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      Recurrent Somatic Mutations in Regulatory Regions of Human Cancer Genomes

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          Abstract

          Aberrant regulation of gene expression in cancer can promote survival and proliferation of cancer cells. Here we integrate TCGA whole genome sequencing data of 436 patients from eight cancer subtypes with ENCODE and other regulatory annotations to identify point mutations in regulatory regions. We find evidence for positive selection of mutations in transcription factor binding sites, consistent with these sites regulating important cancer cell functions. Using a novel method that adjusts for sample- and genomic locus-specific mutation rate, we identify recurrently mutated sites across cancer patients. Mutated regulatory sites include known sites in the TERT promoter and many novel sites, including a subset in proximity to cancer genes. In reporter assays, two novel sites display decreased enhancer activity upon mutation. These data demonstrate that many regulatory regions contain mutations under selective pressure and suggest a larger role for regulatory mutations in cancer than previously appreciated.

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          Most cited references20

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Genome-wide analysis of non-coding regulatory mutations in cancer

            Cancer primarily develops due to somatic alterations in the genome. Advances in sequencing have enabled large-scale sequencing studies across many tumor types, emphasizing discovery of alterations in protein-coding genes. However, the protein-coding exome comprises less than 2% of the human genome. Here, we analyze complete genome sequences of 863 human tumors from The Cancer Genome Atlas and other sources to systematically identify non-coding regions that are recurrently mutated in cancer. We utilize novel frequency and sequence-based approaches to comprehensively scan the genome for non-coding mutations with potential regulatory impact. We identified recurrent mutations in regulatory elements upstream of PLEKHS1, WDR74, and SDHD, as well as previously identified mutations in the TERT promoter. SDHD promoter mutations are frequent in melanoma and associated with reduced gene expression and poor patient prognosis. The non-protein-coding cancer genome remains widely unexplored and our findings represent a step towards targeting the entire genome for clinical purposes.
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              Cell-of-origin chromatin organization shapes the mutational landscape of cancer

              Cancer is a disease potentiated by mutations in somatic cells. Cancer mutations are not distributed uniformly along the genome. Instead, different genomic regions vary by up to 5-fold in the local density of somatic mutations 1 , posing a fundamental problem for statistical methods of cancer genomics. Epigenomic organization has been proposed as a major determinant of the cancer mutational landscape 1-5 . However, both somatic mutagenesis and epigenomic features are highly cell-type-specific 6,7 . We investigated the distribution of mutations in multiple samples of diverse cancer types and compared them to cell-type-specific epigenomic features. Here, we show that chromatin accessibility and modification, together with replication timing, explain up to 86% of the variance in mutation rates along cancer genomes. Overwhelmingly, the best predictors of local somatic mutation density are epigenomic features derived from the most likely cell type of origin of the corresponding malignancy. Moreover, we find that cell-of-origin chromatin features are much stronger determinants of cancer mutation profiles than chromatin features of cognate cancer cell lines. We show further that the cell type of origin of a cancer can be accurately determined based on the distribution of mutations along its genome. Thus, DNA sequence of a cancer genome encompasses a wealth of information about the identity and epigenomic features of its cell of origin.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                15 May 2015
                08 June 2015
                July 2015
                01 January 2016
                : 47
                : 7
                : 710-716
                Affiliations
                [1 ]Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
                [2 ]Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, CA, USA
                Author notes
                [3 ]Correspondence to: mpsnyder@ 123456stanford.edu
                Article
                NIHMS690173
                10.1038/ng.3332
                4485503
                26053494
                45e5f1ed-84b6-4f39-ae57-bb81d2056fd2
                History
                Categories
                Article

                Genetics
                Genetics

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