IMPORTANCE: This collaborative international study defined the global heterogeneity of HPV11 and established the largest collection of globally circulating HPV11 genomic variants to date. Thirty novel complete HPV11 genomes were determined and submitted to the available sequence repositories. Global phylogenetic analysis revealed two HPV11 variant lineages and four sublineages. The HPV11 (sub)lineage-specific SNPs and the representative region identified within the partial genomic region E2/noncoding region 2 (NCR2) will enable the simpler identification and comparison of HPV11 variants worldwide. This study provides an important knowledge base for HPV11 for future studies in HPV epidemiology, evolution, pathogenicity, prevention, and molecular assay development.
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 (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 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 cancer susceptibility and prioritize genes for experimental characterization.