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      Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

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      1 , 2 , 3 , 4 , 2 , 5 , 6 , 7 , 8 , 9 , 3 , 10 , 11 , 1 , 2 , 3 , 12 , 13 , 14 , 15 , 16 , 17 , 13 , 18 , 3 , 19 , 12 , 16 , 14 , 1 , 7 , 8 , 9 , 20 , 1 , 2 , 21 , 7 , 8 , 22 , 18 , 21 , 7 , 8 , 9 , 18 , 2 , 23 , 22 , 24 , 16 , 3 , 24 , 17 , 2 , 5 , 25 , 26 , 25 , 27 , 28 , 8 , 5 , 29 , 17 , 3 , 4 , 17 , 15 , 30 , 31 , 5 , ICGC MMML-Seq Consortium, 7 , 8 , 9 , 32 , 29 , 33 , 3 , 12 , , 1 , 2 ,
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          Abstract

          Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG- MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing.

          Abstract

          Burkitt lymphoma (BL) is the most common pediatric B-cell lymphoma. Here, within the International Cancer Genome Consortium, the authors performed whole genome and transcriptome sequencing of 39 sporadic BL, describing the landscape of mutations, structural variants, and mutational processes that underpin this disease how alterations on different cellular levels cooperate in deregulating key pathways and complexes.

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          Most cited references63

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          Sequencing newly replicated DNA reveals widespread plasticity in human replication timing.

          Faithful transmission of genetic material to daughter cells involves a characteristic temporal order of DNA replication, which may play a significant role in the inheritance of epigenetic states. We developed a genome-scale approach--Repli Seq--to map temporally ordered replicating DNA using massively parallel sequencing and applied it to study regional variation in human DNA replication time across multiple human cell types. The method requires as few as 8,000 cytometry-fractionated cells for a single analysis, and provides high-resolution DNA replication patterns with respect to both cell-cycle time and genomic position. We find that different cell types exhibit characteristic replication signatures that reveal striking plasticity in regional replication time patterns covering at least 50% of the human genome. We also identified autosomal regions with marked biphasic replication timing that include known regions of monoallelic expression as well as many previously uncharacterized domains. Comparison with high-resolution genome-wide profiles of DNaseI sensitivity revealed that DNA replication typically initiates within foci of accessible chromatin comprising clustered DNaseI hypersensitive sites, and that replication time is better correlated with chromatin accessibility than with gene expression. The data collectively provide a unique, genome-wide picture of the epigenetic compartmentalization of the human genome and suggest that cell-lineage specification involves extensive reprogramming of replication timing patterns.
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            Realizing the promise of cancer predisposition genes.

            Genes in which germline mutations confer highly or moderately increased risks of cancer are called cancer predisposition genes. More than 100 of these genes have been identified, providing important scientific insights in many areas, particularly the mechanisms of cancer causation. Moreover, clinical utilization of cancer predisposition genes has had a substantial impact on diagnosis, optimized management and prevention of cancer. The recent transformative advances in DNA sequencing hold the promise of many more cancer predisposition gene discoveries, and greater and broader clinical applications. However, there is also considerable potential for incorrect inferences and inappropriate clinical applications. Realizing the promise of cancer predisposition genes for science and medicine will thus require careful navigation.
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              A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling.

              The distinction between Burkitt's lymphoma and diffuse large-B-cell lymphoma is unclear. We used transcriptional and genomic profiling to define Burkitt's lymphoma more precisely and to distinguish subgroups in other types of mature aggressive B-cell lymphomas. We performed gene-expression profiling using Affymetrix U133A GeneChips with RNA from 220 mature aggressive B-cell lymphomas, including a core group of 8 Burkitt's lymphomas that met all World Health Organization (WHO) criteria. A molecular signature for Burkitt's lymphoma was generated, and chromosomal abnormalities were detected with interphase fluorescence in situ hybridization and array-based comparative genomic hybridization. We used the molecular signature for Burkitt's lymphoma to identify 44 cases: 11 had the morphologic features of diffuse large-B-cell lymphomas, 4 were unclassifiable mature aggressive B-cell lymphomas, and 29 had a classic or atypical Burkitt's morphologic appearance. Also, five did not have a detectable IG-myc Burkitt's translocation, whereas the others contained an IG-myc fusion, mostly in simple karyotypes. Of the 176 lymphomas without the molecular signature for Burkitt's lymphoma, 155 were diffuse large-B-cell lymphomas. Of these 155 cases, 21 percent had a chromosomal breakpoint at the myc locus associated with complex chromosomal changes and an unfavorable clinical course. Our molecular definition of Burkitt's lymphoma clarifies and extends the spectrum of the WHO criteria for Burkitt's lymphoma. In mature aggressive B-cell lymphomas without a gene signature for Burkitt's lymphoma, chromosomal breakpoints at the myc locus were associated with an adverse clinical outcome. Copyright 2006 Massachusetts Medical Society.
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                Author and article information

