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Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

IMMUNOLOGY AND IMMUNE SYSTEM DISORDERS

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IMMUNOLOGICAL AND MOLECULAR DIAGNOSIS OF CANCER

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

IMMUNOLOGY AND IMMUNE SYSTEM DISORDERS Additional books in this series can be found on Nova’s website under the Series tab.

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CANCER ETIOLOGY, DIAGNOSIS AND TREATMENTS Additional books in this series can be found on Nova’s website under the Series tab.

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Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

IMMUNOLOGY AND IMMUNE SYSTEM DISORDERS

IMMUNOLOGICAL AND MOLECULAR DIAGNOSIS OF CANCER

MAHER ALBITAR Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

EDITOR

Nova Science Publishers, Inc. New York Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

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Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book.

Library of Congress Cataloging-in-Publication Data Immunological and molecular diagnosis of cancer / editor, Maher Albitar. p. ; cm. Includes bibliographical references and index. ISBN:  (eBook) 1. Cancer--Immunodiagnosis. 2. Cancer--Molecular diagnosis. I. Albitar, Maher. [DNLM: 1. Neoplasms--diagnosis. 2. Immunologic Tests--methods. 3. Molecular Diagnostic Techniques--methods. QZ 241] RC270.3.I45I45 2010 616.99'4061--dc22 2010027267

Published by Nova Science Publishers, Inc. † New York Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Contents

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Preface

vii

Chapter I

General Techniques and Methods

1

A.

Nucleic Acid Methods Maher Albitar and Amber C. Donahue

1

B.

Immunological Methods Amber C. Donahue and Maher Albitar

8

C.

Proteomics in Oncology Cory E. Bystrom and Nigel J. Clarke

Chapter II

Methods for Diagnosis, Prognosis, and Monitoring of Lymphomas Zhong Zhang and Maher Albitar

33

Methods for Diagnosis, Prognosis, and Monitoring of Myeloproliferative Neoplasms Sally S. Agersborg and Maher Albitar

85

Immunological and Molecular Studies in Plasma Cell Neoplasms Mohammad R. Sheikholeslami and Maher Albitar

109

Methods for Diagnosis, Prognosis, and Monitoring of Leukemias Sally S. Agersborg and Maher Albitar

123

Chapter III

Chapter IV

Chapter V

Chapter VI

Immunological and Molecular Studies in Kidney Tumors Sean R. Williamson, Antonio Lopez-Beltran, Shaobo Zhang,Gregory T. MacLennan, Rodolfo Montironi and Liang Cheng

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177

vi Chapter VII

Contents Immunological and Molecular Studies in Tumors of the Urinary Bladder Darrell D. Davidson, Antonio Lopez-Beltran, Sean R. Williamson, Shaobo Zhang, Rodolfo Montironi and Liang Cheng

193

Chapter VIII

Immunological and Molecular Studies in Breast Tumors Lei Huo, Constance Albarracin and Nour Sneige

209

Chapter IX

Immunological and Molecular Studies in Lung Cancer Neda Kalhor and Cesar A. Moran

245

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Index

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271

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

Preface One of the major problems in clinical practice is the diagnosis of cancer and determining how to manage cancer patients. More than any other disease, cancer diagnosis and management at this time depend on broad range of molecular and immunological tests. Diagnosis, determining therapeutic approach, monitoring effects of therapy, and detecting minimal residual disease are all depend on both molecular and immunological methods. However, rarely the two classes of methods are discussed and presented in one book. Our book “The Immunological and Molecular Diagnosis of Cancer” is written specifically to show how both immunological and molecular techniques can be used in cancer diagnosis and management. It bridges between the two technologies. The book is written as a reference encompassing both methodologies and presents general guidance for the diagnosis and management of patients with various types of cancers. It is designed as an educational aid to be used by general practitioners, clinicians and pathologists. The book starts with a chapter describing the general techniques used in molecular testing followed by a second chapter describing techniques used in immunological tests. However, most of the chapters are dedicated to specific types of cancers and present complete description of how immunological and molecular techniques are used in each of these cancers. The book discusses in details the immunological and molecular tests used in these cancers and provides algorithms for using these tests. The specific cancers that are discussed in this book are lymphoma, acute leukemia, chronic leukemia, plasma cell dyscrasia, kidney tumors, urinary bladder tumors, breast tumors, and lung cancers. The book is designed to be used as a day-to-day reference by practicing physicians, specialists, medical students, laboratorians, researchers and educators. It is written by leaders in the field and provides a unique reference. It provides straight-to-the-point, state-of-the-art strategies for diagnosis, determining prognosis, detecting minimal residual disease and predicting relapse. It describes various immunological techniques such as immunohistochemistry, flow cytometry, enzyme-linked immunosorbent assays, and multiplexed immune assays as well as molecular techniques such as real-time quantitative PCR assays, mutation analysis, RNA/DNA microarray and FISH studies. A full section is dedicated to proteomics. The book is designed to help every physician or scientist working with cancer.

Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

In: Immunological and Molecular Diagnosis of Cancer ISBN: 978-1-61728-949-1 Editor: Maher Albitar © 2011 Nova Science Publishers, Inc.

Chapter I

General Techniques and Methods A. Nucleic Acid Methods Maher Albitar and Amber C. Donahue Nichols Institute, Quest Diagnostics, 33608 Ortega Highway San Juan Capistrano, California, USA

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Abstract Diagnosis and classification of cancer is becoming increasingly dependent on elucidation of underlying molecular abnormalities. The development of new therapeutic agents that target specific molecular abnormalities necessitates methods for diagnosis and classification of these specific aberrations. The progress being made in the development of various molecular techniques is also providing discovery tools for better definition of existing diagnoses, and the recognition of new diagnostic entities that were previously indistinguishable from other related diseases. More importantly, the determination of therapeutic approaches and patient monitoring are becoming increasingly dependent on the molecular abnormalities present in the disease, as well as the genetic background of the patient. In this chapter, we will briefly review the nucleic acid techniques used in the testing of patients with various types of cancer.

Introduction The progress that has been made in the decades since the elucidation of the structure of nucleic acid is nothing short of staggering. The dedicated work of thousands of researchers, clinicians, and diagnosticians worldwide has created invaluable schematics for the etiology, diagnosis, progression, and prognosis of a multitude of cancers. These pictures become ever clearer with the advent of new technologies and the resulting influx of new data.

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The tissue expression patterns of known oncogenes and tumor suppressors have been established, and the signaling pathways in which these proteins function are being studied feverishly the world over. Understanding the effect of a mutation on the resulting protein, and understanding the role of that protein in signal transduction in the susceptible cell type are pivotal to the understanding of how to treat that particular malignancy. As molecular techniques have increased in sensitivity, it has become possible to pinpoint the multiple genetic lesions in a tumor. These techniques have further allowed researchers to tease out those mutations that are likely more causative from those which arise later in the progression of cancer, as well as those mutations which confer resistance to targeted therapy. In addition, this sensitivity allows the detection of lesions present in only a fraction of the cells in a heterogeneous tumor. As the picture of each unique malignancy becomes clearer, treatment decisions will be better informed. Oncologists will be able to design combination therapies that will target the dysregulated signaling pathway(s) and more effectively kill malignant cells. The molecular techniques that allow this view into the intricacies of each cancer are described in this chapter.

1. Genomic Profiling

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Genomic profiling is used to characterize specific variations in the genome. It is frequently used to test for variations in somatic cells, especially cancer cells, but it also can be used to test for variations in the germline. The most common types of genomic profiling are:

1.1. Messenger RNA Expression Profiling It is estimated that the human genome contains approximately 35,000 genes. However, following the recent completion of the human genome, it is estimated that only 20,000-25,000 of these genes actually code for proteins. Current microarray technology provides the ability to profile the levels of messenger RNA (mRNA) expression of these genes in various tissues at various physiologic states [1]. In the past two decades, scientists have used this approach extensively to define the molecular pathways involved in the pathophysiology of numerous types of cancers; many landmark discoveries in cancer were originally observed through expression profiling. The two most common platforms used in mRNA expression profiling are microarrays consisting of defined cDNA clones, and synthesized oligonucleotides complementary to specific mRNA sequences. The cDNA clones are spotted onto glass slides, while the oligos can also be spotted, or synthesized directly on the microarray surface [1;2]. The heterogeneous mixture of mRNA transcripts is generally fluorescently labeled, then hybridized to the oligonucleotides or cDNA clones on the surface of the microarray. The signal intensity is proportional to the amount of mRNA bound, and thus to the level of transcription.

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Nucleic Acid Methods

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However, as multiple factors may influence the intensity of binding of a specific mRNA sequence, the technique of dual hybridization using a reference mRNA is frequently used. Dual hybridization is not used with synthesized oligonucleotide platforms, however. mRNA expression profiling has been used extensively as a discovery tool. Recently, an abbreviated form of this profiling involving a limited number of genes was shown to be practical in a clinical laboratory environment.

1.2. MicroRna Expression Profiling

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MicroRNAs (miRNAs) are small noncoding RNAs that regulate the expression of various mRNAs [3]. In most cases, miRNAs act by binding to the 3’ untranslated region and degrading these mRNAs or inhibiting their translation. Microarray technology has been used extensively to conduct genome-wide analyses of miRNA expression in normal and disease samples. The miRNA expression signature of each analyzed disease appears to be specific for that disease. It is believed that this approach can therefore be used for diagnosis, prognosis and therapeutic intervention in various diseases [3]. It is also believed that because miRNAs are small, they are better preserved and might thus be more reliable than mRNA when paraffin-embedded tissue is used as a source of nucleic acids [3]. The current estimate puts the number at approximately 1,000 miRNA genes in the human genome. Therefore, profiling the majority of these miRNAs on a single array is entirely within the realm of possibility. Most of the miRNA array platforms presently in use consist of oligonucleotide probes printed on glass slides. In principle, the assays are performed by converting RNA to cDNA via reverse transcription, and labeling the cDNA with Cy5 dye. Reference DNA oligos complementary to the probes are labeled with Cy3 dye, and the mixture is then hybridized to the probes on the array surface. Signal detection and data analysis is similar to that used for mRNA arrays.

1.3. SNP Arrays Single nucleotide polymorphisms (SNPs) are DNA sequence variations that occur when a single nucleotide is altered in the genome of a subset of individuals. There are more than 12 million documented SNPs in the human genome. Most of these SNPs are not relevant, however. The important SNPs are those that have been shown to be involved in linkage disequilibrium, or in gene regulation and protein expression. When a SNP is linked to an important sequence that is involved in a specific disease state, the SNP is considered to be a “tag” SNP. These tags form the basis for the International HapMap Project, whose goal is to map the causative loci in the human genome [4]. In the case of a non-synonymous SNP, the single base change results in a change in the amino acid sequence of a protein. Although synonymous SNPs do not result in protein sequence changes, these SNPs still may influence RNA stability or promoter activities [5;6]. The important SNPs are estimated to number between 500,000 and 1 million, and are believed to be relevant for phenotype, genetic susceptibility (directly or by association), pharmacogenomics, host response, and disease behavior [7-9].

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A genome-wide association study (GWAS) depends upon the analysis of SNPs, and is used to scan many people to find genetic variations associated with a particular disease [9]. Generally these studies are used to find the genetic contributions to cancer and other common diseases, as well as specific toxicity of or response to therapy. In addition, this approach, when used with the proper controls, can be used to detect genomic deletions, amplifications, and other chromosomal abnormalities.

2.1. Detection of Mutations

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Multiple methods are used to detect mutations in leukemic samples. Sequencing remains the gold standard, and the most accurate approach. However, the sensitivity of direct sequencing is low (5% to 20%) when conventional methods such as Sanger sequencing are used. New sequencer instruments, or so called “next generation” sequencers, hold the promise of high throughput with higher sensitivity, but these instruments remain in the research phase and are not yet adaptable to the clinical laboratory in a cost-effective fashion [10]. However, numerous additional methods are currently used for the detection of mutations, most of which are based on primer-specific hybridization and polymerase chain reaction (PCR) amplification of target sequences in RNA or DNA. Methods based on high performance liquid chromatography (HPLC) are also used for screening, but mutations detected by HPLC, in general, should be confirmed using conventional methods [11]. Mutations that generate a new restriction enzyme site can be efficiently detected with restriction fragment length analysis. When mutations are in the form of deletion or duplication of a segment of DNA, rather than a point mutation, simple amplification and resolution of the amplification product by fragment length analysis or even visualization on an agarose gel can be an adequate approach. Additional promising new approaches that have made their way to the clinical laboratory are described in greater detail below. 2.1.1. Pyrosequencing Pyrosequencing is a sequencing approach based on measurement of the release of pyrophosphate (PPi) by nucleotide incorporation during DNA synthesis [12]. Briefly, a PCRamplified, single-stranded DNA template is hybridized with a specific primer in the presence of DNA polymerase, luciferase, ATP sulfurylase, apyrase, luciferin, and adenosine 5´ phosphosulfate. Deoxynucleotides (dNTPs) are then added one at a time. If the added dNTP is complementary to the template strand, DNA polymerase catalyzes its incorporation into the DNA strand with the release of PPi. Light emission is achieved by converting the released PPi to ATP via ATP sulfurylase, providing energy to oxidize luciferin. The amount of light generated is proportional to the number of incorporated nucleotides. The next dNTP is added after the unincorporated dNTPs are degraded by apyrase, and the process repeats. The most important advantage of pyrosequencing is its potential for quantification. It is also reported to be slightly more sensitive than conventional Sanger sequencing (5% sensitivity), and it may also prove helpful in sequencing DNA with difficult secondary structures [12].

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3. mRNA Quantification Measurement of gene expression levels is now used extensively in clinical laboratories, most often to detect abnormal expression secondary to chromosomal translocations. The quantification methodology used most frequently is quantitative real-time PCR, which is based on determining the rate of release of a dye during the amplification of the target sequence. The most common approaches used with real-time PCR are SYBR Green 1 (or other dyes) and Taqman® probes [13;14]. Numerous questions regarding the standardization and robustness of these real-time PCR methods remain unanswered, and need to be addressed if results from one laboratory are to be compared with results from others [15]. However, this approach remains the most widely used for molecular testing in monitoring patients, especially those with chromosomal translocations.

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4. Methylation Profiling DNA methylation plays an important role in the regulation of expression and imprinting of genes [16;17]. DNA methylation typically occurs in CpG islands, which are usually found in the GC-rich region upstream of a gene’s promoter. Numerous approaches can be used to study DNA methylation, and no single method is appropriate for every application; method selection requires understanding of the type of information needed and the potential for bias and artifacts associated with each approach. Bisulfite modification of DNA is the foundation for the majority of assays geared toward clinical testing [18-20]. The differences in bisulfitebased methylation assays arise from the manner in which bisulfite-modified DNA is analyzed. Bisulfite modification converts non-methylated cytosines to uracils, which are then converted to thymines during DNA amplification by PCR, whereas methylated cytosines are protected from bisulfite modification [20]. DNA sequencing and the use of methylationsensitive primers are the two most commonly used techniques to analyze bisulfite-treated DNA. The extension of an oligonucleotide to the 5' end of a CpG site using dideoxycytidine (ddCTP) or dideoxythymidine (ddTTP), followed by real-time PCR, allows for a quantitative assessment of methylation patterns and can be applied to multiple sites simultaneously [18]. Digesting the DNA with methylation-sensitive restriction enzymes and analyzing the digestion products by PCR or Southern blot remains a viable and reliable approach as well, but is less commonly used due to its relative complexity [19]. The current next-generation sequencers allow for high-throughput genome-wide methylation analysis [21]. Measuring levels of methylation in a particular tissue or plasma is increasingly used for the diagnosis and prediction of prognosis in various tumor types, including leukemias, and will likely become ever more widespread in the near future [22].

5. Fluorescence In Situ Hybridization (FISH) Although conventional karyotyping analysis has been very helpful in understanding the involvement of large genome changes in cancer, karyotyping has very limited resolution and small abnormalities can be easily missed. The FISH technique was introduced to increase the

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resolution of conventional karyotyping [23]. FISH uses a fluorescently labeled DNA fragment containing the genomic locus of interest to probe either chromosomal preparations (metaphase FISH), or nuclei (interphase FISH), for detection with a fluorescent microscope. This allows the detection of amplifications, deletions (monosomy), and trisomy. Using two probes with different labels also allows the detection of chromosomal translocations. Currently, immunohistochemical staining using antibodies directed against the dye in the probe is being used along with light microscopy for FISH studies, rather than fluorescent microscopes. This makes it possible to combine morphological evaluation with genomic evaluation.

