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Abstract
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.
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.