Precision Molecular Pathology of Aggressive B-Cell Lymphomas (Molecular Pathology Library) 3031468414, 9783031468414

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Molecular Pathology Library Series Editor: Timothy C. Allen

Genevieve M. Crane Sanam Loghavi Editors

Precision Molecular Pathology of Aggressive B-Cell Lymphomas

Molecular Pathology Library Series Editor Timothy C. Allen, Department of Pathology Univ of Mississippi Medical Center Jackson, MS, USA

Creating a diagnostic, prognostic, and therapeutic treatment strategy precisely tailored to each patient’s requirements is the fundamental idea behind precision medicine. The Molecular Pathology Library series integrates molecular biology with clinical data for treatment designed for the patient’s individual genetic makeup. This approach is widely recognized as the future of medicine and it is vital for practicing pathologists to know the molecular biology, diagnostics and predictive biomarkers for specific forms of cancer or other diseases and their implications for treatment. Each volume focuses on a specific type of cancer or disease and provides concise essential information in a readily accessible, user friendly, convenient format. Each volume is oriented towards the pathologist who needs this information for daily practice, tumor boards, and conferences or for preparation for certification boards or other tests. Written by experts focusing on patient care, these books are indispensible aids to pathologists’ participation in precision medicine in the 21st century.

Genevieve M. Crane  •  Sanam Loghavi Editors

Precision Molecular Pathology of Aggressive B-Cell Lymphomas

Editors Genevieve M. Crane Pathology and Laboratory Medicine Institute Cleveland Clinic Cleveland, OH, USA

Sanam Loghavi Department of Hematopathology The University of Texas, MD Anderson Cancer Center Houston, TX, USA

ISSN 1935-987X     ISSN 1935-9888 (electronic) Molecular Pathology Library ISBN 978-3-031-46841-4    ISBN 978-3-031-46842-1 (eBook) https://doi.org/10.1007/978-3-031-46842-1 © Springer Nature Switzerland AG 2023, corrected publication 2024 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

We would like to dedicate this book to all the authors who generously gave of their time and expertise to continually update this text during production. Their efforts helped to ensure that the most recent advances in our understanding of the molecular landscape of aggressive B-cell lymphomas are included and placed in context of the revised classification systems. We also thank Dr. Philip Cagle, MD and Dr. Timothy C. Allen, MD, JD for their vision and support in production of this series, facilitating education, translational research, and clinical care in this rapidly evolving and increasingly critical area of pathology. Genevieve M. Crane, MD, PhD Sanam Loghavi, MD

Foreword

In the preface to the very first edition of the Molecular Pathology Library series in 2007 Dr. Philip T. Cagle noted that molecular diagnostics and therapeutics impacts every field of medicine. Now, more than a decade and a half later, Dr. Cagle’s words remain true, and even more relevant, as the unprecedented, exponential explosion of knowledge of molecular biology has led to extraordinary and continuing diagnostic, prognostic, and therapeutic advancements, involving diseases from essentially every organ system. The Molecular Pathology Library series books will continue to provide, as it has with each book for over a decade and a half, (1) succinct background of the essential terminology, concepts, and technology of molecular biology; (2) an overview of the broad application of molecular biology principles to disease; and (3) specific application of molecular pathology to the pathogenesis diagnosis, and treatment of neoplastic and nonneoplastic diseases specific to each organ system. Each book will continue to bridge the gap between basic science and clinical understanding and practice and serve the basic scientist, the clinical researcher, and the practicing physician or other health care provider who require more understanding of the application of basic research to patient care, from “bench to bedside.” Department of Pathology Corewell Health’s Beaumont Hospital Royal Oak, MI, USA

Timothy C. Allen

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Preface

Aggressive B-cell lymphomas comprise a diverse group of neoplasms, which differ in their pathology, clinical course, and response to treatment. Recent advances continue to improve our understanding of their underlying mechanisms, enable potential refinement to diagnostic categories, and yield information relevant to treatment. This text was developed to help synthesize the most relevant and impactful data emerging from the literature and make it readily accessible to practicing physicians, trainees, and researchers. To better place this information in context, the text includes detailed methods chapters to help clarify modern molecular techniques. These summaries feature a number of high-quality figures to simplify complex concepts and are designed to be of value to both trainees, who may be learning this material for the first time, and to practicing physicians, who may have completed training before these methods were developed. A better understanding of the advances in molecular methods will enhance the ability of the reader to interpret and incorporate additional molecular data they may encounter in daily practice and as new findings emerge in the literature. The text uses an evidence-based approach. The goal was to place emerging and established molecular and cytogenetic findings in context of the known biology of each lymphoma, its diagnostic features, and the current treatment strategies. As such, the text provides an important link between molecular pathologists, cytogeneticists, hematopathologists, treating hematologist/oncologists, and lymphoma researchers. The aim is to encourage cross-specialty pollination of ideas, coordination of care, and potentially stimulate further research as underlying mechanisms are further clarified. Some entities are less well evaluated than others, and areas of knowledge gaps are highlighted to encourage further investigation. Importantly and now at the forefront of discussion within the field of hematopathology are the revisions to diagnostic categories. The wave of molecular data has had a particular impact on our understanding of aggressive B-cell lymphomas, which may result in substantial benefit for patients given the heterogenous nature of this category of disease. Better subclassification and improved prognostic markers may allow more focused clinical trials and ultimately the potential for greater success in response to therapy. This book will review the changes introduced in the ix

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fourth revised edition of the World Health Organization (WHO) monograph published in 2017 as well as further modifications in the fifth Edition WHO and the International Consensus Classification, both initially released in 2022. The text is overall divided into five parts. In Part I, a brief history of aggressive B-cell lymphomas and landmark events in their classification and treatment are given in order to place the substantial advances in the field in context. This is followed by a summary of key changes aggressive B-cell lymphoma classification, including the introduction of high-grade B-cell with MYC and BCL2 and/or BCL6 rearrangements in the revised 2017 WHO monograph, which is now appreciated to be better characterized as a distinct process only in the context of combined MYC and BCL2 rearrangements in the fifth Edition WHO and International Consensus Classification. Categorization of diffuse large B-cell lymphoma according to cell of origin is also now required for most clinical trials but may be soon supplanted by a molecular characterization based on mutational landscape which partially correlates with the cell of origin data. Part II of the text reviews molecular pathology methods, including the increasing use next-generation sequencing techniques in clinical practice. A baseline knowledge of these testing methods is essential for interpreting the results. The sensitivity, potential artifacts, and pitfalls differ between the particular mutation under investigation, sample type, and expected allele frequency. Gene expression profiling is also variably used in the clinical setting with potential challenges as well as opportunities to better detect certain mutations and gene fusions by their transcribed RNA products. Parts III and IV focus on individual subtypes of aggressive B-cell lymphoma, including a summary of the diagnostic criteria and key pathologic and clinical features for each entity. Importantly, a synthesis of recent literature related to molecular data that may impact diagnosis or clinical management of the disorder is also given. Any gaps in knowledge, challenges to implementing testing or conflicting data from existing reports are also highlighted. Part IV focuses on lymphoproliferative disease arising in the setting of immune suppression. These processes are more likely to be viral-driven (e.g., Epstein-Barr virus or Kaposi sarcoma herpesvirus/ human herpesvirus-­8 related), which may reduce the mutational burden required for tumor initiation. In addition, these processes may show unique biologic features and may respond to restoration of immune function in some cases. Finally, Part V focuses on emerging molecular technologies that may significantly impact clinical practice. Of these, circulating or the so-called cell-free DNA has generated considerable interest due to the potential to assess for residual disease or evolution of disease without the need for a tissue biopsy. Neoplastic cells with a high cell turnover may also release a larger amount of cell-free DNA into circulation as compared to normal tissue counterparts. This DNA can be evaluated from the blood for the presence of a known clonal immunoglobulin rearrangement or mutational pattern to assess residual disease and/or response to therapy. The logistics of this exciting technique remain challenging outside of the research setting but are rapidly evolving. Potential pitfalls and applications of this technique as well as other emerging technologies are discussed.

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As the most up-to-date text on the molecular pathology of aggressive B-cell lymphomas and including the most recent revisions from the fifth Edition WHO and 2022 International Consensus Classification diagnostic categories, this text will be an important resource for trainees, pathologists, hematologists/oncologists, other clinicians involved in lymphoma care, and lymphoma researchers. It provides a comprehensive yet concise synthesis of emerging molecular advances that inform patient care and improve understanding of disease mechanisms. All chapters are contributed by experts in the field. We sincerely hope that you will find this resource useful and informative. Cleveland, OH, USA Houston, TX, USA 

Genevieve M. Crane Sanam Loghavi

Contents

Part I Background 1

 Historical Perspectives in B-Cell Lymphoma Classification: From Hodgkin to WHO��������������������������������������������������������������������������    3 Michael E. Kallen, Sanam Loghavi, and L. Jeffrey Medeiros

2

 Revisions to the Classification of Aggressive B-Cell Lymphomas ������   17 Michael E. Kallen and Rima Koka

Part II Methods 3

 Cytogenetics and FISH in Precision Molecular Pathology of Aggressive B-Cell Lymphomas ��������������������������������������������������������������   39 Yi Ning and Jocelyn Reader

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 Introduction to Next-Generation Sequencing ��������������������������������������   47 Tauangtham Anekpuritanang, Philipp W. Raess, and Richard D. Press

5

 Next-Generation Sequencing-Based Methods for the Detection of B-Cell Clonality������������������������������������������������������������������������������������   83 Karin P. Miller and Rena R. Xian

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 Next-Generation Sequencing Detection of Copy Number Variants and Translocations��������������������������������������������������������������������  103 James P. Solomon and Wei Song

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 RNA-Seq and RNA Expression Profiling����������������������������������������������  113 Michael M. Franklin, Laura N. Toth, and Devon Chabot-Richards

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 Flow Cytometry Applications in the Diagnosis and Classification of Aggressive B-Cell Lymphoma������������������������������������  125 Hong Fang and Sa A. Wang

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Part III Molecular Characteristics of Specific Large B-Cell Lymphoma Subtypes 9

High-Grade B-Cell Lymphomas������������������������������������������������������������  145 Alisha D. Ware and Michael J. Borowitz

10 Precision  Medicine in Burkitt and Burkitt-­Like Lymphomas������������  159 Shunyou Gong 11 Precision  Medicine in Diffuse Large B-Cell Lymphoma����������������������  179 Siba El Hussein and Francisco Vega 12 Mediastinal  Gray Zone Lymphoma ������������������������������������������������������  213 Julie Y. Li, Laura M. Wake, and Gang Zheng 13 Special  Sites: Primary Mediastinal Large B-Cell Lymphoma, Primary CNS Diffuse Large B-Cell Lymphoma, and Primary Testicular Diffuse Large B-Cell Lymphoma������������������������������������������  221 Tatyana Gindin and Shafinaz Hussein 14 Primary  Cutaneous Diffuse Large B-Cell Lymphoma, Leg Type ������  245 Mushal Noor and Gabriel C. Caponetti 15 Epstein-Barr  Virus-Positive Diffuse Large B-Cell Lymphoma, Not Otherwise Specified��������������������������������������������������������������������������  263 Mahsa Khanlari and Pei Lin 16 Lymphomatoid Granulomatosis ������������������������������������������������������������  281 Christian Salib and Julie Teruya-Feldstein 17 T-Cell/Histiocyte-Rich  Large B-Cell Lymphoma����������������������������������  295 Kirill A. Lyapichev and Joseph D. Khoury 18 ALK  Positive Large B-Cell Lymphoma ������������������������������������������������  305 Sharmila Ghosh, Christian Salib, and Julie Teruya-Feldstein 19 HHV8-Positive  Diffuse Large B-Cell Lymphoma, Not Otherwise Specified/KSHV/HHV8-Positive Diffuse Large B-Cell Lymphoma������������������������������������������������������������������������������������  315 Michael E. Kallen and Sanam Loghavi 20 Large  B-Cell Lymphomas with IRF4 Rearrangements ����������������������  329 Rajeswari Jayakumar and Laura M. Wake 21 Diffuse  Large B-Cell Lymphoma Associated with Chronic Inflammation and Fibrin-Associated Large B-Cell Lymphoma ��������  339 Jonathon Gralewski and Daniel Babu

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Part IV Immune Deficiency Related Lymphoproliferative Disease 22 Plasmablastic Lymphoma ����������������������������������������������������������������������  353 Mehrnoosh Tashakori and Sanam Loghavi 23 Genetic  Landscape of Post-transplant Lymphoproliferative Disorders��������������������������������������������������������������������������������������������������  359 Rima Koka and Michael E. Kallen 24 Epstein-Barr Virus-Positive Mucocutaneous Ulcer������������������������������  379 Tapan Bhavsar Part V Emerging Molecular Technologies 25 Circulating  Tumor DNA in Lymphoma ������������������������������������������������  395 Jialing Huang and Christopher D. Gocke  Correction to: Epstein-Barr Virus-Positive Diffuse Large B-Cell Lymphoma, Not Otherwise Specified. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C1 Mahsa Khanlari and Pei Lin Index������������������������������������������������������������������������������������������������������������������  427

About the Authors

Genevieve M. Crane, MD, PhD  completed her undergraduate work at Rice University in chemical engineering, followed by a Marshall Scholarship at the University of London. She pursued MD and PhD degrees at the University of Michigan, where her graduate work in Cell and Molecular Biology was recognized by a Harold Weintraub Award as one of the most outstanding in the country. She completed residency training at Johns Hopkins Hospital in anatomic pathology and a fellowship in hematopathology. In the course of training, she also did postdoctoral research fellowships at MIT and University of Texas Southwestern Medical Center investigating mouse models of cancer, stem cells, and metabolism. She has more than 60 peer-reviewed publications, two textbooks (Survival Guide to Lymph Node Pathology, Innovative Science Press and Biopsy Interpretation of the Bone Marrow, Wolters Kluwer), multiple textbook chapters, two patents and is invited to speak nationally and internationally based on her expertise. She serves on multiple editorial boards including as Section Editor for Hematopathology at Archives of Pathology and Laboratory Medicine and Deputy Editor in Hematopathology at PathologyOutlines.com. She is passionate about pathology education and outreach, including through the Society of Hematopathology, College of American Pathologists and International Clinical Cytometry Society where she has served on several committees. Sanam  Loghavi, MD  completed her MD degrees at Azad University of Medical Sciences in Tehran Iran followed by AP/CP residency training at Cedars-Sinai Medical Center in Los Angeles, CA. She completed fellowships in surgical pathology, hematopathology, and molecular pathology at MD Anderson Cancer Center (MDACC) in Houston Texas, where she is currently on staff as an Associate Professor in the Department of Hematopathology and the Medical Director of the ECOG-ACRIN Leukemia Bank at the Central Biorepository and Pathology Facility at the Department of Translational Molecular Pathology at MDACC.  She has more than 200 peerreviewed publications and multiple book chapters. She serves regularly as a speaker and session chair at national and international pathology meetings with focus on hematopathology and molecular pathology topics. Dr. Loghavi is the Editor-in-Chief for the ASH American Society of Hematology (ASH) Image bank and serves as a member of several organizational committees including the ASH Publications Committee, College of American Pathologists (CAP) HPATH Committee, and International Clinical Cytometry Society (ICCS) Education Committee.

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Part I

Background

Chapter 1

Historical Perspectives in B-Cell Lymphoma Classification: From Hodgkin to WHO Michael E. Kallen, Sanam Loghavi, and L. Jeffrey Medeiros

Early History For the beginnings of B-cell lymphoma classification, we hematopathologists are forced to fast forward through several millennia of history to one of the founding fathers of our field, Thomas Hodgkin, a brilliant anatomist credited with the first description in 1832 of what we now recognize as lymphoma [1]. Dr. Hodgkin was one of the leading physicians of the nineteenth century. His academic brilliance and professional focus laid in careful correlation of clinical diseases and macroscopic pathological findings, and he curated an extensive catalogue of over 1600 gross specimens [2]. In addition to an impressive set of muttonchop sideburns [3], Dr. Hodgkin had a penchant for publicly speaking his mind on controversial topics of the day, ranging from medical education reform to social injustices practiced on underprivileged ethnic groups; the latter quality may have costed him professional opportunities and made him unpopular with his colleagues [2]. Besides his classic namesake description of Hodgkin disease, his writings included numerous reports far ahead of their time on subjects, including one of the earliest descriptions of aortic incompetence, “lardaceous disease” (subsequently recognized as amyloidosis), a blueprint for randomized controlled trials, and even a plug for the metric system [3]. An important subsequent milestone was the independent descriptions in 1898 and 1902 by Carl Sternberg and Dorothy Reed, of the characteristic binucleate cells in Hodgkin disease [4, 5]. Hodgkin disease was at the time thought to be M. E. Kallen (*) Department of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA e-mail: [email protected] S. Loghavi · L. J. Medeiros Department of Hematopathology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_1

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inflammatory and possibly related to tuberculosis, though Dorothy Reed disagreed [6]. In addition to accurate drawings of today’s Reed-Sternberg cells, she made key clinicopathological observations, which remain true, including an early peak in children and young adults, excellent general health prior to disease onset, and painless progressive cervical adenopathy without leukemia [6–8]. Despite her fascination with pathology and passion for investigative work, Dr. Reed ended up leaving the field, severely frustrated at the injustice of being unable to secure a teaching post at Johns Hopkins as a woman (an injustice they have since rectified and continue to reform [9]). She instead switched into pediatrics and had substantial impact in maternal and infant care, despite personal setbacks including a rocky love affair and the tragic deaths of two of her children [8]. In a poetic twist, there is speculation that Dr. Reed’s love interest may have been William MacCallum, her coworker in pathology at Johns Hopkins who later became chairman of the department, and whose 1916 “Textbook of Pathology” [10] prominently and repeatedly associates Dr. Reed’s name with Hodgkin disease for the first time; Dr. Reed may have given him her heart, and in return he gave her international fame [8]. The decades immediately afterwards brought several attempts at lymphoma classification schemes, with a focus on broad groupings based primarily on morphological features. The first such classification scheme for lymphoma widely used in the United States was proposed by Gall and Mallory in 1941, based on 618 cases reviewed at Massachusetts General Hospital [7, 11]. Their scheme included the categories of stem cell lymphoma, clasmatocytic lymphoma (these first two types were grouped into an entity called reticulum cell sarcoma), lymphoblastic lymphoma, lymphocytic lymphoma, Hodgkin’s lymphoma, Hodgkin’s sarcoma, and follicular lymphoma [11]. The scheme recognized follicular lymphoma as a distinct entity based off of available reports [12, 13], with large cell progression also known at the time [14]. Though limited by lack of immunologic (much less genetic) data, many of these early terms remain in today’s modern classification. The scheme also separately recognized Hodgkin disease, which was subclassified by Jackson and Parker in 1944 into the three types of Hodgkin’s paragranuloma, granuloma, and sarcoma [15]. Another highly prominent figure of the field, Dr. Henry Rappaport, proposed a classification scheme in 1956 [16], which was further developed in the Armed Forces Institute of Pathology (AFIP) Fascicle of 1966 [17]. The Rappaport classification replaced the term “follicular” with “nodular”, placing emphasis on the growth pattern of nodular versus diffuse and thereby losing Gall and Mallory’s distinct entity of follicular lymphoma, and then split nodular lymphomas into four categories: well-differentiated lymphocytic, poorly differentiated lymphocytic, histiocytic, and mixed lymphocytic and histiocytic [7]. At the same time, Lukes and Butler published a classification scheme for Hodgkin disease [18], refining the three Jackson and Parker subtypes into the six categories of lymphocytic and/or histiocytic (L&H) nodular, L&H diffuse, nodular sclerosis, mixed, diffuse fibrosis, and reticular. A nomenclature committee shortly thereafter combined both the nodular and diffuse L&H subtypes into a “lymphocyte predominant” subtype, and the diffuse fibrosis and reticular subtypes into a “lymphocytic depletion” subtype, thus

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reorganizing classification into the four histological subtypes of lymphocytic predominance, nodular sclerosis, mixed cellularity, and lymphocytic depletion [19]. This classification scheme has held up remarkably well into the modern era, and its basic principles have been supported by subsequent biological studies [7].

Early Modernity The 1960s and 1970s saw the beginnings of the immunologic revolution in hematopathology, with the discovery of multiple distinct lymphocytic lineages (B, T, and NK) which were morphologically similar but functionally different and separable by antigen expression. Surface antigens were identified on lymphoid cells, which could be used to assign lineage in both normal and neoplastic cells, leading to recognition that lymphomas were tumors of the immune system [20–24]. In a seminal publication in 1974, Dr. Elaine Jaffe and colleagues at the National Institutes of Health demonstrated B-cell immunoreactivity in six patients with “nodular lymphoma”, via cell suspensions and frozen sections, suggesting their follicular B-cell origin [25], and providing some of the first evidence that neoplastic lymphoid cells recapitulated the functional properties of their predecessors [26]. Similar work demonstrated high levels of IgM in “reticulum cell sarcomas” and thus B-cell derivation [27], and T-cell derivation in most lymphoblastic lymphomas [21, 22]. The emerging immunologic data was quickly applied to lymphoma classification, leading to multiple new schemes, most significantly that of Karl Lennert in Kiel, Germany [7]. The Kiel classification, first published in 1974, grouped lymphomas by degree of differentiation into low-grade malignancies with a predominance of small cells or “-cytes” and high-grade malignancies with a predominance of “-blasts” [7, 28]. This scheme caught on in Europe, but the Rappaport classification remained popular in the United States, causing difficulty in comparing data between centers, and creating a fractured political situation and generalized confusion. Attempts at reaching consensus, the last of which happened in 1975 at Airlie House in Virginia [29], ultimately failed, leading to a Working Formulation [30] to translate between the six separate existing schemes. This Working Formulation stratified lymphomas by clinical outcome, with categories following the Rappaport scheme, terminology from Lukes and Collins [31], and no immunophenotypic data. The end result was a collection of unnecessarily heterogeneous categories containing both B- and T-cell lymphomas based on questionable and non-reproducible morphological distinctions [32]. The Working Formulation was a step backwards, but nevertheless became popular in the United States. Kiel was used in Europe and Asia, and some centers used Lukes-Collins [7]. The political morass remained unresolved until new technologies and a consensus-minded approach could readdress the stalemate.

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Technological Advances The immunologic revolution arguably began with Kohler and Milstein’s 1975 discovery of hybridoma technology [33], which allowed creation of monoclonal antibodies, and for which they were awarded the 1984 Nobel Prize in physiology or medicine. The new technology allowed the development of a broad array of antibodies, which were organized using the “clusters of differentiation” (CD) nomenclature in a series of workshops [34–36]. These markers now number in the hundreds and are near and dear to hematopathologists the world over. The technology’s dramatic impact was furthered by the application of monoclonal antibodies to evaluation of formalin fixed paraffin embedded tissue (FFPE), providing easier implementation and superior morphological characterization, and allowing rapid and widespread adoption by pathology laboratories. In addition to its enormous impact through immunohistochemistry, monoclonal antibodies were dramatically useful in the newly developed technology of flow cytometry, which would go on to transform hematopathology. The invention of the first flow cytometer is credited to Mack Fulwyler (see Fig. 1.1), an electrical engineer at Los Alamos Scientific Laboratory (Los Alamos, New Mexico), who was initially interested in disproving a colleague’s idea that a subset of red blood cells could be separated by manipulating the current in a Coulter counter [38]. To do so, Fig. 1.1  Dr. Mack Fulwyler. (Image is reprinted with permission from Purdue Cytometry Volume 10, 2007, J. Paul Robinson for the Purdue University Cytometry Laboratories, West Lafayette, IN. ISBN 978-1-890473-10-5. http:// www.cyto.purdue.edu/ cdroms/cyto10a/copyright. html [37])

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he conceived of and developed the first flow cytometer (deflected droplet cell sorter) in collaboration with Richard Sweet, inventor of the technology behind ink jet printers [39]. Fulwyler’s seminal publication in 1965 was so novel that it contained a mere five references [40]. The technology was quickly combined with monoclonal antibodies and fluorescent dyes, allowing distinction of lymphocyte subsets among a heterogeneous mixture, called “fluorescence activated cell sorting” (FACS) [39], and now ubiquitous in hematology. Multiparameter techniques have expanded from 1 to 2 in the 1970s to more than 30 parameters today [41], with 8–10 color systems being commonplace in many clinical laboratories as of this writing. Flow cytometry has additionally expanded into genetics, with the development of techniques such as flow karyotyping, allowing chromosome sorting and measurement of genetic material, apoptosis, and cell division [37]. Meanwhile, emerging developments in genetic testing techniques would rapidly propel both our diagnostic abilities and biologic understanding of lymphoid neoplasms. Fluorescence in situ hybridization (FISH) and polymerase chain reaction (PCR) technologies allowed direct testing of FFPE for specific genetic alterations, immediately expanding the ability to evaluate specimens beyond the limits of conventional karyotype testing, and also over the requirement for fresh or snap frozen samples. The discoveries of characteristic alterations in several types of B-cell lymphomas—t(8;14)(q24;q32) in Burkitt lymphoma [42], t(14;18)(q32;q21) in follicular lymphoma [43], t(11;14)(q13;q32) in mantle cell lymphoma [44, 45]—provided targets that lent themselves to FISH testing, and argued strongly for their separate diagnostic categories. PCR testing for rearrangement of the immunoglobulin and T-cell receptor genes allowed establishment of clonality, and in the case of B-cell lineage, stage of differentiation. In 1994, immunoglobulin gene rearrangement testing was able to definitively establish Hodgkin disease as a B-cell neoplasm; and resolve a long-standing question in hematopathology dating back to Thomas Hodgkin himself [46, 47]. The relative paucity of malignant Reed-Sternberg cells was a perennial limitation and was overcome by use of the microdissection technique to isolate single cells for PCR testing. Of ongoing interest in the biology of Hodgkin’s lymphoma is the downregulation of the B-cell gene expression program in Reed-Sternberg cells.

The REAL and the WHO Classifications The unfortunate political stalemate of the mid to late twentieth century began to crack in 1991 with the formation of the International Lymphoma Study Group (ILSG) by Drs. Peter Isaacson and Harald Stein [7]. The group’s first consensus report used a combination of morphological, immunophenotypic, and cytogenetic data to define the category of mantle cell lymphoma (MCL), and importantly, noted the tumor’s characteristic clinical profile [48]. The new diagnostic category of MCL was to replace the overlapping and imprecise terms previously in use from competing classification schemes—centrocytic, intermediate, and diffuse small-cleaved

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cell lymphoma—and paved the way for a unified classification using a multidisciplinary and international consensus-based approach. The ILSG’s next meeting in 1992 defined the category of nodular lymphocyte predominant Hodgkin’s lymphoma as distinct from classic Hodgkin’s lymphoma [49]. From there, the group set its sights on defining as many lymphoid neoplasms as possible. The resultant scheme in 1993 was called the Revised European-­ American Classification of Lymphoid Neoplasms (REAL classification) [50], representing a paradigm shift in hematopathology, and a vast improvement over the existing schemes. Notably, the REAL classification recognized the breadth and complexity of lymphoma as too much for a single pathologist and was, therefore, based on a consensus of perspectives from all 19 contributing members. REAL also for the first time incorporated genetic findings, clinical information, and immunophenotypic data, in a novel comprehensive and integrative approach, which is now a cornerstone of the field [51]. The focus of the REAL classification significantly shifted from prior schemes, in recognizing lymphomas as a heterogeneous landscape of distinct entities, each with a range of morphological features and clinical behavior, rather than stratifying lymphomas by grade across entities, or by attempting to correlate cytological grade and biologic aggressiveness [7, 52, 53]. Although seemingly more complicated, the new scheme and paradigm shift proved to be a step in the right direction, as shown in an international study evaluating the REAL classification that found at least 85% accuracy and 85% reproducibility for most major lymphoma types, in 1403 cases studied across 9 study sites [54]. Building upon the principles and success of the REAL classification, a classification system under the World Health Organization (WHO) Classification of Tumors was then developed, as a joint project between the European Association for Hematopathology (EAHP) and the Society for Hematopathology (SH) [55, 56]. The tumor categories were developed by ten different committees focused on separate cell lineages (myeloid, lymphoid, histiocytic, etc.), and the proposed classification was extensively discussed and vetted at several meetings, including one held once again at the Airlie House in Virginia in 1997. Unlike the 1975 Airlie House meeting, which failed in consensus building, a report from the 1997 meeting noted that the “WHO classification has produced a new and exciting degree of cooperation and communication between oncologists and pathologists around the world, which should facilitate progress in the understanding and treatment of hematologic malignancies” [57]. Examples of practical, nuts and bolts issues resolved by consensus at the Airlie House meeting include the following: should the French American British terms L1–L3 be retained (no), are lymphoblastic leukemias and lymphomas a single disease with different presentations (yes), should genetic abnormalities be included in the classification of B-lymphoblastic leukemia (yes), should the nomenclature of follicle centre lymphoma be changed to follicular lymphoma (yes), should follicular lymphoma be graded by number of large cells (yes), should diffuse areas be reported in follicular lymphoma (yes, though no consensus initial WHO on quantification), etc. [58]. The success of the blue book monograph published in 2001 (third edition) led to an updated version in 2008 (fourth edition) [59]. This revision continued the theme

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of consensus building and a multidisciplinary approach to classification and reflected the continually evolving state of knowledge shared amongst pathologists, oncologists, geneticists, and immunologists. New concepts and changes introduced into B-cell lymphoma classification included monoclonal B-cell lymphocytosis (listed in the definition of chronic lymphocytic leukemia), refinement of the definition of lymphoplasmacytic lymphoma and recognition of Waldenstrom’s macroglobulinemia as a subset, refinement of plasma cell myeloma categories to include symptomatology and cytogenetic information, restructuring the grading of follicular lymphoma to lump grades 1 and 2 and mandate separation of grade 3A from 3B, inclusion of two molecular subtypes of diffuse large B-cell lymphoma (DLBCL), recognition of distinct categories of DLBCL including T-cell/histiocyte—rich large B-cell lymphoma and EBV-positive DLBCL of the elderly, and others [60, 61]. A provisional category of B-cell lymphoma, unclassifiable, with features intermediate between classic Hodgkin lymphoma and DLBCL, was included to recognize the existence of a true biologic gray zone between the two entities, supported by morphological studies [62, 63] and epigenetic profiling [64]. Another provisional borderline category was that between DLBCL and Burkitt lymphoma, also reflecting a gray zone of lymphoma whose existence was supported by gene expression profiling studies [61]; the category suffered from low reproducibility and genetic heterogeneity, and was subsequently revised in 2016 (see separate chapter on revisions to the WHO classification of aggressive B-cell lymphomas). A final important conceptual focus of the 2008 revision was that of early lesions in lymphoid neoplasia, and their implications in lymphomagenesis [65, 66]. The WHO monograph from 2016 was a revision of the fourth edition [59], and not truly a new fifth edition, given other pending volumes in the WHO tumor series pending at the time. The revision included critical updates discussed at the all-­ important Clinical Advisory Committee meeting, held in 2014, and continued the consensus-based approach and incorporation of morphological, genetic, and clinical data [67]. Sadly, this was to be the end of consensus, at least for the time being.

2 022: The Fifth Edition WHO and International Consensus Classifications In 2022, two separate classification schemes were unveiled in hematopathology, both covering myeloid and lymphoid neoplasms—the fifth edition of the WHO and the International Consensus Classification (ICC) [68, 69]. The challenges of working with two systems with implications for clinical trials continue to emerge. Patients are also faced with receiving a pathology report that may include their diagnosis in three systems (fourth revised edition WHO, fifth edition WHO and ICC). While the alternative systems do provide a framework for identifying areas that would benefit from additional research and discussion, the concern based on historical perspectives is that this split may represent a step backwards, and at worst,

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may potentially test the trust of our clinical colleagues in our specialty, and of our patients in the medical system as a whole. Regardless, the changes will undoubtedly increase the workload of the practicing hematopathologist, both in rendering multiple diagnoses per case, and in explaining this discrepancy to clinical colleagues. It remains to be seen whether and to what extent patient care (i.e. treatment selection and clinical trial availability) will be impacted. This chapter’s look back through hematopathology history will hopefully serve as a reminder of the critical importance of consensus building in our complicated field, and as an urgent call to reintegrate the disparate schemes into one future classification system. Figure 1.2 shows a historical timeline. Disclosures  The authors have no conflicts of interest to disclose.

1944: Jackson and Parker subclassify Hodgkin disease into 3 types

1941: Gall and Mallory propose first modem classification scheme widely used in the US

1974: Kiel classification scheme

1966: Lukes and Butler classification scheme

1965: Mack Fulwyler develops first flow cytometer

1956: Rappoport classification scheme

2022: Emergence of two separate classification schemes, WHO 5th ed and ICC

2016: Updated WHO classification (revised 4th edition)

2008: Updated WHO classification (4th edition)

2001: WHO classification (3rd edition)

1997: Validation of REAL classification

1994: REAL classification

1994: IGH rearrangement establishes B-cell lineage of Hodgkin Iymphoma

1992: Foundation of International Lymphoma Study Group

1976, 1979: Discoveries of recurrent translocations in Burkitt and follicular Iymphomas

1975: Meeting at Airlie House in Virginia fails to achieve consensus between competing classification schemes

1975: Kohler and Milstein’s Nobel prize winning discovery of hybridoma technology, Kicking off the immunology revolution

1974: Elaine Jaffe links “nodular Iymphoma” cells to the Iymphoid follicle

Fig. 1.2  Timeline of select events of interest in the history of B-cell lymphoma classification

1898, 1902: Carl Sternberg and Dorothy Reed independently describe features of Hodgkin disease

1832: Thomas Hodgkin’s report “on some morbid appearances of the absorbent glands and spleen”

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References 1. Hodgkin T. On some morbid appearances of the absorbent glands and spleen. Med Chir Trans. 1832;17:68–114. 2. Hancock BW.  Early clinical pathologists. 2. Thomas Hodgkin: pathologist, physician, and philanthropist. J Clin Pathol. 1990;43(8):616–8. 3. Geller SA, Taylor CR. Thomas Hodgkin: the “man” and “his disease”: humani nihil a se alienum putabit (nothing human was foreign to him). Virchows Arch. 2013;463(3):353–65. 4. Reed DM. On the pathological changes in Hodgkin’s disease with special reference to its relation to tuberculosis. Johns Hopkins Hosp Rep. 1902;10:133–98. 5. Sternberg C.  Ueber eine eigenartige unter dem Bilde der pseudoleukemic verlaufende Tuberkulose des lymphatischen Apparatus. Ztschr f Heilk. 1898;19:21–90. 6. Zwitter M, Cohen JR, Barrett A, Robinton ED. Dorothy Reed and Hodgkin’s disease: a reflection after a century. Int J Radiat Oncol Biol Phys. 2002;53(2):366–75. 7. Jaffe ES, Harris NL, Stein H, Isaacson PG. Classification of lymphoid neoplasms: the microscope as a tool for disease discovery. Blood. 2008;112(12):4384–99. 8. Dawson PJ. Whatever happened to Dorothy Reed? Ann Diagn Pathol. 2003;7(3):195–203. 9. Levine RB, González-Fernández M, Bodurtha J, Skarupski KA, Fivush B. Implementation and evaluation of the Johns Hopkins University School of Medicine leadership program for women faculty. J Womens Health (Larchmt). 2015;24(5):360–6. 10. MacCallum WG. A text-book of pathology. Philadelphia: WB Saunders Company; 1916. 11. Gall EA, Mallory TB. Malignant lymphoma: a clinico-pathologic survey of 618 cases. Am J Pathol. 1942;18(3):381–429. 12. Symmers D. Follicular lymphadenopathy with splenomegaly: a newly recognized disease of the lymphatic system. Arch Pathol. 1927;3:816–20. 13. Brill NE, Baehr G, Rosenthal N. Generalized giant lymph follicle hyperplasia of lymph nodes and spleen; a hitherto undescribed type. Am J Med. 1952;13(5):570–4. 14. Symmers D. Giant follicular lymphadenopathy with or without splenomegaly: its transformation into polymorphous cell sarcoma of the lymph follicles and its association with Hodgkin’s disease, lymphatic leukemia and an apparently unique disease of the lymph nodes and spleen— a disease entity believed heretofore undescribed. Arch Pathol. 1938;26(3):603–47. 15. Jackson H Jr, Parker F Jr. Hodgkin’s disease: pathology. N Engl J Med. 1944;231(2):35–44. 16. Rappaport H, Winter WJ, Hicks EB. Follicular lymphoma. A re-evaluation of its position in the scheme of malignant lymphoma based on a survey of 253 cases. Cancer. 1956;9(4):792–821. 17. Rappaport H.  Atlas of tumor pathology. Washington: Armed Forces Institute of Pathology; 1966. p. 47–61. 18. Lukes RJ, Butler JJ, Hicks EB. Natural history of Hodgkin’s disease as related to its pathologic picture. Cancer. 1966;19(3):317–44. 19. Lukes RJ, Craver LF, Hall TC, Rappaport H, Ruben P. Report of the nomenclature committee. Cancer Res. 1966;26(6 Part 1):1311. 20. Berard CW, Cossman J, Jaffe ES. Malignant lymphomas as tumours of the immune system. Br J Cancer. 1980;42(1):1–20. 21. Tsukimoto I, Wong KY, Lampkin BC. Surface markers and prognostic factors in acute lymphoblastic leukemia. N Engl J Med. 1976;294(5):245–8. 22. Jaffe ES, Braylan RC, Frank MM, Green I, Berard CW. Heterogeneity of immunologic markers and surface morphology in childhood lymphoblastic lymphoma. Blood. 1976;48(2):213–22. 23. Shevach EM, Jaffe ES, Green I. Receptors for complement and immunoglobulin on human and animal lymphoid cells. Immunol Rev. 1973;16(1):3–28. 24. Jaffe ES, Braylan RC, Nanba K, Frank MM, Berard CW. Functional markers: a new perspective on malignant lymphomas. Cancer Treat Rep. 1977;61(6):953–62. 25. Jaffe ES, Shevach EM, Frank MM, Berard CW, Green I. Nodular lymphoma—evidence for origin from follicular B lymphocytes. N Engl J Med. 1974;290(15):813–9.

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26. Jaffe ES.  The microscope as a tool for disease discovery—a personal voyage. Annu Rev Pathol. 2017;12:1–24. 27. Stein H, Lennert K, Parwaresch M.  Malignant lymphomas of B-cell type. Lancet. 1972;300(7782):855–7. 28. Lennert K. Malignant lymphomas other than Hodgkin’s disease: histology cytology ultrastructure immunology. Springer Science & Business Media; 2012. 29. Zelenetz AD, Abramson JS, Advani RH, Andreadis CB, Byrd JC, Czuczman MS, et al. Non-­ Hodgkin’s lymphomas. J Nat Comp Cancer Netw. 2010;8(3):288–334. 30. Rosenberg S.  The non-Hodgkin’s lymphoma pathologic classification project. National Cancer Institute sponsored study of classification of non-Hodgkin’s lymphomas. Summary and description of a working formulation for clinical usage. Cancer. 1982;49(10):2112–35. 31. Lukes RJ, Collins RD.  Immunologic characterization of human malignant lymphomas. Cancer. 1974;34(S8):1488–503. 32. Classification of non-Hodgkin’s lymphomas. Reproducibility of major classification systems. NCI non-Hodgkin’s Classification Project Writing Committee. Cancer. 1985;55(1):91–95. 33. Köhler G, Milstein C.  Continuous cultures of fused cells secreting antibody of predefined specificity. Nature. 1975;256(5517):495–7. 34. Engel P, Boumsell L, Balderas R, Bensussan A, Gattei V, Horejsi V, et al. CD nomenclature 2015: human leukocyte differentiation antigen workshops as a driving force in immunology. J Immunol. 2015;195(10):4555–63. 35. Zola H, Swart B, Banham A, Barry S, Beare A, Bensussan A, et al. CD molecules 2006— human cell differentiation molecules. J Immunol Methods. 2007;319(1–2):1–5. 36. Bernard A, Boumsell L. The clusters of differentiation (CD) defined by the first international workshop on human leucocyte differentiation antigens. Human Immunol. 1984;11(1):1–10. 37. Robinson JP.  Purdue cytometry, vol 10. West Lafayette: Purdue University Cytometry Laboratories; 2007. isbn:978-1-890473-10-5. http://www.cyto.purdue.edu/cdroms/cyto10a/ copyright.html 38. Fulwyler M. Mack Fulwyler in his own words. Interview by J. Paul Robinson and Ramunas A. Kondratas. Cytometry A. 2005;67(2):61–7. 39. Robinson JP, Roederer M.  History of science. Flow cytometry strikes gold. Science. 2015;350(6262):739–40. 40. Fulwyler MJ.  Electronic separation of biological cells by volume. Science. 1965;150(3698):910–1. 41. Chattopadhyay PK, Gierahn TM, Roederer M, Love JC. Single-cell technologies for monitoring immune systems. Nat Immunol. 2014;15(2):128–35. 42. Zech L, Haglund U, Nilsson K, Klein G. Characteristic chromosomal abnormalities in biopsies and lymphoid-cell lines from patients with Burkitt and non-Burkitt lymphomas. Int J Cancer. 1976;17(1):47–56. 43. Fukuhara S, Rowley JD, Variakojis D, Golomb HM.  Chromosome abnormalities in poorly differentiated lymphocytic lymphoma. Cancer Res. 1979;39(8):3119–28. 44. Rosenberg CL, Wong E, Petty EM, Bale AE, Tsujimoto Y, Harris NL, et al. PRAD1, a candidate BCL1 oncogene: mapping and expression in centrocytic lymphoma. Proc Natl Acad Sci U S A. 1991;88(21):9638–42. 45. Li JY, Gaillard F, Moreau A, Harousseau JL, Laboisse C, Milpied N, et al. Detection of translocation t(11;14)(q13;q32) in mantle cell lymphoma by fluorescence in situ hybridization. Am J Pathol. 1999;154(5):1449–52. 46. Marafioti T, Hummel M, Foss H-D, Laumen H, Korbjuhn P, Anagnostopoulos I, et al. Hodgkin and Reed-Sternberg cells represent an expansion of a single clone originating from a germinal center B-cell with functional immunoglobulin gene rearrangements but defective immunoglobulin transcription. Blood. 2000;95(4):1443–50. 47. Kuppers R, Rajewsky K, Zhao M, Simons G, Laumann R, Fischer R, Hansmann ML. Hodgkin disease: Hodgkin and Reed-Sternberg cells picked from histological sections show clonal

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immunoglobulin gene rearrangements and appear to be derived from B cells at various stages of development. Proc Natl Acad Sci U S A. 1994;91:10962. 48. Banks P, Chan J, Cleary M, Delsol G, De Wolf-Peeters C, Gatter K, et al. Mantle cell lymphoma a proposal for unification of morphologic, immunologic, and molecular data. Am J Surg Pathol. 1992;16(7):637–40. 49. Mason DY, Banks PM, Chan J, Cleary ML, Delsol G, de Wolf PC, et al. Nodular lymphocyte predominance Hodgkin’s disease. A distinct clinicopathological entity. Am J Surg Pathol. 1994;18(5):526–30. 50. Harris NL, Jaffe ES, Stein H, Banks PM, Chan JK, Cleary ML, et al. A revised European-­ American classification of lymphoid neoplasms: a proposal from the International Lymphoma Study Group [see comments]. Blood. 1994;84:1361. 51. Jaffe ES.  Hematopathology: integration of morphologic features and biologic markers for diagnosis. Mod Pathol. 1999;12(2):109–15. 52. Pileri SA, Leoncini L, Falini B. Revised European-American lymphoma classification. Curr Opin Oncol. 1995;7(5):401–7. 53. Harris NL. A practical approach to the pathology of lymphoid neoplasms: a revised European-­ American classification from the International Lymphoma Study Group. Important Adv Oncol. 1995:111–40. 54. Armitage JO, Weisenburger DD.  New approach to classifying non-Hodgkin’s lymphomas: clinical features of the major histologic subtypes. Non-Hodgkin’s lymphoma classification project. J Clin Oncol. 1998;16(8):2780–95. 55. Harris NL, Jaffe ES, Diebold J, Flandrin G, Muller-Hermelink HK, Vardiman J. Lymphoma classification—from controversy to consensus: the R.E.A.L. and WHO classification of lymphoid neoplasms. Ann Oncol. 2000;11(Suppl 1):3–10. 56. Jaffe ES, Harris NL, Diebold J, Muller-Hermelink HK. World Health Organization classification of neoplastic diseases of the hematopoietic and lymphoid tissues. A progress report. Am J Clin Pathol. 1999;111(1 Suppl 1):S8–12. 57. Harris NL, Jaffe ES, Diebold J, Flandrin G, Muller-Hermelink HK, Vardiman J, et al. World Health Organization classification of neoplastic diseases of the hematopoietic and lymphoid tissues: report of the Clinical Advisory Committee meeting-Airlie House, Virginia, November 1997. J Clin Oncol. 1999;17(12):3835–49. 58. Harris NL, Jaffe ES, Diebold J, Flandrin G, Muller-Hermelink HK, Vardiman J, et  al. The World Health Organization classification of neoplastic diseases of the haematopoietic and lymphoid tissues: report of the Clinical Advisory Committee Meeting, Airlie House, Virginia, November 1997. Histopathology. 2000;36(1):69–86. 59. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, et al. WHO classification of tumours of haematopoietic and lymphoid tissues. Lyon: International Agency for Research on Cancer; 2008. 60. Jaffe ES, Pittaluga S. Aggressive B-cell lymphomas: a review of new and old entities in the WHO classification. Hematology Am Soc Hematol Educ Program. 2011;2011:506–14. 61. Campo E, Swerdlow SH, Harris NL, Pileri S, Stein H, Jaffe ES. The 2008 WHO classification of lymphoid neoplasms and beyond: evolving concepts and practical applications. Blood. 2011;117(19):5019–32. 62. Garcia J, Mollejo M, Fraga M, Forteza J, Muniesa J, Pérez-Guillermo M, et al. Large B-cell lymphoma with Hodgkin’s features. Histopathology. 2005;47(1):101–10. 63. Traverse-Glehen A, Pittaluga S, Gaulard P, Sorbara L, Alonso MA, Raffeld M, et  al. Mediastinal gray zone lymphoma: the missing link between classic Hodgkin’s lymphoma and mediastinal large B-cell lymphoma. Am J Surg Pathol. 2005;29(11):1411–21. 64. Eberle FC, Rodriguez-Canales J, Wei L, Hanson JC, Killian JK, Sun H-W, et al. Methylation profiling of mediastinal gray zone lymphoma reveals a distinctive signature with elements shared by classical Hodgkin’s lymphoma and primary mediastinal large B-cell lymphoma. Haematologica. 2011;96(4):558.

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65. Ganapathi KA, Pittaluga S, Odejide OO, Freedman AS, Jaffe ES.  Early lymphoid lesions: conceptual, diagnostic and clinical challenges. Haematologica. 2014;99(9):1421–32. 66. Jaffe ES. The 2008 WHO classification of lymphomas: implications for clinical practice and translational research. Hematology Am Soc Hematol Educ Program. 2009:523–31. 67. Swerdlow SH, Campo E, Pileri SA, Harris NL, Stein H, Siebert R, et  al. The 2016 revision of the World Health Organization classification of lymphoid neoplasms. Blood. 2016;127(20):2375–90. 68. Cree IA. The WHO classification of haematolymphoid tumours. Leukemia. 2022;36(7):1701–2. https://doi.org/10.1038/s41375-­022-­01625-­x. Epub 2022 Jun 22. PMID: 35732830; PMCID: PMC9252902. 69. Swerdlow SH, Campo E, Arber DA, Cazzola M, Cook JR, Döhner H, Dreyling M, Hasserjian RP, Jaffe ES, Orazi A, Quintanilla-Martinez L, Scott DW, Tefferi A, Winter JN, Zelenetz AD.  Response to “The WHO classification of haematolymphoid tumours” (editorial). Leukemia. 2022;36(11):2748–9. https://doi.org/10.1038/s41375-­022-­01689-­9. Epub 2022 Aug 27. PMID: 36030304.

Chapter 2

Revisions to the Classification of Aggressive B-Cell Lymphomas Michael E. Kallen and Rima Koka

Introduction A revised fourth edition of the World Health Organization classification of tumors of hematopoietic and lymphoid tissues was introduced in 2016 [1], updating the fourth edition from 2008 [1, 2]. Two classification systems were released in 2022, both building on the 2016 revised fourth edition with a fifth edition of the World Health Organization classification [3] (termed WHO-HAEM5, abbreviated as “WHO5” for simplicity in this chapter) and the International Consensus Classification (ICC) [4]. These latest revisions continue the scientific goal of arranging entities into well-defined and more homogeneous groups, based on ongoing refinement in our biologic understanding to better predict prognosis and ultimately improve treatments and patient outcomes. In the intervening years since the 2008 WHO classification, important contributions have been made to our understanding of lymphoid neoplasms, through the application of technology, including gene expression profiling and next-generation sequencing. These tools have revealed new insights into mechanisms of lymphomagenesis, generated evidence justifying the creation of new provisional entities and begun to provide molecular therapeutic targets for specific subcategories of lymphomas [1]. The updated classification of aggressive B-cell lymphomas in particular illustrates the promise of high-­throughput molecular techniques in providing a genetically based risk stratification and potential for personalized cancer therapy. (See Table 2.1). This chapter will discuss the updated WHO and ICC classifications of several aggressive B-cell neoplasms, including diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS), high-grade B-cell lymphomas (HGBL) and the emphasis on the need for a separate category for cases with MYC and BCL2 M. E. Kallen (*) · R. Koka Department of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_2

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rearrangements, the uncertainty regarding the role of combined MYC and BCL6 rearrangements, the improved understanding of features of large B-cell lymphoma with 11q aberration, and the paradigm shift in EBV-positive diffuse large B-cell lymphoma (EBV DLBCL, formerly “of the elderly”), which may affect a range of patients (see Fig.  2.1). The discussion will focus on specific novel molecular insights, and their impact on the latest developments in our understanding of the respective lymphomas. Table 2.1  Summary of 2022 classification updates to aggressive B-cell lymphomas 2008 WHO, fourth edition [2] DLBCL, NOS

B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and Burkitt lymphoma (BCLU)

2016 WHO, fourth 2022 WHO, fifth revised edition [1] edition [3] – Requirement Unchanged for cell of origin determination (GCB, ABC subtypes) – Rationale: inferior prognosis of ABC patients with R-CHOP chemotherapy regimen

2022 ICC [4] –  Cell of origin designation should be maintained, but is considered insufficient to fully capture biologic complexity –  The role of morphological, phenotypic, and double expressor variants is de-emphasized

Molecular features – GCB: “constitutive germinal center BCR signaling”, EZH2 and BCL2 mutations –  ABC: NFκB activation, MYD88 and CD79B mutations – Additional categories identified by molecular sequencing, not yet in clinical use Mixed category including DLBCL, Burkitt, and double/triple hit cases

–  HGBCL, with MYC and BCL2 rearrangements (some may express TdT) –  HGBCL with MYC and BCL6 rearrangements –  HGBCL, NOS

– Combination of mutations causes synergy for oncogenesis – Resultant clinical impact is poor response to conventional chemotherapy and short overall survival –  Need for multicenter prospective clinical trials

Removed category

High-grade B-cell lymphomas:  –  HGBCL with MYC and BCL2 and/or BCL6 rearrangements  –  HGBCL, NOS Rationale: creation of distinct category for double and triple hit lymphomas for ease of clinical trial enrollment

DLBCL/ HGBCL with MYC and BCL2 rearrangements Subtypes:  –  without BCL6 rearrangement  –  with BCL6 rearrangement  –  with/ without BCL6 rearrangement and TdT expression

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Table 2.1 (continued) 2008 WHO, fourth edition [2] Burkitt lymphoma

2016 WHO, fourth 2022 WHO, fifth revised edition [1] edition [3] 2022 ICC [4] Unchanged Unchanged Unchanged  –  Subset  –  Neoplasms genetically with precursor reclassified as B-cell phenotype HGBCL, NOS and MYC rearrangement will be called B-ALL/LBL with MYC rearrangement, rather than Burkitt leukemia/ lymphoma Large B-cell High-grade Added new lymphoma with provisional entity: B-cell lymphoma with 11q aberration Burkitt like 11q aberrations  –  Entity still lymphoma with 11q aberration considered Rationale: refined provisional subcategorization of aggressive pediatric B-cell lymphomas EBV+ DLBCL EBV+ DLBCL, EBV+ DLBCL Replaced former NOS of the elderly provisional Morphologically designation with heterogeneous but EBV+ DLBCL, this does not have NOS significance in the Rationale: elderly identified cases in THRLBCL-like younger patients pattern is more with significant common in patients better prognosis 80% of the tumor cells (d) (400× magnification)

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Fig. 2.2  Diffuse Large B-cell lymphoma, not otherwise specified, germinal center B-cell type presenting as a paraspinal mass. Mutations characteristic of the GCB subtype were identified by next-generation sequencing, including in the EZH2, BCL2 and CREBBP genes. An IGH::BCL2 rearrangement was identified by FISH testing, and additional evaluation revealed evidence of low-­ grade follicular lymphoma in a separate specimen from which this may have transformed. Hematoxylin and eosin-stained sections are shown in (a) 10× and (b) 40× objectives. (Images courtesy of Genevieve Crane, MD, PhD, Cleveland Clinic, Cleveland, OH)

a

b

Fig. 2.3  Diffuse large B-cell lymphoma, not otherwise specified, activated B-cell type. This aggressive B-cell neoplasm, which presented as a soft tissue mass, demonstrated multiple mutations, including in the CD79B gene. CD79B mutations may potentiate B-cell receptor signaling and abrogate B-cell anergy to help drive tumorigenesis and are associated with an activated B-cell phenotype. This lymphoma was negative for MYC, BCL2 or BCL6 gene rearrangements. Immunohistochemical stains were consistent with non-germinal center B-cell type by Hans criteria (not shown). This entity would be classified as DLBCL, NOS by fourth revised WHO, WHO5 and ICC classification systems. Hematoxylin and eosin-stained sections are shown with (a) 10× and (b) 40× objectives. (Images courtesy of Genevieve Crane, MD, PhD, Cleveland Clinic, Cleveland, OH)

generally required for clinical trials and also considered informative for routine treatment decision-making. Thus far, clinical trial data suggests that the addition of bortezomib, lenalidomide, and ibrutinib to the R-CHOP regimen may deliver benefit for patients with the ABC, but not GCB, subtype of DLBCL [1]. The GCB subtype has been found to demonstrate inactivation of several chromatin modifiers, including KMT2D, CREBBP, and EP300, in turn promoting germinal center differentiation [8]. Also seen almost exclusively in the GCB subtype are recurrent mutations of EZH2 [1], a gene involved in maintaining the GC phenotype

2  Revisions to the Classification of Aggressive B-Cell Lymphomas

a

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b

Fig. 2.4  Diffuse large B-cell lymphoma, not otherwise specified, status post-therapy with high variant allele frequency TP53 mutation. This aggressive B-cell lymphoma harbored a BCL6 gene rearrangement, and mutations in B-cell receptor signaling associated with activated B-cell subtype DLBCL, NOS including in the CD79B and CARD11 genes. CARD11 mutations may promote tumorigenesis by activating the NF-κB pathway. TP53 mutations have been associated with a poor response to therapy and aggressive course. This entity would be classified as DLBCL, NOS by fourth revised edition WHO, WHO5 and ICC classification systems. Hematoxylin and eosin-­ stained sections are shown with (a) 10× and (b) 40× objectives. (Images courtesy of Genevieve Crane, MD, PhD, Cleveland Clinic, Cleveland, OH)

as a repressor involved in the polycomb repressive complex [8]. By contrast, the ABC subtype is characterized by NF-κB activation [12], driving expression of the IRF4 transcription factor and hence differentiation towards activated B-cells, though terminal differentiation to plasma cells is blocked by other repressors, including SPIB and BCL6 [8]. Additional evidence has illuminated the complexity of the molecular pathogenesis underlying DLBCL with ABC subtype. As briefly mentioned, ABC tumor cell propagation has been found to rely on chronic active BCR signaling. One such mechanism of this is through mutations in CARD11, subsequent formation of the CARD11, BCL10, MALT1 (CBM) complex, and activation of the NF-κB pathway (Fig. 2.4). CD79A and CD79B mutations have been shown to potentiate BCR signaling, and self-antigen stimulation may have a role in lymphomagenesis. CD79B mutations may also abrogate B-cell anergy, and allow self-reactive cells to enter the germinal center reaction and acquire additional hits on the pathway to DLBCL. MYD88 L265P mutations are present in ~29% of ABC DLBCL (Fig. 2.5), but are rare in GCB DLBCL, and co-occur with CD79B mutations in ABC DLBCL more often than would be expected by chance; this association is particularly strong in primary extranodal DLBCLs; and raises the possibility of MYD88 collaboration in BCR signaling [1]. TLR9 has been identified as important in ABC cell lines with CD79A/B and MYD88 L265P mutations, and is hypothesized to coordinate signaling through a MyD88-TLR9-BCR (My-T-BCR) supercomplex; this supercomplex demonstrated unexpected proximity within endolysosomal vesicles to the mTORC1 complex, which transduces PI3 kinase signaling, and may provide a mechanistic explanation for the synergism of ibrutinib (binds BTK and inhibits BCR signaling) and PI3 kinase pathway inhibitors in killing ABC cell lines, and a rationale for their combined use in clinical trials [8, 13].