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6. Comparative Genomic Hybridization (CGH) Although FISH has added increased resolution as compared to classical cytogenetics for the evaluation of genomic abnormalities, FISH is not amenable for use as a screening tool for large numbers of abnormalities. Spectral karyotyping allows the painting of each chromosome with labeled probes, and the evaluation of each chromosome is very helpful [24]. However, spectral karyotyping requires cells to be in metaphase, and the capture of cells in metaphase is difficult, particularly in solid tumors. In contrast, CGH provides better resolution than the FISH approach, allows the screening of the entire genome, and uses extracted DNA without the need for intact cells [25]. Several modifications exist for the technique, but the most common approach makes use of an array that contains genomic probes that can be chosen to cover as much as possible of the genome, in sizes up to one megabase (Mb). The DNA to be tested is labeled with a specific fluorescent dye, and hybridized to an equal amount of normal DNA that has been labeled with a dye of a different color. The mixture of labeled nomal and test DNAs is then hybridized to the probes on the slide. Probes on the slide could be either oligonucleotides or large DNA fragments from genomic clones generated by bacterial artificial chromosomes (BACs). Other approaches make use of normal cells in metaphase, which are dropped on glass slides in order to use the normal chromosomes as probes. CGH generates very large amounts of data, whose uses in diagnostics are still being explored [25].

Conclusion In this chapter we hope to have provided an overview of the predominant techniques and assays currently in use for the characterization of molecular abnormalities in cancer. Molecular oncology is a constantly growing field, and new and improved technologies continue to add to the arsenal at the diagnostician’s disposal. Researchers are constantly gathering more information about the signaling pathways involved in the etiology and progression of various malignancies, and every day we come to understand more about the genetic factors that predispose certain patients to cancer. Armed with ever more knowledge about each patient and each tumor, oncologists are truly coming to know the enemy, and defeat it.

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References [1] [2] [3] [4] [5]

[6]

[7] [8] [9] [10]

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[11]

[12] [13] [14] [15]

[16] [17] [18] [19]

Cowell JK, Hawthorn L. The application of microarray technology to the analysis of the cancer genome. Curr. Mol. Med. 2007;7(1):103-120. Gao X, Gulari E, Zhou X. In situ synthesis of oligonucleotide microarrays. Biopolymers 2004;73(5):579-596. Cho WC. MicroRNAs: potential biomarkers for cancer diagnosis, prognosis and targets for therapy. Int. J. Biochem. Cell Biol 2009. Manolio TA, Brooks LD, Collins FS. A HapMap harvest of insights into the genetics of common disease. J. Clin. Invest 2008;118(5):1590-1605. Duan J, Wainwright MS, Comeron JM, Saitou N, Sanders AR, Gelernter J, et al. Synonymous mutations in the human dopamine receptor D2 (DRD2) affect mRNA stability and synthesis of the receptor. Hum. Mol. Genet 2003;12(3):205-216. Wang D, Johnson AD, Papp AC, Kroetz DL, Sadee W. Multidrug resistance polypeptide 1 (MDR1, ABCB1) variant 3435C>T affects mRNA stability. Pharmacogenet Genomics 2005;15(10):693-704. Abraham J, Earl HM, Pharoah PD, Caldas C. Pharmacogenetics of cancer chemotherapy. Biochim. Biophys. Acta 2006;1766(2):168-183. Imyanitov EN. Gene polymorphisms, apoptotic capacity and cancer risk. Hum. Genet. 2009;125(3):239-246. Savas S, Liu G. Genetic variations as cancer prognostic markers: review and update. Hum. Mutat. 2009;30(10):1369-1377. Voelkerding KV, Dames SA, Durtschi JD. Next-generation sequencing: from basic research to diagnostics. Clin Chem 2009;55(4):641-658. Yu B, Sawyer NA, Chiu C, Oefner PJ, Underhill PA. DNA mutation detection using denaturing high-performance liquid chromatography (DHPLC). Curr. Protoc. Hum. Genet 2006;Chapter 7:Unit7. King C, Scott-Horton T. Pyrosequencing: a simple method for accurate genotyping. J. Vis. Exp. 2008;(11). Kaltenboeck B, Wang C. Advances in real-time PCR: application to clinical laboratory diagnostics. Adv. Clin. Chem. 2005;40:219-259. Lutfalla G, Uze G. Performing quantitative reverse-transcribed polymerase chain reaction experiments. Methods Enzymol. 2006;410:386-400. Zhang T, Grenier S, Nwachukwu B, Wei C, Lipton JH, Kamel-Reid S. Inter-laboratory comparison of chronic myeloid leukemia minimal residual disease monitoring: summary and recommendations. J. Mol. Diagn. 2007;9(4):421-430. Ciccone DN, Chen T. Histone lysine methylation in genomic imprinting. Epigenetics 2009;4(4):216-220. Vucic EA, Brown CJ, Lam WL. Epigenetics of cancer progression. Pharmacogenomics 2008;9(2):215-234. Derks S, Lentjes MH, Hellebrekers DM, de Bruine AP, Herman JG, van EM. Methylation-specific PCR unraveled. Cell Oncol. 2004;26(5-6):291-299. Hashimoto K, Kokubun S, Itoi E, Roach HI. Improved quantification of DNA methylation using methylation-sensitive restriction enzymes and real-time PCR. Epigenetics 2007;2(2):86-91.

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[20] Sulewska A, Niklinska W, Kozlowski M, Minarowski L, Naumnik W, Niklinski J, et al. Detection of DNA methylation in eucaryotic cells. Folia Histochem Cytobiol 2007;45(4):315-324. [21] Ansorge WJ. Next-generation DNA sequencing techniques. N. Biotechnol. 2009;25(4):195-203. [22] Garcia-Manero G, Yang H, Kuang SQ, O'Brien S, Thomas D, Kantarjian H. Epigenetics of acute lymphocytic leukemia. Semin Hematol 2009;46(1):24-32. [23] Volpi EV, Bridger JM. FISH glossary: an overview of the fluorescence in situ hybridization technique. Biotechniques 2008;45(4):385-6, 388, 390. [24] Bayani J, Squire J. Multi-color FISH techniques. Curr. Protoc. Cell Biol. 2004;Chapter 22:Unit. [25] Shinawi M, Cheung SW. The array CGH and its clinical applications. Drug Discov. Today 2008;13(17-18):760-770.

B. Immunological Methods Amber C. Donahue and Maher Albitar Department of Hematopathology, Quest Diagnostics-Nichols Institute 33608 Ortega Highway, San Juan Capistrano, California, USA

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Abstract Most of the immunological methods used in the diagnosis, grading and prediction of clinical behavior in cancer are based on the use of antibodies. The platforms that rely on antibodies are numerous, and include enzyme-linked immunosorbent assays (ELISA), flow cytometry, radioimmunoassays (RIA), immunohistochemistry and immunocytochemistry (IHC/ICC), and antibody arrays. However, proteomics and the use of mass spectrometry have added a new dimension to protein analysis. Here we will give an overview of the immunological methods used in testing patients with cancer; the proteomic approach will be discussed in an independent section. These techniques provide valuable information about the myriad proteins that have been found to be involved in the etiology or progression of cancer, including but not limited to expression levels, post-translational modifications, and subcellular localization.

Introduction If understanding the abnormalities that make a cancer cell malignant is half the battle, then immunological methods of studying these abnormal cells and proteins have contributed heavily to the victories won in the field of oncology. Historically, millions of immunoblots were largely responsible for the explication of the signaling pathways affected by known oncogenes and tumor suppressors. Until relatively recently, moreover, immunological

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Immunological Method

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methods represented the most widely accepted way to study post-translational modifications such as phosphorylation and ubiquitination, which provide information about a protein’s activation status or targeting for degradation. Most basic and in some ways most crucial, these methods also provide information about the actual expression levels and turnover of important proteins; this information does not always correlate with molecular data such as mRNA expression levels. Although some of the techniques described in this chapter are older, and in some cases, have fallen out of common use, they are nonetheless powerful tools in oncology research. Recent advances in other methods have kept them current, and made them indispensable in the fields of cancer diagnostics and therapeutics research. One such technology is flow cytometry, whose ability to measure a large number of parameters for each cell analyzed is a boon to hematopathologists in particular. Another is the antibody array, allowing the screening of a large number of analytes in cell lysate, which provides valuable information to researchers studying the effects of targeted therapies on malignant cells, for instance. A good grasp of the immunological techniques described in this chapter is important for understanding a great number of the diagnostic and prognostic tests used in the characterization of cancer today.

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1. Immunoprecipitation Immunoprecipitation (IP) involves the incubation of cell lysate or bodily fluid with antibody specific for the target [1]. Following capture of the target protein by the specific antibody, the antibody is bound by bacterial Protein A, Protein G, or a combination of both that has been coated onto beads. These beads can then be spun out of solution and the supernatant removed or transferred to another tube. The protein of interest, which has been greatly concentrated through binding to the beads and should be the only protein remaining, can then be visualized via immunoblotting. For some assays, a large volume of bodily fluid is required, owing to a low concentration of the protein of interest. In this case, it is possible to use IP to concentrate the target prior to detection with the assay platform of choice. The technique is extremely valuable and used extensively in the discovery stage, although it is only rarely used in clinical testing.

2. Immunoblotting Immunoblotting (IB) or Western blotting does not always require the use of IP, and is frequently used to analyze a specific protein in cell lysates or other matrices. Following heat denaturation and incubation with SDS, the proteins in a sample are separated by mass via polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to a nitrocellulose or polyvinylidene flouride (PVDF) membrane for detection. The membrane is incubated with specific primary antibody, followed by enzyme-conjugated secondary anti-species antibody. A chemiluminescent substrate is then added, generating a band of light at the site of the target protein which was traditionally detected by exposure to autoradiography film. Camera-based documentation systems are also becoming increasingly popular for the detection and

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quantitation of IB bands. Despite being an older technique, immunoblotting provides an opportunity to physically view the interactions of an antibody with the proteins in a sample, and thus remains a gold standard for the analysis of an antibody’s specificity and off-target interactions. For this reason, IB remains a valuable tool for the validation of antibodies to be used in other assay types, despite being relatively rare as a clinical test in its own right.

3. Radioimmunoassays The radioimmunoassay (RIA) was one of the first highly sensitive methods for measuring the levels of proteins like hormones in the blood (e.g. [2]). The RIA is a classic competition assay in which a known quantity of purified target protein is radiolabeled, generally with a gamma radioisotope of iodine. This “hot” protein is mixed with an immobilized specific antibody, and then with the biological sample containing the unlabeled “cold” target protein. The radiolabeled and cold proteins will compete for binding to the antibody, and the displaced radioactivity can be measured, giving an indirect measure of the amount of the target protein present in the sample. Although assays that do not require radioactivity are generally preferred, the development of the RIA allowed some of the first sensitive and specific measures of important hormones like insulin in human blood [3]. Although some clinical laboratories still perform RIAs, the technique has largely been replaced by enzymatic immunoassays.

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4. Enzymatic Immunoassays Enzyme immunoassays (EIA) are the classic antibody-based high-throughput tests used in clinical laboratories [4]. The most common of these, the enzyme-linked immunosorbent assay (ELISA) [5], has been used to detect relevant biological information in cell lysates and in nearly all bodily fluids, including whole blood, bone marrow aspirates, serum, plasma, cerebrospinal fluid, urine, and more. The assay is generally performed in microtiter plates of 96 or more wells, and the often identical treatment of each well and the availability of robotic systems and automated plate washers make the ELISA an excellent platform for highthroughput testing of patient samples, as well as making possible a high level of standardization from batch to batch. Further, the assay design is amenable to several reporter types, giving clinical laboratories a great deal of flexibility with respect to the desired type of signal read-out. ELISA designs can vary greatly [5]. The simplest ELISA assays detect target protein adsorbed to the surface of the well, and thus require only a single reporter-conjugated primary antibody. The more common “sandwich” ELISAs can utilize from two to four antibodies. Researchers often prefer this format for the greater level of specificity afforded by using two target-specific antibodies to first capture and then detect the target protein. The capture antibody is bound to the plate, either directly, or through interaction with a corresponding anti-species antibody which is bound to the plate instead. Target protein is bound by the capture antibody, irrelevant proteins are washed away, and the target is then bound by the detection antibody. This detection antibody can be conjugated to a reporter, or can be detected

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itself by a secondary reporter-conjugated anti-species antibody. The major caveat of sandwich ELISAs is the requirement that, if using a secondary anti-species antibody for detection, the capture and detection antibodies must be derived from different species to prevent binding of the secondary antibody to both. Finding two antibodies of sufficient affinity and specificity for diagnostic assays is a constant challenge in the development of clinical tests. The detection of specialized protein motifs is made possible by the versatility of the sandwich ELISA. These specialized motifs include different isoforms created by alternative splicing (eg. [6]), as well as post-translational modifications like phosphorylation, acetylation, glycosylation, methylation, ubiquitination, S-nitrosation, and even cleavage of the protein [611]. The activation status of specific pathways or the turnover rate of important proteins can be inferred from these modifications, which can reveal a great deal about the signaling occurring in cells. The target protein is bound by the capture antibody, and the posttranslational change in the target, if present, can then be revealed by a detection antibody specific for the modification of interest. The strategy can also be reversed, for example to determine whether a protein of interest is among those captured by a primary antibody directed against total phosphotyrosine. Fusion proteins like BCR-Abl, one of the causative agents in chronic myeloid leukemia (CML), can also be detected in this way. For example, an anti-BCR capture antibody should immobilize both the wildtype (WT) and fused version of BCR, while the anti-Abl detection antibody would reveal only those captured proteins which also contain the Abl epitope for which the antibody is specific. This versatility of sandwich ELISAs is augmented by the increasing availability of multiplexing technologies, as well as the use of electrochemiluminescent (ECL) substrates and advanced detection systems. The enzyme-linked immunosorbent spot assay (ELISpot) is a variation on the ELISA platform which allows the detection and enumeration of single cells secreting specific proteins [12]. Monoclonal or polyclonal antibodies specific for the secreted protein of interest are coated onto membrane-backed wells. Targets can include cytokines and antigen-specific immunoglobulin [13;14]. Cells are then added to the wells and stimulated to produce the target proteins. Proteins of interest are captured in the immediate vicinity of that cell by the immobilized antibodies as they are secreted, effectively marking the location of the active cell. Following the prescribed incubation period, the wells are washed to remove the cells and any debris, and the wells are incubated with a second specific antibody, making the ELISpot assay a sandwich assay. The detection antibody is generally directly conjugated to biotin, or bound by a biotin-conjugated secondary antibody. The wells are then incubated with streptavidin-conjugated horseradish peroxidase (HRP) followed by 3-amino-9-ethylcarbazole (AEC), or streptavidin-ALP followed by 5-bromo-4chloro-3-indolyl phosphate and nitro blue tetrazolium chloride (BCIP/NBT). These substrates yield colored precipitates on the membrane, providing a blue/black spot for quantitation. ELISpot protocols have also begun to make use of fluorescent reporters as well. The ELISpot assay provides valuable information, in that it allows quantification of the number of cells responding to the stimulus. The assay requires fewer cells per well than other assays designed to gather similar information, which is a boon for diagnosticians assaying precious sample types. The assay is also very valuable for the detection of rare cell populations like antigenspecific T cells, down to about 1 in 100,000 cells, which is made possible by the immediate capture of the secreted protein in the vicinity of the activated cell before the protein is diluted,

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degraded, or bound by other cells. Advances in detection systems and software developments allow the counting of multiple reporter types through the use of light filters and automated counting of the plates, greatly increasing throughput. A growing number of secreted proteins are being assayed in this manner in clinical laboratories.

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5. Immunocytochemical and Immunohistochemical Assays Pathologists use the related techniques of immunohistochemistry (IHC) and immunocytochemistry (ICC) to identify specific cells or to examine the subcellular localization of important proteins like tumor markers, as well as markers of proliferation and apoptosis [15;16]. Suspension cells or cells taken from a smear (ICC), or intact tissue sections (IHC), are incubated with specific primary antibodies which, as in ELISAs, can be directly conjugated to a reporter or detected with a reporter-conjugated secondary anti-species antibody. These techniques make use of both enzymatic and fluorescent reporters. Pathologists often also include other standard dyes or antibodies that label specific cellular structures, such as the nucleus. The samples are examined using advanced microscopy and computer-based image analysis systems. The value of IHC/ICC for diagnostics lies in the ability to determine both whether a protein is expressed in the cells being examined, as well as the subcellular location of the protein. Some proteins are regulated wholly or in part by localization. For example, many transcription factors are rendered inactive by sequestration in the cytoplasm, and become active following translocation to the nucleus. Genetic lesions that give rise to malignancies can include mutations which lead to improper localization of important proteins. Antibodies directed against these proteins, as well as antibodies specific for different isoforms, posttranslational modifications, and mutant proteins, are extremely valuable as diagnostic and prognostic tools for pathologists.

