GWAS meets TCGA to illuminate mechanisms of cancer predisposition

Hyun Seok Kim; John D. Minna; Michael A. White

doi:10.1016/j.cell.2013.01.027

GWAS meets TCGA to illuminate mechanisms of cancer predisposition

Hyun Seok Kim, John D. Minna, Michael A. White

Research output: Contribution to journal › Short survey › peer-review

37 Scopus citations

Abstract

Genome-wide association studies (GWASs) have unraveled a large number of cancer risk alleles. Understanding how these allelic variants predispose to disease is a major bottleneck confronting translational application. In this issue, Li and colleagues combine GWASs with The Cancer Genome Atlas (TCGA) to disambiguate the contributions of germline and somatic variants to tumorigenic gene expression programs. They find that close to half of the known risk alleles for estrogen receptor (ER)-positive breast cancer are expression quantitative trait loci (eQTLs) acting upon major determinants of gene expression in tumors.

Original language	English (US)
Pages (from-to)	387-389
Number of pages	3
Journal	Cell
Volume	152
Issue number	3
DOIs	https://doi.org/10.1016/j.cell.2013.01.027
State	Published - Jan 31 2013

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)

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title = "GWAS meets TCGA to illuminate mechanisms of cancer predisposition",

abstract = "Genome-wide association studies (GWASs) have unraveled a large number of cancer risk alleles. Understanding how these allelic variants predispose to disease is a major bottleneck confronting translational application. In this issue, Li and colleagues combine GWASs with The Cancer Genome Atlas (TCGA) to disambiguate the contributions of germline and somatic variants to tumorigenic gene expression programs. They find that close to half of the known risk alleles for estrogen receptor (ER)-positive breast cancer are expression quantitative trait loci (eQTLs) acting upon major determinants of gene expression in tumors.",

author = "Kim, {Hyun Seok} and Minna, {John D.} and White, {Michael A.}",

note = "Funding Information: H.K., J.M., and M.W. are supported by the Welch Foundation (I-1414), the National Institutes of Health (CA71443, CA129451, P50 CA70907), and the Cancer Prevention Research Institute of Texas (CPRIT).",

year = "2013",

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doi = "10.1016/j.cell.2013.01.027",

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T1 - GWAS meets TCGA to illuminate mechanisms of cancer predisposition

AU - Kim, Hyun Seok

AU - Minna, John D.

AU - White, Michael A.

N1 - Funding Information: H.K., J.M., and M.W. are supported by the Welch Foundation (I-1414), the National Institutes of Health (CA71443, CA129451, P50 CA70907), and the Cancer Prevention Research Institute of Texas (CPRIT).

PY - 2013/1/31

Y1 - 2013/1/31

N2 - Genome-wide association studies (GWASs) have unraveled a large number of cancer risk alleles. Understanding how these allelic variants predispose to disease is a major bottleneck confronting translational application. In this issue, Li and colleagues combine GWASs with The Cancer Genome Atlas (TCGA) to disambiguate the contributions of germline and somatic variants to tumorigenic gene expression programs. They find that close to half of the known risk alleles for estrogen receptor (ER)-positive breast cancer are expression quantitative trait loci (eQTLs) acting upon major determinants of gene expression in tumors.

AB - Genome-wide association studies (GWASs) have unraveled a large number of cancer risk alleles. Understanding how these allelic variants predispose to disease is a major bottleneck confronting translational application. In this issue, Li and colleagues combine GWASs with The Cancer Genome Atlas (TCGA) to disambiguate the contributions of germline and somatic variants to tumorigenic gene expression programs. They find that close to half of the known risk alleles for estrogen receptor (ER)-positive breast cancer are expression quantitative trait loci (eQTLs) acting upon major determinants of gene expression in tumors.

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