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Fig. 2.5  Large B-cell lymphoma involving the testis. In the fourth revised edition WHO, this was entity was included in the broader category of diffuse large B-cell lymphoma, not otherwise specified. WHO5 defines a new category “Primary large B-cell lymphoma of immune privileged sites”, to include DLBCL arising in the CNS, vitreoretina and testis. In the ICC, it is separately recognized as primary diffuse large B-cell lymphoma of testis. These neoplasms are of activated B-cell type and frequently harbor an MYD88 L265P mutation placing them in the MCD molecular subtype [5, 12, 13]. They are typically associated with an aggressive clinical course. Hematoxylin and eosin-stained sections are shown with (a) 10× and (b) 40× objectives. (Images courtesy of Genevieve Crane, MD, PhD, Cleveland Clinic, Cleveland, OH)

GCB DLBCL lymphomagenesis, by contrast, is less well characterized at the molecular level. GCB DLBCL cell lines have been shown to rely on constitutive BCR signaling, which is both antigen independent and NF-κB independent (unlike the chronic active BCR signaling in ABC DLBCL) [14]. The constitutive BCR signaling in GCB DLBCLs is also distinct from the tonic BCR signaling of normal B-cells, in its dependence on LYN kinase [8, 14]. Investigators from the NCI have proposed the name “constitutive germinal center BCR signaling” for this process [13], as well as the term “toncogenic” BCR signaling, to highlight its distinction from tonic BCR signaling in normal B-cells . Additional work has begun to incorporate the complex genetic landscape of DLBCLs into updated categories beyond the GCB and ABC subtypes. A landmark study of 574 DLBCL biopsies using exome and transcriptome sequencing, array-­ based DNA copy-number analysis and targeted amplicon resequencing, identified four prominent genetic subtypes, termed MCD (based on co-occurrence of MYD88 and CD79B mutations), BN2 (based on BCL6 fusions and NOTCH2 mutations (see Fig. 2.6), N1 (based on NOTCH1 mutations), and EZB (based on EZH2 mutations and BCL2 translocations) [15]. Many GCB DLBCLs demonstrated mutations in EZH2 and alterations in BCL2, corresponding to the EZB subtype. Similarly, concurrent MYD88 and CD79B mutations are largely seen in ABC tumors, corresponding to the MCD subtype. BN2 tumors were enriched in the unclassified subtype of DLBCL fitting neither GCB nor ABC, indicating unique genetic features to this unclassified group. N1 was defined by NOTCH1 mutations in a subset of ABC tumors lacking NOTCH2 mutations, highlighting newly recognized separate groupings within the ABC category. Validation that these subtypes represent biologically distinct malignancies is provided by significant differences between groups in gene expression signatures, as well as in overall survival following R-CHOP

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b

Fig. 2.6  Diffuse large B-cell lymphoma, not otherwise specified, associated with a NOTCH2 mutation. Soft tissue from a deep dermal/subcutaneous lesion demonstrates areas of large cell transformation in a patient with a reported history of cutaneous marginal zone lymphoma. The cells were non-germinal center subtype by Hans criteria, and a MYC rearrangement was identified by FISH. Molecular studies demonstrated mutations in NOTCH2, TP53 and B2M. DLBCL, NOS with NOTCH2 mutations have been grouped into a “BN2” molecular subgroup [12] with more favorable survival, although this may be affected by the concurrent TP53 mutation. Hematoxylin and eosin-stained sections are shown with (a) 10× and (b) 40× objective. (Images courtesy of Genevieve Crane, MD, PhD, Cleveland Clinic, Cleveland, OH)

chemotherapy, with favorable survival in the BN2 and EZB subtypes, and inferior outcomes in the MCD and N1 subtypes [8, 15]. A similar large multi-institution study analyzed 304 primary DLBCLs by whole exome sequencing, and identified five robust tumor clusters, showing remarkable overlap with the Schmitz et al. categorization and prognostic findings [16]. Chapuy et al. define five genetic groups of DLBCL including a cluster (named C5) of majority ABC tumors with concurrent CD79B and BCL2 mutations; a second cluster (C1) of majority ABC tumors with BCL6 structural variants and NOTCH2 signaling pathway mutations (see Fig. 2.6); a third cluster (C3) of majority GCB tumors with EZH2 mutations and BCL2 structural variants; a fourth cluster (C4) of unique GCB tumors with mutations in linker and core histone genes, multiple immune evasion molecules, BCR/Pi3K signaling intermediates, NF-κB modifiers, and JAK/STAT signaling pathway members; and a fifth cluster of GCB/ABC-independent tumors (C2) with TP53 inactivation as well as CDKN2A and RB1 copy loss. They also describe a small group of non-ABC/GCB cases (C0) lacking apparent genetic drivers. These were enriched for T-cell/histiocyte–rich large B-cell lymphomas [16], with lack of detected mutations potentially related to the frequency of tumor cells within the sample. Notably, tumors with co-occurring BCL2 and MYC rearrangements (the so-called double hit lymphomas) were found to be significantly more frequent in the GCB rich cluster with EZH2 mutations; these tumors have been reclassified in the latest WHO revision as high-grade B-cell lymphoma with MYC and BCL2 rearrangement (Fig.  2.7), as will be discussed further below. Also of interest, the C1 ABC enriched tumors were found to have alterations similar to those described in marginal zone lymphomas, but without histological features of this entity, suggesting potential occult transformation from a marginal zone lymphoma or derivation from a common extrafollicular B-cell precursor (see Fig. 2.6).

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Importantly, the newly defined genetic clusters by Chapuy et al. demonstrated significant prognostic differences, with more favorable outcomes associated with C0, C1, and C4 DLBCLs, and less favorable with C3 and C5 tumors [16]. Additionally, newly defined subsets of genetically distinct ABC and GCB tumors were found to have prognostic differences, with favorable outcomes in C1 ABC and C4 GCB tumors (as compared to other ABC and GCB subsets, respectively) [16]. The remarkable overlap in findings between these studies, as well as others, suggests the utility of a genetic framework for organizing heterogeneous categories into clinically actionable groups, and for the potential development of appropriately tailored chemotherapy based on affected signaling pathways. Future clinical trials could evaluate drugs within particular subgroups of DLBCL and optimize therapy within the context of numerous genetic abnormalities. The recent 2022 classification systems are largely similar to the categories in the 2016 WHO revision. The WHO5 notes that cell of origin subtyping has a disappointing lack of impact as a predictive marker, specifically in ABC type DLBCL, and that upcoming specific subgroups including double-hit signature positive cases, gene rearrangements including MYC and TP53, MYC copy number alterations, and the previously discussed mutational subgroups will confer clinical impact; however, these approaches currently suffer from lack of clinical management consensus and relevant clinical trials, not to mention gaps in availability of genetic testing [3]. For the ICC system, the cell of origin requirement will be maintained, but is considered insufficient to capture the biologic complexity, and that molecular profiling studies have identified functional genetic subgroups, which will help with more precise patient stratification [4]. For these reasons, as well as for clinically actionable differences in treatment, the 2016 revision and most recent classification systems all require GCB and ABC subtype reporting in DLBCL. As gene expression profiling is less routinely available, immunohistochemistry is currently considered an acceptable alternative, despite the algorithms’ limitations (lack of reproducibility, binary classification, and imperfect prognostic utility). A newer method of classification, utilizing RNA transcripts extracted from formalin-fixed paraffin-embedded tissue, shows concordance with conventional gene expression profiling results, and shows promise as an improvement over immunohistochemistry [17], although it has not been widely adopted.

High-Grade B-Cell Lymphomas The 2008 WHO classification introduced a category called “B-cell lymphoma, unclassifiable, with features intermediate between diffuse large B-cell lymphoma and Burkitt lymphoma” (BCLU). This heterogeneous category contained aggressive B-cell lymphomas, in which the distinction between DLBCL and Burkitt lymphoma (BL) was difficult. While BL has a characteristic translocation between MYC at 8q24 and IGH at 14q32, or less commonly with IGK at 2p12 or IGL at

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22q11, approximately 10% of classic BL cases lack an identifiable MYC rearrangement. Given that routinely available cytogenetic techniques cannot definitively exclude all cryptic MYC translocations, cases without a characteristic BL translocation are classified by morphological and immunophenotypic criteria; and can pose diagnostic challenges. Gene expression profiling studies have investigated groups of high-grade B-cell lymphomas, including examples of BL, DLBCL, and the former category of BCLU and identified a characteristic BL molecular signature, by using features including high levels of expression of c-Myc target genes, expression of a subgroup of germinal center B-cell genes, and low level of expression of MHC class I and NF-κB target genes [18, 19]. This molecular signature was interestingly also detected in some cases that do not meet WHO criteria for BL and are better classified as DLBCL by morphology as well as mutational pattern. Also found were a subset of lymphomas with a gene expression profile intermediate between DLBCL and BL [1], identifying a true intermediate molecular profile. These findings highlight the discrepancy and imperfect overlap between the morphological, immunophenotypic, and genetic features of BL and DLBCL, and further establish the potential need for additional subcategories including a “high-grade B-cell lymphoma” category. Additionally, some tumors formally categorized as BCLU are known to have rearrangements both of MYC, and simultaneously of BCL2 and/or BCL6, comprising the so-called double (see Fig. 2.7) and triple hit lymphomas (see Fig. 2.1a and b). These aggressive B-cell lymphomas, though sharing some genetic features, are not well predicted by morphological or immunophenotypic findings and are best identified based on assessment by FISH testing for the specific translocations [20]. The 2016 WHO revision designated a new entity called “high-grade B-cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements”, to contain the double a

b

Fig. 2.7  High-grade B-cell lymphoma with MYC and BCL2 rearrangements. Additional molecular studies by next-generation sequencing demonstrated MYC amplification and pathogenic mutations in KDM6A, RB1, TNFRSF14, BCL2 and KRAS. There is broad agreement in the classification of so-called “double-hit” lymphomas with MYC and BCL2 rearrangements, with similar terminology in the fourth revised WHO, WHO5 and ICC systems, which are typically associated with an aggressive clinical course. In contrast to the case in Fig. 2.1, this neoplasm demonstrated a non-­ germinal center B-cell phenotype by Hans criteria (not shown). Hematoxylin and eosin-stained sections are shown with (a) 10× and (b) 40× objectives. (Images courtesy of Genevieve Crane, MD, PhD, Cleveland Clinic, Cleveland, OH)

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and triple hit lymphomas (DHL/THL). However, the 2022 WHO5 and ICC both refine this category recognizing large B-cell lymphoma cases with MYC and BCL2 as potentially requiring more aggressive therapy (DLBCL/HGBL-MYC/BCL2  in the WHO5 and HGBL-DH-BCL2 in the ICC). Large B-cell lymphoma with MYC and BCL6 continues to be recognized by ICC as a provisional category (HGBL with MYC and BCL6 rearrangement (HGBL-DH-BCL6) while additional information is gathered. Additional cases with features intermediate between DLBCL and BL, or with blastoid morphology, but lacking the exact requisite gene rearrangements, can be designated in the 2016 revision as “high grade B-cell lymphoma, not otherwise specified (HGBL, NOS)”. This is retained by both systems in 2022 but should be used sparingly, excluding cases with large cell morphology. HGBL, NOS remains a gray area for clinical management and shows less consensus amongst pathologists for diagnosis. The former entity of BCLU has been removed from the 2016 and 2022 systems.

 igh-Grade B-Cell Lymphoma with MYC and BCL2 H Rearrangements (DLBCL/HGBL-MYC/BCL2) By definition, these aggressive B-cell lymphomas contain rearrangements of MYC and BCL2 and may contain additional rearrangement of BCL6. MYC is a member of a transcription factor family of genes, controlling expression of numerous target genes involved in cell cycle and DNA repair, and supporting growth and proliferation [21, 22]. Most MYC breakpoints are likely mediated by activation-induced cytidine deaminase in mature B-cells [23]. In roughly 65% of DHL, the MYC rearrangement partner is one of the IG genes (usually IGH, less frequently IGK or IGL); this rearrangement has been observed in non-neoplastic conditions, and additional factors are needed for malignant transformation [1, 23]. MYC translocation has been proposed as a secondary and transformative event occurring in t(14;18)carrying B-cells, in the pathogenesis of BCL2 and MYC rearranged DHL. A minority of DHL cases demonstrate a non-IG MYC rearrangement partner, including at 9p13 (gene unknown), 3q27 (BCL6), and others, though the mechanisms for this are less well understood. The acquisition of multiple genetic breakpoints is likely synergistic for oncogenesis. MYC drives proliferation and an active metabolic state and also induces DNA stress leading to activation of apoptotic pathways; resultant apoptosis could be inhibited by concurrent TP53 inactivating mutations, or by simultaneous BCL2 rearrangement. BCL2 also represses proteins involved in DNA repair, and constitutive BCL2 deregulation in t(14;18) could further synergize proliferation with concurrent MYC rearrangements. The t(14;18) may also lead to an accumulation of germinal center B-cells, in which high levels of activation induced cytidine deaminase are present, promoting further mutations including in MYC. This may explain the high genomic complexity frequently seen in DHLs [23]. BCL6 is required for

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germinal center formation, and is a transcriptional repressor of many target genes involved in apoptosis, proliferation, and cell cycle control, including both MYC and BCL2. Because DNA damage induced by MYC can repress BCL6 expression, constitutive activation of BCL6 could also provide a competitive advantage in Myc-­ overexpressing tumor cells [23]. While MYC rearrangement has been found to infrequently co-occur with other rearrangements besides those of BCL2 and BCL6, the absence of systematic clinical studies in these cases precludes them from inclusion in this category [1]. BCL3 (19q13) is an Iκβ protein family member, expressed in mature B-cells and involved in germinal center formation, and rearranged in a large variety of leukemias and lymphomas [23]. Cases with CCND1 and MYC rearrangements represent aggressive mantle cell lymphomas with acquisition of a secondary MYC breakpoint. Lymphomas with a combination of gene rearrangements and copy number increases/ amplifications also do not qualify, unless they show MYC and BCL2 rearrangements, as there is insufficient data to merit inclusion, and the exact clinical impact of specific copy number increases is controversial [21]. Similarly, the diagnostic category is restricted to tumors with DLBCL or HGBL/blastoid morphology, and does not include follicular lymphomas with double hits, or rare cases of B-lymphoblastic leukemia/lymphoma with evidence of double hits [1]. DHLs and THLs most frequently present in elderly patients, with a median age in the sixth to seventh decade, a slight male predominance, and only rare cases in young adults [1]. Patients also typically present with advanced disease, extranodal involvement, a high International Prognostic Index, and elevated lactate dehydrogenase [1]. Common extranodal disease sites include the bone marrow and central nervous system. Though the morphology is variable, roughly half of cases have morphology best fitting DLBCL, NOS. Overall, these comprise roughly 4–8% of tumors, which would otherwise be called DLBCL [1] (see Fig. 2.1a and b). HGBL-­ DH-­ BCL2 lymphomas are more common than HGBL-DH-BCL6 lymphomas. They are more likely to be positive for CD10 and BCL2 and negative for MUM1 by immunohistochemistry, to be classified as GCB type (though this requirement for subtyping is restricted to DLBCL), and to have transformed from an antecedent follicular lymphoma [24]. HGBL-DH-BCL6 is thought to be a biologically different disease. These cases are in general less cytogenetically complex and frequently lack TP53 mutations [25, 26] (Fig. 2.1). The use of MYC and BCL2 immunohistochemistry has identified “double expresser” lymphomas, with expression of MYC (using a cutoff of at least 40% of tumor cells), plus BCL2 (suggested cutoff of at least 50% of tumor cells) [24, 25]. Double expresser status was considered a prognostically relevant finding in DLBCL in the 2016 WHO with intermediate status between DLBCL and DHLs [7], but the importance of this finding for prognosis has been de-emphasized in the WHO5 and ICC and is no longer considered required. While the majority of DHL cases are immunohistochemical double expressers, the converse is not true, as the majority of double expresser lymphomas are actually the ABC subtype of DLBCL and do not harbor the requisite translocations. The use of immunohistochemistry is, therefore,

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not considered an acceptable surrogate for cytogenetic testing in detection of true DHLs. While consensus has not been reached on selection criteria for performing fluorescence in situ hybridization (FISH) testing, a common approach is to order rearrangement testing on all DLBCLs [24]. DHL and THL with MYC and BCL2 rearrangements have been associated with a poor response rate and short overall survival with conventional chemotherapy for DLBCL, though reports of few patients with a less dismal outcome exist. DHLs are enriched in patients who do not respond well to induction therapy with R-CHOP, or who have early relapses [27], and survival after failure of front-line therapy is poor [28]. The optimal treatment strategy has been difficult to define, due to low incidence and prior lack of uniform study criteria with ongoing need for multicenter prospective trials [25].

 arge B-Cell Lymphoma with 11q Aberration (ICC)/ L High-­Grade B-Cell Lymphoma with 11q Aberration (WHO5) The WHO revision introduced in 2016 described a new provisional entity called “Burkitt-like lymphoma with 11q aberration”, featuring similar morphology, immunophenotype, microRNA expression, and gene expression profile to BL, but lacking the typical IG-MYC translocation [1]. Instead, these lymphomas feature a proximal interstitial gain in 11q23.2-23.3, and telomeric loss in 11q24.1-qter. Cases also frequently lack the 1q gain frequently seen in BL, have more complex karyotypes, and frequently have a nodal presentation. These cases are rare, but potentially more common in the patients with a history of transplantation and immunosuppression [29], in children and young people, and in males. An analysis by Salaverria et al. in 2014 of BL11q identified a molecularly distinct subset reminiscent of BL, but with different chromosomal imbalance patterns and a lack of ID3 mutations (which are common in BL) [30]. They suggested that activation of genes included in the 11q region of gain may cooperate with functional inactivation of genes in the recurrent region of loss, including FLI1 and ETS1. A recent analysis of 15 BL11q cases by whole exome sequencing demonstrated a mutational pattern distinct from BL as well as FL and DLBCL, sharing minimal overlap with few BL-associated mutations (in the GNA13 and DDX3X genes) and few DLBCL-/FL-associated mutations (in GNA13, TTN, and EZH2), and conspicuously lacking significant BL-associated mutations (MYC, ID3, TCF3, TP53, and SMARCA4) and DLBCL/FL-associated mutations (KMT2D and CREBBP) [31]. The study also detected recurrent mutations (4 of 15 cases) in NFRKB, a gene encoding a nuclear factor related to the κB binding protein and belonging to the INO80 chromatin-remodeling complex, leading the authors to speculate a comparable function with mutations in the SWI/SNF complex seen in BL [31]. Another recent analysis of 11 BL11q cases again showed a different mutational profile from that of BL (lacking typical BL mutations in ID3, TCF3, and CCND3,

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and having mutations in BTG2, DDX3X, and ETS1 not seen in BL), but demonstrated mutations in epigenetic modifier genes common in DLBCL, particularly of the GCB subtype (EP300, CREBBP, KMT2C, EZH2, ARID1A, KMT2D, HIST1H1D, HIST1H2BC) [29]. These findings suggest that BL11q is closer to other germinal center derived B-cell lymphomas rather than BL and support its inclusion as a separate provisional entity. Also noted were isolated cases with single 11q24.1-qter terminal loss, or 11q23 gain with 11q24-qter copy number neutral loss of heterozygosity, identified using copy number arrays, which may be clinically valuable until FISH probes have been further studied in these cases. Additionally, the specific 11q alteration in this entity should be distinguished from other 11q aberrations, including 11q24 gains (including ETS1 and FLI1) described in DLBCL, 11q25 losses (missing ETS1 and FLI1) described in some post-transplant lymphoproliferative disorders, and 11q23 gain/11q24-qter loss seen in transformed follicular lymphomas [32]. 11q gain/loss is also not specific for BL11q, but has been demonstrated to occur recurrently in both MYC-rearranged BL and MYC-rearranged HGBL [33]. The 2016 WHO also describes a “certain degree of cytological pleomorphism” to these cases, with Gonzalez-Farre et al. describing a series of 11 cases noting a prominent starry sky pattern and high proliferation rate, but cytological departures from the typical BL, meriting initial classification as high-grade B-cell lymphoma or BCLU [29]. A recent study of 75 cases of BL, 12 cases of HGBL, NOS, and 3 cases of BL11q demonstrated immunohistochemical negativity for LMO2 and positivity for CD38 in 74/75 cases of BL and 3/3 cases of BL11q [34]. LMO2 was positive in 12/12 cases of HGBL NOS, suggesting a potential utility of LMO2 and CD38 immunostaining in separating BL from HGBL NOS, but not from BL11q. By contrast, a recent series of 10 BL11q cases demonstrated immunohistochemical positivity for LMO2 in 7/10 cases, and additionally describe a distinct flow cytometric immunoprofile in BL11q, with CD16/CD56 expression in 6/10 BL11q cases (and none in BL cases), greater expression of CD45 in BL11q than in BL cases, and lesser CD38 expression (comparable to T-cells) in BL11q than in BL [35]. The authors suggest LMO2/CD56 immunohistochemistry and CD16/CD56 with CD38 flow cytometry in screening aggressive CD10+ B-cell neoplasms. Recently, the morphological feature of coarse apoptotic debris within starry sky macrophages has been identified in association with these tumors, and should prompt assessment of 11q status [36]. The clinical course of BL11q seems to be similar to that of BL, though very few cases have been reported. Future studies will require screening of cases for 11q aberrations, either by FISH or copy number analysis, and particularly in children and younger patients. Overall, the 2016 classification as a provisional entity helped provide a framework for further characterization of such cases as intended. New terminology has been introduced as large B-cell lymphoma with 11q aberration (ICC) and high-­ grade B-cell lymphoma with 11q aberration (WHO5) to better recognize that they may have features distinct from both BL and other forms of DLBCL/HGBL.

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EBV-Positive DLBCL, NOS The 2008 WHO classification included a provisional entity called “EBV-positive DLBCL of the elderly”, which occurred in immunocompetent patients >50 years old, had a worse prognosis than EBV negative tumors [7], and were postulated to be the result of defective immune surveillance for EBV as a result of aging (Fig. 2.8). EBV+ DLBCL has now been recognized to occur in younger patients as well, prompting removal of “the elderly,” and replacement with “not otherwise specified” to distinguish from other EBV+ large B-cell lymphomas, including lymphomatoid granulomatosis. The 2016 WHO required that 80% of the atypical cells are positive by EBV-encoded small RNAs (EBER) in situ hybridization, in order to exclude misinterpretation of staining bystander non-malignant B-cells in EBV- or T-cell lymphomas [1] (see Figs. 2.1c, d and 2.8). The seminal study by Nicolae et  al. of 46 EBV+ DLBCL patients, all under 46 years of age, demonstrated a similar male predominance, a lesser extent of extranodal disease, and notably a significantly better overall survival as compared to a

b

c

Fig. 2.8  EBV-Positive Diffuse Large B-cell lymphoma involving the colon. While this case did occur in an elderly male, a bimodal distribution is recognized with these lymphomas also occurring in younger patients. Hematoxylin and eosin-stained sections are shown in (a) 10× and (b) 40× objective. The atypical lymphoid proliferation shows a degree of pleomorphism, including occasional multinucleated forms (b). There is extensive associated necrosis (a). The diagnosis requires that >80% of tumor cells are positive for the EBV non-coding RNA, EBER, by in situ hybridization as can be seen in (c), 40× objective. The diagnostic entity name is preserved in the ICC from the fourth Revised WHO with WHO5 dropping the “not otherwise specified” qualifier. (Image courtesy of Genevieve Crane, MD, PhD, Cleveland Clinic, Cleveland, OH)

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elderly patients with EBV+ DLBCL [37]. Cases were found to have morphological heterogeneity and divided into three histological groups: a large subset resembling T-cell/histiocyte-rich large B-cell lymphoma (THRLBCL-like), a group resembling gray zone lymphoma (EBV+ GZL), and a group of EBV+ DLBCL, NOS.  The WHO suggests reserving the term THRLBCL for EBV negative cases, and EBV positive cases are regarded as the TLHRLCL-like pattern of EBV+ DLBCL. THRLBCL-like cases appear to have a better prognosis, typically occurring in younger patients than monomorphic EBV+ DLBCL [1]. EBV+ DLBCL cells are variably positive for EBER, EBV latent membrane protein 1 (LMP1), and EBV nuclear antigen 2 (EBNA2), and can be sorted into latency II (LMP1+, EBNA2-) or latency III (LMP1+, EBNA2+) subtypes. In the series by Nicolae et  al., the younger cohort were predominantly latency type II, a pattern more in keeping with an immunocompetent patient [38]. EBV+ DLBCLs also usually have an ABC/non-GCB cell of origin subtype, as well as CD30 expression, both related to LMP1 expression. Mutations in CD79B, CARD11, and MYD88, which are often found in ABC DLBCL, are absent in this entity, though gene expression profiling shows activation of the JAK/STAT and NF-κB pathways . Clonality of the IG genes can usually be detected, and can be helpful in distinguishing EBV+ DLBCL from infectious mononucleosis and reactive hyperplasia [39]; fewer than half of all cases of EBV-positive mucocutaneous ulcer demonstrate clonal IG gene rearrangements [1]. The addition of rituximab to chemotherapy regimens likely improved survival even beyond the good outcomes associated with younger age in lymphoma patients. The tumor cells also showed PD-L1 positivity, and high expression of PD-L1 and indoleamine 2,3-dioxygenase in the histiocytic/dendritic cell microenvironment. This combined expression likely has an immunosuppressive effect and promotes tumor immune escape, though it did not appear to have a negative prognostic impact on the study cohort [37]. The PD-L1/PD-1 pathway represents a potential therapeutic approach for EBV+ DLBCL and is under investigation in ongoing clinical trials. Immunotherapy may also offer additional promise in these patients, with chimeric antigen receptor (CAR) T-cells directed against LMP1, already in use in other EBV-­ driven neoplasms [39]. The 2022 revisions for this entity feature a minor difference in nomenclature: the ICC retains the same name with the “NOS” suffix, whereas the WHO5 removes “NOS”.

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22. Klapproth K, Wirth T. Advances in the understanding of MYC-induced lymphomagenesis. Br J Haematol. 2010;149(4):484–97. 23. Aukema SM, Siebert R, Schuuring E, van Imhoff GW, Kluin-Nelemans HC, Boerma EJ, et al. Double-hit B-cell lymphomas. Blood. 2011;117(8):2319–31. 24. Swerdlow SH. Diagnosis of ‘double hit’ diffuse large B-cell lymphoma and B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and Burkitt lymphoma: when and how, FISH versus IHC. Hematology Am Soc Hematol Educ Program. 2014;2014(1):90–9. 25. Rosenthal A, Younes A. High grade B-cell lymphoma with rearrangements of MYC and BCL2 and/or BCL6: double hit and triple hit lymphomas and double expressing lymphoma. Blood Rev. 2017;31(2):37–42. 26. Pillai RK, Sathanoori M, Van Oss SB, Swerdlow SH.  Double-hit B-cell lymphomas with BCL6 and MYC translocations are aggressive, frequently extranodal lymphomas distinct from BCL2 double-hit B-cell lymphomas. Am J Surg Pathol. 2013;37(3):323–32. 27. Cuccuini W, Briere J, Mounier N, Voelker HU, Rosenwald A, Sundstrom C, et  al. MYC+ diffuse large B-cell lymphoma is not salvaged by classical R-ICE or R-DHAP followed by BEAM plus autologous stem cell transplantation. Blood. 2012;119(20):4619–24. 28. Landsburg DJ, Ayers EC, Bond DA, Maddocks KJ, Karmali R, Behdad A, et  al. Poor outcomes for double-hit lymphoma patients treated with curative-intent second-line immunochemotherapy following failure of intensive front-line immunochemotherapy. Br J Haematol. 2020;189(2):313–7. 29. Gonzalez-Farre B, Ramis-Zaldivar JE, Salmeron-Villalobos J, Balagué O, Celis V, Verdu-­ Amoros J, et al. Burkitt-like lymphoma with 11q aberration: a germinal center-derived lymphoma genetically unrelated to Burkitt lymphoma. Haematologica. 2019;104(9):1822–9. 30. Salaverria I, Martin-Guerrero I, Wagener R, Kreuz M, Kohler CW, Richter J, et al. A recurrent 11q aberration pattern characterizes a subset of MYC-negative high-grade B-cell lymphomas resembling Burkitt lymphoma. Blood. 2014;123(8):1187–98. 31. Wagener R, Seufert J, Raimondi F, Bens S, Kleinheinz K, Nagel I, et al. The mutational landscape of Burkitt-like lymphoma with 11q aberration is distinct from that of Burkitt lymphoma. Blood. 2019;133(9):962–6. 32. Ferreiro JF, Morscio J, Dierickx D, Marcelis L, Verhoef G, Vandenberghe P, et  al. Post-­ transplant molecularly defined Burkitt lymphomas are frequently MYC-negative and characterized by the 11q-gain/loss pattern. Haematologica. 2015;100(7):e275–9. 33. Grygalewicz B, Woroniecka R, Rymkiewicz G, Rygier J, Borkowska K, Kotyl A, et al. The 11q-gain/loss aberration occurs recurrently in MYC-negative Burkitt-like lymphoma with 11q aberration, as well as MYC-positive Burkitt lymphoma and MYC-positive high-grade B-cell lymphoma, NOS. Am J Clin Pathol. 2017;149(1):17–28. 34. Liu Y, Bian T, Zhang Y, Zheng Y, Zhang J, Zhou X, et al. A combination of LMO2 negative and CD38 positive is useful for the diagnosis of Burkitt lymphoma. Diagn Pathol. 2019;14(1):100. 35. Rymkiewicz G, Grygalewicz B, Chechlinska M, Blachnio K, Bystydzienski Z, Romejko-­ Jarosinska J, et al. A comprehensive flow-cytometry-based immunophenotypic characterization of Burkitt-like lymphoma with 11q aberration. Mod Pathol. 2018;31(5):732–43. 36. Horn H, Kalmbach S, Wagener R, Staiger AM, Hüttl K, Mottok A, et al. A diagnostic approach to the identification of Burkitt-like lymphoma with 11q aberration in aggressive B-cell lymphomas. Am J Surg Pathol. 2021;45(3):356–64. 37. Nicolae A, Pittaluga S, Abdullah S, Steinberg SM, Pham TA, Davies-Hill T, et al. EBV-positive large B-cell lymphomas in young patients: a nodal lymphoma with evidence for a tolerogenic immune environment. Blood. 2015;126(7):863–72. 38. Said J. The expanding spectrum of EBV+ lymphomas. Blood. 2015;126(7):827–8. 39. Castillo JJ, Beltran BE, Miranda RN, Young KH, Chavez JC, Sotomayor EM. EBV-positive diffuse large B-cell lymphoma, not otherwise specified: 2018 update on diagnosis, risk-­ stratification and management. Am J Hematol. 2018;93(7):953–62.

Part II

Methods

Chapter 3

Cytogenetics and FISH in Precision Molecular Pathology of Aggressive B-Cell Lymphomas Yi Ning and Jocelyn Reader

Introduction Aggressive B-cell lymphomas are the most prevalent form of non-Hodgkin lymphoma with heterogeneous morphological, immunophenotypic, and genetic features. Integration of specific morphological, immunohistochemical (IHC), and cytogenetic findings has significantly improved diagnosis and management of these lymphomas. The importance of cytogenetic findings in classification of aggressive B-cell lymphomas is reflected in the 2016 revision of the WHO classification of lymphoid neoplasms [1]. High-grade B-cell lymphoma traditionally designated B-cell lymphomas that are morphologically aggressive with increased mitotic activity, often a starry sky pattern, and a high proliferation rate as shown by Ki-67 expression and these features correlate with aggressive clinical behavior [2]. A new category “high-grade B-cell lymphoma”, including rearrangements of MYC and BCL2 and/or BCL6, has been established. This recognition not only has prompted the development of clinical trials focused on the high-risk subgroups but also may have immediate treatment implications [3]. We discuss karyotype and FISH analyses of aggressive B-cell lymphomas in this chapter. The importance of HGBL with MYC and BCL2 rearrangements continues to be emphasized in the 5th edition WHO and ICC released in 2022.

Y. Ning (*) Department of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA e-mail: [email protected] J. Reader Department of Obstetrics, Gynecology and Reproductive Medicine, University of Maryland School of Medicine, Baltimore, MD, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_3

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 onventional Cytogenetic Study of Aggressive C B-Cell Lymphomas Giemsa banding-based karyotype analysis is the conventional method for the detection of chromosomal abnormalities in hematological malignancies. It allows scanning of the entire genome in a single test. While this analysis has limited resolution, it remains the most comprehensive method to investigate the genetic complexity of lymphomas in individual cells. Karyotype analysis can be performed on bone marrow aspirates, lymph node and tissue samples. Short-term tissue culture is required to obtain dividing cells. When the cultures yield metaphase cells, karyotype analysis can be performed to identify numerical and structural abnormalities in individual cells. Identification of specific cytogenetic aberrations has contributed to the diagnosis and risk stratification of lymphoma subtypes [4, 5]. Diffuse large B-cell lymphoma (DLBCL) is the most common histological subtype of non-Hodgkin lymphomas. A major change in the revised WHO classification of DLBCL is the recommendation that routine practice should recognize tumors belonging to the germinal center B-cell (GCB) and activated B-cell (ABC) subsets [1]. Although cell-of-origin is useful for predicting outcome, the GCB and ABC subtypes remain heterogeneous. Next-generation sequencing (NGS) analysis of DLBCL has facilitated global identification of numerous and diverse genetic abnormalities in these tumors and has shown differences in the molecular pathogenesis of GCB and ABC tumors [6]. High-grade B-cell lymphomas (HGBL) is a general designation that was used for B-cell lymphomas with high-grade features, including increased mitotic activity and high proliferation rate. Most DLBCLs with aggressive clinical features are associated with complex karyotypes. A large spectrum of chromosomal abnormalities have been identified through karyotype analyses of DLBCL. While the occurrence of genetic rearrangements in B-cell neoplasms, including rearrangements involving MYC, BCL2, and BCL6, has been recognized for decades, the clinical feature-based classification was not defined until recently [7–9]. Zhao et al. reported on the cytogenetic study of tumor samples from lymph nodes or extranodal tissues from 231 patients diagnosed with primary/de novo DLBCL. Complex karyotypes were observed in 89.1% of the samples [10]. A large cytogenetic study of bone marrow samples from 1585 patients with newly diagnosed DLBCL was described by Kim et al. [11]. They found that two or more cytogenetic abnormalities were associated with inferior overall survival (OS) compared with a normal karyotype or single abnormality in both patients with histological bone marrow involvement (5-year OS, 16.5% vs. 52.7%; P  6 repeated nucleotides is problematic

NGS next-generation sequencing, PCR polymerase chain reaction, bp base pair(s), Gb gigabases

Sequencing Currently there are two sequencing platforms that are widely used in the clinical molecular diagnostic laboratories: the Illumina (Illumina) and the Ion Torrent (Thermo Fischer Scientific) platforms. These two platforms utilize the same sequencing-by-synthesis principle, but are different in sequencing chemistry and signal generation/detection. Each platform has its own advantages and disadvantages, and understanding these sequencing concepts will assist the pathologist in interpreting the results. Key differences in the platforms are listed in Table 4.2.

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Illumina adaptor

a P5

I5 Index

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UMI

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Ion Torrent adaptor UMI

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SP = Universal Sequencing primers P1 = P1 Graft binding adapter

Fig. 4.5  The Illumina platform (a) uses two graft binding sequences, P5 and P7, with one on each side of the DNA insert. The Ion Torrent platform (b) uses one graft binding sequence. An adaptor generally consists of (1) the graft binding sequence; a specific sequence complementary to the oligonucleotide graft attached to the solid plane in the sequencing platform; (2) the sequencing primer; an initiating site for sequencing reaction; (3) unique molecular indices (UMIs), 12-­nucleotide sequences used to identify each DNA molecule prior to amplification; and (4) the sample index sequence (sample ID barcode), a short sequence unique to each sample in the batch. For PCR-based target genes (panel) sequencing, the sample index is usually attached to the library DNA after target enrichment

Instruments/Platform Illumina (Fluorescently-Labeled Reversible-Terminator Sequencing) The distinct features of the Illumina sequencing platform are bridge-amplification cluster generation and block-reversible nucleotide utilization. The first feature is for generating clonal clusters of DNA to amplify signal. The second feature is for accurate sequencing signal detection using fluorescence-tagged block-dNTPs (Fig. 4.5). The sequencing reaction occurs on an instrument-specific chamber called a “flow cell”. The flow cell has a solid two-dimensional plane that serves as the reaction surface. Numerous oligonucleotides are attached to the reaction surface that are complementary to the graft binding sequences of the adaptor. The Illumina platform uses two graft binding sequences, P5 and P7, with one on each side of the DNA insert (Fig. 4.5a). When the library DNA enters the flow cell, microfluidics distributes it evenly throughout the reaction surface and each DNA molecule (with ligated

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In a tube (by emulsion PCR)

Library of fragments with region of interest

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PCR clonal amplification 1 2

PCR clonal amplification 3

Distribution of each amplified fragment on sequencing matrices 1 2 3

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Fig. 4.6  Clonal cluster generation of Illumina and Ion Torrent platforms. The Illumina platform generates the cluster on two-dimensional flow cell plane while the Ion Torrent platforms generate the clonal cluster on suspending microbeads. (Reprinted from Huang J, Chen N, Press R. Molecular Methodologies and Molecular Pathology of Hematolymphoid Neoplasms. In: Cheng L, Bostwick D, editors. Essentials of Anatomic Pathology. Cham, Switzerland: Springer; 2016, with permission from Springer Nature [29])

adaptor) binds to the surface of the flow cell. With proper concentration and distribution of the library DNA, each DNA molecule bound to the flow cell is surrounded by empty grafts. These empty grafts will function as binding sites for the free-end of the bound DNA, forming a loop or bridge. Then each cluster will be amplified, generating a local cluster of DNA clones (around 1000 copies from a single original DNA fragment) (Fig. 4.6, left). These clones serve as templates for the sequencing reaction. During the sequencing phase, the system uses modified nucleotides as building blocks and signal generators. Each nucleotide is tagged with a fluorophore; four colors correspond to each type of nucleotide. They also contain a reversible reaction

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blocker that prohibits the 3′ extension of the DNA. This allows only one nucleotide to be incorporated into the each synthesized strand in each cycle. After fluorescently tagged nucleotide incorporation, a snapshot of the flow cell provides a nucleotide read from all of the DNA clusters in the flow cell. After the image is recorded, enzymes cleave the fluorescent dyes and the 3′ reaction blocker, allowing the next nucleotide to be incorporated in the next cycle. These nucleotide incorporation and blocker removal cycles continue until the desired length or read length limit is reached. Then, short reaction cycles are performed to flip the template by utilizing the paired adaptor (P5 to P7). This allows the sequencing to be performed again on the opposite direction. This bi-directional paired end sequencing is another advantageous feature of the Illumina platform and serves to increase read accuracy. Ion Torrent (Semiconductor H+ Chip Sequencing) Instead of an optical signal from nucleotide-specific fluorophores, the Ion Torrent system uses a semiconductor chip to detect electrical signals. When a nucleotide is incorporated into the DNA, the chemical reaction releases a free hydrogen ion (H+). These hydrogen ions alter the pH of the surrounding fluid, which is detected by a specialized semiconductor chip [33] (Fig. 4.7). Instead of a solid surface as used by Illumina, the oligonucleotide graft for the Ion Torrent system is attached to a floating microbead. Each bead captures one fragment of library DNA, which will then be amplified to completely occupy the grafts on the surface of the bead. In this sense, each bead is a clone of an original template DNA similar to the clusters generated by the Illumina system. This can be achieved by a process called emulsion PCR. By creating an emulsion of water and oil, water molecules form microspheres in the oil media. These microspheres serve as reaction microchambers. With proper conditions, each microsphere will house one DNA molecule attached to one microbead. Clonal amplification occurs within this microsphere, resulting in the microbeads being coated with clonal DNA (Fig. 4.6, right). The solution with amplified beads is put into the sequencing chip, which has numerous microwells on the sequencing surface. Each well will house one bead, and will detect a change in pH within the well during the sequencing cycles. Unmodified nucleotides are added sequentially. If there is a nucleotide incorporation event, the pH drops. The H+ released from reaction is equimolar to the nucleotide incorporated. Therefore, for strings of identical nucleotides, signal is created in proportion to the number of nucleotides (similar to the pyrosequencing). As expected, this system has difficulty sequencing long homopolymers. The emulsion/bead clonal amplification is uni-directional, resulting in one read per DNA fragment. However, electrical signals can be detected and processed faster than a fluorescent image, making this system faster than fluorescent-labeled reversible terminator sequencing. Millions of reads can be generated within a few hours, making the system useful for a small target panel with a fast turnaround time.

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Fig. 4.7  Ion Torrent platform utilized pH change during nucleotide incorporation as a method to determine the genetic sequence. Unmodified nucleotides are added sequentially. If there is a nucleotide incorporation event, the pH drops due to H+ release from the reaction. The system detects this H+ and is able to determine the nucleotide at that particular position. (Reprinted from Huang J, Chen N, Press R.  Molecular Methodologies and Molecular Pathology of Hematolymphoid Neoplasms. In: Cheng L, Bostwick D, editors. Essentials of Anatomic Pathology. Cham, Switzerland: Springer; 2016, with permission from Springer Nature [29])

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A Brief Outline of Third-Generation MPS The MPS platforms described in the previous section generate the signal from clones that are amplified from the original template DNA. This is necessary to generate sufficient signal from the reaction. However, the amplification inevitably introduces sequencing error and/or amplification bias into the output sequence. It also significantly increases the turnaround time of an assay. The ability to read and sequence the DNA from a single molecule without the need for amplification is the conceptual underpinning of the generation of MPS. Technology such as Zero-mode Waveguides [34] enables an instrument to record fluorescent signals emitted by incorporated nucleotides from a single DNA molecule [35]. Nanopore technology allows long DNA strands to pass through a small channel and an instrument then measures ionic signal unique to each nucleotide when each of them passes through the gate [36], allowing DNA sequence to be read without the need for pre-­sequencing DNA modification. Nevertheless, in clinical practice, fluorescently labeled reversible-­terminator sequencing and semiconductor H+ chip sequencing will stay relevant for the foreseeable future.

Bioinformatic Processes Fundamentally, bioinformatic processes after NGS are not different from that performed after Sanger sequencing: the sequence is read and checked for quality, aligned to the reference genome, and alterations or variations from the reference genome are noted. However, NGS platforms generate huge amounts of sequence data, currently up to 15–60 billion bases per run for commercially available systems. An NGS run in a clinical laboratory may multiplex 15–25 samples in one flow cell or sequencing chip. Computationally intensive bioinformatics processes are required to deconvolute these reads, align them to the reference genome, and determine the presence of alterations from the reference genome. Primary Data Processing The primary data is a collection of millions of read sequences including the adaptor sequences (sample indices, UMIs, etc.). Each nucleotide will be accompanied by its quality score, determining the error probability of that particular nucleotide. This probability of error is calculated from several factors such as strength of the signal, noise signal in the similar region, and read complexity. The sample index, ligated during library preparation, enables the system to be able to accurately assign each read to the correct patient’s sample in that run. The output of this process is called a

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FASTQ file, which is a simple text file. However, consumer-grade text editors may not be able to handle a large text file and specialized applications may be needed to view this file directly. Read Mapping and Alignment The next step is to map these reads onto the reference genome. This process is not as straightforward as the FASTQ generation. The human genome of different individuals are not identical and each person has thousands of DNA polymorphisms. Neoplastic cells also contain somatic mutations. Therefore, mapping and alignment of the reads are not just matching the reads to the reference genome; alignment mismatch must be allowed to a certain degree. If alignment criteria are too stringent, most of the reads will not be aligned and excluded due to mismatches. At the same time, if alignment criteria are too lax, there will be too many misalignments, which will also result in incorrect variant calling. Alignment criteria need to be balanced and validated for each test panel offered for clinical testing. Importantly, large insertions or deletions cause problems during alignment. There can be insufficient normal sequence to map the read to the genome. Therefore, knowledge about genomic landscape of a particular disease in question is important for the assay design and interpretation. The output with aligned reads is called a BAM file. This file can be opened by a genome browser such as IGV (Fig. 4.8) [37]. Variant Calling After reads are aligned to the reference genome, variant calling is the next step. Variants are differences in the sequence between the read and the reference genome. From a bioinformatic perspective, a variant can be a single nucleotide variant (SNV), a small or large insertion or deletion (indel), a fusion/translocation between two non-contiguous genes, a duplication (dup), an inversion (inv), or a copy number variation (CNV). The mutation panels widely used in the clinical laboratory are predominantly focused on SNVs and small indels, as these are the types of variants that are more easily (and sensitively) detected by routine NGS/bioinformatics methodologies. RNA-based gene fusion panels are now gaining more usage in the clinical setting and will be discussed in another chapter. Nevertheless, most laboratories still rely on cytogenetic/FISH methods for large structural alterations and gross chromosomal translocations (such as IGH-MYC fusion), and this chapter will focus on SNVs and short indels as they are the main variants detected by routine NGS-­ based assays. The variant calling process is usually performed by multiple software algorithms (variant callers). As the logic of calling SNVs and indel differs, variant calling pipelines often utilize multiple complementary algorithms, each with a strength for detecting different mutation types. A BAM file from a sample is then often analyzed by multiple variant callers, allowing specialized callers to be used as ancillary tools

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to an ‘all-purpose’ variant calling algorithm. The bioinformatic specifics of variant callers is beyond the scope of this chapter. Another critical step in NGS data processing is variant filtering. Called variants will include known benign germline polymorphisms, which many labs will want to exclude when evaluating cancer samples for actionable somatically acquired pathogenic mutations. Filtering strategies should be adjusted based on the genes of interest, clinicopathological findings, and the intended clinical use of the NGS assay. Professional guidelines are a useful resource and, although often not reflective of the rapidly advancing science/technology, are essential tools for maintaining inter-­ laboratory reproducibility, reporting standardization, and assay precision [38].

Variant Analysis and Annotation Variants are defined as sequence reads that differ from the reference genome; they may be clinically significant actionable pathogenic mutations, benign polymorphisms, or variants of unknown significance. Each variant must be analyzed and annotated within the specific clinical context of the patient’s case. To analyze these variants and interpret the mutational profile requires a significant amount of background knowledge and experience. A deep understanding of gene function and pathogenesis/oncogenesis for each particular disease is required. In addition, high-­ quality variant analysis and annotation requires an understanding of the basic biochemistry of DNA and RNA, population genetics, a patient’s current clinical setting, and the pathology of the disease under investigation. Professional societies have come up with consensus guidelines to standardize clinical NGS reporting. There are two major guidelines currently widely used: American College for Medical Genetics (ACMG) guidelines for inherited diseases [39] and Association for Molecular Pathology/American Society for Clinical Oncology/College of American Pathologists (AMP/ASCO/CAP) guideline for cancer/neoplasia [40]. Although the focus of this book as well as most oncologic NGS gene panel testing is neoplastic diseases, the framework of the ACMG guidelines provides interpretation logic for some somatic variants that can be situationally applied. Moreover, as many of the somatically acquired mutations targeted by cancer NGS panels also occur in the germline, encountering a germline variant of potential clinical relevance in a lymphoma (or other cancer) sample is not uncommon. A complete discussion on ACMG and AMP/ASCO/CAP guidelines is beyond the scope of this chapter. This section will provide an outline for practical variant interpretation for the practicing pathologist. The first, and preferred, method to determine the clinical relevance (i.e. “actionability”) of each variant is to ascertain the breadth of existing knowledge about that variant. A significant proportion of actionable oncogenic mutations are recurrent and many of them have been thoroughly studied. The COSMIC database is a commonly used database of somatic variants previously identified in a variety of cancers

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Fig. 4.8  The figure shows the standard screenshot of the IGV (version 2.4.10) user interface. The top panel displays the reference genome currently used by the software and the genomic position of the region currently displayed in the main interface. The lower panel displays the gene reference sequence and the corresponding protein sequences. Multiple protein sequences are displayed due to the presence of multiple transcripts and reading frames. The blue arrow indicates the reference transcript currently used for analysis (in this case transcript reference NM_002468, exon 5, leucine 265 residue). This position corresponds to codon “CTG” in the above reference gene sequence. The thin horizontal line on the left-handed side of the protein sequences represents the intron, with an arrow indicating the direction of the reference strand (in this case a forward strand). The central space in the screen shows the coverage and read tracks. The horizontal bars in the read track, highlighted by the green arrow, represent individual sequence reads. Each bar represents one unique read, and the total number of these bars indicates the total read counts or sequencing depth. The red and blue colors of each read in the read track correspond to the direction of sequencing (e.g. 5′ to 3′ or the reverse). All reads cannot be functionally displayed when the read depth is high, so read depth is visually displayed by the height of the grey vertical bars in the coverage track immediately above the read tracks, with a higher bar representing greater sequencing depth. The black arrow highlights mutant reads at a particular codon. Here, there is a frequent T to C mutation (T = red, C = blue, A = green, G = brown) resulting in a nucleotide change from CTG to CCG and Leucine to Proline (p.L265P). The nucleotide reads are sorted by nucleotide, and the rare A and G nucleotides present represent the low-level background noise inherent to the assay. The magnified view is present with the sequencing artifact intentionally removed to make the figure conceptually clear for the audience, but low-level background reads are expected to be present in ‘real life’ analyses

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[41]. Virtually all variants with strong clinical significance (i.e. entity-defining variants and FDA-approved targetable variants) and variants of potential clinical significance will be reported in association with particular tumor types in COSMIC.  Examples of these variants include MYD88 p.L265P, BRAF p.V600E, and KRAS p.G12D. These types of common variants are easy to identify and annotate, often by automated or semi-automated algorithms within the bioinformatics/ interpretive pipeline. Variants that are rare in public databases and the medical literature can often have their pathogenicity accurately predicted based on the type of variant. For example, tumor suppressor genes (TSG) typically become cancer drivers after they undergo loss-of-function mutations. Therefore if a rare variant in a TSG is a truncating variant involving an important functional domain of the protein, the likelihood of that variant being pathogenic will be high. This can be a nonsense variant, frameshift variant with early stop gain, start loss variant (missense at the first methionine residue), or splice variant. These loss of function variants can be presumed pathogenic in most cases even if they have not been previously reported. On the contrary, the pathogenicity of non-truncating variants in TSG’s are more difficult to predict as they can be benign or oncogenic. Another useful source of information for variant interpretation is a population database such as dbSNP [42] or gnomAD [43]. These public databases are collections of genetic variation data from large numbers of “healthy” human subjects (of known ethnicity) without known disease. The general assumption is that a germline variant with 1% or more prevalence in the normal population is unlikely to be oncogenic; however, as we gain more experience sequencing large numbers of healthy subjects, exceptions to this rule are frequently identified. Similar to medical practice in any other specialty, molecular pathology is both an evidence-based practice and also requires subjective interpretation of incomplete data. Variant analysis and interpretation should be based on the best available evidence. Final decisions about the pathogenicity of variants still often requires a judgment decision, preferably with interdisciplinary communication such as discussion at a molecular tumor board.

 orrelation with Pathology/Clinical Information C and Report Preparation Genomic information alone, interpreted without an appropriate clinical/pathological context, can sometimes be misleading. The molecular result that does not seemingly correlate with pathological and clinical information (as with any other lab result) should be questioned and revisited. At the very least, sample swap and contamination, although unusual, are always a possibility in any molecular (or other)

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clinical laboratory test. Even without laboratory errors, molecular results that do not adequately explain the pathological and clinical status of a particular patient at a particular time may uncover an alternative pathological process within the patient (and/or family). Therefore, complete clinicopathological correlation should always be performed by the molecular pathologist at the result interpretation and report preparation steps. As molecular science/information is becoming increasingly more complex, not all health care providers possess the same level of understanding of genomic medicine. Explanations of the clinical significance of molecular findings should then be included in reports as appropriate. For example, when reporting a variant of unknown significance in a well-known oncogene (such as BRAF), one should consider including a note in the report specifying that this variant may not be a candidate for specific targeted therapy.