6. Flow Cytometry The considerable versatility of immuno-based approaches is perhaps best demonstrated in flow cytometry [17]. Antibodies can be conjugated to a wide array of reporter fluorophores, which absorb the energy of laser light and then emit the energy at a different specific wavelength. Multiple lasers and an intricate series of filters currently allow the most advanced cytometers to record up to 11 parameters simultaneously for each cell that passes through the instrument. A staggering number of analyte combinations can be examined for each cell, due in part to the further adaptability provided by biotin-conjugated antibodies and streptavidinconjugated fluorophores. Flow cytometry was originally a cell-based platform designed to measure the expression levels of proteins expressed on the cell surface. The ability to examine multiple surface markers simultaneously on intact cells allows diagnosticians to find and enumerate populations of abnormal cells, most notably for circulating hematological malignancies of the

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peripheral blood and bone marrow. Flow cytometry has expanded in recent years, however, to include the analysis of intracellular and soluble proteins, as well as cellular DNA content. Although ELISAs and immunoblotting are powerful techniques for the elucidation of events occurring inside the cell, both actually provide what could be considered an average measure. Unless highly purified, cell preparations are a heterogeneous mix of different cell types, which may express differential levels of proteins of interest. Further, cell types present in greater numbers tend to mask the response of less numerous subsets. Even cells within highly purified populations may express slightly different levels of a given protein, or respond heterogeneously to a specific stimulus. The ability to combine lineage-defining surface staining with intracellular staining of fixed and permeabilized cells is therefore an invaluable tool. The technique makes possible the analysis of intracellular events side by side in mixed populations of cells, without the need for purification or enrichment of specific cell subsets [18-23]. This intracellular staining has made possible the analysis of expression and posttranslational modification of proteins, and even the elucidation of signal transduction networks in single cells [24]. This ability is a windfall for researchers and diagnosticians attempting to study the effect of a specific treatment on the signaling pathway targeted by the drug. To facilitate the analysis of mixed samples, for example two different patients or a single patient pre- and post-treatment, Krutzik and Nolan also developed a cell-based “barcoding” method. Each sample is first incubated with a different fluorescent signature that emits light at a discrete wavelength [25]. The samples are then mixed together for standard surface and intracellular antibody staining, and the samples can be differentiated during acquisition and analysis by the barcode signature. The ability to enumerate cell types and observe intracellular events on a cell by cell basis is of enormous importance, and is already providing excellent insights to diagnosticians.

7. Bead-Based Assays Historically, the ability to detect soluble proteins in cell culture supernatant and body fluids was also the province of immunoblots and ELISAs. However, recent advances in flow cytometry allow detection of soluble protein, including intracellular proteins released into the blood by dying leukemia cells. These techniques include microbead technologies that are similar to the sandwich ELISA in design [26-28]. Capture antibody is coated onto beads rather than a plate, the beads are incubated with the body fluid or supernatant, and the captured protein is then bound by the specific detection antibody. Although fewer antibodies are generally preferred, bead assays can make use of two to four antibodies, like a sandwich ELISA. In addition to the simple detection of whole protein in solution, bead-based assays can also be used to detect post-translational modifications and the mutant proteins resulting from chromosomal translocations. The multiplexing opportunities for bead-based assays are slightly different, however, and include the Luminex and cytometric bead array technologies. Although the most advanced cytometers can measure up to 11 parameters, even softwareaided calibration is often difficult as the number of parameters increases. As an alternative to using multiple fluorophores for the measurement of soluble proteins, one multiplexing option for flow cytometry is to assay several analytes using the same fluorophore. In this assay,

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known as a cytometric bead array (CBA), each capture antibody is conjugated to beads of a different size [29]. Multiple bead sizes are recognized as discrete populations, due to the fact that one of the parameters measured by cytometers is the size of the particle passing the detector. Each analyte can thus be easily distinguished from the others, and like multispot ELISAs, this approach allows the measurement of several analytes side by side in the same sample. In an improvement over the ELISA, however, recent advances in flow cytometry now also allow quantitation of the number of antibody molecules bound to a bead. With each experiment, a tube containing four groups of beads with increasing levels of bound reporter fluorophore is run, creating a standard curve relating the mean fluorescence intensity (MFI) of the fluorophore recorded by the instrument, or signal, to the known number of fluorophore molecules bound to the standard. Using this curve, the number of reporter-conjugated secondary antibodies bound to the bead in an experimental sample can then be extrapolated from the MFI of the sample. This quantitation of the number of bound antibodies can also be applied to the antibodies bound to proteins on the surface of intact cells as well as intracellular proteins in fixed and permeabilized cells [30]. Luminex technology has created a methodology purportedly capable of analyzing up to 100 analytes simultaneously in a single well through a unique combination of the principles of flow cytometry and microbead assays, (see Luminex Corporation for examples of this technology). Polystyrene microspheres are color-coded using titrations of red and infrared dyes, with each analyte being assigned a unique color signature. These beads are then coated with the appropriate capture antibodies and combined in a single well, where they are incubated with cell lysate or biological fluids. This is followed by a detection antibody in another sandwich-style assay. The beads are then analyzed in a manner based on the principles of flow cytometry, in which the internal dyes are excited by a red laser to reveal the color code of the bead, thus identifying what target should be captured by the antibody coated onto that bead [31]. Any reporter that is bound through recognition of the target protein by the detection antibody is excited by a green laser and recorded as well, allowing measurement of the protein captured. This technology holds the potential to provide nearly as much information about a sample as some forms of antibody microarrays or multi-spot ELISAs.

8. Antibody Microarrays Like its older cousin the DNA microarray, the antibody microarray allows the detection of a very large number of analytes in a mixed sample [32;33]. Albeit on a larger scale, in many ways most antibody microarray formats are similar to the ELISA. Antibody arrays are thought to be nearly invaluable as diagnostic and prognostic tools for cancer due to the wealth of information that can be collected from a small volume of sample. More importantly, the patterns within this information can be characterized and relationships between proteins can be analyzed from this format. There are multiple designs in use for antibody microarrays, but the first consideration in choosing a protocol is determining whether it will be protein or antibody bound to the array. The earliest antibody arrays mimicked DNA arrays, with the monoclonal antibody probes spotted onto the surface of the array, followed by incubation with labeled proteins for

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detection [32]. In some cases the proteins are directly labeled with reporters, and in others, with biotin or digoxigenin for indirect detection. Two samples, for instance pre- and posttreatment samples, or tumor and adjacent normal tissue, can also be directly compared by labeling each with a different reporter, and incubating them together in a competition assay. This design is generally referred to as a direct antibody array, and is the most amenable to truly large numbers of analytes, being limited primarily by the availability of specific antibodies and space. Most commercially available arrays offer targets numbering in the hundreds. Major concerns with direct arrays are limited sensitivity and specificity, background levels, and the possibility that direct conjugation of the protein with a reporter or indirect label may somehow mask the epitope, interfering with the ability of the antibody to recognize the protein. Other versions of the antibody microarray include both capture and detection antibodies, truly becoming sandwich ELISAs on a grand scale [34]. The specificity and sensitivity of the assay are greatly increased by the use of two specific antibodies for protein detection, and background problems are also reduced. Moreover, the possible interference of the label with the antibody-target interaction is avoided, as this method does not require the direct labeling of proteins. The sandwich antibody microarray does have one limiting factor, however, which is the sometimes inadequate availability of good matched antibody pairs. Concern about cross-reactivity among detection antibodies also limits the number of targets in sandwich microarrays as compared to direct arrays, creating another caveat. Despite the smaller number of possible targets allowed by the sandwich method, highly customized arrays are becoming extremely valuable for diagnostic, prognostic, and research purposes. For example, arrays are designed to study particular groups of targets known to be breast cancer markers, or for screening the effects of drug candidates on their target cells. The reverse-phase antibody microarray represents a contrast to the designs described above, beginning with the immobilization of a complex mixture of sample proteins on the array surface rather than antibodies [34]. Specific antibodies are then used to probe these protein spots. Reverse-phase arrays allow multiple samples to be spotted on a single array, providing side by side analysis. The method also makes analysis of insoluble proteins easier. However, non-specific interactions are a concern for this assay design as well, and restricted reporter multiplexing options limit the number of antibodies that can be used on a given array. Despite these limitations, reverse-phase antibody microarrays also provide a wealth of useful information for clinicians.

9. Multiplexing IHC/ICC Advances have been made in automation and higher throughput solutions for IHC/ICC in recent years. Tissue arrays, which allow multiple patients’ samples to be placed on a single slide, greatly increase the speed and uniformity of preparations. In addition, new automation systems and sophisticated software reduce the amount of time spent screening slides and thus improve throughput.

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Conclusion In the face of some of the recent spectacular advances in molecular technologies, some immunological techniques may begin to seem outmoded. However, immunological methods remain a crucial part of the diagnostician’s arsenal, not least because molecular information does not provide the entire picture. For example, it has long been established that mRNA expression levels, while extremely valuable in many ways, do not necessarily reflect the amount of protein that is actually translated. Nor can molecular assays provide information about the rate of protein turnover in the cell, or even about the post-translational modifications or cellular localization of the protein that indicate that the protein has been activated or targeted for degradation. The ability to study a protein of interest directly, whether it be expression of a gene fusion product or reduced activation of the target of a new therapy, is a fundamental part of knowing as much about the malignancy as possible. And the field of immunological detection methods is not without its own technological advances, as described above. For these reasons, immunological assays play a pivotal role in the diagnosis of cancer.

References

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[1]

Bonifacino JS, Dell'Angelica EC, Springer TA. Immunoprecipitation. Curr. Protoc Immunol 2001;Chapter 8:Unit. [2] Zamrazilova L, Kazihnitkova H, Lapcik O, Hill M, Hampl R. A novel radioimmunoassay of 16alpha-hydroxy-dehydroepiandrosterone and its physiological levels. J Steroid Biochem Mol Biol 2007;104(3-5):130-135. [3] Yalow RS, Berson SA. Immunoassay of endogenous plasma insulin in man. J. Clin. Invest 1960;39:1157-1175. [4] Porstmann T, Kiessig ST. Enzyme immunoassay techniques. An overview. J. Immunol. Methods 1992;150(1-2):5-21. [5] Hornbeck P. Enzyme-linked immunosorbent assays. Curr. Protoc. Immunol 2001;Chapter 2:Unit. [6] Bulanova E, Budagian V, Duitman E, Orinska Z, Krause H, Ruckert R, et al. Soluble Interleukin IL-15Ralpha is generated by alternative splicing or proteolytic cleavage and forms functional complexes with IL-15. J. Biol. Chem. 2007;282(18):13167-13179. [7] Kocinsky HS, Girardi AC, Biemesderfer D, Nguyen T, Mentone S, Orlowski J, et al. Use of phospho-specific antibodies to determine the phosphorylation of endogenous Na+/H+ exchanger NHE3 at PKA consensus sites. Am. J. Physiol. Renal. Physiol. 2005;289(2):F249-F258. [8] Liang Z, Wong RP, Li LH, Jiang H, Xiao H, Li G. Development of pan-specific antibody against trimethyllysine for protein research. Proteome Sci. 2008;6:2. [9] Spoettl T, Hausmann M, Klebl F, Dirmeier A, Klump B, Hoffmann J, et al. Serum soluble TNF receptor I and II levels correlate with disease activity in IBD patients. Inflamm. Bowel. Dis. 2007;13(6):727-732. [10] Sumbayev VV, Yasinska IM. Protein S-nitrosation in signal transduction: assays for specific qualitative and quantitative analysis. Methods Enzymol 2008;440:209-219.

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[11] Takada K, Nasu H, Hibi N, Tsukada Y, Ohkawa K, Fujimuro M, et al. Immunoassay for the quantification of intracellular multi-ubiquitin chains. Eur. J. Biochem. 1995;233(1):42-47. [12] Czerkinsky CC, Nilsson LA, Nygren H, Ouchterlony O, Tarkowski A. A solid-phase enzyme-linked immunospot (ELISPOT) assay for enumeration of specific antibodysecreting cells. J. Immunol. Methods 1983;65(1-2):109-121. [13] Klinman DM, Nutman TB. ELISPOT assay to detect cytokine-secreting murine and human cells. Curr. Protoc. Immunol. 2001;Chapter 6:Unit. [14] Lycke NY, Coico R. Measurement of immunoglobulin synthesis using the ELISPOT assay. Curr Protoc Immunol 2001;Chapter 7:Unit. [15] Hofman F. Immunohistochemistry. Curr. Protoc. Immunol 2002;Chapter 21:Unit. [16] Polak JM, Van Noorden S. Introduction to Immunocytochemistry. 2002. Oxford, BIOS Scientific Publishers, Ltd. Ref Type: Generic. [17] Sharrow SO. Overview of flow cytometry. Curr. Protoc. Immunol. 2002;Chapter 5:Unit. [18] Darzynkiewicz Z, Huang X. Analysis of cellular DNA content by flow cytometry. Curr Protoc Immunol 2004;Chapter 5:Unit. [19] Donahue AC, Fruman DA. Distinct signaling mechanisms activate the target of rapamycin in response to different B-cell stimuli. Eur. J. Immunol. 2007;37(10):29232936. [20] Donahue AC, Kharas MG, Fruman DA. Measuring phosphorylated Akt and other phosphoinositide 3-kinase-regulated phosphoproteins in primary lymphocytes. Methods Enzymol 2007;434:131-154. [21] Foster B, Prussin C, Liu F, Whitmire JK, Whitton JL. Detection of intracellular cytokines by flow cytometry. Curr. Protoc. Immunol. 2007;Chapter 6:Unit. [22] June CH, Moore JS. Measurement of intracellular ions by flow cytometry. Curr. Protoc. Immunol 2004;Chapter 5:Unit. [23] Schulz KR, Danna EA, Krutzik PO, Nolan GP. Single-cell phospho-protein analysis by flow cytometry. Curr Protoc Immunol 2007;Chapter 8:Unit. [24] Irish JM, Czerwinski DK, Nolan GP, Levy R. Kinetics of B cell receptor signaling in human B cell subsets mapped by phosphospecific flow cytometry. J. Immunol. 2006;177(3):1581-1589. [25] Krutzik PO, Nolan GP. Fluorescent cell barcoding in flow cytometry allows highthroughput drug screening and signaling profiling. Nat. Methods 2006;3(5):361-368. [26] Jilani I, Kantarjian H, Faraji H, Gorre M, Cortes J, Ottmann O, et al. An immunological method for the detection of BCR-ABL fusion protein and monitoring its activation. Leuk Res 2008;32(6):936-943. [27] Jilani I, Kantarjian H, Gorre M, Cortes J, Ottmann O, Bhalla K, et al. Phosphorylation levels of BCR-ABL, CrkL, AKT and STAT5 in imatinib-resistant chronic myeloid leukemia cells implicate alternative pathway usage as a survival strategy. Leuk. Res. 2008;32(4):643-649. [28] Kellar KL, Douglass JP. Multiplexed microsphere-based flow cytometric immunoassays for human cytokines. J. Immunol. Methods 2003;279(1-2):277-285. [29] Morgan E, Varro R, Sepulveda H, Ember JA, Apgar J, Wilson J, et al. Cytometric bead array: a multiplexed assay platform with applications in various areas of biology. Clin Immunol 2004;110(3):252-266.

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[30] Pannu KK, Joe ET, Iyer SB. Performance evaluation of QuantiBRITE phycoerythrin beads. Cytometry 2001;45(4):250-258. [31] Gu AD, Xie YB, Mo HY, Jia WH, Li MY, Li M, et al. Antibodies against Epstein-Barr virus gp78 antigen: a novel marker for serological diagnosis of nasopharyngeal carcinoma detected by xMAP technology. J. Gen. Virol. 2008;89(Pt 5):1152-1158. [32] Borrebaeck CA, Wingren C. High-throughput proteomics using antibody microarrays: an update. Expert Rev. Mol. Diagn. 2007;7(5):673-686. [33] Haab BB. Antibody arrays in cancer research. Mol. Cell Proteomics 2005;4(4):377-383. [34] Jaras K, Ressine A, Nilsson E, Malm J, Marko-Varga G, Lilja H, et al. Reverse-phase versus sandwich antibody microarray, technical comparison from a clinical perspective. Anal. Chem. 2007;79(15):5817-5825.

C. Proteomics in Oncology Cory E. Bystrom and Nigel J. Clarke Quest Diagnostics-Nichols Institute 33608 Ortega Highway, San Juan Capistrano, California, USA

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Abstract Biological mass spectrometry is a key supporting technology for oncology researchers from the bench to the bedside and its use has grown dramatically over the past 25 years. Technological innovations in instrument performance and sample introduction methodology allowed mass spectrometry to play an important role in both qualitative and quantitative measurements of both small and large molecules. The impact of these developments accelerated the growth of proteomics for basic molecular research as well as translational applications like biomarker identification. In this chapter we introduce the basic elements of preanalytical sample preparation, instrumentation, data interrogation and general workflows to provide an introduction to proteomics for the oncology researcher.

Introduction For nearly 100 years, mass spectrometry has been a fundamental tool for the analysis of chemical structure and reactivity. Manipulation and measurement of gas phase ions which enabled detailed analysis of atomic structure of single atoms in 1920 is now being used to explore the depths of the proteome. Mass spectrometry, informatics, protein chemistry, and biology have coalesced into an interdisciplinary field now known as proteomics – the large scale study of proteins and their associated structure and function. This introduction is intended to help investigators understand the basic principles and technical approaches that underlie mass spectrometry based proteomics. Although the term “proteomics” has grown to cover many protein centric technologies, the focus here is on those that utilize mass spectrometry as the penultimate analytical tool.

