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      Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA

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          Abstract

          Clustered somatic mutations are common in cancer genomes and previous analyses reveal several types of clustered single-base substitutions, which include doublet- and multi-base substitutions 15 , diffuse hypermutation termed omikli 6 , and longer strand-coordinated events termed kataegis 3, 79 . Here we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome-sequenced cancers from 30 types of cancer 10 . Clustered mutations were highly enriched in driver genes and associated with differential gene expression and changes in overall survival. Several distinct mutational processes gave rise to clustered indels, including signatures that were enriched in tobacco smokers and homologous-recombination-deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, whereas most multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, which have previously been attributed to APOBEC3 activity 6 , accounted for a large proportion of clustered substitutions; however, only 16.2% of omikli matched APOBEC3 patterns. Kataegis was generated by multiple mutational processes, and 76.1% of all kataegic events exhibited mutational patterns that are associated with the activation-induced deaminase (AID) and APOBEC3 family of deaminases. Co-occurrence of APOBEC3 kataegis and extrachromosomal DNA (ecDNA), termed kyklonas (Greek for cyclone), was found in 31% of samples with ecDNA. Multiple distinct kyklonic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kyklonic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fuelling the evolution of ecDNA.

          Abstract

          An analysis of clustered substitutions and indels across 30 cancer types provides insight into the role of APOBEC3 in giving rise to clustered mutation events through its activity on extrachromosomal DNA.

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          The Ensembl Variant Effect Predictor

          The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.
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            Signatures of mutational processes in human cancer

            All cancers are caused by somatic mutations. However, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here, we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, kataegis, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer with potential implications for understanding of cancer etiology, prevention and therapy.
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              The Cancer Genome Atlas Pan-Cancer analysis project.

              The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.
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                Author and article information

                Contributors
                L2alexandrov@health.ucsd.edu
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                9 February 2022
                9 February 2022
                2022
                : 602
                : 7897
                : 510-517
                Affiliations
                [1 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Cellular and Molecular Medicine, , University of California San Diego, ; La Jolla, CA USA
                [2 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Bioengineering, , University of California San Diego, ; La Jolla, CA USA
                [3 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Moores Cancer Center, , University of California San Diego, ; La Jolla, CA USA
                [4 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Bioinformatics and Systems Biology Graduate Program, , University of California San Diego, ; La Jolla, CA USA
                [5 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Computer Science and Engineering, , University of California San Diego, ; La Jolla, CA USA
                [6 ]GRID grid.66859.34, ISNI 0000 0004 0546 1623, Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [7 ]GRID grid.48336.3a, ISNI 0000 0004 1936 8075, Division of Cancer Epidemiology and Genetics, , National Cancer Institute, ; Bethesda, MD USA
                [8 ]GRID grid.83440.3b, ISNI 0000000121901201, Research Department of Pathology, Cancer Institute, , University College London, ; London, UK
                [9 ]GRID grid.412945.f, ISNI 0000 0004 0467 5857, Department of Cellular and Molecular Pathology, , Royal National Orthopaedic Hospital NHS Trust, ; Stanmore, UK
                [10 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Halıcıoğlu Data Science Institute, , University of California San Diego, ; La Jolla, CA USA
                [11 ]GRID grid.168010.e, ISNI 0000000419368956, Department of Pathology, , Stanford University School of Medicine, ; Stanford, CA USA
                [12 ]GRID grid.168010.e, ISNI 0000000419368956, ChEM-H, , Stanford University, ; Stanford, CA USA
                [13 ]GRID grid.17635.36, ISNI 0000000419368657, Howard Hughes Medical Institute, , University of Minnesota, ; Minneapolis, MN USA
                [14 ]GRID grid.17635.36, ISNI 0000000419368657, Masonic Cancer Center, , University of Minnesota, ; Minneapolis, MN USA
                [15 ]GRID grid.17635.36, ISNI 0000000419368657, Institute for Molecular Virology, , University of Minnesota, ; Minneapolis, MN USA
                [16 ]GRID grid.17635.36, ISNI 0000000419368657, Department of Biochemistry, Molecular Biology and Biophysics, , University of Minnesota, ; Minneapolis, MN USA
                Author information
                http://orcid.org/0000-0002-5650-780X
                http://orcid.org/0000-0003-2124-2706
                http://orcid.org/0000-0003-0579-4105
                http://orcid.org/0000-0003-4507-329X
                http://orcid.org/0000-0002-5810-6241
                http://orcid.org/0000-0002-4560-2211
                http://orcid.org/0000-0002-9034-9112
                http://orcid.org/0000-0003-3596-4515
                Article
                4398
                10.1038/s41586-022-04398-6
                8850194
                35140399
                2ffcb41f-1874-4d49-b576-893f34731dd7
                © The Author(s) 2022

                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
                : 27 May 2021
                : 4 January 2022
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                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                Uncategorized
                cancer,cancer genetics,cancer genomics
                Uncategorized
                cancer, cancer genetics, cancer genomics

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