2015 Articles

Integrative epigenomic and genomic filtering for methylation markers in hepatocellular carcinomas

Shen, Jing; LeFave, Clare; Sirosh, Iryna; Siegel, Abby B.; Tycko, Benjamin; Santella, Regina M.

Background: Epigenome-wide studies in hepatocellular carcinoma (HCC) have identified numerous genes with aberrant DNA methylation. However, methods for triaging functional candidate genes as useful biomarkers for
epidemiological study have not yet been developed. Methods: We conducted targeted next-generation bisulfite sequencing (bis-seq) to investigate associations of DNA methylation and mRNA expression in HCC. Integrative analyses of epigenetic profiles with DNA copy number
analysis were used to pinpoint functional genes regulated mainly by altered DNA methylation. Results: Significant differences between HCC tumor and adjacent non-tumor tissue were observed for 28 bis-seq
amplicons, with methylation differences varying from 12% to 43%. Available mRNA expression data in Oncomine were evaluated. Two candidate genes (GRASP and TSPYL5) were significantly under-expressed in HCC tumors in comparison with precursor and normal liver tissues. The expression levels in tumor tissues were, respectively, 1.828 and − 0.148, significantly lower than those in both precursor and normal liver tissue. Validations in an additional 42 paired tissues showed consistent under-expression in tumor tissue for GRASP (−7.49) and TSPYL5 (−9.71). A highly consistent DNA hypermethylation and mRNA repression pattern was obtained for both GRASP (69%) and TSPYL5 (73%), suggesting that their biological function is regulated by DNA methylation. Another two genes (RGS17 and NR2E1) at Chr6q showed significantly decreased DNA methylation in tumors with loss of DNA copy number compared to those without, suggesting alternative roles of DNA
copy number losses and hypermethylation in the regulation of RGS17 and NR2E1. Conclusions: These results suggest that integrative analyses of epigenomic and genomic data provide an efficient way to filter functional biomarkers for future epidemiological studies in human cancers.