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The word "proteome" is a combination of the words "protein" and "genome" and was coined by Marc Wilkins in 1994 in the symposium: "2D Electrophoresis: from protein maps to genomes" and subsequently published in 1995 [1]. Wilkins used it to describe the entire complement of proteins expressed by a genome, cell, tissue or organism and “proteomics” refers to the holistic measurement of these proteins. To the extent that cancer can be characterized as a product of aberrant biochemical processes driven by changes in protein structure and function, the promise and utility of proteomics are of particular interest to the research oncologist. From basic to applied research, the growth of mass spectrometry based approaches for proteomic analysis has been dramatic to say the least. The growth of proteomics was somewhat surprising given the promise and success of the human genome project and related genomic technologies. However, just as a blueprint for a house cannot reveal the failure of an air conditioner, it became clear that the genomic blueprint may not allow for the direct examination of chemical processes involved in disregulated cellular signaling. With approximately 25,000 human genes, many fewer than expected, it became apparent that the complexity of the proteome had been underestimated. A number of published estimates taking account of splice variants and post-translational modifications suggested that 25,000 gene products might generate more than 1,000,000 unique protein species [2,3]. Coupling this number of proteins with the known dynamic range of protein abundance in biological organisms and temporal nature of the proteome, the frontier of proteomic research appears to be nearly limitless in promise and complexity. For such investigation, protein centric tools were required and mass spectrometry was the tool of choice given its ability to identify proteins and their post-translational modifications [4,5].

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Proteomic Discovery and Applications to Oncology Driven by the advances of the genomic era and the completion of the human genome, deciphering the proteome became an inviting target for investigation. Although, proteomic work was being done with 2D gels long before the word proteomics was coined in the early 90’s, the lack of a suitable high-throughput protein identification tool mitigated its appeal for many researchers. Fortunately, the concomitant development of microscale protein chemistry coupled to facile, computer aided, mass spectrometric analysis of proteins and peptides quickly altered this situation and by the mid 90’s proteomics research was expanding rapidly. The field of proteomics experienced a period of exceedingly high expectations in the late 1990’s that was tempered as shortcomings of early proteomic analyses were revealed. The analytical variability of first generation proteomics platforms was high and the success of any experiment was very dependent on operator skill. The labor intensive nature of many approaches also constrained the ability to run technical replicates. Second, depth of interrogation of the proteome was identified as essential but lacking. Third, the necessary bioinformatic and statistical tools for the analysis of large proteomic datasets were relatively undeveloped. Although the genomics revolution had paved the way for large scale informatics and information management, the complexity of the proteome required that many new software tools be written from scratch. Despite the process of resetting expectations over time, investigators persevered and proteomics has continued to flourish.

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One of the promises of the emerging proteomics era was the opportunity to re-invigorate the fight against cancer through the discovery of biomarkers with utility in early diagnosis, prognosis, and therapeutic monitoring. Two general ideas coalesced in the diagnostic and oncology fields that helped to cement the role that proteomics would play in oncology research today: the primacy of the proteome and its direct relationship to aberrant growth and the successful discovery and commercialization of clinically useful protein biomarkers. Although mapping the human genome and associated genomic techniques had promised a new era in cancer diagnostics and therapeutics, the impact was less dramatic than hoped. A series of seminal studies with parallel genomic and protoeomic analyses showed that the correlation between the transciptome and the proteome was modest at best [6-7]. This observation offered a suggestion as to why genomic approaches might be having limited impact on the diagnosis and treatment of cancer. If a genomic experiment indicated a very high level of transcript associated with a particular disease state but did not show that the corresponding protein abundance was likewise increased, then a direct mechanistic link was hard to explain. In light of this work, it was widely proposed that a high-throughput and direct examination of proteins, the fundamental cellular machinery, would more readily reveal components and mechanisms of dysfunctional metabolism and growth. In this paradigm, the promise of proteomics was to facilitate ‘unbiased’ biomarker discovery. It seemed reasonable that direct comparison of the proteomes of healthy and diseased samples would unambiguously reveal differences in protein abundance mechanistically correlated to disease and that these differences could be leveraged in the treatment and diagnosis of cancer. The clinical research community had long understood that proteins in biological fluids might reveal signs of disease. However, identifying and validating cancer biomarkers was laborious and often delivered markers with limited specificity and sensitivity. Indeed, the limitations of widely accepted markers such as PSA and CA-125 have been used as arguments for expanding proteomic research in oncology. For almost every form of cancer, a very compelling case has been made for vigorous research to support the discovery of new markers. Therefore it is no surprise that large number(s) of academic and industrial groups have vigorously pursued the discovery of oncology biomarkers. Although no new diagnostic tests have been commercialized as of this writing, the impact of proteomics on the field of basic oncology research is unquestioned and a vigorous research community remains active with substantial funding from public and private granting organizations. In order to achieve the daunting task of proteomic analysis, a range of scientific disciplines and their associated technologies have been integrated into a systematic approach. These technologies cover several major scientific fields including, protein chemistry, separations science, mass spectrometry, and bioinformatics. Cleary each of these fields covers a range of disparate yet complimentary science. With this in mind, we will introduce the basic technological elements and experimental procedures that are used in basic proteomic experiments. While the field is still developing rapidly, the basic principles presented here are applied in many proteomic experiments.

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Sample Preparation Every experiment begins with a sample. Whether purified protein, cell lysate, or patient serum, every sample will require some kind of manipulation before reaching the mass spectrometer. Although the range of analytes that can be measured by mass spectrometry has grown though innovation in mass spectrometer design and application, many things must be considered to achieve optimal performance. As expected, biological samples present their own unique set of challenges. By far the most difficult facet of any proteomic analysis is managing the enormous range of protein concentrations within any given proteome. Elegantly summarized in the literature, the range of protein concentrations within a typical proteome covers 7-12 orders of magnitude [16]. With analytical tools that generally have a dynamic range of 2-3 orders of magnitude, the use of separations technology to enrich pools of proteins that are amenable to analysis is essential. The second fundamental reason for the application of separation techniques prior to mass spectrometry is related to the duty cycle and capacity of a mass spectrometer to perform experiments. A single protein digested with a protease such as trypsin will yield 10’s to 100’s of pepetides and a complex proteome sample is frequently composed of >100,000 peptides. Despite modern mass spectrometry’s ability to collect multiple spectra per second, the complexity of even a modest proteome quickly exceeds the performance of the mass spectrometer. Therefore, separations technologies are also applied in the proteomics lab to deliver analytes to the mass spectrometer over time so that the duty cycle and subsequent depth of analysis are more closely matched to the sample. The third advantage is that separations technology allows samples in matricies incompatible with ionization to be liberated from these interferences prior to analysis. Biological samples are frequently rich in salts, lipids, and other metabolic products that make co-ionization of the analyte and these contaminating substances difficult or impossible [9,10]. By using selective bulk or chromatographic separations the majority of these compounds can be removed while simultaneously shifting the composition of the solvent system toward one favorable for ionization.

Electrophoretic Separation Many proteomics labs use polyacryalamide gel electrophoresis (PAGE) as a starting point for many experiments. As a low cost and robust way to achieve significant separation with little optimization, the approach is without compare. Traditional PAGE separates proteins by molecular weight in a gel matrix via the application of an electric field [11]. After separation, gels are often stained to reveal a ladder of protein bands where the distance of the protein band from the origin is inversely proportional to its molecular weight. Conveniently, the visualized bands can be excised and processed to liberate the proteins or peptides for analysis by mass spectrometry. Complex mixtures of proteins can also be separated by isoelectric focusing (IEF). Similar to traditional PAGE, IEF is also performed in a gel matrix with an applied electric field. However, immobilized or carrier ampholytes are utilized during

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Cory E. Bystrom and Nigel J. Clarke

the separation to develop a pH gradient across which proteins move until they acquire an equal number of positive and negative charges [12]. In the early development of proteomics technology, two-dimensional gel separations that coupled both IEF and molecular weight based separations were common [13]. The impressive resolving power that could be achieved by coupling orthogonal separation techniques was a key feature in addressing the problem of protein abundance. By careful selection of separation parameters (isoelectric and molecular weight ranges) the interference of highly abundant proteins could be dramatically reduced. The use of 2-dimensional PAGE also provided an entry point for doing comparative and quantitative proteomics. With the ability to reproducibly separate hundreds to thousands of proteins and protein isoforms on a single gel, comparisons of control and experimental gels permitted observation of changes in protein abundance across a protein constellation [14]. Despite limitations, early successes with these approaches using model systems helped develop confidence that the application of proteomics would also offer similar insight into human biology and disease.

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High Performance Liquid Chromatography Even in proteomics labs fully equipped with gel based separation equipment, application of high performance liquid chromatography (HPLC) is essential and is generally set up with the effluent from the chromatography column being channeled directly into the mass spectrometer. The principle of HPLC based separations is based on the interaction of an analyte, a solid support (the stationary phase) and a liquid stream of variable composition known as the mobile phase. The most commonly used form of HPLC is known as reverse phase chromatography and uses a hydrophobic stationary phase typically bound to spherical silica particles homogeneously packed into a pressure resistant column through which mobile phase is pumped. The initial conditions are set so that the proteins/peptides that are to be analyzed are reversibly adsorbed to the stationary phase. After the capture of the analytes of interest on the front of the column the mobile phase composition is normally altered to increase the amount of organic solvent. As the composition of the mobile phase changes over time from mainly aqueous to mainly organic, the analytes adsorbed within the hydrophobic coating on the stationary phase partition into the mobile phase and are swept out of the column in turn. The instrument’s ability to deliver reproducible subtle mobile phase composition gradients allows a skilled practioner to separate very similar compounds. This sequential separation of all the analytes within the complex sample reduces the complexity of the signal recorded by the mass spectrometer and leads to formation of a mass chromatogram, a graph of selected m/z signal intensities versus time.

Solid Phase and Bioaffinity Separations When gel based or HPLC separations alone (or in tandem) are still insufficient to manage sample complexity, additional modes of separation can be added. An enormous array of separation modes is available for exploration and include typical ion-exchange, hydrophilic

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interaction, hydrophobic interaction, and size exclusion phases [15]. Antibody and protein/protein interaction based separations are also commonly used and offer tremendous advantages in selectivity and the ability to concentrate low levels of analyte into small volumes suitable for mass spectrometry analysis. One particularly innovative application of biological affinity separations was the development of the Tandem Affinity Purification Tag (TAP-Tag) system which was used to develop a proteomic view of a whole cell protein-protein interaction map. In this experiment, yeast proteins were expressed with dual tags so that two rounds of gentle protein/protein affinity reagents could be used to isolate biologically relevant protein complexes. Once these complexes were isolated, they were resolved on a 1D gel and the members of the complex were identified using proteomics approaches. The analysis pipeline presented in this seminal work took advantage of all of the separations technologies mentioned here. First, biological affinity modes were employed to isolate intact cellular protein complexes. The protein complexes were resolved to individual bands on one-dimensional PAGE gels and the bands were excised for processing. Finally, the proteolytically produced peptides derived from each protein in each gel slice were resolved by HPLC directly interfaced to a mass spectrometer. The protein identification data was then interrogated to develop a protein interaction map [16].

Mass Spectrometry

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Once a sample has been prepared appropriately, it is destined for the mass spectrometer. Generally, all mass spectrometers consist of an ion source, mass analyzer, detector, vacuum system, and computerized control and data analysis system (Figure 1).

Figure 1. Block diagram of a typical triple quadrupole mass spectrometer. In this arrangement, Q1 and Q3 are operated as mass analyzers while Q2 is utilized as a collision cell. Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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Cory E. Bystrom and Nigel J. Clarke

In recent years, innovations brought to instrumentation have yielded an array of source, analyzer, detector combinations that is too lengthy to cover here. However, all mass spectrometry experiments comprise three steps, ionization, mass analysis, and detection.

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Ionization Mass spectrometric techniques depend upon the capacity to control ions in an electric field to yield a measurement of mass to charge ratio (m/z). Therefore the starting point for any mass spectrometry experiment is the generation of a gas phase ion. In the early applications of mass spectrometry, high energy ionization methods were routinely used to analyze chemical species amenable to mass spectrometric analysis owing to their reasonable volatility and chemical stability. A fundamental hurdle in the application of mass spectrometry to proteins and peptides was the challenge of generating gas phase ions from labile molecules with very low vapor pressures. Although peptide sequencing work began in the 1960’s, progress accelerated with the invention and application of atom bombardment (FAB) to peptide and protein bioanalysis [17, 18]. The introduction of electrospray ionization (ESI) by Fenn and matrix assisted laser desorption ionization (MALDI) by Karas and Tanaka then revolutionized peptide and protein mass spectrometry by providing two very gentle ionization procedures with few of the liabilities that had limited the application of mass spectrometry to sensitive, non-volatile biological materials [19-21]. The technique of ESI is elegant in its simplicity and relies on formation of an aerosol of charged droplets in an electric field. In an ESI source, a stream of liquid is drawn or pumped to a small orifice in the source region of the mass spectrometer. A high voltage potential is established between the orifice and the entrance of the mass spectrometer which causes an aerosol to form from the liquid droplets appearing at the orifice. The small droplets in the aerosol begin to desolvate under the action of electrostatic repulsion, occasionally with the assistance of heat and/or nebulizing gas introduced to source. In the final step of desolvation, each analyte ion is freed of all solvent and is drawn into the mass spectrometer for analysis. ESI is exceptionally robust and a wide range of solvent types and flow rates can be accommodated. ESI’s great utility is the ability to establish a direct, high performance interface between a separations platform and the mass spectrometer for on-line, automated, real time analyses. Another popular ionization technique, matrix assisted laser desorption ionization (MALDI) is a discontinuous ionization process. In a MALDI experiment, analyte is first cocrystallized with matrix on a metal or conductive glass target. For peptide and protein analysis, the matrix is typically a small, aromatic organic acid such as dihydroxybenzoic acid (DHB) or α-cyano-4-hydroxycinnamic acid (HCCA). After crystallization, the sample is introduced to a high vacuum region of the mass spectrometer and short pulses of laser light are used to ablate a small portion of the sample. At the crystal surface, the laser energy excites the matrix which leads to the transfer of the protonated analyte to the gas phase through a complex thermal and chemical process [22]. While MALDI has not been as widely used as ESI for biomolecular analysis due to its discontinuous nature, it served as a starting point for protein identification approaches via the mass spectrometric analysis of peptide masses. The advantage afforded by MALDI continues to lie in the speed of data acquisition.

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In a modern MALDI mass spectrometer, a full spectrum can be obtained from a sample every 3-5 seconds making it very attractive for analyzing large numbers of samples. A range of new ionization techniques have been described in recent years. Many of these techniques seek to improve on the shortcomings of ESI and to extend the range of operating conditions and acceptable analytes. Atmospheric Pressure Matrix Desorption Ionization (APMALDI) and Desorption Electrospray Ionization (DESI) and Atmospheric Pressure Photo Ionization (APPi) are examples of recently developed source configurations with bioanalytical applications [23-25].

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Mass Analysis When a gas phase ion is generated in the source region of the mass spectrometer, it acquires a specific mass-to-charge ratio (m/z) dependent on the mechanism of ionization and chemical properties of the analyte. Once the ion enters the vacuum region of the mass spectrometer, a mass analyzer (or series of analyzers) can then be employed to manipulate and detect them. In a quadrupole instrument, the mass analyzer is a tunable and selective mass-to-charge filter. Adjustment of direct current voltages and radio frequency amplitudes applied to the ion optics, allows a narrow range of m/z ions to pass through the filter and reach the detector. These adjustments can be made in real-time so that scanning experiments covering a range of m/z 200 to 2000 can be accomplished a few hundred milliseconds. This selectivity makes mass spectrometry very powerful – complete resolution of chemical species differing by only 1 Da is continuously achievable on a properly operated quadrupole instrument. High performance quadrupole platforms are able to offer complete resolution of chemical species differing by only 0.2 Da. In a triple quadrupole instrument (QQQ), a sequential arrangement of two mass analyzers separated by a fragmentation cell, is used to manipulate a continuous beam of ions. Often called tandem mass spectrometers, they allow two stages of mass analysis to occur independently in space. For example, an ion with a specific charge to mass ratio (m/z) can be filtered out of a complex mixture of ions arriving at the first quadrupole; passed to the collision cell where the selected ions can be fragmented, and the fragment ions with their own unique m/z ratios, can be sequentially scanned by the third analyzer for detection. This mass spectrometer experiment, known as the product ion scan is one of the most powerful experiments due to the structural information that is revealed upon fragmentation. Triple quadrupole instruments may have modest mass accuracy and resolution but they are favored for their sensitivity, wide dynamic range, and robustness. Ion trap mass spectrometers are closely related to triple quadrupoles but differ in the mass analyzer. In an ion trap, a single 3 dimensional quadrupole mass analyzer is controlled in a time dependent fashion to manipulate a single packet of ions. This allows stages of mass analysis to be achieved in time, rather than in space as in a triple quadrupole. In an ion trap instrument, a product ion experiment is achieved by filling the trap with ions; isolating the m/z species of interest; fragmenting and containing product ions; and scanning the product ions to the detector. Similar to triple quadrupoles, ion trap instruments have modest mass accuracy and resolution. However, their enormous popularity in the field of proteomics is

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partially attributed to their high price to performance ratio and their early use in pioneering proteomics research. Time of flight (TOF) mass analyzers operate using a fundamentally different approach to resolving m/z species than quadrupole instruments. These analyzers rely on the simple principle that drift time is proportional to m/z. After acceleration, low m/z ions travel quickly through the drift tube while high m/z ions travel slowly. Single stage TOF instruments are not capable of product ion experiments which require tandem capability. However, TOF/TOF instruments with product ion capability are now widely used in proteomic research. The major advantages of TOF mass spectrometers are their high mass accuracy, high resolution, and speed of operation. Mass spectrometers are often classified by the type of mass analyzer and detection system. These classifications also tend to be associated with specific applications and their associated requirements for speed, resolving power, and sensitivity. Traditional instrument classes associated with bioanalytical applications have been triple quadrupole (QQQ), ion trap (QIT/LIT), and maldi-time of flight (MALDI-TOF). New analyzers and multiple configurations of analyzers are rapidly being brought to market to meet the technical demands of proteomic research. Hybrid instruments that combine two different classes of mass analyzer are commonly found in proteomics labs. The impetus for developing these types of instruments is to combine functionality and performance not found in instruments with a single class of mass analyzer. For example, quadrupole time-of-flight (qTOF) class instruments offer the mass selective capabilities of a triple quadrupole with the high mass accuracy and resolution of a TOF instrument. In recent years, Fourier transform ion cyclotron resonance (FTICR) and Orbittrap instruments have been deployed in the study of biological molecules.

