumor cell lysis or induces complement-dependent cell-mediated cytotoxicity (CDCC) through the generation of C3b, an opsonin which enhances phagocytosis of the tumor cells by the effector cells [11, 20]. In the third approach, mABs are conjugated with cytotoxic agents such as toxins, radioisotopes, drugs, or cytokines to selectively transport these agents to the targeted cancer cells [1, 11]. Though mABs may show high selectivity toward a specific target, they may lack sufficient cytotoxicity. Binding of a mAB to a certain target may not guarantee a powerful killing activity by itself. On the contrary, the cytotoxic agents frequently have potent cell killing effects but lack adequate selectivity. The conjugation process may be perceived as a mechanism to either provide the required cytotoxicity to the mAB or the selectivity of the mAB to the cytotoxic agents. This combined transport mechanism facilitates the use of potent cytotoxic agents by avoiding the potential high toxicity and adverse side effects on normal tissue [21]. Conjugation with the mAB prolongs the serum half-life of the conjugate cytotoxin and “detoxifies” it. A cytotoxic drug remains joined to the mAB during circulation, which keeps it biologically inactive, i.e., “non toxic” during transit. It resumes its cytotoxicity on separation from the mAB within the cell. Upon attachment to the target cell, internalization of the conjugate takes place by endocytosis. After internalization, cleavage of the link between the drug and the mAB occurs in the lysosomes to discharge the cytotoxic drug in its active form within the cell. Internalization is important for cytotoxic drugs and toxins to destroy the cells and spread throughout the tumor [21]. This is not a limitation of radioisotope conjugates because isotopic decay particles may penetrate 1 cm to destroy cells along the particle path [14]. Though considered to be an attribute for unconjugated antibodies, prolonged circulation half-life of the radioconjugates is undesirable because prolonged exposure of the bone marrow to radiation may produce severe myelosuppression [22]. In 1975, Georges Kohler and Cesar Milstein developed the somatic hybridization technique, or hybridoma technology [23], by fusing malignant myeloma cells with antibody-producing B cells to generate specific monoclonal antibodies. This technique produced clonogenic hybrid cells with immortalized replication and production of specific antibodies to enable mass production of identical antibodies

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that target selected antigens. Initially, monoclonal antibodies were derived from mouse cell hybridomas which hindered their use in the therapeutic field due to their immunogenicity [24], clearance by human anti-mouse antibodies, short half–life, and reduced ability to induce an immune effector action [9, 11, 25]. Advances in recombinant DNA technology and genetic engineering facilitated the subsequent production of chimeric, humanized, and human types of monoclonal antibodies with a greater fraction of human immunoglobulin component, consequent lower immunogenicity, longer half-life, and increased efficacy [26]. Both chimeric and humanized types of mABs are derived from two species, human and murine, in different proportions. In the chimeric antibodies, the constant regions of the immunoglobulin are derived from human origin and represent 75% of the mAB protein content, while the variable regions are of murine origin [24]. The suffix of the name of the mAB-drug indicates the type of monoclonal antibody by denoting the species of origin as follows: mumab (human), -zumab (humanized), -momab (murine), -ximab (chimeric) [9]. In 1997, the FDA approved rituximab (a chimeric antibody) as the first therapeutic monoclonal antibody to target cancer, which achieved a radical change in the treatment of non-Hodgkin’s lymphoma (NHL) [11, 14, 27]. Subsequently, several chimeric mABs have been approved by the FDA for therapeutic purposes (Table 9.1). Although chimeric mABs have notably decreased immunogenicity and the human anti-mouse antibody reactions, these adverse side effects have not been entirely eliminated [28]. There remains a need for further reduction of the immunogenicity to accomplish tolerance to the increased and multiple dosing required to combat some cancer targets [29, 30]. Increasing the human component in mABs not only decreases the xenogenicity and immunogenicity but also enhances the immune function mediated by the mAB through effective interaction between the human Fc region and the Fc receptor on the immune effector cells [14]. The humanized type of mAB has been developed with 95% human component with the complementarity-determining regions (CDRs) remaining as the only murinederived fraction [11, 31]. Specific targeting is maintained in both the chimeric and the humanized mABs by the murine variable region fragment. Ultimately, development of human monoclonal antibodies with 100% human component has been achieved (Table 9.1) [1, 6, 11, 14, 32]. Specific therapeutic monoclonal antibodies approved by the FDA for treatment of various hematologic malignancies are summarized in Table 9.1. General features of most of these mABs are as follows: 1. Most of these therapies target lymphoid malignancies. 2. They target cell surface molecules that are expressed on both normal and neoplastic cells. 3. The target molecule is not expressed on hematopoietic stem cells. 4. All are administered intravenously. 5. They may be used in conjunction with chemotherapeutic agents without increased toxicity.

Rituxan

Mylotarg

Campath

Rituximab

Gemtuzumab ozogamicin

Alemtuzumab

90Y-Ibritumomab Zevalin tiuxetan

Trade name

Generic name of the agent

CD20

CD52

CD33

CD20

Target

Murine IgG1

Humanized IgG1

Humanized IgG4

Chimeric IgG1

Antibody Non-Hodgkin’s lymphoma (NHL)

Hematologic malignancy

Conjugation with yttrium-90 radioisotope

NHL

Acute myeloid Conjugation leukemia with toxin (AML) calicheamicin; cleaves DNA; caspase-mediated apoptosis Immune-mediated Chronic cytotoxicity lymphocytic leukemia (CLL)

Immunemediated cytotoxicity

Mechanism of action Monitoring

FDA approval

CBC; CD4 counts; 2001 avoid live vaccines; Herpes and Pneumocystis prophylaxis recommended CBC; pretreatment 2002 Severe, prolonged antibody titers in myelosuppression; patients who have severe mucocutaneous received other reactions; risk of murine-based secondary malignancies radioimmunother(e.g., acute myeloid apy leukemia); radiation regimens safety precautions required for 1 week after administration

Hematologic toxicity opportunistic infections; rash

CBC; signs of active 1997 Rheumatoid arthritis; HBV infection or lymphocytopenia; HBV hepatitis in reactivation; severe mucocutaneous reactions patients who are HBV carriers Live vaccines should be avoided Severe CBC; electrolyte 2000 myelosuppression; levels; liver hepatotoxicity chemistries

Adverse effects

Table 9.1 Therapeutic monoclonal antibodies: approved by the FDA for hematologic malignancies or investigational clinical trials

9 Targeted Therapy in Hematologic Malignancies 299

NA

NA

Lumiliximab

Epratuzumab

CD22

CD23

CD20

Arzerra

Ofatumumab

Target

CD20

Trade name

[131 I]Tositumomab Bexxar

Generic name of the agent

Humanized IgG1(κ, kappa)

NA

Humanized IgG1(κ, kappa)

Murine IgG2

Antibody

Immune-mediated cytotoxicity

Immune-mediated cytotoxicity

Immune effector B-cell lysis (CDC and ADCC)

Conjugation with iodine-131 radioisotope

Mechanism of action

Relapsed or refractory, indolent B-cell NHL

B-cell CLL

Refractory B-cell CLL

NHL

Hematologic malignancy

Table 9.1 (continued) Monitoring

FDA approval

CBC; thyroid function 2003 Hypothyroidism; tests; pretreatment severe, prolonged antibody titers in myelosuppression; patients who have nausea and vomiting; received other secondary murine-based malignancies (e.g., radioimmunotheracute myeloid apy leukemia); radiation regimens safety precautions required for 1 week after administration 2009 Cytopenia, pneumonia, CBC; multifocal fever, cough, diarrhea, leukoencephalopafatigue, dyspnea, rash, thy; risk for nausea hepatitis B virus reactivation Unspecified Unspecified Phase II clinical trials Unspecified Unspecified Clinical trials

Adverse effects

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NA

Remitogen

NA

NA

NA

MT103

AME-133, GA101, veltuzumab

Apolizumab

HCD122

MDX-1411

Galiximab

Blinatumomab

CD19 and CD3

CD80

CD70

HLADRß (beta)1D10 CD40

CD20

Target

Recombinant bispecific

Human IgG1

Human

Human

Humanized

Antibody

CDC

ADCC of tumor necrosis factor (TNF)-expressing cells ADCC

ADCC

Fcγ(gamma)RIIIa; activates natural killer (NK) cells; FcRγ(gamma)III, ADCC; caspase-independent apoptosis Immune effector B-cell lysis (CDC and ADCC)

Mechanism of action

Relapsed B-cell NHL T-cell CLL

CLL

CLL

Unspecified

Unspecified

Unspecified

Unspecified

Unspecified

Unspecified

CLL

Relapsed or refractory CLL

Adverse effects

Hematologic malignancy

Unspecified

Unspecified

Unspecified

Unspecified

Unspecified

Unspecified

Monitoring

Phase III clinical trials Phase 1 clinical trials

Phase 1 clinical trials Phase 1 clinical trials

Phase II clinical trials

Clinical trials or preclinical investigations

FDA approval

CD, cluster of differentiation; CBC, complete blood count; CDC, complement-dependent cytotoxicity; ADCC, antibody-dependent cellular cytotoxicity; NHL, non-Hodgkin’s lymphoma; AML, acute myeloid leukemia; CLL, chronic lymphocytic leukemia; NA, not available. Data from [1, 4, 6, 7, 9, 11, 14]

Trade name

Generic name of the agent

Table 9.1 (continued)

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Examples of Investigational Monoclonal Antibodies in Hematologic Malignancies The success of rituximab and alemtuzumab in targeting non-Hodgkin’s lymphoma and chronic lymphocytic leukemia has increased the interest in the development of more targeted antibody therapeutic approaches. Rituximab is a chimeric antibody; thus there is a need to develop fully humanized antibodies to minimize infusion reactions and eliminate the development of human antibodies against the drug. Clinical evaluation of alternative antibodies based on knowledge of antigen expression on the surface of lymphoma cells [33] has led to the development of antibodies against CD22 [unconjugated epratuzumab and calicheamicin conjugate CMC-544 (inotuzumab ozogamicin)], CD80 (galiximab), CD52 (alemtuzumab), CD2 [MEDI-507 (siplizumab)], CD30 [SGN-30 and MDX-060 (iratumumab)], and CD40 (SGN-40) (Table 9.1). In addition, the VEGF inhibitor bevacizumab, which was first approved for the treatment of colon cancer, is currently under investigation for treating NHL. Small molecules that bind directly to receptor molecules (agonists) directed to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) are also being investigated as treatments for both advanced solid tumors and NHL, instead of targeted antibodies [33]. Cancer cells may become resistant to a targeted therapy by activating an alternative pathway to evade apoptosis. This has prompted studies of combination treatment regimens of mABs (such as epratuzumab plus rituximab) or mABs plus chemotherapy such as CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) and other schema [33]. Soluble forms of the antigens (sCD30) represent potential mechanisms of resistance by binding mAB before the mAB can bind to the lymphoma cell. Antibody-based therapeutic approaches have already had a profound impact on the treatment of NHL, and continued refinement will optimize the clinical benefits [33]. The characteristic B-cell immunophenotype of the lymphocytosis associated with chronic lymphocytic leukemia (CLL) (CD5+ /CD19+ /CD20+ /HLADR+ /CD23+ /surface immunoglobulin dim) [34] is also a target of specific mAB agents including lumiliximab (anti-CD23) [35] (summarized in Table 9.1). Other mABs such as AME-133 not only have high specificity for CD20 but also contains an Fc region which binds CD16 [Fcγ(gamma)RIIIa] with high affinity, thus improving its ability to activate natural killer (NK) cells. GA101 is a humanized anti-CD20 with high affinity for FcRγ (gamma)III, producing enhanced ADCC and strong caspase-independent apoptosis activity to bind CD20 [36]. Veltuzumab is another humanized IgG1κ (kappa) monoclonal antibody that, despite targeting the same CD20 epitope as rituximab [37], has shown clinical activity at lower doses than rituximab. Epratuzumab, an anti-CD22 mAB of the IgG1κ (kappa) class, is active as a single agent [38], and in combination with rituximab, for the treatment of patients with relapsed or refractory, indolent B-cell NHL. Apolizumab (Hu1D10; Remitogen) is designed to target the HLA-DRß (beta) polypeptide, on 80–90% of cases of CLL, and is currently being tested in patients with relapsed or refractory CLL [39]. HCD122 and MDX-1411 are mABs which target CD40 and CD70, respectively; they are being evaluated in phase I trials for patients

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with CLL [35]. Several novel immunotherapeutics may also be implemented in the treatment of CLL including bispecific monoclonal antibodies (anti-CD20 and anti-CD22) [40]; small molecule immunopharmaceuticals targeting CD37, a glycoprotein strongly expressed on the surface of CLL cells; and T-cell antibodies such as blinatumomab (MT103/MEDI-538), which targets CD19 and CD3 simultaneously. These are currently undergoing evaluation in phase I clinical trials [41].

Small Molecule Drugs Small molecule drugs, also known as kinase inhibitors, signal transduction inhibitors, and small molecule inhibitors [5, 42, 43], are drugs that interfere with the function of molecules involved in the processes and pathways of carcinogenesis primarily targeting kinases. FDA-approved small molecule drugs used in treating patients with hematologic malignancies are summarized in Table 9.2. Kinases regulate the phosphorylation of other proteins by the transfer of the terminal phosphate of adenosine triphosphate (ATP) to serine, threonine, or tyrosine amino acid residues [42, 44]. The human genome encodes nearly 518 kinases which mediate multiple signal transduction pathways by regulating the transfer of phosphate molecules through cascades that control diverse cell processes including proliferation, differentiation, contact inhibition, angiogenesis, apoptosis, and cell cycle progression [45]. Genetic mutations, gene overexpression, or chromosomal translocations may cause deregulation of phosphorylation patterns and consequently aberrant signal transduction deregulation that can lead to tumorigenesis [4, 9, 11, 44]. Approximately 100 tyrosine kinases have been identified, which include two groups of enzymes: cytosolic, non-receptor tyrosine kinases (non-RTKs) and transmembrane receptor tyrosine kinases (RTKs) [8, 11, 43]. At least 58 receptor tyrosine kinases (RTKs) have been identified and are grouped into 20 subfamilies [45]. Epidermal growth factor (EGF) receptor, platelet-derived growth factor (PDGF) receptor, vascular endothelial growth factor (VEGF) receptor, and the RET proto-oncogene protein are examples of receptor tyrosine kinases [4, 8, 11]. Binding of a ligand (e.g., growth factor) to the extracellular domain of the receptor tyrosine kinase activates the receptor. This initiates a cascade of signaling via phosphorylation of intracellular proteins which conveys the extracellular signal to the inside of the cell [45, 46]. The extracellular ligand-binding domain of the receptor is frequently targeted by a therapeutic monoclonal antibody, while the intracellular catalytic domain may be targeted by a small molecule drug [8, 11, 47]. Examples of non- receptor tyrosine kinases (non-RTKs) are the oncogenic protein products of the SRC, ABL1, and JAK2 genes. The SRC oncogenic protein was the first non-receptor tyrosine kinase identified [43, 48] and represents a group of nine cytoplasmic proteins that are important in many cellular processes including cell growth and differentiation, cell adhesion and motility, carcinogenesis, immune cell function, and even learning and memory [49, 50]. JAK2, a member of the Janus

Tasigna

Revoke the block Vesanoid PML– caused by RARα(alpha) PML–RARα (retinoic acid receptor fusion fusion on the differentiation of protein) immature promyelocytes into normal mature blood cells

All-transretinoic acid (ATRA), tretinoin

BCR–ABL1

Kinase inhibition

Kinase inhibition

Nilotinib

BCR–ABL1, Src family, c-KIT, PDGFR

Sprycel

Dasatinib

Kinase inhibition

Mechanism of action

Gleevec BCR–ABL1, c-KIT, PDGFR

Target

Imatinib

Generic name Trade of the drug name Adverse side effects

ALL, CML, Rash; hypereosinophilic weight gain; syndrome, edema; systemic pleural effusion; mastocytosis, cardiac toxicity; GISTa nausea and vomiting; arthralgias and myalgias; myelosuppression CML, ALL Rash; diarrhea; pleural effusion; fluid retention; mucositis; myelosuppression; QT interval prolongation CML Cytopenia, rash, headache, nausea, itching APL Hyperleukocytosis; weight gain; peripheral edema; dyspnea; fever

Hematologic malignancies

2006

CBC; ECG; liver Oral route chemistries; weight; signs and symptoms edema Cardiac Oral route irregularities CBC, liver Oral route function

1995

2007

2001

The FDA Administration approval

Oral route CBC; liver chemistries; weight; signs and symptoms of fluid retention

Monitoring

Table 9.2 Small drug molecules approved by the FDA for hematologic malignancies

304 B. Zehnbauer and M. Nasser

Folotyn

Pralatrexate

Hematologic malignancies

Clolar

Clofarabine

DNA synthesis Purine nucleoside inhibition and analogue induction of apoptosis

Velcade 26S proteasome Induction of apoptosis by proteasome inhibition

Bortezomib

Adverse side effects

Monitoring

Intravenous route

Intravenous route

Intravenous route Oral route

2004

2008

2009

2009

2006

2004

The FDA Administration approval

Intravenous Signs and Multiple myeloma, Peripheral neuropathy; route symptoms of mantle cell myelosuppression; rash; peripheral lymphoma constipation; diarrhea; neuropathy; edema; nausea and CBC vomiting Pediatric leukemia, Vomiting, nausea, CBC, ECG, Intravenous ALL, T-cell diarrhea; bone marrow hepatic and route lymphoma suppression; renal function hepatobiliary toxicity

