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      COSMIC: the Catalogue Of Somatic Mutations In Cancer

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          Abstract

          COSMIC, the Catalogue Of Somatic Mutations In Cancer ( https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC’s deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.

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          Most cited references1

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          Open Targets: a platform for therapeutic target identification and validation

          We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.
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            Author and article information

            Journal
            Nucleic Acids Res
            Nucleic Acids Res
            nar
            Nucleic Acids Research
            Oxford University Press
            0305-1048
            1362-4962
            08 January 2019
            29 October 2018
            29 October 2018
            : 47
            : Database issue , Database issue
            : D941-D947
            Affiliations
            [1 ]Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
            [2 ]Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge CB4 0QA, UK
            [3 ]Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
            Author notes
            To whom correspondence should be addressed. Tel: +44 1223 494730; Email: jt6@ 123456sanger.ac.uk
            Article
            gky1015
            10.1093/nar/gky1015
            6323903
            30371878
            fadd4e60-162e-4e65-9327-4cbb2818fd7c
            © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

            History
            : 11 October 2018
            : 10 October 2018
            : 14 September 2018
            Page count
            Pages: 7
            Funding
            Funded by: Wellcome Trust 10.13039/100004440
            Award ID: 206194
            Categories
            Database Issue

            Genetics
            Genetics

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