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Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.

Original publication

DOI

10.1038/s41588-018-0086-z

Type

Journal article

Journal

Nature genetics

Publication Date

05/2018

Volume

50

Pages

682 - 692

Addresses

Oxford Big Data Institute, University of Oxford, Oxford, UK. david.wedge@bdi.ox.ac.uk.

Keywords

CAMCAP Study Group, TCGA Consortium