The FDA-approved apoptosis-inducing agents in hematologic malignancies

Istodax

Romidepsin

Hypomethylating agent Kinase inhibition, anti-angiogenic

Mechanism of action

Myelodysplastic Nausea, vomiting, CBC, liver syndromes diarrhea, cytopenia function AML, renal cell Headache, fever, dry skin, CBC, thyroid carcinoma, GISTa nausea, vomiting, rash, function flu-like symptoms Histone complex Histone deacetylase Cutaneous T-cell Nausea, fatigue, bone CBC, ECG, on condensed (HDAC) lymphoma marrow suppression chromatin inhibition RFC-1 Folate pathway T-cell lymphoma Mucositis, CBC, mucositis, inhibition, DNA thrombocytopenia, renal function, synthesis nausea, fatigue liver function, inhibition pregnancy

Target

5-azacytidine, Vidaza, DNA methyldecitabine Dacogen transferases Sunitinib Sutent FLT3

Generic name Trade of the drug name

Table 9.2 (continued)

9 Targeted Therapy in Hematologic Malignancies 305

Target

Mechanism of action

Hematologic malignancies Adverse side effects

Monitoring

a FDA-approved non-hematologic indications ALL, Acute lymphocytic leukemia; CML, chronic myeloid leukemia; GIST, gastrointestinal stromal tumor; APL, acute promyelocytic leukemia; RAR, retinoic acid receptor; PML, promyelocytic leukemia; AML, acute myeloid leukemia; CBC, complete blood count; ECG, electrocardiogram. Data from [4, 6, 7, 9, 11, 12, 69]

2006

2006

The FDA Administration approval

Thalomid AntiInhibition of Multiple myeloma Sedation, neuropathy, Pregnancy, CBC, Oral angiogenesis endothelial cells constipation, deep (anti-angiogenic) venous thrombosis, myelosuppression, teratogenic Multiple myeloma, Hematologic toxicities, Pregnancy, CBC, Oral Lenalidomide Revlimid AntiInhibition of myelodysplastic deep venous clotting angiogenesis endothelial cells thrombosis, teratogenic function, liver (anti-angiogenic), syndrome function immunomodulatory

Thalidomide

The FDA-approved angiogenesis inhibitors in hematologic malignancies

Generic name Trade of the drug name

Table 9.2 (continued)

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family of kinases, was incidentally discovered in 1989 and considered “just another kinase” [51]. The name was later modified to Janus kinases (JAKs; JAK1, JAK2, JAK3, and tyrosine kinase 2). JAK gene mutations relevant to human cancers have been described for JAK1 [T-cell acute lymphocytic leukemia (T-ALL), acute myeloid leukemia (AML), breast cancer, lung cancer], JAK3 (AML cell lines and primary cells, breast cancer, gastric cancer) [52], and JAK2 [myeloproliferative neoplasms (MPN) and other myeloid malignancies such as trisomy 21-associated ALL]. Only the JAK2 mutations in MPN [53] and JAK1 mutations in T-ALL are observed with significant frequency [54]. Like JAK2, Abelson 1 (ABL1) is a cytoplasmic tyrosine kinase. Normally, the ABL1 protein plays a role in non-erythroid myelopoiesis [55], cytoskeletal rearrangement, and inhibition of cell migration. Its oncogenic counterpart the BCR–ABL1 fusion protein is a diagnostic feature in the pathogenesis of chronic myelogenous leukemia (CML) and an indicator of poor prognosis for some patients with ALL or AML [56]. Kinases may be classified into three categories according to their varying roles in the process of carcinogenesis [42]. The first category of kinases demonstrates transforming or oncogenic activity with constant activation of these kinases required for the development and proliferation of cancer cells. An example of this category is the V617F (Val617Phe)-activating mutation in the auto-inhibitory pseudokinase domain of JAK2 which is frequently observed in patients with polycythemia vera, essential thrombocythemia, and idiopathic myelofibrosis [53]. This finding plus the rapid proliferation of molecular diagnostic testing for these disorders have stimulated the rapid progression of several JAK2 inhibitors into phase I studies [57]. The second category of kinases is not associated with cell transformation but is essential for the proliferation or survival of cancer cells. They may also be components of the downstream signaling pathway of the first, transforming category of kinases [58]. An example of this functional category is MTOR, which is part of the PI3K–AKT signaling pathway [59]. MTOR inhibitors are being tested as therapies for renal cell carcinoma. The third category includes kinases which exhibit action during different stages of cancer establishment and preservation. For example, the vascular endothelial growth factor receptor (VEGFR) and the fibroblast growth factor receptor (FGFR) kinases are significant in developing and maintaining blood supply of solid tumors (neovascularization) but are rarely deregulated in hematologic neoplasms [60]. Small molecular weight drug molecules penetrate the plasma membrane of cells to target the intracellular, cytoplasmic domains of cell surface receptors or intracellular signaling molecules [11]. Most of the current kinase inhibitors are competitive binding molecules that target the ATP-binding sites of the kinase activation loop, constitutively locking that domain in either the active or the inactive conformation regardless of ligand binding [42]. All kinases have a conserved activation loop important to the regulation of kinase activity which can assume a large number of conformations. The conformation may be catalytically competent and normally phosphorylated, or an “inactive” conformer in which the activation loop normally serves to block a substrate-binding site; phosphorylation alters the loop three-dimensional structure and reveals the binding site [61, 62]. Therefore, small molecule drugs may act directly on the key signaling proteins, in contrast to many

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mABs, which indirectly exert their targeted action through the induction of immune responses [11]. Unlike monoclonal antibodies, small molecule inhibitors are administered orally, with the exception of bortezomib (an apoptosis-inducing drug), which is administered intravenously [9]. The half-life of the small molecule drugs is a few hours compared to days or weeks for mABs. This correlates with the daily dosing of small molecule inhibitors versus the weekly or monthly administration of mAB. The majority of small molecule inhibitors may interfere with metabolism by cytochrome P450 enzymes. Thus patients also taking multiple medications such as azole antifungals, anticonvulsants, dexamethasone, macrolide antibiotics, isoniazid, protease inhibitors, rifampin, St. John’s wort, warfarin, and verapamil may have drug side effects [9, 63]. Other small molecule inhibitors are directly metabolized by cytochrome P450 drug-metabolizing enzymes [63]. Therapeutic monoclonal antibodies are developed by genetic engineering, which is a more expensive and complex process in comparison to small molecule drugs which are chemically manufactured [64]. Small molecule inhibitors may be less specific than mABs due to their potential to target several signaling pathways without specificity to a single enzyme [65]. Though this multi-targeting approach may carry a risk for increased toxicity, it may also be regarded as a therapeutic advantage [66]. Multi-targeting could provide efficient elimination of the cancer cells since most cancers, especially solid tumors, are multi-factorial and result from multiple gene mutations [8, 67]. For example, imaR R or Gleevec ), one of the early and most predominantly tinib mesylate (Glivec used small drug inhibitors, has dramatically changed the treatment of CML [68] and is an example of multi-targeting. This agent targets the intracellular portions of at least three tyrosine kinases: BCR–ABL1, which is the product of the fusion gene formed by the t(9;22) (q34;q11) chromosomal translocation implicated in the pathogenesis of CML [68]; KIT, which is involved in metastatic gastrointestinal stromal tumors (GISTs), and PDGFRA, which is involved in neoplasms such as glioblastoma and chronic myeloproliferative syndromes characterized by eosinophilia [8, 11, 69]. The downstream signal transduction pathways that receive signals from these kinases include RAS/RAF/ mitogen-activated kinase (MAPK), SRC family kinases, JUN NH2 -terminal kinase/stressactivated protein kinase, phosphatidylinositol 3 kinase (PI3K), STAT5/Janus kinase, nuclear factor-κB, CRC oncogene-like protein/focal adhesion kinase, and MYC [70]. Imatinib mesylate [71, 72] and the second-generation tyrosine kinase inhibitors, dasatinib [73] and nilotinib [69], directly target the fusion protein BCR–ABL1 and are approved for the treatment of CML. Imatinib mesylate R R , or Glivec ) [69, 72], first desig(2-phenylaminopyrimidine; imatinib, Gleevec nated CGP57148B and later signal transduction inhibitor 571(STI571) [71], was developed as a result of a long process of random screening of different compounds that could target the ATP-binding site of the kinase [74, 75]. The tyrosine kinase activity is essential to the transforming function of BCR–ABL1. By competing with R renadenosine triphosphate (ATP) for binding to the tyrosine kinase, Gleevec ders the BCR–ABL1 fusion protein unable to activate downstream effector tyrosine

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kinase molecules that drive white blood cell proliferation [76, 77]. It does not affect the activity of the normal ABL1 tyrosine kinase in the same cells. Imatinib is both highly effective in treating CML and well tolerated by the patients [69, 78]. Seminal work by Druker [56] also demonstrated substantial therapeutic utility in the blast crisis phase of CML and in BCR–ABL1-positive ALL. Imatinib also inhibits the products of the KIT (CD117) and platelet-derived growth factor receptor (PDGFR) genes [79]. KIT is a receptor tyrosine kinase which is commonly mutated in gastrointestinal stromal tumors (GISTs), resulting in ligand-independent activity, autophosphorylation, stimulation of downstream signaling pathways, and uncontrolled cell proliferation [80]. Imatinib is effective at downregulation of these mutant products and is an effective treatment for patients with GIST. Similar activating mutations of KIT are observed in some patients with somatic mastocytosis and imatinib has also been an effective tyrosine kinase inhibitor in some of these cases [81]. The PDGFRA gene on chromosome 4q12 is frequently involved in an interstitial deletion producing a fusion gene with the FIP1L1 gene in chronic myeloproliferative syndromes characterized by eosinophilia. The fusion gene is a constitutively active tyrosine kinase that is also effectively inhibited by imatinib to control hematopoietic cell transformation [8, 79]. Different mechanisms have been suggested for developing resistance to kinase inhibitors. Point mutations that produce amino acid substitutions that alter the protein folding and interfere with drug binding; activation of alternative kinase pathways; amplification of target molecules [82]; and presence of quiescent, hematopoietic stem cells that are resistant to kinase inhibitors are some routes which contribute to resistance [83]. There are typically three stages in the clinical course of CML: chronic phase (CP), accelerated phase (AP), and blast crisis (BC) [84]. Imatinib is a highly effective therapy for early, chronic phase CML. However, the imatinib-based therapy has three main problems: the limited response of CML-blast crisis or Philadelphia chromosome-positive ALL patients to imatinib; the development of resistance in approximately 40% of patients with CML, that develops through the emergence of cell populations with mutations in the BCR– ABL1 kinase domain, which impair the binding of imatinib required for inhibition; and the relative insensitivity of CML stem cells to imatinib constituting a reservoir of malignant cells for leukemic relapse [82, 83, 85]. As the number of Philadelphia chromosomes increases with disease progression, the amount of BCR–ABL protein expressed in the cell increases and the efficacy of imatinib decreases [86]. Numerous second-generation ATP-competitive ABL tyrosine kinase inhibitors such as dasatinib, nilotinib, bosutinib, and INNO-406 have been developed to counter this resistance. These new agents provide some clinical success in targeting most of the ABL kinase point mutations responsible for imatinib resistance. However, a nucleotide change that creates an amino acid substitution of isoleucine for threonine at codon position 315 (Thr315Ile or T315I) is the most frequently observed mutation. It is located within the ATP-binding polypeptide loop and is not effectively targeted by any of these agents [69]. Nilotinib or AMNI07, an aminopyrimidine derivative of imatinib, is a small molecule drug rationally developed from the crystalline structure of the

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imatinib–ABL complex [70, 87]. The N-methylpiperazine ring of imatinib has been replaced by a trifluoromethylimidazole-substituted phenyl group, which allows for increased binding affinity to residues lining the binding site of the kinase. Like imatinib, nilotinib binds to and stabilizes BCR–ABL in the inactive state [88, 89]. Nilotinib has some increased potency (30-fold in vitro) and activity as a result of an improved topologic fit penetrating further into the central region of the kinase and blocking ATP binding [90]. Dasatinib (BMS-354825; Bristol-Myers Squibb) is structurally distinct from imatinib. Dasatinib is a dual SRC/ABL kinase inhibitor with less stringent conformational requirements allowing binding to both the active and the inactive conformations of the ABL kinase domain [73, 91]. Dasatinib does not interact with the same amino acid residues of the kinase P-loop region; thus it is still an effective inhibitor against many imatinib-resistant BCR–ABL1 mutations with the exception of T315I [73, 77]. The loss of the hydroxyl side chain and addition of a methyl group of the substituted isoleucine residue prevents binding of both dasatinib and nilotinib in the Thr315Ile variants. Dasatinib also inhibits SRC and Src-family kinases including FGR, FYN, HCK, LCK, LYN, and YES55 [92]. Src kinase inhibition might be advantageous in imatinib-resistant disease. Also, dasatinib has some inhibitory action against BCR– ABL1 in CD34+CD38− CML stem cells, at least more effectively than nilotinib or imatinib [91, 93]. Current investigations with dasatinib include potential antitumor effects in cell lines of head and neck squamous cell carcinoma, non-small cell lung cancer (NSCLC), prostate cancer, breast cancer, and multiple myeloma [94].

All-Trans-Retinoic Acid (ATRA) All-trans-retinoic acid (ATRA or tretinoin), a metabolic product of vitamin A (retinol), is one of the most important morphogens which induce the differentiation of immature blood cells to mature end-stage cells which then die [95]. In addition to being the first molecularly targeted cancer therapy [96], ATRA is also the first example of cancer differentiation induction therapy [97]. ATRA selectively targets the cancer cells of the majority of patients (>95%) with acute promyelocytic leukemia (APL) which harbor a t(15;17) (q22; q21) chromosomal translocation between the promyelocytic leukemia (PML) gene and the retinoic acid receptor alpha gene [RARα (alpha)]. This PML–RARα (alpha) configuration produces a retinoic acid receptor fusion protein which blocks cells at the immature promyelocytic stage of myeloid differentiation. This drug releases the maturation block caused by this oncoprotein allowing the cells to differentiate to normal, mature blood cells; decreasing the proliferation of promyelocytes; and producing cells which will undergo programmed cell death [96–98]. Less than 5% of patients with APL may have other variant rearrangements between RARα and translocation partner genes other than PML [96, 98]. These alternative fusions may involve the promyelocytic leukemia zinc finger (PLZF) or the nucleophosmin (NPM), nuclear mitotic apparatus (NUMA), and STAT5b partner genes. The nature of the fusion partner impacts the response of the cells to ATRA therapy [98, 99].

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RARα is a ligand-dependent transcription factor and a nuclear hormone receptor protein. In the presence of its ligand, retinoic acid, RARα regulates the expression of a large number of target genes, a subset of which is important for normal myeloid cell differentiation [96]. RARα normally dimerizes with a member of the retinoid-X receptor (RXR) family leading to the formation of a heterodimer with high DNAbinding affinity. In the absence of retinoic acid, these RARα/RXR heterodimers bind to specific retinoic acid response elements (RAREs) in the promoters of target genes and induce transcriptional repression. This repression is mediated by the RARα/RXR heterodimer interacting with transcriptional repressors including the nuclear receptor–corepressor (N-CoR)/silencing mediator of the retinoid and thyroid (SMRT) receptor, the transcriptional corepressors SIN3A or SIN3B, and histone deacetylases (HDACs) [96, 100]. ATRA binds with more affinity to the fusion oncoprotein PML–RARα than it does to these normal cellular targets [100]. This drug induces a conformational change in PML–RARα that dissociates the N-CoR and recruits transcriptional coactivators [96, 100]. Moreover, ATRA also induces cleavage of the PML–RARα oncoprotein through a proteasome-mediated pathway to reverse the fusion protein targeting of normal PML function. Together, these activities induce growth arrest and terminal differentiation of the malignant promyelocytes [96]. Leukemic cells with variant chromosomal translocations producing NPM–RARα and NPM–RARAα fusion genes are also sensitive to ATRA [100]. Although ATRA is highly effective at inducing the terminal differentiation of promyelocytes, it is not curative as a single agent. Resistance to ATRA can develop from the acquisition of mutations in the RARα ligand-binding domain of the fusion protein. ATRA is now used in combination with other chemotherapeutic agents, such as anthracyclines, with responses that are superior to treatment with either ATRA or chemotherapy alone [96, 101]. Arsenic trioxide (As2 O3 ) has also been used to treat patients with APL. This compound does not bind to RARα but instead binds to the PML portion of the chimeric product, inducing its degradation through a proteasome-dependent mechanism. Arsenic trioxide’s primary effect on promyelocytes is thought to be induction of apoptosis and is an option for patients who have relapsed APL following ATRA therapy [96].

Examples of Small Molecule Investigational Agents for Acute Myeloid Leukemia (AML) AML is characterized by many different molecular genetic abnormalities, both among different subtypes of AML and throughout the clinical progression of subtypes. Additional genetic changes may accrue to increase the genomic instability and dysregulation of cellular functions. Unlike CML, in which the principal oncogenic protein is BCR–ABL1, successful results with newly synthesized inhibitors would represent a compelling case for the power of targeted molecular therapy in AML, a genetically complex cancer [96].

