Dataset Information

Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci.

ABSTRACT: BACKGROUND:Genome-wide association studies (GWAS) have identified multiple loci associated with epithelial ovarian cancer (EOC) susceptibility, but further progress requires integration of epidemiology and biology to illuminate true risk loci below genome-wide significance levels (P < 5 × 10-8). Most risk SNPs lie within non-protein-encoding regions, and we hypothesize that long noncoding RNA (lncRNA) genes are enriched at EOC risk regions and represent biologically relevant functional targets. METHODS:Using imputed GWAS data from about 18,000 invasive EOC cases and 34,000 controls of European ancestry, the GENCODE (v19) lncRNA database was used to annotate SNPs from 13,442 lncRNAs for permutation-based enrichment analysis. Tumor expression quantitative trait locus (eQTL) analysis was performed for sub-genome-wide regions (1 × 10-5 > P > 5 × 10-8) overlapping lncRNAs. RESULTS:Of 5,294 EOC-associated SNPs (P < 1.0 × 10-5), 1,464 (28%) mapped within 53 unique lncRNAs and an additional 3,484 (66%) SNPs were correlated (r2 > 0.2) with SNPs within 115 lncRNAs. EOC-associated SNPs comprised 130 independent regions, of which 72 (55%) overlapped with lncRNAs, representing a significant enrichment (P = 5.0 × 10-4) that was more pronounced among a subset of 5,401 lncRNAs with active epigenetic regulation in normal ovarian tissue. EOC-associated lncRNAs and their putative promoters and transcription factors were enriched for biologically relevant pathways and eQTL analysis identified five novel putative risk regions with allele-specific effects on lncRNA gene expression. CONCLUSIONS:lncRNAs are significantly enriched at EOC risk regions, suggesting a mechanistic role for lncRNAs in driving predisposition to EOC. IMPACT:lncRNAs represent key candidates for integrative epidemiologic and functional studies. Further research on their biologic role in ovarian cancer is indicated. Cancer Epidemiol Biomarkers Prev; 26(1); 116-25. ©2016 AACR.

SUBMITTER: Reid BM

PROVIDER: S-EPMC5312656 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci.

Reid Brett M BM Permuth Jennifer B JB Chen Y Ann YA Teer Jamie K JK Monteiro Alvaro N A AN Chen Zhihua Z Tyrer Jonathan J Berchuck Andrew A Chenevix-Trench Georgia G Doherty Jennifer A JA Goode Ellen L EL Iverson Edwin S ES Lawrenson Kate K Pearce Celeste L CL Pharoah Paul D PD Phelan Catherine M CM Ramus Susan J SJ Rossing Mary Anne MA Schildkraut Joellen M JM Cheng Jin Q JQ Gayther Simon A SA Sellers Thomas A TA

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20161229 1

<h4>Background</h4>Genome-wide association studies (GWAS) have identified multiple loci associated with epithelial ovarian cancer (EOC) susceptibility, but further progress requires integration of epidemiology and biology to illuminate true risk loci below genome-wide significance levels (P < 5 × 10<sup>-8</sup>). Most risk SNPs lie within non-protein-encoding regions, and we hypothesize that long noncoding RNA (lncRNA) genes are enriched at EOC risk regions and represent biologically relevant f ...[more]

PMID: 28035019

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Dataset Information

Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci.

Publications

Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci.

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