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    Analysis of 10,478 cancer genomes identifies candidate driver genes and opportunities for precision oncology

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    Authors
    Kinnersley, B.
    Sud, A.
    Everall, A.
    Cornish, A. J.
    Chubb, D.
    Culliford, R.
    Gruber, A. J.
    Lärkeryd, A.
    Mitsopoulos, C.
    Wedge, David
    Houlston, R.
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    Affiliation
    Manchester Cancer Research Centre, University of Manchester, Manchester, U
    Issue Date
    2024
    
    Metadata
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    Abstract
    Tumor genomic profiling is increasingly seen as a prerequisite to guide the treatment of patients with cancer. To explore the value of whole-genome sequencing (WGS) in broadening the scope of cancers potentially amenable to a precision therapy, we analysed whole-genome sequencing data on 10,478 patients spanning 35 cancer types recruited to the UK 100,000 Genomes Project. We identified 330 candidate driver genes, including 74 that are new to any cancer. We estimate that approximately 55% of patients studied harbor at least one clinically relevant mutation, predicting either sensitivity or resistance to certain treatments or clinical trial eligibility. By performing computational chemogenomic analysis of cancer mutations we identify additional targets for compounds that represent attractive candidates for future clinical trials. This study represents one of the most comprehensive efforts thus far to identify cancer driver genes in the real world setting and assess their impact on informing precision oncology. Analysis of whole-genome sequencing data from over 10,000 tumor samples spanning 35 cancer types identifies putative driver genes and highlights new therapeutic opportunities.
    Citation
    Kinnersley B, Sud A, Everall A, Cornish AJ, Chubb D, Culliford R, et al. Analysis of 10,478 cancer genomes identifies candidate driver genes and opportunities for precision oncology. Nature genetics. 2024 2024 JUN 18.
    Journal
    Nature Genetics
    URI
    http://hdl.handle.net/10541/627090
    DOI
    10.1038/s41588-024-01785-9
    PubMed ID
    38890488
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41588-024-01785-9
    Scopus Count
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    All Paterson Institute for Cancer Research

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