                Contributors
                m.schlesner@Dkfz-Heidelberg.de
                reiner.siebert@uni-ulm.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                29 March 2019
                29 March 2019
                2019
                : 10
                : 1459
                Affiliations
                [1 ]GRID grid.410712.1, Institute of Human Genetics, , Ulm University and Ulm University Medical Center, ; 89081 Ulm, Germany
                [2 ]ISNI 0000 0001 2153 9986, GRID grid.9764.c, Institute of Human Genetics, , Christian-Albrechts-University, ; 24105 Kiel, Germany
                [3 ]ISNI 0000 0004 0492 0584, GRID grid.7497.d, Division of Theoretical Bioinformatics (B080), , German Cancer Research Center (DKFZ), ; 69120 Heidelberg, Germany
                [4 ]ISNI 0000 0001 2190 4373, GRID grid.7700.0, Department for Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology and Bioquant, , University of Heidelberg, ; 69120 Heidelberg, Germany
                [5 ]ISNI 0000 0001 2153 9986, GRID grid.9764.c, Hematopathology Section, , Christian-Albrechts-University, ; 24105 Kiel, Germany
                [6 ]ISNI 0000 0000 8584 9230, GRID grid.411067.5, Pediatric Hematology and Oncology, , University Hospital Giessen, ; 35392 Giessen, Germany
                [7 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Interdisciplinary Center for Bioinformatics, , University of Leipzig, ; 04107 Leipzig, Germany
                [8 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Bioinformatics Group, Department of Computer, , University of Leipzig, ; 04107 Leipzig, Germany
                [9 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Transcriptome Bioinformatics, LIFE Research Center for Civilization Diseases, , University of Leipzig, ; 04107 Leipzig, Germany
                [10 ]Department of Pediatric Immunology, Hematology and Oncology, University Hospital, 69120 Heidelberg, Germany
                [11 ]GRID grid.482664.a, German Cancer Research Center (DKFZ), Division of Stem Cells and Cancer, , Heidelberg, Germany and Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), ; 69120 Heidelberg, Germany
                [12 ]ISNI 0000 0004 0492 0584, GRID grid.7497.d, Bioinformatics and Omics Data Analytics (B240), , German Cancer Research Center (DKFZ), ; 69120 Heidelberg, Germany
                [13 ]ISNI 0000 0001 2190 4373, GRID grid.7700.0, Faculty of Biosciences, , Heidelberg University, ; 69120 Heidelberg, Germany
                [14 ]ISNI 0000 0001 2190 4373, GRID grid.7700.0, Cell Networks, Bioquant and Biochemistry CenterBiochemie Zentrum Heidelberg (BZH), , University of Heidelberg, ; 69120 Heidelberg, Germany
                [15 ]Institute for Medical Informatics Statistics and Epidemiology, 04107 Leipzig, Germany
                [16 ]ISNI 0000 0004 0495 846X, GRID grid.4709.a, Genome Biology Unit, , EMBL Heidelberg, ; 69117 Heidelberg, Germany
                [17 ]ISNI 0000 0004 0492 0584, GRID grid.7497.d, Division of Molecular Genetics, , German Cancer Research Center (DKFZ), ; 69120 Heidelberg, Germany
                [18 ]ISNI 0000 0004 0492 0584, GRID grid.7497.d, Division of Applied Bioinformatics (G200), , German Cancer Research Center (DKFZ), ; 69120 Heidelberg, Germany
                [19 ]ISNI 0000 0001 2190 4373, GRID grid.7700.0, Medical Faculty Heidelberg, , Heidelberg University, ; 69120 Heidelber, Germany
                [20 ]ISNI 0000 0000 9071 0620, GRID grid.419538.2, Department of Genome Regulation, , Max Planck Institute for Molecular Genetics, ; 14195 Berlin, Germany
                [21 ]ISNI 0000 0004 0646 2097, GRID grid.412468.d, Department of Pediatrics, , University Hospital Schleswig-Holstein, ; Campus Kiel, 24105 Kiel, Germany
                [22 ]ISNI 0000 0001 2176 9917, GRID grid.411327.2, Medical Faculty, Department of Pediatric Oncology, Hematology and Clinical Immunology, , Heinrich-Heine-University, ; 40225 Düsseldorf, Germany
                [23 ]ISNI 0000 0004 1936 9721, GRID grid.7839.5, Senckenberg Institute of Pathology, , University of Frankfurt Medical School, ; 60590 Frankfurt am Main, Germany