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Anti-cancer agents being examined for possible treatment of acute leukemias (Table 9.3) include immunoconjugate drugs; inhibitors of the multidrug resistance P-glycoprotein, ABCB1; farnesyltransferase inhibitors; histone deacetylase and proteasome inhibitors; anti-angiogenic agents, anti-sense oligonucleotides to block BCL2 gene transcription; inhibitors of MTOR; alkylating agents; purine analogues; inhibitory anti-FLT3 antibodies; and finally, small molecule FLT3 tyrosine kinase inhibitors [102]. Table 9.3 Novel targeted agents under investigation for treatment of patients with acute myeloid leukemia (AML) Agents

Mechanism of action

Target

Zosuquidar Oblimersen (18-mer BCL2 anti-sense oligonucleotide)

Direct drug resistance modulation Drug resistance modulators

• PKC412 • CEP701 • MLN518

Tyrosine kinase inhibitors (TKI) of FLT3

Anti-GM-CSF receptor

Immunotherapy

Tipifarnib (Zarnestra)

Farnesyltransferase inhibitors

P-glycoprotein and other multidrug resistance proteins BCL2 gene expression; overexpression of BCL2 is common, poor prognostic indicator in AML [119] Clinical trials of TKIs of FLT3 ITD mutations in combination with chemotherapy; in both relapsed and newly diagnosed FLT3-mutant AML patients [103] Antibody conjugated to truncated diphtheria toxin targets GM-CSF receptor [119] Post-translational modification of RAS, lamin A, and HJJ-2 with a farnesyl lipid moiety is inhibited which restricts subsequent translocation to the cell membrane surface [119]

ITD, internal tandem duplication; GM-CSF, granulocyte macrophage colony-stimulating factor

The FMS-related tyrosine kinase (FLT3) gene encodes an RTK expressed on early hematopoietic progenitor cells that is activated upon binding with its ligand, FL, to generate a cascade of tyrosine phosphorylation of FLT3 and other downstream targets. Somatic mutations of FLT3 include internal tandem duplications (ITDs) detected in ∼30% of patients with AML. The ITDs activate the FLT3 kinase function in the absence of ligand and is associated with a more aggressive disease course and poor prognosis [103].

Examples of Investigational Agents for the Treatment of Myeloproliferative Neoplasms (MPN) The 2008 World Health Organization (WHO) classification system [104] now describes myeloproliferative neoplasms (MPN) as chronic myelogenous leukemia

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(CML), polycythemia vera (PV), essential thrombocythemia (ET) and primary myelofibrosis (PMF), systemic mastocytosis (SM), chronic neutrophilic (CNL) and eosinophilic (CEL) leukemias to replace the former “myeloproliferative disorders” terminology. Therapeutically validated oncoproteins for targeted treatment of MPN include BCR–ABL1 and rearranged PDGFR proteins. Just as these genotype– phenotype associations have been effectively exploited in the development of highly accurate diagnostic assays and molecular targeted therapy, similar approaches are being explored for other MPN with specific genetic alterations: polycythemia vera (JAK2 V617F and other JAK2 mutations), essential thrombocythemia (JAK2 V617F and MPL W515L mutations), primary myelofibrosis (JAK2 V617F and MPL W515L mutations), systemic mastocytosis (KIT D816V and other KIT mutations), and stem cell leukemia/lymphoma (ZNF198–FGFR1 and other FGFR1 fusion genes) [96]. Table 9.4 New agents under development for treatment of chronic myeloid leukemia (CML) [69, 70] Effectiveness against BCR–ABL1 T315I mutant

Agent

Primary target/inhibition

Bosutinib (SKI-606) INNO-406 (S-187, CNS-9)

Tyrosine kinases including c-Abl, v-Abl, No (second-generation BCR–ABL, Src family kinases Abl TKIs) Tyrosine kinases: c-Abl, v-Abl, BCR–ABL, No (second-generation and Lyn kinase Abl TKIs)

• MK-0457 (VX-680) • PHA-739358 • AT-9283

Yes Aurora kinases. These kinases play an important role in the regulation of mitotic process during cell division [70]

• ON-012380

Abl kinase (substrate competitive)

Yes

• Tipifarnib (R115777, Zarnestra) • Lonafarnib (SCH66336, Sarasar) • BMS-214662

Farnesyltransferase inhibitors block post-translational modification and constitutive activation of RAS in BCR–ABL1-positive cells

Yes

• Sorafenib (Nexavar)

Multiple tyrosine kinases are inhibited

Yes

• LAQ824 • LBH589 • Suberoylanilide hydroxamic acid

Histone deacetylase inhibitor down-decreases levels of mutant BCR–ABL1 with T3151; induces apoptosis

Yes

• Geldanamycin • IPI504 • PEG-ZnPP, SMA-Znpp • Homoharringtonine (HHT; cephalotaxine alkylating agent)

Binds heat-shock protein (HSP90); induces BCR–ABL1 protein degradation

Yes

Inhibits protein synthesis and induces apoptosis

Yes

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Novel Targeted Agents Under Investigation for the Treatment of CML Second-generation ABL1 TKIs, nilotinib and dasatinib, have been developed to override imatinib resistance. Third-generation INNO-46 and bosutinib are under development but the T315I missense mutation remains the biggest obstacle. Several promising inhibitors which may target the Aurora kinase, heat-shock proteins, and farnesyltransferase among others are in clinical trials as summarized in Table 9.4 [69].

Angiogenesis-Inhibiting Drugs Angiogenesis, the formation of new blood vessels from existing vasculature, is essential to maintain sufficient supply of nutrients and oxygen to the tissue necessary for growth of tumors and spread of tumor cells to other parts of the body (metastasis). Cancer cells contribute to this process by secreting growth factors, such as vascular endothelial growth factor (VEGF) and platelet-derived endothelial cell growth factor (PDECGF), which stimulate endothelial cell proliferation required for development of capillaries. Most research on tumor growth and angiogenesis factors has focused on solid tumors and the extent to which vascularization may predict the aggressive course of tumor growth. However, anti-angiogenesis drugs may also serve in the treatment of multiple myeloma, myelofibrosis, and myelodysplastic syndrome. Since the pharmacological effects of thalidomide extended beyond its neurosedative effects, it was subsequently investigated in a number of dermatologic, rheumatologic, and malignant diseases [105]. Thalidomide and its analogue lenalidomide (Table 9.2) have immuno-modulatory, anti-angiogenic, and anti-neoplastic properties. Lenalidomide was designed to enhance immunologic and anti-cancer properties while potentially decreasing the neurotoxic and teratogenic adverse effects of the parent compound, thalidomide [106]. Unexpectedly, thalidomide was found to have anti-myeloma activity when it was thought its anti-angiogenic activity could slow the disease by inhibiting the formation of new blood vessels in this highly vascularized cancer. However, the anti-cancer activity of thalidomide and its immunomodulators in multiple myeloma (MM) likely occurs through different mechanisms and sites in the bone [107]. At least four distinct, but potentially complementary, mechanisms have been proposed to account, at least in part, for the antitumor activity of thalidomide and its derivatives: (a) direct anti-proliferative/proapoptotic effects against multiple myeloma (MM) cells, including inhibition of the transcriptional activity of nuclear factor kappa B(NF-κB) and its anti-apoptotic target genes; (b) indirect targeting of MM cells by blocking interactions with bone marrow stromal cells; (c) immuno-modulatory inhibition of endothelial cell migration, adhesion and capillary-tube formation, and inhibition of key pro-angiogenic growth factors such as VEGF [105, 108]; and (d) immuno-modulatory enhancement of natural killer (NK) cell-mediated cytotoxicity against tumor cells.

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Apoptosis-Inducing Drugs Apoptosis or programmed cell death is an important mechanism for elimination of damaged, excess, or abnormal cells. Apoptosis is a common feature of aging cells but also occurs during embryonic development of select tissues and organs. In cancer cells, apoptosis is often inhibited and contributes to accumulation of an excess cell population which, in turn, may also be susceptible to accumulation of genetic mutations. Apoptosis-inducing drugs are molecules which inhibit proteasomes, the histone protein complexes that regulate gene expression [4]. Bortezomib (Velcade) is a modified boronic acid dipeptide with the molecular formula C19 H25 BN4 O4 . It is a selective and reversible proteasome inhibitor that induces apoptosis through inhibition of the chymotrypsin-like activity of the 20S proteasome, a subunit of the 26S proteasome [109, 110]. The inhibition of the proteasome system creates an imbalance of various regulatory proteins, triggering cell cycle arrest at the G1–S and G2–M phases of the cell cycle and activating apoptotic pathways within the cell [111], including the caspase-8-mediated extrinsic death-receptor pathway, the intrinsic mitochondrial apoptotic pathway, involving caspase-9 activation, and the endoplasmic reticulum stress response pathway, involving caspase-12. In addition, bortezomib also mediates downregulation of cytokine signaling, cell-adhesion molecules, and angiogenesis factors, via inhibition of the NF-κB signaling pathway [110]. Bortezomib was originally FDA approved in 2004 for the treatment of relapsed and refractory multiple myeloma [6] and is now FDA approved as a frontline treatment for myeloma patients [109] and for relapsed mantle cell lymphoma [112]. While multiple myeloma remains incurable, improving overall survival (OS) is the ultimate goal for new treatment options. Complete response (CR) has become a well-established surrogate for OS. For myeloma patients who may be candidates for hematopoietic stem cell transplant, frontline therapy must not adversely affect the ability to harvest sufficient stem cells, or their viability. Combinations of bortezomib plus established and novel agents, such as melphalan– prednisone, dexamethasone, doxorubicin, thalidomide–dexamethasone, and, most recently, lenalidomide–dexamethasone, may prove more promising than previous standards of care [109, 110].

Cancer Vaccines The goal of cancer vaccines is to increase the recognition of cancer cell components by the host immune system. Cancer vaccines are developed by obtaining cancer cells from the patient (autologous) or from an established line of cancer cells (allogeneic). These are genetically engineered in vitro or fused with mouse/human hybridoma cells to create a fusion that secretes the specific idiotype or cancer cell immunoglobulin protein of each patient. This purified fraction is linked to an immune stimulant and then administered to the patient to trigger a specific immune response by the autologous immune system to specifically target the patient’s cancer cell profile.

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These vaccines may be designed to either treat or prevent solid tumors. For examR has been approved for the prevention of infection from some ple, GARDASIL types of human papillomaviruses which are specifically associated with the majority of cases of cervical cancer plus some head and neck, vulvar, vaginal, penile, and R , a personalized therapeutic anal cancers as well as genital warts [4]. BiovaxID vaccine with the potential for treating follicular B cell non-Hodgkin’s lymphoma, R includes tumoris in FDA- and NIH-approved phase 3 clinical trials. BiovaxID specific immunoglobulin protein, idiotype (ID), that is expressed on the surface of cancerous B cells to initiate an immune response that targets these cells [113–116].

Gene Therapy Gene therapy is a general term applied to a therapy that implements genetic material to modify cells. Gene therapy is generally achieved using the process of oncolytic virotherapy or gene transfer with many of these technologies still under development [117]. Oncolytic virotherapy involves genetically engineering viruses to target and kill cancer cells, while sparing healthy tissue. Early trials identified unanticipated problems with the use of viral agents and incompletely understood requirements for patient safety. Also, most people have antibodies to the viruses commonly used as vectors to transfer the genes such as adenovirus or herpes simplex virus type 1 [4]. The virus constructs readily enter the cells but are neutralized by host antibodies that were developed due to prior viral infection. Gene transfer is the process of introducing a foreign gene into the genome of a cancer cell, or the tissue surrounding it, to replace an abnormal or disease-causing gene copy. Virus-derived vectors are required to deliver the gene into the cancer cells and maintain the gene copy until it is inserted into the host cell genome [4]. Regulatory gene sequences are commonly included to enhance the expression of the introduced therapeutic gene copy. Non-viral alternatives have also been investigated for introducing genes into cancer cells. These range from directly introducing therapeutic DNA into the cells (requires large quantities of DNA); encapsulating the DNA into a liposome which fuses with the cell membrane to pass the DNA into the cell; and chemically linking the DNA to molecules that will bind to a cancer cell surface receptor which will then invaginate into the cell membrane and transfer the DNA to the interior. Gene therapy introduces DNA coding for tumor suppressor genes, to restrict growth and proliferation, or suicide genes, which express enzymes that can convert an inactive prodrug into an active anti-neoplastic compound. Attempts have also been made to block or replace oncogenes in cancer cells [4]. Many challenges have been encountered, most commonly the lack of efficient and selective vectors to deliver the genes, failure to mobilize the genes to the nucleus for expression, and insufficient or poorly regulated promotion of the expression of gene functions [8].

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Challenges and Changes in Clinical Practice in the Era of Targeted Therapy Targeted therapies have expanded the concept of individually tailored cancer treatment because some of these agents may be effective only in patients with cancers that carry a specific molecular target but lack response in the absence of the target. This distinction may be influenced by patient ethnicity and sex, as well as by tumor histology [9]. In addition, targeted therapies require new approaches to determine optimal dosing, to assess patient adherence to therapy, and to evaluate treatment effectiveness. The intravenous administration of the traditional chemotherapy in an observed infusion area facilitated monitoring of compliance and management of toxicities. Most small molecule inhibitors are taken at home on a long-term daily basis. Thus, assessing patient adherence resembles the challenges encountered with therapies for chronic diseases such as diabetes and hypertension. Limited studies indicate that patient adherence to oral cancer treatment regimens can be highly variable and somewhat unpredictable [9]. The cost of these agents, which can exceed several thousand dollars per month, may become an important issue in health-care economics [9]. Substituting oral, small molecule inhibitors for traditional chemotherapy eliminates some treatment costs, including those associated with vascular access and intravenous infusions. However, targeted therapy is often used in addition to, rather than in place of, traditional chemotherapy. If targeted therapy includes monoclonal antibodies, costs can escalate exponentially [9]. Tumorigenesis can involve dozens of independent genetic mutations in multiple pathways; thus targeting even a few gene products may be overly simplistic and even ineffective. As many as 12 different pathways can be involved in a single cancer type because biological processes have alternate pathways, developed as a result of evolutionary pressures, giving rise to a redundancy, should one path become blocked or targeted, that is unlikely to be bypassed by a single, highly targeted agent or even by groups of targeted agents such as TKIs [118]. Selective inhibition of an enzyme target may produce unexpected consequences, such as when the protein or its subtypes being inhibited have multiple roles; it now seems that this is the case for many enzymes. The range of problems that can result from high selectivity includes the rapid development of resistance, which is more likely if a single molecular target is being inhibited with high selectivity [118]. Strategies for developing multiple inhibitors to simultaneously target different kinase sites and for discovering synergistic inhibitor combinations are urgently needed [42]. The development of these agents will require new skill sets and research technologies. First, the efficacy of targeted agents requires that the subset of tumors show dependency on the target for cancer cell growth or survival. Patient selection strategies will likely include molecular genetic diagnostic assays to confirm the presence of the specific target prior to treatment selection; drug and diagnostic test combinations will proceed together through the FDA-approved process. Second, it may be instructive to screen for the presence of the target in the tumors and to seek indications of target association with the study agent. Third, the therapy endpoints

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with these agents may require new definitions and assessments of outcome and survival. Some of these agents may not induce (detectable) tumor shrinkage, thus the measures of response to past chemotherapy may prove insensitive and insufficient in gauging anti-neoplastic effect(s). Fourth, some of these agents will have limited activity by themselves yet may have the capacity to markedly enhance the antitumor activity of conventional agents like chemotherapy or even other biological agents. This latter point is well exemplified by the anti-angiogenesis mAB bevacizumab, which has no activity as a single agent and yet is clinically active when combined with chemotherapy. Lastly, there is a risk that novel agents that are tested in a previously treated patient population may not be the ideal population to detect the antitumor activity of novel agents because their cancers may have resistance to any type of therapy [43].

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86. Gorre ME, Mohammed M, Ellwood K, et al. Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science. 2001;293: 876–880. 87. Jarkowski A, Sweeney RP. Nilotinib: a new tyrosine kinase inhibitor for the treatment of chronic myelogenous leukemia. Pharmacotherapy. 2008;28:1374–1382. 88. Kantarjian HM, Giles F, Gattermann N, et al. Nilotinib (formerly AMN107), a highly selective BCR-ABL tyrosine kinase inhibitor, is effective in patients with Philadelphia chromosome-positive chronic myelogenous leukemia in chronic phase following imatinib resistance and intolerance. Blood. 2007;110:3540–3546. 89. Weisberg E, Manley PW, Breitenstein W, et al. Characterization of AMN107, a selective inhibitor of native and mutant Bcr-Abl. Cancer Cell. 2005;7:129–141. (Erratum in Cancer Cell. 2005;7:399.) 90. Jorgensen HG, Allan EK, Jordanides NE, et al. Nilotinib exerts equipotent antiproliferative effects to imatinib and does not induce apoptosis in CD34+ CML cells. Blood. 2007;109:4016–4019. 91. Copland M, Hamilton A, Elrick LJ, et al. Dasatinib (BMS-354825) targets an earlier progenitor population than imatinib in primary CML but does not eliminate the quiescent fraction. Blood. 2006;107:4532–4539. 92. Das J, Chen P, Norris D, et al. 2-Aminothiazole as a novel kinase inhibitor template. Structure-activity relationship studies toward the discovery of N-(2-chloro-6-methylphenyl)2-[[6-[4-(2-hydroxyethyl)-1- piperazinyl)]-2-methyl-4-pyrimidinyl]amino)]-1,3-thiazole-5carboxamide (dasatinib, BMS-354825) as a potent pan-Src kinase inhibitor. J Med Chem. 2006;49:6819–6832. 93. Jorgensen HG, Holyoake TL. Characterization of cancer stem cells in chronic myeloid leukaemia. Biochem Soc Trans. 2007;35(Pt 5):1347–1351. 94. Steinberg M. Dasatinib: a tyrosine kinase inhibitor for the treatment of chronic myelogenous leukemia and Philadelphia chromosome-positive acute lymphoblastic leukemia. Clin Ther. 2007;29:2289–2308. 95. Lu J, Tan L, Li P, Gao H, Fang B, Ye S, et al. All-trans retinoic acid promotes neural lineage entry by pluripotent embryonic stem cells via multiple pathways. BMC Cell Biol. 2009;10:57. 96. Downing JR. Targeted therapy in leukemia. Mod Pathol. 2008;21(Suppl. 2):S2–S7. 97. Zhou GB, Zhang J, Wang ZY, Chen SJ, Chen Z. Treatment of acute promyelocytic leukaemia with all-trans retinoic acid and arsenic trioxide: a paradigm of synergistic molecular targeting therapy. Philos Trans R Soc Lond B Biol Sci. 2007;362:959–971. 98. Ohnishi K. PML-RARalpha inhibitors (ATRA, tamibarotene, arsenic trioxide) for acute promyelocytic leukemia. Int J Clin Oncol. 2007;12:313–317. 99. Redner RL. Variations on a theme: the alternate translocations in APL. Leukemia. 2002;16:1927–1932. 100. Fang J, Chen SJ, Tong JH, Wang ZG, Chen GQ, Chen Z. Treatment of acute promyelocytic leukemia with ATRA and As2O3: a model of molecular target-based cancer therapy. Cancer Biol Ther. 2002;1:614–620. 101. Sanz MA. Treatment of acute promyelocytic leukemia. Hematol Am Soc Hematol Educ Program. 2006:147–155. 102. Schenone S, Brullo C, Botta M. Small molecules ATP-competitive inhibitors of FLT3: a chemical overview. Curr Med Chem. 2008;15:3113–3132. 103. Small D. Targeting FLT3 for the treatment of leukemia. Semin Hematol. 2008;45 (3 Suppl. 2):S17–S21. 104. Swerdlow SH, Campo E, Harris NL, et al. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues; 2008. Lyon, France: IARC. 105. Melchert M, List A. The thalidomide saga. Int J Biochem Cell Biol. 2007;39:1489–1499. 106. Chanan-Khan AA, Cheson BD. Lenalidomide for the treatment of B-cell malignancies. J Clin Oncol. 2008;26:1544–1552.

