Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous XXXX Risk.

@entity43 @entity39837 @entity71439 @entity5 @entity29198 @entity45457 @entity37068 @entity56546
BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with @entity43 (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes ( @entity45457 , @entity39837 , @entity29198 , @entity56546 at 17q21.32 and @entity71439 , @entity37068 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into @entity5 susceptibility and prioritize genes for experimental characterization.