Application of Mass Spectrometry to Protein and Peptide Bioanalysis Bioanalytical mass spectrometry has enormous utility because it permits mass measurements that reveal structural properties of proteins. While many kinds of scan modes are available on most commercial mass spectrometers, the two most common deserve attention; the survey scan which provides mass information of an intact ion(s), and the product ion scan which reveals chemically distinct fragments that arise from the decomposition of one intact species. In a survey (MS) scan, every ion that enters the mass analyzer is scanned to the detector to generate a typical spectrum shown in Figure 2. Based on the knowledge of the molecular structures of amino acids and their assembly into polypeptides, full scan mass analysis can be used to directly assess protein and peptide structure. After a chemical formula of a polypeptide is established by its amino acid sequence, it is easy to calculate a theoretical mass and relate it to the observed mass measured in a full scan experiment. With a full scan spectrum of an intact protein providing a mass measurement with less than 0.1% error, the integrity of a purified protein can easily be achieved and the presence of a significant mass deviation readily reveals the presence of amino acid substitutions or modifications. For

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smaller peptides, the m/z measurement can be accurate to the low parts per million (ppm) range depending on the type of instrumentation used to make the measurement. In the product ion (MS/MS) scan, a single molecular species, identified by a specific m/z measurement is isolated by a mass analyzer prior to dissociation in the collision cell. The fragments from the collision cell are then subject to a second round of mass analysis to generate a spectrum of fragments that are derived from the precursor ion. The utility of tandem analysis as it relates to polypeptides lies in the fact that fragmentation leads to fragmentation along the amide backbone. Therefore, the product ion spectrum of a peptide contains a ladder of masses associated with the amino acid sequence (Figure 3).

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Figure 2. A theoretical full scan spectrum of the peptide EGVNDNEEGFFSAR. The spectrum shows peaks where z=1, 2, and 3 by virtue of a variable number protons being acquired by the peptide during ionization.

Figure 3. A theoretical fragment ion spectrum of the peptide EGVNDNEEGFFSAR. The mass differences between peaks in the spectrum are related to amide bond fragmentation events that result from dissociation of the peptide in the collision cell.

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Basic Proteomics Experiments To provide a context for the technical information provided we will step through three prototypical proteomics experiments; : protein identification, shot gun proteomics for relative quantitation, and a targeted absolute quantitative analysis.

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Protein Identification There are two typical approaches to protein identification, those based on peptide m/z values alone and those that use both intact peptide and peptide fragment masses. One of the first approaches to protein identification without significant prior knowledge of the protein relied on a technique called peptide mass fingerprinting [26]. In this approach, a protease with known cleavage specificity generates a collection of peptides by its cleavage of intact protein. The peptides are then mixed with matrix and transferred to a MALDI-TOF mass spectrometer for full scan MS acquisition. The resulting spectrum is interrogated and each peak at a specific m/z, assumed to represent a unique tryptic peptide, is tabulated. This list of m/z values is then compared against a database containing the theoretical masses of in-silico digested proteins. In a process similar to using a reverse phone directory, a list of matched peptides is then used to determine a list of proteins that potentially match the m/z data. Early methods of discriminating protein identifications simply relied on selecting the protein with the largest number of matches within a specified m/z tolerance. These early approaches were quickly augmented with statistical models to provide confidence measures of protein identifications with respect to expected and observed instrument performance. This approach is rapid and dovetailed nicely with early proteomic pipelines that were highly dependent on two-dimensional gels where each excised spot would frequently contain only one or two proteins. While this technique is still in use, its has diminished due to the higher specificity data that is frequently delivered via automated MS/MS experiments. Peptide identification by tandem (MS/MS) mass spectrometry is a two stage process: characterizing an intact peptide m/z value by MS followed by characterizing the product ion spectra (MS/MS) of that single m/z species. In the first stage, the mass spectrometer is operated in full scan mode where the m/z of all of the peptide ions entering the system are characterized. Once the operator, or automated software identifies the m/z of a species interest, a product ion scan is performed to reveal the entire or part of the amino acid sequence of the peptide. While an experienced mass spectrometrist can manually interpret the MS and MS/MS data to derive a peptide sequence, this process is often automated [27]. Once a series of peptide spectra have been collected and processed, protein identity is inferred through a parsimonious recombination of peptide identification data [28].

Shotgun Proteomics for Biomarker Discovery A classical workflow for proteomic biomarker discovery in its current conception would start with the collection of 3-10 samples of human plasma believed to be representative of both disease and healthy states. These samples would be split to generate technical replicates

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and subsequently processed in parallel. To address the problems of protein abundance afforded by the most common serum proteins, an immunoaffinity depletion step is undertaken on each sample to remove 90% or more of the total mass of protein from each sample. The remaining pool of proteins would be digested with trypsin to yield several micrograms of peptides. Since this pool is far too complex to separate in a single HPLC run, an offline fractionation is performed to separate tryptic peptides by ion exchange into 10-20 individual pools. Each of these ion exchange fractions would then be injected onto a reverse phase column and subject to automated MS and MS/MS data collection. The raw data is then processed in two steps. First, 3D contour maps of m/z and intensity measurements as a function of time are generated and retention time differences between technical and experimental replicates are minimized while peak intensities are normalized using a suite of mathematical models. The aligned data sets are then probed for statistically significant relative differences in intensity with the assumption that these observations may be biologically relevant to the disease state under investigation. In the second step, the MS/MS data is concomitantly interrogated by database search to provide a catalog of identified proteins. Differences in intensity are then associated with protein identifications to generate a list of candidate proteins that may be associated with the biology of the disease. The investigator can then apply a suite of bioinformatics tools to collections of differentially expressed proteins to place the candidates into biological context [29].

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Targeted Absolute Quantitation With a candiate protein biomarker in hand, a mass spectrometry method to perform absolute quantiation is necessary for validation of the candidate as a selective and specific indicator of disease. To develop a method for absolute quantitation, a suitable set of protein or peptide calibrators and an internal standard are devised. Calibrators are used to develop a dose response curve for the mass spectrometer while the internal standard is incorporated in the sample preparation process to control for the variability introduced in the pre-analytical phase. During chromatography of each unknown sample, peak areas are determined for the signal derived from one or more specific ions observed in a product ion spectrum. Data for both the peptide derived from the protein of interest and the internal standard are collected in parallel. Peak areas in the mass chromatogram are calculated for both the analyte and internal standard and the ratio calculated. The calibration curve is then used to convert area ratios for unknown samples to an absolute concentration [30].

Information Management and Bioinformatics Although the raw data of that comes from a mass spectrometer is of primary interest to the mass spectrometrist, a proteomics experiment often requires integration of an entire constellation of data: patient information, sample collection and storage details, preanalytical steps and laboratory conditions for those manipulations, raw and reduced mass spectrometry data, separations platform performance data, protein abundance and identification data,

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bioinformatic analysis of technical and experimental replicates, etc. The diversity and volume of data is overwhelming. Indeed, many mass spectrometry platforms being used in biomedical applications are capable of generating gigabytes of raw data per day. Given the deluge of data, it is no surprise that data management and bioinformatic analysis now play a central role in proteomics experiments. Like many multidimensional and highly interrelated projects, management of proteomics experiments now makes use of a modular approach. Many high throughput proteomics projects are centrally organized via a Laboratory Information Management System (LIMS). These systems operate as hubs through which an entire experimental dataset is captured, reduced, and interrogated. Frequently, such systems are set up to automatically capture metadata and raw data from samples as they move through the analytical pipeline. When possible, automated data reduction and bioinformatics analyses are run continuously and the results served to investigators for manual validation. Finally, the entire data set is made available for interactive analysis and review. Within the information management aspect of a large proteomics project, a range of bioinformatic tools are used to convert complex mass spectrometry data sets into lists of proteins and their relative abundances. This data is further processed to put the information in some biological context. As the number, depth, and quality of publicly available databases have grown, a number large scale, multi-institutional projects have been launched to develop high-level data mining tools that mine proteomic databases. PRIDE, Peptide Atlas, Global Proteome Machine, and the Plasma Proteome Database are examples of some of the available resource [31-34].

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Conclusion Proteomics approaches to understanding cancer biology have been enthusiastically adopted by the oncology community. The unmet need for new diagnostic tools and the promise of applying proteomic data to fundamental questions of biology have been responsible for this growth. Clearly the technologies that support proteomic research are continuing to develop rapidly. Improvements in mass spectrometers, sample preparation strategies, and bioinformatic tools will certainly impact oncology research for the foreseeable future.

References [1] [2] [3] [4] [5] [6] [7] [8]

2D Electrophoresis: From Protein Maps to Genomes. Proceedings of the International Meeting. Siena, Italy, September 5-7, 1994. (1995) Electrophoresis 16, 1077-1132 Claverie, J. (2001) Science 291, 1255–7. Pennisi, E. (2003) Science 301, 1040-1041. Wilkins, M. et. al. (1999) Journal of Molecular Biology 289, 645-57. Mann, M., Jensen O. (2003) Nature Biotechnology 21, 255-61. Gygi S, et al. (1999) Molecular and Cellular Biology 19, 1720–1730. Greenbaum D, et al. (2003) Genome Biology 4, 117. Anderson, N. and Anderson, N. (2002) Molecular and Cellular Proteomics, 1, 845-867

Immunological and Molecular Diagnosis of Cancer, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Proteomics in Oncology [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27]

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[28] [29] [30] [31] [32] [33] [34]

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Taylor P. (2005) Clinical Biochemistry 38, 328-334. Matuszewski B. (2003) Analytical Chemistry 75, 3019–3030. Laemmli U (1970) Nature 227, 689. Righetti P., Drysdale J. (1971) Biochimica Biophysica Acta 1971 236, 17-28. O’ Farrell P. (1975) Journal of Biological Chemistry 250, 4007-21. Gygi S. et al., (2000) Proceedings of the National Academy of Science 97, 9390-9395. Simpson N (2000) Solid-Phase Extraction: Principles, Strategies and Applications CRC Press, Marcel Dekker, New York. Gavin A, et al. (2002) Nature 415, 141-147. Biemann K., et al. (1966) Journal of the American Chemical Society 88, 5598-6061. Morris H., et al. (1981) Biochemical Biophysical Research Communications 101, 62331. Fenn J., et al. (1989) Science, 246, 64. Karas M., Bachmann D., Hillenkamp F. (1985) Analytical Chemistry 57, 2935-2939. Tanaka K., et al. (1988) Rapid Communications in Mass Spectrometry 2, 151–153. Hillenkamp F, (1991) Analytical Chemistry 63, 1193A–1203A. Laiko V., Baldwin M., Burlingame A. (2000) Analytical Chemistry 72: 652-657. Takats Z., et al. (2004) Science, 306, 471-473. Hanold K., et al., (2004) Analytical Chemistry 76, 2842-2851. Henzel W., Watanabe C., Stults J., 2003 Journal of the American Society for Mass Spectrometry 14, 931-942. Eng J., McCormack A., Yates J. (1994) Journal of the American Society of Mass Spectrometry 5, 976–989. Nesvizhskii A., et al. (2003) Analytical Chemistry 75, 4646-4658. Koomen J. et al (2005) Journal of Proteome Research 4, 972-981. 30 ) Gerber S, et al. (2003) Proceeding of the National Academy of Sciences 100, 69406945. Jones P. et al. (2006) Nucleic Acids Research 1 (Database issue) D659-D66. Desiere F, et al. (2004) Genome Biology 6, R9. Craig R., Cortens J., Beavis R., (2004) Journal of Proteome Research 3, 1234-42. Babylakshmi M, et al (2005) Proteomics 5, 3531-3536.

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In: Immunological and Molecular Diagnosis of Cancer ISBN: 978-1-61728-949-1 Editor: Maher Albitar © 2011 Nova Science Publishers, Inc.

Chapter II

Methods for Diagnosis, Prognosis, and Monitoring of Lymphomas Zhong Zhang and Maher Albitar Quest Diagnostics, Nichols Institute, San Juan Capistrano, California, USA

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Abstract In this chapter, we discuss the most important and common lymphomas in lymph node and extranodal tissues. Algorithms followed immediately by explanatory notes are used extensively to simplify the steps needed to make a proper diagnosis. Lymphomas are grouped based on site, dominance of tumor cells, and lineages. Next, diagnosis of individual lymphomas is discussed in more detail, incorporating morphologic examination, immunohistochemistry, flow cytometry, cytogenetics, FISH, and molecular studies. The prognosis, monitoring, and features needing special attention of each lymphoma are also considered. The NCCN guidelines and WHO classifications are adapted throughout the chapter. In general, morphologic examination serves as base for ancillary testing. Immunophenotyping data should be obtained by flow cytometry, or if unavailable, IHC should be used. If possible, cytogenetics and/or FISH should be performed for every case, for their diagnostic as well as prognostic values. PCR tests are useful for complicated cases, for determining minimal residual disease, and for monitoring disease recurrence. Whenever a diagnosis of lymphoma is made, additional studies should be performed, including a complete laboratory chemistry evaluation, bone marrow staging, and prognostic marker studies.

Introduction Lymphoma is a malignant neoplasm that manifests by involving one of the lymphoid organs or tissues, or by involving other organs. In 2008, an estimated 74,320 new Hodgkin lymphoma and non-Hodgkin lymphoma cases were diagnosed and 20,510 deaths occurred in the United States. The incidence of non-Hodgkin lymphoma has increased significantly

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Zhong Zhang and Maher Albitar

during past 30 years. Successful management of these lymphoma patients lies in correct diagnosis, appropriate selection of treatment, and accurate prediction of disease progression. The recent development of complex esoteric testing has brought lymphoma diagnosis into a new dimension. Irrespective of the kind of tissue involved, proper diagnosis of lymphoma now requires combining clinical history, morphologic examination, immunophenotypic analysis (flow cytometry or immunohistochemistry), molecular studies, cytogenetics, and FISH studies. While most of the tests are required to establish a diagnosis, some are necessary to establish a baseline for future follow up, to detect minimal residual disease, or to predict disease progression. In this chapter, we discuss algorithms, features of lymphomas, and tools necessary for their diagnosis, prognosis and monitoring. Initial Screening Approach for Lymphoma:

POTENTIAL DIAGNOSIS OF LYMPHOMA

Submit biopsy tissue for 1-Morphology 2-Flow cytometry 3-Molecular Studies 4-Storage (frozen) 5-Cytogenetics/FISH

LYMPH NODE

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PREDOMINANTLY NEOPLASTIC CELLS

B-CELL LYMPHOMAS T-CELL LYMPHOMAS NK CELL LYMPHOMAS

FIG. 2A-2E

EXTRANODAL SITES

PREDOMINANTLY REACTIVE CELLS WITH SCATTERED NEOPLASTIC CELLS

CHL NLPHL TCRBL

ORGANS, SKIN, BONE MARROW, AND SOFT TISSUE

FIG. 4A-4C

FIG. 3

CHL: Classical Hodgkin lymphoma. NLPHL: Nodular lymphocyte predominant Hodgkin lymphoma. TCRBL: T-cell/histiocyte rich B-cell lymphoma.

Figure 1. Clinical information usually helps decide whether the tissue is from lymph node or extranodal tissues. It is crucial to plan ahead of time and prepare to handle the tissue properly. Divide representative tissue into aliquots as suggested. If available tissue is limited, prioritization of its use should be based on the available data and morphologic evaluation. If the biopsy is from lymph node and initial microscopic evaluation suggests a B- or T-cell neoplastic process, proceed as indicated in figures 2A to 2E. If classical Hodgkin lymphoma, nodular lymphocyte predominant Hodgkin lymphoma, or T-cell/histiocyte rich B-cell lymphoma is suggested, or in the case of a predominance of a reactive process, proceed to Figure 3. For lymphomas involving extranodal tissues such as skin, bone marrow, solid organs, and soft tissue, see Figure4A-4C.