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Chapter 10

Micro-RNAs in Hematologic Malignancies Muller Fabbri and George A. Calin

Keywords Micro-RNAs · Leukemias · Lymphomas · Noncoding RNAs · Polyadenylated precursor pri-miRNA · Precursor pre-miRNA · RISC complex · Cancer-associated genomic regions (CAGRs), Tumor suppressor genes · Fragile sites · Loss of heterozygosity (LOH) · Insulin-like growth factor receptor (IGFR) · Chemokine receptor 4 (CXCR4) · Promyelocytic leukemia zinc finger (PLZF) · Burkitt lymphoma

Introduction Micro-RNAs (miRNAs) are noncoding RNAs (ncRNAs) which regulate gene expression. MiRNAs are involved in a variety of biological processes, spanning from development, differentiation, apoptosis, and proliferation to senescence and metabolism [1–6]. MiRNA biogenesis is initiated by an RNA polymerase II, which initially transcribes the miRNA gene into a long, capped, and polyadenylated precursor, called pri-miRNA [7, 8]. By means of a double-stranded RNAspecific ribonuclease called Drosha, in conjunction with its binding partner DGCR8 (DiGeorge syndrome critical region gene 8, or Pasha), the pri-miRNA is processed into a hairpin RNA precursor (pre-miRNA), about 70–100 nucleotides (nt) long [9]. The following step is a translocation of pre-miRNA from the nucleus to the cytoplasm, by means of Exportin 5. Once in the cytoplasm, the precursor is cleaved into a 18–24 nt duplex by a ribonucleoprotein complex, composed of a ribonuclease III (Dicer), and TRBP (HIV-1 transactivating response RNA binding protein). Finally,

M. Fabbri (B) Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University Comprehensive Cancer Center, Columbus, OH 43210, USA e-mail: [email protected] G.A. Calin (B) Departments of Experimental Therapeutics and Cancer Genetics, University of Texas, M.D. Anderson Cancer Center, Houston, TX, USA e-mail: [email protected]

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9_10, 

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the duplex interacts with a large protein complex called RISC (RNA-induced silencing complex), which includes proteins of the Argonaute family (Ago1-4 in humans). One strand of the miRNA duplex remains stably associated with RISC and becomes the mature miRNA, which guides the RISC complex mainly (but not exclusively) to the 3’-UTR (3’-untranslated region) of the target mRNAs. According to the miRNA:mRNA degree of base-pair complementarity, the target mRNA can be cleaved (in case of perfect Watsonian match) or its translation into protein can be prevented (in case of imperfect Watsonian match). Figure 10.1 summarizes the events that occur during miRNA biogenesis. Overall, the effect of miRNAs is to silence the expression of the target mRNAs either by mRNA cleavage or by translational repression. However, researchers have discovered that miRNAs can actually also increase the expression of a target mRNA [10]. Each miRNA can target several different transcripts. For instance, it has been demonstrated that a cluster of two miRNAs (namely miR-15a and miR-16) can affect the expression of about 14% of the human genome in a leukemic cell line [11]. In addition, the same mRNA can be targeted by several miRNAs [12]. By using high-throughput profiling methods [13, 14], differences in the miRNome (defined as the full complement of miRNAs in a genome) have been detected in normal versus pathologic tissues or in the same tissues at different stages of differentiation. The first evidence of a relationship between miRNAs and human cancer is derived from the observation that miRNAs are more frequently located in cancer-associated genomic regions (CAGRs), which include fragile sites

miRNA gene

Cell Nucleus

Rna Pol II

Pri-miRNA DGCR8 + Drosha

Pre-miRNA

Dicer

Exportin 5

RISC Ago

Pre-miRNA Passenger Strand

RISC Ago

Target mRNA

Translational Repression mRNA cleavage Fig. 10.1 Biogenesis of miRNAs

TRBP + Dicer

miRNA duplex

Cell Cytoplasm

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(FRA) where tumor suppressor genes (TSGs) are located and regions of frequent loss of heterogeneity (LOH), deletion, amplification, and translocation. After having mapped 186 miRNAs and compared their locations to those of previously reported nonrandom genetic alterations, it was observed that 52.5% of miRNAs are in CAGRs [15]. Overall 19% of miRNAs are located inside or close to fragile sites (FRA), including FRA in which no known tumor suppressor genes map (e.g., FRA7H and miR-29a and miR-29b-1). About 43% of miRNAs are in LOH regions or in regions of amplification [15]. Since then, several groups have identified aberrancies of the miRNome in almost all human tumors [16–18], and specific signatures of de-regulated miRNAs have been associated with specific tumors, and sometimes harbor prognostic implications [19–24]. In hematology, miRNA expression differs during normal hematopoiesis, and miRNA expression aberrations can lead to pathologic phenotypes. This chapter will focus on the role of miRNAs in human hematological malignancies, after a brief description of the physiological changes of the miRNome during normal hematopoiesis.

Micro-RNAs in Normal Hematopoiesis Physiologic variations in miRNA expression levels occur during normal hematopoiesis and affect differentiation and commitment of the multipotent hematologic progenitor (MPP). The differentiation of MPP cell into either the common myeloid progenitor (CMP) or the common lymphoid progenitor (CLP) cell is controlled by miR-128a and miR-181a. On one side miR-146 blocks lymphoid differentiation, whereas miR-155, -24a, and -17 inhibit myeloid differentiation at an early stage [25]. The expression of miR-223 is low in CD34+ MPPs and CMPs, but increases steadily in the granulocyte compartment, while it is downregulated in the monocytes lineage [26]. Fazi et al. demonstrated that miR-223 targets NFI-A and C/EBPa, two transcription factors involved in human granulopoiesis, which, in turn, can silence or activate miR-223 expression, respectively [27]. Despite these findings, in miR-223 knockout mice models it has been described increased numbers of granulocyte progenitors in the bone marrow and higher levels of mature circulating neutrophils [28]. These effects are probably mediated by downregulation of either MEF2c, a transcription factor that promotes myeloid progenitor proliferation, or the insulin-like growth factor receptor (IGFR) [28] and establish a role for miR223 as a negative regulator of maturation but not differentiation of granulocytes. Overall, an important role for miR-223 in human granulopoiesis can be claimed, albeit further investigations are needed to clarify whether high or low expression of this miRNA is associated with myeloid differentiation. By targeting the transcription factor NFI-A, miR-424 induces monocytic/macrophage differentiation in acute myeloblastic leukemia (AML) cell lines and in CD34+ MPPs, therefore promoting myeloid hematopoiesis [29]. A systematic analysis of miRNA expression during erythroid commitment of erythrocyte precursors showed three different miRNA expression patterns: a first

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group of miRNAs whose expression progressively reduces during erythroid differentiation (including miR-150, -155, -221, -222), a group of miRNAs whose expression increases (namely miR-451, -16 at late stages), and a group of miRNAs with biphasic trend (miR-339, -378) [30]. Previously, another group showed that erythroid differentiation of MPPs is paralleled by a progressive downregulation of miR-221 and miR-222 and upregulation of their direct target: the Kit receptor [31]. Moreover, Georgantas et al. showed that miR-155 transduction in normal primary human CD34+ cells inhibits both myeloid and erythroid colony formation [25]. In addition, the C57BL6 mouse model transplanted with mice MPPs overexpressing miR-155 develops a myeloproliferative disorder associated with a decrease in the erythroid/megakaryocytic lineage in the bone marrow [32], supporting other studies indicating an miR-155 block of erythrocytic/megakaryocytic differentiation [25, 30, 33]. MiR-451 belongs to an miR-144/451 cluster, whose expression is under the control of the master erythrocyte transcription factor GATA-1 [34]. In a zebra fish embryo model, silencing of miR-451 with anti-miRNA molecules resulted in normal erythroid precursors with strong impairment of their development into mature circulating red cells. Conversely, no alterations were observed when miR-144 was silenced, revealing an miR-451-specific function in the late stages of erythropoiesis [34], and supporting that high levels of miR-451 are needed in order for a normal erythropoiesis to occur. Megakaryocyte differentiation occurs in parallel with the downregulation of a panel of 20 miRNAs, which includes miR-10a and miR-130a [33]. These two miRNAs target MAFB and HOXA-1, two genes overexpressed during megakaryopoiesis, indicating that miRNAs are responsible for the regulation of their expression level during megakaryocytic commitment [33]. Labbaye et al. have shown that in megakaryopoietic cultures of CD34+ progenitors, high levels of the promyelocytic leukemia zinc finger (PLZF) protein transactivate miR-146a, which in turn directly silences the chemokine receptor 4 (CXCR4) [35], a key factor for megakaryocytic proliferation, differentiation, and maturation [36]. MiRNAs are differentially expressed also during normal lymphoid differentiation. Ectopic expression of miR-181a in hematopoietic progenitor cells which were subsequently transplanted into lethally irradiated mice resulted in increased B cells and a paucity of T lymphocytes [37]. More recently, Neilson et al. have shown that high expression of miR-181 occurs also in the thymus and in the DP (doublepositive CD4+ /CD8+ ) stage of thymocyte development [38]. MiR-181a directly targets CD69. Since the CD69 signaling pathway affects the egress of lymphocytes from the thymus [39], it can be postulated that the ectopic expression of miR-181 passing the DP stage, as performed by Chen et al. might have resulted in low CD69expressing CD4 or CD8 lymphocytes [37]. As a result, those cells have a reduced ability to leave the thymus, leading to a general decrease in circulating T cells. In addition to CD69, miR-181a directly targets also BCL2 and TCR-α, whose levels of expression are known to increase in DP thymocytes following positive selection to the CD4 or CD8 stage [38]. Reduced levels of TCR-α shift the threshold for positive and negative selection, while the targeting of BCL2 upon positive selection would

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result in cell death. These two mechanisms contribute to the overall reduced levels of peripheral T cells upon forced expression of miR-181. An miRNA regulating the transition from pro-B to pre-B-cell stage is miR-150 [40]. Selectively expressed in mature, resting B and T cells, but not in their progenitors [41], miR-150 significantly reduces the number of mature B cells in spleen, lymph nodes, and peripheral blood, when ectopically expressed in murine hematopoietic stem and progenitor cells [40]. These effects are dependent on miR-150 direct target c-MYB, a transcription factor which directs multiple steps of lymphocyte development [42]. By silencing c-MYB, miR-150 induces apoptosis of pro-B cells [42]. Deletion of Dicer at an early B-cell stage blocks almost completely the pro-B to pre-B-cell transition, which coincides with a significant upregulation of the pro-apoptotic protein Bim [43]. At least in part responsible for this effect is the miR-17-92 cluster, since a targeted deletion of the cluster leads to increased levels of the pro-apoptotic protein Bim in mice, and inhibits B-cell development at the pro-B to pre-B transition [44]. Overall, miRNAs are involved in normal hematopoiesis and act as “fine tuners” of their target expression levels, therefore orchestrating commitment and differentiation of the pluripotent hematopoietic progenitors. These physiological mechanisms are aberrant in cancer and contribute to the pathogenesis of hematological malignancies.

Micro-RNAs in Lymphomas MiRNAs are involved in human lymphomagenesis (Table 10.1). Tam et al. initially observed that the final part of the B-cell integration cluster (BIC) noncoding RNA (ncRNA), where miR-155 is located [45], accelerates MYC-mediated lymphomagenesis in a chicken model [46]. Subsequently, high levels of BIC/miR-155 were described in pediatric Burkitt lymphoma (BL) [47], but not in the adult primary cases [48], probably indicating a specific age-dependent role of this miRNA-based on the age of onset of BL. In the B-cell-specific miR-155 transgenic (TG) mouse model an acute lymphoblastic leukemia/high-grade lymphoma at approximately 9 months of age was described [49]. These malignancies are preceded by a polyclonal pre-B-cell proliferation, have variable clinical presentation, are transplantable, and develop oligo/monoclonal expansion [49]. Recently, it was shown that in these TG mice the B-cell precursors with the highest miR-155 expression were at the origin of the leukemias [50]. Moreover, by directly targeting the Src homology 2 domain-containing inositol-5-phosphatase (SHIP) and the CCAAT enhancer-binding protein beta (C/EBPbeta), two key regulators of the interleukin-6 signaling pathway, miR-155 triggers a chain of events that promotes the accumulation of large pre-B cells and acute lymphoblastic leukemia/high-grade lymphoma [50]. Two different groups have studied miR-155 knockout (KO) mice models and have demonstrated that lack of this miRNA switches cytokine production toward TH 2 differentiation [51], and also compromises the ability of dendritic cells (DC) to activate T cells, because of a defective antigen presentation or abnormal co-stimulatory functions [52].

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M. Fabbri and G.A. Calin Table 10.1 Most frequently de-regulated miRNAs in human leukemias and lymphomas

miRNA

Chromosomal location

Deregulation

Diseases

Targets

miR-155

21q21.3

Up

SHIP, C/EBP-β

miR-17-92 cluster

13q31.3

Up

miR-106a-363 cluster miR-106b-25 cluster miR-143/145 cluster miR-9

Xq26.2

Up

7q22.1

Up

BL, DLBCL, HL, CLL, AML (FLT-IDT+) B-cell lymphomas, CML, ALL B-cell lymphomas, T-cell leukemias B-cell lymphomas

5q33.1

Down

1q22 (miR-9-1) 5q14.3 (miR-9-2) 15q26.1 (miR-9-3) 9q22.32 (let-7a-1) 11q24.1 (let-7a-2) 11q13.31 (let-7a-3) 3p21.2 (miR-135a-1) 13q23.1 (miR-135a-2) 13q14.2

Up

B-cell lymphomas/leukemias HL PRDM1/BLIMP-1

Up

HL

PRDM1/BLIMP-1

Down

HL

JAK2

Down

Indolent CLL

BCL2, MCL1

7q32.3 (miR-29b-1) 1q32.2 (miR-29b-2) 1q32.1 (miR-181b-1) 9q33.3 (miR-181b-2) 14q32.33 17q21.32 3p22.3 8p23.1 (miR-124a-1) 8q12.3 (miR-124a-2) 20q13.33 (miR-124a-3) 9q21.11

Down

Aggressive CLL, AML

Down

Aggressive CLL, aggressive AML

TCL1, DNMT3A, DNMT3B, SP1, MCL1, CXXC6, CDK6 TCL1, TLR, and IL-6 pathways

Down Down Up Down

CML CML ALL ALL

ABL1 USF2 Unknown CDK6

Down

AML

HOXA10

let-7a

miR-135a

miR-15a/16-1 cluster miR-29b

miR-181b

miR-203 miR-10a miR-128b miR-124a

miR-204

PTEN, BIM, E2F1 BIM, TGF-β signaling BIM, TGF-β signaling ERK5

BL, Burkitt lymphoma; DLBCL, diffuse large B-cell lymphoma; HL, Hodgkin lymphoma; CLL, chronic lymphocytic leukemia; AML, acute myeloid leukemia; CML, chronic myeloid leukemia; ALL, acute lymphoblastic leukemia. For the targets legend, see main text.

