Systematic discovery of germline cancer predisposition genes through large-scale cancer genomics
Tipus de documentText en actes de congrés
Data publicació2020
EditorBarcelona Supercomputing Center
Condicions d'accésAccés obert
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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.
At the end of my scientific talk, I want to share my personal experiences as a female
scientist in the field of computational biology.
CitacióPark, S. Systematic discovery of germline cancer predisposition genes through large-scale cancer genomics. A: . Barcelona Supercomputing Center, 2020, p. 59-60.
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