Abstract: The genetic causes of cancer include both somatic mutations and inherited germline variants. Large-scale tumor sequencing has revolutionized the identification of somatic driver alterations but has had limited impact on the identification of cancer predisposition genes (CPGs). Here we present a statistical method, ALFRED, that tests Knudson’s two-hit hypothesis to systematically identify CPGs from cancer genome data. Applied to ~10,000 tumor exomes the approach identifies known and putative CPGs – including the chromatin modifier NSD1 – that contribute to cancer through a combination of rare germline variants and somatic loss-of-heterozygosity (LOH). Rare germline variants in these genes contribute substantially to cancer risk, including to ~14% of ovarian carcinomas, ~7% of breast tumors, ~4% of uterine corpus endometrial carcinomas, and to a median of 2% of tumors across 17 cancer types.

Place: Aula de Teleensenyament (B3 Building, Campus Nord)

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Bioinfo4Women seminars / SORS

Venue: Barcelona

Date: 21/02/2020

Time: 11:00

Host: Barcelona Supercomputing Center

Systematic discovery of germline cancer predisposition genes through large-scale cancer genomics


Solip Park

Computational Cancer Genomics Group Leader, CNIO

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