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High levels of miR-155 have been described also in diffuse large B-cell lymphoma (DLBCL), the most frequent lymphoma in adults worldwide [53, 54]. By comparing miR-155 levels in the activated B-cell phenotype of DLBCL (ABCDLBCL), versus the germinal center B-cell-like phenotype (GCB-DLBCL), miR155 was significantly higher in the ABC phenotype [45, 53]. Since ABC-DLBCL and GCB-DLBCL have 5-year survival rates of 30 and 59%, respectively [55], miR-155 expression in DLBCL has a prognostic value. A correlation between miR155 and NF-kB expression was found in DLBCL cell lines and patients [56]. In addition to miR-155, high levels of miR-21 and miR-221 are also associated with ABC-DLBCL and severe prognosis [51]. Roehle et al. identified miRNA-specific signatures for DLBCLs and follicular lymphomas (FLs) [54], and showed that four miRNAs (namely miR-330, -17-5p, -106a, and -210) can accurately differentiate DLBCL, FL, and reactive lymph nodes with an overall accuracy of 98% [54]. Noteworthly, miR-17-5p and miR-106a belong to two paralogous clusters located on chromosome 13 and X, respectively, with a well-established oncogenic role in several human malignancies, both solid and hematologic [57]. The miR-17-92 cluster is located at 13q31-32, a region frequently amplified in malignant B-cell lymphomas [58], and is overexpressed in over 60% of B-cell lymphoma patients [59]. Overexpression of the cluster in murine pluripotent cells from MYC transgenic mice accelerates lymphomagenesis [59]. The oncogenic potential of this miRNA cluster is supported also by B-cell miR-17-92 cluster TG mice models, in which a higher than expected rate of lymphoproliferative disorders and autoimmunity and premature death did occur [60]. The molecular bases of the observed phenotype reside, at least in part, in the direct targeting of the TSG PTEN, and the pro-apoptotic Bim protein, which controls B-lymphocyte apoptosis [60]. Members of the miR-17-92 cluster have homologues in two other clusters: on chromosome 7 (the miR-106b-25 cluster) and on chromosome X (the miR-106a-363 cluster). The OG c-MYC transactivates both clusters on chromosomes 7 and 13 [61] in addition to E2F1, a transcription factor which promotes cell cycle progression [62]. In turn, E2F1 regulates the host genes for the miR-106b-25 and for the miR-17-92 clusters. The miR-106a-363 polycistron is also overexpressed in 46% of acute and chronic human T-cell leukemias [63], claiming a role in leukemogenesis. Interestingly, two of the three clusters (namely miR-106b-25 and miR-17-92) interfere with the transforming growth factor beta (TGF-β) signaling [64], a pathway which is inhibited in several tumors [65]. Moreover, Ventura et al. have shown that the miR-17-92 and miR-106b-25 double-knockout mouse model has a more severe phenotype than the miR-17-92 single-knockout mouse model [44], suggesting that both clusters control apoptosis. Also miR-143 and miR-145 are frequently downregulated in B-cell lymphomas and leukemias [66]. In non-Hodgkin lymphoma cell lines, restoration of these two miRNAs induced a dose-dependent growth inhibitory effect which was associated with downregulation of Erk5 [66], a recently characterized MAPK, most similar to the well-studied ERK1/2 subfamily [67]. MiRNA expression in Hodgkin lymphoma (HL) has been object of some studies. Navarro et al. identified a distinctive signature of 25 miRNAs discriminating HL

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from reactive lymph nodes and 36 miRNAs differentially expressed in the nodular sclerosis and mixed cellularity subtypes [68]. Three miRNAs (namely miR-96, -128a, and -128b) were selectively downregulated in EBV+ HL [68]. Since only one of the miRNAs differentially expressed in EBV+ cases was also included in the 25-miRNA signature distinguishing HL from reactive lymph nodes, it seems safe to conclude that EBV is not a primary transforming event in HL. Among the upregulated miRNAs in HL there are miR-9 [68, 69] and let-7a [69], which directly target PRDM1/blimp-1 [69], a master regulator in terminal B-cell differentiation [70]. A more recent study has compared miRNA profiles of microdissected Reed– Sternberg cells and Hodgkin cell lines versus CD77+ B cells [71]. In this study a profile of 12 over and 3 underexpressed miRNAs was identified [71], showing only a partial overlap with Navarro’s profile. This discrepancy might be due to the different procedure used to collect the HL cells. MiRNAs have also prognostic implications in HL. Low expression of miR-135a has been associated to higher relapse risk and shorter disease-free survival for HL patients [72]. The TSG nature of miR-135a is determined by its direct targeting of JAK2, an activator of the antiapoptotic gene Bcl-XL [72]. Also in HL higher expression of miR-155 has been reported [69, 71, 73], although the function of this upregulation in Hodgkin Reed–Sternberg cells is still poorly understood.

Micro-RNAs in Leukemias MiRNAs are also involved in leukemogenesis (Table 10.1). Chronic lymphocytic leukemia (CLL) is the most common leukemia among adults in the Western world and is characterized by slow accumulation in blood, bone marrow, and lymphatic tissue of small, non-proliferating, mature B lymphocytes, which display typical surface markers such as CD19 and CD20 in addition to CD5 [74]. The majority of CLLs are characterized by hemizygous and/or homozygous deletion of the genomic region 13q14.3 [75], where a cluster of miRNAs (namely the miR-15a/16-1 cluster) is located [76]. It has been demonstrated that both miR15a and miR-16-1 are deleted or downregulated in approximately 68% of CLL cases [76], suggesting a role as TSG for this miRNA cluster. Indeed, miR-15a and miR-16 directly target the antiapoptotic BCL2 [77], a protein which is overexpressed in the majority of CLL malignant B cells [78], and it is believed to mediate the anti-tumoral effect of these miRNAs. Restoration of miR15a/16-1 expression in the leukemic MEG-01 cell line (which recapitulates the genetic abnormalities of CLL with 13q deletion) leads to apoptosis and inhibition of tumor growth in xenograft mice models, further corroborating a role for miR15a/16-1 as TSGs [77, 79]. Interestingly, the pattern of these miRNA cluster-controlled genes includes both oncogenes (OGs) and TSGs, suggesting that miRNAs cannot be simply described as OGs or TSGs, but dual in nature [80], probably depending on the specific microenvironment in which they act, which differs among cell types and species. MiRNAs also harbor prognostic implications in CLL, since a specific miRNA signature can

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distinguish between the indolent form of CLL (characterized by low levels of ZAP70- and IgVH-mutated status), and the aggressive form [81]. Finally, miRNAs are involved also in familial CLLs, since a germ-line mutation in pre-miR-16 sequence, which causes low levels of micro-RNA expression both in vitro and in vivo was associated with deletion of the normal allele in leukemic cells of two CLL patients, one of which with a family history of CLL and breast cancer [81]. Intriguingly, in the New Zealand Black mouse strain model characterized by spontaneously occurring late-onset CLL [82], Raveche et al. described a point mutation adjacent to the miR-16-1 locus, which is responsible for lower expression of this miRNA in this CLL-prone mouse model [83], further suggesting that reduced levels of miR-15a/16-1 contribute to CLL genesis. High expression of TCL1 (T-cell leukemia/lymphoma 1A) is associated with aggressive CLL. Pekarsky et al. have shown that miR-29b and miR-181b directly target TCL1, therefore impacting on the protein kinase AKT (v-akt murine thymoma viral oncogene homolog 1) pathways which affect cell survival, proliferation, and death [84]. Another study, conducted in 110 patients, showed a correlation between low levels of miR-29c and poor prognosis CLL [85]. Interestingly, the authors found the first evidence of a specific threshold of expression for miR-29c and miR-223, able to predict treatment-free survival (TFS) and overall survival (OS) [85]. Finally, high levels of miR-155 have been described also in CLL versus normal CD19+ B cells [86]. In chronic myeloid leukemia (CML), the miR-17-92 cluster seems to have a central role. Indeed, the cluster is transactivated both by c-MYC and by BCR– ABL1, the fusion protein which results from the reciprocal translocation t(9;22), hallmark of the disease (Philadelphia chromosome) [87]. The BCR–ABL1–MYC complex can transactivate miR-17-92 only in early chronic phase, but not in blast crisis CML CD34+ cells [87], suggesting a role for miR-17-92 cluster in the early phases of CML pathogenesis. MiR-203 directly targets ABL1, and high expression of this miRNA inhibits cancer cell proliferation in an ABL1-dependent manner [88]. In turn, both genetic and epigenetic mechanisms coordinately inactivate this miRNA, and a high rate of miR-203 promoter hypermethylation has been described in Ph+ tumors, including B-cell ALLs, primary CMLs, and cultured CML cell lines, whereas no methylation was observed in other hematologic tumors that do not carry ABL1 alterations [88]. Overall, miR-203 and miR-17-92 cluster expression seems to be intertwined and acts as key player in CML pathogenesis. Finally, a role for miR-10a also emerged in CML. In a group of 85 newly diagnosed CML patients, miR-10a was found downregulated in 71% of cases, and an inverse correlation with the expression of the oncogenic upstream stimulatory factor 2 (USF2) was described [89]. Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Zanette et al. compared miRNA expression profile in seven ALL patients versus normal CD19+ B cells from six healthy individuals and described the miR-17-92 cluster as upregulated in ALL samples [90]. Recently, a role for miR-17-92 cluster has been described also in the less common T-cell subtype of ALL [91]. In another study, Mi et al. have identified a specific miRNA signature able to discriminate ALL

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from AML (acute myeloid leukemia) with high accuracy. In particular four miRNAs (namely miR-128a and -128b upregulated in ALL versus AML and let-7b and miR223 downregulated in ALL versus AML) can differentially diagnose between the acute leukemias with an accuracy rate of 98% [92]. Moreover, miR-128b was also upregulated in ALL versus normal CD19+ cells, suggesting a high specificity for ALL [92]. The leukemogenic mechanism of miR-128b is still poorly understood. Epigenetic factors affect the expression of miRNAs in ALL and harbor prognostic implications. In a recent report conducted on 353 ALL samples, Roman-Gomez et al. observed that 65% of patients had at least one miRNA methylated, and this methylation status was associated with reduced disease-free and overall survival [93]. In particular miR-124a is frequently downregulated because of its promoter hypermethylated status, and this contributes to the development of the malignant phenotype, since this miRNA directly targets cyclin-dependent kinase 6 (CDK6), an oncogene that promotes cell proliferation by inducing phosphorylation of Rb [94]. Also histone modifications regulate miRNA expression profile in ALL. In this leukemia miR-22 expression can indeed be restored by treatment with trichostatin A, a well-known histone deacetylase inhibitor [95]. In childhood pre-B ALL patients high levels of miR-222, -339, and -142-3p, paralleled by low expression of miR-451 and miR-373∗ , were also described [96]. In acute myeloid leukemia (AML), high levels of miR-191 and miR-199a seem to have prognostic implications, since they correlate with reduced overall and disease-free survival [97]. Specific miRNA signatures are also associated with balanced 11q23 translocations, isolated trisomy 8, and FLT3-ITD (fms-like tyrosine kinase 3 internal tandem duplications) mutations [97]. Also in AML with normal karyotype (which represents about 30–40% of all AMLs), mutations of NPM1 (nucleophosmin-1) and FLT3-ITD occur [98], and a specific set of miRNAs are able to differentiate these mutation statuses in normal karyotype AMLs [99]. In particular, high levels of miR-10a, -10b, several let-7, and miR-29 family members, as well as downregulation of miR-204, characterize NPM1-mutated versus NPM1unmutated cases [99]. Given that miR-204 directly targets HOXA10, the high levels of HOX proteins observed in NPM1-mutated AMLs might derive, at least in part, from low expression of HOX-regulating miRNAs [99]. Despite an overexpression of miR-155 is associated with FLT3-ITD+ status, there is evidence that this upregulation is actually independent from FLT3 signaling [99]. Therefore, a combined therapy with anti-miR-155 molecules and FLT3-ITD pathway inhibitors might represent a rationale approach for this subset of AML patients. In AML with normal cytogenetics but high-risk molecular features (such as FLT3-ITD+, or unmutated NPM1, or both) low expression of miR-181 family contributes to an aggressive AML phenotype through mechanisms associated with the activation of pathways controlled by toll-like receptors and interleukin-1b [100]. The t(8;21) translocation, which is the most common chromosomal aberrancy in AML, generates the AML1/ETO fusion oncoprotein. This fusion product causes epigenetic silencing of miR-223, by recruiting chromatin remodeling enzymes at an AML1-binding site on the pre-miR-223 gene [27]. By silencing miR-223 expression, the oncoprotein inhibits the differentiation of myeloid precursors, therefore actively contributing

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to the pathogenesis of this myeloproliferative disorder. More recently, it has been demonstrated that miR-29b is a key player in the epigenetics and AML. Both in cell lines and in primary samples, miR-29b directly regulates the two “de novo” DNA methyltransferases (DNMT3A and DNMT3B) [101], as previously observed also in lung cancer [102], and indirectly modulates the levels of the “maintenance” DNMT (DNMT1), by directly targeting DNMT1 activator Sp1 [101]. These effects lead to the re-expression of epigenetically silenced TSGs, such as ESR1 (estrogen receptor alpha) and p15(INK4b) [101]. Moreover, restoration of miR-29b in AML cell lines and primary samples suppresses the expression of OGs such as MCL1, CXXC6, and CDK6, which are direct targets of miR-29b [103]. Overall, miRNAs play an important role in all kinds of human leukemias, by affecting the expression levels of important genes which control hematopoiesis.

Concluding Remarks From the first evidence that aberrancies of the miRNome occur in hematological malignancies to the progressive understanding of the molecular meaning of these aberrations, scientists are progressively reaching the threshold of introducing miRNA-based therapies into the common clinical management of these malignancies. A better understanding of the many targets of the most frequently and widely de-regulated miRNAs has been replaced by a more pathway-based kind of inquiry, aimed at defining which molecular pathways are mainly affected by the miRNome abnormality. This approach has proven to be very successful, providing pathogenetic and prognostic information of the utmost importance. Finally, the encouraging (and in some cases even astonishing) results obtained by miRNA-based treatments in xenograft mouse models and in transgenic and knockout mice models have provided the final proof not only that miRNAs can be used to treat cancer but also in some cases that they should be used as therapeutics. The next challenge will be to determine how to effectively combine miRNAs and more traditional anticancer drugs, in order to achieve better efficacy and/or lower incidence of side effects. A not so far future will answer these questions.

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Index

Note: The letters ‘f’ and ‘t’ following locators refer to figures and tables respectively.

A Abelson 1 (ABL1), 20, 50, 55–57, 57f, 65–66, 82–86, 83t, 88–90, 88t, 104t, 105–110, 106t, 115, 136, 146, 216–218, 220–233, 235, 241, 293, 295, 303, 304t, 307–313, 333 Absorbance, 9 ACD, see Acid–citrate–dextrose (ACD) Acid–citrate–dextrose (ACD), 4 Acute leukemia, 43, 58–59, 61, 86–90, 99, 106, 110–111, 116f, 128, 133–134, 138, 146, 217, 219, 243, 312, 334 cytogenetic findings, 88t with no specific cytogenetic findings, 89–90 subcategories, 89 Acute lymphoblastic leukemia (ALL), 20, 30, 44, 51, 66, 86, 221, 329, 333 Acute megakaryoblastic leukemia (AMKL), 63, 89, 110–112, 116f Acute myeloid leukemia (AML), 13, 59–63, 127–147 AML with myelodysplasia-related changes, 62 cytogenetic abnormality in, WHO classification scheme AML (megakaryoblastic) with t(1;22)(p13;q13) – RBM15MKL1, 62 AML (promyelocytic) with t(15;17)(q22;q12) – PML/RARα, 60–61, 61f AML with inv(16)(p13q22) or t(16;16)(p13;q22) – CBFβ/MYH11, 61f, 62 AML with inv(3)(q21q26.2) or t(3;3)(q21;q26.2) – RPN1/EVI1, 62 AML with t(6;9)(p23;q34) – DEK/NUP214, 62

AML with t(9;11)(p22;q23) – MLLT3/MLL, 61, 61f AML with t(8;21)(q22;q22) – RUNX1/RUNX1T1, 60 “myeloid cytogenetic markers,” 63 rearrangements wrt chemotherapy, 62 therapy-related AML (t-AML), 62 See also AML, molecular pathology of ADCC, see Antibody-dependent cellular cytotoxicity (ADCC) Agarose gels, 11–12 AITL, see Angioimmunoblastic T-cell lymphoma (AITL) ALCL, see Anaplastic large-cell lymphoma (ALCL) ALL, see Acute lymphoblastic leukemia (ALL) Allele-specific PCR, 20–21, 129, 134, 145, 246 All-trans-retinoic acid (ATRA or tretinoin), 61–62, 310–311 AMKL, see Acute megakaryoblastic leukemia (AMKL) AML, see Acute myeloid leukemia (AML) AML, molecular pathology of AML-associated mutations, 129t AML with recurrent genetic abnormalities AML with balanced translocations/ inversions, 130–133 AML with gene mutations, 139–142 core binding factor AML, 133–137 gene expression and prognosis in NK-AML, 145–146 gene mutations with prognostic significance, 143–145 other recurrent translocations, 137–139 rare subtypes of AML, 139 mutations and translocations associated with other myeloid neoplasms, 146

D. Crisan (ed.), Hematopathology, Molecular and Translational Medicine, C Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-262-9, 

341

342 AML with mutated CCAAT/enhancer-binding protein alpha (CEBPA), 141 AML with mutated nucleophosmin 1 (NPM1), 139–141 AML with myelodysplasia-related changes, 142, 142t, 143f AML with recurrent genetic abnormalities AML with balanced translocations/ inversions PML–RARA translocation, detection of, 130–133 AML with gene mutations, 139–142 AML with mutated CCAAT/enhancerbinding protein alpha (CEBPA), 141 AML with mutated nucleophosmin 1 (NPM1), 139–141 AML with myelodysplasia-related changes, 142, 142t CBF AML AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFBMYH11, 135 AML with t(8;21)(q22;q22) RUNX1-RUNX1T1, 133–134, 134f good prognosis AML, 133 MRD by RQ-PCR in CBF-AML, 136–137 gene expression and prognosis in NK-AML, 145–146 gene mutations with prognostic significance, 143–145 FLT3-LM and FLT3-TKD, 143–145 WT1, 145 other recurrent translocations, 137–139 MLLT3-MLL and other MLL abnormalities, 137–138, 138f MRD in AML with MLL abnormalities, 138–139 rare subtypes of AML, 139 AMNI07, see Nilotinib Anaplastic large-cell lymphoma (ALCL), 73, 95–96, 186–189 ALK translocations in, 187t detection of ALK dysregulation, 189–190 genetic abnormalities in, 190–191 Aneuploid cell, 48 Angiogenesis-inhibiting drugs, 314 Angioimmunoblastic T-cell lymphoma (AITL), 96, 191, 196–197, 199 genetic abnormalities in, 191–192 An International System of Human Cytogenetic Nomenclature (2009), 48