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LYMPH NODE WITH PREDOMINANTLY NEOPLASTIC CELLS

IHC and/or flow cytometry for immunotyping: CD20 CD19* CD3 CD30 CD20/CD19+, CD3-, CD30B-cell lymphomas FIG. 2B1-2B2

CD3+, CD20/CD19-, CD30-

CD30+, CD20/CD19-, CD3-

T-cell lymhomas (CD3+) NK cell lymphoma (cCD3+)

ALCL TCL BCL

FIG. 2C

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FIG. 2D

CD20/CD19-, CD3-, CD30ALL NK PCM MONOCYTIC OR MYELOID SARCOMA MAST CELL DISORDER NON-HEMATOPOIETIC TUMORS FIG.2E

IHC:Immunohistochemistry. ALL:Lymphoblastic lymphoma/leukemia. NK:Natural killer cell lymphoma. TCL:T-cell lymphoma. ALCL:Anaplastic large cell lymphoma. BCL:B-cell lymphoma. PCM:Plasma cell myeloma.*CD19 by flow cytoemtry or CD20/ CD79a/PAX5 by IHC. Figure 2A.When dealing with lymph node containing predominantly lymphoma cells and bearing abnormal structure, in most cases the immunostains of CD3, CD20/CD19, and CD30 allow triage of cases into several major categories, such as T-cell lymphomas, B-cell lymphomas, NK cell lymphoma, anaplastic large cell lymphoma, and others. More immunostains, cytogenetic analysis, and molecular studies should help in defining the direction of the diagnosis.

LYMPH NODE WITH PREDOMINANTLY NEOPLASTIC CELLS CD20/CD19+, CD3-, CD30-/+

Mainly small to medium cells

Mainly medium to large cells

CD5, CD23, BCL1, CD10, BCL6, BCL2, MUM1, FISH, CYTO, Molecular

CD5, CD23, BCL1, CD10, BCL6, BCL2, FISH, CYTO, Molecular CD5+, CD23+ BCL1t(11;14)B-R+

CD5+, CD23BCL1+ t(11;14)+ B-R+ BCL1-R

CD10+, BCL6+ BCL2+ t(14;18)+ B-R+ BCL2-R

CD5-, CD10BCL6t(14;18)B-R+

FL

CLL/SLL

BCL2 Ki67 CYTO FISH

Pre-B ALL

Lymphoplasmacytic lymphoma Hairy cell leukemia

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CD10+, TdT+ B-R+ t(9;22)+/-

BCL2+/Ki6790% cMYC+, t(8;14) Burkitt or Atypical Burkitt

CD10-, BCL6CD5+/B-R+

DLBCL or LCT NGCB (MUM1+ CD10BCL6-/+)

GCB (MUM1-/+CD10+ or MUM1-CD10BCL6+) CLL:Chronic lymphocytic leukemia. MCL:Mantle cell lymphoma. FL:Follicular lymphoma. SMZL:Splenic marginal zone lymphoma. ALL:Lymphoblastic lymphoma. DLBCL:Diffuse large B-cell lymphoma. LCT:Large cell transformation. GCB:Germinal center type. NGCB:Non-Germinal center type . B-R+:B-cell gene rearrangement positive. BCL1-R:BCL-1 rearrangement. BCL2-R:BCL-2 rearrangement. BMCL:Blastic mantle cell lymphoma.

Figure 2B1. If lymphoma cells are positive for CD20, CD19, Pax5, or CD79a, and are mainly small to medium-sized lymphoid cells in a lymph node, the differential diagnosis includes small lymphocytic lymphoma (SLL), mantle cell lymphoma (MCL), follicular lymphoma (FL), and marginal zone B-cell lymphoma (MZL). The potential prolymphocytoid transformation of CLL should be considered based on morphology. If the lymphoma cells are positive for CD20/CD19 and are mainly large to medium-sized lymphoid cells in a lymph node, the differential diagnosis includes diffuse large B-cell lymphoma, Burkitt’s/atypical Burkitt’s lymphoma, and precursor B-cell lymphoblastic lymphoma. Flow cytometry analysis and/or immunostains for CD5, cyclin D1, CD10, bcl-6, bcl-2, Ki-67, TdT, and CD34 should be evaluated. In addition, cytogenetics, FISH, and PCR studies for immunoglobulin gene rearrangements t(11;14), t(8;14), t(8;22), t(2;8), and t(14;18) are necessary for confirmation of the diagnosis, as well as for predicting outcome and monitoring disease. When adequate tissue is unavailable, or to monitor disease, considers PCR-based assays for detection of B-cell gene rearrangements or translocations.

Methods for Diagnosis, Prognosis, and Monitoring of Lymphomas

37

B-Cell Lymphoma Small Lymphocytic Lymphoma Diagnosis Morphology: Small lymphocytic lymphoma is a low-grade B-cell lymphoma usually comprised of monomorphous small lymphoid cells with clumped chromatin, growing in a diffuse or nodular pattern with pseudofollicle formation. Their mitotic rate is low and scattered prolymphocytes are present. Biopsy is preferred for initial diagnosis of lymphoma over a FNA of a mass. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be performed for staging. Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for CD5 and CD23, with dim CD20 and light chain expression. It is negative for FMC-7 and cyclin D1. CD38 is usually determined for prognostic purposes. Molecular and cytogenetic studies: Trisomy 12, deletion 13q14, deletion 11q22-23, deletion 17p13, and deletion 6q21 are often seen by FISH or cytogenetics. Immunoglobulin gene rearrangement is present.

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Prognosis Clinical staging, cytogenetics, CD38, Zap70, and IgVH are currently widely used for prognostic purposes and to guide the direction of treatment [1]. Many other markers predict disease progression, including CD138, thrombopoietin, beta2-microglobulin, IL-6, and soluble CD23. Diffuse bone marrow involvement, unmutated IgVH, positive CD38, positive Zap70, deletion of 11q, deletion 17p, and Richter transformation indicate a poor prognosis. Expression of IgVH3-21 by the lymphoma predicts a poor prognosis regardless of mutational status [2]. For a detailed description, please see CLL in the chronic leukemia section. Monitoring According to the NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, detection of which requires imaging study and bone marrow biopsy, are used to determine the response to therapy. Monitoring treatment response or disease recurrence employs flow cytometry analysis. The disease can also be monitored at the molecular level by checking immunoglobulin gene rearrangement. Caveats 1. Small lymphocytic lymphoma occasionally expresses dim or negative CD23, causing it to be confused with mantle cell lymphoma, which rarely expresses CD23 [3]. FISH or IHC analysis for cyclin D1 is necessary in these cases. 2. Occasionally, or when transformation has occurred, the lymphoid cells may lose their CD5 and/or CD23 expression, which may make diagnosis difficult if the patient's previous history is unknown [4]. 3. When sheets of large cells or prolymphocytes are present in a patient with history of SLL/SLL, it should be described because they represent transformation and rapid disease progression.

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Zhong Zhang and Maher Albitar 4. There is increased evidence of small lymphocytic lymphoma coexisting with Hodgkin lymphoma. The Hodgkin cells may represent transformation of CLL cells or a de novo Hodgkin lymphoma [4-6]. 5. Most common genetic abnormalities are not recurring balanced translocations; therefore they cannot be routinely detected by PCR. The FISH panel is more useful.

Mantle Cell Lymphoma

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Diagnosis Morphology: Mantle cell lymphoma is a high-grade B-cell lymphoma usually comprised of monomorphous small to medium-sized lymphoid cells. They have cleaved or irregular nuclei in a diffuse or nodular growth pattern without large cell transformation. Blastoid and pleomorphic variants are described which show a high mitotic rate or increased large cells. “In Situ” mantle cell lymphoma has been recognized as those cases that involve strictly inner mantle zones [7]. Mantle cell lymphoma is most commonly found in lymph nodes, gastrointestinal tract, and spleen. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be performed for staging. Flow cytometry and immunohistochemistry: Mantle cell lymphoma is characteristically positive for CD5 and cyclin D1, in addition to B-cell markers. It is negative for CD23, distinguishing it from chronic lymphocytic leukemia/small lymphocytic lymphoma [8]. Molecular and cytogenetic studies: PCR, FISH and cytogenetic studies usually show the t(11;14) involving the cyclin D1 gene [9]. Other abnormalities of ATM, P53, P16, P21, and P18 genes have been reported but are not disease specific. Translocations of MYC and BCL-6 occur rarely. Prognosis A high mitotic rate, blastic morphology, and other cytogenetic abnormalities, in addition to t(11;14) and peripheral blood involvement, offer a poor prognosis. Descriptions of unusual morphology, cytogenetics, and flow cytometry analysis of peripheral blood are recommended. Recently, a cDNA microarray study has identified a set of genes that can stratify cases and better predict survival [10]. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, detection of which requires imaging study and bone marrow biopsy, are used to determine the response to therapy. From our point of view, if primary tumor is positive for t(11;14), blood or serum PCR analysis of t(11;14) or immunoglobulin heavy chain may be useful for early detection, or for monitoring disease response or recurrence. Caveats 1. Occasionally, mantle cell lymphoma can express CD23, which may cause it to be confused with CLL/SLL. Additionally, sometimes mantle cell lymphoma can be negative for CD5, and positive for CD10 and bcl-6 [11]. However, cyclin D1 is

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Methods for Diagnosis, Prognosis, and Monitoring of Lymphomas

2.

3. 4.

5.

39

usually positive, therefore, it is recommended to assay for its overexpression whenever there is a morphologic suspicion. Immunohistochemistry is still the gold standard since cyclin D1 overexpression can occur not only by t{11;14), but also by point mutation, in which case the FISH, cytogenetics, and PCR tests would be negative [12]. Cyclin D1 overexpression is not entirely mantle cell lymphoma specific. It has been detected in some plasma cell myelomas and hairy cell leukemias [13;14]. A recent gene profiling study for mantle cell lymphoma suggests that genetic abnormalities extend far beyond the amplification of cyclin D1. Many deletions, amplifications, and mutations have been identified which are able to predict patient outcome. Cyclin D1-negative mantle cell lymphoma has also been proposed, which exhibits characteristic morphologic features and a gene expression signature similar to those of cyclin D1-positive mantle cell lymphoma, except these lymphomas are positive for cyclin D2 and D3 [15;16]. Note that some healthy individuals may have circulating cells carrying t{11;14) [17].

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Follicular Lymphoma Diagnosis Morphology: Follicular lymphoma is a B-cell lymphoma usually comprised of small cleaved centrocytes admixed with some larger centroblasts that grow in a follicular (>75% follicular), focally follicular (15 centroblasts/hpf). Any areas of diffuse large B-cell lymphoma or large cell transformation should be noted as a separate diagnosis since its management is different from that of follicular lymphoma. A biopsy is preferred for histologic grading; it cannot be performed on an FNA sample. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be taken for staging. Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for CD10, bcl-2, and bcl-6, in addition to B-cell markers. Neoplastic cells in follicular centers are positive for bcl-2, in contrast to reactive lymphoid follicles in most cases. Molecular and cytogenetic studies: PCR, FISH and cytogenetic studies usually show a t(14;18) involving the bcl-2 and IgVH genes. Rare cases may show a t(2;18) which involves bcl-2 and light chain genes. Rearrangement and mutations of the bcl-6 gene can be found in 15-40% of cases [18]. Immunoglobulin gene rearrangement is present. Cytogenetic abnormalities involving 1p, q, 10q, 17p, 7, 8, 12q, and X have been reported. Prognosis The follicular lymphoma international prognostic index (FLIPI) and international prognostic index (IPI) have been used to predict the outcome. Clinical stage, betamicroglobulin, LDH, histologic grade, amount of bone marrow involvement, and degree of large cell transformation are correlated with the prognosis. High levels of CD10 and bcl-6 expression are said to correlate with favorable survival, whereas the presence of more than 15 CD68+ cells/hpf suggests inferior overall survival. Abnormalities involving 6q23-26, 17p,

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Zhong Zhang and Maher Albitar

and 9p are correlated with a higher risk of large cell transformation. Other chromosomal abnormalities that are associated with poor outcome include del(1), dup(18q), and +12. Translocation of MYC along with bcl-2 suggests a very aggressive course. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which requires imaging study and bone marrow biopsy, are used to determine the response to therapy. From our point of view, if the primary tumor is positive for t(14;18), blood or serum detection of bcl-2 t(14;18) may be useful for early detection, or for monitoring disease response or recurrence. Immunoglobulin gene rearrangement studies can also be used to monitor disease progression at molecular level.

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Caveats 1. Occasionally, follicular lymphoma does not express CD10, but bcl-6 is usually positive, so we recommend determining both of these markers. 2. Bcl-2 expression can be negative (by IHC) in follicular lymphoma, especially in high-grade follicular lymphoma, possibly due to mutations that affect the antibody binding site [19]. Some follicular lymphomas do not have a rearrangement of bcl-2, but still show its overexpression due to other mechanisms. 3. Occasionally, lymphomas comprised of follicular center cells (positive for bcl-6 and CD10) grow in a diffuse pattern and do not show follicular formation. In these cases, the name of diffuse follicle lymphoma is used. 4. Although t(14;18) is most often seen in follicular lymphoma, not all lymphomas with t(14;18) are follicular. A bcl-2/IgH rearrangement is found in the peripheral blood of 25-75% of healthy donors and also in reactive follicles [20]. 5. Most pediatric cases are high grade, usually are bcl-2 negative, and lack t(14;18) [21]. 6. Occasionally, a lymph node with normal architecture has one or more follicles with bcl-2 overexpressing centrocytes and centroblasts. Those are called in situ follicular lymphoma, of which some later develop overt follicular lymphoma [22].

Marginal Zone B-Cell Lymphoma Diagnosis Morphology: Nodal marginal zone B-cell lymphoma is a low-grade, relatively rare B-cell lymphoma, usually comprised of small lymphoid cells, and most often seen in neck lymph nodes. Monocytoid B-cells may be prominent and expansion of the marginal zone is usually noted. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be performed for staging. Flow cytometry and immunohistochemistry: Nodal marginal zone B-cell lymphoma does not have a characteristic immunophenotype, but is usually a diagnosis of exclusion of other lymphomas. It is negative for CD5, CD10, bcl-6, and cyclin D1, but positive for all pan-Bcell markers.

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Methods for Diagnosis, Prognosis, and Monitoring of Lymphomas

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Molecular and cytogenetic studies: PCR, fish and cytogenetic studies do not usually show the t[11;18] and trisomy 3 associated with MALT lymphoma [23]. However, NCCN guidelines recommend that FISH or cytogenetics be done for t(11;18), t(11;14), t(14;18), and del(13q). The immunoglobulin gene rearrangement is present. Prognosis Because this disease is relatively rare, prognostic factors have not been well studied. In general, patients with nodal marginal zone lymphoma have an inferior survival rate to those with extranodal MALT lymphoma. The follicular lymphoma international prognostic index can be used to predict prognosis. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats

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1. Secondary involvement should be considered if any evidence of an extranodal or splenic lesion is present when a primary nodal marginal zone lymphoma is diagnosed. 2. In patients with MALT lymphoma, Hashimoto thyroiditis, or Sjögren's syndrome, the WHO classification suggests that nodal marginal zone lymphoma be considered as secondary involvement by MALT lymphoma. 3. When a lymphoma shows a follicular pattern, but is negative for CD10 and bcl-6, a marginal zone lymphoma with follicular colonization may be considered.

Burkitt Lymphoma Diagnosis Morphology: Burkitt lymphoma is a high-grade B-cell lymphoma usually comprised of monomorphous medium-sized lymphoid cells with a high mitotic rate. A starry sky pattern is usually present. A morphologic variant, atypical Burkitt lymphoma, shows greater pleomorphism, is part of the spectrum of Burkitt lymphoma or gray zone lymphoma that displays features of both Burkitt lymphoma and diffuse large cell lymphoma. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be performed for staging. Flow cytometry and immunohistochemistry: Burkitt lymphoma is characteristically positive for CD10, bcl-6, and B-cell markers, and is negative for bcl-2 and TdT. Nearly 100% of the cells are positive for ki-67. Molecular and cytogenetic studies: FISH and cytogenetic studies show MYC amplification, usually resulting from translocation between chromosome 8q24 and the immunoglobulin heavy or light chains. Breakpoints are different for endemic and sporadic forms [24]. Abnormalities in P53, P16, BCL8, and other genes have been reported but are not disease specific. EBV genomes are present in almost all endemic cases and some immunodeficiency-associated cases. EBER (in situ hybridization) is the method of choice for

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Zhong Zhang and Maher Albitar

EBV detection. Gene profiling studies have shown a distinct map of gene expression for Burkitt lymphoma [25]. Prognosis Three forms of Burkitt lymphoma are recognized: endemic, sporadic, and immunedeficiency associated. For endemic and sporadic forms, the tumors are aggressive but potentially curable, especially in early stages. An advanced clinical stage, high LDH level, abnormality of 1q, and expression of FLIP are correlated with poor outcome. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy.