Common Problems and Troubleshooting One commonly encountered issue in NGS interpretation is discriminating between acquired somatic mutations and inherited germline mutations. The gold standard to determine any variant’s somatic-germline status is a comparison of the sequencing result between neoplastic tissue and normal/non-neoplastic tissue. In practice, this means doubling the sequencing resources and pre-sequencing infrastructure to include the collection and analysis of a matched normal tissue sample. Unlike solid tumors, hematolymphoid neoplasms can circulate within the body. Therefore, even normal-appearing tissue may contain neoplastic hematopoietic cells that can sometimes confound data interpretation. Since NGS studies have quantitative output, the variant allele fraction (VAF) can often be used to inform germline versus somatic status. As a germline variant will appear in every cell (except when mosaic), heterozygous germline variants will have a VAF around 50% while homozygous germline variants will have a VAF of nearly 100%. If a variant is present at an allele fraction significantly disparate from 50% or 100%, and this VAF is not the result of technical inaccuracies, it likely represents a somatic variant. A common caveat, however, is that if there are genomic copy number variations within the tumor, this simple 50% VAF “rule of thumb” may not apply. As always, quantitative VAF information should thus be used in combination with all other genetic, pathological, and clinical information available. In our practice, we generally analyze each variant based on its potential biochemical pathogenicity, regardless of whether it is germline or somatic. If it has clinical significance, then we will further determine whether there are any different clinical implications if the variant is germline versus somatic. In the frequent instances in which we cannot accurately distinguish germline from somatic variants, we provide information for both possibilities in the report. In medical centers where anti-cancer treatment efficacy is monitored by molecular methods, the post-treatment sample, often with a lower tumor burden, can definitively clarify the somatic versus germline dilemma. If the variant is truly somatically acquired (and the tumor volume is

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reduced by treatment), it will often show a proportionally reduced VAF. In contrast, a persisting 50% VAF after treatment (in the setting of a reduced tumor burden) is convincing evidence for that variant being of germline origin. Another common interpretive issue is to determine whether a variant is a true somatic cancer-associated variant or a technical artifact (false variant), especially when dealing with low-level variants in the setting of neoplastic subclones or minimal residual disease analysis. Each laboratory should perform assay validation that addresses this issue [38] by determining their assay-specific limit of detection for various classes of mutations.

Utilization of NGS in B-Cell Lymphoma NGS is able to generate a vast amount of genetic data from normal and neoplastic cells, and underlies remarkable gains in understanding the genetic basis of disease and the promise of personalized medicine. NGS has several practical applications in the evaluation of B-cell lymphomas, which are discussed further below.

Interrogating Genomic DNA for Gene Mutations Before the age of NGS, the most characterized genetic hallmarks of B-cell lymphomas were chromosomal translocations. Many B-cell lymphoma subtypes are still defined (entirely or partly) by translocations (e.g., t(11;14)(q13.3;q32.3) in mantle cell lymphoma, among others). Now that NGS has become widely available, clinically relevant point mutations have also been characterized in B-cell lymphoma subtypes. Combinations of point mutations and other genetic aberrations detected by NGS have been shown to be relevant in the subtyping of lymphomas that have not previously had a clear genetic definition, or those with high genetic heterogeneity such as diffuse large B-cell lymphoma (DLBCL) [44]. Many genes (MYD88, CD79B, NOTCH1, EZH2, etc.) may also be candidates for entity-defining mutations or patterns of mutations in future classification schema [45].

 etecting Fusion Transcripts Consequent D to Gene Rearrangement As NGS can also be performed using cDNA converted from mRNA transcripts, gene fusion detection can also be performed by NGS. The ability to multiplex hundreds of fusion targets within the same NGS panel makes this a potential tempting alternative to current FISH assays, in which a specific probe is required for each

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fusion/translocation target. Unlike mutations, oncogenic translocations are usually mutually exclusive from each other and the list of known oncogenic translocations is small (but ever-expanding). Thus, using a large NGS-based fusion panel rather than FISH may not be turnaround time efficient or economically appropriate. However, the cost of NGS is expected to continue to decrease, and NGS turnaround time should decrease with future automation, making NGS a potential future application for detecting clinically relevant gene rearrangements.

 etermining Clonality Via Antigen Receptor D Gene Rearrangements PCR-based amplicon-sizing assays [46] are currently the gold standard for antigen receptor gene rearrangement clonality testing. However, determining a clone based on amplicon size alone is not sensitive, as low-level clones may hide under the signals from DNA derived from other lymphocytes with the same sized fragments. In addition, the interpretation of the size-based clonality assay is, even with standard guidelines, substantially subjective and non-reproducible. With NGS, clonal lymphocyte populations can be determined by their exact antigen receptor sequences rather than amplicon size [47]. This increased sensitivity and specificity makes it possible, for example, to monitor a minimal residual disease B-cell lymphoma clone in a polyclonal background. It can also provide additional information such as somatic hypermutation and VDJ usage. The use of NGS for clonality assessment will be discussed in detail in Chap. 5.

Expression Profiling/RNA Transcriptome Gene expression profiling in B-cell lymphoma has been studied for decades and underlies major subclassification schemes such as for DLBCL [48]. However, gene expression analysis assays have not been routinely available in most laboratories. With the increasing availability of NGS, which can interrogate the mRNA transcriptome, this information will become more accessible. This particular utilization of NGS in B-cell lymphoma will also be discussed in a subsequent chapter.

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Epigenetics NGS can also be used to evaluate the methylation status of large areas of the genome. Several studies have used methylation profiles as a tool for categorizing lymphoma [49, 50]. As the methylation profile is closely related to gene expression, this technique has the potential to become an integrated component of comprehensive tumor profiling.

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18. Murphy KM, Levis M, Hafez MJ, Geiger T, Cooper LC, Smith BD, et al. Detection of FLT3 internal tandem duplication and D835 mutations by a multiplex polymerase chain reaction and capillary electrophoresis assay. J Mol Diagn. 2003;5(2):96–102. 19. De Wit P, Pespeni MH, Ladner JT, Barshis DJ, Seneca F, Jaris H, et al. The simple fool’s guide to population genomics via RNA-Seq: an introduction to high-throughput sequencing data analysis. Mol Ecol Resour. 2012;12(6):1058–67. 20. Brown RS, Edwards J, Bartlett JW, Jones C, Dogan A. Routine acid decalcification of bone marrow samples can preserve DNA for FISH and CGH studies in metastatic prostate cancer. J Histochem Cytochem. 2002;50(1):113–5. 21. Choi SE, Hong SW, Yoon SO. Proposal of an appropriate decalcification method of bone marrow biopsy specimens in the era of expanding genetic molecular study. J Pathol Transl Med. 2015;49(3):236–42. 22. McDonough SJ, Bhagwate A, Sun Z, Wang C, Zschunke M, Gorman JA, et  al. Use of FFPE-derived DNA in next generation sequencing: DNA extraction methods. PLoS One. 2019;14(4):e0211400. 23. Lam NYL, Rainer TH, Chiu RWK, Lo YMD. EDTA is a better anticoagulant than heparin or citrate for delayed blood processing for plasma DNA analysis. Clin Chem. 2004;50(1):256–7. 24. Beutler E, Gelbart T, Kuhl W.  Interference of heparin with the polymerase chain reaction. Biotechniques. 1990;9(2):166. 25. Sidstedt M, Hedman J, Romsos EL, Waitara L, Wadso L, Steffen CR, et al. Inhibition mechanisms of hemoglobin, immunoglobulin G, and whole blood in digital and real-time PCR. Anal Bioanal Chem. 2018;410(10):2569–83. 26. Shi M, Spurgeon S, Press R, Olson S, Fan G. MYD88 mutation analysis of a rare composite chronic lymphocyte leukemia and lymphoplasmacytic lymphoma by flow cytometry cell sorting. Ann Hematol. 2015;94(11):1941–4. 27. Sun W. Chapter 4. Nucleic extraction and amplification. In: Grody WW, Nakamura RM, Strom CM, Kiechle FL, editors. Molecular diagnostics. San Diego: Academic Press; 2010. p. 35–47. 28. Sun W. Chapter 5. General procedures. In: Grody WW, Nakamura RM, Strom CM, Kiechle FL, editors. Molecular diagnostics. San Diego: Academic Press; 2010. p. 49–57. 29. Huang J, Chen N, Press R. Molecular methodologies and molecular pathology of hematolymphoid neoplasms. In: Cheng L, Bostwick D, editors. Essentials of anatomic pathology. Cham: Springer; 2016. 30. Peng Q, Xu C, Kim D, Lewis M, DiCarlo J, Wang Y.  Targeted single primer enrichment sequencing with single end duplex-UMI. Sci Rep. 2019;9(1):4810. 31. Zakrzewski F, Gieldon L, Rump A, Seifert M, Grützmann K, Krüger A, et al. Targeted capture-­ based NGS is superior to multiplex PCR-based NGS for hereditary BRCA1 and BRCA2 gene analysis in FFPE tumor samples. BMC Cancer. 2019;19(1):396. 32. Mertes F, Elsharawy A, Sauer S, van Helvoort JM, van der Zaag PJ, Franke A, et al. Targeted enrichment of genomic DNA regions for next-generation sequencing. Brief Funct Genomics. 2011;10(6):374–86. 33. Rothberg JM, Hinz W, Rearick TM, Schultz J, Mileski W, Davey M, et al. An integrated semiconductor device enabling non-optical genome sequencing. Nature. 2011;475(7356):348–52. 34. Levene MJ, Korlach J, Turner SW, Foquet M, Craighead HG, Webb WW. Zero-mode waveguides for single-molecule analysis at high concentrations. Science. 2003;299(5607):682–6. 35. Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, et al. Real-time DNA sequencing from single polymerase molecules. Science. 2009;323(5910):133–8. 36. Branton D, Deamer DW, Marziali A, Bayley H, Benner SA, Butler T, et al. The potential and challenges of nanopore sequencing. Nat Biotechnol. 2008;26(10):1146–53. 37. Robinson JT, Thorvaldsdottir H, Winckler W, Guttman M, Lander ES, Getz G, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29(1):24–6. 38. Roy S, Coldren C, Karunamurthy A, Kip NS, Klee EW, Lincoln SE, et al. Standards and guidelines for validating next-generation sequencing bioinformatics pipelines: a joint recommenda-

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tion of the Association for Molecular Pathology and the College of American Pathologists. J Mol Diagn. 2018;20(1):4–27. 39. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–24. 40. Li MM, Datto M, Duncavage EJ, Kulkarni S, Lindeman NI, Roy S, et al. Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. J Mol Diagn. 2017;19(1):4–23. 41. Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal N, et al. COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res. 2019;47(D1):D941–7. 42. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29(1):308–11. 43. Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, et  al. Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes. bioRxiv. 2019:531210. 44. Karube K, Enjuanes A, Dlouhy I, Jares P, Martin-Garcia D, Nadeu F, et al. Integrating genomic alterations in diffuse large B-cell lymphoma identifies new relevant pathways and potential therapeutic targets. Leukemia. 2018;32(3):675–84. 45. Schmitz R, Wright GW, Huang DW, Johnson CA, Phelan JD, Wang JQ, et al. Genetics and pathogenesis of diffuse large B-cell lymphoma. N Engl J Med. 2018;378(15):1396–407. 46. Langerak AW, Groenen PJ, Bruggemann M, Beldjord K, Bellan C, Bonello L, et  al. EuroClonality/BIOMED-2 guidelines for interpretation and reporting of Ig/TCR clonality testing in suspected lymphoproliferations. Leukemia. 2012;26(10):2159–71. 47. Arcila ME, Yu W, Syed M, Kim H, Maciag L, Yao J, et al. Establishment of immunoglobulin heavy (IGH) chain clonality testing by next-generation sequencing for routine characterization of B-cell and plasma cell neoplasms. J Mol Diagn. 2019;21(2):330–42. 48. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, et  al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403(6769):503–11. 49. De S, Shaknovich R, Riester M, Elemento O, Geng H, Kormaksson M, et al. Aberration in DNA methylation in B-cell lymphomas has a complex origin and increases with disease severity. PLoS Genet. 2013;9(1):e1003137. 50. Hopp L, Loffler-Wirth H, Binder H.  Epigenetic heterogeneity of B-cell lymphoma: DNA methylation, gene expression and chromatin states. Genes (Basel). 2015;6(3):812–40.

Chapter 5

Next-Generation Sequencing-Based Methods for the Detection of B-Cell Clonality Karin P. Miller and Rena R. Xian

 ermline Immunoglobulin Gene Rearrangements G in B-Cell Development Mature B-cells produce B-cell receptors/immunoglobulins, which are heterodimeric proteins consisting of two identical heavy chains linked to two identical light chains, either kappa or lambda. Immunoglobulin (IG) gene rearrangements occur in a sequential manner starting in the earliest B-cell precursors in the bone marrow with immunoglobulin heavy chain (IGH) gene rearrangements followed by immunoglobulin light chain gene rearrangements, kappa then lambda [1]. The ultimate purpose of these gene rearrangements is to produce functional B-cells with receptor diversity capable of responding to a wide variety of antigens necessary for biologically robust humoral immunity. Since these gene rearrangements remain with the B-cell throughout its lifespan, and are unique to that particular B-cell, this genetic “fingerprint” can be harnessed to detect a single clone that has massively expanded to form a B-cell malignancy, such as lymphoma, leukemia, or multiple myeloma. In order to understand the laboratory methods to detect these clones, an understanding of how these gene rearrangements ensue is essential.

K. P. Miller Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, CA, USA Keck School of Medicine, University of Southern California, Los Angeles, CA, USA e-mail: [email protected] R. R. Xian (*) Department of Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_5

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Immunoglobulin Gene Rearrangements Germline rearrangement of the IG genes begins with IGH in the earliest B-cell precursor, and does not occur at all in other cell types. If a functional IGH is produced, the cell will proceed to immunoglobulin light chain-kappa (IGK) gene rearrangement. If this rearrangement is successful, the B-cell will become a kappa-expressing B-cell. If this rearrangement is not successful, then the immunoglobulin light chain-­ lambda (IGL) gene will begin rearrangement. This latter event is accompanied by an additional IGK rearrangement, in which a portion of the kappa gene locus is segmentally deleted removing the IGK constant region [2]; this renders that IGK allele nonfunctional, and can be recognized by molecular methods as the kappa-deleting element (Kde) [1–3]. Since all human cells are diploid, either mono-allelic or biallelic rearrangements of these IG genes are possible in B-cells. B-cells that fail to rearrange a functional B-cell receptor will undergo cell death. The remaining mature B-cells will carry the mark of all preceding genetic events, including failed IG rearrangement attempts, which serve to uniquely identify that B-cell for the entirety of its lifespan. The IG gene loci are each located on different chromosomes and comprise varying numbers of variable (V), diversity (D), joining (J) and constant (C) gene segments. The IGH gene locus, located at 14q32.3, contains 44–52 functional/open reading frame V genes (79 V pseudogenes), 25 functional D genes (2 D pseudogenes) and 6 functional J genes (3 J pseudogenes) [3, 4]. The functional VH segments can be grouped into six to eight VH subgroups depending upon their homology [1, 3, 5–7]. Interestingly, both normal and neoplastic B-cells most frequently use VH3, VH4 and VH1 subgroups in IGH gene rearrangements, which account for approximately 75–95% of VH usage. B-Lymphoblastic Leukemia/Lymphoma (B-ALL) also frequently uses VH6 gene segments [3]. The IG light chain (kappa and lambda) gene loci lack D elements, and only comprise V and J segments. The IGK gene locus, located at 2p11.2, consists of 76 VK and 5 JK segments. The IGL gene locus, located at 22q11.2, contains 56 VL elements and 7JL-CL clusters [1]. Due to the number of possible rearrangements between these gene segments, the diversity of the immunoglobulin repertoire based on germline rearrangement alone is on the order of magnitude of 1012. Since IG locus rearrangement is orderly and predictable, it can be summarized schematically in Fig. 5.1. This is further refined as B-cells undergo antigen affinity selection/somatic hypermutation (SHM).

Somatic Hypermutation The previously described rearrangements occur in the bone marrow, and result in an antigen-naive B-cell expressing a low affinity IgM antibody. Once the B-cell arrives in peripheral lymph nodes, and other secondary lymphoid structures, the B-cell

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Fig. 5.1 (a) Schematic of how the IGH locus rearranges in B-cells. First, a DH segment combines with a JH segment producing an incomplete DJH rearrangement. This DJ segment then combines with a VH segment producing a complete VDJH sequence. After VDJH rearrangement, terminal deoxynucleotidyl transferase (TdT) randomly adds nucleotides to the junctional regions. This occurs on one allele of IGH, and if an in-frame rearrangement that produces a functional protein is achieved, the B-cell will continue to rearrange light chains. If a non-productive rearrangement is generated, the B-cell will repeat this process on the second IGH allele. (b) Schematic of how IGK locus rearranges in B-cells. Light chain rearrangement begins with the gene encoding kappa (IGK). A VK segment combines with a JK segment. If an in-frame rearrangement that produces a functional protein is achieved, the B-cell will become a kappa-expressing B-cell. If IGK unsuccessfully rearranges, it will undergo K-deleting (Kde) rearrangement preventing further IGK rearrangement. The B-cell will then progress towards rearrangement of the gene encoding lambda (IGL). (c) Schematic of how K-deleting (Kde) rearrangements occur in B-cells. Kde can occur via two different pathways. In the first pathway, the VJK combines with the Kde segment. In the second pathway, the intron-RSS segment combines with Kde. Both result in deletion of the constant region of IGK. (Adapted from van Zelm MC, van der Burg M, de Ridder D, Barendregt BH, de Haas EF, Reinders MJ, et al. Ig gene rearrangement steps are initiated in early human precursor B cell subsets and correlate with specific transcription factor expression. J Immunol. 2005;175(9):5912–22 [1])

receptor gene undergoes additional somatic mutational events, as antigens are encountered, which is termed somatic hypermutation (SHM). As this occurs in the germinal center, this may also be known as the “germinal center reaction”, and results in higher affinity and class-switched B-cell receptors/immunoglobulins. When antigen binds to the low-affinity IG receptor, B-cells undergo rapid proliferation in lymphoid follicles, which transition from a quiescent primary follicle to a reactive secondary follicle harboring germinal centers, inside which B-cells undergo SHM. SHM primarily introduces single nucleotide substitutions into the V gene of the heavy and/or light chains via activation-induced cytidine deaminase (AID), which has a preference for the complementarity determining regions (CDRs), as

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opposed to the framework (FR) regions [8]. The germinal center reaction also includes IG heavy chain class switch recombination, which rearranges the previous VDJH segment with one of the C gene segments leading to B-cells that express high-­ affinity IgG, IgA or IgE [9]. Successful SHM and class-switch recombination leads to terminal B-cell differentiation into a memory B-cell, or a plasma cell, that is capable of producing high antigen-affinity antibody, whereas unsuccessful mutations lead to apoptosis of the cell [10]. Although SHM is biologically necessary to further diversify the B-cell IG repertoire, this process can also interfere with molecular techniques used to assess clonality.

Molecular Methodologies to Assess Clonality Polymerase Chain Reaction (PCR)-Based Clonality Testing At the advent of the twenty-first century, PCR-based methods to detect clonality replaced Southern blot; PCR-based methods remain the most commonly used molecular technique to assess clonality [11, 12]. PCR-based methods have a sensitivity of 88% in detecting clonality in B-cell lymphomas when only complete VH-JH IGH gene rearrangements are assessed; 91% when both complete VH-JH and incomplete DH-JH gene rearrangements are assessed; 99% when IGK rearrangements are also evaluated [13, 14]. Due to biologic factors, such as somatic hypermutation, the sensitivity of these assays varies depending on the cell-of-origin of the B-cell malignancy (pre-germinal center/un-mutated vs. germinal-center/post-germinal-center/ hypermutated). The diagnostic sensitivity of IG detection by PCR for various B-cell malignancies is summarized in Fig.  5.2, as well as lineage-discordant clonality detection. Methodology To identify complete (VH–JH) IGH gene rearrangements, PCR-based methods take advantage of framework region (FR) sequences within the VH gene, which are more conserved and less susceptible to SHM [3]. As discussed above, the various VH segments are grouped into seven productive VH subgroups (VH1–VH7). Each VH segment contains three FRs and two complementarity-determining regions (CDRs), and a third CDR (CDR3) that spans V, D and J genes [19]. Across the various VH segments, the FRs are similar, while the CDRs are markedly different, as they afford receptor diversity with specific antigen-affinity. Given their function, CDRs are highly susceptible to SHM, and the FRs are less susceptible, though these additional mutational events can occur in the framework regions [3]. While the conserved nature of the FR regions make them amenable primer targets to assess IGH clonality, this approach can be hindered by low-level SHM.

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Fig. 5.2 (a) Diagnostic sensitivity of standardized BIOMED-2 PCR method for B-cell clonality when assessing different framework primers and combinations thereof [13, 15, 16]. (b) Detection of lineage discordant T-cell clones in B-cell malignancies is far more common in B-cell ALL, and less common in mature B-cell lymphoma [13, 17]. (c) Detection of lineage discordant B-cell clones in T-cell malignancies is most common in AITL [17, 18]. (b and c) demonstrate the importance of interpreting molecular results in combination with clinical and histopathological findings. MCL Mantle Cell Lymphoma, CLL/SLL Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma, FL Follicular Lymphoma, MZL Marginal Zone Lymphoma, DLBCL Diffuse Large B-cell Lymphoma, ALL Acute Lymphoblastic Leukemia/Lymphoma, CHL Classical Hodgkin Lymphoma, AITL Angioimmunoblastic T-cell Lymphoma, PTCL Peripheral T-cell Lymphoma, T-PLL T-cell Prolymphocytic Leukemia, T-LGL T-cell Large Granular Lymphocyte Leukemia, ALCL Anaplastic Large Cell Lymphoma

Forward PCR primers that are 21–25 nucleotides in length capable of annealing to a corresponding VH segment FR region were designed and standardized in 2003 by the European EuroClonality/BIOMED-2 collaborative group [3]. For each VH segment subgroup, there are three forward primers targeting FR1, FR2 and FR3. Additionally, a reverse JH primer that targets the most homologous 3′-end of the six JH segments was also standardized. The forward VH-FR primers are combined into three multiplex tubes (tubes A, B, and C) each paired with the same reverse JH primer, as depicted in Fig. 5.3a. Clonal, either mono-allelic or biallelic, rearrangements can be detected by one or all three of these multiplex tubes. Detecting incomplete DH-JH gene rearrangements follows a similar principle, and testing for these rearrangements can increase the sensitivity of the assay, particularly since incomplete DH-JH rearrangements are less susceptible to SHM [3]. The 27 DH segments can be grouped into seven DH families (DH1–7) based on sequence homology, and a single forward primer was designed to target each of the seven DH family genes as a part of the BIOMED-2 initiative. These DH primers are separated

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Fig. 5.3 (a) Primer design associated with the BIOMED-2 PCR method for detecting complete IGH VDJ rearrangements. (b) Primer design associated with the BIOMED-2 PCR method for detecting incomplete IGH DJ rearrangements [3]

Fig. 5.4  Primer design associated with the BIOMED-2 PCR method for detecting complete IGK VJ rearrangements (tube A), and for detecting Kde rearrangements (tubes B and C). Since all lambda-expressing cells carry a Kde rearrangement, detection of clonality by Kde can serve as a surrogate for IGL rearrangements [3]

into two multiplex PCR tubes (tubes D and E) each with the common reverse JH primer described above (Fig. 5.3b). Tube D contains forward primers for DH1–6, and tube E contains a forward primer for DH7. The DH7 amplicon was separated into a tube of its own because non-rearranged DH7 segments will amplify the germline state with a predictable product, and the EuroClonality guidelines recommended distinguishing this specific product from other DH1–6/JH rearrangements. Lastly, assessing IGK gene rearrangements by PCR further improves diagnostic sensitivity for B-lineage malignancies to 99% [13, 14]. Similar to incomplete DH–JH rearrangements, VK–JK gene rearrangements, which can be detected in all kappa-­ expressing B-cells, are less susceptible to SHM. Furthermore, the presence of Kde, described in the previous section, can be found in lambda-expressing B-cells [3]. For this reason, VK–JK, along with Kde, assessment is sufficient for detection of all light-chain gene rearrangements in either kappa- or lambda-expressing B-cells obviating the need for dedicated IGL assessment on a routine basis. In terms of assay design, the previously described VK gene segments can be grouped into seven VK gene families (VK1–7). Six forward primers targeting these VK families have been designed and standardized by the EuroClonality/BIOMED-2 collaborative group [3]. Only six primers are necessary, as the VK1 and VK6 families are covered by the same primer (Fig. 5.4). In tube A, all six forward VK primers are

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combined with two reverse JK primers (one primer covering JK1–4 and the other covering JK5). In tube B, the six VK forward primers are combined with two primers designed to detect Kde. One primer consists of a Kde reverse primer. The other consists of a forward primer that recognizes an isolated recombination signal sequence in the JK–CK intron (intron RSS-Kde). Interpretation The PCR multiplex reactions described above generate PCR products, or amplicons, of varying fragment lengths, and each primer set has predefined expected amplicon size ranges. Once PCR products are amplified, representing rearranged IG locus genes, they are separated by fragment length to determine if there is an over-­ abundance of an amplicon of a particular fragment length sufficient to suggest clonality. This can be visualized by either capillary or gel electrophoresis. Currently, the more commonly used method is capillary electrophoresis, which separates fragments with a 1–2 base pair resolution using an internal DNA ladder, and generates an electropherogram consisting of peaks representing different fragment lengths. Representative clonal patterns are shown in Fig. 5.5. Interpretation of the capillary electropherograms requires recognition of clonal patterns. This analysis has largely been standardized by clinical labs, and takes into account peak heights, as well as peak height ratios. It is generally recommended that all PCR gene rearrangement studies be run in duplicate with DNA input from the same specimen, as repeatability improves assay specificity. This type of analysis can yield different molecular interpretations including clonal, oligoclonal, non-­ clonal with a polyclonal pattern, non-clonal with a pseudoclonal pattern, or not evaluable due to insufficient quantity/quality DNA, or insufficient quantity/quality of B-cell DNA [20]. In clear-cut non-clonal cases with a polyclonal pattern, the amplicons will appear as a rough Gaussian distribution when separated by molecular weight, which represents the various amplicon lengths resulting from multiple B-cells carrying different IG gene rearrangements. Polyclonality can also be represented by numerous peaks in an irregular, non-Gaussian pattern. In clear-cut clonal cases, one or two peaks, repeatable between the duplicate reactions, will be present. A reproducible clonal peak may also be present in a polyclonal background, and the presence of the polyclonal background may correlate with the histological impression of background normal B-cells. Thus, it may be beneficial to describe the presence/absence, and abundance, of the polyclonal background signal in clinical molecular diagnostic reports. Additionally, the number of clonal peaks, and their patterns between the tubes, can be used to determine if mono-allelic or biallelic products (or biclonal populations) are present [20]. When multiple (three or more) different repeatable peaks are present, this would be consistent with oligoclonality, which is less common in IG clonality assessment than in T-cell gene rearrangement assessment. When a few non-repeatable peaks are present, this likely represents the phenomenon of pseudoclonality, which results from samples with a suboptimal input DNA. In

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Fig. 5.5  Representative electropherograms of typical clonal patterns observed using a PCR-based method for IGH coupled with capillary electrophoresis. (a) Monoallelic rearrangement of a complete IGH VDJ rearrangement, as demonstrated by a dominant peak migrating at 340 bases, with moderate polyclonal background detected in Tube A (FR1-JH primer sets). This rearrangement was NOT detected in Tubes B or C (FR2-JH and FR3-JH primer sets), as only polyclonal rearrangements were present. All tubes were performed in duplicate, and the peak seen in Tube A was repeated in the replicate reaction. (b) Biallelic rearrangement of two complete IGH VDJ rearrangements, as demonstrated by two dominant peaks migrating at 330 and 354 bases in Tube A (FR1-JH primer sets) and two dominant peaks migrating at 263 and 284 bases in Tube B (FR2-JH primer sets), with a mild polyclonal background. Tubes C, D and E in this specimen did not demonstrate clonal peaks. These clonal peaks are most likely associated with a single population of B-cells with both alleles rearranged. Although, the possibility of two separate populations of clonal B-cells each harboring a single rearrangement cannot be definitively excluded. (C) Biallelic rearrangement of a complete IGH VDJ rearrangement and an incomplete IGH DJ rearrangement, as demonstrated by a dominant peak migrating at 268 bases (FR2-JH primer sets) in Tube B and a dominant peak migrating at 280 bases (DH-JH primer sets) in Tube D, with a mild polyclonal background. These clonal peaks are most likely associated with a single population of B-cells with both alleles rearranged, one harboring a VDJ rearrangement and one harboring a DJ rearrangement

these types of samples, there is selective amplification of the few available rearranged IG sequences leading to the presence of different dominant peak(s) lacking a polyclonal background. Although this creates the impression of clonality, the dominant peaks are not repeatable in the duplicate reaction [20]. Figure 5.5 demonstrates select electropherograms showing select clonal patterns.

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Diagnostic Challenges in PCR-Based Clonality Testing Using PCR for IG gene rearrangement detection presents a number of diagnostic challenges, some of which are technical in nature, others that are biological, and still others that depend upon user interpretation. From a technical standpoint, some amplicon peaks may fall above or below the established size ranges for the primer set, yet still represent real clones. This rarely occurs because the established size range covers approximately 95% of expected amplicons [3]. Additionally, multiplex PCR reactions run the risk of non-specific amplification, and these peaks must be compared against known artifact peaks. In cases where the peaks fall outside of the size range, or if there is a question of non-specific amplification, sequencing the amplicons may be necessary to definitively prove clonality [20]. Technically and biologically, SHM may prevent optimal primer annealing leading to reduced/no amplification of the clone, and a potential false negative result [20]. Although this risk is mitigated by targeting multiple FRs, there is still a fraction of clonal samples (up to 12%) that would appear negative by all three FR primer sets [13]. In these cases, targeting sequences less susceptible to SHM, such as IGH D-J or IGK Kde rearrangements, may improve the sensitivity of the assay to capture 99% of all clonal rearrangements [3, 13, 20]. It is critical to appreciate that presence of clonality is not synonymous with presence of malignancy, as reactive lymphoproliferations can lead to dominant clones as part of an exaggerated immune response. In fact, up to 5% of reactive conditions show evidence of clonal IGH and/or IGK gene rearrangements [21]. Lastly, another pitfall of finding clonality is that it is not synonymous with a malignancy of that lineage (Fig. 5.2b and c). Approximately 22% of all T-cell lymphoblastic leukemia/ lymphomas (ALL) harbor a clonal IG gene rearrangement [22], while up to 93% of all pediatric B-cell ALLs have a demonstrable clonal T-cell receptor gene rearrangement of either the TCRB, TCRG or TCRD genes [17], but this fraction decreases with increasing age [23]. In lymphomas, approximately 10% of all T-cell lymphomas, particularly angioimmunoblastic T-cell lymphoma show a clonal IG rearrangement (32%) [18], and approximately 27% of all B-cell non-Hodgkin lymphomas can show a clonal T-cell receptor gene rearrangement [13]. Therefore, careful selection of cases based on morphologic suspicion of lymphoma, and careful integration of the clonality result, is recommended when IG gene rearrangement studies are incorporated into the initial diagnostic evaluation of lymphadenopathy.

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 ext-Generation Sequencing (NGS)-Based Methods to Detect N IG Gene Rearrangements NGS Background Next-generation sequencing (NGS) refers to massively parallel sequencing methods that have revolutionized the field of molecular diagnostics. It has allowed for the generation of enormous amounts of genomic data in a timely and relatively inexpensive manner. Different NGS platforms (Illumina, Ion Torrent, Nanopore, etc.) use different chemistries and techniques to generate these data. As described in the previous chapter, NGS platforms universally employ three broad stages: library preparation, sequencing, and bioinformatic analysis [24]. These stages can be uniquely tailored to the assessment of IG gene rearrangements.

NGS-Based Methods: Detecting IG Gene Rearrangements Introduction The use of NGS to detect IG gene rearrangements offers many advantages over current PCR-based methods. At diagnosis, NGS-based methods have proven more sensitive than PCR-based methods in terms of establishing clonality. As opposed to PCR-based methods, which establish clonality on the basis of clonal fragment size alone, NGS allows sequencing of the clone, as well as the background B-cell repertoire. Knowing the particular clonal sequence confers multiple advantages. If two separate clones have identical or nearly identical sizes, it allows for discrimination between these two clones since their sequences may differ. Alternatively, differently sized fragments by PCR-based methods can still represent the same rearrangement, if they share substantial gene-usage and sequence homology. Biallelic and/or biclonal rearrangements can also be more readily recognized by determining the exact sequences of the dominant clones. Further, knowing the sequence of the clone can enable simultaneous assessment of somatic hypermutation, as a percent deviation from the germline gene sequence. As leukemias and lymphomas progress, new clonal rearrangements and/or evolution of the previous clone may emerge. NGS-based methods not only allow for a deeper understanding of this phenomenon but also enable more accurate disease monitoring for the presence of related vs. unrelated clonal processes. Disease monitoring is perhaps the most important advantage of NGS, as the diagnostic clonal sequence(s) can be tracked post-treatment when it may be present at very low levels, and otherwise masked by polyclonal IG sequences. Thus, NGS-based clonality detection facilitates more sensitive and accurate minimal residual disease (MRD) monitoring in B-cell malignancies.

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Methodology There are now commercially available and custom consensus NGS-based methods to detect IG gene rearrangements, including LymphoTrack® (Invivoscibe, Inc), ClonoSeq® (Adaptive Biotechnologies, Inc.; previously known as LymphoSIGHT from Sequenta, Inc), and Euroclonality-NGS [25]. A few clinical validation studies have explored the use of these platforms with very promising results. However, their use requires further validation and standardization across laboratories, both nationally and internationally, before routine clinical use. Nonetheless, we anticipate that NGS-based methods to establish B-cell clonality will become the new gold standard in the upcoming years, similar to how PCR-based methods supplanted Southern blot methods. The added benefit of NGS-based methods is adaptability for both diagnostic and disease monitoring purposes. Each platform employs similar, yet unique approaches for assessing clonality. Technical and performance characteristics are summarized in Table 5.1, and potential assay designs are summarized in Fig. 5.6. The LymphoTrack® assay for IGH gene rearrangements targets FR1, FR2 and FR3 [30] sequences, in addition to a conserved sequence upstream of FR1, the leader sequence [31, 32]. The LymphoTrack® library preparation enriches for IG sequences by PCR using master mixes containing primers that target the consensus FR regions and JH regions, which are similar to the primers used in conventional PCR-based methods. These primers Table 5.1  Comparison of NGS platforms for B-cell clonality detection compared to a conventional PCR method Method Name

Targets

a

PCR EuroClonality BIOMED-2 [3, 13, 20] IGH (FR1, FR2, FR3); IGK (VJ, Vkde, IntronRSS-Kde)

Amplification method Detection method Sequencing instrument

PCR

Diagnostic sensitivity

IGH VDJ: 88%; IGH VDJ and DJ: 91%; IGH VDJ, IGH DJ and IGK: 99%

Capillary/Gel electrophoresis n/a

Multiple Myeloma-specific

NGS ClonoSEQ® [26–28]

EuroClonality NGS [11]

LymphoTrack® [29]

IGH (VDJ and DJ); IGK; IGL; BCL1/IGH; BCL2/IGH; and house-keeping genes PCR

IGH (FR1, FR2, FR3, DJ); IGK (VJ, VKde, Intron RSS-Kde)

IGH (Leader, FR1, FR2, FR3); IGK

PCR

PCR

Sequencing

Sequencing

Sequencing

Illumina NextSeq

Illumina MiSeq; Thermo Fisher Ion Torrent IGH VDJ: 69%; IGH FR3: 71%; IGH DJ: 48%; IGH FR3 and IGH IGK 55%; IGH DJ: 91%; IGH VDJ, IGH DJ FR3, IGH DJ and and IGK: 91%a IGK: 100%

Illumina MiSeq; Thermo Fisher Ion Torrent IGH FR1: 86%, IGH FR1 and Leader: 95%; IGH FR1, Leader, FR2, and FR3: 97%

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Fig. 5.6  Possible approaches to designing sequencing primers for NGS detection of B-cell clonality, much of which is similar to traditional PCR-based methods. Given the massively parallel nature of NGS, VH-gene specific primers may be used to increase sensitivity and decrease PCR-­ based skewing of amplification of particular rearrangements

can be tagged with sample index sequences that allow for pooling of libraries from several different samples to be sequenced on the same flow cell or chip, depending upon the NGS platform utilized. Following purification and quantification, the libraries can be sequenced using either the Illumina MiSeq or Thermo Fisher Ion Torrent instruments. The resulting sequences are then aligned and analyzed using the LymphoTrack® software, which can be further analyzed using customized laboratory-­developed tools, one possible customized analysis is depicted in Fig. 5.7. Similar assays are offered for sequencing IGK, and IGHV leader sequence for determination of SHM. ClonoSeq® is a custom B- and T-cell gene rearrangement NGS method that also relies on PCR-enrichment for IG and T-cell receptor gene sequences [26]. This became the first FDA-approved NGS-based test for MRD monitoring in multiple myeloma and acute lymphoblastic leukemia [27]. Sequencing libraries are prepared by PCR using barcoded primers that target individual IGH (VDJ), IGH (DJ), IGK and IGL genes, as well as BCL1/IGH (J) and BCL2/IGH (J) translocations, and housekeeping genes [33]. Once pooled, the amplified barcoded DNA is sequenced on an Illumina NextSeq. The sequences are analyzed using a proprietary algorithm that removes amplification bias followed by assessment of the immune repertoire to identify any dominant, or previously identified clones, consistent with clonality. The EuroClonality-NGS Working Group published their approach to detecting IG gene rearrangements for minimal residual disease monitoring in B-ALL in 2019, and as well as a parallel approach to detecting T-cell gene rearrangements in T-ALL [25]. Similar to the other two methods, this group designed consensus primers targeting FR1, FR2 and FR3 to detect complete IGH VDJ rearrangements, primers to

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b

Fig. 5.7  Histograms obtained from NGS data demonstrating how clones can be determined by a similar approach as gold-standard PCR/capillary electrophoresis. The unique IGH VDJ rearrangements (color-coded by sequence and rank) are separated by amplicon length (0–400 bases) on the x-axis in relation to read depth on the y-axis. Blue represents the most dominant sequence, while red represents the second most dominant sequence, and so on. All sequencing profiles were reproduced in a replicate reaction (data not shown). (a) A representative polyclonal distribution of sequences. (b) A representative clonal (biallelic) pattern with virtually no background polyclonal sequences

detect IGH DJ rearrangements, and primers to detect IGK rearrangements (IGK-VJ and V-Kde and Intron RSS-Kde). They further modified the IGH-VDJ FR3 primers to better detect B-cell clonality in formalin-fixed paraffin-embedded (FFPE) tissue, as this framework produces smaller amplicons more suited for highly fragmented DNA extracted from FFPE tissue [11]. Library preparation proceeds via a two-step PCR reaction resulting in amplified and barcoded pools of sample libraries. Sequencing proceeds on the Illumina MiSeq [25] or Ion Torrent instruments [11]. Sequencing data can be analyzed using ARResT/Interrogate, a data manipulation tool for NGS-based immunoprofiling [34]. Establishing Clonality by NGS As with PCR-based methods, NGS can be used to establish B-cell clonality at diagnosis, as well as assessing degree of SHM, which is important in prognostication of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) [32]. As discussed in previous sections, PCR-based methods are quite sensitive for detecting B clonality. However, NGS-based methods have even further improved upon this sensitivity, especially in cases affected by SHM. The diagnostic sensitivity of NGS-based methods for IG detection has been studied in tissue specimens using the LymphoTrack® [29] and the EuroClonality-NGS [11]. Arcila et al. showed that the LymphoTrack® IG assays showed a high level of concordance (96%) with PCR assays, and that the only discordant cases were demonstrated to be clonal by NGS, and not PCR. With respect to specific IG targets, this group showed that a sequential approach (FR1 followed by leader, followed by FR2 and FR3) maximized sensitivity without excessive unnecessary sequencing studies.

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In their cohort, when tumor cells exceeded 5% by immunophenotyping, FR1 clones were detectable in 86% of samples [29], which is superior to FR1-only sensitivity of 79% based on the original BIOMED-2 PCR method [13]. The sensitivity of LymphoTrack® NGS improves to 95% when leader sequence is incorporated, and further improves to 97% when FR2 and FR3 targets are assessed [29]. Expectedly, tumors with more extensive SHM required the incorporation of FR2 and FR3 assessment. Although clonality was not detected by IGH sequences in 3% of cases, the addition of IGK analysis reduced false negativity to 1.4% [29]. While little data are available regarding the diagnostic sensitivity of ClonoSeq®, a 2014 study of ClonoSeq® in multiple myeloma showed that clonal sequences were identified in 91% of all diagnostic myeloma samples with 69% of clones detected by IGH VDJ rearrangements, 55% of clones detected by IGK rearrangements, and 48% of clones detected by IGH DJ rearrangements [28]. Similarly robust data have been found using the EuroClonality-NGS method, particularly FFPE tissues. This group assessed FR3 targets, and found clonal sequences in 71% of tumor samples studied [11]. This sensitivity improved to 91% when IGH DJ primers were used, and further improved to 100% when IGK primers were added. Thus, the diagnostic sensitivity of NGS-based methods of IG detection is similarly, if not more, sensitive than PCR-based methods. However, these techniques also introduce diagnostic challenges, and intensive bioinformatics needs, that limit broad clinical application today. Diagnostic Challenges Unlike PCR-based methods analyzed by capillary electrophoresis, which relies on pattern recognition of clonality, most NGS-based methods yield semi-quantitative sequence read counts and percentages that still lack uniform recommendations on what constitutes a clonal sequence in clinical practice [35]. Arcila et al. are the first to address this question in a large series of clinical samples tested in an academic hospital setting using the LymphoTrack® IGH assay [29]. In addition to confirming the manufacture’s recommendations for clonality of >2.5% of reads and >3 times the third most prevalent sequence, this group also established more stringent clonality calling rules for various scenarios depending on the total B-cell reads achieved and the number of dominant sequences. When there are 1–2 dominant sequences, and the sample has at least 50,000 total reads, the authors recommended the following criteria for determining clonality using the most dominant sequence(s): >2.5% of the total reads and >10 times the polyclonal background. In samples that have 30,000–50,000 total reads, dominant sequence(s) should represent >5% of the total reads and >20x the polyclonal background. Samples that have 5% of the sample based on morphology and/or flow cytometry, and stringent clonality calling rules are applied [29]. Additionally, SHM continues to lower the sensitivity of the NGS-based assays, as library preparation still relies upon multiplex PCR and SHM may prevent primer annealing [11, 35]. Similar to PCR-­ based methods, the solution is to increase the number of IG targets assessed. Determination of IGVH Hypermutation Status by NGS Not only is clonality detection a diagnostically useful marker for B-cell malignancies, it is also prognostic when considering IGVH hypermutation status, or the degree of SHM in the variable gene region, in CLL/SLL [32]. Cases with limited, or no SHM, have a worse prognosis and different biology than cases with significant hypermutation from the germline genes [32]. Although the degree of hypermutation can be derived from sequences that target FR1 of the IGH VH gene, leader sequence primers enable amplification of the full VDJ rearrangement, and are more reflective of true SHM [32]. While IGHV hypermutation determination has traditionally been performed by Sanger Sequencing (SS), NGS-based methods have been developed for this purpose, and provide additional benefits as compared to SS-based methods. SS-based methods fail in approximately 3–4% of cases, and can only provide insight into the most dominant clone [36]. NGS-based methods are able to assess more IG rearrangements, including less dominant clones, either related or unrelated, that may also be subjected to SHM. A recent study using NGS-based methods to assess IGHV hypermutation status demonstrated that approximately 25% of CLL/SLL patients displayed multiple productive unrelated IG clones, and that patients with disease characterized by multiple unmutated clones had worse prognosis than patients with either one hypermutated or unmutated clone, multiple hypermutated clones, or a mixture of hypermutated and unmutated clones [37]. As NGS-based methods become more commonplace, understanding the clonal heterogeneity and the mutation status within this heterogeneity may provide further insight into genetically driven clinical behavior of the disease. Lastly, SHM status is not performed in a vacuum for CLL/SLL and is often performed alongside other NGS assays that assess for mutations in commonly mutated, and prognostic genes, in CLL/SLL, such as ATM, NOTCH1, SF3B1 and TP53 [36]. As hematologic malignancy NGS panels become more widely adopted in clinical oncology, this information can only be complemented by the additional prognostic value afforded by NGS-based clonality and SHM determination.

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Minimal Residual Disease Monitoring by NGS As stated earlier, another major advantage of NGS-based methods for clonality detection is the ability to monitor minimal residual disease (MRD) by deep sequencing techniques. MRD refers to a state in which tumor can no longer be identified morphologically, but is still present at a very low level (0.01% or greater) and detectable by other laboratory studies. In acute lymphoblastic leukemia (ALL), MRD has been shown to have a significant impact on prognosis in both pediatric and adult populations, and now guides treatment paradigms [38]. In ALL, flow cytometry (FC) has the ability to detect leukemic blasts down to 0.01% of all cells (1  in 10,000 cells) [38], and has emerged as the standard-of-care for MRD in ALL. However, NGS-based techniques are showing robust sensitivity in ALL, multiple myeloma (MM) and other B-cell lymphomas [34, 39, 40]. The ClonoSeq® assay is perhaps the most widely studied NGS technique for MRD detection, which is why it became the first FDA-approved NGS-based test for MRD monitoring in ALL and MM [24]. In ALL, this method shows 95% concordance with FC, and demonstrates a superior analytical sensitivity down to 0.0001% of all reads (1 in 1,000,000 reads) [39]. Given the improved sensitivity, up to 10% of cases would be MRD-positive by NGS, while being MRD-negative by FC [39]. This improved sensitivity appears to have clinical relevance, as NGS MRD positivity predicted relapse and survival more accurately than FC [40], particularly in the early post-transplant setting. Part of the improved prognostic value of NGS may be attributed to the ability to identify the specific clonal sequence to differentiate between very low-level residual leukemic blasts and regenerating B-cells/hematogones [40]. In MM, NGS-based methods show 83% concordance with FC-methods of evaluating MRD with 12% of samples being MRD-positive by NGS but MRD-­ negative by FC, and 5% of samples being MRD-negative by NGS but MRD-positive by FC [28]. When MRD-negativity by NGS is defined as clonal sequences found in adults

EBV negative Unknown Often low clinical stage, nodal disease common; often involving head and neck region Starry sky less prominent, tumor cells more pleomorphic looking, usually not vacuolated, slightly lower proliferation rate usually higher polymorphism Similar to BL but MYC positivity usually low, CD38 rarely positive No MYC translocation, higher chromosomal complexity, 11q proximal gain/terminal loss required for diagnosis Molecular signatures similar to BL

TCF3/ID3 and CCND3 mutations not detected; PAFAH1B2, USP2 and CBL as possible genes in the 11q duplicated region; ETS1 and NFRKB as possible genes in the 11q deleted region No consensus, usually treated as BL or DLBCL

Similar to BL or better

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low clinical stages and commonly involving the head and neck areas [65–68]. However, one case was reported in an elderly patient with disseminated disease and bone marrow involvement [69]. Additionally, HGBL/LBCL 11q may present as a form of monomorphic post-transplant lymphoproliferative disorder (M-PTLD), and has been reported in the post-transplant setting [67]. Histologically, HGBL/LBCL 11q shows a diffuse infiltrate of medium- to large-­ sized lymphoid cells, which may resemble Burkitt lymphoma cells but usually demonstrate more cytological pleomorphism. Starry sky pattern may be prominent, and mitotic activity is very high. A case series reported conspicuous coarse apoptotic debris within starry sky macrophages as a characteristic morphological hint of HGBL/LBCL 11q [70]. The immunophenotype of the lymphoma cells is similar to Burkitt lymphoma, positive for pan-B cell markers and germinal center B-cell makers, negative or only weakly positive for BCL-2. Additionally, flow cytometry demonstrated less frequent alterations in CD38 (higher) and CD45 (diminished) but

Fig. 10.3 High-grade B-cell lymphoma/large B-cell lymphoma with 11q aberration: morphology. The patient was a 14-year-old male at the time of diagnosis with no significant past medical history who presented with a cervical mass. Excisional biopsy was performed. (a) Touch imprint showed medium to large lymphoma cells with minimal cytoplasm and no vacuoles (wright-Giemsa, ×1000). (b) Tissue section revealed a diffuse infiltrate of medium- to large-sized lymphoid cells with moderate pale cytoplasm, slightly irregular nuclear contours, finely clumped to vesicular chromatin, and inconspicuous to small nucleoli. Tingible-body macrophages and starry-sky pattern were less prominent (H&E, ×400)

a

b

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Fig. 10.4  High-grade B-cell lymphoma/large B-cell lymphoma with 11q aberration: immunophenotype. Immunohistochemical stains showed that the tumor cells were positive for CD20 (a, x200), CD10 (c, x200), BCL6 (d, x200), and negative for BCL2 (e, x200). The lymphoma cells were almost 100% positive for Ki-67 (b, x200), and 95%. Br J Haematol. 2011;152(2):175–81. 55. Mead GM, Sydes MR, Walewski J, Grigg A, Hatton CS, Pescosta N, et al. An international evaluation of CODOX-M and CODOX-M alternating with IVAC in adult Burkitt's lymphoma: results of United Kingdom lymphoma group LY06 study. Ann Oncol. 2002;13(8):1264–74. 56. Thomas DA, Faderl S, O'Brien S, Bueso-Ramos C, Cortes J, Garcia-Manero G, et  al. Chemoimmunotherapy with hyper-CVAD plus rituximab for the treatment of adult Burkitt and Burkitt-type lymphoma or acute lymphoblastic leukemia. Cancer. 2006;106(7):1569–80. 57. Dunleavy K, Pittaluga S, Shovlin M, Steinberg SM, Cole D, Grant C, et  al. Low-intensity therapy in adults with Burkitt's lymphoma. N Engl J Med. 2013;369(20):1915–25. 58. Goldman S, Smith L, Anderson JR, Perkins S, Harrison L, Geyer MB, et al. Rituximab and FAB/LMB 96 chemotherapy in children with stage III/IV B-cell non-Hodgkin lymphoma: a Children's oncology group report. Leukemia. 2013;27(5):1174–7. 59. Meinhardt A, Burkhardt B, Zimmermann M, Borkhardt A, Kontny U, Klingebiel T, et al. Phase II window study on rituximab in newly diagnosed pediatric mature B-cell non-Hodgkin's lymphoma and Burkitt leukemia. J Clin Oncol. 2010;28(19):3115–21. 60. Ngoma T, Adde M, Durosinmi M, Githang'a J, Aken'Ova Y, Kaijage J, et al. Treatment of Burkitt lymphoma in equatorial Africa using a simple three-drug combination followed by a salvage regimen for patients with persistent or recurrent disease. Br J Haematol. 2012;158(6):749–62. 61. Dunleavy K. Approach to the diagnosis and treatment of adult Burkitt's lymphoma. J Oncol Pract. 2018;14(11):665–71.