Index Antibody-dependent cellular cytotoxicity (ADCC), 296–297 Anti-cancer action of mABs, approaches, 296–297 delivery of cytotoxic materials to tumor cells, 297 direct inhibitory effect on the tumor antigen–antibody binding mechanism, 296 EGFR as target, effective signal transduction inhibitors, 297 induction of immune-mediated mechanisms, 297 Anti-cancer therapies, 294, 296 Antigen receptor, 26–31, 27t, 81, 87, 91, 95, 103, 171, 178, 272 Apolizumab, 301t, 302–303 Apoptosis, 278–279 Apoptosis-inducing drugs, 295, 315 A Proposed Standard System of Nomenclature of Human Mitotic Chromosomes, 48 Arcturus/MDS Analytical Technologies, 3–4 ARID5B gene, 113 Array comparative genomic hybridization (array-CGH), 41, 47, 158, 267–268 Asymmetric PCR, 25 Ataxia telangiectasia, 113, 259 Automation, 12, 15, 17 B B-ALL, see B-lymphoblastic leukemia (B-ALL) “Banding era,” 42 Banding patterns of “banding era” C banding, 42 Giemsa banding, 42 quinacrine banding, 42 B-cell biology and maturation, 158–163 class switch of IGH, 162–163, 163f FRs/CDRs in IGH gene, 161 IGH rearrangement, 160f immunoglobulin gene rearrangement/ SHM, 158–163, 159t Kappa and lambda light-chain gene rearrangement, 161, 161f lymphomagenic or leukemogenic genetic alterations, 163 pro-B cells turning pre-B cells, 160 somatic hypermutation, role in antigen selection, 165 TdT expression in pro-B cells, 160

Index clonality testing, 163–165 indications, 163 PCR over Southern blot, advantages, 164 PCR testing, false positives/negatives, 164–165 PCR with CE gene scanning using primers to FR3, 164–165, 164f somatic hypermutation testing, 166 VH mutational status determination for CLL/SLL/MZL, 166 B-cell integration cluster (BIC), 329 B-cell non-Hodgkin lymphoma (B-NHL), 158–182 B-cell receptor pharmacological inhibition of BCR signaling, 277 somatic mutations of Ig variable region genes, 271–274 stereotypy, 274–277 BCL6 gene, 71–72, 74, 172, 261 BCR–ABL1-negative “classic” myeloproliferative neoplasms effect of JAK2 allelic burden, 235–236 epidemiology, clinical, and laboratory features, 232–233 JAK2 mutation detection methods, 236–237 JAK2 mutations in PV, 234–235 JAK2 – unresolved issues, 237–238 JAK2 V617F’s contribution to diagnosis of MPNs, 233–234 MPL, 238 BCR–ABL1-negative disorders, 84–85 BCR–ABL1-negative myeloproliferative neoplasms chronic neutrophilic leukemia, 84 essential thrombocythemia, 84 polycythemia vera, 84 primary myelofibrosis, 84 Bevacizumab, 295, 302, 318 BIC, see B-cell integration cluster (BIC) R BigDye , 15 BIOMED-2 primers, 165, 185, 192 R BiovaxID , 316 B-LBL, see Precursor B-lymphoblastic lymphoma (B-LBL) Bloom syndrome, 113 B-lymphoblastic leukemia (B-ALL), 63–66, 88t, 103, 107 high hyperdiploidy ALL, 64 hypodiploid ALL, 64

343 pediatric B-cell ALL, trisomy of chromosomes in, 65f pediatric B-cell ALL with hyperdiploid karyotype, 64f B-NHL, see B-cell non-Hodgkin lymphoma (B-NHL) Bone marrow basophilia, 219 Bone marrow eosinophilia, 219 Bone marrow/leukemic blood, cytogenetic analysis of culture harvesting/slide preparation/ staining, 46 historical perspectives banding patterns of “banding era,” 42 Burkitt lymphoma, 42 CISH, 42 FISH, diagnostic utility in cytogenetics, 42–43 “microarray era,” impact, 43 Philadelphia chromosome, CML, 42 karyotype and cytogenetic nomenclature chromosomal abnormalities, types, 48 G-banded bone marrow karyotype, 47f hematolymphoid chromosomal abnormalities (ISCN nomenclature), 49t refinement of chromosome morphology, techniques, 48 structural chromosomal rearrangements in neoplasia, 49t microscopic analysis of, guidelines for, 46–47 specimen collection and storage, 43–44 specimen processing and tissue culture culture conditions used for hematolymphoid disorders, 45t optimal cell density determination, methods, 44 short-term cultures, advantages, 44–45 Bone marrow/leukemic blood, FISH analysis of advantages/disadvantages of FISH, 54–55 clinical indications, 51 FISH, basic principles of, 50–51 FISH probes used, types of, 52f CEPs, 52 commercially available probes for hematolymphoid disorders, 53t–54t LSI, 52 WCP, 52 “Buffy coat,” 3

344 Burkitt lymphoma (BL), 42, 70, 72–73, 72f, 90t, 94, 97, 178–180, 179t, 262 endemic, sporadic, and immunodeficient BLs, 179t and MYC, 179–180 MYC/IGH rearrangement in endemic/sporadic BL, 179f MYC translocation testing, diagnosis of BL, 180 other genetic abnormalities in, 180–181 genetic differences between BL/DLBCL, 181t “starry sky” pattern of macrophages, 178 C CAGRs, see Cancer-associated genomic regions (CAGRs) Cancer-associated genomic regions (CAGRs), 326 Cancer stem cell (CSC), 113–116 Cancer vaccines, 295, 315 R BiovaxID , 316 R GARDASIL , 316 Capillary electrophoresis (CE), 10, 12–13, 28, 140f, 144f, 164f, 223, 236 advantages over conventional gel electrophoresis, 12 applications, 13 detection window, 12 separation of analytes, 12 shadow peak, 12 Carl Zeiss, 4 C banding, 42, 46 CBFB-MYH11, 133, 135 exon–intron structure of, 136f CCD, see Charge-coupled device (CCD) CDC, see Complement-dependent cytotoxicity (CDC) CDCC, see Complement-dependent cell-mediated cytotoxicity (CDCC) CDRs, see Complementarity-determining regions (CDRs) Cell enrichment, 3–4 Centromere enumeration probes (CEPs), 52 CEPs, see Centromere enumeration probes (CEPs) CGH, see Comparative genomic hybridization (CGH) Chaotropic salt, 7–8 Charge-coupled device (CCD), 12 Chemokine receptor 4 (CXCR4), 328 Chemotherapy, 60, 62, 63f, 87, 114, 119–120, 130, 142, 165, 293, 295, 302, 311, 312t, 317–318

Index Chimeric mABs, 298 CHL, see Classical Hodgkin lymphoma (CHL) Chromatin remodeling, 108, 334 Chromogenic in situ hybridization (CISH), 42 Chromosomal abnormalities numerical abnormalities, 48 structural abnormalities, 48 Chromosomal rearrangements in neoplasia, molecular mechanisms, 48–50, 49t Chromosomal translocations resulting into BCL2 rearrangement, 263–264 Chromosome band, 48 Chromosome microarray analysis/microarray CGH, 43 Chronic eosinophilic leukemia/idiopathic hypereosinophilic syndrome, 58 Chronic lymphocytic leukemia (CLL), 29, 43, 45t, 51, 67, 90, 166, 255–280, 299t, 302, 332 See also CLL, molecular pathology of; Cytogenetic abnormalities in CLL Chronic myelogenous leukemia (CML), 13, 333 diagnostic testing cytogenetic karyotyping, 222 FISH, 223 PCR strategies, 223 RT-PCR technique, 222 disease monitoring/response to therapy, 223–226 criteria for lack of response, 225t cytogenetic response, 223–226 hematologic response, 223–226 imatinib mesylate therapy, 224–225 molecular response, 223–226 response types and equivalent estimated tumor burden, 224t samples/recommended frequencies for various types of response, 225t epidemiology, clinical, and laboratory features absolute basophilia/eosinophilia/ leukocytosis, 219 splenomegaly and purpura, 219 symptoms at diagnosis, 219 WHO criteria for diagnosis, 219 historical perspective and current relevance, 217–218 BCR–ABL1 fusion, study, 218 imatinib, treatment of CML, 218 molecular diagnostics, impact, 218 Philadelphia chromosome, discovery of, 217–218

Index timeline of landmark developments in CML to use of targeted therapy, 218f management of, integration of molecular diagnostic testing in, 231–232 quantitative RT-PCR in disease monitoring, 226–228 resistance to tyrosine kinase inhibitor therapy, 229–231 structure and pathogenesis of BCR–ABL1, 220–222 ABL1 tyrosine kinase activity, study in mouse models, 221–222 abnormalities in blast-phase/ accelerated-phase, 222 breakpoints in ABL1, results, 220 breakpoints in BCR, 220–221 chimeric nature of BCR-ABL1 fusion, 221 Philadelphia chromosome from reciprocal translocation, 220, 220f t(9;22) mechanism, 220 Chronic myeloproliferative disorders, 82–85 BCR–ABL1-negative myeloproliferative neoplasms chronic neutrophilic leukemia, 84 essential thrombocythemia, 84 polycythemia vera, 84 primary myelofibrosis, 84 molecular and cytogenetic findings, 83t molecular tests for BCR–ABL1 diagnosis of CML, 83 other BCR–ABL1-negative disorders, 84–85 Philadelphia chromosome, reciprocal translocation of diagnosis of CML, 83 Chronic neutrophilic leukemia (CNL), 58 CISH, see Chromogenic in situ hybridization (CISH) Classical Hodgkin lymphoma (CHL), 200–201 CLL, see Chronic lymphocytic leukemia (CLL) CLL, molecular pathology of cytogenetic abnormalities apoptosis, 278–279 B-cell receptor, 270–277 chromosomal translocations resulting into BCL2 rearrangement, 263–264 deletion 17p13, 260–261 deletion 6q, 261 deletion 13q14, 257–259 deletion 11q22-q23, 259–260

345 epigenetic changes, 266 FISH/cytogenetics, identification methods, 256, 258f high-throughput molecular methods to assess CLL, 266–270 8q24 gain, 262 role of the microenvironment, 279–280 stimulation with CD40 ligand expressing cells and IL-4, 256 stimulation with CpGoligodeoxynucleotides and IL-2, 256 t(2;14)(p16;q32), 265 t(14;19)(q32;q13), 262–263 translocations involving chromosome 14q32, 266 Trisomy 12, 260 Trisomy 3q27, 261 incidence in western/Asian countries, 256 lymphocytosis in CLL/lymphadenopathy in SLL patients, 256 Clonal abnormality, (ISCN 2009), 47 Clonality assessment, 25–31 IGH receptor gene, 26, 27f Ig/TCRs, characteristics and recombination process, 26–28, 27t limitations, 30–31 malignant or reactive/benign cells, characterization, 25–26 techniques PCR-based assessment of TCR, 30 PCR-based methods, analysis of the IGH gene, 28–29, 29f somatic hypermutation process, 29–30 Southern blotting, 28 CLP, see Common lymphoid progenitor (CLP) CML, see Chronic myelogenous leukemia (CML) CMP, see Common myeloid progenitor (CMP) Common hematolymphoid chromosomal abnormalities (ISCN nomenclature), 49t Common lymphoid progenitor (CLP), 327 Common myeloid progenitor (CMP), 327 Comparative genomic hybridization (CGH), 41, 43, 47, 82, 109, 120, 158, 191, 194, 260, 267, 267f See also Array comparative genomic hybridization (array-CGH) Complementarity-determining regions (CDRs), 27f, 29, 160f, 161, 296, 298 Complement-dependent cell-mediated cytotoxicity (CDCC), 296–297

346 Complement-dependent cytotoxicity (CDC), 296 Conventional karyotyping, 69, 81, 128–130, 132, 135, 139, 257 Core binding factor AMLs (CBF-AML), 133 Corticosteroids, 118 CRLF2, see Cytokine receptor-like factor 2 (CRLF2) CXCR4, see Chemokine receptor 4 (CXCR4) Cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP), 302 Cytogenetic abnormalities in CLL apoptosis, 278–279 B-cell receptor, 270–277 pharmacological inhibition of BCR signaling, 277 somatic mutations of Ig variable region genes, 271–274 stereotypy, 274–277 chromosomal translocations resulting into BCL2 rearrangement, 263–264 deletion 17p13, 260–261 deletion 6q, 261 deletion 13q14 miR-15a/miR-16-1 deletion, role in pathogenesis, 258–259 13q14, site of a tumor suppressor gene, 258–259 Rb1 deletion, role in pathogenesis, 258 deletion 11q22-q23 ATM gene mutations, poor prognosis, 259–260 ATM gene, role in CLL pathogenesis, 259 ATM-mutant CLL cases, 259 CUL5 (ubiquitin-dependent apoptosis regulation), 260 NPAT (cell cycle regulation), 260 PPP2R1B (component of the cell cycle and apoptosis regulating PP2A), 260 epigenetic changes, 266 high-throughput molecular methods to assess CLL, 266–270 8q24 gain MYC abnormalities, 262 MYC overexpression in CLL, 262, 263f role of the microenvironment, 279–280 t(2;14)(p16;q32), 265, 265f t(14;19)(q32;q13), 262–263, 264f translocations involving chromosome 14q32, 266 Trisomy 12, 260

Index Trisomy 3q27 BCL6 gene, repression of transcription, 261 BCL6 gene, translocations in, 261 Cytogenetic tests, 81 conventional karyotyping, 81 FISH, 81 Cytokine receptor-like factor 2 (CRLF2), 111–112 D Dasatinib, 16, 230, 245, 277, 308–310, 314 Degradation of nucleic acids, 5–6 Deletion 17p13, 260–261 Deletion 6q, 261 Deletion 13q14, 257–259 Deletion 11q22-q23, 259–260 Delta-like ligand, 117 Denaturing high-performance liquid chromatography (DHPLC), 266–267 “de novo” DNA methyltransferases, 335 Deoxynucleotide triphosphates (dNTPs), 14, 18 DEPC, see Diethylpyrocarbonate (DEPC) Detection window, 12 DHPLC, see Denaturing high-performance liquid chromatography (DHPLC) Diethylpyrocarbonate (DEPC), 8 Diffuse large B-cell lymphoma (DLBCL), 70–72, 90t, 93–94, 168, 172–174, 181t, 330 BCL6 alterations in, 172–174 groups based on pathogenic mechanisms, 174 other genetic alterations in, 174–175 other lymphomas of large B cells, 173t specific diffuse large B-cell subtypes, 172t subtyping of germinal center B-cell (GC) type, 171–172 post-germinal center or activated B-cell (ABC) type, 171 DiGeorge syndrome critical region gene 8 (DGCR8), 325 Diploid cell, 48 DLBCL, see Diffuse large B-cell lymphoma (DLBCL) DNA sequencing NGS, 17–18 pyrosequencing, 16–17 drawbacks, 16–17

Index Sanger sequencing, 14–15 limitations, 15 DNTPs, see Deoxynucleotide triphosphates (dNTPs) Down syndrome, 110–113 Dried blood spots (guthrie cards), 5 Drosha, 325 Dual-color break-apart (DCBA) probe, 43 Dual-color, dual-fusion (DCDF) LSI probes, 52–53 Dye-primer chemistry, 15 E Early T-cell precursor (ETPs), 120 EATL, see Enteropathy-associated T-cell lymphoma (EATL) EDTA, see Ethylenediaminetetraacetic acid (EDTA) EGFR, see Epithelial growth factor receptor (EGFR) Electrophoresis, 10–13 agarose gels, use of, 11 capillary electrophoresis, advantages, 11 Enteropathy-associated T-cell lymphoma (EATL), 97, 197 Epithelial growth factor receptor (EGFR), 294, 297 Essential thrombocythemia, 58, 82, 83t, 84, 110, 216, 221, 232, 307, 313 Ethidium bromide, 10–11, 11f, 22 Ethylenediaminetetraacetic acid (EDTA), 4 ETPs, see Early T-cell precursor (ETPs) Exportin 5, 325 Extranodal marginal zone B-cell lymphoma (MALT-type), 73 Extranodal natural killer-/T-cell lymphoma, 197–198 F FACS, see Fluorescent antibody cell sorting (FACS) FBXW7, 119 Fiber FISH, 43 Ficoll-Hypaque, 3 FISH, see Fluorescence in situ hybridization (FISH) FISH, basic principles of, 50–51 analysis on metaphase chromosomes interphase FISH, 51 analysis on paraffin-embedded tissue section advantage/disadvantage, 51 Flow cytometry, 1, 25, 80–81, 85–88, 91, 95, 104, 186, 272

347 FLT3-LM and FLT3-TKD, 143–145 PCR detection of FLT3-LM, 144f structure of FLT3 gene, 144f Fluorescence dye-terminator chemistry, 15 Fluorescence in situ hybridization (FISH), 42 See also Chromogenic in situ hybridization (CISH) Fluorescence resonance energy transfer (FRET) technology, 15 Fluorescent antibody cell sorting (FACS), 3 Fluorometric methods, 9–10 Follicular lymphoma (FL), 71–72, 92, 166–169 and BCL2 t(14;18), 166–168 BCL2, antiapoptotic effect, 166 BCL2/IGH rearrangement at MBR, 167, 167f cytogenetics/FISH/PCR, detection methods, 168 grade 3B follicular lymphomas, 168 +18q mechanism, 168 genetic abnormalities in grade 3B FL, 168–169, 169t additional abnormality by routine cytogenetics, 168 gene expression profiling, 169 transformation to higher grade lymphoma, 168 Formalin, 5–6, 28, 30 FRA, see Fragile sites (FRA) Fragile sites (FRA), 326 Framework regions (FRs), 161 French–American–British (FAB) scheme, 41 FRET, see Fluorescence resonance energy transfer (FRET) technology G γ-secretase inhibitors (GSIs), 117 R GARDASIL , 316 Gastrointestinal stromal tumors (GISTs), 245, 308–309 GATA1, 110–112 G-banded bone marrow karyotype, 47f GCB-DLBCL, see Germinal center B-cell-like phenotype (GCB-DLBCL) Gel electrophoresis, 10, 11f, 12, 14, 19, 25, 192 Gene expression profiles (GEP), 82, 93–94, 169, 190–191, 198–199, 201 Gene therapy, 316 Gene transfer process, 316 GEP, see Gene expression profiles (GEP) Germinal center B-cell-like phenotype (GCB-DLBCL), 331

