Open Access Research article

Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian cancer

Devin C Koestler1, Prabhakar Chalise1, Mine S Cicek3, Julie M Cunningham4, Sebastian Armasu3, Melissa C Larson3, Jeremy Chien2, Matthew Block5, Kimberly R Kalli5, Thomas A Sellers6, Brooke L Fridley1* and Ellen L Goode3

Author Affiliations

1 Department of Biostatistics, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS 66160, USA

2 Department of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66160, USA

3 Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA

4 Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA

5 Medical Oncology, Mayo Clinic, Rochester, MN 55905, USA

6 Office of the Director, Moffitt Cancer Center, Tampa, FL 33612, USA

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BMC Medical Genomics 2014, 7:8  doi:10.1186/1755-8794-7-8

Published: 30 January 2014

Abstract

Background

Both genetic and epigenetic factors influence the development and progression of epithelial ovarian cancer (EOC). However, there is an incomplete understanding of the interrelationship between these factors and the extent to which they interact to impact disease risk. In the present study, we aimed to gain insight into this relationship by identifying DNA methylation marks that are candidate mediators of ovarian cancer genetic risk.

Methods

We used 214 cases and 214 age-matched controls from the Mayo Clinic Ovarian Cancer Study. Pretreatment, blood-derived DNA was profiled for genome-wide methylation (Illumina Infinium HumanMethylation27 BeadArray) and single nucleotide polymorphisms (SNPs, Illumina Infinium HD Human610-Quad BeadArray). The Causal Inference Test (CIT) was implemented to distinguish CpG sites that mediate genetic risk, from those that are consequential or independently acted on by genotype.

Results

Controlling for the estimated distribution of immune cells and other key covariates, our initial epigenome-wide association analysis revealed 1,993 significantly differentially methylated CpGs that between cases and controls (FDR, q < 0.05). The relationship between methylation and case-control status for these 1,993 CpGs was found to be highly consistent with the results of previously published, independent study that consisted of peripheral blood DNA methylation signatures in 131 pretreatment cases and 274 controls. Implementation of the CIT test revealed 17 CpG/SNP pairs, comprising 13 unique CpGs and 17 unique SNPs, which represent potential methylation-mediated relationships between genotype and EOC risk. Of these 13 CpGs, several are associated with immune related genes and genes that have been previously shown to exhibit altered expression in the context of cancer.

Conclusions

These findings provide additional insight into EOC etiology and may serve as novel biomarkers for EOC susceptibility.

Keywords:
Integrative genomics; Ovarian cancer; Blood-based DNA methylation