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Caveats 1. MYC translocation is not entirely specific and can occasionally be seen in lymphoblastic lymphoma, follicular lymphoma, and some diffuse large B-cell lymphomas. 2. The differential diagnosis between Burkitt lymphoma and diffuse large B-cell lymphoma carrying MYC is important clinically. Most diffuse large B-cell lymphomas obtain MYC as a secondary change, meaning other genetic abnormalities are probably also present [26]. Although ki-67 can be high in diffuse large B-cell lymphoma, it usually doesn't reach 100%, and the morphology in most cases is different from Burkitt lymphoma. In addition, bcl-2 is usually negative in Burkitt lymphoma, but often positive in diffuse large B-cell lymphoma. However, it is not always easy to distinguish between these two entities. Gene expression profiles in recent microarray studies are different between these two tumors [27]. Interestingly, rare cases with a gene expression profile of Burkitt lymphoma do not carry MYC. The new WHO classification includes gray zone lymphoma, which has features of both diffuse large B-cell lymphoma and Burkitt lymphoma. 3. There are some Burkitt lymphoma cases that are negative for MYC translocation by FISH, even though morphologically they resemble Burkitt lymphoma [28].

Precursor B Lymphoblastic Lymphoma Diagnosis Morphology: Lymphoblastic lymphoma is a high-grade B-cell lymphoma usually comprised of monomorphous small to medium-sized lymphoid cells with a high mitotic rate and a diffuse growth pattern. According to the WHO classification, bone marrow blasts should be 25% or less, otherwise lymphoblastic leukemia with peripheral involvement is a more appropriate diagnosis. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be performed for staging.

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Diffuse Large B-Cell Lymphoma DIFFUSE LARGE B-CELL LYMPHOMA (DLBCL)

Diffuse Large B-cell Lymphoma, Not Otherwise Specified

Immunohistochemical Subgroups

CD5-positive DLBCL

Germinal Center B-cell-like (GCB)

Germinal center B-cell-like (GCB)

Activated B-celllike (ABC)

Non-germinal center B-cell-like (non-GCB)

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Molecular Subgroups

Diffuse Large B-cell Lymphoma Subtypes

Other Lymphomas of Large B-cells Primary mediastinal LBCL

Common Morphologic Variants

Rare Morphologic Variants

T-cell/histiocyterich LBCL

Intravascular LBCL

Centroblastic

Spindle cell

Primary DLBCL of the CNS

DLBCL associated with chronic inflammation

Immunoblastic

Signet ring cells

Primary cutaneous DLBCL, leg type

Lymphomatoid granulomatosis

EBV positive DLBCL of the elderly

ALK-positive LBCL

Anaplastic

Plasmablastic lymphoma

Borderline Cases

B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and Burkitt lymphoma B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and classical Hodgkin lymphoma

Large B-cell lymphoma arising in HHV-8 associated multicentric Castleman disease Primary effusion lymphoma

Figure 2B2. The new WHO classification of diffuse large B-cell lymphoma includes variants, subgroups, and subtypes/entities, such as diffuse large B-cell lymphoma (not otherwise specified), diffuse large B-cell lymphoma subtypes, other lymphomas of large B-cells, and borderline cases. The subtypes for diffuse large B-cell lymphomas include T-cell/histiocyte-rich large B-cell lymphoma, primary diffuse large B-cell lymphoma (DLBCL) of the CNS, primary cutaneous DLBCL, leg type, and EBV positive DLBCL of the elderly. Other lymphomas of large B-cells include primary mediastinal large B-cell lymphoma, intravascular large B-cell lymphoma, DLBCL associated with chronic inflammation, lymphomatoid granulomatosis, ALK positive LBCL, plasmablastic lymphoma, large B-cell lymphoma arising in HHV8-associated multicentric Castleman disease, and primary effusion lymphoma. Borderline cases include Bcell lymphoma with features intermediate between diffuse large B-cell lymphoma and Burkitt lymphoma, and also B-cell lymphoma with features intermediate between diffuse large B-cell lymphoma and Hodgkin lymphoma.

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Zhong Zhang and Maher Albitar

Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for CD34, TdT, CD19, cytoplasmic CD79a, and CD10. CD22 and CD20 are variable. Surface light chains are usually absent. Molecular and cytogenetic studies: FISH and cytogenetic studies usually show multiple abnormalities including hypodiploidy, hyperdiploidy, t(9;22), t(12;21), and t(1;19), and abnormalities involving MLL genes. Abnormalities in the ATM, P53, P16 and P18 genes have been reported but are not disease specific. Prognosis Hyperdiploid (51-65) and t(12;21) are generally associated with good prognosis. Hypodiploidy, t(9;22), an abnormality of the MLL gene, and t(1;19) usually predict poor prognosis. For more details, please see the chapter for precursor B lymphoblastic leukemia. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats B-cell gene rearrangement analysis is less useful in this tumor, because some T-cell lymphoblastic lymphoma, and sometimes even acute myeloid leukemia/myeloid sarcoma, can show immunoglobulin gene rearrangement, and T-cell receptor gene rearrangement can be positive in B-ALL as well [29-31].

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Diffuse Large B-Cell Lymphoma, Not Otherwise Specified Diagnosis Morphology: Diffuse large B-cell lymphoma is a high-grade B-cell lymphoma usually comprised of large lymphoid cells with their nuclear size equal to or exceeding normal macrophage/histiocytes, more than twice the size of a normal lymphocyte. The main cytologic variants include centroblastic, immunoblastic, and anaplastic DLBCL. They may rise de novo or represent transformation from other low-grade B-cell lymphomas. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be performed for staging. Flow cytometry and immunohistochemistry: This lymphoma is positive for Pan B-cell markers including CD20, CD19, and CD79a, but may lack one or more of these. Germinal center B-cell type is positive for CD10, or positive for Bcl-6 but negative for MUM-1. All other cases are considered non-germinal center B-cell type[32]. Molecular and cytogenetic studies: PCR, FISH and cytogenetic studies usually show abnormalities involving bcl-2 or bcl-6[26], and C-MYC is amplified in some cases. Gene profiling distinguishes two major subtypes: germinal center B-cell type and activated B-cell type [33;34].

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Prognosis This lymphoma is aggressive but potentially curable. A high proliferative rate, bcl-2, CCND2, SCYA2, and MUM1/CD138 expression, p53 overexpression, loss of 17p, 18q amplification, and an activated B-cell expression profile indicate a worse prognosis. Expression of Bcl-6/CD10, germinal center type, and expression of LMO2 and FN1 are associated with favorable prognosis. High FOXP1 and CD44v expression are also associated with poor outcomes. Immunoglobulin gene rearrangement in peripheral blood or bone marrow is associated with poorer survival. Beta-2-microglobulin is considered a major risk determinant in some centers; therefore it should be evaluated in addition to molecular genetic studies. Clinically, the international prognostic index is widely used. The germinal center Bcell type has a better prognosis than the non-germinal center B-cell type or activated B-cell type. Whether this is still true after addition of rituximab to the treatment regimen remains to be seen. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which requires imaging study and bone marrow biopsy, are used to determine the response to therapy. Assaying Bcl-2 or immunoglobulin rearrangement by PCR can also be performed.

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Caveats 1. Caution is advised in making a diagnosis of diffuse large B-cell lymphoma in tonsil or cervical lymph node in young adults, because infectious mononucleosis can mimic lymphoma in these areas. 2. The PCR based test for bcl-6 has limited use because large numbers of translocations and frequent somatic mutations are noted. 3. Expression of BCL-6 is usually associated with good prognosis. However, if the translocation partner of Bcl-6 is not IgH, then a worse prognosis is indicated. 4. When DLBCL involves bone marrow, it usually shows discordant morphology, which means small cell lymphoma in the bone marrow [35].

T-Cell/Histiocyte-Rich Large B-Cell Lymphoma See Figure 3, lymphoma with predominantly reactive cells and scattered neoplastic cells.

Primary Diffuse Large B-Cell Lymphoma of the CNS See Extranodal Lymphoma, CNS.

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EBV-Positive Diffuse Large B-Cell Lymphoma of the Elderly Diagnosis Morphology: EBV-positive diffuse large B-cell lymphoma of the elderly is a high-grade B-cell lymphoma. It has two morphologic variants, polymorphous and large cell; both subtypes show large transformed cells and geographic necrosis. Most reports came from Asian countries and are not associated with immunodeficiency [36]. Flow cytometry and immunohistochemistry: This lymphoma is usually positive for B-cell markers, and negative for CD10 and bcl-6. EBV is detectable and occasionally some cells are positive for CD30. Molecular and cytogenetic studies: IgH rearrangement is present. Prognosis It is an aggressive lymphoma and the international prognostic index predicts the prognosis. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats Some well defined lymphomas with EBV positivity are not included in this entity, such as lymphomatoid granulomatosis, plasmablastic lymphoma, and DLBCL associated with chronic inflammation.

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Primary Mediastinal Large B-Cell Lymphoma See Extranodal Lymphoma, mediastinum. Intravascular Large B-Cell Lymphoma See Extranodal Lymphoma, vessels. Diffuse Large B-Cell Lymphoma Associated with Chronic Inflammation See Extranodal Lymphoma, body cavity.

ALK-Positive Large B-Cell Lymphoma Diagnosis Morphology: ALK-positive large B-cell lymphoma is rare. It is comprised of large cells similar to immunoblasts or plasmablasts growing in a sinusoidal pattern, and involves the lymph nodes as well as extranodal sites.

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Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for CD138, CD38, EMA, and ALK, and is negative for CD20, CD3, or CD79a. Molecular and cytogenetic studies: B-cell gene rearrangement is usually present as well as t(2;17)(p23;q23) [37]. A few cases show t(2:5). Prognosis It is an aggressive lymphoma and most patients die within a year. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Plasmablastic Lymphoma See Extranodal Lymphoma, oral cavity.

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Large B-Cell Lymphoma Arising in HHV8-Associated Multicentric Castleman Disease Diagnosis Morphology: This lymphoma shows plasmablastic morphology in a context of Castleman disease. Most individuals with this have HIV and are infected with HHV8 [38]. Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for LANA-1, IgM, HHV-8, and lambda light chain, and is negative for CD138, pax5, and CD79a. CD38 and CD20 may be positive. Molecular and cytogenetic studies: B-cell gene rearrangement is usually present in frank lymphoma but can be negative at an early stage. Prognosis This is an aggressive lymphoma and patients die within months.

Primary Effusion Lymphoma See Extranodal Lymphoma, body cavity. B-Cell Lymphoma, Unclassifiable, with Features Intermediate between Diffuse Large B-Cell Lymphoma and Burkitt Lymphoma Diagnosis Morphology: This lymphoma has features of both DLBCL and BL; morphology is also intermediate between DLBCL and BL[39]. It excludes DLBCL with MYC amplification, or morphologic BL without demonstratable MYC rearrangement.

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Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for B-cell markers, CD10, and bcl-6. Bcl-2 is usually negative. Ki-67 is high, between 50% and 100%. Molecular and cytogenetic studies: B-cell gene rearrangement is usually present. Rearrangements of MYC, bcl-2, and bcl-6 are common. Prognosis This is an aggressive lymphoma. No optimal consensus therapeutic regimen has been established. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats 1. When BL morphology is noted but with positive bcl-2, a BL with both MYC and bcl2 rearrangement should be investigated. 2. Grey zone lymphoma is challenging and it is advised to have an expert opinion.

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B-Cell Lymphoma, Unclassifiable, with Features Intermediate between Diffuse Large B-Cell Lymphoma and Classical Hodgkin Lymphoma Diagnosis Morhology: This lymphoma includes a spectrum of diseases that have overlapping features of both Hodgkin lymphoma and DLBCL, mainly seen in mediastinum and lymph node [39-41]. Tumor cells usually grow in sheets and are pleomorphic. Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for CD30, CD15, CD20, CD79a, PAX5, Oct2, and Bob1, and is negative for CD45 (LCA) and ALK-1. Molecular and cytogenetic studies: Very few cases have been studied. Prognosis It is more aggressive than either Hodgkin lymphoma or DLBCL. There is no consensus on an optimal therapeutic regimen.

Angioimmunoblastic T-Cell Lymphoma (AILD) Diagnosis Morphology: Angioimmunoblastic T-cell lymphoma is a high-grade T-cell lymphoma arising in germinal center-derived T-cells (Th cells). It is usually comprised of polymorphous small to medium-sized lymphoid cells with a clear cytoplasm and shows diffuse growth pattern.

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T-Cell Lymphoma LYMPH NODE/BONE MARROW WITH PREDOMINANTLY NEOPLASTIC CELLS CD3+, CD20-, CD30-/+

T-CELL LYMPHOMAS (CD3+) NK CELL LYMPHOMAS (cCD3+) FCM/IHC for CD2, CD5, CD7 CD4, CD8, CD10, BCL6, TdT CD1a, CD56 TCR

Aberrant T-antigen expression CD10+, BCL6+, CXC L+ T-R+

Aberrant T-antigen expression TdT+ and/or CD1a+ T-R+ del(9p)

CD3-, cCD3+, CD2+/-, CD7+/-, CD56+ EBV+/T-R-

Pre-T ALL

NKL

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AILT

Aberrant T- antigen expression TdT-, CD1aCD10-, BCL6T-R+

PTL

FCM:Flow cytometry. IHC:Immunohistochemistry. AILT:Angioimmunoblastic T-cell lymphoma. Pre-T ALL:Precursor T lymphoblastic lymphoma/leukemia. NKL:Natural killer cell lymphoma. PTL:Peripheral T-cell lymphoma. T-R:T-cell receptor gene rearrangement.

Figure 2C. If lymphoma cells are positive for CD3 by flow cytometry or immunohistochemistry (T-cell lymphoma positive for surface CD3, and NK cell lymphoma negative for surface CD3 but positive for cytoplasmic CD3), the differential diagnosis should include angioimmunoblastic T-cell lymphoma, peripheral T-cell lymphoma, precursor T lymphoblastic lymphoma, and NK cell lymphoma. Immunostains for CD2, CD5, CD7, CD4, CD8, TdT, CD1a, and CD56 should be conducted. Analysis of CD10, bcl-6, T-cell receptor gene rearrangement, cytogenetics, and FISH may also be necessary.

50

Zhong Zhang and Maher Albitar CD30+ Lymphoma LYMPH NODE/BONE MARROW WITH PREDOMINANTLY NEOPLASTIC CELLS

CD30+, CD20-, CD3-

ALK+ TCR+ ALK Translacation+

ALCL

ALK-

FCM/IHC for CD2, CD5, CD4, CD8 CD7, CD79a, Pax5, CD43 T-R B-R

Some T-antigen expression T-R+

T-CELL LYMPHOMA or ALK-ALCL

Some B-antigen expression B-R+

B-CELL LYMPOMA

FCM: Flow cytometry. IHC:Immunohistochemistry. ALK-ALCL: ALK-negative anaplastic large cell lymphoma. ALCL: Anaplastic large cell lymphoma. T-R: T-cell receptor gene rearrangement. B-R: B-cell immunoglobulin gene rearrangement.

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Figure 2D. If the lymphoma cells are positive for CD30, and negative for CD3 and CD20 by immunohistochemistry, the differential diagnosis should include anaplastic large cell lymphoma, ALKnegative anaplastic large cell lymphoma, and certain B-cell and T-cell lymphomas. Stains for ALK, CD2, CD5, CD4, CD8, CD7, CD79a, and Pax5 should be performed to determine the lineage. In addition, FISH and cytogenetic studies for the ALK translocation and T-cell and B-cell gene rearrangements should be conducted at the same time or later.

Background cells include reactive lymphocytes, eosinophils, plasma cells, and histiocytes. A proliferation of endothelial venules, dendritic cells and immunoblastic B-cells are evident. Systemic symptoms, polyclonal hypergammaglobulinemia, skin rash, hepatosplenomegaly, and hemolytic anemia are often found clinically. Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for CD4, CD10, bcl-6, CXCL-13, and T-cell markers [42;43]. Some EBV positive B-cells are present. An expanded CD21 positive dendritic meshwork surrounds the venules. Molecular and cytogenetic studies: The T-cell receptor gene rearrangement is usually present. FISH and cytogenetic studies may show trisomy 3 and trisomy 5. Comparative genomic hybridization shows gains of 22q, 19, and 11q, and loss of 13q in some cases [44]. Prognosis AILD is an aggressive disease and patients die in a short period of time. The international prognostic index is widely used to predict outcome.

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Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which requires imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats 1. Even though this is a T-cell lymphoma, immunoglobulin gene rearrangement is sometimes present (20-30%), most likely representing EBV infected B-cell clonal expansion [45].