                [24 ]ISNI 0000 0001 2218 4662, GRID grid.6363.0, Institute of Pathology, , Charité – University Medicine Berlin, ; 10117 Berlin, Germany
                [25 ]ISNI 0000 0001 2153 9986, GRID grid.9764.c, Institute of Clinical Molecular Biology, , Christian-Albrechts-University, ; 24105 Kiel, Germany
                [26 ]ISNI 0000 0001 1958 8658, GRID grid.8379.5, Institute of Pathology, Comprehensive Cancer Center Mainfranken, , University of Würzburg, ; 97080 Würzburg, Germany
                [27 ]GRID grid.497650.9, Pathodiagnostik Berlin, ; 12099 Berlin, Germany
                [28 ]ISNI 0000 0004 1936 9748, GRID grid.6582.9, Department for Internal Medicine III, , Ulm University, ; 89081 Ulm, Germany
                [29 ]ISNI 0000 0001 2187 5445, GRID grid.5718.b, Institute of Cell Biology (Cancer Research), Medical School, , University of Duisburg-Essen, ; 45147 Essen, Germany
                [30 ]GRID grid.410712.1, Institute of Pathology, , University of Ulm and University Hospital of Ulm, ; 89081 Ulm, Germany
                [31 ]ISNI 0000 0001 2364 4210, GRID grid.7450.6, Department of Hematology and Oncology, , Georg-August-University of Göttingen, ; 37075 Göttingen, Germany
                [32 ]ISNI 0000 0000 9999 5706, GRID grid.418245.e, Computational Biology, , Leibniz Institute on Ageing-Fritz Lipmann Institut (FLI), ; 07745 Jena, Germany
                [33 ]ISNI 0000 0004 0551 4246, GRID grid.16149.3b, University Hospital Münster - Pediatric Hematology and Oncology, ; 48149 Münster, Germany
                [34 ]Department of Internal Medicine/Hematology, Friedrich-Ebert-Hospital, Neumünster, 24534 Germany
                [35 ]ISNI 0000 0004 0477 2585, GRID grid.411095.8, Department of Medicine III - Campus Grosshadern, , University Hospital Munich, ; Munich, 81377 Germany
                [36 ]ISNI 0000 0001 1958 8658, GRID grid.8379.5, University Hospital Würzburg, Department of Medicine and Poliklinik II, , University of Würzburg, ; Würzburg, 97080 Germany
                [37 ]GRID grid.491861.3, Department of Medicine III, Hematology and Oncology, , Dr. Horst-Schmidt-Kliniken of Wiesbaden, ; Wiesbaden, 65199 Germany
                [38 ]ISNI 0000 0004 0646 2097, GRID grid.412468.d, Department of Internal Medicine II: Hematology and Oncology, , University Medical Centre, ; Campus Kiel, Kiel, 24105 Germany
                [39 ]Hospital of Internal Medicine II, Hematology and Oncology, St-Georg Hospital Leipzig, Leipzig, 04129 Germany
                [40 ]ISNI 0000 0004 0603 4965, GRID grid.416008.b, Department of Pathology, , Robert-Bosch-Hospital, ; Stuttgart, 89081 Germany
                [41 ]ISNI 0000 0000 8785 9045, GRID grid.459927.4, Clinic for Hematology and Oncology, , St.-Antonius-Hospital, ; Eschweiler, 52249 Germany
                [42 ]National Centre for Tumor Disease, Heidelberg, 69120 Germany
                [43 ]GRID grid.410712.1, Comprehensive Cancer Center Ulm (CCCU), , University Hospital Ulm, ; Ulm, 89081 Germany
                [44 ]ISNI 0000 0001 2153 9986, GRID grid.9764.c, Department of General Internal Medicine, , University Kiel, ; Kiel, 24105 Germany
                Author information
                http://orcid.org/0000-0001-6644-1659
                http://orcid.org/0000-0002-1859-2281
                http://orcid.org/0000-0003-3042-9521
                http://orcid.org/0000-0001-5633-8826
                http://orcid.org/0000-0002-1905-4717
                http://orcid.org/0000-0002-6121-4737
                http://orcid.org/0000-0001-5940-3101
                http://orcid.org/0000-0002-2798-3794
                http://orcid.org/0000-0002-9543-4084
                http://orcid.org/0000-0002-5016-5191
                http://orcid.org/0000-0001-8287-5967
                http://orcid.org/0000-0002-0034-4036
                http://orcid.org/0000-0002-6691-7191
                http://orcid.org/0000-0002-5896-4086
                Article
                8578
                10.1038/s41467-019-08578-3
                6440956
                30926794
                dc240e59-03dc-4d08-a853-b4deede8f63e
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 August 2018
                : 18 January 2019
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