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62. Kochenderfer JN, Somerville RPT, Lu T, Shi V, Bot A, Rossi J, et  al. Lymphoma remissions caused by anti-CD19 chimeric antigen receptor T cells are associated with high serum Interleukin-15 levels. J Clin Oncol. 2017;35(16):1803–13. 63. Rimsza L, Pittaluga S, Dirnhofer S, Copie-Bergman C, de Leval L, Facchetti F, et  al. The clinicopathologic spectrum of mature aggressive B cell lymphomas. Virchows Arch. 2017;471(4):453–66. 64. Gonzalez-Farre B, Ramis-Zaldivar JE, Salmeron-Villalobos J, Balague O, Celis V, Verdu-­ Amoros J, et al. Burkitt-like lymphoma with 11q aberration: a germinal center-derived lymphoma genetically unrelated to Burkitt lymphoma. Haematologica. 2019;104(9):1822–9. 65. Salaverria I, Martin-Guerrero I, Wagener R, Kreuz M, Kohler CW, Richter J, et al. A recurrent 11q aberration pattern characterizes a subset of MYC-negative high-grade B-cell lymphomas resembling Burkitt lymphoma. Blood. 2014;123(8):1187–98. 66. Pienkowska-Grela B, Rymkiewicz G, Grygalewicz B, Woroniecka R, Krawczyk P, Czyz-­ Domanska K, et  al. Partial trisomy 11, dup(11)(q23q13), as a defect characterizing lymphomas with Burkitt pathomorphology without MYC gene rearrangement. Med Oncol. 2011;28(4):1589–95. 67. Ferreiro JF, Morscio J, Dierickx D, Marcelis L, Verhoef G, Vandenberghe P, et  al. Post-­ transplant molecularly defined Burkitt lymphomas are frequently MYC-negative and characterized by the 11q-gain/loss pattern. Haematologica. 2015;100(7):e275–9. 68. Grygalewicz B, Woroniecka R, Rymkiewicz G, Rygier J, Borkowska K, Kotyl A, et al. The 11q-gain/loss aberration occurs recurrently in MYC-negative Burkitt-like lymphoma with 11q aberration, as well as MYC-positive Burkitt lymphoma and MYC-positive high-grade B-cell lymphoma. NOS Am J Clin Pathol. 2017;149(1):17–28. 69. Moshref Razavi H, Hrynchak M.  Unusual presentation of Burkitt-like lymphoma with 11q aberration in an elderly patient. Blood. 2019;133(4):381. 70. Horn H, Kalmbach S, Wagener R, Staiger AM, Huttl K, Mottok A, et al. A diagnostic approach to the identification of Burkitt-like lymphoma with 11q aberration in aggressive B-cell lymphomas. Am J Surg Pathol. 2021;45(3):356–64. 71. Rymkiewicz G, Grygalewicz B, Chechlinska M, Blachnio K, Bystydzienski Z, Romejko-­ Jarosinska J, et al. A comprehensive flow-cytometry-based immunophenotypic characterization of Burkitt-like lymphoma with 11q aberration. Mod Pathol. 2018;31(5):732–43. 72. Havelange V, Ameye G, Theate I, Callet-Bauchu E, Lippert E, Luquet I, et al. The peculiar 11q-gain/loss aberration reported in a subset of MYC-negative high-grade B-cell lymphomas can also occur in a MYC-rearranged lymphoma. Cancer Genet. 2016;209(3):117–8. 73. Zajdel M, Rymkiewicz G, Chechlinska M, Blachnio K, Pienkowska-Grela B, Grygalewicz B, et al. miR expression in MYC-negative DLBCL/BL with partial trisomy 11 is similar to classical Burkitt lymphoma and different from diffuse large B-cell lymphoma. Tumour Biol. 2015;36(7):5377–88. 74. Wagener R, Seufert J, Raimondi F, Bens S, Kleinheinz K, Nagel I, et al. The mutational landscape of Burkitt-like lymphoma with 11q aberration is distinct from that of Burkitt lymphoma. Blood. 2019;133(9):962–6.

Chapter 11

Precision Medicine in Diffuse Large B-Cell Lymphoma Siba El Hussein and Francisco Vega

Introduction Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma worldwide [1]. The treatment of DLBCL was first shown to be improved by the addition of rituximab (R) to CHOP (Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone) in two series of treatment-naïve patients in 2001 and 2005 [2–6]. Since then, R-CHOP regimen has been established as the standard frontline therapy across most cases of DLBCL. However, R-CHOP remains a toxic therapy that does not benefit every patient (as ~50% of patients will relapse) and may result in serious side effects. In the last few years, our understanding of the pathobiology of DLBCL and its molecular landscape has increased dramatically. This knowledge is expected to enhance our ability to identify high-risk patients and help design treatment based on patient-specific molecular profiles. DLBCL is a very heterogeneous disease from the genetic, immunophenotypic, and clinical points of view. Thus, it presents significant challenges in terms of personalized medicine and outcome prediction. With the introduction of next-­generation sequencing, the characterization of genomic landscapes of neoplasms has been occurring at a rapid pace and at relatively low costs. In the near future, advances and FV receives funding from the National Cancer Institute, National Institutes of Health (grant R01CA222918) and CRISP Therapeutics Inc. FV also received honorarium from Congressionally Directed Medical Research Program, i3health, Elsevier, Society of Hematology Oncology and American Society of Hematology. S. El Hussein (*) Department of Pathology, The University of Vermont Medical Center, Burlington, VT, USA F. Vega Department of Hematopathology, MD Anderson Cancer Center, Houston, TX, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_11

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accessibility to sequencing technology are expected to allow widespread, real-time clinical incorporation of patient-specific data into useful prognostic models, contributing to the design of algorithms for therapeutic decision-making. It is also expected that more therapeutic agents that specifically target key molecules and relevant biological pathways will become available for clinical studies. This chapter summarizes our current knowledge of the pathobiology of DLBCL, focusing on genetic and epigenetic alterations that could potentially be translated into the clinical practice and new therapeutic approaches that are being entertained in light of recent molecular findings of this neoplasm.

Outcome Prediction in DLBCL and Unmet Challenges The clinical and genetic heterogeneity of DLBCL presents significant challenges for accurate outcome prediction. Over the past three decades, methods of outcome prediction in DLBCL have utilized a diverse array of data sources including clinical factors, Cell-of-Origin (COO) and genetic subgroups. However, it remains unclear what combination of these or other data sources will ultimately yield optimal prognostic models for integration into clinical practice. Prognostic factors and biomarkers that have been shown to predict outcomes in DLBCL include:

The International Prognostic Index (IPI) Developed more than 25 years ago using stepwise regression analysis, it provides risk assessment according to five clinical characteristics (age, stage, lactic dehydrogenase level, performance status, and number of extranodal sites) [7, 8]. Although the IPI constitutes a robust and accessible clinical tool to effectively predict survival, one of its limitations is its inability to identify targetable vulnerabilities to guide the use of individualized therapy [9].

Cell-of-Origin (COO) In an effort to understand the heterogeneity of DLBCL, gene expression profile studies using an early genomic technology, the DNA microarray, was performed almost 20 years ago on a large cohort of DLBCL patient samples [10]. Clustering of these GEP data revealed two dominant molecular subgroups with roughly equal frequencies. The germinal center (GC) B-cell-like subgroup is marked by expression of genes commonly found in GC B-cells such as recurrent t(14;18) translocations, amplification of the c-REL gene on chromosome 2p [11], and lack of expression of early post-GC markers [10, 12, 13]. In contrast, the activated B-cell (ABC)-like subgroup expresses genes characteristic of circulating B-cells that have been acutely stimulated through the B cell receptor (BCR), notably including many NF-κB target genes [10, 13]. The importance of this study resides in predicting the outcome of patients following R-CHOP regimen, as it

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appears to be less favorable in ABC than GC-DLBCL (~40% versus ~75% three-year progression-free survival, respectively) [14]. Nevertheless, there has not been a uniform reproducibility of the prognostic value of the COO classification. This suggested that residual diversity within these subsets exists and carries valuable prognostic information. Indeed, this has been recently demonstrated [15, 16]. GC- and ABC-DLBCLs have been officially incorporated as molecular subtypes of DLBCL-NOS in the most recent revision (2017) of the world health organization (WHO) classification of lymphoid neoplasms [17]. While immunohistochemical algorithms are deemed acceptable, recent advances in technology have improved the use of formalin-fixed paraffin-­embedded tissue to apply gene expression profiling approaches such as NanoString for reliable COO assignment [18, 19]. In our opinion, the COO classification, as currently understood, has very limited value for therapeutic decision-making in DLBCL patients.

Comprehensive Consensus Clustering (CCC) Is an alternative transcriptional profiling classification that identified three distinct groups based on BCR, oxidative phosphorylation, and host response. The CCC schema highlights the role of tumor microenvironment and host inflammatory response to differentiate between variants of DLBCL [20]. In contrast to COO, this study offers a non-overlapping categorization of subgroups and suggests potential rational therapeutic targets for each group. However, to date it has had a more limited role in clinical practice [20].

Double-Hit and Double-Expressor Status Apart from the COO and CCC classifications, lymphomas with concurrent translocations involving MYC and BCL-2 or BCL-6 have been shown in different studies to portend an aggressive and refractory clinical course [21, 22]. DLBCL/High grade B-cell lymphoma with translocations involving MYC and BCL-2 and/or BCL-6, were included in the 2017 revised edition of the WHO Classification under the category of “High grade B-cell lymphoma with MYC and BCL-2 and/or BCL-6 gene rearrangements” [17], reflecting the prognostic importance of these genomic alterations. The impact of MYC rearrangement on prognosis has been proven to be influenced by the MYC partner gene (immunoglobulin “IG” or a non-IG gene) [23]: Rosenwald et  al. evaluated a large cohort of patients through the Lunenburg Lymphoma Biomarker Consortium, to validate the prognostic significance of MYC rearrangement in DLBCL/High grade B-cell lymphoma, within the context of MYC partner gene [23]. The authors found that patients with MYC double hit/triple-hit disease in which MYC is translocated to an IG partner have a worse prognosis and suggested that diagnostic strategies should be adopted to identify this high-risk cohort [23]. Nevertheless, in consequent studies, DLBCL/High grade B-cell lymphoma cases with MYC and BCL6 translocations have shown variable risk association in different recent series, demonstrating a heterogeneous category with variable gene expression profiles and mutational landscape [23–28]. Furthermore, unlike

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Fig. 11.1  Diffuse large B-cell lymphoma/high grade B-cell lymphoma with MYC and BCL-2 gene rearrangements. This lymphoma category is defined by the presence of gene rearrangements involving MYC and BCL-2 independently of the morphologic or immunophenotyic findings. Some case will have blastoid morphology resembling lymphoblastic lymphoma, others a “Burkitt-like” appearance with features intermediate between Burkitt lymphoma and Diffuse large B-cell lymphoma and finally other will be indistinguishable from classical Diffuse large B-cell lymphoma. These lymphomas were previously named as double hit lymphomas

DLBCL/High grade B-cell lymphoma with translocations involving MYC and BCL-2, which exhibits a mutational signature more similar to follicular lymphoma (CREBBP, BCL2, KMT2D, MYC, EZH2, and FOX1 mutations) than to DLBCL, not otherwise specified (GCB subtype) [29, 30], DLBCL/High grade B-cell lymphoma  cases with MYC and BCL6 translocations demonstrate ABC-like gene expression profiles [16, 29, 31–33]. In light of these observations, cases of DLBCL/High grade B-cell lymphoma  with  MYC  and  BCL6  translocations have been excluded from the  DLBCL/ HGBL-MYC/BCL2 category and included in DLBCL, NOS or HGBL, NOS depending on morphologic examination, in the fifth edition of the WHO classification [34], and have been moved back to as a provisional entity according to the international consensus classification (ICC) [35]. Recent studies have used RNA sequencing data to delineate a gene expression signature that identifies GC subtype DLBCL with a double-hit gene expression signature, in the absence of MYC or BCL-2 translocations (as detected by FISH), recognizing patients with a poorer prognosis [36, 37]. Applying IHC stains for MYC and BCL-2 to reiterate the pathobiology of DHL has demonstrated that an increase in MYC expression identifies a group of DLBCL patients with an aggressive clinical course [38]. In addition, DLBCL with MYC and BCL-2 protein expression, termed double-expressor lymphoma (DEL), has been shown to represent an unfavorable subgroup with inferior outcomes after standard frontline therapy and autologous stem-cell transplantation [21, 39, 40]. However, DEL status is not considered a surrogate of “double hit” lymphoma (or vice versa), as DEL and “double hit” disease are not identical or even strongly overlapping groups [9] (Figs. 11.1 and 11.2).

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Fig. 11.2  Rearrangements of MYC and BCL-2 genes and MYC and BCL-2 protein expression define two non-overlapping subtypes of Diffuse large B-cell lymphoma /high-grade B-cell lymphomas with MYC and BCL-2 gene rearrangements (previously double hit lymphoma, DHL) and double-expressor MYC and BCL-2 Diffuse large B-cell lymphoma, respectively. A Diffuse large B-cell lymphoma is considered a double expressor when MYC is expressed by at least 40% of the neoplastic cells and when BCL-2 is expressed at least by 50% of the lymphoma cells (both as detected by immunohistochemical stains). Double-expressor lymphomas represent about 30% of Diffuse large B-cell lymphomas

Germinal Centers, a Dangerous Place to Be for a Lymphocyte B-lymphocytes, after having been exposed to antigens, undergo cell division and acquire the ability to produce high-affinity antibodies in the GCs [41, 42]. GCs are polarized into two distinct microenvironments: The dark and light zones. In the dark zone, numerous centroblasts divide rapidly and undergo somatic hypermutation. Somatic hypermutation of the variable (V) regions of the Ig heavy and light chains genes result in BCR diversity with varying antigenic affinities. In the light zone, B-cells that are able to make high-affinity antibodies will further undergo class-switching recombination before differentiating into a plasma cell or memory B cell. Class switch recombination is a process by which the heavy chain class of an antibody produced by a GC B-cell clone changes from IgM to IgG, IgA, or IgE. Both somatic hypermutation and class switch recombination are mediated by activation-induced cytidine deaminase (AID). The selection process includes re-entry into the dark zone for further rounds of mutation and selection. Because of the unique and complex set of events that are associated with the GC reaction, the GCs pose a significant risk to the genomic integrity of the GC cells, which have to

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endure high replication stress while undergoing multiple DNA breaks and recombination events. To withstand this high-stress environment, GC events are tightly regulated by a complex network of transcription factors and epigenetic switches. It is believed that most cases of DLBCL derived from the neoplastic expansion of B-cells undergo “arrest” at various stages during their transit inside the GCs. On the other hand, recent data suggest that primary extranodal lymphomas and those DLBCL with MYD88 mutation originate from aberrant memory B cells [43].

Transcription Factors Controlling GC Reaction The development of B-cells is a multi-step process that involves the dynamic upand down-regulation of large gene signatures, allowing differentiation-state-specific processes to take place. For example, BCL-6 drives the silencing of a large set of genes that allow GC B-cells to undergo rounds of proliferation and tolerate DNA damage associated with somatic hypermutation and class switch recombination. Following affinity maturation, GC B-cells receive terminal differentiation signals through their BCR and from follicular helper T-cells via CD40. This induces the expression of the IRF4 transcription factor, which suppresses BCL-6 expression and reactivates a large set of genes that are suppressed in GC B-cells, thereby driving GC exit and terminal B-cell differentiation. These processes are deregulated in DLBCLs that fail to activate GC exit programs. Most genetic alterations associated with DLBCL converge on transcription factors that are normally used by the GC B-cells to assume distinct functional states during the GC reaction. Some of the master regulators of the GC reaction are briefly described below: BCL-6 is a 95-kD nuclear phosphoprotein that contains zinc-finger motifs to mediate specific DNA binding sites. BCL-6 acts as a transcriptional repressor [44] and is strongly upregulated by GC B-cells (and GC T-cells). BCL-6 coordinates a gene expression program that blocks B-cell activation and plasmacytic differentiation (silencing PRDM1) and promotes the proliferation of GC B-cells. BCL-6 is critical to establish the hyperproliferative status of GC B-cells, in the dark zone, while allowing them to tolerate the DNA breaks associated with SHM and CSR without eliciting cell-cycle arrest and apoptotic responses. BCL-6 cooperates with the histone methyltransferase EZH2 to maintain many gene regulatory elements in a bivalent chromatin state, thereby enforcing the GC phenotype while allowing signal-induced activation of certain genes [45] (Fig. 11.3). MYC is a potent proto-oncogene and plays a major role as a global driver of cell growth and division. In the setting of GC B-cells, MYC is characterized by a bimodal pattern of expression: Upon contact of B-cells with antigen and T-helper cells, activation of BCR and CD40 leads in the light zone to a short period of MYC expression crucial for B-cell recirculation back to the dark zone of GC for further affinity-based positive selection [46–48]. In the dark zone, activity of AID ensures an additional round of SHM and CSR, however BCL-6 upregulation directly

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Fig. 11.3  The role of EZH2 and BCL-6 interaction in terminal B-cell differentiation suppression: BCL-6 cooperates with the histone methyltransferase EZH2 to maintain many gene regulatory elements in a bivalent chromatin state, thereby enforcing the germinal center (GC) phenotype while allowing signal-induced activation of certain genes. The termination of EZH2 activity is required for B-cells to exit the GC reaction and undergo terminal B-cell differentiation. Missense mutations of EZH2 occur in a subset of GC lymphomas. These mutations result in an enzymatic gain of function that increases H3K27me3 at target gene promoters, causing their transcriptional repression and imposing a centroblast transcriptional program. Selective EZH2 inhibitors have been developed and are effective to reactivate genes repressed or silenced by mutant EZH2

inhibits MYC expression [49]. The balancing of MYC levels in normal GC seems to be essential to reduce the number of B-cell divisions, proper migration between light and dark zone of GC, and affinity maturation [50, 51]. B-cells that do not express MYC in the light zone continue their differentiation pathway to either memory cells or plasmablasts. The conversion of plasmablasts to plasma cells is mediated by the powerful MYC repressor, BLIMP1 [52]. Conversely, B-cells with MYC overexpression undergo multiple cycles of dark zone re-entry, leading to an increased number of divisions and cellular proliferation unbalance (Fig. 11.4). Activation of the NF-kB signaling cascade represents a critical step in both the initiation and the termination of the GC reaction [53]. In addition, constitutive activation of NF-kB is the hallmark of ABC-DLBCL [54]. CD40:CD40L interaction in the light zone results in the activation of NF-kB and upregulation of IRF4, which is critical for terminal B-cell differentiation [55]. Expression of IRF4 is essential for the survival of ABC-DLBCL cells and is responsible of the plasmacytic phenotype seen in this DLBCL subset [13]. IRF4 can repress BCL-6 through the induction of BLIMP1, encoded by PRDM1 gene, which is required to initiate the plasma cell program by suppressing BCL-6 [56]. Consequently, the phenotype of ABC-DLBCL is likely to mirror that of plasmablasts. However, several genetic events in ABC-­ DLBCL block full plasmacytic differentiation by reducing expression of BLIMP1.

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Fig. 11.4  The role of MYC expression in the GC reaction: MYC expression is important for B-cell recirculation inside the GC, between dark to light and back to the dark zone for several rounds of affinity-based positive selection. This process is in part also regulated by BCL-6. BCL-6 upregulation directly inhibits MYC expression, which reduces the number of B-cell divisions, through controlled migration between light and dark zone of GC.  Furthermore, activation of NF-kB in the light zone results in upregulation of IRF4 which is critical for the induction of BLIMP1 (PRMD1 gene) and termination of the GC cycle, through the suppression of BCL-6 and MYC expression. (AID: activation-induced cytidine deaminase; SHM: somatic hypermutation; CSR: class switch recombination; GC: germinal center; ABC: activated B-cell)

These include genetic events that inactivate PRDM1 itself [57], as well as translocations or amplifications targeting BCL-6 and SPIB, both of which repress PRDM1 transcription [58] (Fig. 11.4).

Epigenetic Regulation of the GC GC B-cells are able to quickly remodel their epigenetic landscape to accommodate and coordinate responses to signals from the microenvironment. This reprograming process requires the activity of histone/chromatin modifying enzymes that catalyze the deposition of specific histone markers associated with open or closed chromatin (bivalent role). Bivalent chromatin markers play a key role in establishing the GC B-cell phenotype and preventing their premature differentiation to plasma cells [59]. Somatic mutations of histone/chromatin modifying enzymes leads to the alteration of histone markers’ bivalency at poised promoters, decreasing normal transit

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from GC B-cells to plasma cells and resulting in addiction to GC formation and therefore potential malignant transformation [59]. The most frequently somatically mutated epigenetic modifiers in DLBCL include EP300, CREBBP and EZH2, among others. EP300 and CREBBP are members of the KAT3 family of histone acetyl transferases (HATs). They encode wide-ranging expressed enzymes that in turn act as global transcriptional co-activators by interacting with more than 400 transcription factors, and by catalyzing the modification of lysines on both histone and non-­ histone proteins [60, 61]. In the GC B-cells, there are two critical non-histone substrates of CREBBP and EP300-mediated acetylation: The tumor suppressor p53, which requires acetylation for its transcriptional activity [62] and the proto-­oncogene BCL-6, a potent transcriptional repressor that regulates the GC reaction and is impaired by CREBBP and EP300-mediated acetylation [63]. By catalyzing H3K18 and H3K27 acetylation at promoter and enhancer regions, CREBBP modulates the expression of a selected number of genes that are implicated in GC exit, including signaling pathways triggered by engagement of the BCR and CD40 receptor, the plasma cell regulator IRF4, and antigen processing and presentation through the major histocompatibility complex class II (MHC-II) complex [64]. The GC-specific CREBBP transcriptional network encompasses almost all BCL-6 direct target genes, suggesting a critical role for this acetyltransferase in opposing the oncogenic activity of BCL-6, while ensuring the rapid activation of programs that sustain terminal B-cell differentiation in the GC light zone [65]. EP300 and CREBBP mutations result in either loss of function or dominant negative effects, that in turn lead to failure to induce acetylation of BCL-6 target enhancers, preventing termination of the BCL-6 transcriptional program, and favoring the constitutive activity of the BCL-6 oncogene at the expense of the p53 tumor suppressor gene [61] (Fig. 11.5). Enhancer of zeste homologue 2 (EZH2) and BCL-6, form part of the epigenetic switches that control the GC reaction. EZH2 encodes the catalytic subunit of the polycomb repressor 2 (PRC2) complex [66]. It creates bivalent promoters that control the transcription of genes involved in the negative regulation of cell cycle (CDKN1A and B) and in terminal B-cell differentiation (IRF4, PRDM1). It transiently places the B-cell differentiation and proliferation program into a poised bivalent state, so that B cells can proliferate and undergo SHM. The termination of EZH2 activity is required for B-cells to exit the GC reaction and undergo terminal differentiation. This occurs through two players, CD40 and BCR signaling, which strongly induce activation of differentiation, thus terminating the EZH2 poising effect, and presumably switching bivalents promoters to an active state, allowing differentiation to occur [67]. BCL-6 forms a complex with SMRT at active enhancers (marked with H3K4me1), causing their H3K27 deacetylation through HDAC3 and placing them in a repressed/poised configuration. Both EZH2 and BCL-6 switches result in transcriptional repression of genes that define the centroblast phenotype. Missense mutations of EZH2 occur in 22% of patients with GC-DLBCL, 12% of patients with follicular lymphoma, and are absent in ABC-DLBCL [68]. These mutations are always heterozygous, and the vast majority affect tyrosine residue 641 [69]. Mutation of EZH2 results in an enzymatic gain of function that increases H3K27me3 at target gene promoters, causing their

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Fig. 11.5  NF-Kb and CREBBP effects on terminal B-cell differentiation and GC exit: Activation of NF-kB leads to upregulation of IRF4 which is critical for terminal B-cell differentiation. IRF4 can repress BCL-6 through the induction of BLIMP1 which is required to initiate the plasma cell program. In a physiologic state, BCL-6 function is impaired by CREBBP-mediated acetylation. CREBBP mutations result in either loss of function or dominant negative effects that in turn lead to failure to induce acetylation of BCL-6 target enhancers, preventing the termination of BCL-6 transcriptional activity and contributing to impose a centroblast transcriptional program. Histone deacetylase (HDAC) inhibitors may help to oppose the loss of function of mutated CREBBP by removing acetylation marks in some critical genes such as BCL-6 (GC: Germinal Center)

transcriptional repression and imposing a centroblast transcriptional program. EZH2 mutation is inconsistent with the ABC-DLBCL phenotype, as it represses CD40 and NF-kB target genes that lead to GC exit and drive the ABC-DLBCL phenotype. Wildtype EZH2 GCB-DLBCLs are biologically dependent on EZH2, and display a GC bivalent gene repression signature, similar to EZH2 Y641mutant patients [59] (Fig. 11.3).

B-Cell Receptor (BCR) Signaling Pathway BCR is of particular importance to the biology of normal and neoplastic B cells. Each mature B-cell carries 120,000 BCR complexes on its surface, with identical antigen binding sites. The BCR is a membrane-bound antibody that can transduce signals intra-cellularly by virtue of its non-covalent association with a CD79A-­ CD79B heterodimer [70]. The antibody portion of the BCR is composed of two immunoglobulin heavy (IgH) and two immunoglobulin light (IgL) chains [70]. The

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shuffling of gene segments that encode the IgH and IgL chains generates BCRs that can recognize a tremendous diversity of antigens, both foreign and self, resulting in a unique BCR for each B-cell [70]. The antibody portion of the BCR, associated with a heterodimer of CD79A and CD79B, forms a complete BCR on the cell surface which in turn binds antigen and initiates signal transduction. Signaling is primarily mediated through the single Immunoreceptor Tyrosine based Activation Motif (ITAM) present in the cytoplasmic tail of both CD79A and CD79B [71]. Each ITAM contains two tyrosine residues surrounded by a conserved YxxL/Ix(6–8)YxxL/I sequence [70]. Two main BCR-signaling pathways exist: “Chronic active” and “Tonicogenic”. In chronic active BCR signaling, antigen engagement induces aggregation of the BCR on the plasma membrane, leading to rapid phosphorylation ITAM tyrosines of CD79A/CD79B by Src-family kinases (SFKs), including LYN, FYN, and B-cell lymphocyte kinase (BLK) [72]. Phosphorylated ITAMs can then recruit SYK kinase by virtue of its tandem Src homology 2 (SH2) domains that can bind dually phosphorylated ITAMs, ultimately resulting in SYK activation [73]. The active BCR signalosome recruits a host of adapter proteins, including BLNK and LAT2, and additional kinases, including Bruton’s tyrosine kinase (BTK), phosphatidylinositol 3-kinase (PI3K) and a serine/threonine protein kinase (AKT). Subsequently, antigen-stimulated BCR activation engages multiple signaling cascades to impact proliferation, survival, and differentiation of B-cells, mainly through calcium signaling and NF-κB, the dominant downstream pathway utilized by B-cells to maintain their viability [70] (Fig. 11.6). ABC-DLBCL cells are highly dependent on NF-kB for their viability [74] which is triggered by BCR-dependent activation of BTK [75]. Several mechanisms facilitate this dependence. CARD11 mutations are present in 15% of ABC-DLBCL resulting in spontaneous formation of the CARD11, BCL-10, MALT1 (CBM) complex which activates IkB kinase β (IKKβ), the main kinase in activation of the classical NF-kB pathway [76]. Gain-of-function mutations of CD79B and CD79A are seen in about 20% of DLBCLs [75]. These mutations target the ITAMs, interfering with the negative feedback mediated by the tyrosine kinase Lyn and inducing the microclustering of BCRs on the plasma membrane and interfering with internalization of the BCR complex. A large subset (about 30%) of ABC-DLBCL with wildtype CD79B/A and CARD11 are addicted to chronic BCR signaling that are explained in part by the autoreactivity of BCR to sugars on self-antigens (glycoproteins) using the segment IgVH4–34, also called “self-antigen-driven” BCR signaling [77]. In contrast, GC-DLBCL is not dependent on BTK-activation of NF-kB for their viability, rather it utilizes BCR, CD19 and SYK to engage PI3K as the main downstream survival pathway, through the “tonicogenic” BCR signaling [78]. This signaling pathway is ligand independent and does not involve BCR microclustering, as it maintains the survival by primarily stimulating the PI3K pathway [79].

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Fig. 11.6  An integrated representation of BCR-signaling pathway and its downstream players with their corresponding targeted inhibitors. The supercomplex integrated by MYD88, TLR9 and the BCR (MY-T-BCR) is also shown: Stimulation of the BCR initiates aggregation of the BCR complex and induces the phosphorylation of the ITAMs within the cytoplasmic tails of the CD79A and B heterodimer. Phosphorylation of the ITAMs is mediated by SRC-family kinases (SFKs) including LYN, FYN and BLK. Phosphorylated ITAMS can then recruit SYK kinase and BTK is activated, which in turn activates PLC-γ, recruits PI3K and activates AKT signaling. PLC-γ generates diacylglycerol (DAG) and the release of Ca2 + (not shown). These second messengers induce the activation of PKC-β finally leading to the activation of the CBM complex and NF-kB pathway. My-T-BCR signaling relies in two pools of BCRs; one enriched for mutant isoforms of CD79B (indicated as a red start) located in the plasma cell membrane that contribute to activate the CBM complex, and the pother pool is enriched with wildtype CD79B. This wildtype CD79B pool is internalized into the endolysome and interacts with TLR9 to form the My-T-BCR complex. The My-T-BCR requires the active CBM complex to activate IKK and NF-kB.  This mechanism explains why double mutant MYD88 and CD79B lymphomas are highly dependent of BTK and are highly sensitive to Ibrutinib

MYD88 and the NF-kB Signaling Pathway Myeloid differentiation factor (MYD88) is an adaptor molecule that contains three main structures: A death domain (DD) at the N terminus, an intermediate linker domain (ID), and a Toll/interleukin-1 receptor domain (TIR) at the C terminus [80]. Following ligand binding, the cytoplasmic TIR domain of Toll-like receptors (TLR) or IL1R associate with the TIR of MYD88 [81], this is followed by the serine– threonine kinase of IL1-receptor–associated kinase 4 (IRAK4) binding to MYD88 through the interaction of the death domains of both molecules [80]. IRAK4 interacts and phosphorylates IRAK2 and IRAK1 to form a complex known as the “Myddosome“[82]. Phosphorylated IRAKs 1 and 2 interact with the E3 ubiquitin ligase TNF receptor–associated factor 6 (TRAF6), via their TRAF binding domains [80]. TRAF6 ultimately recruits TAK1-binding protein 2 (TAB2) and activates

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TAB2-associated TGFβ activated kinase 1 (TAK1), which promotes cell survival through activation of both the canonical NF-kB pathway and the mitogen-activated protein kinase (MAPK) pathway [81–83] (Fig. 11.6). Mutations targeting MYD88 are among the most frequent gain-of-function genetic events in DLBCL (~30% of cases of ABC-DLBCL) [84]. The most prevalent MYD88-mutant isoform, L265P, seems to be restricted to ABC-DLBCL, whereas the other recurrent mutated MYD88 isoforms are equally distributed between the two DLBCL subtypes [15]. MYD88L265P is distinguished from the other isoforms by its ability to form a stable signalosome in which IRAK4 hyperphosphorylates IRAK1 [80]. Consequently, IRAK4 inhibitors are selectively toxic for ABC-DLBCL cell lines with MYD88L265P [80]. JAK–STAT3 signaling gene signature overlaps significantly with the MYD88- and IRAK1-regulated gene signatures in ABC-DLBCL, as knockdown of MYD88 appears to significantly diminish the secretion of IL6, IL10, and IFNβ and the phosphorylation of STAT3  in ABC-­ DLBCL cells [84]. In addition, IL6, IL10, and IFNβ secretion is blocked by IRAK1/4 kinase inhibitor or MYD88 knockdown, indicating that MYD88 mutations, along with IRAK1/4, contribute to JAK–STAT3 and type I interferon signaling in ABC-DLBCL [84]. STAT3 is a critical transcriptional regulator of ABC-DLBCL, as STAT3 upregulates genes related to NF-kB, PI3K–AKT–mTORC1, and E2F/ G2–M cell-cycle checkpoint and downregulates the expression of IRF7, IRF9, STAT1, and STAT2 in ABC-DLBCL cell lines with MYD88L265P [85]. Thus, STAT3 accentuates survival signaling pathways while dampening the lethal type I interferon pathway in ABC-DLBCL cells with MYD88L265P [80]. Therefore, JAK1 inhibitors appear to be toxic for ABC-DLBCL lines with mutant MYD88 [86].

MyD88-TLR9-BCR TLR9 (my-T-BCR) Supercomplex Interaction between BCR and MYD88 signaling through a MyD88-TLR9-BCR (My-T-BCR) supercomplex has been suggested using proteomic data [70]. The My-T-BCR coordinates the majority of pro-survival NF-κB signaling by the intervention of two players: MYD88 and the CBM (multi-protein complex consisting of CARD11, BCL10, MALT1, and TRAF6) [87], and this interaction occurs on the surface of endolysosomes and includes also the mTOR1 complex [78] (Fig. 11.4). Wildtype CD79B and CD79A subunits of surface BCR undergo endocytosis and form the My-T-BCR, whereas BCRs with mutant CD79B/A isoforms engage signaling mediators on the plasma membrane to further promote My-T-BCR formation [70]. This explains the sensitivity MYD88/CD79B double-mutant tumors to the BTK inhibitor, Ibrutinib. In fact, a clinical trial testing the efficacy of Ibrutinib in DLBCL showed that patients with tumors harboring both MYD88L265P and CD79B mutations had an 80% overall response rate (ORR), whereas those with only a MYD88 mutation did not respond. These findings suggested that MYD88/CD79B double-mutant tumors are hyper-addicted to BCR-dependent NF-κB signaling and are therefore hyper-responsive to Ibrutinib [88] (Fig. 11.6).

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Genomic Landscape of DLBCL Using the COO to guide therapy is suboptimal due to the presence of diverse subgroups within the GC and ABC categories. This genomic heterogeneity in DLBCL has been unveiled using techniques that incorporate next generation sequencing, illustrating the wide range of genetic alterations that drive or contribute to lymphomagenesis. Initial genomic analyses, although limited by small sample size, identified the genetic diversity of DLBCL [89–91]. For example, one study identified a subgroup of DLBCL with frequent mutations in histone-modifying genes such as MLL2, which encodes a methyltransferase enzyme and MEF2B, a calcium-regulated gene that cooperates with CREBBP and EP300 in acetylating histones [89]. This was followed by another study in which whole-exome sequencing demonstrated recurrent mutations in genes such as: MYD88, CARD11, EZH2, and CREBBP [91]. In addition to mutations, copy-number alterations were also highlighted in DLBCL. In one limited analysis of DLBCL, 90 copy-number alterations were identified among six patients, with significant variability across samples [90]. Another analysis of a larger cohort of patients identified 47 recurrent copy-number alterations, including 21 copy gains and 26 copy losses, with frequencies of 4% to 27%, many of which resulted in decreased p53 activity and perturbed cell-cycle regulation [92]. These studies contributed to understanding the genomic complexity of DLBCL.  However, they were limited by the small number of patients, and thus could not provide a map of disease sub-categorization and suitable therapeutic approach based on genomic characteristics. Subsequently, a whole-exome sequencing and transcriptome analyses from a cohort of more than 1000 patients with DLBCL identified single-nucleotide variants, insertions/deletions, and copy-­number alterations in DLBCL, resulting in the discovery of approximately 150 recurrent mutated driver genes, including some that occur at low frequencies and could be missed in smaller studies [93]. Although most identified mutations occurred in GC and ABC subtypes, a small number of alterations were specific to each COO classification. For example, EZH2, SGK1, GNA13, SOCS1, STAT6, and TNFRSF14 mutations were more frequently mutated in GC DLBCLs, whereas ETV6, MYD88, PIM1, and TBL1XR1 were more frequently mutated in ABC-DLBCLs [93]. The functional role of these aberrations was also subject to study by unbiased CRISPR screens [93]. Additional studies incorporating analyses of a broad range of genomic aberrations in large cohorts of patients with DLBCL have been published. In one study of 151 patients, a total of 761 potential driver mutations were identified, and all tumors were found to have copy-number alterations, including frequent losses, gains, and amplifications [94]. In addition, the clinical influence of genetic alterations in pre-­ defined functional pathways was analyzed. For example, mutations in the NOTCH signaling pathway and in TP53/CDKN2A were associated with poorer outcomes, whereas JAK/STAT pathway mutations were associated with improved outcomes. It is also worth mentioning that, in the same study, 46% of patients were found to have

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at least one genomic alteration that could be a predictive biomarker of drug response and could potentially be exploited to guide targeted therapy [94]. Another impactful study incorporated whole-exome and transcriptome sequencing, array-based copy-number analysis, and targeted amplicon re-sequencing in 574 DLBCL samples, aimed to use these genetic aberrations to sub-categorize ABC and GC subtypes [15]. CD79B and MYD88L265P mutations were found to be enriched in ABC subtype DLBCLs, whereas EZH2 mutations and BCL-2 translocations frequently co-existed in the same tumor and occurred often in the GC subtype [15]. Interestingly, mutations such as NOTCH2 and BCL-6 fusions were less likely to be classifiable by COO [15]. Based on these findings, DLBCL tumors were classified into 4 genomic subtypes, characterized by (1) CD79B/MYD88L265P double mutations (MCD subtype), (2) NOTCH2 mutations or BCL-6 fusions in ABC or unclassified DLBCL (BN2 subtype), (3) NOTCH1 mutations (N1 subtype), and (4) EZH2 mutations or BCL-2 translocations (EZB subtype) [15]. These subtypes had prognostic relevance even after accounting for COO assignment, with inferior responses found in patients with CD79B/MYD88L265P double mutations (MCD subtype) and NOTCH1 mutations (N1 subtype) [15]. It is worth mentioning that these genomic subtypes represented less than half of the investigated cases, proposing that a distinct pattern of genomic diversity might be identified in the remaining group of patients [15] (Fig. 11.7). The MCD subtype is composed mostly of ABC cases and is thought to be a pure form of ABC-DLBCL that is highly enriched with many genetic events that distinguish ABC from GC. Deletion of the CDKN2A tumor suppressor locus occurs in 83% of cases. Tumors with both MYD88L265P and CD79B mutations and amplifications are common in this subtype. These mutations are also the hallmark of extranodal lymphomas, including primary central nervous system lymphoma, primary testicular lymphoma, primary breast lymphoma, primary cutaneous lymphoma, and intravascular lymphoma [95–97]. The MCD subtype is characterized by the BCRdependent NF-KB activity and abrogation of immune surveillance inactivating class I HLA genes or CD58 [15]. The 5-year survival for the MCD subtype (using R-CHOP) is 26%, and these tumors have a high response rate to Ibrutinib [98]. The BN2 subtype has a large contribution from unclassified and ABC-DLBCL but is also a substantial component of GC tumors. This subtype is characterized by BCL-6 translocations and gain-of-function NOTCH2 mutations, in addition to inactivating mutations of SPEN an inhibitor of NOTCH-dependent gene activation. BN2 is genetically similar to marginal zone lymphomas, which acquire NOTCH2 and SPEN mutations. BN2 may arise from an occult marginal zone lymphoma or possibly from monoclonal B-cell lymphocytosis with marginal zone features (CD5 negative), which also has recurrent NOTCH2 mutations [99]. The 5-year survival for the BN2 subtype is 65% [15]. The N1 subtype is rare and is characterized by gain-of-function of NOTCH1 mutations. This subtype has a prominent plasmacytic gene expression pattern, likely secondary to mutations or amplification of IRF4. These tumors appear associated

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Fig. 11.7  Summary of the major findings in the four subtypes of DLBCL based on integrated genomic analysis performed by Dr. Staudt group. These subtypes had prognostic relevance with inferior responses for those patients with CD79B/MYD88L265P double mutations (MCD subtype) and NOTCH1 mutations (N1 subtype). These genomic subtypes represent less than half of the cases, proposing that a distinct pattern of genomic diversity might be identified in the remaining group of patients

with a rich immune cell microenvironment. The 5-year survival for the N1 subtype is 36% [15]. EZB subtype is composed of GC tumors and is enriched with common genetic abnormalities ascribed to GC-DLBCL, such as BCL-2 translocations and EZH2 mutations, which frequently co-occur in the same EZB tumor. CREBBP and EP300 are inactivated in EZB tumors. EZB tumors are enriched with genetic alterations affecting PI3K pathway, including PTEN mutations and deletions, and amplification of MIR17HG, which encodes a microRNA targeting PTEN, in addition to MTOR mutations and inactivating lesions targeting S1PR2/Ga13 pathway, which negatively regulates AKT [100, 101]. The 5-year survival for the EZB subtype is 68% [15]. Additional analysis of a large cohort of previously untreated patients has identified distinct genomic subtypes of DLBCL using comprehensive genomic analyses [16]. Recurrent mutations, somatic copy-number alterations, and structural variants were incorporated to characterize patient samples into distinct genomic clusters, using genomic signatures subsequently correlated with outcome data [16]. Again,

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this genomic-based classification suggested heterogeneity even within the COO subgroups, with a newly identified poor-risk GC subtype and a favorable-risk ABC subtype [16]. Specific subsets of tumors clusters with particular genetic signatures included: (1) high-risk ABC-DLBCLs with near-uniform BCL-2 copy gain, frequent activating MYD88L265P, CD79B mutations, and extranodal tropism (cluster 5); (2) low-risk ABC DLBCLs with genetic features recapitulating an extra-follicular, possibly marginal zone origin such as NOTCH2, SPEN and MYD88 non-L265P mutations, and BCL-6 structural variations (cluster 1); (3) high-risk GC DLBCLs with BCL-2 structural variations, inactivating mutations and/or copy loss of PTEN and alterations of epigenetic enzymes (cluster 3); (4) a newly defined group of low-­ risk GC DLBCLs with distinct alterations in JAK/STAT and BRAF pathway components and multiple histones (cluster 4); and (5) an ABC/GC-independent group of tumors with bi-allelic inactivation of TP53, 9p21.3/CDKN2A copy loss and associated genomic instability (cluster 2). The genetically distinct subtypes were found to have significant differences in progression-free survival (PFS), with a significantly higher risk of relapse in clusters 5 and 3 [16] (Fig. 11.8). These recent comprehensive genomic analyses have shed light on the previously unappreciated genomic complexity of DLBCL, the limitations of gene expression-­ based classification systems, and the challenge of adopting a uniform treatment approach in this disease. They have also opened doors to specific therapeutic approaches of tumor subsets characterized by genomic means. In 2020, and following the seminal genomic studies by Schmitz et  al. [15] and Chapuy et  al. [16], Wright et al. suggested the implementation of their proposed “LympGen” algorithm

Fig. 11.8  Summary of the major findings in the five identified clusters of DLBCL based on integrated genomic analysis, and their corresponding risk categories performed by Dr. Shipp group. The genetically distinct subtypes were found to have significant differences in progression-free survival (PFS), with a significantly higher risk of relapse in clusters 5 and 3

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in precision medicine trials, to help determining the probability of assigning a certain DLBCL patient to one of seven isolated genetic subtypes, with distinct clinical outcomes and aberrant genetic pathways: (1) MCD; (2) N1; (3) A53; (4) BN2; (5) ST2; (6) EZB MYC+; and (7) EZB MYC− [102].

Precision Medicine in DLBCL Standard of Care in DLBCL Despite the availability of several prognostic tools to predict response to treatment, efforts to tailor therapeutic interventions for specific subtypes have so far demonstrated little success, and R-CHOP is still considered the frontline therapy across most DLBCL subtypes, except for primary mediastinal B-cell lymphoma where DA-EPOCH-R has showed high efficiency, with overall survival rates greater than 90% with long term follow-up [103, 104]. However, data collected retrospectively advocates the application of more aggressive combination chemotherapy strategies in high-grade B-cell lymphoma with translocations involving MYC and BCL-2 and/ or BCL-6 [105–107]. The clinical implications of the new proposed molecular subtypes and risk identifiers [102], potentially guiding future development of personalized and targeted therapy in DLBCL, remain to be elucidated in prospective clinical trials.

Targeted Therapy BCR-Signaling Pathway Inhibitors • Ibrutinib: Inhibiting BTK using Ibrutinib has proved to be groundbreaking in the therapeutic management of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) [108]. BTK is responsible for the generation of pro-­ survival signals from BCR and is frequently constitutively active in ABC-­ DLBCL [88]. Increasing data suggest that Ibrutinib may be beneficial in poor-risk, BCR/NF-kB-dependent ABC-DLBCL patients. In a phase I/II trial of 80 patients, single-agent Ibrutinib was well-tolerated and had an ORR of 37% in ABC-DLBCL, compared to only 5% in GC-DLBCL patients [88]. In addition, in a phase I study examining Ibrutinib in combination with rituximab-based chemotherapy, all non-GC patients achieved complete remission [109]. Following the success of these trials, Ibrutinib is being tested in several phase III trials for ABC-DLBCL, which includes a combination with R-CHOP for newly diagnosed ABC-DLBCL patients (NCT01855750), and in relapsed/refractory ABC-­ DLBCL patients undergoing stem cell transplant (NCT02443077). While a

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clinical trial demonstrated that Ibrutinib could induce complete and partial responses in relapsed/refractory ABC-DLBCL, the median PFS of these patients was only 6.41  months, indicating that Ibrutinib resistance develops rapidly in this lymphoma subgroup [88] owing to genetic and non-genetic mechanisms [70]. • SYK inhibitors: SYK kinase is an appealing therapeutic target to treat all BCR-­ dependent lymphomas, as it transduces both chronic active and tonic BCR signals [70]. The pro-drug version of the SYK inhibitor R406 is Fostamatinib (R788). Fostamatinib treatment has been shown to prolong survival in mouse models of lymphoma that rely on either tonic or antigen-dependent BCR signaling [110]. In addition, the R406 treatment was toxic to cell line models of GC-­ DLBCL [111] and ABC-DLBCL [75]. Although it has demonstrated clinical activity against DLBCL, one drawback to the therapeutic application of Fostamatinib is its lack of selectivity to SYK [112, 113], which increases its toxicity profile and precludes further clinical development [114]. To address the issue of toxicity, more selective SYK inhibitors are in development, including PRT062607 and Entospletinib (GS-9973) [78, 115]. However, these drugs have limited efficacy as monotherapy. A phase 2 study of Entospletinib in relapsed/ refractory indolent lymphomas and mantle cell lymphoma demonstrated that this agent has manageable toxicity but modest efficacy as monotherapy [116]. In addition, a similar study in relapsed/refractory DLBCL resulted in no objective responses [117]. • PI3K inhibitors: PI3K is a lipid kinase that phosphorylates the 3-hydroxy position of PI(4,5)P2 to form phosphatidylinositol (3,4,5)-trisphosphate (PIP3) [70]. BCR-dependent PI3K activity results in localized increases in PIP3, which can recruit signaling effectors [118] including AKT and BTK. Active AKT has many potential substrates, but its phosphorylation and activation of mTOR is key, since mTOR is a master regulator of cellular metabolism that is constitutively active in many lymphomas [119]. Three classes of PI3K exist, but only the class I PI3K signal is proximal to the BCR [120]. Class I PI3Ks contain a regulatory p85 subunit paired to one of four catalytic p110 subunits to form PI3Kα, PI3Kβ, PI3Kγ, and PI3Kδ. A constitutively active form of PI3Kα can substitute tonic BCR signaling [79]. In addition, PI3Kα and PI3Kδ are both essential for B-cell development in mice [121]. Pre-clinical studies have demonstrated that inhibition of PI3K activity with the pan-class I PI3K inhibitor, BKM-120, is toxic for ABC cell lines harboring CD79B ITAM mutations [122]. However, PI3Kα and PI3Kβ are ubiquitously expressed, and pan-PI3K inhibitors such as BKM-120 can have significant adverse effects [123], which may limit their usage in treating GC-DLBCL that relies on tonic signaling. Idelalisib (CAL-101/GS-1101), a specific PI3Kδ inhibitor, has been approved for the treatment of follicular lymphoma as well as relapsed/refractory CLL/SLL [70]. Copanlisib (BAY 80–6846) is a dual inhibitor of PI3Kδ and PI3Kα that is approved for the treatment of relapsed/ refractory follicular lymphoma [70]. Pre-clinical studies of PI3K inhibitors in cell line models of ABC-DLBCL have demonstrated that selective PI3Kδ inhibition is quickly countered by an increase in PI3Kα activity, which can be targeted

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by Copanlisib [124, 125]. PI3Kδ expression is restricted to lymphocytes and is specifically activated following BCR ligation [126], making it an appropriate target in lymphomas with chronic active or tonic BCR signaling. • mTOR inhibitors: Rapamycin (Sirolimus) was the first mTOR (mammalian target of rapamycin) inhibitor discovered over 40 years ago [127]. However, currently, there are numerous mTOR inhibitors available on the market, such as Temsirolimus and Everolimus, which have shown objective responses in 28% [128] and 30% [129] of patients with relapsed/refractory DLBCL, in two phase II clinical trials. Nevertheless, the remissions were unfortunately temporary. The discovery of unique mutations of the RRAGC and the V-ATPase ATP6V1B2 and ATP6AP1 genes in around 30% of follicular lymphoma patients, enforcing mTORC1 activation [130–132], was made after these two trials were done. This suggests re-examining previously trialed agents, to detect mTOR pathway mutations, and study their effect on therapeutic response. The mTORC1 complex is a component of the My-T-BCR supercomplex in ABC-DLBCL of the MCD subtype [78]. Treatment of ABC lines with Ibrutinib reduced the association of mTOR with other My-T-BCR components, and decreased mTOR activation of downstream pathways. Treatment of these same lines with the mTOR inhibitor AZD2014 augmented the ability of Ibrutinib to disrupt the My-T-BCR complex, resulting in a marked decline in NF-κB activity [78, 133] providing clinical evidence of the efficacy of combination therapy targeting both BTK and the mTOR pathway in at least a subset of ABC-DLBCL. Bortezomib Bortezomib is a proteasome inhibitor that blocks degradation of IkBa, consequently inhibiting NF-kB activity. There has been limited data regarding the role of Bortezomib as a single agent in relapsed/refractory DLBCL, however when combined with chemotherapy, a small study consisting of 12 patients with ABC and 15 with GC-DLBCL demonstrated that there were increased responses (83% versus 13%) and median OS (10.8 versus 3.4 months) in ABC compared with GC-DLBCL, respectively [134]. In another study, Bortezomib was used in combination with R-CHOP for the initial therapy of DLBCL [135]. Unlike previous studies of R-CHOP alone, patients with GC and ABC subtype DLBCL were found to have comparable outcomes, suggesting possible improvement in the outcome of ABC patients [135]. Following these promising results, a randomized phase 2 Trial was designed to compare R-CHOP alone with R-CHOP plus Bortezomib in patients with non-GC subtype DLBCL, determined by IHC [136]. Overall response rates with R-CHOP and R-CHOP plus Bortezomib were 98% and 96%, respectively, and there was no significant OS with the addition of Bortezomib [136].

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EZH2 Inhibitors As mentioned above, EZH2 is a histone methyltransferase that acts as the catalytic subunit of the polycomb repressor complex two and catalyzes repressive monomethylation, dimethylation and trimethylation of the histone 3 lysine 27 (H3K27) residues. In GC lymphomas, its important role in regulating the normal GC reaction [42] is subverted by heterozygous mutations, most commonly altering tyrosine 646 (Y646) within the catalytic SET domain [69]. These gain-of-function mutations alter the catalytic activity of the mutant EZH2 enzyme so that it preferentially catalyzes the conversion of H3K27me1 into the strongly repressive H3K27me2/3 marks at target gene promoters, causing their transcriptional repression and imposing a centroblast transcriptional program, whereas the wildtype protein continues to deposit H3K27me1 [137]. It has been shown in one study that MHC-II deficient-­ DLBCL in murine models harbor somatically acquired gene mutations that reduce MHC-II expression, with a strong enrichment of EZH2 mutations (mutant Ezh2 Y641) [138]. This finding could represent an acquired immune escape in GC-DLBCL [138]. In the same study, EZH2 inhibitors were found to be efficient in restoring MHC expression in EZH2-mutated human DLBCL cell lines providing a rationale for the combination of immunotherapy with epigenetic reprograming [138]. Selective EZH2 inhibitors have been developed (EPZ6438, tazemetostat) [139], GSK126 [140] and CPI-1205 [141], with preclinical data indicating that these compounds are generally more active in mutant cell lines and able to reactivate genes repressed or silenced by mutant EZH2 [139, 140]. Phase I/II clinical trials have now been launched for all of these compounds to examine their efficacy for lymphomas with recent interim data suggesting that tazemetostat is efficacious for EZH2mutated follicular lymphoma (92% ORR in mutant versus 26% in wildtype) and to a lesser extent in DLBCL (29% ORR in mutant versus 15% in wildtype) [142, 143].

New Strategies Using HDAC Inhibitors CREBBP mutations are one of the earliest events in GC lymphomas [65, 89, 93, 144–147], with an established role in promoting GC lymphoma expansion [64, 65, 132, 146–148]. Phylogenetic analysis has revealed that common progenitor cells or long-lived premalignant cells, which are believed to be t(14;18)-positive and typically contain mutations within the histone regulatory genes CREBBP and KMT2D [149–152], give rise to overt FL, and subsequent relapses of the disease. It is therefore suggested that the successful targeting of these genes can offer new therapeutic alternatives, with the potential of eradicating disease-propagating cells. It has been proposed that the inhibition of the histone deacetylase (HDAC) enzymes, that normally oppose CREBBP by removing acetylation marks, could mitigate the deep-­ rooted loss of histone acetyltransferases CREBBP and EP300 [153]. The occurrence of significant toxicities following the administration of pan-HDAC inhibitors, alongside the absence of a biomarker to track their efficacy and an unclear

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mechanism of action, has precluded progress beyond phase II trials [153], although pan-­HDAC inhibitors have demonstrated efficiency in GC lymphomas [154–156]. However, this may change in the future, with recent studies exploring the relationship between CREBBP mutations and HDAC isoforms revealing that: HDAC3 opposes the activity of CREBBP at enhancers and hyper-represses these enhancers following the loss of CREBBP, resulting in an increased dependency on HDAC3 for survival [65]. Targeting the HDAC3 isoform thus offers a potential therapeutic strategy with the promise of reactivating CREBBP-regulated genes while minimizing toxicity associated with pan-HDAC inhibitors [153].

Combination Therapy Aggressive lymphomas rely on an integrated network of cellular signaling cascades to promote malignant growth. Inhibition of a single pathway can be compensated by either mutation or biochemical rewiring of these signal networks, which likely accounts for the limited frequency and durability of responses to individual targeted agents. Thus, inhibition of parallel survival pathways cannot only result in synergistic killing of malignant cells but also reduces the emergence of therapy resistance. The challenge is to identify drug combinations that can synergistically kill malignant B-cells while minimizing side effects. In part, this can be done using the wealth of data generated in the genetics, biology, and oncogenic signaling of lymphoma. For example, ABC-DLBCL relies on a minimum of five pathways to remain viable: (a) NF-κB; (b) PI3K/mTOR; (c) JAK1/STAT3; (d) BCL-2 family and (e) lineage-­ defining transcription factors [70]. One strategy is to perform unbiased large-scale screens of clinically active compounds. One such screen has profiled toxicity in an ABC-DLBCL line treated with increasing doses of Ibrutinib versus titrations of over 500 active compounds [157]. This screen has revealed synergy of Ibrutinib in combination with inhibitors of SYK, the PI3K pathway, and the BCL-2 family, as well as with standard chemotherapy agents [157]. Additional studies observed synergy between Ibrutinib and inhibitors of JAK1, 187 IRAK family kinases, 99 BET proteins 188 and the lineage-defining transcription factor IRF4 [158]. The addition of Ibrutinib to combination chemotherapy in the DA-TEDDi-R regimen produced complete responses in 86% of patients with primary CNS lymphomas that have been sustained for at least 2 years in 67% of patients with relapsed/refractory disease [159]. These promising results await further confirmation in an ongoing phase 2 trial. A double-blind phase 3 Trial randomly assigned 838 patients with non-GC-­ DLBCL into two treatment arms comparing R-CHOP chemotherapy plus placebo, to R-CHOP plus Ibrutinib [160]. Patients under 60 years of age had significantly improved survival on the R-CHOP plus Ibrutinib arm, with Ibrutinib increasing the 5-year overall survival rate by roughly 12%. Patients over the age of 60 years experienced increased toxicity when Ibrutinib was included, which led to discontinuation of both Ibrutinib and chemotherapy, resulting in correspondingly worse clinical outcomes and accounting for the selective activity of Ibrutinib in younger patients.

