Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci

Germline determinants of gene expression in tumors are infrequently studied due to the complexity of transcript regulation caused by somatically acquired alterations. We performed expression quantitative trait locus (eQTL)-based analyses using the multi-level information provided in The Cancer Genom...

Full description

Saved in:
Bibliographic Details
Published in:Cell 2013-01, Vol.152 (3), p.633-641
Main Authors: Li, Qiyuan, Seo, Ji-Heui, Stranger, Barbara, McKenna, Aaron, Pe’er, Itsik, LaFramboise, Thomas, Brown, Myles, Tyekucheva, Svitlana, Freedman, Matthew L.
Format: Article
Language:English
Subjects:
breast neoplasms
Breast Neoplasms - genetics
Cell Line, Tumor
DNA methylation
gene expression
Gene Expression Profiling
Genetic Predisposition to Disease
genome
Genome-Wide Association Study
germ cells
Humans
loci
Quantitative Trait Loci
risk
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Germline determinants of gene expression in tumors are infrequently studied due to the complexity of transcript regulation caused by somatically acquired alterations. We performed expression quantitative trait locus (eQTL)-based analyses using the multi-level information provided in The Cancer Genome Atlas (TCGA). Of the factors we measured, cis-acting eQTLs accounted for 1.2% of the total variation of tumor gene expression, while somatic copy-number alteration and CpG methylation accounted for 7.3% and 3.3%, respectively. eQTL analyses of 15 previously reported breast cancer risk loci resulted in the discovery of three variants that are significantly associated with transcript levels (false discovery rate [FDR] < 0.1). Our trans-based analysis identified an additional three risk loci to act through ESR1, MYC, and KLF4. These findings provide a more comprehensive picture of gene expression determinants in breast cancer as well as insights into the underlying biology of breast cancer risk loci. [Display omitted] ► A method to identify eQTLs from tumors by adjusting for somatic alterations ► Application of method to The Cancer Genome Atlas (TCGA) breast cancer data set ► Discovery of candidate causal genes for 6 breast cancer risk loci An eQTL-based method discriminates between germline versus somatic contributions to gene expression changes in breast cancer and identifies candidate causal genes for 6 risk loci.
ISSN:0092-8674
1097-4172
DOI:10.1016/j.cell.2012.12.034