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      Subtype-specific and co-occurring genetic alterations in B-cell non-Hodgkin lymphoma

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      1 , * , 1 , * , 2 , 2 , 1 , 1 , 3 , 4 , 3 , 1 , 1 , 1 , 5 , 5 , 6 , 7 , 8 , 9 , 9 , 10 , 11 , 12 , 1 , 1 , 1 , 1 , 8 , 7 , 1 , 5 , 13 , 2 , 2 , 14 , 5 , 1 , 14 , 15 ,
      Haematologica
      Fondazione Ferrata Storti

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          Abstract

          B-cell non-Hodgkin lymphoma (B-NHL) encompasses multiple clinically and phenotypically distinct subtypes of malignancy with unique molecular etiologies. Common subtypes of B-NHL, such as diffuse large B-cell lymphoma, have been comprehensively interrogated at the genomic level, but rarer subtypes, such as mantle cell lymphoma, remain less extensively characterized. Furthermore, multiple B-NHL subtypes have thus far not been comprehensively compared using the same methodology to identify conserved or subtype-specific patterns of genomic alterations. Here, we employed a large targeted hybrid-capture sequencing approach encompassing 380 genes to interrogate the genomic landscapes of 685 B-NHL tumors at high depth, including diffuse large B-cell lymphoma, mantle cell lymphoma, follicular lymphoma, and Burkitt lymphoma. We identified conserved hallmarks of B-NHL that were deregulated in the majority of tumors from each subtype, including frequent genetic deregulation of the ubiquitin proteasome system. In addition, we identified subtype-specific patterns of genetic alterations, including clusters of co-occurring mutations and DNA copy number alterations. The cumulative burden of mutations within a single cluster were more discriminatory of B-NHL subtypes than individual mutations, implicating likely patterns of genetic cooperation that contribute to disease etiology. We therefore provide the first cross-sectional analysis of mutations and DNA copy number alterations across major B-NHL subtypes and a framework of co-occurring genetic alterations that deregulate genetic hallmarks and likely cooperate in lymphomagenesis.

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          Most cited references65

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            Analysis of protein-coding genetic variation in 60,706 humans

            Summary Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes.
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              The 2016 revision of the World Health Organization classification of lymphoid neoplasms.

              A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities. The revision clarifies the diagnosis and management of lesions at the very early stages of lymphomagenesis, refines the diagnostic criteria for some entities, details the expanding genetic/molecular landscape of numerous lymphoid neoplasms and their clinical correlates, and refers to investigations leading to more targeted therapeutic strategies. The major changes are reviewed with an emphasis on the most important advances in our understanding that impact our diagnostic approach, clinical expectations, and therapeutic strategies for the lymphoid neoplasms.
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                Author and article information

                Journal
                Haematologica
                Haematologica
                HAEMA
                Haematologica
                Fondazione Ferrata Storti
                0390-6078
                1592-8721
                01 April 2021
                01 March 2022
                : 107
                : 3
                : 690-701
                Affiliations
                [1 ]Department of Lymphoma and Myeloma, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center , Houston, TX, USA
                [2 ]Department of Pathology and Microbiology, University of Nebraska Medical Center , Omaha, NE, USA
                [3 ]Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center , Omaha, NE, USA
                [4 ]Department of Pathology and Laboratory Medicine, University of Calgary , Calgary, Alberta, Canada
                [5 ]Section of Hematology, Department of Medicine, University of Calgary , Calgary, Alberta, Canada
                [6 ]Northern Institute for Research, Newcastle University , Newcastle upon Tyne, UK
                [7 ]Diamantina Institute, University of Queensland , Queensland, Australia
                [8 ]Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai , New York, NY, USA
                [9 ]Department of Internal Medicine, Division of Hematology-Oncology, University of Nebraska Medical Center , Omaha, NE, USA
                [10 ]Department of Pathology, Massachusetts General Hospital and Harvard Medical School , Boston, MA, USA
                [11 ]Department of Pathology, University of Massachusetts Medical School , UMass Memorial Medical Center, Worcester, MA, USA
                [12 ]Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center , Omaha, NE, USA
                [13 ]Department of Pathology, Brigham and Womens Hospital , Boston, MA, USA
                [14 ]Department of Genomic Medicine, University of Texas MD Anderson Cancer Center , Houston, TX, USA
                [15 ]Center for Cancer Epigenetics, University of Texas MD Anderson Cancer Center , Houston, TX, USA.
                Author notes
                *MCJM and ST contributed equally as co-first authors

                Disclosures

                No conflicts of interest to disclose.

                Contributions

                MCJM and ST performed experiments, analyzed data and wrote the manuscript. AB analyzed data. TH, HY, QD, DM, KH, NJ, JS, and SG performed experiments. AA, LS, MD, CC, JT, DP, KMV, MAL, ARS, BJC, RB, SN, LN, RED, JW, SP, MG, DS, KB, JI, SR, and AM provided samples and/or clinical data. MRG conceived and supervised the study, performed experiments, analyzed the data and wrote the manuscript. All authors reviewed and approved the manuscript.

                Article
                10.3324/haematol.2020.274258
                8883549
                33792219
                6900e8fe-7703-403a-8d0d-e3ea6aac9609
                Copyright© 2022 Ferrata Storti Foundation

                This article is distributed under the terms of the Creative Commons Attribution Noncommercial License ( by-nc 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

                History
                : 16 October 2020
                : 15 March 2021
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 66, Pages: 12
                Funding
                Funding : This research was supported by NCI R01CA201380 (MRG), the Nebraska Department of Health and Human Services (LB506 2016-17; MRG), and NCI cancer center support grants to the University of Texas MD Anderson Cancer Center (P30 CA016672) and the Fred & Pamela Buffet Cancer Center (P30 CA036727). HY is supported by a Fellow award from the Leukemia and Lymphoma Society. MRG is supported by a Scholar award from the Leukemia and Lymphoma Society and an Andrew Sabin Family Foundation Fellow award.
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