Exome sequencing identifies a spectrum of mutation frequencies in advanced and lethal prostate cancers.
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ABSTRACT: To catalog protein-altering mutations that may drive the development of prostate cancers and their progression to metastatic disease systematically, we performed whole-exome sequencing of 23 prostate cancers derived from 16 different lethal metastatic tumors and three high-grade primary carcinomas. All tumors were propagated in mice as xenografts, designated the LuCaP series, to model phenotypic variation, such as responses to cancer-directed therapeutics. Although corresponding normal tissue was not available for most tumors, we were able to take advantage of increasingly deep catalogs of human genetic variation to remove most germline variants. On average, each tumor genome contained ~200 novel nonsynonymous variants, of which the vast majority was specific to individual carcinomas. A subset of genes was recurrently altered across tumors derived from different individuals, including TP53, DLK2, GPC6, and SDF4. Unexpectedly, three prostate cancer genomes exhibited substantially higher mutation frequencies, with 2,000-4,000 novel coding variants per exome. A comparison of castration-resistant and castration-sensitive pairs of tumor lines derived from the same prostate cancer highlights mutations in the Wnt pathway as potentially contributing to the development of castration resistance. Collectively, our results indicate that point mutations arising in coding regions of advanced prostate cancers are common but, with notable exceptions, very few genes are mutated in a substantial fraction of tumors. We also report a previously undescribed subtype of prostate cancers exhibiting "hypermutated" genomes, with potential implications for resistance to cancer therapeutics. Our results also suggest that increasingly deep catalogs of human germline variation may challenge the necessity of sequencing matched tumor-normal pairs.
SUBMITTER: Kumar A
PROVIDER: S-EPMC3193229 | biostudies-literature | 2011 Oct
REPOSITORIES: biostudies-literature
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