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This is the first randomized phase 3 Trial in 17 years to report a regimen that produces a significantly higher rate of long-term survival than achieved with R-CHOP alone. The success of this platform may be extended in the future with the addition of targeted agents that synergize with Ibrutinib. This phase 3 Trial used immunohistochemistry to select patients with non-GC-DLBCL. Most tumors were also analyzed by gene expression profiling and were found to be enriched for ABC and unclassified cases, as expected. Interestingly, the effect of Ibrutinib was not significantly greater in the pure ABC subset than in the entire cohort, possibly because the non-ABC tumors had genetic lesions in the BCR-dependent NF-κB pathway. In line with this hypothesis, genetic lesions in the BCR pathway are infrequent in GC-DLBCL but are clearly overrepresented in both ABC and unclassified DLBCL. An understanding of the molecular determinants of response to the combination of R-CHOP plus Ibrutinib awaits the comprehensive genomic characterization of biopsies from this trial. Although many candidates for combination trials have known safety profiles as single agents, unexpected toxicities may occur in combination with other agents. For example, two patients died and others fell ill of pneumonitis on a combination trial of Idelalisib and Entospletinib, due to release of inflammatory cytokines [161]. In primary CNS lymphoma patients treated with the DA-TEDDi-R regimen mentioned above, opportunistic infections were detected in the lung and/or brain in 7/18 patients and resulted in two deaths [159]. Some of these infections occurred when the patients were only receiving Ibrutinib monotherapy in a 2-week window prior to the addition of chemotherapy, suggesting that these infections were potentially due to an effect of Ibrutinib on the immune system.

An Integrated Approach The challenge ahead has mainly two facets: (a) to identify drug combinations that can overcome drug resistance and relapse, while limiting toxicities, and (b) to detect subtypes of DLBCL for which particular pathway inhibitors produce a high rate of durable remissions. The identification of tumors likely to respond to certain drug combinations will require the application of genetic profiling [15, 16], RNA profiling [10, 19] and evaluation of biomarkers of transducing pathways, to detect active signaling even in the absence of a genetic marker [78]. One way to overcome these challenges is by conducting large trials with extensive molecular profiling of tumors, to identify those with the constellation of abnormalities that foster addiction to oncogenic survival pathways, targeted by the drug combination under study. An interesting opportunity for combination therapy has arisen with the success of CAR-T therapy for lymphoma [162, 163] and the efficacy of an anti-CD47 monoclonal antibody (Hu5F9-G4) plus rituximab in lymphoma [164]. Although they show an undeniable efficacy in some instances, these immunotherapies do not work in all patients, and it is possible that in some cases failure is a result of tumor growth outstripping the rate at which immunotherapy can kill the malignant cells [70]. Therapies targeting the BCR may improve outcomes in such patients, by inducing

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an extensive depletion of the tumor mass, allowing immunotherapies a chance to clear the residual cells [70]. Circulating tumor DNA (ctDNA) as a biomarker in DLBCL: ctDNA has been an attractive approach to monitor and detect relevant mutations in the setting of tumor diagnosis, as it is minimally invasive, allows serial sampling, and can be sensitive enough to detect subclinical disease. Although not routinely used yet, ctDNA has been proven to be a useful biomarker to assess therapeutic response [27]. In fact, one study demonstrated the successful use of ctDNA sequencing for dynamic assessment of minimal residual disease in 17 patients with DLBCL and mediastinal large B-cell lymphoma post chemo-immunotherapy [27]. In addition, the presence of ctDNA in the plasma appears to precede PET/CT detection of relapsed disease and correlates with disease progression [28, 29]. This has been illustrated in a study in which, detection of molecular disease by immunoglobulin high-throughput sequencing from peripheral blood was able to provide an alternate strategy for surveillance, with specificity superior to PET/CT [29]. Another study performed an interim monitoring of ctDNA at the end of two treatment cycles in 108 patients with DLBCL and showed a 5-year time to progression of 41.7% in patients with detectable ctDNA and 80.2% in those without detectable ctDNA (p 60  years at diagnosis, respectively—and more often involve females with a female-to-male ratio of 2:1. They present in the thymic area with bulky anterior mediastinal mass that can invade adjacent structures such as lungs, pleura, pericardium and breasts [4]. There may be regional lymph node involvement, but distant lymph nodes or bone marrow are typically uninvolved. Signs and symptoms associated with the tumor mass in the mediastinum include superior vena cava syndrome such as dyspnea, coughing, plethora and swelling of the face, neck, upper trunk, and extremities. PMBL arising from non-­ mediastinal sites with no obvious mediastinal involvement has been described, but definitive identification of these cases requires gene expression profiling (GEP) studies [6, 7].

Microscopic and Immunophenotypic Features Morphologically, PMBL demonstrates a diffuse growth pattern composed of medium to large atypical cells in a background of fine compartmentalizing fibrosis. The neoplastic cells show cytologic variation from round-ovoid to multilobated nuclei with abundant pale cytoplasm. Hodgkin-like forms may be seen. Immunophenotypically, the neoplastic cells uniformly express B-cell lineage antigens such as CD19, CD20, CD22, PAX5, OCT2, and BOB1, but they are negative for surface immunoglobulins. CD30 positivity is seen in the majority of cases, but,

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unlike CHL, the expression is weak and heterogeneous. A small subset of cases demonstrates CD15 staining, which may create a diagnostic challenge with CHL. In contrast to DLBCL, the majority of PMBL cases express CD23, MAL, PDL1, and PDL2 [8, 9]. MAL is normally expressed by a subset of normal thymic B-cells and suggests a possible cell-of-origin of PMBL [8]. EBV is almost always absent [10]. With advances in gene expression technology, a 58-gene expression assay (Lymph3Cx), applied to formalin-fixed paraffin-embedded tissue samples, has been shown to be robust, accurate and reproducible in the classification of PMBL and DLBCL, potentially supplementing diagnostic tools that currently rely on clinic-­ pathologic consensus [11].

Genetic Profile Constitutive activation of NFκB and JAK-STAT pathways are characteristic of PMBL (Fig. 13.1, Table 13.1). A third important feature is the immune privilege phenotype of the tumor cells—conferred by a number of genetic alterations—which allows evasion of immune surveillance and highlights the importance of the tumor microenvironment in disease pathogenesis [12]. MYC, BCL2, and BCL6 rearrangements are rare, unlike systemic DLBCL [13].

RIP

CD79A

MYD88 IRAK4

TNFAIP3

SOCS1

TRAF6

NEMO

NFKBIE

…

Cytoplasm plasm plas m

…

IKKa IKKb

pSTAT6

Extracellular space

TLR

TRAF1

CCL17

PTPN1

BCR

IL6/IL10

CD79B

NFkB pathway TNF receptor

CD2

JAK2 STAT6

CD58

TCR

TCR MHC II

IL4R

B2M MHC I

PD1

Effector T cell

PD-L1

JAK/STAT pathway

CCR4

Treg

CARD11 BCL10 MALT1

…

NFKBIZ pSTAT6

PD-L1/2

CIITA

MHC II

IkBa Nucleus eus

NFKB1 REL

PMBL

PTL

Fig. 13.1  Major pathways involved in pathogenesis on extranodal B-cell lymphomas

NSL PCNSL

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Table 13.1  Summary of main molecular alterations and pathways involved in primary mediastinal B-cell lymphoma (PMBL), primary CNS diffuse large B-cell lymphoma (PCNSL), and primary testicular large B-cell lymphoma (PTL) PMBL NFKB pathway Activated REL, TRAF1, TRAF3, NFKBIE, TNFAIP3 Toll-like receptor pathway B-cell receptor Activated pathway BCL10, MALT1 JAK-STAT pathway Cell cycle

Immune evasion

PCNSL Activated TNFAIP3

PTL Activated NFKBIZ, TANK, TRAF1

Activated MYD88 L265P

Activated MYD88 L265P

Activated CD79B, CARD11, MALT1, BCL10

Activated CD79B

Dysregulated CDKN2A (biallelic)

Dysregulated CDKN2A (biallelic), MDM2, CCND1, BCL2 Dysregulated CIITA, MHC I/II, B2M, PD-L1/2

Activated IL4-R, JAK2, STAT6, SOCS1, PTPN1

Dysregulated Dysregulated PD-L1/2, CIITA, MHC I/ MHC I/II, PD-L1/L2 II, CD58, B2M

Aberrant activation of the NFκB pathway leads to downstream activation of anti-­ apoptotic genes (such as BCL2 family members) and activation of caspases and transcription regulators cyclins D1 and D2, resulting in uncontrolled proliferation [14]. REL amplification, with concomitant nuclear REL expression, is a common mechanism of abnormal NFκB pathway activation in PMBL and is observed in up to 75% of cases [12, 15–17]. REL is located at chromosome 2p16.1 and encodes a proto-oncogene transcription factor that plays a role in the survival and proliferation of B-cells. Alterations in TNFAIP3 encoding protein A20—a ubiquitin-modifying enzyme that inhibits NFκB signaling downstream of the TNF receptor—is also a common mechanism promoting NFκB signaling seen in 59% of PMBL cases. TNFAIP3 alterations consist predominantly of mutations (41%) followed by copy number loss (24%), with 6% showing biallelic gene disruption [17, 18]. IκBε is another negative regulator of the NFκB pathway that was recently found to be altered in PMBL. In the resting state, NFκB proteins are rendered inactive by binding to inhibitors of NFκB (IκBs), which sequester them in the cytoplasm. Aberrations in IkBε, encoded by NFKBIE, are seen in 22–27% of PMBL and CHL but rarely in other B-cell malignancies [12, 17]. The loss of NFKBIE contributes to constitutive NFκB pathway signaling and is associated with treatment failure and unfavorable outcomes in PMBL [19, 20]. Amplifications of BCL10 (1p.22) and MALT1 (18q21)—NFκB pathway regulators that form multimeric signaling complex (BCM) with CARD11 and mediate pathway activation—were reported in 9% and 24% of cases, respectively, using array-based comparative genomic hybridization [21] (Fig. 13.1).

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The JAK-STAT pathway is critical for cell growth, survival, and differentiation of hematopoietic cells as well as modulation of the immune system. STAT6 is the STAT family transcription factor that is activated by phosphorylation, which is initiated by interleukin-4 (IL4) or interleukin-3 (IL3) cytokine receptor binding and plays a prominent role in the function of the immune system [22]. Recurrent activating p.D419 hotspot variant in STAT6 DNA binding domain is seen in 36–43% of PMBL cases and results in increased expression of STAT6 target genes [12, 17, 23]. Gain-of-function mutations in upstream interleukin-4 receptor (IL4R) were observed in 24% of PMBL cases and were shown to result in ligand-independent phosphorylation of STAT5 and STAT6 [24]. Constitutive activation of the JAK-­ STAT pathway results in up-regulation of CD23 and CCL17. When secreted, CCL17 interacts with the CCR4 receptor on regulatory T-cells in the tumor microenvironment and results in the recruitment of these cells in the tumor milieu, thus allowing PMBL to acquire an immune escape phenotype. Particularly noteworthy is the high expression of CCL17 in Reed-Sternberg cells in CHL. Moreover, CCL17 is detectable in the patient’s serum and has been used as a biomarker for monitoring disease progression and response to therapy [25, 26]. However, no relationship between CCL17 levels and survival was found in PMBL. Loss-of-function mutations involving negative regulators of the JAK-STAT pathway, such as suppressors of cytokine signaling (SOCS) and tyrosine phosphatases (PTPs), have been observed in PMBL and CHL and lead to activation of the pathway. Whole exome sequencing (WES) studies have identified SOCS1 as one of the most commonly mutated genes, with mutations seen in 65% of cases [12, 17], with bi-allelic alterations of SOCS1 locus reported [27, 28]. Gunawardana et al. demonstrated that PTPN1 tyrosine phosphatase mutations are seen in 22% of PMBLs and 33% of tumor cell lines [29]. WES studies of large PMBL cohorts have confirmed the presence of PTPN1 loss-of-function mutations [12, 17]. JAK2 locus amplification at 9p24.1 is the most common copy number variation seen in PMBL (approximately 70% of cases) and is also characteristic of CHL [17, 30]. CD274 (PD-L1) and PDCD1LG2 (PD-L2) are located on 9p24.1 in close proximity to JAK2, and copy number gains seen in this region result in the amplification of both genes in a large percentage of PMBL. Moreover, JAK2 amplification not only increases JAK2 transcripts and signaling but also amplifies PD-L1 expression through the regulatory loop, thus providing the link between JAK-STAT signaling and immune evasion [30]. The interaction of PD-L1/2 with PD-1 receptors present on T-cells induces peripheral tolerance by modulating T-cell function and creating an immune-suppressive environment favorable for tumor cells. Studies using FISH and break-apart probes demonstrated that PD-L1 is specifically rearranged in 20% of PMBL cases, with 14 unique PD-L1 and 19 PD-L2 rearrangements described. Both amplifications and translocations resulted in increased transcript and protein levels [31, 32]. Peptide-MHC complex (pMHC) expressed on tumor cells allows their recognition, and subsequent destruction, by T-cells. The loss or down-regulation of MHC

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protein on the cell surface is, therefore, an important mechanism of immune evasion that has been reported in a number of B-cell lymphomas. Copy number loss of 6q21.32 locus, where genes encoding MHC-I/II are found, is a characteristic feature of PMBL [33–35] identified in 32% of cases [17]. Roberts et al. showed that a complete loss of HLA-DR surface expression in PMBL is associated with inferior survival [34]. Over 70% of PMBL cases harbor aberrations of the master regulator of MHC class II, CIITA, located on chromosome 16. These aberrations in the form of mutations, deletions or translocations, lead to loss of MHC II surface expression [36, 37]. Intriguingly, CIITA gene fusions were found to up-regulate PD-L1 and PD-L2 [32]. Interaction of CD58 ligand, expressed on the surface of B-cells, with CD2, an immunoglobulin family receptor on T-cells, brings these cells in close proximity to each other and results in stabilization of the complex allowing extended interaction between pMHC and T-cell receptor, and subsequent T-cell activation. Studies have shown that in  vitro loss of CD58 or CD2 decreases T-cell activity [38]. PMBL exhibits recurrent genomic alterations of CD58, including mono- and bi-allelic microdeletions, resulting in the loss of expression that is described as one of the driver events [12, 39]. In other B-cell lymphomas, including DLBCL and CHL, mutations in CD58 frequently occur with B2M mutations, suggesting synergistic mechanisms of immune evasion. B2M encodes beta-microglobulin—an integral part of MHC I molecules—and is commonly altered in PMBL, with 30% of cases showing mutations, 27% focal copy loss, and 6% biallelic loss [17]. A study by Mottok et al. integrating WES and GEP methodologies found recurrent mutations in interferon response genes (IRF) and their downstream targets in 52% of their cohort [12]. The hotspot mutation p.C99R was seen in >50% of IRF4 mutated cases. The genes mutated in at least 10% of the samples included IRF1, IRF4, IRF8, and IRF2BP2. Additional significantly mutated genes described in large WES studies were PAX5 (11%) and IKZF3 (11%), both B-cell transcription factors with important roles in B-cell differentiation. Recurrent mutations in TP53 were described in 22% of PMBL, a frequency comparable to nodal DLBCL. However, in contrast to DLBCL, most TP53 mutations in PMBL were found to be monoallelic. Mutations described in germinal center B-cell subtype (GCB) of DLBCLs were also seen in PMBL, including GNA13 (35%) and EZH2 (14%). EZH2 mutations were shown to contribute to MHCI and II expression loss in DLBCL lymphoma [40]. Mutational signature analysis performed in large WES studies identified patterns associated with cellular aging, defective DNA mismatch repair and AID/APOBEC activity. The presence of an ‘aging’ signature—characterized by spontaneous deamination of CpGs—in a neoplasm typically diagnosed in younger populations may be attributed to the high rate of cell division and has been reported in other cancers including pediatric tumors. The frequency of microsatellite instability (MSI)hypermutated tumors was similar in PMBL and CHL and significantly higher than in nodal DLBCL. The discovery of microsatellite unstable cases, as well as cases with high tumor mutational burden, further supports the use of checkpoint inhibitors in PMBL [12, 17].

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Prognosis and Therapy Historically, PMBL has shown a relatively favorable prognosis, with a 5-year survival rate of 64% compared to 59% and 30% for GCB and activated B-cells (ABC) DLBCL, respectively [4]. First-line chemotherapy regimens currently in use include R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) and dose-adjusted R-EPOCH (rituximab, etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin) with or without consolidation radiotherapy (RT). With the addition of rituximab to the treatment regimens, the 5-year overall survival (OS) is 79–97%—superior to de novo DLBCL [41, 42]. Clinical trials are investigating the use of PET/CT to identify patients who may or may not require RT at the end of induction [43]. Currently, there is no consensus regarding the optimal therapy for patients with relapsed or refractory PMBL. Disease management involves salvage regimens, followed by an autologous stem cell transplantation (ASCT), as is generally accepted for patients with DLBCL.  However, conventional salvage immunochemotherapy regimens deliver unsatisfactory results in PMBL, so the identification of disease-specific targetable molecular lesions is a priority. Current FDA-approved targeted therapies include immune checkpoint inhibitors [44] and CAR-T therapy for relapsed or refractory PMBL. Other targeted therapies being investigated in clinical trials include JAK2 inhibitors [45], anti-CD30 therapy [46], and BTK inhibitors [47].

Primary CNS Lymphoma Primary CNS diffuse large B-cell lymphoma (PCNSL) is rare, accounting for approximately 2% of all CNS neoplasms [48]. It can occur in immunocompetent and immunodeficient patients, but in the latter group PCNSL is categorized under immunodeficiency-associated lymphomas [3]. The incidence of PCNSL peaked in the mid-1990s and declined in younger populations 65 years) unrelated to HIV infection [49, 50]. The discussion in this section will focus primarily on PCNSL not associated with known immunodeficiency.

Clinical Features The mean age of PCNSL diagnosis is >60 years with a slight predominance of male patients [51, 52]. It may involve the brain parenchyma, spinal cord, eyes, cranial nerves and/or leptomeninges, while neoplasms originating from the dura, intravascular large B-cell lymphoma, and lymphoma with systemic disease, are excluded

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from the category of PCNSL [3]. The majority of immunocompetent patients present with solitary intracranial lesion at diagnosis, usually in the supratentorial region with predilection for periventricular white matter [48], while immunodeficient patients often show multifocal lesions [53]. Disease restricted to the eyes, spinal cord, or cerebrospinal fluid (CSF) is rare. Primary large B-cell lymphoma of the vitreoretinal is categorized under the new entity of primary large B-cell lymphoma of immune-­privileged sites [2] Symptoms of PCNSL vary according to the site of involvement and may include cognitive or behavioral changes, focal neurologic deficits, and symptoms of increased intracranial pressure, such as headache, nausea and vomiting. Seizures are uncommon. Ocular symptoms may include floaters or blurred vision [48, 54]. Contrast-enhanced MRI exhibits homogeneous contrast enhancement with well-defined borders [55]. In the case of male patients, a testicular examination and ultrasound are helpful to exclude primary testicular diffuse large B-cell lymphoma (PTL), which has a high frequency of CNS involvement [56]. Systemic disease with secondary CNS involvement must also be excluded.

Microscopic and Immunophenotypic Features The gold standard of diagnosis is a brain biopsy, which should be obtained prior to administration of corticosteroids, as it can distort or obscure important histomorphologic features [48]. Morphologically, the majority of cases show centroblastic features [51, 52] and cells infiltrate in a diffuse or perivascular pattern [51]. Immunophenotypically, the neoplastic cells are positive for B-cell antigens such as CD19, CD20, PAX5, CD79a, and CD22, and negative for plasma cell markers CD38 and CD138. Additionally, cells express surface IgM and IgD, but not IgG (3, 57). CD10 expression is rare (approximately 2% of cases) while the vast majority of cases are MUM1-positive (approximately 70–90% of cases), and a substantial number are BCL6-positive (approximately 50–60% of cases), hence most cases are classified as non-GC type based on Hans algorithm [51, 52]. The proliferation rate is typically high, exceeding 50% [51]. Stains for evidence of EBV should be negative, while positivity would suggest an underlying immunodeficient state [57]. MYC is overexpressed in the majority of cases (approximately 70–80%), as is BCL2 (approximately 70%), thus double-positive cases are frequent (approximately 60–80%). Increased MYC expression is unrelated to MYC rearrangement but may be a result of MYC amplification, mutation and/or alternate post-translational mechanisms [51, 58, 59]. PDL1 expression by tumor cells is observed in 30% of cases [60].

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Genetic Profile Based on GEP studies, PCNSL corresponds to late germinal center B cells [61], which is consistent with the presence of ongoing somatic hypermutation (SHM) [62] and the typical immunoprofile of CD10-/BCL6+/MUM1+/IgM+/IgD+/IgG[61]. PCNSL demonstrates active and aberrant SHM and harbors an extremely high load of somatic mutations suggestive of prolonged or ongoing germinal center reaction. In the majority of cases, SHM aberrantly targets not only IgH but also a number of the proto-oncogenes including PIM1 and c-MYC [62]. Missense mutations in PIM1, which encodes a protein important in cell proliferation and survival, are frequent in PCNSL (71–75% of cases) [33, 60]. When compared to nodal DLBCL, both PCNSL and secondary CNS lymphoma (systemic DLBCL involving the CNS) exhibit a higher expression of PIM1 [63], suggesting the influence of the microenvironment in tumors involving the CNS. Involvement of the MYC pathway in the pathogenesis of PCNSL is supported not only by the higher expression of c-MYC, which encodes a transcription factor that mediates cell proliferation and apoptosis, and MINA53, a MYC target gene [63], but also up-regulation of micro-RNAs associated with this pathway (miR-17-5p, miR-20a, and miR-9) [64]. Other genes targeted by SHM are PAX5, which encodes a transcription factor required for B-cell lineage commitment, differentiation and isotype switching; Rho/TTF, which encodes a GTP-binding protein of the RAS superfamily involved in signal transduction; and CD95, a tumor suppressor gene that is highly expressed in normal germinal centers and regulates cell survival and apoptosis [62]. Activation of the NFκB pathway is central to the pathogenesis of PCNSL, similar to ABC type DLBCL, and is mediated by toll-like receptor (TLR) and B-cell receptor (BCR) pathway signaling. MYD88 is an adapter protein that activates the TLR pathway, and activating MYD88 L265P mutation is a frequent finding in PCNSL, with a reported prevalence ranging from 55% up to 94% [33, 54, 60]. In the BCR pathway, CD79B mutation, primarily involving Y196, is frequently observed, reported in 38–83% of cases [33, 60]. Interestingly, the majority of CD79b mutations were found in cases harboring the MYD88 L265P mutation. Concurrent MYD88 and CD79B mutations are more frequent in PCNSL than in ABC DLBCL and are a distinguishing feature of this entity [33, 60]. Mutations have not been reported in CD79A, which encodes the partner heterodimer subunit with CD79B in the BCR complex [54]. CARD11 is a component of the BCR pathway that forms a complex with MALT1 and BCL10 (BCM complex) and promotes NFκB activation. Mutations in CARD11 are seen in 16–29% of cases [33, 60] and often observed in the context of MYD88 L265P mutation, again highlighting the synergistic role of the TLR and BCR pathways in NFκB activation [33, 65]. Data suggest putative mutational hotspot motifs in CARD11 [65, 66]. Cases harboring mutations in all three genes, MYD88, CD79B and CARD11, have also been identified [33]. Several studies investigating copy number alterations in PCNSL have shown complex genomes, with high copy number alterations and recurrent losses affecting 9p21 (CDKN2A locus), 6p21 (MHC locus), and 6q (multiple affected regions) [33, 67]. Gains were also noted commonly involving 12q and 18q [33, 67–69]. Loss of 9p21, involving deletion of tumor suppressor CDKN2A (also known as p16), is a

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frequent finding in PCNSL (50–71%), with a majority demonstrating bi-allelic deletion [33, 60, 70]. CpG island methylation is an alternative mechanism of transcriptionally silencing and abrogating CDKN2A function, as described by Cobber et al. This gene encodes several proteins including p14 (ARF), which inhibits cell cycle progression from G1 to S phase by binding to MDM2 and preventing degradation of p53 [71]. Therefore, the absence of tumor suppressor CDKN2A promotes deregulated cell proliferation of tumor cells. Unlike systemic DLBCL, TP53 mutations are rarely seen in PCNSL [33, 70]. Loss of 6p21, involving the HLA (MHC) locus, is frequent in PCNSL, identified in 79% of cases [72]. These deletions are important mechanisms for loss of MHC expression, seen in approximately half of PCNSL, as demonstrated by immunohistochemical studies. This is in contrast to nodal DLBCL, where 5% of cases show loss of MHC expression [73]. Loss of MHC is a mechanism for tumor cells to evade immune surveillance and promote survival and growth. Deletion involving 6q is broad, but primarily encompasses 6q21–23. This is identified in approximately 60% of cases [33, 74], and candidate genes in this region include PTPRK, PRDM1/BLIMP1, and TNFAIP3. PTPRK is a protein tyrosine phosphatase that regulates a wide variety of cellular processes, such as growth and differentiation. In the study by Nakamura et  al. [74], PCNSL cases showing del 6q22–23 were associated with loss of PTPRK protein expression. Tumor suppressor gene PRDM1/BLIMP1, located on 6q21-q22.1, encodes a transcriptional repressor required for the terminal differentiation of germinal center B cells to plasma cells. Inactivation of PRDM1/BLIMP1, by deletions and mutations, has been described in systemic DLBCL, mostly restricted to ABC-type [75]. In PCNSL, deleterious PRDM1 mutations were identified in approximately 20% of cases and were associated with the absence of protein expression [76, 77]. Homozygous deletions of PRDM1 have been reported in PCNSL, seen in 2 of 29 PCNSL cases in one study [72]. Up-regulation of micro-RNAs miR-9 and miR30b/c, involved in blocking terminal B-cell differentiation, has also been identified in PCNSL [64]. PCNSL also demonstrates impaired class switch recombination secondary to deletions of the switch μ region [78]. These features indicate impaired differentiation and are consistent with the late germinal center molecular and immunophenotypic profile, including fixed IgM+/IgD+, as described above. Tumor suppressor TNFAIP3, located at 6q23, encodes a ubiquitin-editing enzyme called A20 protein, which inhibits NFκB activity, and therefore loss of this protein enhances NFκB activity and promotes cell proliferation. Inactivating mutations in TNFAIP3 are frequent in nodal DLBCL, but rare in PCNSL [66]. Copy number gains frequently involve 12q (41%) and 18q21 (36%) [68, 69, 79]. 18q21 contains oncogenes BCL2 (an NFκB target gene) and MALT1 (part of the BCM complex that activates NFκB pathway). Transcriptional profiling of PCNSL identified elevated levels of MALT1, CARD11, and BCL2 but lower expression of BCL10 [80–82]. There have been conflicting findings of copy number gains involving PDL-1/PDL-2 loci at 9p24. Chapuy et al. identified 9p24 amplification in 52%

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of PCNSL cases [33]; however, other recent studies have failed to identify this particular amplification [60, 83]. Nayyar et al. described PDL1 expression by tumor cells in 30% of PCNSL cases, but these cases lacked PDL1 amplification, thus suggesting an alternate mechanism [60]. Notably, PDL-1/PDL-2 translocations are uncommon, observed in only 6% of cases in the study by Chapuy et al. [33]. BCL6 rearrangements are seen in about 20% of cases, with IGH as the partner gene in a subset of cases [79, 84]. BCL2 translocations are rare, seen in  60 years, performance status >1, elevated LDH levels, elevated CSF protein concentration, and the involvement of deep regions of the brain [96]. Del(6)(q22) has been associated with shorter survival [69, 84]. ETV6-­ IGH rearrangement was recently found to show improved OS compared to wildtype ETV6 [86]. The prognostic implications of BCL6 remain unclear due to conflicting results in several studies [97, 98]. Expression of BCL2 has been shown to lack prognostic impact, unlike in systemic DLBCL [52, 59, 99]. The significance of MYC and BCL2 co-expression (also known as “double-expressers”), known to have adverse prognosis in systemic DLBCL, also remains unclear [51, 59]. CD79B mutations were associated with improved PFS and OS [60]. High-dose methotrexate, a key component of PCNSL therapy, is recommended for patients with good performance status in the induction phase, in combination with chemotherapy. This combined therapy is more effective than single-agent methotrexate, but the latter may be used for those with decreased performance status and those unable to tolerate toxicities associated with chemotherapy. The addition of rituximab, which has improved outcomes in systemic DLBCL, remains controversial in PCNSL.  Consolidation therapy may include reduced-dose

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whole-­ brain radiation, high-dose chemotherapy with autologous hematopoietic stem cell transplant, and non-myeloablative chemotherapy [100]. Molecular changes involved in PCNSL pathogenesis are potential targets for therapy and many are currently under investigation. Bruton’s tyrosine kinase (BTK) inhibitor, ibrutinib, targets the BCR pathway, and recent studies have shown clinical response of PCNSL to a combination treatment of BTK inhibitor and chemotherapy [101, 102]. Immunomodulatory drugs, such as lenalidomide, target the NFκB pathway and PI3K/AKT pathway, and have been shown to cross the blood-brain-barrier. In a recent study, combination lenalidomide and rituximab was found to have a positive response in relapsed / refractory PCNSL [103]. Treatment with checkpoint inhibitors are also currently being explored, given PDL1 expression in a subset of cases [104]. Chimeric-antigen-receptor (CAR) T-cell therapy, shown to traverse the blood-brain-barrier, has been found to be effective in the few cases of relapsed/ refractory PCNSL [105, 106].

Primary Testicular Large B-Cell Lymphoma Primary testicular large B-cell lymphoma (PTL) is rare and amounts to approximately 1% of all non-Hodgkin lymphoma in the United States. Most patients are greater than 60 years of age at the time of diagnosis [56, 107, 108]. HIV-positive patients are generally younger with dismal prognosis (median OS of 50% PTL, and correspond to an increased expression of PDL1 and PDL2 proteins in neoplastic cells. Structural rearrangements of PDL1/2 loci, with the resulting overexpression of corresponding proteins, are less frequent, reported in 10% of PTLs [31, 32, 120]. PDL1 translocations involving IGHG4, PTPN1, and TBL1XR1 partner genes have been described, as well as intra-chromosomal events that involve 3′ untranslated region (UTR). Deletion of the PDL1 3′- UTR results in an inhibition of microRNA binding, PDL1 transcript stabilization, increase in transcript half-life and subsequent protein expression. Furthermore, studies demonstrated that disruption of the PDL1 3′-UTR in mice enabled immune evasion of tumor cells with elevated PDL1 expression in vivo [121] (Table 13.1).

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Prognosis and Therapy The majority of patients achieve complete remission following systemic chemotherapy (approximately 80–90% of patients), which consists of R-CHOP. However, relapse is frequent and survival after relapse is extremely poor [56]. Relapse most commonly involves the contralateral testis and CNS, but other sites may also be involved, such skin/soft tissues, Waldeyer’s ring, pleura, adrenal glands, and bone marrow [56, 108, 122]. Given the increased risk of relapse in the contralateral testis and CNS, prophylactic scrotal radiation and intrathecal methotrexate are recommended after the completion of chemotherapy. Ibrutinib, lenalidomide, and checkpoint inhibitors are potential therapeutic agents capable of crossing the blood-brain barrier, thus providing additional CNS prophylaxis in theory. Studies evaluating the efficacy of these therapeutic agents and other potential targeted therapies in PTL are still ongoing [123].

Conclusion PMBL, PCNSL, and PTL are unique subtypes of DLBCL, with clinical and biologic features distinct from nodal DLBCL that require strategic management and therapy. PCNSL and PTL are aggressive lymphomas occurring in older patients in immune-privileged sites with high rates of relapse. Both show overlapping molecular features, specifically near-uniform activation of TLR, BCR, and NFκB pathways, which are similar to DLBCL with C5 genetic signature. Given these similarities, PCNSL and PTL are grouped together in the fifth edition of the WHO under the new category of primary large B-cell lymphoma of immune-privileged sites. PMBL affects younger patients with a preponderance of female subjects and shares molecular genetic features with CHL: constitutive activation of NFκB, JAK-­ STAT signaling, and PD-1 immune evasion. GEP has demonstrated that PMBL is more akin to CHL than DLBCL, NOS. Molecular and genetic characterizations of these entities have shown to be not only powerful in clarifying disease pathogenesis but also impactful in diagnostics, prognostication, and treatment.

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71. Pomerantz J, Schreiber-Agus N, Liégeois NJ, Silverman A, Alland L, Chin L, et al. The Ink4a tumor suppressor gene product, p19Arf, interacts with MDM2 and neutralizes MDM2’s inhibition of p53. Cell. 1998;92(6):713–23. 72. Gonzalez-Aguilar A, Idbaih A, Boisselier B, Habbita N, Rossetto M, Laurenge A, et  al. Recurrent mutations of MYD88 and TBL1XR1 in primary central nervous system lymphomas. Clin Cancer Res. 2012;18(19):5203–11. 73. Riemersma SA, Jordanova ES, Schop RFJ, Philippo K, Looijenga LHJ, Schuuring E, et  al. Extensive genetic alterations of the HLA region, including homozygous deletions of HLA class II genes in B-cell lymphomas arising in immune-privileged sites. Blood. 2000;96(10):3569–77. 74. Nakamura M, Kishi M, Sakaki T, Hashimoto H, Nakase H, Shimada K, et al. Novel tumor suppressor loci on 6q22-23  in primary central nervous system lymphomas. Cancer Res. 2003;63(4):737–41. 75. Pasqualucci L, Compagno M, Houldsworth J, Monti S, Grunn A, Nandula SV, et  al. Inactivation of the PRDM1/BLIMP1 gene in diffuse large B cell lymphoma. J Exp Med. 2006;203(2):311–7. 76. Nakamura T, Tateishi K, Niwa T, Matsushita Y, Tamura K, Kinoshita M, et  al. Recurrent mutations of CD79B and MYD88 are the hallmark of primary central nervous system lymphomas. Neuropathol Appl Neurobiol. 2016;42(3):279–90. 77. Courts C, Montesinos-Rongen M, Brunn A, Bug S, Siemer D, Hans V, et al. Recurrent inactivation of the PRDM1 gene in primary central nervous system lymphoma. J Neuropathol Exp Neurol. 2008;67(7):720–7. 78. Montesinos-Rongen M, Schmitz R, Courts C, Stenzel W, Bechtel D, Niedobitek G, et  al. Absence of immunoglobulin class switch in primary lymphomas of the central nervous system. Am J Pathol. 2005;166(6):1773–9. 79. Montesinos-Rongen M, Zühlke-Jenisch R, Gesk S, Martín-Subero JI, Schaller C, Van Roost D, et al. Interphase cytogenetic analysis of lymphoma-associated chromosomal breakpoints in primary diffuse large B-cell lymphomas of the central nervous system. J Neuropathol Exp Neurol. 2002;61(10):926–33. 80. Courts C, Montesinos-Rongen M, Martin-Subero JI, Brunn A, Siemer D, Zühlke-Jenisch R, et al. Transcriptional profiling of the nuclear factor-κB pathway identifies a subgroup of primary lymphoma of the central nervous system with low BCL10 expression. J Neuropathol Exp Neurol. 2007;66(3):230–7. 81. Deckert M, Montesinos-Rongen M, Brunn A, Siebert R.  Systems biology of primary CNS lymphoma: from genetic aberrations to modeling in mice. Acta Neuropathol. 2014;127(2):175–88. 82. Montesinos-Rongen M, Siebert R, Deckert M.  Primary lymphoma of the central nervous system: just DLBCL or not? Blood. 2009;113(1):7–10. 83. Braggio E, Wier SV, Ojha J, McPhail E, Asmann YW, Egan J, et al. Genome-wide analysis uncovers novel recurrent alterations in primary central nervous system lymphomas. Clin Cancer Res. 2015;21(17):3986–94. 84. Cady FM, O’Neill BP, Law ME, Decker PA, Kurtz DM, Giannini C, et al. Del(6)(q22) and BCL6 rearrangements in primary CNS lymphoma are indicators of an aggressive clinical course. J Clin Oncol. 2008;26(29):4814–9. 85. Villa D, Tan KL, Steidl C, Ben-Neriah S, Al Moosawi M, Shenkier TN, et al. Molecular features of a large cohort of primary central nervous system lymphoma using tissue microarray. Blood Adv. 2019;3(23):3953–61. 86. Bruno A, Labreche K, Daniau M, Boisselier B, Gauchotte G, Royer-Perron L, et  al. Identification of novel recurrent ETV6-IgH fusions in primary central nervous system lymphoma. Neuro-Oncology. 2018;20(8):1092–100. 87. Montesinos-Rongen M, Purschke FG, Brunn A, May C, Nordhoff E, Marcus K, et  al. Primary central nervous system (CNS) lymphoma B cell receptors recognize CNS proteins. J Immunol. 2015;195(3):1312–9.

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88. Thurner L, Preuss KD, Bewarder M, Kemele M, Fadle N, Regitz E, et  al. Hyper-N-­ glycosylated SAMD14 and neurabin-I as driver autoantigens of primary central nervous system lymphoma. Blood. 2018;132(26):2744–53. 89. Rubenstein JL, Wong VS, Kadoch C, Gao HX, Barajas R, Chen L, et al. CXCL13 plus interleukin 10 is highly specific for the diagnosis of CNS lymphoma. Blood. 2013;121(23):4740–8. 90. Carey AJ, Tan CK, Ulett GC.  Infection-induced IL-10 and JAK-­ STAT. JAKSTAT. 2012;1(3):159–67. 91. Mocellin S, Marincola FM, Young HA. Interleukin-10 and the immune response against cancer: a counterpoint. J Leukoc Biol. 2005;78(5):1043–51. 92. Sasayama T, Nakamizo S, Nishihara M, Kawamura A, Tanaka H, Mizukawa K, et  al. Cerebrospinal fluid interleukin-10 is a potentially useful biomarker in immunocompetent primary central nervous system lymphoma (PCNSL). Neuro-Oncology. 2012;14(3):368–80. 93. Ngo VN, Young RM, Schmitz R, Jhavar S, Xiao W, Lim KH, et  al. Oncogenically active MYD88 mutations in human lymphoma. Nature. 2011;470(7332):115–9. 94. Chapuy B, Stewart C, Dunford AJ, Kim J, Kamburov A, Redd RA, et al. Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes. Nat Med. 2018;24(5):679–90. 95. Panageas KS, Elkin EB, DeAngelis LM, Ben-Porat L, Abrey LE. Trends in survival from primary central nervous system lymphoma, 1975–1999. Cancer. 2005;104(11):2466–72. 96. Ferreri AJM, Blay JY, Reni M, Pasini F, Spina M, Ambrosetti A, et al. Prognostic scoring system for primary CNS lymphomas: the international Extranodal lymphoma study group experience. J Clin Oncol. 2003;21(2):266–72. 97. Momota H, Narita Y, Maeshima AM, Miyakita Y, Shinomiya A, Maruyama T, et al. Prognostic value of immunohistochemical profile and response to high-dose methotrexate therapy in primary CNS lymphoma. J Neuro-Oncol. 2010;98(3):341–8. 98. Preusser M, Woehrer A, Koperek O, Rottenfusser A, Dieckmann K, Gatterbauer B, et  al. Primary central nervous system lymphoma: a clinicopathological study of 75 cases. Pathology. 2010;42(6):547–52. 99. Chang CC, Kampalath B, Schultz C, Bunyi-Teopengco E, Logan B, Eshoa C, et al. Expression of p53, c-Myc, or Bcl-6 suggests a poor prognosis in primary central nervous system diffuse large B-cell lymphoma among immunocompetent individuals. Arch Pathol Lab Med. 2003;127(2):208–12. 100. Cai Q, Fang Y, Young KH. Primary central nervous system lymphoma: molecular pathogenesis and advances in treatment. Transl Oncol. 2019;12(3):523–38. 101. Lionakis MS, Dunleavy K, Roschewski M, Widemann BC, Butman JA, Schmitz R, et  al. Inhibition of B cell receptor signaling by Ibrutinib in primary CNS lymphoma. Cancer Cell. 2017;31(6):833–843.e5. 102. Grommes C, Pastore A, Palaskas N, Tang SS, Campos C, Schartz D, et  al. Ibrutinib unmasks critical role of Bruton tyrosine kinase in primary CNS lymphoma. Cancer Discov. 2017;7(9):1018–29. 103. Ghesquieres H, Chevrier M, Laadhari M, Chinot O, Choquet S, Moluçon-Chabrot C, et al. Lenalidomide in combination with intravenous rituximab (REVRI) in relapsed/refractory primary CNS lymphoma or primary intraocular lymphoma: a multicenter prospective ‘proof of concept’ phase II study of the French Oculo-cerebral lymphoma (LOC) network and the lymphoma study association (LYSA). Ann Oncol. 2019;30(4):621–8. 104. Nayak L, Iwamoto FM, LaCasce A, Mukundan S, Roemer MGM, Chapuy B, et  al. PD-1 blockade with nivolumab in relapsed/refractory primary central nervous system and testicular lymphoma. Blood. 2017;129(23):3071–3. 105. Tu S, Zhou X, Guo Z, Huang R, Yue C, He Y, et al. CD19 and CD70 dual-target chimeric antigen receptor T-cell therapy for the treatment of relapsed and refractory primary central nervous system diffuse large B-cell lymphoma. Front Oncol. 2019;9:1350. 106. Abramson JS, McGree B, Noyes S, Plummer S, Wong C, Chen YB, et al. Anti-CD19 CAR T cells in CNS diffuse large-B-cell lymphoma. N Engl J Med. 2017;377(8):783–4.

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Chapter 14

Primary Cutaneous Diffuse Large B-Cell Lymphoma, Leg Type Mushal Noor and Gabriel C. Caponetti

Introduction Primary cutaneous lymphomas are lymphomas that are initially present in the skin, most commonly without extra-cutaneous involvement at the time of diagnosis. They include cutaneous T-cell lymphomas (CTCLs) and cutaneous B-cell lymphomas (CBCLs). CTCLs comprise the majority (75–80%) of all primary cutaneous lymphomas in the United States and the Western world, with CBCLs representing the remainder (20–25%) of cases [1]. Primary cutaneous lymphomas usually display distinct clinicopathologic features and prognoses in comparison to morphologically similar primary extracutaneous lymphomas with secondary skin involvement; therefore, it is essential to identify their primary cutaneous origin. According to the fifth edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours, the International Consensus Classification of Mature Lymphoid Neoplasms, and the 2018 update of the WHO-­ European Organisation for Research and Treatment of Cancer, the primary CBCLs include primary cutaneous marginal zone lymphoma (PCMZL), primary cutaneous follicle center lymphoma (PCFCL), PCDLBL-LT, intravascular large B-cell lymphoma (IVLBCL), and EBV+ mucocutaneous ulcer [1–3].

M. Noor · G. C. Caponetti (*) Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_14

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Epidemiology PCDLBL-LT is an aggressive cutaneous lymphoma that comprises approximately 4% of all primary cutaneous lymphomas and 20% of CBCLs [1]. It is characterized by initial presentation in the skin, most commonly in the legs of females (M:F ratio 1:2–4) during the seventh and eighth decades of life [4–6].

Clinical Features PCDLBL-LT presents as red to plum-colored, rapidly growing cutaneous nodules or tumors. The lesions may be solitary or multiple and may be present on one or both legs. Approximately 10–15% of cases can present at a cutaneous location other than the leg [7, 8]. Disease progression may involve dissemination to extracutaneous sites including lymph nodes, bone marrow, viscera, and central nervous system, which can be observed in >40% of cases [6, 9]. Location on the leg and the presence of multiple skin lesions are negative prognostic factors [6]. The 5-year disease-­ specific survival rates for PCDLBL-LT have been reported to range from 41% to 62%, in contrast to the indolent CBCLs (primary cutaneous marginal zone lymphoma and primary cutaneous follicle center lymphoma), which have 5-year disease-­specific survival rates of 95–99% [1, 6, 8, 10]. Consensus guidelines recommend cases of PCDLBL-LT be treated similarly to a systemic diffuse large B-cell lymphoma (DLBCL) with multiagent immunochemotherapy such as R-CHOP (rituximab, cyclophosphamide, doxorubicin/adriamycin, oncovin/vincristine, and prednisone) [11].

Histology and Immunophenotype Histologically, PCDLBL-LT shows a diffuse dermal infiltrate of large lymphoid cells with centroblastic and/or immunoblastic appearance with frequent subcutaneous involvement but without epidermotropism (Figs.  14.1 and 14.2). Abundant mitoses and a few, often perivascular, reactive T cells can also be seen. Immunophenotypically, the lymphoma cells express monotypic light chains, B-cell markers such as CD20, CD19, CD79a, and PAX5, and are usually strongly positive for BCL2, IRF4/MUM1, FOXP1, cytoplasmic IgM, and MYC [10, 12–18]. However, up to 10% of cases may display no expression of BCL2 and/or IRF4/ MUM1 [8, 10]. BCL6 is usually also expressed but may be weak, whereas CD10 is most commonly negative [8, 15]. In addition to cytoplasmic IgM, approximately 50% of cases express IgD [19]. High proliferative activity with MIB-1/Ki-67 expression on more than 80% of the lymphoma cells is common [18]. The lymphoma cells do not express EBV proteins or RNA and are not associated with

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Fig. 14.1 Primary cutaneous diffuse large B cell lymphoma, leg type. This skin biopsy shows a diffuse dermal infiltrate of large lymphoid cells with centroblastic and/or immunoblastic appearance without epidermotropism (H&E, 100×)

Fig. 14.2 Primary cutaneous diffuse large B cell lymphoma, leg type. In this example, the lymphoma cells exhibit a predominantly immunoblastic appearance, with large and round nuclei, prominent nucleoli, and abundant mitoses (H&E, 1000× under oil)

preserved follicular dendritic cell networks. Overexpression of FOXP1 may be associated with an adverse prognosis [16]. Co-expression of MYC and BCL2 (a “double expresser” immunophenotype) may be seen in up to two-thirds of cases [20]. Such co-expression, known to be an adverse prognostic factor in nodal DLBCL, NOS, does not appear to be associated

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with inferior survival in PCDLBL-LT [20]. Expression of interferon regulatory factor 4 (IRF4), also known as multiple myeloma antigen 1 (MUM1), is seen in 68–90% of cases and appears to be an independent adverse prognostic factor in PCDLBL-LT [21].

Tumor Microenvironment The non-malignant cells and stromal environment surrounding the tumor cells comprise the tumor microenvironment (TME). The major components of the TME include tumor-infiltrating lymphocytes (TILs), tumor-suppressing M1 macrophages, tumor-promoting M2 macrophages, and myeloid-derived suppressor cells (MDSCs). The main task of these cells is to mediate antitumor defense but, in certain cases, they can also contribute to tumor survival. In PCDLBL-LT, the TME is known to consist predominately of CD163+ M2 macrophages, less numerous CD68+ M1 macrophages, a considerable proportion of CD33+ MDSCs with PD-L1 co-expression, and only a minor proportion of T-cells [22]; however, the role of these cells is still not well understood. Expression of programmed death-ligand 1 (PD-L1) and the number of M2 macrophages have been reported to be negative prognostic factors in nodal DLBCL [23, 24]. In regards to the PD-L1 and PD-L2 expression by tumor cells in PCDLBL-LT, the results of the studies to date are controversial: in two studies, the tumor cells were rarely positive for PD-L1 and PD-L2 [23, 25], whereas, in other reports, expression of PD-L1 was seen in many or all of the cases [22, 26]. In one of the studies with only a rare case of PCDLBL-LT with PD-L1-positive lymphoma cells, PD-L1 expression was mainly observed on M2 tumor-associated macrophages (TAMs) which constituted the majority of the cells in the TME of PCDLBL-LT [25]. The apparently high abundance of PD-L1-positive M2-type TAMs in PCDLBL-LT suggests that PD-L1 may play a role in tumor immune escape, angiogenesis, or matrix remodeling and that it possibly represents a therapeutic target [25].

Cytogenetic Abnormalities PCDLBL-LT exhibits a greater number of recurrent chromosomal imbalances, genomic gains, and losses than other cutaneous B-cell lymphomas. Comparative genomic hybridization (CGH) and FISH studies have demonstrated that gains in chromosomes 18q, 12q, 2q, 3, 7, 1q, 11, and X and losses in chromosomes 6q, 9, 13, 14, 17p, and 19 are the most frequent numerical aberrations in PCDLBL-LT [27– 30]. Gain of 18q is the most frequent recurrent imbalance in PCDLBL-LT (62% of cases), followed by gains in 1q (38% of cases), while loss of 6q is the most common deletion (31% of cases) [27]. Up to two-thirds of cases of PCDLBL-LT show high-­ level DNA amplification of 18q21.31-q21.33, which includes BCL2 (18q21.33) and

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MALT1 (18q21.32) [31, 32], although one study has documented the absence of this finding [30]. However, t(14;18) IGH::BCL2 is absent in PCDLBL-LT [27]. Although deletions in 6q are associated with a poor prognosis in extracutaneous lymphomas and may also be associated with poor clinical course in PCDLBL-LT [27], deletion of PRDM1 (BLIMP1, at 6q21) which has been described in 15–61% of cases of PCDLBL-LT [32–34], does not appear to have prognostic impact [33]. Trisomy 7, which can be observed in 20% of cases of PCDLBL-LT, may also be associated with an adverse outcome [28]. Similar to primary diffuse large B-cell lymphoma of the central nervous system and primary testicular lymphoma (PTL), 40% of PCDLBL-LT cases harbor PDL1/PDL2 translocations, which lead to overexpression of PD-L1 or PD-L2 in 50% of the cases [26]. Variable proportions of PCDLBL-LT demonstrate chromosomal rearrangements of MYC (5–43%), BCL6 (4–36%), and IGH (50–80%) [17, 20, 30, 33, 35, 36]. MYC is most commonly rearranged with IGH, resulting in the translocation t(8;14) (q24;q32), and rearrangements of the BCL6 locus may involve IGH, IGL, and non-­ IG genes [35]. However, only a few PCDLBL-LT cases with rearrangements of MYC and BCL6 (but not with rearrangements of MYC and BCL2) have been reported (4% in one series) [20]. MYC rearrangements in PCDLBL-LT are associated with an inferior disease-specific survival and disease-free survival but not with reduced overall survival [20]. Recurrent deletions in 9p21.3 encompassing the CDKN2A (p14ARF/p16INK4A) (22–83%), CDKN2B (p15INK4B) (28–45%), and MTAP (83%) genes have been reported in PCDLBL-LT [30–34, 37]. Smaller proportions (25–30%) of cases may display CDKN2A promoter hypermethylation, or, more rarely, cryptic deletion of p16INK4a/CDKN2A [31, 37]. Inactivation of CDKN2A by either deletion of chromosome 9p21.3 or promoter hypermethylation is associated with an adverse prognosis in PCDLBL-LT [31, 33, 37]. The CDKN2A (cyclin-dependent kinase inhibitor 2A) region encodes for the tumor suppressor genes p16 and p14ARF. Deletion of CDKN2A causes a loss of function of the inhibitor of kinase 4 (INK4), resulting in p53 degradation and increased CDK4 activity, causing enhanced cell proliferation. It appears that standard FISH analysis with commercially available probes may not detect small 9p21 deletions; hence, other techniques such as array-based comparative genomic hybridization (aCGH) or multiplex ligation-dependent probe amplification may be more sensitive to identify CDKN2A deletions [38]. TNFAIP3 (A20) is a tumor suppressor gene that acts as a negative regulator of NF-kB signaling. Heterozygous (but not homozygous) TNFAIP3 deletions have been observed in 25–40% of cases of PCDLBL-LT [32, 34, 39]. Deletion of TNFAIP3 explains the low transcriptional levels of TNFAIP3 seen in a subset of cases of PCDLBL-LT; however, in those without these deletions, other abnormalities that alter transcription factor activity (except for epigenetic silencing through promoter hypermethylation or the formation of transcripts with premature stop codons) may mediate decreased expression of its RNA [39]. The FOXP1 (Forkhead box-P1) gene is a transcriptional repressor and putative tumor suppressor gene that maps to chromosomal region 3p14.1. The commonly observed overexpression of FOXP1  in PCDLBL-LT is associated with a gain of

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FOXP1 (seen in 82% of cases) but not with FOXP1 translocations and appears to convey an adverse prognosis [16]. TP53 deletions have been observed in up to 13% of cases of PCDLBL-LT; however, TP53 is rarely mutated in this entity [32].

Gene Mutations The mutational landscape of PCDLBL-LT exhibits a restricted set of highly recurrent mutations in genes involved in the NF-kB and B-cell receptor signaling pathways, as demonstrated by whole-exome sequencing and targeted next-generation sequencing studies. Although the mutational profile of PCDLBL-LT has some overlapping features with that of the nodal DLBCL, NOS, ABC type, it is most similar to that of DLBCL cases arising in immune-privileged sites such as primary CNS DLBCL and PTL [3, 26], as several of the most commonly mutated genes include MYD88 (up to 78% of cases), TNFAIP3/A20 (40%), CD79B (20%), CARD11 (10%), and other genes also mutated in these lymphomas [1, 26, 34, 39]. According to the genetic classification of DLBCL, and because of the associated high frequency of MYD88 L265P and CD79B mutations, many cases of PCDLBL-LT belong to the DLBCL MCD/C5 genetic subgroup [3].

