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

Brooke L Fridley et al. Cancer Epidemiol Biomarkers Prev. 2012 Mar.

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.

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Conflict of interest statement

Disclosure of Potential Conflicts of Interest

The authors have no conflict of interest to declare.

Figures

Figure 1
Figure 1
Hierarchical clustering dendrogram of gene sets with p < 0.005 (distance measure based on proportion of SNPs in common between gene sets) for the analysis of (A) all cases and (B) HGS cases.

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