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 | |
| State | Published - Jan 31 2013 |
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ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
Cite this
GWAS meets TCGA to illuminate mechanisms of cancer predisposition. / Kim, Hyun Seok; Minna, John D.; White, Michael A.
In: Cell, Vol. 152, No. 3, 31.01.2013, p. 387-389.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - GWAS meets TCGA to illuminate mechanisms of cancer predisposition
AU - Kim, Hyun Seok
AU - Minna, John D.
AU - White, Michael A.
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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UR - http://www.scopus.com/inward/citedby.url?scp=84873279841&partnerID=8YFLogxK
U2 - 10.1016/j.cell.2013.01.027
DO - 10.1016/j.cell.2013.01.027
M3 - Article
C2 - 23374335
AN - SCOPUS:84873279841
VL - 152
SP - 387
EP - 389
JO - Cell
JF - Cell
SN - 0092-8674
IS - 3
ER -