MYD88 Mutations in MYD88 (myeloid differentiation primary response gene 88), specifically the p.L265P mutation, have been reported in 40–78% of cases of PCDLBL-LT [18, 26, 32, 34, 40, 41], while other MYD88 mutations (i.e. p.S243N, S219C, p.V217F, and p.M240T) are rare [26, 32, 34, 42]. The MYD88 L265P mutation is usually heterozygous and somatically acquired [42]. Both the MYD88 L265P and the CD79B mutations appear to be important drivers in immune-privileged site-­ associated DLBCL such as DLBCL arising in the central nervous system (75%) and testis (71%), and less commonly found in nodal DLBCL, NOS, ABC type (17–29%) [43, 44]. Non-L265P MYD88 mutations (V217F, W218R, S219C, I220T, S222R, M232T, S243N, T294P) have been reported in 8% of cases of nodal DLBCL and may comprise up to one-third of MYD88-mutated nodal DLBCL cases [43]. Except for the p.S243N, S219C, and p.V217F mutations, the non-L265P mutations seen in nodal DLBCL have not been reported so far in PCDLBL-LT [32, 42]. The MYD88 protein is a signaling adaptor protein that activates Toll-like receptors (TLRs) and receptors for IL-1 and IL-18 resulting in NF-kB activation during normal innate immune responses. MYD88 coordinates the assembly of a multi-­ subunit signaling complex including the IRAK1 and IRAK4 serine-threonine kinases [42]. The most frequent MYD88 mutation in PCDLBL-LT is a thymine to cytosine base transition at position 794 of the complementary DNA coding sequence

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(c.794 T > C), which causes a L265P (leucine to proline) amino-acid change. The MYD88 L265P protein forms a stable complex containing phosphorylated IRAK1 and promotes NF-kB and JAK-STAT3 signaling, conferring a selective advantage in cell survival [43]. The MYD88 L265P mutation is of prognostic significance in PCDLBL-LT as it is associated with shorter disease-specific and overall survival, as well as with advanced age and more frequent involvement of the leg [41]; however, this association has not been seen in all studies [32]. The high variant allele frequency (VAF) commonly observed in association with MYD88 mutations in PCDLBL-LT suggests a clonal alteration carried by most tumor cells, supporting the role of MYD88 L265P as an oncogenic driver [34].

PIM1 The proviral integration site for Moloney murine leukemia virus 1 (PIM1) gene is a proto-oncogene that encodes a serine/threonine protein kinase that has antiapoptotic activity. The PIM1 kinase is an upstream regulator of NF-κB signaling and has been shown to mediate cell survival, proliferation, cell differentiation, transformation, tumor progression, and angiogenesis in lymphoma through cooperation with MYC and BCL6 [45, 46]. PCDLBL-LT shows frequent PIM1 mutations (up to 70% of cases) [32, 34] and PIM overexpression (~90% of cases) [14].

IGH Amplification of the rearranged genes of the variable region of IGH used by PCDLBL-LT cells shows a single monoclonal PCR product in the majority of cases, with only rare biallelic rearrangements and no biased usage of any particular Vh segments [36]. The variable region of the immunoglobulin heavy chain (IGH) gene in PCDLBL-LT displays somatic hypermutation in 100% of cases, with a mutation rate that ranges from 5.5% to 15% (mean: 9.0%) [36, 47]. Along with the high degree of BCL6 mutations seen in PCDLBL-LT (see below), the presence of somatic hypermutation indicates that the neoplastic cells of PCDLBL-LT derive from B cells that have experienced the germinal center reaction.

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BCL6 The B-cell lymphoma 6 (BCL6) gene encodes a protein that acts as a sequence-­ specific transcriptional repressor and is necessary for germinal center formation. Heterozygous BCL6 mutations have been found in 80% of PCDLBL-LT cases in a small cohort, with one to multiple single nucleotide substitutions per allele [36].

CD79A/b CD79B and CD79A are components of the B-cell receptor (BCR), which activates the NF-kB pathway to promote cell survival, proliferation, and inhibition of apoptosis. Activating mutations in the ITAM (immunoreceptor tyrosine-based activation motif) domain of CD79B, most commonly p.Y196 and less frequently E197D, are seen in 20–56% of cases of PCDLBL-LT [32, 39]. Mutations in the CD79A ITAM region are of splice type and have been identified in 6% of cases of PCDLBL-LT, consisting of a deletion across the intron 4/exon 5 that removes a part of the ITAM domain, including the first tyrosine [32]. CD79B and CD79A mutations are mutually exclusive with those of CARD11 [32]. The relatively high frequency of CD79B and CD79A in PCDLBL-LT suggests that chronic active B-cell receptor signaling with activation of the NF-kB pathway is a frequent lymphomagenic mechanism involved in these cases. Mutations involving the BCR pathway (including CD79/B and CARD11) are associated with an aggressive clinical course [32].

TBLXR1 TBLXR1 (transducing beta like 1 X-linked receptor 1) is a component of the NCoR/ SMRT co-repressor complex that modulates toll-like receptor/MYD88 target genes, whereby it may act as a tumor suppressor [34]. In PCLBCL-LT, TBLXR1 is mutated in approximately one-third of the cases. It is thought that TBLXR1 and MYD88 genomic alterations may be synergistic in PCDLBL-LT [34].

Other Mutations Other mutations, including CREBBP (16%), IRF4 (16%), KLHL6 (11%), GNA13 (10%), KMT2D (10%), NOTCH2 (9%), MYC (9%), IKZF3 (7%) CARD11 (6%), CXCR4 (6%), MEF2 (6%), ARID1A (6%), FOXO1 (6%), XPO1 (6%), CCND3 (6%), SOCS1 (6%), BCL2 (6%), BMF (6%), NOTCH1 (3%), EP300 (3%), TP53 (3%), and PLCG2 (3%) have also been identified in PCDLBL-LT [32, 34, 48].

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Interestingly, in nearly all MYD88 wild-type cases, oncogenic mutations that either activate the NF-kB pathway through alternative genes (NFKBIE or REL) or activate other canonical cancer pathways such as BRAF (up to 3%), MED12 (3%), PIK3R1 (3%), and STAT3 (10%) can be identified [26, 32]. Evasion of the immune system is also important in the pathogenesis of PCDLBL-LT, representing the second most commonly mutated pathway after the NF-kB pathway, with mutations predicted to downregulate antigen processing [B2M (up to 6%), CIITA (up to 6%), HLA (50%)] or T-cell co-stimulation (CD58, up to 10%) [26, 32].

Gene Expression Profile Gene expression profiling of nodal DLBCL, NOS has identified two main signatures: the germinal center B-cell (GCB) type, and the post-germinal center or activated B-cell (ABC) type. DLBCL, NOS ABC type is characterized by poorer overall survival with constitutive activation of the NF-kB pathway and a higher proliferation index [49, 50]. In PCDLBL-LT, the gene expression profile is similar to that of DLBCL, NOS ABC type, with expression of more than 40 genes involved in cell cycle/proliferation (e.g. cyclin E, CDC6, PCNA), DNA synthesis, replication and repair (e.g. CTP synthetase, DNA polymerase, replication factors 3 and 5), signaling (e.g. IgM heavy chain, PIM1, PIM2, LYN, BLK), transcription regulation (e.g. MUM1/IRF4, cMYC, BCL6, OCT2, TFDP1, MYBL2) and others, of which IgM heavy chain, MUM1/IRF4, and PIM1 are the most consistently expressed [14]. The high expression of MYC seen in a subset of PCDLBL-LT is the result of chromosomal translocation of MYC to IGH, whereas deregulated expression of BCL6 is thought to be due to somatic hypermutations on BCL6 that prevents BCL6 from exerting its negative autoregulatory effect [14, 51]. The increased expression of MYC and/or BCL6 plus that of other various genes associated with proliferation, or that allow uncontrolled proliferation (such as MUM1/IRF4), contributes to the high proliferative activity seen in PCDLBL-LT [14, 51].

MicroRNA Profile MicroRNAs (miR) are small (~22 nucleotides long) noncoding RNA molecules that can regulate translation of several specific target messenger RNAs (mRNAs), thereby controlling the post-translational expression of around 60% of human protein-­coding genes. Alterations in microRNA expression contribute to oncogenesis, and although they have been extensively studied in nodal DLBCL, NOS, only a few studies have focused on their characterization in PCDLBL-LT to date [52, 53]. The miR-17-92 cluster includes miR-17-5p, miR-18a-5p, miR-19a-3p, miR-­19b-3p, miR-20a-5p, and miR-92a-3p [54]. The presence of the miR-17-92

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cluster is critical for normal B-cell development [55] and is potentially oncogenic [56] through the activation of proliferation and inhibition of apoptosis [52]. In one study, certain members of this cluster (miR-19a-3p and miR-19b-3p) were highly expressed in PCDLBL-LT, comprising 11% and 12% of the total microRNome, respectively, whereas the other members made up only a very small proportion (1% or less) of the mRNA profile [52]. However, the expression of miR-19a-3p and miR-­19b-3p in PCDLBL-LT is not specific, as they also comprise a substantial part of the microRNome of PCFCL [52]. Although unsupervised hierarchical clustering analysis of the microRNome of PCDLBL-LT, PCFCL, and non-neoplastic activated B-cells does not result in distinct separation of these two tumor types and/or activated B-cells, PCDLBL-LT and PCFCL can be distinguished by the greater degree of expression of miR-129-2-3p, miR-214-3p, miR-31-5p and miR-9-5p in PCFCL [52] and higher expression of miR-20a, miR-20b, and miR-106a in PCDLBL-LT [53]. Interestingly, the multivariate analysis in one study revealed that higher miR-­20a and miR-20b expression levels were associated with shorter disease-free and overall survival, independently from the histologic type (PCDLBL-LT and PCFCL) [53]. The microRNA profile of nodal DLBCL, NOS, ABC type can be distinguished from that of nodal DLBCL, NOS GCB type by the higher expression of miR-­155-5p, miR-21-5p, miR-221-3p, and miR-222-3p in the former. However, the expression of these microRNAs is not significantly different in PCDLBL-LT and PCFCL [52]. Surprisingly, the expression of miR-92a-3p, one of the most abundantly expressed microRNAs in nodal DLBCL, NOS, and primary central nervous system DLBCL, is low in PCDLBL-LT [52].

Role of Genomic Testing in Treatment Immunochemotherapy with R-CHOP is the mainstay of treatment for PCDLBL-LT, and has increased patient response rate and survival. However, nearly a quarter to half of the patients experience progression or relapse, underscoring the need for targeted therapies directed against signaling pathways such as the B-cell receptor, Toll-like receptor or NF-kB pathways [34]. Given the high frequency of MYD88 L265P mutations in PCDLBL-LT, the MYD88 signaling complex represents a promising therapeutic target in this disease. The IRAK4 kinase is a part of this complex, and inhibitors of IRAK4 kinase have been shown to inhibit cell survival in nodal DLBCL, NOS ABC type with the MYD88 L265P mutation, therefore representing a target also in the treatment of PCDLBL-LT as well [42]. Several other targeted therapeutic strategies seem promising in the treatment of PCDLBL-LT. The B-cell receptor signaling pathway can be targeted by ibrutinib which is a small molecule inhibitor of Bruton’s tyrosine kinase (BTK). The susceptibility of PCDLBL-LT to BTK inhibitors may also depend on the combination of MYD88 with other mutations, as demonstrated by the better response to ibrutinib in

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nodal DLBCL with both MYD88 and CD79B mutations than in patients with CARD11 mutations. In contrast, PIM1 mutations have been found to reduce sensitivity to ibrutinib in DLBCL, NOS ABC type. Other therapeutic options include lenalidomide, which targets interferon regulatory factor-4 (IRF-4) and the transcription factor SPIB, and bortezomib, which targets the NF-kB proteasome [34, 41]. Checkpoint inhibitors such as pembrolizumab and nivolumab may also have value in the treatment of PCDLBL-LT, particularly in relapsed/refractory cases, given the frequent overexpression of PD-L1/PD-L2 in the tumor cells, [25, 26, 57]; such patients could be included in currently active clinical trials with genomically similar PCNSL and PTLs [26].

Role of Genomic Testing in the Differential Diagnosis Primary cutaneous follicle center cell lymphoma: The distinction between PCDLBL-LT and PCFCL is extremely relevant because these entities differ in prognosis and management approach. PCFCL is a tumor of neoplastic follicle center cells, often with a predominance of large centrocytes and a follicular and/or diffuse growth pattern, which commonly presents with localized skin lesions on the head or trunk. PCFCL can be managed with local radiotherapy and generally has an excellent prognosis [1]. Immunohistochemistry (IHC) is instrumental in establishing the diagnosis of PCDLBL-LT and can help distinguish it from PCFCL because of differences in expression of BCL2, FOXP1, MUM1 and IgM/IgD, all of which are usually strongly positive in PCDLBL-LT but not in PCFCL [17, 18]. In addition, the presence of complete or incomplete follicular dendritic cell meshworks, which can be determined by IHC for CD21, can be seen in many cases of PCFCL but is not observed in PCDLBL-LT [18]. Although IHC is useful in distinguishing PCFCL from PCDLBL-LT, mutation analysis, and cytogenetic studies may also be helpful in this regard. For example, the MYD88 L265P mutation seen in most cases of PCDLBL-LT is not observed in PCFCL [18, 42]. Also, in contrast to PCDLBL-LT, PCFCL exhibits fewer chromosomal imbalances and lacks translocations affecting the IGH, MYC, and BCL6 loci [27] as well as deletion of 9p21.3 (CDKN2A) [31]. In turn, while BCL2 rearrangements or 1p36 deletion is not seen in PCDLBL-LT, some studies have reported these abnormalities in a subset of cases of PCFCL [58–61]. Gene expression profiling and microRNA testing are not yet widely available for clinical use; however, these studies also reveal differences between PCDLBL-LT and PCFCL. In contrast to PCDLBL-LT which has a gene expression profile similar to that of DLBCL, NOS ABC type, PCFCL has a gene expression profile similar to DLBCL, NOS GCB type. Unsupervised hierarchical clustering analysis of the microRNome of PCDLBL-LT and PCFCL does not result into distinct separation of these two tumor types, but the expression of miR-129-2-3p, miR-214-3p, miR-­31-5p and miR-9-5p is higher in PCFCL [52] while that of miR-20a, miR-20b, and miR-­106a is higher in PCLBCL-LT [53].

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Secondary cutaneous involvement by extra-cutaneous (nodal) diffuse large B-cell lymphoma: Systemic DLBCL, NOS with cutaneous involvement is likely to be more aggressive and demonstrate worse prognosis than PCDLBL-LT [62]; therefore, it is important to distinguish these two entities. This can be done through careful evaluation of the clinical history, and the immunophenotypic, genomic, and staging studies. Regarding their distinguishing immunophenotypic features, strong expression of CD10 and/or absence of BCL2, FOXP1, MUM1 and IgM expression in a diffuse large B-cell infiltrate involving the skin is highly suggestive of secondary cutaneous involvement by systemic DLBCL rather than PCDLBL-LT [2]. Gene expression profiling shows that PCDLBL-LT shares more similarities with nodal DLBCL, NOS ABC type than with DLBCL, NOS GCB type [14, 33, 39]. PCDLBL-LT also shares a comparable mutational profile with nodal DLBCL, NOS ABC type, but also with primary CNS DLBCL and PTL, as the MYD88 L265P mutation, frequently identified in PCDLBL-LT, can also be seen in up to 33% of cases of systemic DLBCL, NOS ABC type, in more than 50% of primary CNS DLBCL cases and in more than 70% of PTL cases [42, 44, 63, 64]; therefore, its identification cannot be reliably used to differentiate between these entities. However, the main differential diagnosis of PCDLBL-LT in this scenario includes systemic DLBCL, NOS ABC type as cutaneous involvement by primary CNS DLBCL or PTL is unusual [65, 66]. Of note, MYD88 mutations can also be identified in up to 10% of cases of systemic DLBCL, NOS GCB type and in low-grade B-cell neoplasms, such as lymphoplasmacytic lymphoma (up to 100% of cases), chronic lymphocytic leukemia (up to 10% of cases), and marginal zone lymphoma, MALT-type (5% of cases), although the morphology of low-grade B-cell neoplasms is significantly different from that of PCDLBL-LT and systemic DLBCL, NOS, and therefore they are usually not considered in their differential diagnosis [34, 42, 67– 69]. Importantly, PCDLBL-LT can unusually spread to the CNS or the vtesticles, where it can potentially mimic primary CNS DLBCL and PTL, respectively [6, 9, 70, 71]. Other genomic abnormalities observed in PCDLBL-LT such as PIM1, CD79B, TBLXR1, TNFAIP3(A20), CARD11, KLHL6, CREBBP, IRF4, BRAF, and CD58 mutations have also been identified in subsets of nodal (systemic) DLBCL, NOS, and therefore the presence of any of these mutations does not aid in distinguishing these two entities [44, 63, 72, 73]. Conversely, the presence of a BCL2 rearrangement and/or a mutation in TP53 (but not deletion), NOTCH1, EP300, EZH2, or STAT6 in a diffuse large B-cell lymphoma with cutaneous involvement suggest secondary cutaneous involvement by a nodal (systemic) DLBCL, NOS, given the rarity or complete absence of these mutations in PCDLBL-LT and their more frequent identification in nodal (systemic) DLBCL, NOS [4, 32, 34, 68].

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17. Menguy S, Frison E, Prochazkova-Carlotti M, Dalle S, Dereure O, Boulinguez S, et al. Double-­ hit or dual expression of MYC and BCL2 in primary cutaneous large B-cell lymphomas. Mod Pathol. 2018;31(8):1332–42. 18. Menguy S, Beylot-Barry M, Parrens M, Ledard AP, Frison E, Comoz F, et al. Primary cutaneous large B-cell lymphomas: relevance of the 2017 World Health Organization classification: clinicopathological and molecular analyses of 64 cases. Histopathology. 2019;74(7):1067–80. 19. Koens L, Vermeer MH, Willemze R, Jansen PM. IgM expression on paraffin sections distinguishes primary cutaneous large B-cell lymphoma, leg type from primary cutaneous follicle center lymphoma. Am J Surg Pathol. 2010;34(7):1043–8. 20. Schrader AMR, Jansen PM, Vermeer MH, Kleiverda JK, Vermaat JSP, Willemze R. High incidence and clinical significance of MYC rearrangements in primary cutaneous diffuse large B-cell lymphoma. Leg Type Am J Surg Pathol. 2018;42(11):1488–94. 21. Pham-Ledard A, Prochazkova-Carlotti M, Vergier B, Petrella T, Grange F, Beylot-Barry M, et al. IRF4 expression without IRF4 rearrangement is a general feature of primary cutaneous diffuse large B-cell lymphoma, leg type. J Investig Dermatol. 2010;130(5):1470–2. 22. Mitteldorf C, Berisha A, Pfaltz MC, Broekaert SMC, Schon MP, Kerl K, et al. Tumor microenvironment and checkpoint molecules in primary cutaneous diffuse large B-cell lymphoma-new therapeutic targets. Am J Surg Pathol. 2017;41(7):998–1004. 23. Kiyasu J, Miyoshi H, Hirata A, Arakawa F, Ichikawa A, Niino D, et al. Expression of programmed cell death ligand 1 is associated with poor overall survival in patients with diffuse large B-cell lymphoma. Blood. 2015;126(19):2193–201. 24. Shen L, Li H, Shi Y, Wang D, Gong J, Xun J, et al. M2 tumour-associated macrophages contribute to tumour progression via legumain remodelling the extracellular matrix in diffuse large B cell lymphoma. Sci Rep. 2016;6:30347. 25. Menguy S, Prochazkova-Carlotti M, Beylot-Barry M, Saltel F, Vergier B, Merlio JP, et  al. PD-L1 and PD-L2 are differentially expressed by macrophages or tumor cells in primary cutaneous diffuse large B-cell lymphoma. Leg Type Am J Surg Pathol. 2018;42(3):326–34. 26. Zhou XA, Louissaint A Jr, Wenzel A, Yang J, Martinez-Escala ME, Moy AP, et al. Genomic analyses identify recurrent alterations in immune evasion genes in diffuse large B-cell lymphoma. Leg Type J Investig Dermatol. 2018;138(11):2365–76. 27. Hallermann C, Kaune KM, Siebert R, Vermeer MH, Tensen CP, Willemze R, et  al. Chromosomal aberration patterns differ in subtypes of primary cutaneous B cell lymphomas. J Investig Dermatol. 2004;122(6):1495–502. 28. Wiesner T, Streubel B, Huber D, Kerl H, Chott A, Cerroni L. Genetic aberrations in primary cutaneous large B-cell lymphoma: a fluorescence in situ hybridization study of 25 cases. Am J Surg Pathol. 2005;29(5):666–73. 29. Gimenez S, Costa C, Espinet B, Sole F, Pujol RM, Puigdecanet E, et  al. Comparative genomic hybridization analysis of cutaneous large B-cell lymphomas. Exp Dermatol. 2005;14(12):883–90. 30. Belaud-Rotureau MA, Marietta V, Vergier B, Mainhaguiet G, Turmo M, Idrissi Y, et  al. Inactivation of p16INK4a/CDKN2A gene may be a diagnostic feature of large B cell lymphoma leg type among cutaneous B cell lymphomas. Virchows Arch. 2008;452(6):607–20. 31. Dijkman R, Tensen CP, Jordanova ES, Knijnenburg J, Hoefnagel JJ, Mulder AA, et al. Array-­ based comparative genomic hybridization analysis reveals recurrent chromosomal alterations and prognostic parameters in primary cutaneous large B-cell lymphoma. J Clin Oncol. 2006;24(2):296–305. 32. Ducharme O, Beylot-Barry M, Pham-Ledard A, Bohers E, Viailly PJ, Bandres T, et  al. Mutations of the B-cell receptor pathway confer chemoresistance in primary cutaneous diffuse large B-cell lymphoma leg-type. J Investig Dermatol. 2019;139(11):2334–2342.e8. https://doi. org/10.1016/j.jid.2019.05.008. Epub 2019 May 29 33. Pham-Ledard A, Prochazkova-Carlotti M, Andrique L, Cappellen D, Vergier B, Martinez F, et al. Multiple genetic alterations in primary cutaneous large B-cell lymphoma, leg type s­ upport

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a common lymphomagenesis with activated B-cell-like diffuse large B-cell lymphoma. Mod Pathol. 2014;27(3):402–11. 34. Mareschal S, Pham-Ledard A, Viailly PJ, Dubois S, Bertrand P, Maingonnat C, et  al. Identification of somatic mutations in primary cutaneous diffuse large B-cell lymphoma, leg type by massive parallel sequencing. J Investig Dermatol. 2017;137(9):1984–94. 35. Hallermann C, Kaune KM, Gesk S, Martin-Subero JI, Gunawan B, Griesinger F, et al. Molecular cytogenetic analysis of chromosomal breakpoints in the IGH, MYC, BCL6, and MALT1 gene loci in primary cutaneous B-cell lymphomas. J Investig Dermatol. 2004;123(1):213–9. 36. Paulli M, Viglio A, Vivenza D, Capello D, Rossi D, Riboni R, et al. Primary cutaneous large B-cell lymphoma of the leg: histogenetic analysis of a controversial clinicopathologic entity. Hum Pathol. 2002;33(9):937–43. 37. Senff NJ, Zoutman WH, Vermeer MH, Assaf C, Berti E, Cerroni L, et al. Fine-mapping chromosomal loss at 9p21: correlation with prognosis in primary cutaneous diffuse large B-cell lymphoma, leg type. J Investig Dermatol. 2009;129(5):1149–55. 38. Wiesner T, Obenauf AC, Geigl JB, Vallant EM, Speicher MR, Fink-Puches R, et al. 9p21 deletion in primary cutaneous large B-cell lymphoma, leg type, may escape detection by standard FISH assays. J Investig Dermatol. 2009;129(1):238–40. 39. Koens L, Zoutman WH, Ngarmlertsirichai P, Przybylski GK, Grabarczyk P, Vermeer MH, et al. Nuclear factor-kappaB pathway-activating gene aberrancies in primary cutaneous large B-cell lymphoma, leg type. J Investig Dermatol. 2014;134(1):290–2. 40. Menguy S, Gros A, Pham-Ledard A, Battistella M, Ortonne N, Comoz F, et  al. MYD88 somatic mutation is a diagnostic criterion in primary cutaneous large B-cell lymphoma. J Investig Dermatol. 2016;136(8):1741–4. 41. Pham-Ledard A, Beylot-Barry M, Barbe C, Leduc M, Petrella T, Vergier B, et al. High frequency and clinical prognostic value of MYD88 L265P mutation in primary cutaneous diffuse large B-cell lymphoma. Leg-Type JAMA Dermatol. 2014;150(11):1173–9. 42. Pham-Ledard A, Cappellen D, Martinez F, Vergier B, Beylot-Barry M, Merlio JP.  MYD88 somatic mutation is a genetic feature of primary cutaneous diffuse large B-cell lymphoma, leg type. J Investig Dermatol. 2012;132(8):2118–20. 43. Ngo VN, Young RM, Schmitz R, Jhavar S, Xiao W, Lim KH, et  al. Oncogenically active MYD88 mutations in human lymphoma. Nature. 2011;470(7332):115–9. 44. Kraan W, Horlings HM, van Keimpema M, Schilder-Tol EJM, Oud MECM, Scheepstra C, et  al. High prevalence of oncogenic MYD88 and CD79B mutations in diffuse large B-cell lymphomas presenting at immune-privileged sites. Blood Cancer J. 2013;3(9):e139. 45. Kuo HP, Ezell SA, Hsieh S, Schweighofer KJ, Cheung LW, Wu S, et  al. The role of PIM1  in the ibrutinib-resistant ABC subtype of diffuse large B-cell lymphoma. Am J Res. 2016;6(11):2489–501. 46. Baron BW, Anastasi J, Hyjek EM, Bies J, Reddy PL, Dong J, et al. PIM1 gene cooperates with human BCL6 gene to promote the development of lymphomas. Proc Nati Acad Sci U S A. 2012;109(15):5735–9. 47. Perez M, Pacchiarotti A, Frontani M, Pescarmona E, Caprini E, Lombardo GA, et  al. Primary cutaneous B-cell lymphoma is associated with somatically hypermutated immunoglobulin variable genes and frequent use of VH1-69 and VH4-59 segments. Br J Dermatol. 2010;162(3):611–8. 48. Kim EJ, Lewis DJ, Duvic M.  Novel mutations involving NF-kappaB and B-cell signaling pathways in primary cutaneous large B-cell lymphoma, leg-type and comparison with Sezary syndrome. J Investig Dermatol. 2017;137(9):1831–3. 49. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, et  al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403(6769):503–11. 50. Lenz G, Staudt LM. Aggressive lymphomas. N Engl J Med. 2010;362(15):1417–29.

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51. Pasqualucci L, Migliazza A, Basso K, Houldsworth J, Chaganti RS, Dalla-Favera R. Mutations of the BCL6 proto-oncogene disrupt its negative autoregulation in diffuse large B-cell lymphoma. Blood. 2003;101(8):2914–23. 52. Koens L, Qin Y, Leung WY, Corver WE, Jansen PM, Willemze R, et al. MicroRNA profiling of primary cutaneous large B-cell lymphomas. PLoS One. 2013;8(12):e82471. 53. Battistella M, Romero M, Castro-Vega LJ, Gapihan G, Bouhidel F, Bagot M, et al. The high expression of the microRNA 17-92 cluster and its paralogs, and the downregulation of the target gene PTEN, is associated with primary cutaneous B-cell lymphoma progression. J Investig Dermatol. 2015;135(6):1659–67. 54. Mogilyansky E, Rigoutsos I. The miR-17/92 cluster: a comprehensive update on its genomics, genetics, functions and increasingly important and numerous roles in health and disease. Cell Death Differ. 2013;20(12):1603–14. 55. Ventura A, Young AG, Winslow MM, Lintault L, Meissner A, Erkeland SJ, et al. Targeted deletion reveals essential and overlapping functions of the miR-17 through 92 family of miRNA clusters. Cell. 2008;132(5):875–86. 56. He L, Thomson JM, Hemann MT, Hernando-Monge E, Mu D, Goodson S, et al. A microRNA polycistron as a potential human oncogene. Nature. 2005;435(7043):828–33. 57. Kraft RM, Ansell SM, Villasboas JC, Bennani NN, Wang Y, Habermann TM, et  al. Outcomes in primary cutaneous diffuse large B-cell lymphoma, leg type. Hematol Oncol. 2021;39(5):658–63. 58. Gango A, Batai B, Varga M, Kapczar D, Papp G, Marschalko M, et  al. Concomitant 1p36 deletion and TNFRSF14 mutations in primary cutaneous follicle center lymphoma frequently expressing high levels of EZH2 protein. Virchows Arch. 2018;473(4):453–62. 59. Aguilera NS, Tomaszewski MM, Moad JC, Bauer FA, Taubenberger JK, Abbondanzo SL. Cutaneous follicle center lymphoma: a clinicopathologic study of 19 cases. Mod Pathol. 2001;14(9):828–35. 60. Kim BK, Surti U, Pandya A, Cohen J, Rabkin MS, Swerdlow SH. Clinicopathologic, immunophenotypic, and molecular cytogenetic fluorescence in situ hybridization analysis of primary and secondary cutaneous follicular lymphomas. Am J Surg Pathol. 2005;29(1):69–82. 61. Szablewski V, Ingen-Housz-Oro S, Baia M, Delfau-Larue MH, Copie-Bergman C, Ortonne N. Primary cutaneous follicle center lymphomas expressing BCL2 protein frequently harbor BCL2 gene break and may present 1p36 deletion: a study of 20 cases. Am J Surg Pathol. 2016;40(1):127–36. 62. Lee WJ, Won KH, Won CH, Chang SE, Choi JH, Moon KC, et  al. Secondary cutaneous diffuse large B-cell lymphoma has a higher international prognostic index score and worse prognosis than diffuse large B-cell lymphoma. Leg Type Acta Dermato-Venereologica. 2016;96(2):245–50. 63. Schmitz R, Wright GW, Huang DW, Johnson CA, Phelan JD, Wang JQ, et al. Genetics and pathogenesis of diffuse large B-cell lymphoma. N Engl J Med. 2018;378(15):1396–407. 64. Lee JH, Jeong H, Choi JW, Oh H, Kim YS. Clinicopathologic significance of MYD88 L265P mutation in diffuse large B-cell lymphoma: a meta-analysis. Sci Rep. 2017;7(1):1785. 65. Dalal V, Kaur M, Siraj F, Singh A, Bansal A. Primary testicular lymphoma with solitary cutaneous nodule as the initial presentation. J Can Urol Assoc. 2015;9(9–10):E744–7. 66. Zucca E, Conconi A, Mughal TI, Sarris AH, Seymour JF, Vitolo U, et al. Patterns of outcome and prognostic factors in primary large-cell lymphoma of the testis in a survey by the international Extranodal lymphoma study group. J Clin Oncol. 2003;21(1):20–7. 67. Rossi D.  Role of MYD88  in lymphoplasmacytic lymphoma diagnosis and pathogenesis. Hematol Am Soc Hematol Educ Program. 2014;2014(1):113–8. 68. Vaque JP, Martinez N, Batlle-Lopez A, Perez C, Montes-Moreno S, Sanchez-Beato M, et  al. B-cell lymphoma mutations: improving diagnostics and enabling targeted therapies. Haematologica. 2014;99(2):222–31. 69. Bogusz AM, Bagg A. Genetic aberrations in small B-cell lymphomas and leukemias: molecular pathology, clinical relevance and therapeutic targets. Leuk Lymphoma. 2016;57(9):1991–2013.

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Chapter 15

Epstein-Barr Virus-Positive Diffuse Large B-Cell Lymphoma, Not Otherwise Specified Mahsa Khanlari and Pei Lin

Abbreviations BTK Bruton’s tyrosine kinase CTAR C-terminal activation region EBNA Epstein–Barr virus nuclear antigen ERK Extracellular signal-regulated kinase IKK IκB kinases ITAM Immunoreceptor tyrosine-based activation motif JAK-STAT Janus kinase (JAK)-signal transducer and activator of transcription(STAT) JNK C-Jun N-terminal kinase LMP Latent membrane proteins MAPK Mitogen-activated protein kinase NEDD4 Neural precursor cell expressed developmentally down-regulated protein 4 NF-KB Nuclear factor kappa B PD-1 Programmed cell death protein 1 PD-L1 Programmed death-ligand 1 PI3K phosphatidylinositol 3-kinase S1PR2 Sphingosine-1-phosphate receptor 2 TRAF Tumor necrosis factor receptor-associated factor TRADD Tumor necrosis factor receptor type 1-associated death-domain The original version of the chapter has been revised. A correction to this chapter can be found at https://doi.org/10.1007/978-3-031-46842-1_26. M. Khanlari Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA e-mail: [email protected] P. Lin (*) Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023, corrected publication 2024 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_15

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Definition Epstein–Barr virus (EBV) is associated with various B cell lymphoproliferative diseases (LPD) and lymphoma. These include EBV-associated B-LPD of the immunocompromised, Hodgkin lymphoma (HL), Burkitt lymphoma (BL), diffuse large B cell lymphoma (DLBCL), plasmablastic lymphoma (PBL), and primary effusion lymphoma (PEL). EBV+ DLBCL, not otherwise specified (NOS), is an EBV-driven clonal proliferation of large B cells in the absence of known immunodeficiency or iatrogenic immunosuppression. Described initially in patients >50 years of age and considered a provisional entity [1, 2], subsequent reports of the disease occurring among younger patients expanded the spectrum. It is currently recognized as a distinct clinicopathological entity in the 5th WHO classification and International Consensus Classification [3]. The NOS designation is used to exclude more specific types of EBV-positive lymphomas, as mentioned above. Demonstration of EBV in the tumor cells is required for the diagnosis and in situ hybridization for detection of EBV-encoded small RNAs (EBER) is typically used for this purpose. However, the fraction of EBV+ tumor cells needed for the diagnosis has not yet been established, although the WHO and ICC both indicate that 80% or more are atypically seen [3, 4]. Different cutoffs ranging from 10% to >80% have been used in the published studies resulting in a range of reported disease prevalence [5–7].

Epidemiology EBV-positive DLBCL accounts for 8–15% of DLBCL among Asian and Latin American patients and 2–5% among Western patients [5–8]. Most cases occur after 60 with a median age of 71, but younger patients can be affected, with 6.7% to 8% of cases occurring in younger patients [9–12]. Extranodal mass with or without lymphadenopathy is present in about 70% of patients at diagnosis [12]. The gastrointestinal tract, skin, and bone marrow are the most commonly affected sites. One study described that Mexican patients tend to be younger and mostly had nodal involvement [8].

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Morphology Two main morphological subtypes have been described, polymorphous and monomorphic [4] (Figs.  15.1 and 15.2). The polymorphous subtype contains a broad range of variable-sized B cells that are admixed with variable amounts of reactive elements. Large cells resembling Reed-Sternberg or Hodgkin cells can be observed, and geographic necrosis is frequently present. The monomorphic subtype shows sheets of monotonous large transformed cells similar to other cases of DLBCL. Some instances of monomorphic type resemble plasmablastic lymphoma [13]. Both subtypes can coexist in the same tumor. Some polymorphic and monomorphic subtypes show striking similarities with polymorphic and monomorphic post-transplant lymphoproliferative disorder (PTLD) [1]. Both subtypes are clinically aggressive. a

b

c

d

Fig. 15.1  Examples of polymorphic EBV+ DLBCL, lower power view, and high-power view showing atypical large cells in a background of small lymphocytes and histiocytes. The red arrow in (d) marks the atypical large cell ((a), hematoxylin and eosin (H&E) stain, original magnification ×100; (b) H&E, original magnification ×200; (c) H&E, original magnification ×400; (d) H&E, original magnification ×500)

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Fig. 15.2  Example of EBV  +  DLBCL: Note the zonal necrosis (Green arrows, H&E, original magnification ×200, (a). The scattered binucleated Reed-Sternberg-like cells (red arrow) and marked inflammatory response in the background (H&E, original magnification ×400), (b). The lymphoma cells show a strong expression of MUM1 (original magnification ×400). In situ hybridization reveals the presence of EBV-encoded RNA in the small B cells and large tumor cells (original magnification ×400)

Immunohistochemistry/In Situ Hybridization The most consistently expressed viral gene in EBV-related neoplasia is EBV-­ encoded RNA (EBER). Since EBER is not translated into protein, RNA-based detection methods are required to detect EBER. EBER in situ hybridization is the most sensitive and definitive laboratory test for proving that a neoplasm is EBV-­ related. LMP1 is expressed in 2/3 of cases while EBNA2 in 1/3 of patients [14, 15]. Immunophenotypically, the lymphoma cells express B-cell markers such as CD19, CD20, CD22, and CD79. CD30 expression ranges from 40–80% based on different ethnic populations. The lymphoma cells are usually positive for MUM1,

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Fig. 15.3  Examples of monomorphic EBV+ DLBCL, high power view showing atypical large cells, some with prominent nucleoli (a, hematoxylin and eosin (H&E) stain, original magnification ×500). The lymphoma cells show expression of CD20 and MUM-1 (b and c, original magnification ×400). In situ hybridization reveals EBV-encoded RNA in the large B cells (d, original magnification ×400)

very rarely positive for CD15, but often negative for CD10 and BCL6 [16–18] (Figs. 15.3 and 15.4) EBV+ DLBCL typically expresses the so-called activated B cell-like phenotype (ABC) according to the Hans (95%) or Choi (78%) algorithms [19]. However, the Visco-Young algorithm, which integrates FOXP1 expression, may reclassify a subset of these cases into the germinal center B cell (GCB)-like category [20–22]. Expression of BCL2 is common [12, 16]. Most cases show a proliferative index of >50% of the cells, as measured by Ki-67 staining [16]. About 79% of patients show nuclear staining for p105/p50, 74% for p100/p52, and 63% for both proteins due to NF-κB activation and phosphorylated STAT3 frequently expressed [17].

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a

b

Fig. 15.4 (a) Immunophenotype of EBV+ DLBCL. The lymphoma cells are positive for CD20 (uniform), CD30 (subset), and LMP1 and negative for CD15. (b) Note the tumor may display a polymorphic pattern on one area (left) but a monomorphic pattern on another (right), as highlighted by CD20

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Prognosis Elderly patients with EBV+ DLBCL have a poor prognosis with median overall survival ranging from 24 to 36 months, even after being treated with R-CHOP [2, 5–7, 23]. The estimated 2-year overall survival was reported to be 40 ± 10%, and the estimated 2-year progression-free survival was 36 ± 9%. In younger patients, the clinical outcome and response to therapy are significantly superior compared to the elderly [10, 11]. Novel therapies targeting CD30, PD-1, Btk or NF-KB components, histone deacetylase (HDAC) inhibitor, EBV specific T cells, or CAR-T therapy may improve outcomes [24, 25].

EBV Virology EBV is a human member of the gammaherpesvirus (HHV4) composed of 170 kb double-stranded DNA. Human EBV infection usually occurs in three phases, the lytic phase, latent phase, and reactivation phase. The virus enters the epithelia of the oropharyngeal mucosa during primary infection, causing cellular destruction and lytic viral replication. The virus also enters the surrounding lymphoid tissue’s naïve B cells by binding to the CD21 receptor and human leukocyte antigen class II (HLA-2) molecules [25, 26]. The infected B cells then transit through the germinal centers and differentiate into quiescent memory B cells, where the virus establishes a latent phase. During the latent phase, the virus exists as an episome, replicates using host B cells’ machinery, and expresses limited viral antigens, escaping the host immune attack. Viral reactivation may occur due to antigen stimulation in resting memory B cells but is promptly eliminated in immunocompetent hosts. Thus, most individuals carrying the latent viral genome remain asymptomatic. However, in individuals with impaired immunity and chronic antigenic activation, the resting B cells may undergo malignant transformation, resulting in unchecked proliferation [26]. EBV virus contains six nuclear antigens [EBNA1, 2, 3A, 3B, and 3C and EBNA leader protein (EBNA-LP)]; three latent membrane proteins: LMP1, two isoforms of LMP2 (LMP2A and LMP2B), and EBV-encoded small RNAs (EBER1 and EBER2) and two families of microRNAs (BHRF1- and BARTs). EBNA1 is the viral genome maintenance protein. EBNA-LP is a transcriptional activator/regulator. Depending on the expression pattern of viral genes and their products, three latency patterns are recognized: I (expresses EBNA1, EBERs, microRNAs), II (expresses EBNA1, EBERs, microRNAs, LMP1 and LMP2A and B), or III (full latent gene expression) [27–29]. Different latency patterns are observed in various types of EBVassociated B cell LPDs and lymphomas (Table 15.1) [30]. Cases of EBV+ DLBCL arising in elderly patients and the Asian population tend to display latency III infection (EBNA2), suggesting tumors grow due to “immunosenescence” in these populations, particularly the elderly. Immunosenescence is related to diminished T and B cell

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Table 15.1  Different latent patterns of Epstein–Barr virus in EBV-associated lymphoma EBV latent type I Wp-restricted II

III

EBV latent genes expressed EBNA1, EBERs, BARTs EBNA1, EBNA3A/B/C/LP EBNA1, LMP1, LMP2A, LMP2B, EBERs, BARTs EBNA1, LMP1, LMP2A, LMP2B, EBNA2, EBNA3A/B/C/LP, EBERs, EBV-miR-BHRF1/BARTs

Diseases BL, PEL BL CHL, NK/T cell lymphomas, EBV + DLBCL (subset), PBL (subset), LyG (subset), PTLD (subset) DLBCL with CI, AIDs-related NHL, PTLD, LyG, EBV+ DLBCL (subset)

BL Burkitt lymphoma, CHL classic hodgkin lymphoma, CI chronic inflammation, DLBCL diffuse large B-cell lymphoma, EBV epstein-barr virus, EBNA epstein-barr nuclear antigen, EBER epsteinbarr encoded RNA, LMP latent membrane proteins, LyG Lymphomatoid granulomatosis, NHL Non-Hodgkin lymphoma, PEL primary effusion lymphoma, PTLD post-transplant lymphoproliferative disorder

functions such as reduced T cell repertoire, including anti-EBV cytotoxic T cells, and reduced cytokine activities associated with aging. By contrast, EBV-positive DLBCLs in younger patients and Western populations are more frequently associated with a latency II (positive for LMP1 and lack of EBNA2) pattern, suggesting an alternative mechanism of lymphomagenesis as chronic antigen stimulation [1, 9, 14].

Pathways Affected in EBV-Positive DLBCL Unchecked growth and immortalization of EBV-positive lymphoma cells are driven by disrupted cellular mechanisms regulating cell cycle, apoptosis, and ineffective immune response of host cells. (Table 15.2, Fig. 15.5) Several viral oncoproteins and viral miRNAs can activate oncogenes such as BCL2 and MYC while inhibiting tumor suppressors such as p53, leading to activation of multiple signaling pathways, with enhanced survival and suppressed apoptosis. NF-KB is the primary pathway involved, but other pathways such as JNK (c-Jun N-terminal kinase/AP-1), the MEK (MAPK/ ERK) pathways, c-Jun N-terminal kinase (JNK), p38/mitogen-­ activated protein kinase (MAPK), and Janus kinase (JAK) signal transducers and activators of transcription (STAT) are also activated [31]. The precise mechanism is still a subject of an ongoing investigation, but the roles of several well-studied oncogenic viral products are well established. Below is a summary of the current knowledge of pathogenesis.

Proliferative and Survival Pathways LMP1 and LMP2A, and B are signal transducers. LMP1 functions as the significant oncoprotein that mimics CD40 receptor, a member of TNFR superfamily regulating a wide range of immune responses, including B-cell activation and proliferation. LMP1 has a short N terminal, six trans-membrane spanning regions, and a long C

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Table 15.2  Pathogenic pathways in lymphomagenesis of EBV-associated lymphoma Functional Gene (FG)/ protein Oncogenes MYC

BCL2

Functional gene responsibility

EBV latent genes (ELG)

Cell cycle regulation (promotor of G1/S transition)

LMP2A, EBNA2, LMP2A, EBNA3A/C: EBNA3A, EBNA3C Upregulation EBNA2: Directly activates LMP1 and c-Myc. LMP1/2A, EBER, Upregulation of BCL2, EBNA2/3A/3C, inhibition of BCL6 (releases EBV-miRNAs BCL2), encode BCL2 homologs

Apoptosis (inhibitor)

Tumor suppressors ARF/ p14 Cell cycle regulation/ apoptosis E2F1/ Cell cycle regulation p16INK4A/ Rb CIP1/ p21WAF1

CDKN1B/ p27kip1

TP53

Cell cycle regulation (inhibitor of G1/S transition)/ inhibit cyclin A/E/CDK2 Cell cycle regulation (inhibitor of S/G2 and G2/M transition)/ inhibit cyclin A-E/CDK2 Apoptosis

Effect of ELG on FG

EBNA3A, 3C

Epigenetic repression

LMP1, EBNA3A, 3C

LMP1: Regulates telomerase activity (promote cell immortalization). EBNA3A, 3C: Epigenetic repression. EBNA3C causes proteasomal degradation of p21 by Pim-1.

EBNA3C

LMP2A, EBER, EBNA3A, 3C

LMP2A: Degradation. EBNA3A & C: Epigenetic repression.

LMP2A, EBNA1, EBNA3C

Bypass p53 by expression of oncogenes, degrade p53, inhibits transcription of p53

terminal, which contains two domains named C-terminal activation region 1 (CTAR1) and CTAR2, also known as transformation site 1 (TES1) and transformation site 2 (TES2), respectively. CTAR1 interacts directly with tumor necrosis factor receptor (TNFR)-associated factors (TRAFs) while CTAR2 interacts with death-­ domain-­containing protein TRADD, which in turn activates NF-KB [32–36]. The process starts with the aggregation of LMP1 transmembrane domains followed by constitutive activation of the receptor and activation of both classical and alternative NF-KB pathway with the generation of p50–p65 heterodimers and p52–p65 heterodimers, respectively. CTAR2 also activates the JNK pathway via a TRAF2dependent pathway. P38/MAPK pathway activation is independent of NF-KB pathway activation but converges with the NF-KB pathway at TRAF2. LMP1 also activates JAK/STAT, the pathway through the interaction of CTAR3 with JAK3 to enhance JAK3 tyrosine phosphorylation. CTAR3 is an intermediate region between CTAR1 and CTAR2 [32, 35]. PI3K/AKT is activated indirectly by suppressing a sphingosine-1-phosphate (S1P) receptor S1PR2, a molecule that inhibits PI3K/AKT pathway activation [36, 37]. LMP2A contains a cytoplasmic amino-terminal domain that has an immunoreceptor tyrosine-based activation motif (ITAM). The phosphorylated ITAM negatively

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LMP2A

LMP1

LMP1

LMP2A

BFL1

BCL6

BCL2

EBNA1

EBNA3C

S1 PR2

TRAFS

PI3K BTK

LYN

P P

SYK

ITAM

EBNA3A/B

Epitope

CTAR1

EBNA2

LMP1

MHC-1

PD-L1

PD-1

Immune escape pathway

T-cell receptor

T - Cell

NEDD4

P P

Ras

AKT

P27 G1

Cyclin B-D CDK4/6

M

S

Cyclin A-E CDK2

CTAR2

P53

P21 MYC

CTAR3

P16 JaK/STAT

MAPK

JNK ERK TRAF2

IKKα NF-Kβ

COOH

P38

TRADD

ubiquitination of LMP2A

NH2

G2

Cell cycle progression and anti-apoptotic pathways

Proliferative and survival pathways

Fig. 15.5  Epstein–Barr virus latent membrane proteins (LMP1, LMP2A) and nuclear antigens (EBNA1, 2, and 3) contribute to dysregulating three significant pathways in infected lymphoma cells. These three pathways are proliferative and survival pathways (pink color), cell cycle progression & anti-apoptotic pathways (blue color), and immune surveillance/escape pathways (violet color). These increase pro-survival signals, suppress pro-apoptotic proteins, and increase the possibility of infected cells escaping from the immune system. ┴: Inhibitory effect; ↓: Stimulatory effect

regulates SRC family activities of protein tyrosine kinase and SYK tyrosine kinase activities [24, 38–40]. LMP2A also activates the Ras/PI3K/Akt pathway [24, 41]. LMP2A mimics active B-cell receptors (BCR) and rescues B cells deficient in BCR from apoptosis. The enhanced BCR signaling further activates the NF-KB cascade [39, 42–44]. LMP2A requires the early signaling molecules of the SYK/RAS/PI3K pathway to increase IL-10. The binding of IL-10 to its receptors activates STAT3 signaling. PI3K-regulated kinase BTK is ultimately responsible for phosphorylating STAT3. Thus, LMP2A signaling results in STAT3 phosphorylation in B cells through a PI3K/BTK-dependent pathway [45]. EBNA1 maintains viral DNA replication during the latent phase and is expressed in all EBV-associated lymphomas. The exact oncogenic function is unknown. The oncogenic role of EBNA2 and EBNA-LP is better understood. EBNA2 mimics Notch functionally and affects cell cycles. It also activates the NF-KB and AKT pathways by inducing miR-21 and downregulating miR-146a, respectively [24, 46]. Activation of ERK1/2 and AKT pathway increases the expression of B7-H4, which in turn enhances cell survival by inhibiting apoptosis [47]. Other mechanisms for activation of the NF-KB and JAK-STAT pathways include tumor cells’ interaction with their microenvironment. The interaction may activate NF-KB via the TOLL-like receptor (TLR) pathway and nucleotide-binding

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oligomerization domain (NOD)-like receptor signals. The interactions also lead to increased production of IL6, which activates the JAK-STAT pathway, allowing “cross-talk” between NF-KB and JAK-STAT pathways [36, 48, 49]. Furthermore, similar to other ABC types of DLBCL, CARD11 mutation in EBV + DLBCL also activate NF-KB signaling [44].

Cell Cycle Progression and Anti-Apoptotic Pathways LMP1 induces BCL2 expression in infected B cells, thereby inhibiting their apoptosis [29, 32, 50, 51]. Activation of the NF-KB pathway leads to the expression of pro-survival proteins, including BCL-XL, cIAP1, cIAP2, and c-FLIP, conferring chemoresistance. LMP2A increases BCL-XL expression to bypass p53 and activates the Ras/PI3K/Akt pathway to enhance B-cell survival [24, 41, 52]. It also potentiates MYC-induced cell growth by downregulating p27 in a proteasome-dependent manner [53]. LMP1 regulates telomerase activity through the p16INK4A/Rb/E2F1 signaling pathway to promote cell immortalization. LMP1 and LMP2A also activate the expression of HLX via STAT3. HLX is a member of the NKL homeobox gene family products that inhibits plasma cell differentiation and decreases the pro-apoptotic factor BCL2 L11/BIM [54]. LMP2A collaborates with C-MYC to promote G1/S transition through promoting the expression of cyclin D. EBNA1 can interact with herpes virus-associated ubiquitin-specific protease (HAUSP/USP7) and degrade p53 to inhibit apoptosis [29, 55]. EBNA2 also upregulates BFL1/A1 (a pro-survival BCL2 family protein) [32, 56], as well as MYC and cyclin D2 [57–60]. EBNA-LP acts as a transcriptional coactivator for EBNA2. EBNA3A, 3B, and 3C belong to a family of proteins that regulate viral and host cell gene transcription by interacting with transcription factors. EBNA3A obstructs the E2F1-mediated apoptosis [29, 61]. EBNA3B is essential for transformation. EBNA3C prevents the degradation of MDM2 and uses it to degrade p53 [29, 61]. It also interacts with BCL2 and BCL6 to suppress apoptosis [62]. EBNA3A and 3C jointly suppress tumor suppressors p15INK4b, p16INK4a, and p14ARF, promoting cell proliferation and prevent cell death [63]. These activities are associated with increased H3K27me3 modification at the CDKN2A promoter [16, 63, 64]. EBNA3C interacts with IRF4 and IRF8 proteins to potentiate the oncogenic activity of IRF4 in EBV- transformed B cells [65]. EBNA3C stabilizes IRF4 through inhibition of its degradation by ubiquitin. IRF4, in turn, targets IRF8 and induces its subsequent degradation. The sustained activation of IRF4 allows propagation of downstream signaling to enhance MYC’s expression, Cyclin B1 and CDK6, while inhibiting IRF8-mediated growth suppression and apoptosis. EBNA3C can also directly bind to p53 and inhibit its transcriptional activity [28, 66]. EBV miRNAs target pro-apoptotic proteins BIM and PUMA, thereby enhancing the survival of the infected B cells [32, 67]. BHRF1 and BALF1 encode BCL2 homologs and inhibit apoptosis [29]. EBV-miR-BARTs can also target caspase 3, thereby inhibiting apoptosis. EBV-miR-BARTs downregulating LMP2A and

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promote cell proliferation by down-regulating Wnt’s inhibitory gene and tumor suppressor PTEN. Other lytic genes are detected that contribute to DNA damage response and genomic instability [29, 68]. BCL6, BACH2, PRDM1, and IRF4 are targeted directly or indirectly by EBV [54].

Impaired Immune Surveillance As a homology to CD40, LMP1 has immunomodulatory abilities by inducing PD-L1 [25, 69]. The tumor cells nearly universally express PD-L1 in EBV+ DLBCL compared to only 11% of EBV- DLBCL [70]. The binding of PD-L1 to PD-1 on T cells may lead to an immunosuppressive microenvironment, allowing tumor cells to evade immune surveillance, even in immunocompetent hosts [11, 70]. EBV-positive DLBCL shows a similar T-cell gene expression compared to EBV-negative DLBCL but higher levels of antigen-presenting molecule B2M. The tumor also shows an elevated expression of PD-L1, PD-L2, LAG3, and TIM3 immune checkpoints and higher CD163/CD68 “M2” macrophage scores [25]. These findings suggest that, at least in part, the immune evasion may be related to an altered microenvironment induced by EBV [25]. EBNA1 can suppress antigenic peptides combined with major histocompatibility complex 1 (MHC-1) by restricting its mRNA translation. EBNA1 can also result in changes in MHC I antigen processing via the ubiquitin-proteasome pathway [71]. The altered antigen expression allows the tumor cells to escape cytotoxic T lymphocytes (CTL) [72, 73]. Moreover, EBNA1 can prevent the degradation of lytic enzymes and CTL activation [72, 74]. EBNA2 interacts with EBF1, a negative regulator of tumor suppressor miR-34a. EBNA2 increases PD-L1 by downregulating miR-34a [57]. EBNA2 directly interacts with the cellular RBPJK DNA binding protein (also known as CBF1, which usually mediates intracellular Notch binding) to produce a Notch-like signal [59, 75]. In a mouse model with EBNA3C-deleted virus, tumor cells still expressed the anti-apoptotic proteins, BCL2 and IRF4, cell cycle activators, C-MYC, and cyclin E.  These results suggested that EBNA3C may have immune-modulatory effects in vivo [59]. Finally, BDLF3, EBV lytic gene, can promote the degradation of MHC class I and II molecules [76].