348 Giemsa banding, 42 GISTs, see Gastrointestinal stromal tumors (GISTs) GITC, see Guanidine isothiocyanate (GITC) Guanidine isothiocyanate (GITC), 8 H Hairpin RNA precursor (pre-miRNA), 325 Hairy and enhancer-of-split analog-1 (HES1), 117, 119 Helicobacter pylori, 73, 93, 175 Hematologic malignancies, targeted therapy angiogenesis-inhibiting drugs, 314 apoptosis-inducing drugs, 315 cancer vaccines, 315–316 challenges/changes in clinical practice, 317–318 gene therapy, 316 molecular genetic signatures, clinical use, 293–294 small molecule drugs, 303–310 ATRA, 310–311 examples for AML, 311–312 examples for treatment of CML, 314 examples for treatment of MPN, 312–313 targeted therapy, 294–296 advantages over traditional cancer therapies, 295 conventional cytotoxic chemotherapeutic agents, 295 definitions, 294–295 “magic bullet” therapy, 294 molecular targeted therapy, 294 National Cancer Institute classification, 295 test and the drug criterion by FDA, 294–295 therapeutic monoclonal antibodies in targeted therapy, 296–301 examples, 302–303 Hematolymphoid disorders array-based genomic profiling of, 74–75 disadvantage, 74 FISH analysis, 74 SNP analysis by molecular allelokaryotyping, 74 SNP analysis of AML/MDS samples, 75 uniparental disomy of chromosomes, 74–75 bone marrow/leukemic blood, cytogenetic analysis of

Index culture harvesting, slide preparation, and staining, 46 historical perspectives, 42–43 karyotype and cytogenetic nomenclature, 47–48 microscopic analysis, guidelines for, 46–47 specimen collection and storage, 43–44 specimen processing and tissue culture, 44–45 bone marrow/leukemic blood, FISH analysis of advantages/disadvantages of FISH, 54–55 clinical indications, 51 FISH, basic principles of, 50–51 FISH probes used, types of, 52–54 chromosomal rearrangements in neoplasia, molecular mechanisms, 48–50 diagnosis of, cytogenetic analysis in array CGH, genome-wide study, 41 chromosome analysis, 40–41 FISH, 41 myeloid/lymphoid neoplasms classification, 41 PCR, 41 lymphoid disorders, diagnostic/prognostic cytogenetic markers B-lymphoblastic leukemia/lymphoma with recurrent genetic abnormalities, 63–66 chronic lymphocytic leukemia/small lymphocytic leukemia, 67 Hodgkin lymphoma, 74 non-Hodgkin’s lymphoma, 70–73 plasma cell myeloma, 67–70 T-lymphoblastic leukemia/lymphoma, 66–67 myeloid disorders, diagnostic/prognostic cytogenetic markers AML, 59–63 MDS, 59 MPN, 55–58 Hematopoietic stem cells (HSCs), 103, 222, 245, 298, 309 Hepatosplenic T-cell lymphoma (HSTL), 196–197 HES1, see Hairy and enhancer-of-split analog-1 (HES1) High-throughput molecular methods to assess CLL, 266–270 array-CGH, 267–268 BAC array-based CGH, 268

Index CGH-a technique applied to CLL cases, 268, 268f oligonucleotide-based array-CGH, 268 principles of, 267f gene expression profiling, 269 gene expression levels in CLL, 270f microRNA, 269 MLPA, 269 sequence and mutation analysis, 266–267 array-based mutation analysis, 267 DGGE, 267 DHPLC, 266 SSCP, 267 SNP-arrays, 268–269 High-throughput sequencing, 17 See also Next-Generation Sequencing (NGS) Hodgkin lymphoma (HL), 74, 90, 97–98, 173, 173t, 199, 239, 331 CHL, 200–201 NLPHL, 200 HSCs, see Hematopoietic stem cells (HSCs) HSTL, see Hepatosplenic T-cell lymphoma (HSTL) Humanized type of mABs, 298 Hybridization probes, 22–23, 246 Hydrolysis probes, 23 Hyperdiploid cell, 48 Hypodiploid cell, 48 I IGH, see Immunoglobulin heavy-chain gene (IGH) IKAROS, 108–109, 108f chromatin remodeling, 108 DNA-binding and nuclear localization, 108 IKZF1, 107–109, 108f, 113 IL-7 alpha receptor, 112 R R Imatinib mesylate (Glivec /Gleevec ), 308 dasatinib, 310 nilotinib or AMNI07, 309–310 treatment of CML, 308–309 imatinib-based therapy, problems, 309 treatment of GISTs, 309 Immunoglobulin heavy-chain gene (IGH), 160, 160f, 163f Immunoglobulin (Ig), 26, 27t, 259 Insulin-like growth factor receptor (IGFR), 327 Interferon-α (alpha) therapy, 223 International Prognostic Scoring System (IPSS), 59 Interphase FISH, 51 IPSS, see International Prognostic Scoring System (IPSS)

349 J JAK2, 14, 21–24, 44, 55, 83t, 84–86, 111–112, 146, 194, 216, 216t, 232–238, 303, 307, 313, 332 JAK2 R683 mutation, 111–112 JAK2 V617F mutation, 14, 21–22, 44, 84, 233–234, 236 Janus kinase, 110, 307–308 “Just another kinase,” see Janus kinase K Kappa-deleting element (Kde), 161f, 162 Kinase inhibitors, see Small molecule drugs Kinases, categories, 307 Kit receptor, 245f, 328 L LATE-PCR, see Linear-after-the-exponential PCR (LATE-PCR) Leukemia predisposition, 113 Leukemia stem cell, 114 Linear-after-the-exponential PCR (LATE-PCR), 25 Locus-specific identifier (LSI) probes, 52, 223 LOH, see Loss of heterogeneity (LOH) Loss of heterogeneity (LOH), 327 LPL, see Lymphoplasmacytic lymphoma (LPL) LSI probes, see Locus-specific identifier (LSI) probes Lumiliximab, 300T, 302 Lymphadenopathy, 45t, 91, 193, 195, 199, 244, 256, 261 Lymphoblastic lymphoma, 66, 103, 239, 241, 243 Lymphocytosis, 45t, 256, 302 Lymphoid disorders, diagnostic/prognostic cytogenetic markers B-lymphoblastic leukemia/lymphoma, 63–66 chronic lymphocytic leukemia/small lymphocytic leukemia, 67 Hodgkin lymphoma, 74 non-Hodgkin’s lymphoma, 70–73 plasma cell myeloma, 67–70 T-lymphoblastic leukemia/lymphoma, 66–67 Lymphoid neoplasms classification FAB scheme (1976), 41 REAL (1994), 41 WHO classification (1997), 41 Lymphoplasmacytic lymphoma (LPL), 165, 181–182

350 M mABs, see Monoclonal antibodies (mABs) “Magic bullet” therapy (Paul Ehrlich), 294 Major break point cluster region (M-bcr), 107 Major breakpoint region (MBR), 167, 167f, 173 Malignant lymphomas molecular/cytogenic findings, 90–91 ALCL, 95–96 Burkitt lymphoma, 94 diagnostic problems, 91–92 DLBCL, 93–94 FL, 92 MCL, 92 MZL, 93 NK-cell lymphomas, 96–97 PCN, 94–95 T-cell lymphomas, 95 MALT lymphomas, see Mucosa-associated lymphoid tissue (MALT lymphomas) Mammalian target of rapamycin (mTOR), 120 Mantle cell lymphoma (MCL), 45t, 51, 54t, 70–71, 73, 90t, 92, 169–170, 305t, 315 clinical implications, 171 cyclin D1 dysregulation, detection of testing for t(11;14)(q13;q32), methods, 170 genetic abnormalities in, 170 MAP kinases, see Mitogen-activated protein (MAP) kinases Marginal-zone lymphomas (MZLs), 93, 159t, 175–178 clinical implications, 177 detection of MALT lymphoma translocations, 177 genetic abnormalities in, 176–177 frequencies (%) of MALT lymphoma translocations and trisomies, 176t MALT, site of occurence, 176 other MZLs splenic MZLs, 178 Mast cell disease, 216, 244–246, 245f mastocytosis, 244 diagnosis of, 244 increased risk of myeloid neoplasms, 244 M-bcr, see Major break point cluster region (M-bcr) m-bcr, see Minor break point cluster region (m-bcr) MBR, see Major breakpoint region (MBR)

Index MCL, see Mantle cell lymphoma (MCL) MDS, see Myelodysplastic syndromes (MDS) Megakaryopoiesis, 328 Methylation-specific PCR, 24–25 Methyltransferase enzymes, 13 MF, see Mycosis fungoides (MF) “Microarray era,” 43 Micro-RNAs (miRNAs), 54t, 109, 147, 158, 258, 269, 279, 325–335 Minimal residual disease (MRD), 3, 20–21, 23, 28, 51, 57, 94, 120, 128–129, 131, 133, 135, 163, 180, 184, 189, 218, 223, 227 Minor break point cluster region (m-bcr), 107 miR-230, 109–110 miR-10a, 328, 330t, 333–334 miR-130a, 328 miRNAs, see Micro-RNAs (miRNAs) miRNAs in hematologic malignancies biogenesis of miRNAs, 325–327, 326f miRNAs and human cancer, relationship, 326–327 miRNAs in leukemias, 332–335 miRNAs in lymphomas, 329–332 miRNAs in normal hematopoiesis, 327–329 miRNAs in leukemias, 330t, 332–335 high expression of TCL1, effects on CLL, 333 miR-15a and miR-16, role as TSGs in CLL, 332–333 miR-191 and miR-199a, prognostic implications in AML, 334–335 miR-17-92, role in ALL vs. normal CD19+ B cells, 333–334 miR-17-92, role in CML, 333 miRNAs in lymphomas, 329–332, 330t miR-143 and miR-145, role, 331 miR-106a-363 polycistron overexpression, role, 331 miR-106b-25 and miR-17-92, control of apoptosis, 331 miR-17-92 cluster overexpression, role, 331 miRNA expression in Hodgkin lymphoma, 331–332 miR-155, role in lymphomagenesis ABC-DLBCL vs. and GCBDLBCL, 331 B-cell-specific miR-155 transgenic mouse model, study, 329 miR-155 knockout (KO) mice models, study, 329

Index pediatric Burkitt’s lymphoma, 329 miRNAs in normal hematopoiesis, 327–329 C57BL6 mouse model transplanted with mice MPPs overexpressing miR-155 miR-155 block of erythrocytic/ megakaryocytic differentiation, 328 megakaryocyte differentiation, 328 miR-181a expression, effects, 328 miR-150, inhibition of B-cell development, 329 miRNA expression patterns in erythrocyte precursors, 327–328 miRNAs as “fine tuners,” 329 miR-223, role in human granulopoiesis MEF2c/IGFR, effects, 327 miR-424, role in myeloid hematopoiesis, 327 silencing of miR-451 in zebra fishembryo model, results, 328 Mitogen-activated protein (MAP) kinases, 107, 110, 269 Mitogens, 45 MLPA, see Multiplex ligation-dependent probe amplification (MLPA) “Molecular allelokaryotyping,” 74 Molecular and cytogenetic procedures, 81 CGH, 82 generation of GEP by array analyses, 82 sequencing of DNA, 82 Molecular Machines and Industries, 4 Molecular pathology of AML AML-associated mutations, 129t AML with recurrent genetic abnormalities AML with balanced translocations/ inversions, 130–133 AML with gene mutations, 139–142 core binding factor AML, 133–137 gene expression and prognosis in NK-AML, 145–146 gene mutations with prognostic significance, 143–145 other recurrent translocations, 137–139 rare subtypes of AML, 139 mutations and translocations associated with other myeloid neoplasms, 146 Molecular pathology of B-cell/T-cell lymphomas, see Burkitt Lymphoma (BL); Molecular testing for B-NHL; Molecular testing for T-NHL Molecular pathology of CLL cytogenetic abnormalities apoptosis, 278–279

351 B-cell receptor, 270–277 chromosomal translocations resulting into BCL2 rearrangement, 263–264 deletion 17p13, 260–261 deletion 6q, 261 deletion 13q14, 257–259 deletion 11q22-q23, 259–260 epigenetic changes, 266 FISH/cytogenetics, identification methods, 256, 258f high-throughput molecular methods to assess CLL, 266–270 8q24 gain, 262 role of the microenvironment, 279–280 stimulation with CD40 ligand expressing cells and IL-4, 256 stimulation with CpGoligodeoxynucleotides and IL-2, 256 t(2;14)(p16;q32), 265 t(14;19)(q32;q13), 262–263 translocations involving chromosome 14q32, 266 Trisomy 12, 260 Trisomy 3q27, 261 incidence in western/Asian countries, 256 lymphocytosis in CLL/lymphadenopathy in SLL patients, 256 Molecular pathology of MPN BCR–ABL1-negative “classic” myeloproliferative neoplasms effect of JAK2 allelic burden, 235–236 epidemiology, clinical, and laboratory features, 232–233 JAK2 mutation detection methods, 236–237 JAK2 mutations in PV, 234–235 JAK2 – unresolved issues, 237–238 JAK2 V617F’s contribution to diagnosis of MPNs, 233–234 MPL, 238 CML diagnostic testing, 222–223 disease monitoring/response to therapy, 223–226 epidemiology, clinical, and laboratory features, 219 historical perspective and current relevance, 217–218 management of, integration of molecular diagnostic testing in, 231–232

352 Molecular pathology of MPN (cont.) quantitative RT-PCR in disease monitoring, 226–228 resistance to tyrosine kinase inhibitor therapy, 229–231 structure and pathogenesis of BCR–ABL1, 220–222 mast cell disease, 244–246 PDGFR and FGFR1 abnormalities FGFR1, 243–244 PDGFRA, 240–241 PDGFRB, 241–243 spectrum of eosinophilia-related disorders, 239–240 tyrosine kinases in, 216t “Molecular targeted therapy,” 294 Molecular techniques in hematopathology step 3: assessment of nucleic acid quality and quantity, 9–10 step 2: nucleic acid extraction, purification, and storage extraction techniques, 7–9 step 4: selected techniques allele-specific PCR, 20–21 asymmetric PCR, 25 clonality assessment, 25–31 DNA sequencing, 14–18 electrophoresis, 10–13 methylation-specific PCR, 24–25 nested PCR, 21 PCR, 18–20 Q-PCR, 23–24 real-time PCR, 21–23 restriction enzymes, 13–14 restriction site PCR, 25 RT-PCR, 20 step1: specimen collection and processing cell enrichment and selection techniques, 3–4 patient identification and labeling, 2 source-specific requirements for nucleic acid integrity, 4–6 standard precautions and safety, 2 Molecular testing for B-NHL B-cell biology and maturation, 158–163 clonality testing, 163–165 somatic hypermutation testing, 166 Burkitt Lymphoma, 178–181 and MYC, 178–180 other genetic abnormalities in, 180–181 detection of MALT lymphoma translocations, 177

Index DLBCL, 172–174 BCL6 alterations in, 172–174 genetic alterations in, 174–175 follicular lymphoma, 166–167 and BCL2 t(14;18), 166–168 other genetic abnormalities in, 168–169 lymphoplasmacytic lymphoma, 181–182 MCL, 169 clinical implications, 171 cyclin D1 dysregulation, detection of, 170 genetic abnormalities in, 170 MZLs, 175–176 clinical implications, 177 genetic abnormalities in, 176–177 other MZLs, 177–178 Molecular testing for T-NHL AITL, 191 genetic abnormalities in, 191–192 ALCL, 186–189 detection of ALK dysregulation, 189–190 genetic abnormalities in, 190–191 EATL, 197 extranodal natural killer-/T-cell lymphoma, 197–198 HSTL, 196–197 MF, 192 genetic abnormalities in, 193–195 molecular staging of, 193 PTCL-NOS, 198–199 SS, 195 genetic abnormalities in, 195–196 T-cell biology and maturation, 182–184 clonality testing, 184–186 Molecular tests, 81–82 DNA/RNA analyses, 82 “negative” finding cases, FISH analysis, 82 residual disease detection, 82 structural abnormalities, detection of, 81 Monoclonal antibodies (mABs), 3, 273, 276, 295–298, 299t, 302–303, 308, 317 Monosomy, 48 MPN, see Myeloproliferative neoplasms (MPN) MPN, molecular pathology of BCR–ABL1-negative “classic” myeloproliferative neoplasms effect of JAK2 allelic burden, 235–236 epidemiology, clinical, and laboratory features, 232–233

