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Cancer Epidemiol Biomarkers Prev. 2012 Mar;21(3):529-36. doi: 10.1158/1055-9965.EPI-11-0741. Epub 2012 Feb 2.

Gene set analysis of survival following ovarian cancer implicates macrolide binding and intracellular signaling genes.

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  • 1Departments of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA. fridley.brooke@mayo.edu

Abstract

BACKGROUND:

Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes.

METHODS:

To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype.

RESULTS:

Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10(-5)) and macrolide binding (P = 6.2 × 10(-4)) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10(-4)) and macrolide binding (P = 1.0 × 10(-3)). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS.

CONCLUSION:

This research detected novel gene sets associated with EOC survival.

IMPACT:

Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies.

©2012 AACR.

PMID:
22302016
[PubMed - indexed for MEDLINE]
PMCID:
PMC3297690
Free PMC Article

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