Cytogenetics Specific cytogenetic and genomic aberrations have not been identified in EBV + DLBCL [17]. However, various abnormalities have been described. Copy number gains have been reported in the MYC, BCL2, and BCL6 loci. Approximately

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15% may carry IGH translocation, but an overall rearrangement of IGH, MYC, BCL2, and BCL6 are infrequent [16, 77]. The genetic aberrations often overlap with those in plasmablastic lymphoma (PL) with the involvement of 1p36, 17p13, 10q26, and 20q13 [44]. Frequently, chromosomal gains at 9p24.1 and 1q23.2–23.3 are detected which may contribute to increased expression of PDL1/PDL2 and SLAMF1, respectively [78]. The most frequent copy number amplification (>30%) is gained at 1q23.2–23.3, 1q23.3, 1q32.1, 5p15.3, 8q22.3, 8q24.1–24.2, and 9p24.1. Losses at 6q27, 7q11.2, and 7q36.2–36.3 are also recurrent abnormalities observed [78]. Overall, cytogenetic aberrations seem to be less frequent in EBV+ DLBCL than EBV- DLBCL, suggesting that EBV is the primary driver of the process.

Genetic and Molecular Alterations Monoclonal rearrangements of IGH and IGK or IGL are demonstrable in 64% of cases [16, 27]. In about 20–25% of cases, monoclonal/oligoclonal TCR rearrangement can be detected, possibly related to the reduced T cell diversity associated with aging [16]. Recent genomic studies found the most common recurrent mutations involving MYC and RHOA, affecting cell cycle, followed by PIM1, CARD11, MYD88, and PRDM1 affecting NF-KB pathway components together were identified in 65% cases of EBV+ DLBCL [77]. Alterations of genes involved in epigenetic regulation signaling pathways (15%) and B cell receptor signaling (10%) pathways are less common compared to KMT2D (66%) and CREBBP (50%) in EBV- DLBCL. When NF-kB signaling is constitutively active, inactivating point mutations, deletions, or epigenetic silencing of the PRDM1 gene allow cells to accumulate at the plasmablastic stage [26, 78]. Genetic aberrations involving BCL2, BCL6, MYC, MDM2, MDM4, and TP53 are observed in 5 ~ 11% [17]. LNP1, PRSS3, MUC3A, FADS6, and TRAK1 are the most commonly mutated genes by Sanger sequencing [13]. EZH2 mutation is uncommon [44]. Data regarding MYD88/CD79B, and CARD11 mutations are controversial and inconsistent [13, 44, 77, 79]. GEP confirms activation of NF-KB and JAK-STAT, and pathways are characteristic of EBV+ DLBCL in elderly patients [36]. Genes involved in immune and inflammatory pathways are also differentially expressed. An association with apoptotic/cell cycle signaling pathway, epigenetically related, and B cell receptor signaling pathways have also been identified in different studies [29, 77].

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Chapter 16

Lymphomatoid Granulomatosis Christian Salib and Julie Teruya-Feldstein

Introduction Lymphomatoid granulomatosis (LYG) is an Epstein Barr virus large B cell lymphoma, rare extranodal lymphoid B cell neoplasm that occurs primarily in the lungs, can involve the brain, kidney and skin, remaining in the WHO fifth edition and International Clinical Consensus (ICC) [1, 2]. First described in 1972 by Liebow et al. in a case series of 80 patients, the title of this condition is a misnomer as granulomas are usually not observed. Rather, the name was attributed to its similar clinical presentation as other granulomatous conditions, such as eosinophilic granulomatosis with polyangiitis (Churg Strauss syndrome) and granulomatosis with polyangiitis (Wagener’s syndrome) [3]. Twenty years following its description, LYG was found to be driven by clonal proliferation of Epstein-Barr virus (EBV)positive B lymphocytes admixed in a predominant background of reactive T lymphocytes [4]. While the exact mechanism of disease is not completely understood, it is hypothesized that cytokines, released by EBV-infected B cells, recruit CD8+ cytotoxic T cells that result in vascular damage, via chemokines, cytokines from an in vivo murine model and in vitro data [5–8].

C. Salib Department of Pathology, Molecular, and Cell-Based Medicine, Mount Sinai at Icahn School of Medicine, New York, NY, USA e-mail: [email protected] J. Teruya-Feldstein (*) Department of Pathology, Molecular, and Cell-Based Medicine, Mount Sinai at Icahn School of Medicine, Tisch Cancer Center, New York, NY, USA Histowiz ACLIC, New York, NY, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_16

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Epidemiology The exact prevalence of LYG is unknown, with roughly 600 reported cases to date, most of which are derived from published case series [9–13]. This condition often presents in adulthood; however, it may be seen in children with immunodeficiency disorders. The median age at diagnosis is 30–50 years, with a male-to-female ratio of ≥2:1 [10]. No racial predisposition has been well-established. LYG has been reported more commonly in Western countries than in Asia [14].

Clinical Presentation LYG characteristically affects immunocompromised patients, including predisposing conditions such as HIV infection, allogenic organ transplantation, rare hereditary T-cell deficiencies, Wiskott–Aldrich syndrome (eczema-thrombocytopenia-immunodeficiency syndrome), post-ablation chemotherapy, autoimmune diseases, and in patients with rheumatoid arthritis treated with methotrexate (tetrahydrofolate reductase inhibitor) [15]. As the host immunologic response becomes impaired (environmental or genetic risk factors), EBV-positive B cells proliferate and eventually lead to the development of an independent malignant clone [4]. Moreover, viral proteins that normally stimulate a cytotoxic T cell response appear deficient [16]. Sordillo et  al. found evidence of this ineffective immune response to EBV-infected cells, proposing this pathobiology of LYG as early as 1982 [17]. LYG has been reported in immunocompetent patients, with the majority of cases (90%) experiencing dyspnea and chronic cough from several months to years [8]. Patients often clinically present with non-specific respiratory tract symptoms that wax and wane over time, including chest pain, dyspnea and cough. Fever, weight loss and potentially life-threatening hemoptysis can develop in severe cases [16]. Ear, nose and throat manifestation has been documented in 10–30% of cases or with oral ulceration [18, 19], which can mimic signs and symptoms of granulomatosis with polyangiitis (Wegener’s granulomatosis) [20]. In such cases, evaluation for c-ANCA may help differentiate the two entities (LYG being c-ANCA negative). Infectious etiologies, such as histoplasmosis or coccidioidomycosis, must also be ruled out before a diagnosis of LYG can be confidently given. Extra-pulmonary manifestations include malaise, fever, weight loss, arthralgias, myalgias and gastrointestinal symptoms. Renal involvement has been shown in 10–40% of cases, commonly presenting as a large mass on CT imaging [21]. However, patients typically show no evidence of renal insufficiency of proteinuria. Central nervous system (CNS) involvement has also been reported with varying presentation depending on the site of CNS involvement. Symptoms range from asymptomatic to diplopia, hearing loss, ataxia or altered mental status [22, 23]. Lymph node and hepatosplenic involvement is uncommon in LYG. Bone marrow

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involvement is extremely rare, while heart and adrenal gland involvement remains unknown [24]. Finally, LYG can occur concurrently with other neoplasms [25–27].

Clinical Laboratory Findings In more than 50% of cases, the complete blood count (CBC) is within normal limits; however, lymphopenia or hyperleukocytosis has been previously documented. Nearly half of the patients with LYG present with hypergammaglobulinemia [23]. In some cases, hyperesoinophilia has been reported [9]. Testing for EBV serology should be performed, including testing for EBV viral load. In a study by Song et al., EBV viral load was non-specifically elevated in a cohort of 55 cases, with a median of 18 copies/106 genome equivalents [23]. Most of those patients (94%) had evidence of prior EBV infection confirmed by viral capsid antigen for IgG (VCA-IgG).

Radiologic Findings Radiographic evaluation may visualize the disease process; however, the findings are non-specific. A chest computerized tomography (CT) scan may detect multiple ill-defined lung nodules of varying sizes (80% of cases) predominantly affecting the lower lung fields. The nodules range from 0.5 to 10 cm in size and have a preferential basal localization, with a peribronchiovascular and interlobular distribution [8, 28]. Nodules are often bilateral in distribution. However, hilar lymphadenopathy is rare [29]. In a study by Chung et al., it has been reported that the nodules present with ground-glass halos and peripheral enhancement, historically considered specific to angioinvasive aspergillosis [30, 31]. Given the angiodestructive nature of LYG, the peripheral enhancement likely represents hemorrhage [30]. Anatomical-radiological studies have demonstrated that the nodules rapidly coalesce to form larger mass lesions, frequently exhibiting central necrosis and lung parenchymal cavitation that radiologically closely resembles metastasis or granulomatous polyangiitis [16]. Fluorodeoxyglucose (FDG)-positron emission tomography (PET) scans typically show avid uptake in these lesions [29]. Some studies have shown cases where lung nodules larger than 2 cm failed to show FDG-uptake, likely due to the increased central cavitary necrosis [30]. PET-scans may also identify renal, skin and CNS involvement, and can be used as an adjunct modality in evaluating disease response to therapy.

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Pathology A definitive diagnosis of LYG requires histologic evaluation. A surgical lung biopsy with adequate sampling of lung tissue is the preferred method for a histologic assessment and appropriate grading of LYG.  While endobronchial sampling is a less invasive alternative, samples obtained through this modality have a much lower yield and rarely allow for a definitive histologic diagnosis [16]. This is, in part, due to the bronchocentric and focal nature of the disease. A tissue diagnosis from a more easily accessible site like the skin may be obtained, if involved. However, since LYG displays varied tumoral infiltration and heterogeneous EBV staining patterns, it is recommended to biopsy all accessible sites for a more complete and definitive diagnosis [9]. It has been reported that bronchioalveolar lavage (BAL) cytology may show hypereosinophilia, but this lacks specificity and may be seen in other conditions, such as asthma, drug reactions or parasitic infections.

Macroscopic Findings The most common primary site of involvement is the lungs, occurring in >90% of affected patients; however, synchronous extra-pulmonary involvement is not uncommon, involving the skin (50%), central nervous system (25%), kidneys and liver [9]. Gross examination of explanted lung specimens shows multiple bilateral, ill-defined nodules often necrotic with a central cavitation. In patients with extrapulmonary manifestations, similar nodular lesions can be found in the brain and kidney [14]. More challenging are skin lesions, which are extremely diverse in appearance and occur in 30–50% of cases [12]. There have been reported cases of subcutaneous and dermal nodularities; less commonly cutaneous plaques or maculopapular rash develop predominantly over the trunk and extremities [12, 32].

Microscopic Findings and Immunophenotype The classic histologic hallmark of LYG is nodular replacement of lung parenchyma by relatively well-delineated lesions of polymorphous lymphoid with vascular invasion of small to medium-sized pulmonary arteries and veins [8]. Necrosis is often present and varies from extensive central necrosis surrounded by a rim of viable cells to small foci within dense cellular infiltrates. The cellular infiltrate is composed of predominantly small reactive CD3+ T lymphocytes, with a predominance of CD4+ cells over CD8+ cells [23]. Occasional plasma cells and alveolar macrophages may be present. Neutrophils and eosinophils are usually inconspicuous. Variable number of large atypical B lymphoid cells are seen, frequently within the necrotic areas or concentrated within the walls of blood vessels, and occasionally

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show significant cytologic atypia with one or more atypical nuclei [33]. The atypical EBV-positive large cells express CD45, CD20, PAX5 and CD79a. They can vary in size and resemble lymphocytes, immunoblasts or even Hodgkin-Reed Sternberg (HRS) cells. Variable expression of CD30 is seen, but the cells are negative for CD15, which is a useful finding to differentiate LYG from HRS cells seen in classic Hodgkin lymphoma. Vascular infiltration is often prominent and preferentially affects the intimal layer, appearing thickened from the cellular infiltrate and associated luminal narrowing. Direct vascular damage in the form of fibrinoid necrosis is common. According to prior work by the author, vascular damage is most likely a result of chemokine production induced by EBV-positive cells [5, 6]. The necrosis, which is often coagulative-type, contains nuclear debris but lacks neutrophils – a finding that aids in differentiating LYG from granulomatosis with polyangiitis, which is characteristically neutrophil-rich [34]. More recent studies by Katzenstein et  al. further propose that although LYG has been described as ‘angiocentric, the disease process does not center around blood vessels but that they are secondarily involved by the cellular infiltrate, which randomly affects lung parenchyma [10]. Due to the angiodestructive properties of LYG, it is important to distinguish LYG from nasal-­ type extranodal NK/T-cell lymphoma, which also presents with angiodestruction and is EBV-associated [35]. Several studies have examined the clonality of the atypical large B cells; however, the total number of reported cases is few. While these neoplastic large B cells are monoclonal, clonal analysis by flow cytometry or immunohistochemistry is not required for the diagnosis. Conversely, in situ hybridization for EBV-encoded RNA (EBER) is a diagnostic feature in these cells. Unfortunately, in some cases, the results are negative, particularly in biopsy specimens from skin lesions (up to 50% may be negative) [23], creating diagnostic challenges. Staining for the latent membrane protein of EBV (LMP1) may also be performed, although only 70% of LYG cases are positive [36]. Given their large morphology and positivity for CD30, these large atypical neoplastic B cells may be confused with plasmablasts, immunoblasts, or even Hodgkin/Reed-Sternberg cells [37]. As the disease progresses, vasculitis develops and produces areas of congestion and necrosis. Over time, a central cavitary lesion forms within LYG lesions, which is believed to be the result of coalescing smaller nodules to form a larger mass [16]. The surrounding lung parenchyma is typically uninvolved and benign-appearing [37]. Unlike the name suggests, well-formed granulomas are typically absent in the lung and extranodal sites, although skin lesions may show granulomatous reactions within the subcutaneous tissue [12]. Multinucleated giant cells are usually not seen. In all cases of suspected LYG, an infectious etiology must first be excluded, as well as Hodgkin or other aggressive lymphomas, especially in  localized and unifocal diseases. In many instances, differentiating LYG from granulomatosis with polyangiitis and necrotizing sarcoidosis may prove challenging, whereby clinical correlation becomes critical to aid in accurate diagnosis.

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Tumor Grading LYG grading is essential to guide patient therapy and help inform prognosis. According to the World Health Organization (WHO) Classification of Tumours of Hematopoietic and Lymphoid Tissues, LYG is histologically classified into a 3-tier grading system, based on the proportion of EBV-positive B cells relative to the background reactive lymphocytes in the tumor sample [14, 38, 39]. The more large, atypical cells present in the sample, the higher the LYG grade. According to the most recent WHO classification, grade 1 LYG is composed of a polymorphous cell population with absent or rare large atypical lymphoid cells and less than 5 EBV-­ positive cells per high-power field by in situ hybridization (ISH). Grade 2 LYG contains occasional large atypical lymphoid cells that may form small clusters with a background of polymorphous cells with 5 to 20 EBV-positive large cells per highpower field. In grade 3 LYG, large, atypical B cells are readily identified and may be arranged in larger aggregates, with EBV-positive cells comprising greater than 50 cells per high-power field. Of note, the presence of extensive necrosis may result in an underestimation of the number of EBV+ cells. In grade 3 LYG, the large cells may focally form sheets. However, in cases displaying a more uniform population of large atypical EBV-positive B cells and without other characteristic features of LYG, a diagnosis of EBV+ diffuse large B-cell lymphoma, not otherwise specified may be more appropriate [14] (Fig. 16.1). In general, LYG grading has been shown to correlate with patient mortality. In a large study of 152 cases by Katzenstein et al., mortality rates ranged from 48% in cases with no atypical cells (grade 1 LYG) to 81% in cases containing greater than a

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Fig. 16.1  Histology of LYG involving lung showing vascular angioinvasion in panels (a, b) at 4× and 10× showing a polymorphous lymphoplasmacytic infiltrate in panels (c, d) at 20× and 40× with scattered EBER1 positive cells in panel (e)

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Fig. 16.2  Histology of LYG in a pediatric patient, 4-year-old and brain needle core biopsy inset at 2× showing focal vascular angioinvasion and an atypical lymphohistiocytic infiltrate at 40×

50% atypical lymphoid cells (grade 3 LYG) [11]. Furthermore, grading LYG is often challenging due to tumor heterogeneity. The appearance of inflammatory infiltrate often varies between concurrent tumors at different anatomical sites, and even within the same tumor at a single site. Therefore, adequate sampling is essential for accurate grading. Needle core biopsies can be especially challenging particularly in the CNS and pediatric population as they may be challenging to differentiate from primary EBV infections (Fig. 16.2).

Genetic Profile and Susceptibility In most cases of LYG, clonality of the immunoglobulin (IG) gene can be demonstrated by molecular genetic techniques [40]. As many as 60% of cases can demonstrate clonality when evaluated by polymerase chain reaction (PCR) techniques [41]. Gene rearrangement studies have included single-stranded conformation polymorphism (PCR-SSCP) analysis for use on both small frozen specimens and formalin-­fixed, paraffin-embedded (FFPE) tissue, allowing for detection of lower numbers of malignant cells with monoclonal infiltration [42]. Historically, southern blot analysis was used to detect clonality for EBV [43]. Clonality in grade 1 LYG is much less consistent than in grades 2 and 3, based on the rarity of EBV-positive large atypical cells in these cases. Nevertheless, polyclonal cases of LYG have been reported in the literature [23]. While T cell clonality is a rare phenomenon, it may be seen as a reactive T cell response in patients with an underlying autoimmune disease. There are no reports from next-generation or whole exome sequencing of LYG thus far. LYG has been described in patients with predisposing immunodeficiency states, including Wiskott-Aldrich syndrome, X-linked lymphoproliferative syndrome [14] and interleukin-2-inducible T-cell kinase (ITK) deficiency [44, 45].

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DOCK8 Deficiency Dedicator of cytokinesis 8 (DOCK8) deficiency is an autosomal recessive, combined immunodeficiency disorder that was initially described as an autosomal recessive variant of hyper IgE syndrome (AR-HIES) [46]. DOCK8-deficient patients are commonly of Turkish and Arabic descent, and typically occur in the setting of consanguity [47]. First described in 2004, DOCK8 is a relatively large gene on chromosome 9, comprising of 48 exons and spanning over 200 kilobases in length [48]. It is one of the DOCK180 family of exchange factors responsible for activating Rho-family GTPases involved in actin cytoskeleton regulation, and plays a pivotal role in cell division, survival, adhesion, migration, activation and differentiation [49, 50]. DOCK8 protein is expressed primarily on hematopoietic tissue, most commonly on lymphocytes [51]. It is believed that the elevated rates of EBV infection and early onset lymphomas in the setting of DOCK8 deficiency are likely due to impaired B, T and NK cell function [52]. Deficiency results in dysregulated host immune response and increases patient susceptibility for an infectious spectrum, including cytomegalovirus (CMV), herpes simplex virus (HSV), hepatitis A, B & C, and EBV [46, 53–57]. As with other immunocompromised states, the risk of developing EBV+ LYG is drastically increased. Due to its multiple and variable initial presentations, DOCK8 deficiency may result in underdiagnosis or delayed diagnosis, resulting in organ damage and worse clinical outcomes. In a study of 136 patients by Ayden et al., 50% mortality was observed by 20 years in patients with DOCK8 deficiency [58]. Patients are treated with stem cell transplantation [46, 53–55, 59–61].

Other Genetic Alterations No genetic alterations have been demonstrated to be neither sensitive nor specific for LYG. In a recent publication by Dugge et al. investigating the underlying molecular landscape of a patient with concurrent LYG, chronic myelomonocytic leukemia (CMML) and anaplastic large cell lymphoma (ALCL), sequencing of LYG showed up to 33.1% of cells harbored the SRSF2 (p.P95H) mutations and nearly 87.7% of cells harbored a TET2 (p.C1378R) mutation [26]. However, similar mutations were seen in samples of bone marrow involved by CMML and peripheral blood involved by ALCL. Further gene sequencing showed no germline mutations, suggesting that the three processes harbor genetic alterations arising from a common stem cell. Nevertheless, the relationship between TET2 and SRSF2 with LYG has yet to be studied further for more definitive correlation.

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Differential Diagnosis The differential diagnosis of LYG includes both inflammatory, infectious and EBVpositive B cell lymphomas [62, 63]. Both primary and secondary lymphomas involving the lung may mimic LYG with a polymorphous lymphocytic infiltrate, possible necrotic nodules and vascular infiltration [64]. For this reason, caution should be exercised before diagnosing LYG when there is a history of lymphoma, especially large-cell variants or Hodgkin disease. In cases without a known history of lymphoma, the morphologic features aided by immunohistochemistry and molecular studies are pivotal in distinguishing other types of primary lung lymphomas from LYG, including peripheral T-cell lymphomas (PTCL), natural killer T-cell lymphoma, anaplastic lymphomas and Hodgkin disease, all of which may present in the lung. Infectious etiologies should be excluded, including invasive aspergillosis and tuberculosis (TB). Inflammatory conditions, including granulomatosis with polyangiitis or inflammatory pseudotumors are possible diagnostic considerations. In the setting of prominent plasmacytosis, IgG4 related disease could be considered [65] or potential histiocytic lesions [66]. Post-transplant lymphoproliferative disorder (PTLD) is one of the main differential diagnoses when considering LYG. It is a heterogeneous group of lymphoproliferative disorders that develop following solid organ transplants or bone marrow allografts as a consequence of patient immunosuppression. These are frequently EBV-associated, particularly within the first year post-transplant [67]. These conditions are divided into four broad categories of disease based on their histologic features, which include non-destructive, polymorphic, monomorphic and Hodgkin-­ like PTLD.  There are reported cases of polymorphic PTLD in the lung that are histologically and immunohistochemically identical to LYG, showing EBV-positive B cells with a background of reactive mixed cytotoxic and helper T lymphocytes [68]. In such cases, the distinction between LYG and polymorphous PTLD cannot be made without a documented clinical history of prior solid organ transplant. Several EBV-associated lymphoproliferative conditions have also been described that show striking clinical, histologic or pathologic similarities with LYG [69]. The histologic findings of angiodestructive and angioinvasive lesion with abundant T lymphocytes with prominent necrosis are characteristic of extranodal NK/T cell lymphoma. This condition is positive for EBV in nearly 100% of cases; however, the EBV+ cells are T cells [14]. Co-expression of CD3, CD56 and cytotoxic markers are helpful in diagnosing this entity. Classic Hodgkin lymphoma may also present with EBV-positivity in the large, atypical Hodgkin/Reed-Sternberg (HRS) cells, with a mixed inflammatory background of lymphocytes, histiocytes, plasma cells and often abundant eosinophils. In such cases, CD30 and CD15 may be helpful for differentiation from LYG (CD15 negative) when coupled with a thorough examination of tissue morphology. Ultimately, a broad differential of potential EBV-­ associated lymphoproliferative disorders (LPDs) should be considered before making a diagnosis of LYG, including classic Hodgkin lymphoma, various forms of PTLD, EBV diffuse large B-cell lymphoma, NOS, primary effusion lymphoma,

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plasmablastic lymphoma, angio-immunoblastic T-cell lymphoma and extranodal NK/T cell lymphoma, nasal type [70].

Treatment and Prognosis/Predictive Factors LYG therapeutic recommendations and ongoing clinical trials are challenging, due to the rare nature of the disease. Historically, localized LYG has been treated with surgery or radiotherapy. Currently, treatment decisions are guided by tumor grading. Treatment for LYG grades 1 and 2 include interferon alpha-2, while grade 3 LYG treatment involves high-dose steroids with chemotherapy regimens like as CHOP (cyclophosphamide, hydroxydaunomycin, Oncovin, prednisolone), ICE (Ifosfamide, Carboplatin, Etoposide) and hyperCVAD (Cyclophosphamide, vincristine, doxorubicin and dexamethasone). Immunochemotherapy has also been implemented with variable success [4, 29, 38]. As a result of its known EBV association, the use of interferon-alpha and rituximab for treating LYG have gained popularity as alternative treatment modalities, as well as immunmodulation, immunochemotherapy, and transplantation [63, 71, 72]. The clinical course of LYG is highly variable. While some patients present with an indolent lymphoproliferative process, LYG commonly progresses to an aggressive clinical course, characterized by worsening symptoms and multi-organ involvement. In a study by Katzenstein et al., a retrospective series of 152 cases showed that 63.5% of patients died mainly within the first year of diagnosis, with a median overall survival of about 14 months [11]. Similar findings were reported in a more recent study of 42 patients by Koss et  al., with patients showing poor prognosis regardless of various therapeutic options [73]. Nevertheless, spontaneous remission has been documented [74] and complete clinical remission has been observed in up to 50% of patients receiving cyclophosphamide and steroids [75]. The remaining patients eventually developed disease-related complications, including EBV-­ positive diffuse large B-cell lymphomas. More recent clinical studies have demonstrated a 5-year overall survival rate of 70% when patients were treated with chemoimmunotherapy with dose-adjusted EPOCH-R and/or interferon [24]. In a recent single institutional study of 11 cases, Chavez et al. found that since 75% of their cases showed CD30-positivity, this may be a target for anti-CD30 immunotherapy Brentuximab vedotin [76].

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23. Song JY, Pittaluga S, Dunleavy K, Grant N, White T, Jiang L, et al. Lymphomatoid granulomatosis--a single institute experience: pathologic findings and clinical correlations. Am J Surg Pathol. 2015;39(2):141–56. 24. Roschewski M, Wilson WH. Lymphomatoid granulomatosis. Cancer J. 2012;18(5):469–74. 25. Lee S, Negoro E, Oki H, Imamura Y, Yamauchi T. Simultaneous presentation of Lymphomatoid granulomatosis and multiple myeloma in an Immunodeficient patient with rheumatoid arthritis. Intern Med. 2019;58(19):2845–9. 26. Dugge R, Kreipe H, Rosenwald A, Lehmann U, Moller P, Barth TFE, et al. Coincidence of lymphomatoid granulomatosis, chronic myelomonocytic leukemia, and anaplastic T cell lymphoma after methotrexate therapy for rheumatoid arthritis. Ann Hematol. 2019;98(2):515–7. 27. Rezvani S, Tominna M, Al-Katib S, Smith MD, Cousineau C, Al-Katib A.  Lymphomatoid granulomatosis in a patient with chronic lymphocytic leukemia and rapidly progressing Peribronchovascular pulmonary infiltrates. Case Rep Pulmonol. 2019;2019:9870494. 28. Hare SS, Souza CA, Bain G, Seely JM, Frcpc GMM, et al. The radiological spectrum of pulmonary lymphoproliferative disease. Br J Radiol. 2012;85(1015):848–64. 29. Sirajuddin A, Raparia K, Lewis VA, Franks TJ, Dhand S, Galvin JR, et al. Primary pulmonary lymphoid lesions: radiologic and pathologic findings. Radiographics. 2016;36(1):53–70. 30. Chung JH, Wu CC, Gilman MD, Palmer EL, Hasserjian RP, Shepard JA. Lymphomatoid granulomatosis: CT and FDG-PET findings. Korean J Radiol. 2011;12(6):671–8. 31. Kimura S, Ashizawa K, Matsuyama N, Kadota J, Kohno S, Hayashi K. Imaging of Wegener's granulomatosis: changes by serial chest CT. Nihon Kokyuki Gakkai Zasshi. 2002;40(2):171–6. 32. Jaffe ES, Wilson WH. Lymphomatoid granulomatosis: pathogenesis, pathology and clinical implications. Cancer Surv. 1997;30:233–48. 33. Guinee DG Jr, Perkins SL, Travis WD, Holden JA, Tripp SR, Koss MN. Proliferation and cellular phenotype in lymphomatoid granulomatosis: implications of a higher proliferation index in B cells. Am J Surg Pathol. 1998;22(9):1093–100. 34. Hoffman GS, Kerr GS, Leavitt RY, Hallahan CW, Lebovics RS, Travis WD, et al. Wegener granulomatosis: an analysis of 158 patients. Ann Intern Med. 1992;116(6):488–98. 35. Jaffe ES, Chan JK, Su IJ, Frizzera G, Mori S, Feller AC, et al. Report of the workshop on nasal and related Extranodal Angiocentric T/natural killer cell lymphomas. Definitions, differential diagnosis, and epidemiology. Am J Surg Pathol. 1996;20(1):103–11. 36. Sabourin JC, Kanavaros P, Briere J, Lescs MC, Petrella T, Zafrani ES, et al. Epstein-Barr virus (EBV) genomes and EBV-encoded latent membrane protein (LMP) in pulmonary lymphomas occurring in nonimmunocompromised patients. Am J Surg Pathol. 1993;17(10):995–1002. 37. Sohani ARaF, J.A.  Lymphomas and lymphoproliferative disesaes of the lung. Diagn Histopathol. 2014;20(10):405–14. 38. Wilson WH, Kingma DW, Raffeld M, Wittes RE, Jaffe ES.  Association of lymphomatoid granulomatosis with Epstein-Barr viral infection of B lymphocytes and response to interferon-­ alpha 2b. Blood. 1996;87(11):4531–7. 39. Taniere P, Thivolet-Bejui F, Vitrey D, Isaac S, Loire R, Cordier JF, et al. Lymphomatoid granulomatosis--a report on four cases: evidence for B phenotype of the tumoral cells. Eur Respir J. 1998;12(1):102–6. 40. McNiff JM, Cooper D, Howe G, Crotty PL, Tallini G, Crouch J, et al. Lymphomatoid granulomatosis of the skin and lung. An angiocentric T-cell-rich B-cell lymphoproliferative disorder. Arch Dermatol. 1996;132(12):1464–70. 41. Medeiros LJ, Jaffe ES, Chen YY, Weiss LM. Localization of Epstein-Barr viral genomes in angiocentric immunoproliferative lesions. Am J Surg Pathol. 1992;16(5):439–47. 42. Signoretti S, Murphy M, Cangi MG, Puddu P, Kadin ME, Loda M. Detection of clonal T-cell receptor gamma gene rearrangements in paraffin-embedded tissue by polymerase chain reaction and nonradioactive single-strand conformational polymorphism analysis. Am J Pathol. 1999;154(1):67–75. 43. Medeiros LJ, Peiper SC, Elwood L, Yano T, Raffeld M, Jaffe ES. Angiocentric immunoproliferative lesions: a molecular analysis of eight cases. Hum Pathol. 1991;22(11):1150–7.

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44. Cagdas D, Erman B, Hanoglu D, Tavil B, Kuskonmaz B, Aydin B, et  al. Course of IL-2-­ inducible T-cell kinase deficiency in a family: lymphomatoid granulomatosis, lymphoma and allogeneic bone marrow transplantation in one sibling; and death in the other. Bone Marrow Transplant. 2017;52(1):126–9. 45. Ghosh S, Bienemann K, Boztug K, Borkhardt A. Interleukin-2-inducible T-cell kinase (ITK) deficiency - clinical and molecular aspects. J Clin Immunol. 2014;34(8):892–9. 46. Dimitriades VR, Devlin V, Pittaluga S, Su HC, Holland SM, Wilson W, et al. DOCK 8 deficiency, EBV+ Lymphomatoid granulomatosis, and Intrafamilial variation in presentation. Front Pediatr. 2017;5:38. 47. Kaplan S, Pinar G, Kaplan B, Aslantekin F, Karabulut E, Ayar B, et  al. The prevalence of consanguineous marriages and affecting factors in Turkey: A National Survey. J Biosoc Sci. 2016;48(5):616–30. 48. Ruusala A, Aspenstrom P.  Isolation and characterisation of DOCK8, a member of the DOCK180-related regulators of cell morphology. FEBS Lett. 2004;572(1–3):159–66. 49. Su HC, Jing H, Zhang Q. DOCK8 deficiency. Ann N Y Acad Sci. 2011;1246:26–33. 50. Cote JF, Vuori K.  Identification of an evolutionarily conserved superfamily of DOCK180-­ related proteins with guanine nucleotide exchange activity. J Cell Sci. 2002;115(Pt 24):4901–13. 51. Lambe T, Crawford G, Johnson AL, Crockford TL, Bouriez-Jones T, Smyth AM, et al. DOCK8 is essential for T-cell survival and the maintenance of CD8+ T-cell memory. Eur J Immunol. 2011;41(12):3423–35. 52. Mizesko MC, Banerjee PP, Monaco-Shawver L, Mace EM, Bernal WE, Sawalle-Belohradsky J, et al. Defective actin accumulation impairs human natural killer cell function in patients with dedicator of cytokinesis 8 deficiency. J Allergy Clin Immunol. 2013;131(3):840–8. 53. Dimitrova D, Freeman AF. Current status of dedicator of cytokinesis-associated immunodeficiency: DOCK8 and DOCK2. Dermatol Clin. 2017;35(1):11–9. 54. Al Shekaili L, Sheikh F, Al Gazlan S, Al Dhekri H, Al Mousa H, Al Ghonaium A, et  al. Novel mutation in DOCK8-HIES with severe phenotype and successful transplantation. Clin Immunol. 2017;178:39–44. 55. Biggs CM, Keles S, Chatila TA. DOCK8 deficiency: insights into pathophysiology, clinical features and management. Clin Immunol. 2017;181:75–82. 56. Buchbinder D, Kirov I, Danielson J, Shah NN, Freeman AF, Chavan RS, et al. Compound heterozygous DOCK8 mutations in a patient with B lymphoblastic leukemia and EBV-associated diffuse large B cell lymphoma. J Clin Immunol. 2019;39(6):592–5. 57. Kim D, Uner A, Saglam A, Chadburn A, Crane GM. Peripheral eosinophilia in primary immunodeficiencies of actin dysregulation: A case series of Wiskott-Aldrich syndrome, CARMIL2 and DOCK8 deficiency and review of the literature. Ann Diagn Pathol. 2019;43:151413. 58. Aydin SE, Kilic SS, Aytekin C, Kumar A, Porras O, Kainulainen L, et al. DOCK8 deficiency: clinical and immunological phenotype and treatment options - a review of 136 patients. J Clin Immunol. 2015;35(2):189–98. 59. Cuellar-Rodriguez J, Freeman AF, Grossman J, Su H, Parta M, Murdock H, et al. Matched related and unrelated donor hematopoietic stem cell transplantation for DOCK8 deficiency. Biol Blood Marrow Transplant. 2015;21(6):1037–45. 60. Freeman AF, Yazigi N, Shah NN, Kleiner DE, Parta M, Atkinson P, et al. Tandem Orthotopic living donor liver transplantation followed by same donor Haploidentical hematopoietic stem cell transplantation for DOCK8 deficiency. Transplantation. 2019;103(10):2144–9. 61. Pillay BA, Avery DT, Smart JM, Cole T, Choo S, Chan D, et al. Hematopoietic stem cell transplant effectively rescues lymphocyte differentiation and function in DOCK8-deficient patients. JCI Insight. 2019;4:5. 62. Sanguedolce F, Zanelli M, Zizzo M, Bisagni A, Soriano A, Cocco G, et al. Primary pulmonary B-cell lymphoma: A review and update. Cancers (Basel). 2021;13(3):415. 63. Melani C, Jaffe ES, Wilson WH. Pathobiology and treatment of lymphomatoid granulomatosis, a rare EBV-driven disorder. Blood. 2020;135(16):1344–52.

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Chapter 17

T-Cell/Histiocyte-Rich Large B-Cell Lymphoma Kirill A. Lyapichev and Joseph D. Khoury

Introduction The existence of rare aggressive B-cell neoplasms characterized by a background that is rich in T-cells was raised by multiple groups as the use of immunohistochemical stains for defining the neoplastic cell of origin in different lymphomas started in the late 1970s and early 1980s. One of the first case series was reported by Mirchandari et al. who described seven cases that had been diagnosed disparately as atypical poorly differentiated lymphocytic lymphoma with convoluted nuclei, Lennert lymphoma, mixed lymphocytic–histiocytic lymphoma with large variation in size of abnormal cells, and histiocytic lymphoma with large multilobed nuclei [1]. Four additional cases were described around the same time and categorized as “pseudo-peripheral T-cell lymphomas” [2]. In 1988, Ramsay et al. showed that the neoplastic B-cell component in T-cell-rich large B-cell lymphoma could be as low as 10% of total cells in diagnostic tissue biopsy specimens [3]. Subsequently, in 1992, histiocyte-rich large B-cell lymphoma was proposed as a separate subtype of diffuse large B cell lymphoma (DLBCL) by Delabie et al. in a report of six cases with characteristic pathologic features similar to “Hodgkin’s lymphoma” [4]. This new type of lymphoma was described as an aggressive large B-cell lymphoma characterized by few large B-cells in a background of profuse T-cells and histiocytes. Additionally, it was found that such cases often have bone marrow involvement at presentation and poor clinical outcomes [4, 5]. Terms to describe these cases varied K. A. Lyapichev Department of Pathology, The University of Texas Medical Branch, Galveston, TX, USA e-mail: [email protected] J. D. Khoury (*) Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_17

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widely at the time and included: T-cell-rich B-cell lymphoma; B-cell lymphoma rich in T-cells and simulating Hodgkin disease; histiocyte-rich/T-cell-rich large B-cell lymphoma; T-cell-rich large B-cell lymphoma; T-cell-rich/histiocytes rich large B-cell lymphoma; and, histiocyte-rich large B-cell lymphoma [3, 4]. The current terminology of THRLBCL was introduced in the third edition (2008) of the World Health Organization (WHO) Classification and has been retained in ensuing editions through the current, fifth, edition of the WHO Classification (2022) [6].

Histology and Immunophenotype The neoplastic cells in THRLBCL are typically dispersed, without tendency to form sheets or aggregates, and they show cytomorphologic features resembling those of classic Hodgkin lymphoma and nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) (Fig.  17.1) [5, 7]. It has been proposed that neoplastic cells in THRLBCL may fall into one of the following morphologic groups: lymphocyte predominant-like; centroblast-like; and, Hodgkin Reed-Sternberg cell-like [8]. While this proposal is helpful, the study included reported EBV-positive cases, which would be subsequently classified as EBV-positive DLBCL. THRLBCL has a characteristic cellular background composed of histiocytes and numerous small T-cells (Fig. 17.1, right and left), with large neoplastic cells usually representing less than 10% of the total cell infiltrate. Clusters of non-epithelioid histiocytes are often present, and such a finding is usually a helpful diagnostic feature of THRLBCL [9]. Most of the background lymphocytes are T-cells, with fewer small B-cells. Meshworks of follicular dendritic cells are usually absent, as are eosinophils and plasma cells. The neoplastic cells in THRLBCL express pan-B-cell markers: CD19, CD20, and CD79a, as well as the B-cell transcription factors PAX5, Oct2, and BOB.1 (Fig. 17.2). Neoplastic cells are also usually positive for BCL6 and often express

Fig. 17.1  (Right and Left) Lymph node involved by THRLBCL shows large, atypical cells (arrow) surrounded by numerous small lymphocytes and occasional histiocytes

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Fig. 17.2  (Left) Immunohistochemistry for the B-cell marker, CD20, highlights large neoplastic cells in THRLBCL and most of small lymphocytes in the background are negative for CD20, suggesting T cell origin. (Right) In THRLBCL, most of the background small lymphocytes are positive for CD3

BCL2 and epithelial membrane antigen (EMA) [5, 10]. The characteristic stains for classic Hodgkin lymphoma: CD15 and CD30 are typically negative, and so is CD138. CD10 is variable expressed [11]. Histiocytes can be highlighted with CD68 and CD163, and T-cells with CD3, CD5, and other T-cell markers (Fig. 17.2 right). Background T-cells are mostly CD8-positive, with only few CD4-positive helper T-cells [12, 13]. Hartmann et al. noted that there was no significant difference in the relative number of CD8 positive T cells between typical NLPHL, THRLBCL-like NLPHL and THRLBCL [14]. De novo THRLBCL cases usually lack T-cell rosettes around tumor cells and remnants of B-cell follicles or clusters of small B cells, whereas such features are usually seen in THRLBCL arising in association with NLPHL.  CD279/PD-1-­ positive T-cells may be observed in THRLBCL, but usually do not surround tumor cells in a rosette configuration which could be seen in both NLPHL [15]. The lack of IgD-positive mantle cells and follicular dendritic cell meshworks are features of THRLBCL but not NLPHL. Epstein-Barr virus (EBV) transcripts or proteins should be absent in THRLBCL, which otherwise may be indistinguishable from EBV-­ positive DLBCL [8, 16]. THRLBCL affects lymph nodes mainly; other organs affected include the bone marrow, liver, and spleen. Bone marrow involvement can manifest with different patterns of involvement: intertrabecular and paratrabecular lymphoid aggregates containing numerous small lymphoid cells and rare large neoplastic cells [17]. The spleen is usually involved by numerous pale nodules within the white pulp. The nodules are mostly composed of histiocytes and small lymphocytes, with scattered large neoplastic cells [17]. A similar pattern is identified in cases with liver involvement [17]. Bone marrow involvement in patients with THRLBCL varies from 17 to 60% of cases, compared with a much lower (8.1%) frequency in patients with NLPHL [18]. Bone marrow disease in patients with NLPHL has been found to correlate with a

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more aggressive clinical course, with histologic and clinical features reminiscent of THRLBCL [19].

Molecular and Genetic Pathology The neoplastic cells in THRLBCL are believed to derive from germinal center B-cells and have clonally-rearranged immunoglobulin genes with intraclonal diversity and an average somatic mutation frequency of 15.5% for the immunoglobulin heavy chain gene (IGH) and 5.9% for the light chain genes (VL) [20]. Cytogenetic studies using conventional karyotyping have not shown recurrent chromosomal abnormalities in THRLBCL.  A study by Franke et  al. suggested a higher level of genomic imbalances in NLPHL compared with THRLBCL using comparative genomic hybridization (CGH) [21]. DNA from 17 cases of THRLBCL was isolated from neoplastic cells after microdissection of CD20-positive large cells and amplification by degenerate oligonucleotide-primed polymerase chain reaction (DOP-PCR) and analyzed by CGH. They identified genomic imbalance in all cases analyzed, with the most common aberrations including gain of Xq, 4q13q28, Xp21p11, and 18q21, and loss of 17p [21]. Additionally, they found several distinct features in terms of the number of genomic imbalances (average of 4.7 in THRLBCL vs 10.8  in NLPHL) and their distribution (usually 1–5  in THRLBCL vs 6–22 in NLPHL). Gene expression profiling of DLBCL has demonstrated that THRLBCL is over-­ represented within a distinct cluster whose signature is characterized by a “host immune response” and an association with poor prognosis [22]. However, more recent studies by Hartmann et  al. did not find consistent differences between NLPHL, THRLBCL-like NLPHL and THRLBCL by gene expression profiling of microdissected tumor cells [14]. Based on these findings, they identified BAT3/ BAG6, HIGD1A, and FAT10/UBD as immunohistochemical markers expressed in the tumor cells of all three lymphomas. Additionally, Hartmann and colleagues performed the characterization of the tumor microenvironment for infiltrating T cells and histiocytes that revealed significant differences in the cellular composition between typical NLPHL and THRLBCL. These findings led them to conclude that both of these lymphomas could represent a spectrum of the same disease, and the different clinical behavior may be strongly influenced by differences in the lymphoma microenvironment, due to the immune status of the patient [14]. Hartmann et al. compared 4 groups of cases using CGH array: 7 typical NLPHL, 4 THRLBCL-­ like NLPHL variants, 6 THRLBCL and 4 DLBCL derived from NLPHL. The number of genomic aberrations was higher in THRLBCL compared with both variants of NLPHL: gains of 2p16.1 and losses of 2p11.2 and 9p11.2 were commonly observed. It is known that gain of 2p16.1 affects the REL locus where CGH shows similar aberrations involving the REL locus [23]. Furthermore, REL protein expression in THRLBCL and NLPHL was found to be similar (33–38%), further

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supporting the hypothesis that these lymphomas are part of a pathobiologic spectrum with common molecular features but varying clinical presentations [23]. Interestingly, the main difference between NLPHL and THRLBCL is in components within their respective microenvironments. Van Loo et  al. found that the NLPHL microenvironment is molecularly very similar to lymph node follicular hyperplasia, while the THRLBCL microenvironment was clearly different with upregulation of CCL8, interferon-gamma, indoleamine 2,3-dioxygenase, VSIG4 and Toll-like receptors [24]. These findings could explain the recruitment and activation of T-cells, macrophages and dendritic cells, characterizing the stromal component of this lymphoma. The aggressive behavior of THRLBCL in comparison with that of NLPHL was explained by the gene expression profile which showed features suggestive of a distinct tolerogenic host immune response [24]. An additional difference between these two histologically similar neoplasms was found in histiocytic microenvironment: histiocytes in THRLBCL were found strongly expressing metal-binding proteins, like MT2A, compare to histiocytes in NLPHL [25]. This histiocytic microenvironment in the THRLBCL background could be responsible for a tolerogenic host immune response with a prominent proinflammatory, interferon-dependent signature (IDO, CCL8, VSIG4, STAT1, ICAM1, CD64, and CXCL10), high IL4 levels and expression of metal-binding proteins (MT2A) [24–27]. Recently, Schuhmacher et al. identified that JUNB, DUSP2, SGK1, SOCS1 and CREBBP are frequently mutated in both THRLBCL and NLPHL, which further suggests a close relationship between these two lymphomas [28]. Interestingly, JUNB gene mutations are uncommonly observed in lymphomas and could be specific for both neoplasms. Additionally, Griffin et al. found that 64% of THRLBCL cases showed PD-L1/PD-L2 copy number gains or amplifications and increased PD-L1 expression [29].

Precision Medicine and Targets of Therapy The distinction between NLPHL and THRLBCL is critical for management decisions. Treatment for low stage (I/II) of NLPHL is nodal excision followed by either a “watch-and-wait strategy” or localized radiation [30–34]. Between 3 and 7% of NLPHL patients undergo transformation to large B-cell lymphoma, of which THRLBCL is one of the most common subtypes [35, 36]. Cyclophosphamide, Hydroxydaunorubicin, Oncovin (vincristine), Prednisone (Prednisolone) with Rituximab (R-CHOP) is a therapeutic approach for THRLBCL. The stage-adjusted overall survival for NLPHL and THRLBCL is very different: 90% and 50%, respectively [37]. Lenalidomide showed some positive effect in treatment of transformed THRLBCL [38]. (See Table 17.1 for a comparison of the biologic characteristics of T-cell/histiocyte-rich large B-cell lymphoma to histologically similar B-cell neoplasms.)

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Table 17.1  Comparison of the biologic characteristics of T-cell/histiocyte-rich large B-cell lymphoma to histologically similar B-cell neoplasms Neoplastic cells

THRLBCL Karyotype and Gains of 2p16.1 and aCGH losses of 2p11.2 and 9p11.2 more often compare to NLPHL Gain of Xq, 4q13q28, Xp21p11, and 18q21, and loss of 17p [20, 21]

BCL6 rearrangement PD-L1 Rare T cells

Other mutations Microenvironment T-cells Histiocytes

Other (probably both)

JUNB, DUSP2, SGK1, SOCS1 and CREBBP

NLPHL Recurrent chromosomal defects include: +1/1q + (n = 10) (includes i(1q) in 7/10 patients) (Fig. 17.1) or as a translocated supernumerary long arm (3 patients) 3q27 rearrangements (8 patients) −4/4q28–q32 (6 patients) −7/7q23–q33 (5 patients) −13 (3 patients) and 14q32 rearrangements (6/10) Chromosome 9 imbalances (n = 7), +9 (1/7), −9 (1/7), add (9) (p24) (2/7), add (9) (q22) (1/7) and 9q33–34 rearrangement (2/7) Recurrent IGH-BCL6 juxtaposition T cells forming rosette around Hodgkin’s like cells JUNB, DUSP2, SGK1, SOCS1 and CREBBP

Positive for Negative for metal-­ metal-binding binding proteins, like proteins, like MT2A MT2A Up-regulation of CCL8, interferon-­ gamma, indoleamine 2,3 dioxygenase, VSIG4 and Toll-like receptors

References [21, 23], [39]

[40–42]

[28]

[25]

[24]

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References 1. Mirchandani I, Palutke M, Tabaczka P, Goldfarb S, Eisenberg L, Pak MS. B-cell lymphomas morphologically resembling T-cell lymphomas. Cancer. 1985;56(7):1578–83. 2. Jaffe ES.  Surgical pathology of lymph nodes and related organs. Philadelphia: WB Saunders; 1985. 3. Ramsay AD, Smith WJ, Isaacson PG.  T-cell-rich B-cell lymphoma. Am J Surg Pathol. 1988;12(6):433–43. 4. Delabie J, Vandenberghe E, Kennes C, Verhoef G, Foschini MP, Stul M, et al. Histiocyte-rich B-cell lymphoma. A distinct clinicopathologic entity possibly related to lymphocyte predominant Hodgkin’s disease, paragranuloma subtype. Am J Surg Pathol. 1992;16(1):37–48. 5. Achten R, Verhoef G, Vanuytsel L, De Wolf-Peeters C. Histiocyte-rich, T-cell-rich B-cell lymphoma: a distinct diffuse large B-cell lymphoma subtype showing characteristic morphologic and immunophenotypic features. Histopathology. 2002;40(1):31–45. 6. Alaggio R, Amador C, Anagnostopoulos I, Attygalle AD, Araujo IBO, Berti E, et al. The 5th edition of the World Health Organization classification of haematolymphoid tumours: lymphoid neoplasms. Leukemia. 2022;36(7):1720–48. 7. Achten R, Verhoef G, Vanuytsel L, De Wolf-Peeters C. T-cell/histiocyte-rich large B-cell lymphoma: a distinct clinicopathologic entity. J Clin Oncol. 2002;20(5):1269–77. 8. Lim MS, Beaty M, Sorbara L, Cheng RZ, Pittaluga S, Raffeld M, et al. T-cell/histiocyte-rich large B-cell lymphoma: a heterogeneous entity with derivation from germinal center B cells. Am J Surg Pathol. 2002;26(11):1458–66. 9. Greer JP, Macon WR, Lamar RE, Wolff SN, Stein RS, Flexner JM, et al. T-cell-rich B-cell lymphomas: diagnosis and response to therapy of 44 patients. J Clin Oncol. 1995;13(7):1742–50. 10. Fraga M, Sanchez-Verde L, Forteza J, Garcia-Rivero A, Piris MA.  T-cell/histiocyte-rich large B-cell lymphoma is a disseminated aggressive neoplasm: differential diagnosis from Hodgkin’s lymphoma. Histopathology. 2002;41(3):216–29. 11. Medeiros LJ, Miranda RN. Diagnostic pathology: lymph nodes and extranodal lymphomas. Salt Lake City: Elsevier; 2017. 12. Felgar RE, Macon WR, Kinney MC, Roberts S, Pasha T, Salhany KE. TIA-1 expression in lymphoid neoplasms. Identification of subsets with cytotoxic T lymphocyte or natural killer cell differentiation. Am J Pathol. 1997;150(6):1893–900. 13. Tousseyn T, De Wolf-Peeters C. T cell/histiocyte-rich large B-cell lymphoma: an update on its biology and classification. Virchows Arch. 2011;459(6):557–63. 14. Hartmann S, Doring C, Jakobus C, Rengstl B, Newrzela S, Tousseyn T, et al. Nodular lymphocyte predominant hodgkin lymphoma and T cell/histiocyte rich large B cell lymphoma—endpoints of a spectrum of one disease? PLoS One. 2013;8(11):e78812. 15. Nam-Cha SH, Roncador G, Sanchez-Verde L, Montes-Moreno S, Acevedo A, Dominguez-­ Franjo P, et al. PD-1, a follicular T-cell marker useful for recognizing nodular lymphocyte-­ predominant Hodgkin lymphoma. Am J Surg Pathol. 2008;32(8):1252–7. 16. Nicolae A, Pittaluga S, Abdullah S, Steinberg SM, Pham TA, Davies-Hill T, et al. EBV-positive large B-cell lymphomas in young patients: a nodal lymphoma with evidence for a tolerogenic immune environment. Blood. 2015;126(7):863–72. 17. Dogan A, Burke JS, Goteri G, Stitson RN, Wotherspoon AC, Isaacson PG.  Micronodular T-cell/histiocyte-rich large B-cell lymphoma of the spleen: histology, immunophenotype, and differential diagnosis. Am J Surg Pathol. 2003;27(7):903–11. 18. Agbay R, Loghavi S, Zuo Z, Fayad L, Dabaja B, Medeiros LJ, et al. Bone marrow involvement in patients with nodular lymphocyte predominant Hodgkin lymphoma. Am J Surg Pathol. 2018;42(4):492–9. 19. Khoury JD, Jones D, Yared MA, Manning JT Jr, Abruzzo LV, Hagemeister FB, et al. Bone marrow involvement in patients with nodular lymphocyte predominant Hodgkin lymphoma. Am J Surg Pathol. 2004;28(4):489–95.