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Precursor T Lymphoblastic Lymphoma Diagnosis Morphology: Precursor T lymphoblastic lymphoma is a high-grade T-cell lymphoma usually comprised of monomorphous small to medium-sized lymphoid cells with a high mitotic rate and a diffuse growth pattern. According to WHO classification, bone marrow blasts should be 25% or less, otherwise lymphoblastic leukemia with peripheral involvement is a more appropriate diagnosis. It is found in lymph node but the mediastinum is a frequent place for this lymphoma. Flow cytometry and immunohistochemistry: This lymphoma is characteristically positive for CD34, TdT, CD99, and some T-cell markers. CD1a and coexpression of CD4 and CD8 are frequently seen. Surface CD3 can be negative but cytoplasmic CD3 is positive in the vast majority of cases. Molecular and cytogenetic studies: FISH and cytogenetic studies usually show multiple genetic abnormalities, including in the MYC, TAL1, RBTN1, RBTN2, and HOX11 genes, deletion 9p, and translocations involving T-cell receptors at 14q11.2, 7q35, and 7p14. Prognosis High leukocyte counts, age greater than 15 years old, and mass disease are associated with poor prognosis. Patients who have normal karyotype or t(10;14) are said to have a better prognosis. Patients who have ALL with expression of HOX11 have a favorable prognosis, and patients with expression of NUP214-ABL1 may benefit from tyrosine kinase inhibitor [46]. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats The T-cell receptor gene rearrangement may be positive, but is not lineage specific and thus cannot be used to determine cell lineage. In approximately 20% of cases, immunoglobulin gene is also clonally rearranged [47].

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Zhong Zhang and Maher Albitar

Natural Killer Cell Lymphoma Diagnosis Morphology: NK cell lymphoma is comprised of neoplastic natural killer cells. Primary NK cell lymphoma in a lymph node is rare. Most probably represent NK cell leukemia with lymph node involvement. Primary extranodal NK cell lymphoma is usually found in the nasopharyngeal area and blastic NK cell lymphoma (blastic plasmacytoid dendritic cell leukemia/hematodermatic leukemia) in skin. NK cell lymphomas are composed of monomorphous small to medium-sized lymphoid cells and grow in a diffuse pattern. Morphologically it is indistinguishable from T- or B-cell lymphomas, but it usually has blood or extranodal tissue involvement. The immunophenotype is important for diagnosis. Flow cytometry and immunohistochemistry: NK cell lymphoma involving lymph nodes is characteristically positive for CD16, CD56, CD25, and CD2 or CD7. It is negative for surface CD3 and other general T-cell markers, but positive for cytoplasmic CD3. Extranodal nasal NK/T cell lymphoma is positive for EBV, and blastic NK cell lymphoma is positive for CD4, CD56, and occasional myeloid markers [48;49]. Molecular and cytogenetic studies: T-cell receptor gene rearrangement is negative. Prognosis Most NK cell leukemia/lymphomas are aggressive, except for NK large granular lymphocyte proliferation, which is indolent.

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Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats 1. NK cells are negative for surface CD3, but can be positive for cytoplasmic CD3. By immunostains, this can look positive for CD3, but it displays a weak and more diffuse staining. 2. CD16, CD56, and CD57 are positive in NK-like T-cells, but these cells are also positive for surface CD3 and CD5, and positive for the T-cell receptor gene rearrangement. 3. Some nasal NK/T cell lymphomas are negative for CD56, but are always positive for cytotoxic granules and EBV [50]. 4. Systemic symptoms, enlarged nodes and liver, positive EBV, and negative CD57 are common in aggressive NK cell leukemia, whereas indolent NK cell disorder usually has few symptoms, negative EBV, and positive CD57 [51;52]. Blastic NK cell lymphoma/ hematodermatic leukemia is now a newly defined entity (blastic plasmacytoid dendritic neoplasm), and has an aggressive nature, although it expresses CD56 and CD4.

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Peripheral T-Cell Lymphoma, Not Otherwise Specified Diagnosis Morphology: Peripheral T-cell lymphoma is a general term for a T-cell lymphoma that does not fit any other well-defined classifications. The morphology of lymphoid cells varies significantly (pleomorphic, lymphoepithelioid, and T-zone), but generally the tumor is comprised of medium to large sized cells with pleomorphic nuclei. Increased high endothelial venules and inflammatory cells are usually found. By the time the tumor is discovered, most patients have advanced disease and systemic symptoms. Flow cytometry and immunohistochemistry: This lymphoma is positive for T-cell markers, and most cells are CD4 positive T-cells. Loss or aberrant expression of T-cell antigens is common, mostly involving CD5 and CD7. Molecular and cytogenetic studies: The T-cell gene rearrangement is usually positive. Although a number of cytogenetic abnormalities have been found, none of them are specific. Genomic hybridization shows gains and losses at multiple loci [53]. Prognosis The stage and bone marrow involvement are important prognostic indicators. International prognostic index is used in predicting outcomes. Deletions in 5q, 10q, and 12q are associated with better prognosis.

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Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats Multiple biopsies and analysis of T-cell receptor gene rearrangement may be needed to establish a diagnosis in difficult cases. Sometimes it is difficult to distinguish a peripheral Tcell lymphoma from an atypical T-zone hyperplasia if atypia is not prominent. It is always helpful to contact clinicians. One should be cautious to make a diagnosis if clinical symptoms are absent.

Anaplastic Large Cell Lymphoma Diagnosis Morphology: Anaplastic large cell lymphoma is a high-grade T-cell lymphoma usually comprised of large lymphoid cells that grow in a diffuse or sinusoidal pattern with “horseshoe” shaped nuclei. The common, the lymphohistiocytic, and the small cell variant are the three morphological types identified. It is most commonly found in lymph node, skin, bone, soft tissue, lung, and liver. Flow cytometry and immunohistochemistry: Anaplastic large cell lymphoma is characteristically positive for CD30 and ALK-1, and is usually negative for CD3 and CD7. It may be positive for CD2, CD5, and/or CD4, CD43, clusterin, EMA, and cytotoxic antigens. In some cases, this lymphoma is negative for all T-cell markers (the so called “null” type).

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Zhong Zhang and Maher Albitar

Molecular and cytogenetic studies: PCR, FISH and cytogenetic studies usually show a Tcell receptor gene rearrangement. Abnormalities have been identified involving chromosome 2, which hosts the ALK gene, including t(2;5), t(1;2), t(2;3), t(2;17), and Inv 2. Because of the complexity of the ALK translocations, FISH is probably a better test than PCR. Comparative genomic hybridization shows gains of 7, 17p, and 17q, and losses of 4, 11q, and 13q [54]. Prognosis Alk-1 positivity remains the most important prognostic factor, and is associated with a favorable outcome. The international prognostic index is also useful.

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Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats 1. Some T-cell lymphomas with a morphology and growth pattern similar to those of ALK-positive ALCL, which are positive for CD30 and negative for ALK-1, are currently placed as provisional entities. They are defined as ALK-negative anaplastic large cell lymphomas, to distinguish them from ALK-positive ALCL, and PTCL, NOS. In general, if a large cell lymphoma of a non-B-cell type expresses strong and homogenous CD30 and has ALCL morphology, it should be classified as ALKnegative ALCL. If both CD30 and CD15 are expressed, then it is not yet determined whether it is best classified as ALK-negative ALCL, or PTCL, NOS. Microarray studies suggest ALK-negative and ALK-positive ALCLs have different gene expression profiles [54;55]. In addition, gene expression of ALK-negative ALCL is different from that of peripheral T-cell lymphoma, enteropathy-type T-cell lymphoma, prolymphocytic leukemia, cutaneous ALCL, or adult T-cell leukemia. Therefore, ALK-negative ALCL may represent an independent entity from ALKpositive ALCL and other T-cell lymphomas. 2. Some non-hematopoietic tumors can also be positive for ALK, including rhabdomyosarcoma and inflammatory myefibroblastic tumor [56;57]. Plasma Cell Tumor Diagnosis Morphology: Plasma cell tumors found in lymph node may be from bone marrow as peripheral involvement by plasma cell myeloma, B-cell lymphoma with marked plasmacytic differentiation, or de novo plasmacytoma. One can recognize these tumors by morphology in most cases, because sheets of plasma cells are present. However, some immature plasma cell tumors can mimic large cell lymphoma. Flow cytometry and immunohistochemistry: This tumor is usually negative for CD19 and Pax5, but can be positive or partially positive for CD20. CD138, and CD38.

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Minimally differentiated Lymphoma LYMPH NODE/BONE MARROW WITH PREDOMINANTLY NEOPLASTIC CELLS CD20-, CD3-, CD30CD79a, PAX5, CD2, CD5, CD7, CD138, CD56, BCR, TCR

CD79a+ and/or PAX5+, B-R+

CD2+/-, CD5+/CD7+/-, T-R+

BCL

TCL

CD34+ and/ or TdT+

CD34+ and/ or TdT+

Pre-B ALL

Pre-T ALL

CD2+/-, CD7+/CD56+, T-REBV+/NKL

CD79a+, PAX5CD138+, B-R+ PCM

CD68+, LYZM+ HISTIOCYTIC TUMOR MONOCYTIC LEUKEMIA

NEGATIVE

CD68, LYZM, MPO, CD34 CD117, TRYPTASE, CD45 MPO+, CD34+/MYELOID SARCOMA

CD117+ TRYPTASE+

NEGATIVE

MAST CELL DISORDER

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NON-HEMATOPOIETIC TUMOR

BCL:B-cell lymphoma. TCL:T-cell lymphoma. BCR:B-cell immunoglobulin gene rearrangment. TCR:T-cell receptor gene rearrangement. NKL:Natural killer cell lymphoma. PCM:Plasma cell myeloma. ALL:Acute lymphoblastic leukemia/lymphoma. LYZM:Lysozyme. MPO:Myeloperoxidase.

Figure 2E. If tumor cells are negative for CD2, CD3, and CD30 by immunohistochemistry, the differential diagnosis should include certain B- and T-cell lymphomas, precursor lymphoblastic lymphomas, NK cell lymphoma, plasmacytoma, histiocytic/monocytic tumor, myeloid sarcoma, mast cell tumor, and of course, non-hematopoietic tumors. The next step would be to expand the tests to cover more T-cell, B-cell, and precursor cell markers, such as ALK, CD2, CD5, CD4, CD8, CD7, CD56, CD79a, Pax5, CD138, TdT, and CD34. The T- and B-cell gene rearrangements will then be able to determine the nature of the lymphoma in most cases. If the above markers are negative, it is unlikely that the tumor is a lymphoma or a plasma cell tumor, and additional stains are needed to rule out histiocytic/monocytic tumor, myeloid sarcoma, and mast cell disorder, including CD68, lysozyme, myeloperoxidase, CD117, and tryptase. If all the tests are still negative, a non-hematopoietic tumor should be explored. FISH and cytogenetic studies are always helpful and should be conducted at the same time or later. For more details regarding B-cell, T-cell, NK cell, and anaplastic large cell lymphomas, refer to titles under Figure 2B, 2C, and 2D, respectively..

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Zhong Zhang and Maher Albitar

If it is well differentiated, a light chain restriction can be demonstrated cytoplasmically by flow cytometry or IHC. An in situ hybridization study for light chain usually yields cleaner results. Molecular and cytogenetic studies: PCR usually demonstrates an immunoglobulin gene rearrangement. Prognosis See plasma cell myeloma chapter Monitoring See plasma cell myeloma chapter Caveats 1. When sheets of plasma cells are seen in a lymph node, a bone marrow biopsy is necessary to rule out plasma cell myeloma. Other lymphomas with plasmacytic differentiation, especially marginal zone lymphoma, should be ruled out before diagnosing a plasma cell tumor. 2. When sheets of plasmacytoid cells are identified with CD138 positivity, but light chain is negative (which are unusual findings for plasma cell tumor), metastatic carcinoma should be ruled out by a cytokeratin stain because many epithelial cell tumors can be positive for CD138. Non-secretory plasma cell tumor should also be investigated.

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Histiocytic Sarcoma Diagnosis Morphology: Histiocytic sarcoma is a rare, high-grade tumor usually comprised of large cells with pleomorphic nuclei, indistinguishable from large cell lymphoma. Flow cytometry and immunohistochemistry: Histiocytic sarcoma is characteristically positive for histiocytic/monocytic markers including CD68, lysozyme, CD14, CD163, and CD4. It is negative for B- and T-cell markers and myeloid markers. Molecular and cytogenetic studies: No clonal immunoglobulin or T-cell receptor gene rearrangements have been identified. Prognosis Histiocytic sarcoma is an aggressive tumor and responds poorly to therapy. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy.

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Caveats Myeloid sarcoma of monocytic lineage is immunophenotypically indistinguishable from histiocytic sarcoma. Whether histiocytic sarcoma is a separate disease from myeloid sarcoma is still debatable [58;59].

Myeloid Sarcoma Diagnosis Morphology: Myeloid sarcoma can occur de novo or concurrently with acute myeloid leukemia. It can be of blastic (blasts), immature (blasts and promyelocytes), or differentiated type (promyelocytes and more differentiated cells). Flow cytometry and immunohistochemistry: This tumor is positive for myeloid markers including CD13, CD33, CD117, and MPO. CD34 and lysozyme can also be positive. Molecular and cytogenetic studies: FISH and cytogenetic studies may sometimes show t(8;21) and inv(16). Prognosis Myeloid sarcoma arising in MDS or MPD offers a poor prognosis. However, isolated myeloid sarcoma without bone marrow or blood involvement may have prolonged survival.

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Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats Myeloid sarcoma in a late stage of differentiation may be negative for CD34, but it is always positive for lysozyme and/or myeloperoxidase.

Mast Cell Disorder Diagnosis Morphology: Extracutaneous mastocytoma, systemic mast cell disease, and mast cell sarcoma can all present in lymph node. These consist of sheets of mast cells, with clear to granular cytoplasm, and elongated to round nuclei. Eosinophilia, plasmacytosis and collagen fibrosis may be found. Flow cytometry and immunohistochemistry: This disorder is characteristically positive for tryptase and CD117. Other markers, such as CD33 and CD68, may also be positive, but CD14, T-cell, or B-cell markers are negative. Neoplastic mast cells have been reported to express CD2 and CD25 in contrast to normal mast cells [60]. Molecular and cytogenetic studies: PCR studies may show a mutation in the C-Kit gene [61].

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Zhong Zhang and Maher Albitar

Prognosis Mast cell leukemia and mast cell sarcoma are high-grade tumors, while systemic mast cell disease with cutaneous involvement is indolent. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy. Caveats The morphology of mast cell tumor in lymph node can be deceiving if one is not familiar with it. One clue is provided by flow cytometry study, which usually shows CD117-positive cells in mast cell tumor, but this can also be seen in myeloblasts, plasma cells, and erythroids.

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Classical Hodgkin Lymphoma Diagnosis Morphology: Classical Hodgkin lymphoma is a specific form of B-cell lymphoma characteristically comprised of Hodgkin cells or Reed-Sternberg cells in a mixed reactive background. Four subtypes are identified based on morphology: lymphocyte rich, nodular sclerosis, mixed cellularity, and lymphocyte depleted. Whenever a diagnosis is established, a 2 cm bilateral core biopsy should be performed for staging. Flow cytometry and immunohistochemistry: Classical Hodgkin lymphoma is characteristically positive for CD30, fascin, vimentin, MUM1, and HGAL, and negative for CD45 (LCA). CD15 and EBV (LMP1) are positive in some cases. It is also weakly positive for Pax5. Bob1 and Oct2 are either negative or only one of them positive. Flow cytometry is not routinely used to detect Hodgkin lymphoma due to paucicellularity and the large size of tumor cells. Molecular and cytogenetic studies: A majority of classical Hodgkin lymphoma contains immunoglobulin gene rearrangements, but they may not be detected by whole tissue PCR due to the paucicellularity of the tumor cells. They can only be detected by microdissection [62]. Genomic hybridization shows distinct gains and amplifications in certain chromosomes [63]. Prognosis The stage, systemic symptoms and tumor burden are predictors of prognosis. With modern therapy, there is no significant difference in survival between the subtypes. Some studies suggest bcl-2 and MAL expression is associated with poor prognosis, while HGAL expression is associated with improved survival. Overexpression of bcl2, p53, BAX, and ki67 suggests shorter survival. The response after therapy is also an important prognostic factor. Monitoring According to NCCN revised guidelines, nodal masses, nodules in spleen/liver, and bone marrow involvement, which require imaging study and bone marrow biopsy, are used to determine the response to therapy.

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Caveats Although flow cytometry is not employed to detect Hodgkin lymphoma, it useful to detect small lymphocytic lymphoma that sometimes accompanies Hodgkin lymphoma. Hodgkin Lymphoma LYMPH NODE/ WITH PREDOMINANTLY REACTIVE CELLS AND SCATTERED NEOPLASTIC CELLS

CD30, CD15, CD45 (LCA), CD20, Pax5. Bob1, Oct2

CD30+, CD15+/-, CD45-, CD20-/+, Bob1-/+, Oct-/+, Pax5 weakly+

CD30-/+, CD15-, CD45+, CD20+, Bob1+, Oct2+, Pax5 strongly+

CHL

NLPHL or TCRBL

BCL6, IgD, CD21, CD3, CD57, CD4, CD8, B-R

Neoplastic cells BCL6+ and surrounded by CD57+ T-cells Background mainly IgD+ B-cells Expanded CD21 dendritic meshwork B-R-

Neoplastic cells BCL6+/Background mainly CD4+ T-cells Background B-cells