Genomic Analysis Using Regularized Regression in High-Grade Serous Ovarian Cancer

Abstract

High-grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with copy number alterations, epigenetic processes, and, to a lesser extent, germline variation. We hypothesized that, when summarized at the gene level, tumor methylation and germline genetic variation, alone or in combination, influence tumor gene expression in HGSOC. We used Elastic Net (ENET) penalized regression method to evaluate these associations and adjust for somatic copy number in 3 independent data sets comprising tumors from more than 470 patients. Penalized regression models of germline variation, with or without methylation, did not reveal a role in HGSOC gene expression. However, we observed significant association between regional methylation and expression of 5 genes (WDPCP, KRT6C, BRCA2, EFCAB13, and ZNF283). CpGs retained in ENET model for BRCA2 and ZNF283 appeared enriched in several regulatory elements, suggesting that regularized regression may provide a novel utility for integrative genomic analysis.

Keywords: Elastic Net penalized regression; high-grade serous ovarian cancer; tumor DNA methylation.

Figure 1.

Distribution of BRCA2 CpG locations by retention status in ENET methylation models. CpG location represent gene region feature category describing the CpG position from UCSC: TSS1500 = 200 to 1500 bases upstream of transcription start site (TSS); TSS200 = 0 to 200 bases upstream of TSS; 5′UTR = within the 5′ untranslated region, between the TSS and ATG start site; 1stExon = within first exon of the canonical transcript; body = between the ATG and stop codon, irrespective of the presence of introns, exons, TSS, or promoters; 3′UTR = between the stop codon and polyA signal; Non_gene = region outside of all region listed above; Annotation acquired from Illumina Infinium HumanMethylation450 v1.2 manifest file, column “UCSC_RefGene_Group”; The P value presented represents results of Fisher exact test of CpG location (gene body vs other location); CpG retention in model (retained vs not retained). CpG counts are provided in Supplemental Table 1.