Index JAK2 mutation detection methods, 236–237 JAK2 mutations in PV, 234–235 JAK2 – unresolved issues, 237–238 JAK2 V617F’s contribution to diagnosis of MPNs, 233–234 MPL, 238 CML diagnostic testing, 222–223 disease monitoring/response to therapy, 223–226 epidemiology, clinical, and laboratory features, 219 historical perspective and current relevance, 217–218 management of, integration of molecular diagnostic testing in, 231–232 quantitative RT-PCR in disease monitoring, 226–228 resistance to tyrosine kinase inhibitor therapy, 229–231 structure and pathogenesis of BCR–ABL1, 220–222 mast cell disease, 244–246 PDGFR and FGFR1 abnormalities FGFR1, 243–244 PDGFRA, 240–241 PDGFRB, 241–243 spectrum of eosinophilia-related disorders, 239–240 tyrosine kinases in, 216t MPP, see Multipotent hematologic progenitor (MPP) MRD, see Minimal residual disease (MRD) mTOR, see Mammalian target of rapamycin (mTOR) Mucosa-associated lymphoid tissue (MALT lymphomas), 73, 90t, 93, 175 Multiplex ligation-dependent probe amplification (MLPA), 269 Multiplex PCR, 20 Multipotent hematologic progenitor (MPP), 327 MYC and Burkitt Lymphoma, 178–180 Mycosis fungoides (MF), 192–195 genetic abnormalities in, 193–195 molecular staging of, 193 Myelodysplastic disorders MDS group, entities, 85 “proliferative” clinical features, 85 refractory cytopenia of childhood, 85–86 “cytopenic” features, 85

353 genetic abnormalities, 86 morphological analysis, 85 patients with RARS, 86 5q deletion, 86 Myelodysplastic syndromes (MDS) complex karyotype identified in a 83-year-old female with pancytopenia, 60f conventional cytogenetic analysis chromosomal changes in MDS, 59 FISH analysis in, 59 “Myeloid cytogenetic markers,” 63 Myeloid/lymphoid neoplasms classification, FAB scheme, 41 Myeloproliferative neoplasms (MPN), 55–58, 82–85 chronic eosinophilic leukemia/idiopathic hypereosinophilic syndrome, 58 chronic neutrophilic leukemia, 58 CML, BCR/ABL1 positive, 55–57 karyotyping, FISH, and RT-PCR, 55–57 Philadelphia chromosome, generation of, 55, 56f treatments, 56–57 cytogenetic abnormalities in, 57f essential thrombocythemia, 58 polycythemia vera, 57–58 primary myelofibrosis, 58 See also Chronic myeloproliferative disorders MZLs, see Marginal-zone lymphomas (MZLs) N Nested PCR, 21 Neurofibromatosis, 113 Next-Generation Sequencing (NGS), 14, 17–18 advantages over automated Sanger-based methods, 17 drawbacks, 17 high-throughput sequencing of single DNA, 18 novel applications, 18 NGS, see Next-Generation Sequencing (NGS) Nilotinib, 230, 304t, 308–310, 314 NK-cell lymphomas, 91, 96–97, 198 NLPHL, see Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) NOD/SCID mouse, 114–116 Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL), 74, 159t, 173, 200 Noncoding RNAs (ncRNAs), see Micro-RNAs (miRNAs)

354 Non-Hodgkin’s lymphoma (NHL) anaplastic large-cell lymphoma, 73 Burkitt lymphoma, 72–73 diffuse large B-cell lymphoma, 72 extranodal marginal zone B-cell lymphoma (MALT-type), 73 follicular lymphoma, 71–72 mantle cell lymphoma, 73 splenic marginal zone lymphoma, 73 Non-receptor tyrosine kinases (non-RTKs), 303 examples, 303–307 Non-RTKs, see Non-receptor tyrosine kinases (non-RTKs) “Non-specific” abnormalities, see Chromosomal abnormalities NOTCH1, 106, 106t, 117–120, 118f NPM1, 139–141 exon–intron structure of, 140f Nucleic acid degradation of, 5–6 extraction techniques inorganic (chaotropic salt–silica column), 8 organic (phenol–chloroform), 7–8 integrity, source-specific requirements for bone marrow aspirates/whole blood/body fluids, 4 dried blood spots (guthrie cards), 5 fixed, paraffin-embedded tissue, 5–6 fresh tissue, 5 quality/quantity, assessment of, 9–10 fluorometric methods, 9–10 gel electrophoresis, qualitative assessment, 10, 11f spectrophotometric methods, 9 storage long-term storage, considerations, 9 stability of DNA in storage, 8 stability of RNA in storage, 8–9 O Oncolytic virotherapy, 316 P Palindromic sequences of nucleotides (P nucleotides), 161 PALM Microlaser Technologies, 4 Paraffin, 5–7, 28, 42, 51, 55, 70–71, 82, 91, 165, 170, 177, 193, 273f PCN, see Plasma cell neoplasms (PCN) PCR, see Polymerase chain reaction (PCR) PDGFR and FGFR1 abnormalities FGFR1, 243–244 PDGFRA, 240–241

Index PDGFRB, 241–243 spectrum of eosinophilia-related disorders, 239–240 Peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS), 198–199 Ph+ B-ALL, 107 Phenol–chloroform, 7–8 Philadelphia chromosome, 42, 55, 56f, 83, 107, 217–220, 220f, 222–224, 232, 293, 309, 333 Phosphatase and tensin analog (PTEN), 119 Phosphatidylinositol 3-kinase (PI3K), 107, 110, 118f, 119–120, 189, 222, 234, 235f, 238, 245, 272, 277, 307–308 Phosphatidylinositol-3, 4, 5 trisphosphate (PIP3), 119 Photomultiplier tube (PMT), 12 PI3K, see Phosphatidylinositol 3-kinase (PI3K) PIP3, see Phosphatidylinositol-3, 4, 5 trisphosphate (PIP3) Plasma cell myeloma, 45t, 51, 67–70, 69f, 95, 170 Plasma cell neoplasms (PCN), 68, 94–95, 165 PLZF protein, see Promyelocytic leukemia zinc finger (PLZF) protein PML–RARA translocation, detection of, 130–133 conventional karyotyping, 130 exon–intron structure of PML and RARA, 132f FISH probes, 130, 131f molecular minimal residual disease testing, 133 RQ-PCR, results, 131–133, 132f RT-PCR, 130–131 PMT, see Photomultiplier tube (PMT) P nucleotides, see Palindromic sequences of nucleotides (P nucleotides) Polyacrylamide gels, 12, 15 Polyadenylated precursor (pri-miRNA), 325 Polycythemia vera, 44, 57–58, 82, 83t, 84, 110, 216, 216t, 232–233, 307, 313 Polymerase chain reaction (PCR), 2–4, 18–20, 41, 50, 82, 246, 269 Post-germinal center B-cell malignancies, 29 P210 protein, 221 Precursor B-lymphoblastic lymphoma (B-LBL), 103 Precursor lymphoid malignancy altered NOTCH signaling in T-ALL, 117–119

Index B-lymphoblastic leukemia with t(9;22)(q34;q11.2) ALL lacking BCR–ABL1 expression, findings, 109 BCR–ABL1 fusion mRNA transcript, expression of, 107 BCR–ABL1 signaling and altered IKAROS function, 108–109 genomic organization of the IKZF1 gene, 108f homodimerization of BCR–ABL1, results, 107 M-bcr, BCR break point in adult/pediatric B-ALLs, 107 mice deficient in IKAROS, defects, 108 miRNAs, role, 109–110 Ph+ B-ALL, clinical outcomes, 107 Ph+ B-ALL, SNP analysis, 108 cancer stem cells in precursor B-ALL: definitions and controversies, 113–116 cytogenetic/molecular lesions, 105–106 B-ALL and T-ALL, genetic lesions, 105, 106t chromosomal translocation, effects on gene expression, 106 “type A mutation,” 106 “type B mutation,” 106 down syndrome-associated ALL DS-ALL/ALL, cytogenetic analyses in non-DS children, 110 GATA1 mutations in TMD/AMKL, 110–111, 111f JAK2 mutations, 111 JAK2 R683 mutation, 111 pathogenesis of, role of CRLF2 in, 111–112 identification of novel ALL subtypes, 120 pathogenesis of T-ALL, role of PTEN/PI3K array-based comparative genomic hybridization, 120 mTOR, downstream target of PI3K-AKT, 120 PTEN, negative regulator of PI3K signaling, 119 role of aberrant NOTCH1 and PI3K/AKT signaling, 118f, 119–120 precursor lymphoblastic leukemia/lymphoma, genetic factors ALL development in children, risk factors, 113

355 transplacental leukemic “metastasis,” 113 WHO classification, 104–105, 104t Precursor T-lymphoblastic leukemia (T-ALL), 103 Precursor T-lymphoblastic lymphoma (T-LBL), 103 Primary myelofibrosis (PMF), 58, 82, 83t, 84, 110, 216, 216t, 232, 313 pri-miRNA, 325 Promyelocytic leukemia zinc finger (PLZF) protein, 328 PTEN, see Phosphatase and tensin analog (PTEN) Pyrosequencing, 14, 16–17, 231 Q 8q24 gain, 262 Q-PCR, see Quantitative real-time PCR (Q-PCR) Quantitative real-time PCR (Q-PCR), 23–24, 128–139, 141, 268 Quinacrine banding, 42 R RARS, see Refractory anemia with ring sideroblasts (RARS) Real-time PCR, 21–23 signal detection options, 22–23 Receptor tyrosine kinases (RTKs), 240, 303, 312 examples, 303 Recombination-activating gene (RAG) proteins, 160f, 161 Refractory anemia with ring sideroblasts (RARS), 85–86, 234 Restriction enzymes (REs) defense mechanism of, 13 DNA digestion by, 13 methyltransferase enzymes, role, 13 recombinant DNA technology, role in, 13 variations in fragment pattern by recognition sites, results, 13–14 Restriction site PCR, 25 Reverse transcription PCR (RT-PCR), 20, 24f, 57, 128–130, 132–133, 135–136, 139, 145, 177, 189, 192, 196, 222–223, 226f, 228, 231–232, 241, 243, 246, 270f The “Revised European–American Classification of Lymphoid Neoplasms” (REAL), 41 RISC, see RNA-induced silencing complex (RISC)

356 Rituximab, 174–175, 277, 298, 299t, 302 RNA-induced silencing complex (RISC), 326 RNA stabilization tubes (PAXgene series), 4 RTKs, see Receptor tyrosine kinases (RTKs) RT-PCR, see Reverse transcription PCR (RT-PCR) RUNX1, 20, 53t, 60, 65, 88t, 104t, 106, 113, 129t, 133–135, 134f RUNX1T1, 20, 53t, 60, 88t, 129t, 133–134, 134, 134f S Sanger, 14 Sanger chain termination methods, 14, 231 Sanger sequencing, 14–15, 14–16, 231 Sequencing by synthesis, see Pyrosequencing Sequencing, definition, 14 Sequencing of DNA, 13–15, 17, 82 Sézary syndrome (SS), 195 genetic abnormalities in, 195–196 ‘Shadow peak,’ 12 SHIP, see Src homology 2 domain-containing inositol-5-phosphatase (SHIP) Signal transducers and activators of transcription (STATs), 107 Signal transduction inhibitors, see Small molecule drugs Silica column, 7–8 Single nucleotide polymorphisms arrays (SNP-arrays), 43, 74–75, 108, 267f, 268–269 Single-stranded binding protein (SSB), 16–17 SLL, see Small lymphocytic lymphoma (SLL) Small lymphocytic lymphoma (SLL), 67, 166, 255–256 Small molecule drugs, 303–310 ATRA, 310–311 deregulation of phosphorylation patterns, effects, 303 examples for AML, 311–312, 312t examples for treatment of CML, 312–313, 313t examples for treatment of MPN, 312–313 FDA approved drugs, 304t–306t half-life of, 308 kinases categories, 307 conformations in activation loop of, 307–308 multi-targeting approach imatinib mesylate, treatment of CML, 308–309 oral administration of drugs, 308

Index stages in clinical course of CML accelerated phase (AP), 309 blast crisis (BC), 309 chronic phase (CP), 309 tyrosine kinases, enzyme groups in non-RTKs, 303 RTKs, 303 Small molecule drugs vs. mABs, 307–308 Small molecule inhibitors, see Small molecule drugs SNP-arrays, see Single nucleotide polymorphisms arrays (SNP-arrays) Somatic hybridization technique/hybridoma technology, 297–298 Somatic hypermutation (SHM), 29–30, 159t, 161–166, 174, 179, 200, 259, 261, 271f, 273, 275 Southern blotting technique, 26, 28 Specimen collection and processing cell enrichment and selection techniques density-gradient centrifugation methods, 3 laser capture microdissection, 3 preparation of leukocyte-rich layer, 3 selective erythrocyte lysis, 3 nucleic acid integrity, source-specific requirements for bone marrow aspirates, whole blood, and body fluids, 4 dried blood spots (guthrie cards), 5 fixed, paraffin-embedded tissue, 5–6 fresh tissue, 5 patient identification and labeling, 2 standard precautions and safety, 2 Specimen harvesting, 46 Spectral karyotyping, 43 Spectrophotometers, 9 Spectrophotometric methods, 9 Splenic marginal zone lymphoma, 73, 90t, 96, 166, 177 Src homology 2 domain-containing inositol-5-phosphatase (SHIP), 329 SS, see Sézary syndrome (SS) SSB, see Single-stranded binding protein (SSB) STATs, see Signal transducers and activators of transcription (STATs) Stereotyped BCR, 274 SYBR green, 10, 22 T T-ALL, see Precursor T-lymphoblastic leukemia (T-ALL)

Index TaqMan probes, 23, 236 “Targeted therapy,” 294 T-cell biology and maturation, 182–184 diversity of TCRs (TRA/TRB/ TRD/TRG), 182–183, 183f, 184f TCR delta (TRD), uniqueness, 182, 183f clonality testing detection using primer designs, 185 flow cytometric immunophenotyping with antibodies, 186 PCR, false-positive and false-negative results, 186 PCR for TCR gene rearrangement, 185 predominant peak compared to polyclonal background, 185–186 Southern blot testing, 184 T-cell non-Hodgkin lymphoma (T-NHL), 182–199 T-cell receptors (TCRs), 13, 26, 27t, 66, 70, 87, 164, 182, 184f, 185, 193, 196–197, 240, 272 TCRs, see T-cell receptors (TCRs) TdT, see Terminal deoxynucleotidyl transferase (TdT) Terminal deoxynucleotidyl transferase (TdT), 27, 27f, 103, 160, 161f Therapeutic mABs, in targeted therapy, 296–301 administration by intravenous injections, 296 anti-cancer action of, approaches, 296–297 approved by FDA, 299t–301t chimeric and humanized types of mABs, 298 examples AME-133, 302 apolizumab, treatment of CLL, 302–303 bevacizumab, treatment of colon cancer, 302 bispecific monoclonal antibodies, treatment of CLL, 303 combination treatment regimens of mABs, 302 GA101, 302 lumiliximab, 302 mABs plus chemotherapy, CHOP, 302 rituximab and alemtuzumab, treatment of NHL/CLL, 302

357 small molecules directed to TRAIL, treatment of NHL, 302 veltuzumab, 302 fully humanized antibodies, development of, 298 general features, 298 immunoglobulin polypeptide chains in, 296 rituximab, treatment of NHL, 298 somatic hybridization technique/hybridoma technology, 297–298 water-soluble proteins, 296 Thymic stromal-derived lymphopoietin (TSLP), 112 T-LBL, see Precursor T-lymphoblastic lymphoma (T-LBL) T-lymphoblastic leukemia/lymphoma, 66–67, 103, 104t, 164, 185, 241, 243 TMD, see Transient myeloproliferative disorder (TMD) t(2;14)(p16;q32), 265, 265f t(9;22)(q34;q11.2), see Philadelphia chromosome t(14;19)(q32;q13), 262–263, 264f TRAIL, see Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) Transient myeloproliferative disorder (TMD), 110 Translocations involving chromosome 14q32, 266 Transplacental leukemic “metastasis,” 113 Treatment of AML, examples for, 311–312, 312t Treatment of CML, examples for, 313, 313t Treatment of MPN, examples for, 312–313 Trisomy, 48 Trisomy 12, 54t, 67, 73, 258f, 260, 263, 264f, 274 Trisomy 3q27, 261 R TRIzol-LS  ,8 TSLP, see Thymic stromal-derived lymphopoietin (TSLP) Tumor necrosis factor-related apoptosisinducing ligand (TRAIL), 259, 302 Tumor-specific signature, 31 Tumor suppressor genes (TSGs), 195, 198, 258–259, 316, 327 Tyrosine kinase inhibitor therapy, 229–231 Tyrosine kinases, 55, 58, 65, 73, 98, 106–110, 134, 143, 144f, 187, 189, 195, 216–218, 216t, 221, 229–233, 239–245, 272–273, 295, 303, 307–309, 312

358 U Uniparental disomy (UPD), 74–75, 145, 235, 269 UPD, see Uniparental disomy (UPD) V Vacutainer CPT Mononuclear Cell Preparation Tube, 3 Veltuzumab, 301t, 302 W Waldenström’s macroglobulinemia, 182 Walter Flemming, 42 WCP probes, see Whole-chromosome paint (WCP) probes WHO classification (2008), cytogenetic/ molecular tests acute leukemia, 86–89 with no specific cytogenetic findings, 89–90 chronic myeloproliferative disorders, 82–85 diagnosis of hematolymphoid neoplasms, 97 diagnostic workups, process, 80–82 clonal population tests/detection, 81 evaluation of stained smears and tissue sections, 80

Index flow cytometry analysis, 80 immunohistochemical staining procedures, 81 molecular and cytogenetic procedures, see Cytogenetic tests; Molecular tests Hodgkin lymphoma, 97–98 malignant lymphomas, 90–91 ALCL, 95–96 Burkitt lymphoma, 94 diagnostic problems, 91–92 DLBCL, 93–94 FL, 92 MCL, 92 MZL, 93 NK-cell lymphomas, 96–97 PCN, 94–95 T-cell lymphomas, 95 myelodysplastic disorders refractory cytopenia of childhood, 85–86 other hematolymphoid neoplasms, 98 WHO Classification of Tumors of Hematopoietic and Lymphoid Tissues, 41, 80 Whole-chromosome paint (WCP) probes, 52–53 Wilms Tumor 1 (WT1), 145