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20. Brauninger A, Kuppers R, Spieker T, Siebert R, Strickler JG, Schlegelberger B, et al. Molecular analysis of single B cells from T-cell-rich B-cell lymphoma shows the derivation of the tumor cells from mutating germinal center B cells and exemplifies means by which immunoglobulin genes are modified in germinal center B cells. Blood. 1999;93(8):2679–87. 21. Franke S, Wlodarska I, Maes B, Vandenberghe P, Achten R, Hagemeijer A, et al. Comparative genomic hybridization pattern distinguishes T-cell/histiocyte-rich B-cell lymphoma from nodular lymphocyte predominance Hodgkin’s lymphoma. Am J Pathol. 2002;161(5):1861–7. 22. Monti S, Savage KJ, Kutok JL, Feuerhake F, Kurtin P, Mihm M, et al. Molecular profiling of diffuse large B-cell lymphoma identifies robust subtypes including one characterized by host inflammatory response. Blood. 2005;105(5):1851–61. 23. Hartmann S, Doring C, Vucic E, Chan FC, Ennishi D, Tousseyn T, et  al. Array comparative genomic hybridization reveals similarities between nodular lymphocyte predominant Hodgkin lymphoma and T cell/histiocyte rich large B cell lymphoma. Br J Haematol. 2015;169(3):415–22. 24. Van Loo P, Tousseyn T, Vanhentenrijk V, Dierickx D, Malecka A, Vanden Bempt I, et al. T-cell/ histiocyte-rich large B-cell lymphoma shows transcriptional features suggestive of a tolerogenic host immune response. Haematologica. 2010;95(3):440–8. 25. Hartmann S, Tousseyn T, Doring C, Fluchter P, Hackstein H, Herreman A, et al. Macrophages in T cell/histiocyte rich large B cell lymphoma strongly express metal-binding proteins and show a bi-activated phenotype. Int J Cancer. 2013;133(11):2609–18. 26. Macon WR, Cousar JB, Waldron JA Jr, Hsu SM. Interleukin-4 may contribute to the abundant T-cell reaction and paucity of neoplastic B cells in T-cell-rich B-cell lymphomas. Am J Pathol. 1992;141(5):1031–6. 27. Chetaille B, Bertucci F, Finetti P, Esterni B, Stamatoullas A, Picquenot JM, et al. Molecular profiling of classical Hodgkin lymphoma tissues uncovers variations in the tumor microenvironment and correlations with EBV infection and outcome. Blood. 2009;113(12):2765–3775. 28. Schuhmacher B, Bein J, Rausch T, Benes V, Tousseyn T, Vornanen M, et al. JUNB, DUSP2, SGK1, SOCS1 and CREBBP are frequently mutated in T-cell/histiocyte-rich large B-cell lymphoma. Haematologica. 2019;104(2):330–7. 29. Griffin GK, Weirather JL, Roemer MGM, Lipschitz M, Kelley A, Chen PH, et al. Spatial signatures identify immune escape via PD-1 as a defining feature of T-cell/histiocyte-rich large B-cell lymphoma. Blood. 2021;137(10):1353–64. 30. Chen RC, Chin MS, Ng AK, Feng Y, Neuberg D, Silver B, et al. Early-stage, lymphocyte-­ predominant Hodgkin’s lymphoma: patient outcomes from a large, single-institution series with long follow-up. J Clin Oncol. 2010;28(1):136–41. 31. Nogova L, Reineke T, Eich HT, Josting A, Muller-Hermelink HK, Wingbermuhle K, et  al. Extended field radiotherapy, combined modality treatment or involved field radiotherapy for patients with stage IA lymphocyte-predominant Hodgkin’s lymphoma: a retrospective analysis from the German Hodgkin Study Group (GHSG). Ann Oncol. 2005;16(10):1683–7. 32. Schlembach PJ, Wilder RB, Jones D, Ha CS, Fayad LE, Younes A, et al. Radiotherapy alone for lymphocyte-predominant Hodgkin’s disease. Cancer J. 2002;8(5):377–83. 33. Wilder RB, Schlembach PJ, Jones D, Chronowski GM, Ha CS, Younes A, et  al. European Organization for Research and Treatment of Cancer and Groupe d'Etude des Lymphomes de l'Adulte very favorable and favorable, lymphocyte-predominant Hodgkin disease. Cancer. 2002;94(6):1731–8. 34. Wirth A, Yuen K, Barton M, Roos D, Gogna K, Pratt G, et al. Long-term outcome after radiotherapy alone for lymphocyte-predominant Hodgkin lymphoma: a retrospective multicenter study of the Australasian Radiation Oncology Lymphoma Group. Cancer. 2005;104(6):1221–9. 35. Bagwan IN, Knee G, Abboudi Z, Naresh KN.  Small intestinal presentation of nodular lymphocyte-predominant Hodgkin lymphoma with T cell/histiocyte-rich B cell lymphoma-­ like areas-with review of literature on extranodal presentation of this disease. J Hematop. 2010;3(1):29–34.

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36. Huang JZ, Weisenburger DD, Vose JM, Greiner TC, Aoun P, Chan WC, et al. Diffuse large B-cell lymphoma arising in nodular lymphocyte predominant Hodgkin lymphoma: a report of 21 cases from the Nebraska Lymphoma Study Group. Leuk Lymphoma. 2004;45(8):1551–7. 37. Boudova L, Torlakovic E, Delabie J, Reimer P, Pfistner B, Wiedenmann S, et  al. Nodular lymphocyte-predominant Hodgkin lymphoma with nodules resembling T-cell/histiocyte-rich B-cell lymphoma: differential diagnosis between nodular lymphocyte-predominant Hodgkin lymphoma and T-cell/histiocyte-rich B-cell lymphoma. Blood. 2003;102(10):3753–8. 38. Siricilla M, Irwin L, Ferber A.  A case of chemotherapy-refractory “THRLBCL like transformation of NLPHL” successfully treated with lenalidomide. Case Rep Oncol Med. 2018;2018:6137454. 39. Stamatoullas A, Picquenot JM, Dumesnil C, Ruminy P, Penther D, Bertrand P, et  al. Conventional cytogenetics of nodular lymphocyte-predominant Hodgkin’s lymphoma. Leukemia. 2007;21(9):2064–7. 40. Renne C, Martin-Subero JI, Hansmann ML, Siebert R.  Molecular cytogenetic analyses of immunoglobulin loci in nodular lymphocyte predominant Hodgkin’s lymphoma reveal a recurrent IGH-BCL6 juxtaposition. J Mol Diagn. 2005;7(3):352–6. 41. Wlodarska I, Stul M, De Wolf-Peeters C, Hagemeijer A.  Heterogeneity of BCL6 rearrangements in nodular lymphocyte predominant Hodgkin’s lymphoma. Haematologica. 2004;89(8):965–72. 42. Wlodarska I, Nooyen P, Maes B, Martin-Subero JI, Siebert R, Pauwels P, et al. Frequent occurrence of BCL6 rearrangements in nodular lymphocyte predominance Hodgkin lymphoma but not in classical Hodgkin lymphoma. Blood. 2003;101(2):706–10.

Chapter 18

ALK Positive Large B-Cell Lymphoma Sharmila Ghosh, Christian Salib, and Julie Teruya-Feldstein

Introduction Anaplastic lymphoma kinase (ALK) positive large B cell lymphoma (ALK+ LBCL) is a rare, aggressive B cell lymphoma first described in 1997 by Delsol et al. as a series of 7 patients [1]. It was included as a separate entity in the World Health Organization (WHO) in 2008 [2], International Consensus Classification on Mature B cell Neoplasms [3] and WHO and has been further classified and described as a distinct entity under the category of mature B cell large aggressive B cell neoplasms in the 2017 revised editions of the WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues [4, 5] and the fifth Edition of WHO Classification of Lymphoid Neoplasms [6]. ALK+ LBCL accounts for 30 years) and was originally secondary to the use of a therapeutic artificial pneumothorax for pulmonary tuberculosis [19]. Commonly, the site of involvement is the pleural cavity, but other anatomical locations exist, such as bone (e.g., femur) and joint spaces with surrounding soft tissue. These non-pleural cavity-based cases are usually in the context of prolonged inflammation from other disease processes (e.g., chronic osteomyelitis, prosthetic joint replacement) [20].

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Etiology The peculiar presentation of these neoplasms raises questions about how these lymphomas arise. While lymphomagenesis has not been completely elucidated, the prevailing theory is that the enclosure of this long-standing inflammatory process results in  localized immune dysregulation, creating a suppressed cytolytic T-cell response, thus allowing EBV-infected B-cells to escape immune surveillance. This immune evasion is implicated in permitting unchecked B-cell proliferation with subsequent development of B-cell lymphoma [6, 7]. Epstein-Barr virus (EBV), first discovered in 1964 [21], is a well-known human gamma-1 herpesvirus 4 (HHV-4) that can infect naïve B-cells, usually via the interaction of the viral envelope protein gp350/220 and the complement receptor CD21 [22]. Recent evidence by Ogembo et al. [23] shows that CD35, a regulatory complement protein, also binds to the major viral glycoprotein gp350/220, distinct from CD21, and mediates the entry and latency capabilities of the virus when in conjunction with human leukocyte antigen (HLA) II co-expression. EBV has different gene expression latency patterns, and many EBV-associated cases of DLBCL occurring in older individuals display latency pattern III [24], similar to the pattern seen in DLBCL-CI with co-expression of EBV nuclear antigen-2 (EBNA2) and latent membrane protein-1 (LMP1) [25, 26]. This is in contrast to the latency pattern II more frequently exhibited in EBV-positive DLBCLs of younger individuals, according to one study [27]. This age-stratified difference in EBV patterns could suggest that the tumor development seen in DLBCL-CI could be a consequence of a decreased or inefficient CD8+ T-cell immune response similar to that commonly seen in aging individuals via immunosenescence. The cumulative effect of several downstream factors may contribute to the immune evasion implicated in EBV-­ driven lymphomagenesis. These factors may include increased immunosuppressive IL-10 production [28, 29], downregulation of MHC class I expression [30], the modulatory effect of T-cells related to EBNA3B [31], and autocrine and paracrine stimulatory growth effects from IL-6 and IL-6R [32]. Additional factors such as genetic instability, microRNA regulation (i.e., EBV-miR-BHRF1–2) [33], and other tumor microenvironment players are under continued study for further elucidation. The specific pathogenesis of FA-LBCL is more elusive, particularly since clinical scenarios are many, and not all cases are associated with foreign materials such as synthetic valves [13]. However, similar to DLBCL-CI, a unifying theme is localized immunosuppression [12, 13] associated with EBV-transformed and immortalized B-cells unable to proliferate outside of an immune-privileged niche [13]. Programmed death ligand 1 (PD-L1) is usually positive, which could suggest a role in immune evasion [13]. It is also thought that enclosure within fibrinous material is protective against EBV-specific cytotoxic T-cells [12, 13], permitting a lymphomatous, though non-mass forming, proliferation.

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Clinical Presentation, Radiologic, and Laboratory Findings Patients are considered immunocompetent or at least do not have an established primary or acquired systemic immunodeficiency [i.e. iatrogenic cause, human immunodeficiency virus (HIV), post-transplant state]. In the context of PAL, affected patients typically present with pleuritic, chest, or back pain and chest wall swelling accompanied by respiratory symptoms such as productive cough, dyspnea, and hemoptysis. One large case series of PAL indicates 73% of patients present with clinical stage I or II disease, with tumors usually confined to the thoracic cavity [4]. The vast majority of such cases manifest with isolated pleural involvement (80%), pleural with lung involvement (10%), lung involvement (7%), and, very rarely, no associated mass (3%) [4]. Some patients may suffer lower limb paralysis due to tumor invasion into the spinal cord [5]. Patients with DLBCL-CI involving bone, joints, or periarticular soft tissue typically present with mass lesions with pain [34]. Radiologic imaging of PAL usually demonstrates an extrapulmonary mass, often over 10 centimeters in size, sometimes lenticular or crescentic in shape but always adjacent to an empyema. The tumors may be located within the lateral costal region (50%) or costophrenic angle (30%) and can manifest as a thickened pleura with associated pleural effusion on imaging [35]. There is often evidence of necrosis and adjacent direct invasion, with the chest wall being the most common [35]. In cases involving joint spaces, imaging studies commonly highlight lytic bone lesions [1]. Laboratory findings vary but are altogether nonspecific. Complete blood count (CBC) and peripheral blood smear review often show a nondescript leukocytosis (>10,000/μL), but there is absence of peripheralized lymphoma involvement of blood or bone marrow, and lymphadenopathy is usually not a prominent feature [5]. Lactate dehydrogenase (LDH) and C-reactive protein (CRP) are commonly elevated in the setting of PAL [19]. Elevated levels of neuron-specific enolase (NSE) in serum and pleural effusion contents have also been described in PAL, a nonspecific feature that can nonetheless potentially raise clinical consideration for small cell neuroendocrine carcinoma. The significance of this elevated NSE in PAL is unclear, however.

Gross Findings, Histomorphology, and Phenotype Macroscopic findings in DLBCL-CI have been better described in the setting of PAL and sometimes clarified in autopsy findings [5]. Radiologic findings suggest there is usually a contiguous spread from the pleural cavity into adjacent structures, namely, the lung, diaphragm, mediastinal structures, and even the liver [5]. At autopsy, such tumors appear confined to the thoracic cavity in about half of patients [2, 4], though nodal and distant metastases have been reported [5]. The morphology of the neoplastic cells of DLBCL-CI is rather nonspecific and similar to usual cases of DLBCL.  The proliferation comprises medium-sized to

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a

b

c

d

343

e

Fig. 21.1  Lymphoma cells of DLBCL-CI, present on a pleural fluid cytology cell block, are intermediate-­sized to large with irregular large nuclei, vesicular chromatin, and conspicuous nucleoli (a, ×1000). Cells are largely negative for CD20 (b) but show immunoreactivity for PAX5 (c), MUM1 (d), and EBER (e) (×400). The cells are additionally positive for CD79a and OCT2 and negative for CD5, CD10, and CD138 (not pictured)

large atypical lymphoid cells with centroblastic or immunoblastic appearance, large nuclei with vesicular chromatin, and one to multiple nucleoli (Fig. 21.1a), and there may be accompanying plasmacytic differentiation. In the setting of PAL, pleural tissue may show fibrous thickening with a chronic inflammatory infiltrate of small lymphocytes and plasma cells. Angiocentric growth and necrosis have been described but are not common features [5, 18]. Unlike the mass-forming proliferations of DLBCL-CI, FA-LBCL is considered a “microscopic” lymphoma in which tumor cells are singly dispersed or present in ribbons or small clusters within amorphous eosinophilic material characteristic for fibrin thrombus [1, 8], typically within the superficial layers of fibrin (Fig. 21.2a, b) [13]. A marked inflammatory or suppurative background is not present. These proliferations are typically confined within pre-existing pathologic lesions such as

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a

b

c

d

e

Fig. 21.2  FA-LBCL lymphoma cells within right ventricular clot thrombectomy (a, ×400) demonstrating large pleomorphic features (b, ×1000). The cells are immunoreactive for CD20 (c), MUM1 (d), and EBER (e) (×400) and negative for CD5 and CD10 (not pictured)

myxomas, aortic grafts, atrial thrombi, synthetic heart valves, cystic or pseudocystic lesions, and hydroceles [6, 11], among others. Neoplastic cells of most cases express B-lineage markers CD20, PAX5, and CD79a with activated B-cell phenotype [i.e. CD10(−), BCL6(−/+), MUM1(+)], but a subset of cases may lack CD20 and instead co-express CD138 and MUM1 consistent with plasmacytic differentiation (Figs. 21.1b–d and 21.2c, d). Cells are characteristically positive for EBV-encoded RNA (EBER) (Figs.  21.1e and 21.2e), additionally exhibiting a Type III EBV latency pattern with expression of LMP1 and EBNA2, though rare EBV-negative cases of FA-LBCL have been reported [6, 8]. Aberrant T-cell antigen expression (CD2, CD3, CD4) by B-cells in PAL cases has also been described [18].

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Diagnostic Considerations Given the myriad subtypes and presentations of EBV-positive large B-cell proliferations, recognition of the settings in which the proliferation of DLBCL-CI and FA-LBCL arise is critical to diagnosis, with a careful review of morphologic and phenotypic features in conjunction with clinical history, radiologic findings, and laboratory parameters. Though DLBCL-CI and FA-LBCL both occur within confined spaces in immune-­ sequestered sites [1, 14, 15], FA-LBCL, though termed a “lymphoma,” is distinguished by its lack of mass-forming lesions and lymphoma-related symptomatology, especially as these lesions are discovered incidentally and are limited to confined spaces (e.g. fibrin or cystic cavity) [5]. This contrasts with PAL (DLBCL-CI) which presents as a space-occupying tumor with potentially invasive growth and significant morbidity. The marked chronic or suppurative inflammatory background that typifies PAL-like cases of DLBCL-CI is not a feature of FA-LBCL [5, 14]. Not surprisingly, DLBCL-CI and, in particular, PAL cases show significant diagnostic overlap with primary effusion lymphoma (PEL), especially as both are EBV-­ positive lymphoproliferation within enclosed spaces. However, patients with PEL are very often immunocompromised, usually due to human immunodeficiency virus (HIV) infection, and do not have the antecedent history of a chronic pyothorax, whereas individuals with DLBCL-CI are immunocompetent. Cavitary PEL is limited to body cavity fluids and does not produce mass-forming lesions except in rare cases while mass-forming proliferations are expected in PAL. Importantly, PEL is positive for the latency-associated nuclear antigen (LANA) of Kaposi’s sarcoma herpesvirus or human herpesvirus-8 (KSHV/HHV8), which is negative in DLBCL-CI. As PAL is also an EBV-associated B-cell proliferation that may invade the lung, lymphomatoid granulomatosis (LyG) may be a diagnostic consideration. However, LyG tends to show multifocal parenchymal involvement without primary involvement of the pleural cavity. The chief differential diagnosis for both DLBCL-CI and FA-LBCL is that of EBV-positive DLBCL (WHO-HAEM5), especially as diagnosis of these two neoplasms necessitates exclusion of the latter by clinicopathologic and radiologic correlation. Both entities overlap in age demographic (typically elderly), show activated B-cell phenotype, and EBV latency pattern type III [11, 24]. However, the atypical localized anatomic distribution at presentation in association with a long-standing lesion (e.g., chronic pyothorax, atrial myxoma, mural thrombus, and cyst) is key in confidently establishing a diagnosis of DLBCL-CI or FA-LBCL [11]. In one case series of primary cardiac lymphomas, cases of cardiac DLBCL that showed a more sheet-like growth pattern with myocardial invasion and were EBV negative were better regarded as DLBCL, not otherwise specified [8].

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Molecular Genetic Features Cell lines from PAL cases commonly have a complex karyotype, including numerous structural and numerical chromosomal abnormalities, suggesting genetic instability [36]. Gene expression profiling of such cases is distinctively different from those of nodal DLBCL and is characterized by certain signatures associated with cellular responses to EBV [37]. Additionally, these studies revealed an association of PAL with overexpression of IFI27 (interferon-alpha inducible protein 27), a gene involved in interferon alpha-induced apoptosis that may prevent viral replication by altering innate host immunity [37–39]. Furthermore, these type 1 interferons lead to activation of the JAK/STAT signaling pathway, which, if dysregulated in T helper cells, may contribute to the development of various immune disorders [40]. These factors in conjunction with decreased cytotoxic CD8+ T-cell effect, likely facilitate the development of PAL in the setting of chronic inflammation and evasion of immune surveillance. Neoplastic B-cells of PAL demonstrate gene rearrangement of the immunoglobulin heavy chain (IGH) [41] and show somatic hypermutation [42], further supporting its non-germinal center (or activated B-cell) origin. FA-LBCL cases usually demonstrate IGH and/or IGK clonality but have a low level of genetic abnormalities when compared to DLBCL-CI [43]. PAL cases lack MYC gene (8q24) rearrangements (Fig. 21.3) but often show MYC amplification [44], and TP53 gene mutations are commonly present, found in 67% of cases in one study [45] (Fig. 21.4). Cases of FA-LBCL also lack MYC rearrangements but unlike PAL (DLBCL-CI) are not characterized by amplifications of this gene. Recent evidence shows a subset of DLBCL-CI cases demonstrates deletion of A20 (TNFAIP3), a change that leads to activation of NFκB, a key player in activated B-cell signaling [46, 47]. While not necessarily related to the EBV latency pattern, the loss of A20, also seen in other

Fig. 21.3  Fluorescence in situ hybridization (FISH) shows a lack of MYC rearrangement by a dual color, break-apart probe assay, however, with an extra intact copy of MYC in most cells (red arrow), in comparison to a normal cell (white arrow)

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Fig. 21.4  Next generation sequencing (NGS) panel reveals a TP53 mutation on Integrated Genomics Viewer (IGV) in a case of DLBCL-CI, which is identified by the A detected in multiple reads compared to the wild-type G

EBV-related B-cell lymphomas [47], may certainly contribute to pathogenesis, given the loss of the negative regulatory effect of NFκB [46, 47]. A recent next-generation sequencing study by Sakamoto et al. [48] revealed that EBV-encoded miRNAs accounted for one-third of total annotated miRNA and that miR-BHRF1 was significantly higher in PAL, which could imply an association with EBV latency pattern III. Moreover, EBV miRNAs directly inhibit the expression of viral antigens, thereby masking the presence of EBV-infected B-cells and promoting escape from immune surveillance [49]. Continued research is necessary to further characterize the host–pathogen relationship and the underlying genetic alterations necessary in promoting EBV-driven lymphomagenesis in the setting of DLBCL-CI and FA-LBCL.

Prognosis DLBCL-CI is an aggressive lymphoma with associated poor clinical outcomes. The average 5-year survival rate is 20–35%; however, patients who achieve complete remission following chemoradiation and/or surgery have improved 5-year survival rates approaching approximately 50%. Interestingly, lack of expression of EBNA2 may be associated with worse outcomes in PAL, given that 1-year survival rates

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were 87.5% in EBNA positive cases compared to 0% in EBNA2 negative cases (p < 0.01) in one study, which suggested that EBNA2 downregulation may occur as a result of selection pressure in disease progression [50]. Clinical findings, such as poor patient performance and staging and pertinent laboratory findings (e.g. high LDH) are indicators of poor prognosis. FA-LBCL has a more favorable prognosis compared to DLBCL-CI and is usually cured by surgical excision alone. While deaths in patients with FA-LBCL are documented, these deaths are typically attributed to a different medical cause and not directly related to the lymphoma [13, 51].

References 1. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, Thiele J, Arber D, Hasserjian R, LeBeau M, Orazi A, Siebert R. WHO classification of tumours of haematopoietic and lymphoid tissues. 4th ed. International Agency for Research on Cancer: Lyon; 2017. 2. Iuchi K, Ichimiya A, Akashi A, Mizuta T, Lee Y-E, Tada H, et al. Non-Hodgkin’s lymphoma of the pleural cavity developing from long-standing pyothorax. Cancer. 1987;60(8):1771–5. 3. Aozasa K, Ohsawa M, Iuchi K, Mori T, Komatsu H, Tajima K, et al. Prognostic factors for pleural lymphoma patients. Jpn J Clin Oncol. 1991;21:417–21. 4. Nakatsuka S, Yao M, Hoshida Y, Yamamoto S, Iuchi K, Aozasa K. Pyothorax-associated lymphoma: a review of 106 cases. J Clin Oncol. 2002;20(20):4255–60. 5. Aozasa K, Takakuwa T, Nakatsuka S.  Pyothorax-associated lymphoma. Adv Anat Pathol. 2005;12(6):324–31. 6. King RL, Goodlad JR, Calaminici M, Dotlic S, Montes-Moreno S, Oschlies I, et  al. Lymphomas arising in immune-privileged sites: insights into biology, diagnosis, and pathogenesis. Virchows Arch. 2020;476(5):647–65. 7. Piña-Oviedo S, Moran CA. Primary mediastinal nodal and extranodal non-Hodgkin lymphomas: current concepts, historical evolution, and useful diagnostic approach: part 2. Adv Anat Pathol. 2019;26(6):371–89. 8. Gruver AM, Huba MA, Dogan A, Hsi ED. Fibrin-associated large B-cell lymphoma: part of the spectrum of cardiac lymphomas. Am J Surg Pathol. 2012;36(10):1527–37. 9. Yan J, Luo D, Zhang F, He J, Yao S, Luo X, et al. Diffuse large B cell lymphoma associated with chronic inflammation arising within atrial myxoma: aggressive histological features but indolent clinical behaviour. Histopathology. 2017;71(6):951–9. 10. Hayes C, Alkan S, Kitahara S. Indolent fibrin-associated EBV-positive large B cell lymphoproliferative disorder in a lower extremity aneurysmal hematoma: a case report. J Hematop. 2014;7(3):139–43. 11. Natkunam Y, Goodlad JR, Chadburn A, de Jong D, Gratzinger D, Chan JK, et al. EBV-positive B-cell proliferations of varied malignant potential: 2015 SH/EAHP workshop report—part 1. Am J Clin Pathol. 2017;147(2):129–52. 12. Boroumand N, Ly TL, Sonstein J, Medeiros LJ. Microscopic diffuse large B-cell lymphoma (DLBCL) occurring in pseudocysts: do these tumors belong to the category of DLBCL associated with chronic inflammation? Am J Surg Pathol. 2012;36(7):1074–80. 13. Boyer DF, McKelvie PA, de Leval L, Edlefsen KL, Ko YH, Aberman ZA, et  al. Fibrin-­ associated EBV-positive large B-cell lymphoma: an indolent neoplasm with features distinct from diffuse large B-cell lymphoma associated with chronic inflammation. Am J Surg Pathol. 2017;41(3):299–312. 14. Alaggio R, Amador C, Anagnostopoulos I, Attygalle A, de Oliveira Araujo IB, et al. The 5th edition of the World Health Organization classification of haematolymphoid tumors: lymphoid neoplasms. Leukemia. 2022;36(7):1720–48.

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15. Campo E, Jaffe ES, Cook JR, Quintanilla-Martinez L, Swerdlow SH, et al. The international consensus classification of mature lymphoid neoplasms: a report from the clinical advisory committee. Blood. 2022;140:1229–53. 16. Falini B, Martino G, Lazzi S. A comparison of the international consensus and 5th World Health Organization classifications of mature B-cell lymphomas. Leukemia. 2023;37(1):18–34. 17. Ascani S, Piccioli M, Poggi S, Briskomatis A, Bolis GB, Liberati F, et al. Pyothorax-associated lymphoma: description of the first two cases detected in Italy. Ann Oncol. 1997;8(11):1133–8. 18. Androulaki A, Drakos E, Hatzianastassiou D, Vgenopoulou S, Gazouli M, Korkolopoulou P, et al. Pyothorax-associated lymphoma (PAL): a western case with marked angiocentricity and review of the literature. Histopathology. 2004;44(1):69–76. 19. Narimatsu H, Ota Y, Kami M, Takeuchi K, Suzuki R, Matsuo K, et al. Clinicopathological features of pyothorax-associated lymphoma; a retrospective survey involving 98 patients. Ann Oncol. 2007;18(1):122–8. 20. Cheuk W, Chan AC, Chan JK, Lau GT, Chan VN, Yiu HH. Metallic implant-associated lymphoma: a distinct subgroup of large B-cell lymphoma related to pyothorax-associated lymphoma? Am J Surg Pathol. 2005;29(6):832–6. 21. Burkitt D. A sarcoma involving the jaws in African children. Br J Surg. 1958;46(197):218–23. 22. Fingeroth JD, Weis JJ, Tedder TF, Strominger JL, Biro PA, Fearon DT.  Epstein-Barr virus receptor of human B lymphocytes is the C3d receptor CR2. Proc Natl Acad Sci U S A. 1984;81(14):4510–4. 23. Ogembo JG, Kannan L, Ghiran I, Nicholson-Weller A, Finberg RW, Tsokos GC, et  al. Human complement receptor type 1/CD35 is an Epstein-Barr virus receptor. Cell Rep. 2013;3(2):371–85. 24. Oyama T, Ichimura K, Suzuki R, Suzumiya J, Ohshima K, Yatabe Y, et al. Senile EBV B-cell lymphoproliferative disorders: a clinicopathologic study of 22 patients. Am J Surg Pathol. 2003;27(1):16–26. 25. Oshawa M, Tomita Y, Kanno H, Iuchi K, Kawabata Y, Nakajima Y, et al. Role of Epstein-Barr virus in pleural lymphomagenesis. Mod Pathol. 1995;8(8):848–53. 26. Sasajima Y, Yamabe H, Kobashi Y, Hirai K, Mori S.  High expression of the Epstein-Barr virus latent protein EB nuclear antigen-2 on pyothorax-associated lymphomas. Am J Pathol. 1993;14(5):1280–5. 27. Cohen M, Narbaitz M, Metrebian F, Matteo ED, Preciado MV, Chabay PA. Epstein-Barr virus-­ positive diffuse large B-cell lymphoma association is not only restricted to elderly patients. Int J Cancer. 2014;135(12):2816–24. 28. Kanno H, Naka N, Yasunaga Y, Iuchi K, Yamauchi S, Hashimoto M, et al. Production of the immunosuppressive cytokine interleukin-10 by Epstein-Barr-virus-expressing pyothorax-­ associated lymphoma: possible role in the development of overt lymphoma in immunocompetent hosts. Am J Pathol. 1997;150(1):349–57. 29. Kanno H, Naka N, Yasunaga Y, Aozasa K.  Role of an immunosuppressive cytokine, interleukin-­10, in the development of pyothorax-associated lymphoma. Leukemia. 1997;11(Suppl 3):525–6. 30. Kanno H, Ohsawa M, Hashimoto M, Iuchi K, Nakajima Y, Aozasa K.  HLA-A alleles of patients with pyothorax-associated lymphoma: anti-Epstein-Barr virus (EBV) host immune responses during the development of EBV latent antigen-positive lymphomas. Int J Cancer. 1999;82(5):630–4. 31. Kanno H, Nakatsuka S, Iuchi K, Aozasa K. Sequences of cytotoxic T-lymphocyte epitopes in the Epstein-Barr virus (EBV) nuclear antigen-3B gene in a Japanese population with or without EBV-positive lymphoid malignancies. Int J Cancer. 2000;88(4):626–32. 32. Kanno H, Yasunaga Y, Iuchi K, Yamauchi S, Tatekawa T, Sugiyama, et  al. Interleukin-6-­ mediated growth enhancement of cell lines derived from pyothorax-associated lymphoma. Lab Investig. 1996;75(2):167–73. 33. Ma J, Nie K, Redmond D, Liu Y, Elemento O, Knowles DM, et al. EBV-miR-BHRF1-2 targets PRDM1/Blimp1: potential role in EBV lymphomagenesis. Leukemia. 2016;30:594–604.

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34. Gurbuxani S, Anastasi J, Hyjek E. Diffuse large B-cell lymphoma—more than a diffuse collection of large B-cells: an entity in search of a meaningful classification. Arch Pathol Lab Med. 2009;133(7):1121–34. 35. Ueda T, Andreas C, Itami J, Miyakawa K, Fujimoto H, Ito H, et al. Pyothorax-associated lymphoma: imaging findings. AJR Am J Roentgenol. 2010;194(1):76–84. 36. Takakuwa T, Luo WJ, Ham MF, Mizuki M, Iuchi K, Aozasa K. Establishment and characterization of unique cell lines derived from pyothorax-associated lymphoma which develops in long-standing pyothorax and is strongly associated with Epstein-Barr virus infection. Cancer Sci. 2003;94(10):858–63. 37. Nishiu M, Tomita Y, Nakatsuka S, Takakuwa T, Iizuka N, Hoshida Y, et al. Distinct pattern of gene expression in pyothorax-associated (PAL), a lymphoma developing in long-standing inflammation. Cancer Sci. 2004;95(10):828–34. 38. Chen Y, Jiao B, Yao M, Shi X, Zheng Z, Li S, et  al. ISG12a inhibits HCV replication and potentiates the anti-HCV activity of IFN-alpha through activation of the Jak/STAT signaling pathway independent of autophagy and apoptosis. Virus Res. 2017;227:231–9. 39. Laio X, Wang Y, Ye H, Li S, Chen L, Duan X. Role of interferon-stimulated genes in regulation of HCV infection and type I interferon anti-HCV activity. Future Virol. 2018;13(5):353–9. 40. Seif F, Khoshmirsafa M, Aazami H, Mohsenzadegan M, Sedighi G, Bahar M.  The role of JAK-STAT signaling pathway and its regulators in the fate of T helper cells. Cell Commun Signal. 2017;15(1):23. 41. Miwa H, Takakuwa T, Nakatsuka S, Tomita Y, Iuchi K, Aozasa K.  DNA sequences of the immunoglobulin heavy chain variable region gene in pyothorax-associated lymphoma. Oncology. 2002;62(3):241–50. 42. Takakuwa T, Tresnasari K, Rahadiani N, Miwa H, Daibata M, Aozasa K.  Cell origin of pyothorax-­associated lymphoma: a lymphoma strongly associated with Epstein-Barr virus infection. Leukemia. 2008;22(3):620–7. 43. Dojcinov S, Fend F, Quintanilla-Martinez L. EBV-positive lymphoproliferations of B-T- and NK-cell derivation in non-immunocompromised hosts. Pathogens. 2018;7(1):28. 44. Yamato H, Ohshima K, Suzumiya J, Kikuchi M. Evidence for local immunosuppression and demonstration of c-myc amplification in pyothorax-associated lymphoma. Histopathology. 2001;39(2):163–71. 45. Hongyo T, Kurooka M, Taniguchi E. Frequent p53 mutations at dipyrimidine sites in patients with pyothorax-associated lymphoma. Cancer Res. 1998;58(6):1105–7. 46. Ando M, Sato Y, Takata K, Nomoto J, Nakamura S, Ohshima K, et al. A20 (TNFAIP3) deletion in Epstein-Barr virus-associated lymphoproliferative disorders/lymphomas. PLoS One. 2013;8(2):e56741. 47. Giulino L, Matthew S, Ballon G, Chadburn A, Barouk S, Antonicelli G, et al. A20(TNFAIP3) genetic alterations in EBV-associated AIDS-related lymphoma. Blood. 2011;117(18):4852–4. 48. Sakamoto K, Sekizuka T, Uehara T, Hishima T, Mine S, Fukumoto H, et al. Next-generation sequencing of miRNAs in clinical samples of Epstein-Barr virus-associated B-cell lymphomas. Cancer Med. 2017;6(3):605–18. 49. Wang M, Yu F, Wu W, Wang Y, Ding H, Qian L. Epstein-Barr virus encoded microRNAs as regulators in host immune responses. Int J Biol Sci. 2018;14(5):565–76. 50. Takakuwa T, Ham MF, Luo WJ, Nakatsuka S, Daibata M, Aozasa K. Loss of expression of Epstein-Barr virus nuclear antigen-2 correlates with a poor prognosis in cases of pyothorax-­ associated lymphoma. Int J Cancer. 2006;118(11):2782–9. 51. Loong F, Chan AC, Ho BC, Chau YP, Lee HY, Cheuk W, et al. Diffuse large B-cell lymphoma associated with chronic inflammation as an incidental finding and new clinical scenarios. Mod Pathol. 2010;23(4):493–501.

Part IV

Immune Deficiency Related Lymphoproliferative Disease

Chapter 22

Plasmablastic Lymphoma Mehrnoosh Tashakori and Sanam Loghavi

Plasmablastic lymphoma (PBL) is a rare, aggressive B-cell lymphoma. The entity was initially described as a form of “diffuse large B cell lymphoma” arising in the oral cavity of individuals with HIV infection [1]. Since then, cases of PBL have also been described in the context of other immunodeficiencies including, iatrogenic immunodeficiency and age-related immune senescence, as well as in individuals without known immunodeficiency. PBL is more common in men and more frequently manifests in extra-nodal sites with frequent bone marrow involvement and B symptoms. However, clinical manifestations may be variable depending on the patient’s immune status. For instance, lymph node involvement may be seen in recipients of solid organ or stem cell transplants. The prognosis of patients with PBL is generally poor, with a median survival of ~3–35 months, and the treatment for PBL is not yet standardized [2, 3]. Given the unique phenotype of this disease, perhaps a better delineation of the genetic drivers and biological mechanisms of PBL could pave the way for better treatment strategies. PBL is characterized by plasmablastic or immunoblastic cytomorphology and loss of B-cell lineage markers such as CD20 and PAX5, and expression of plasmacytic differentiation markers such as CD38, CD138, MUM1, and BLIMP1 (Fig. 22.1). Epstein-Barr virus (EBV) infection is present in the majority (60–75%) M. Tashakori Department of Hematopathology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, USA e-mail: [email protected] S. Loghavi (*) Department of Hematopathology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_22

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a

b

c

d

Fig. 22.1  Plasmablastic lymphoma comprised of a proliferation of large, atypical, and pleomorphic lymphoid cells with plasmablastic morphology (a, hematoxylin and eosin, 400×). The neoplastic cells are negative for PAX5 (b), and positive for MUM1 (c) by immunohistochemistry and show diffuse positivity for EBV-encoded RNA by in situ hybridization (d)

of PBL cases; however, it is not required for the pathogenesis and EBV-negative cases of PBL exist [2]. It is postulated that neoplastic cells in PBL are post-germinal activated B cells, transitioning from immunoblasts to plasma cells [4]. Physiologically, the transition from activated B cells to plasma cells requires a proliferative burst which ceases by the formation of non-dividing plasma cells. In this process, the competition of B-cell maintenance versus plasma cell differentiation is tightly modulated by multiple transcription factors and mutually exclusive gene expression programs [5]. Activation of PAX5 (Paired Box Protein 5) is necessary for the maintenance of B cell lineage and prevention of differentiation to plasma cells by repressing the expression of XBP1 (X-box-binding protein 1), immunoglobulin heavy chain, immunoglobulin light chain, and immunoglobulin joining chain. PAX5 repression is a gateway to plasma cell formation [6]; however, it is not sufficient. MITF (Microphthalmia-associated transcription factor) also maintains B cell lineage via repression of IRF-4 (interferon-regulatory factor 4). Absence of MITF results in plasma cell differentiation in an IRF-4-dependent manner [7]. BCL-6 (B-cell lymphoma 6) and MTA3 (Metastasis-associated 1 family, member 3) cooperatively

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repress the expression of BLIMP1 (B-lymphocyte-induced maturation protein 1), a protein that orchestrates plasma cell differentiation [8]. Interestingly, BLIMP1 is sufficient to drive plasma cell differentiation once ectopically expressed in B cells with appropriate developmental stage [9]. Upon induction of its expression, BLIMP1 initiates transcriptional cascades that repress the B cell gene expression program to ensure that plasma cells do not revert to B cells, cease the cell cycle (by suppressing genes such as MYC), and induce immunoglobulin secretion [10–12]. XBP1 (X-box-binding protein 1) functions downstream of BLIMP1 and further regulates the secretory phenotype of plasma cells [13]. Proteomic characterization of PBL by immunohistochemical methods has shown that PBL cells have strong expression of plasma cell markers such as MUM-1/IRF4, CD138, CD38, BLIMP1, and XBP1) and completely lack or show weak expression of B cell markers such as CD20 and PAX-5. This immune profile is more akin to other plasma cell neoplasms, (PCNs) and less similar to other B-cell neoplasms such as typical diffuse large B cell lymphomas (DLBCL) [14]. Gene expression profiling studies have characterized the transcriptional profile of PBL and shown downregulation of B cell receptor signaling genes, including CD79A/B, BLK, LYN, and SWAP70 and increased expression of targets of MYC and MYB target genes which is distinct from DLBCL and more akin to plasma cells [15]. EBV-positivity in PBL is common with a reported incidence of 75% in cases associated with HIV, 67% in cases occurring in the post-transplant setting, and approximately 50% in HIV-negative patients [16]. EBVinfection inhibits MYC-­ induced apoptosis [17]; however, the regulation of MYC in PBL is far more complicated than the simple inhibitory effect of EBV. MYC-IGH translocation is the most commonly detected genetic alteration in PBL with a reported incidence of ~60%, and more commonly associated with EBV-positive cases [18, 19]. MYC rearrangements are more commonly present in PBL associated with HIV and EBV infection and less frequently in the post-transplant setting [16]. Whether MYC alteration is an initiating event or a factor contributing to disease progression in the pathogenesis of PBL remains to be elucidated [15]. In contrast to other AIDS-associated EBV+ lymphomas, Latent Membrane Protein-1 (LMP-1) and LMP2 are not expressed by EBV+ PBL cells. The gene expression profile of EBV+ and EBV− cases of PBL appears to be similar [15]. However, EBV status does appear to impact the immunogenicity of PBL with EBV+ PBL cases showing increased expression of programmed death ligand 1 (PD-­ L1) protein and other immune escape markers and decreased expression of major histocompatibility class II (MHCII)/human leukocyte A (HLA)-DR molecules leading to increased antiviral cytotoxic immunity [20, 21]. In contrast to gene expression profiling, examination of PBL at the genomic level by array comparative genomic hybridization (aCGH) reveals a pattern of genomic aberrations similar to DLBCL with high frequency (>40%) of segmental gains in 1p36.11–1p36.33, 1p34.1–1p36.13, 1q21.1–1q23.1, 7q11.2–7q11.23, 11q12–11q13.2 and 22q12.2–22q13.3. Segmental chromosomal gains and losses specific to PBL shared between PBL and AIDS-associated DLBCL, PBL, and PCN were also identified, but with lower frequency. Overall, the genomic landscape of

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PBL at the chromosomal level appears to be more similar to DLBCL rather than other plasma cell neoplasms, such as plasma cell myeloma [9]. Another study using Single Nucleotide Polymorphism (SNP)-chromosomal microarray also showed recurrent gains and losses of multiple chromosomal loci including recurrent gains of 1q31.1q44, 5p15.33p13.1, 7q11.2q11.23, 8q24.13q24.3, 11p (CD44 and PDHX) and 11q terminal regions, 15q15q26.3, 19p13.3p13.12 and chromosomes 3, 7, 11, and 15, as well as losses of 1p36.33p35.1, 6q25.1q27, 8p23.3p22.14 and 18q21.32q23 [22]. Other studies using SNP-chromosomal microarray have shown that more than half of PBL cases had either deletion or copy-neutral loss of heterozygosity (CN-LOH) involving CDKN2C at 1p32.3. Large CN-LOH (>20 Mb) were also common. Moreover, recurrent copy number losses involving IGH and IGKV (immunoglobulin kappa variable group) were also identified, confirming that recurrent chromosomal copy number alterations are a common genetic theme in PBL and suggesting that there may be substantial overlap in CNVs between PBL and plasma cell myeloma [22]. The mutational landscape of PBL has not been extensively characterized; however, Concurrent mutations in PRDM1 (encoding BLIMP1) have been found in ~50% of cases [23]. More recently, whole exome and targeted sequencing of a cohort of HIV-positive PBL cases have identified recurrent mutations involving the JAK-STAT (62%), MAPK-ERK (28%), and Notch signaling pathways [22]. The most frequently mutated genes in the JAK-STAT pathway included STAT3, JAK1, SOCS1, JAK2, and PIM1 while the most commonly mutated genes in the MAPK-ERK pathway included NRAS, KRAS, BRAF, and MAP2K1. NOTCH1, SPEN, and NCOR2 were among the recurrently mutated genes involved in the Notch pathway. Somatic mutations involving MYC are present in ~9% of PBL cases. Other recurrent mutated genes in PBL included TET2 (9%), TP53 (9%), NPHP4 (5%), and genes encoding epigenetic modifiers and transcription factors implicated in B cell activation (FOXP1), positioning (KLF2), and receptor molecules involved in tumor immune surveillance (e.g. B2M, TNFRSF14) (1–5%). Another study through exome sequencing of 52 cases of de novo HIV-positive PBL cases showed somatic mutations involving members of the non-canonical NFκB pathway and genes involved in immune response [24]. The non-­canonical NF-κB pathway is an important arm of NF-κB signaling that predominantly targets activation of the p52/RelB NF-κB complex. This pathway depends on the inducible processing of p100, a molecule functioning as both the precursor of p52 and a RelBspecific inhibitor. Approximately 70% of PBL in this study showed constitutive p100 signaling. Mutations in the NF-κB pathway were identified in all the analyzed cases, with an average of 4 mutated genes per case. Consistent with the previously reported downregulation in RNA expression of genes implicated in the BCR and canonical NF-κB signaling, recurrent deleterious mutations involving genes in the BCR pathway including, MATL1, FYN, and SYK were identified with respective frequencies of 24%, 16%, and 15%. Importantly this study also revealed frequent novel mutations in the MYD88-PI3P pathway genes including, SHIP2, DOCK8, and PLCG2 in 50%, 39%, and 37% of the HIV+ PBL cases, respectively. The

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authors further evaluated the status of phosphorylation of TAK1 and BTK in these tumors using immunohistochemistry and showed high levels of phosphorylation of these proteins in all tumors analyzed (n = 15). These findings have particular therapeutic implications as these mutations are postulated to result in increased MYD88/ TAK1 and BTK signaling and may be amenable to targeted therapy using specific inhibitors. MicroRNA (miRNA) profiling of PBL has shown that PBL has overlapping features with both Burkitt lymphoma and extramedullary plasmacytoma and that PBL can be divided into 2 distinct subgroups based on miRNA profiling, one group with a miRNA profile akin to extramedullary plasmacytoma and the second group with a miRNA profile akin to Burkitt lymphoma, respectively. Interestingly, these molecular subgroups correspond to different clinicopathological features including, HIV status, MYC rearrangement, and disease localization [25]. In summary, although numerous studies have been performed attempting to characterize the clinical, phenotypic, and genotypic features of plasmablastic lymphoma, the small sample size of most studies due to the rarity of this entity continues to be a limiting factor. Therefore, despite extensive research on the regulation of MYC in PBL, its causative role in the initiation vs progression of PBL remains speculative. The same applies to the role of HIV and EBV in the pathogenesis of this aggressive disease. Additional large multi-institutional and cooperative group studies of PBL may help overcome this limitation and further characterize the unique genetic landscape of this aggressive lymphoma.

References 1. Delecluse HJ, Anagnostopoulos I, Dallenbach F, Hummel M, Marafioti T, Schneider U, et al. Plasmablastic lymphomas of the oral cavity: a new entity associated with the human immunodeficiency virus infection. Blood. 1997;89(4):1413–20. 2. Loghavi S, Alayed K, Aladily TN, Zuo Z, Ng SB, Tang G, et al. Stage, age, and EBV status impact outcomes of plasmablastic lymphoma patients: a clinicopathologic analysis of 61 patients. J Hematol Oncol. 2015;8:65. 3. Castillo JJ, Bibas M, Miranda RN. The biology and treatment of plasmablastic lymphoma. Blood. 2015;125(15):2323–30. 4. Castillo JJ, Reagan JL.  Plasmablastic lymphoma: a systematic review. Sci World J. 2011;11:687–96. 5. Shapiro-Shelef M, Calame K.  Regulation of plasma-cell development. Nat Rev Immunol. 2005;5(3):230–42. 6. Cobaleda C, Schebesta A, Delogu A, Busslinger M. Pax5: the guardian of B cell identity and function. Nat Immunol. 2007;8(5):463–70. 7. Lin L, Gerth AJ, Peng SL. CpG DNA redirects class-switching towards “Th1-like” Ig isotype production via TLR9 and MyD88. Eur J Immunol. 2004;34(5):1483–7. 8. Fujita N, Jaye DL, Geigerman C, Akyildiz A, Mooney MR, Boss JM, et  al. MTA3 and the Mi-2/NuRD complex regulate cell fate during B lymphocyte differentiation. Cell. 2004;119(1):75–86. 9. Chang CC, Zhou X, Taylor JJ, Huang WT, Ren X, Monzon F, et  al. Genomic profiling of plasmablastic lymphoma using array comparative genomic hybridization (aCGH): revealing

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significant overlapping genomic lesions with diffuse large B-cell lymphoma. J Hematol Oncol. 2009;2:47. 10. Angelin-Duclos C, Cattoretti G, Lin KI, Calame K. Commitment of B lymphocytes to a plasma cell fate is associated with Blimp-1 expression in vivo. J Immunol. 2000;165(10):5462–71. 11. Lin Y, Wong K, Calame K. Repression of c-myc transcription by Blimp-1, an inducer of terminal B cell differentiation. Science. 1997;276(5312):596–9. 12. Shaffer AL, Lin KI, Kuo TC, Yu X, Hurt EM, Rosenwald A, et al. Blimp-1 orchestrates plasma cell differentiation by extinguishing the mature B cell gene expression program. Immunity. 2002;17(1):51–62. 13. Shaffer AL, Shapiro-Shelef M, Iwakoshi NN, Lee AH, Qian SB, Zhao H, et al. XBP1, downstream of Blimp-1, expands the secretory apparatus and other organelles, and increases protein synthesis in plasma cell differentiation. Immunity. 2004;21(1):81–93. 14. Montes-Moreno S, Gonzalez-Medina AR, Rodriguez-Pinilla SM, Maestre L, Sanchez-Verde L, Roncador G, et  al. Aggressive large B-cell lymphoma with plasma cell differentiation: immunohistochemical characterization of plasmablastic lymphoma and diffuse large B-cell lymphoma with partial plasmablastic phenotype. Haematologica. 2010;95(8):1342–9. 15. Chapman J, Gentles AJ, Sujoy V, Vega F, Dumur CI, Blevins TL, et al. Gene expression analysis of plasmablastic lymphoma identifies downregulation of B-cell receptor signaling and additional unique transcriptional programs. Leukemia. 2015;29(11):2270–3. 16. Morscio J, Dierickx D, Nijs J, Verhoef G, Bittoun E, Vanoeteren X, et al. Clinicopathologic comparison of plasmablastic lymphoma in HIV-positive, immunocompetent, and posttransplant patients: single-center series of 25 cases and meta-analysis of 277 reported cases. Am J Surg Pathol. 2014;38(7):875–86. 17. Fanidi A, Hancock DC, Littlewood TD.  Suppression of c-Myc-induced apoptosis by the Epstein-Barr virus gene product BHRF1. J Virol. 1998;72(10):8392–5. 18. Valera A, Balague O, Colomo L, Martinez A, Delabie J, Taddesse-Heath L, et al. IG/MYC rearrangements are the main cytogenetic alteration in plasmablastic lymphomas. Am J Surg Pathol. 2010;34(11):1686–94. 19. Taddesse-Heath L, Meloni-Ehrig A, Scheerle J, Kelly JC, Jaffe ES. Plasmablastic lymphoma with MYC translocation: evidence for a common pathway in the generation of plasmablastic features. Mod Pathol. 2010;23(7):991–9. 20. Gravelle P, Pericart S, Tosolini M, Fabiani B, Coppo P, Amara N, et al. EBV infection determines the immune hallmarks of plasmablastic lymphoma. Onco Targets Ther. 2018;7(10):e1486950. 21. Laurent C, Fabiani B, Do C, Tchernonog E, Cartron G, Gravelle P, et al. Immune-checkpoint expression in Epstein-Barr virus positive and negative plasmablastic lymphoma: a clinical and pathological study in 82 patients. Haematologica. 2016;101(8):976–84. 22. Liu Z, Filip I, Gomez K, Engelbrecht D, Meer S, Lalloo PN, et al. Genomic characterization of HIV-associated plasmablastic lymphoma identifies pervasive mutations in the JAK-STAT pathway. Blood Cancer Discov. 2020;1(1):112–25. 23. Montes-Moreno S, Martinez-Magunacelaya N, Zecchini-Barrese T, Villambrosia SG, Linares E, Ranchal T, et al. Plasmablastic lymphoma phenotype is determined by genetic alterations in MYC and PRDM1. Mod Pathol. 2017;30(1):85–94. 24. Cinar M, Rong HR, Chineke I, Louissaint A, Chapman-Fredricks JR, Vega F, Gunthel CJ, Love C, Mosunjac M, Flowers CR, Dave S, Lossos IS, Bernal-Mizrachi L. Genetic analysis of plasmablastic lymphomas in HIV (+) patients reveals novel driver regulators of the noncanonical NF-κB pathway. Blood. 2018;132:1565. 25. Ambrosio MR, Mundo L, Gazaneo S, Picciolini M, Vara PS, Sayed S, et  al. MicroRNAs sequencing unveils distinct molecular subgroups of plasmablastic lymphoma. Oncotarget. 2017;8(64):107356–73.

Chapter 23

Genetic Landscape of Post-transplant Lymphoproliferative Disorders Rima Koka and Michael E. Kallen

According to the WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues, post-transplant lymphoproliferative disorders (PTLD) are any lymphoid or plasmacytic neoplasms that arise as a consequence of solid organ or stem cell transplantation-­associated immunosuppression [1]. Therefore, PTLDs encompass a large variety of neoplasms that are morphologically and genetically unique. This heterogeneity makes understanding the pathophysiology of PTLD extremely difficult. One of the major forces behind the development of PTLD is the Epstein-Barr virus (EBV). EBV-associated PTLD ranges from non-destructive polyclonal proliferations to monoclonal aggressive lymphomas. PTLDs that are not driven by EBV are significantly harder to understand from a pathophysiologic standpoint. Since many EBV-negative PTLD tend to be more aggressive lymphomas that occur years after transplantation, it is unclear whether these patients would have developed malignancies even in the absence of transplantation and immunosuppression. Interestingly, the newly proposed “hit-and-run” hypothesis postulates that a certain subset of EBV-negative Hodgkin and aggressive B-cell lymphomas are initially EBV-driven but with loss of the viral episomal genome once the tumor clone is established [2]. Fragments of EBV nucleic acids were found by using real-time quantitation PCR and RNAscope in several cases of diffuse large B-cell lymphoma, Burkitt lymphoma, and classical Hodgkin lymphoma, previously designated to be EBV-negative. This was done in a cohort of lymphomas outside of the transplantation setting. Therefore, additional studies in EBV-negative PTLD will be of particular interest to ascertain whether the “hit-and-run” hypothesis applies in this cohort [2]. Understanding the genetics of PTLD and contrasting them to similar

R. Koka (*) · M. E. Kallen Department of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2023 G. M. Crane, S. Loghavi (eds.), Precision Molecular Pathology of Aggressive B-Cell Lymphomas, Molecular Pathology Library, https://doi.org/10.1007/978-3-031-46842-1_23

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lymphomas that develop in immunocompetent patients may hold the key to understanding the pathophysiology of PTLD, and the exact role transplantation plays in their development.

Epidemiology Patients receiving solid organ transplantation have a higher risk of developing PTLD than those receiving stem cell transplantation, with the latter showing a frequency of 1–2%. Among the solid organ transplant recipients, combined heart/lung, lung, and gastrointestinal tract transplantation have the highest frequency of PTLD (≥5%), followed by heart and liver at 1–5%. Kidney transplantation carries the lowest risk at