Identification of Prognostic Markers in Cholangiocarcinoma Using Altered DNA Methylation and Gene Expression Profiles - Mishra, Nitish Kumar; Niu, Meng; Southekal, Siddesh; Bajpai, Prachi; Elkholy, Amr; Manne, Upender; Guda, Chittibabu (Frontiers in Genetics, 2020)
Background: Cholangiocarcinoma (CCA) is a rare disease, but it is among the deadliest cancers with a median survival under one year. Alterations in DNA methylation and gene expression have been widely studied in other cancers for their role in pathogenesis and disease prognosis, but such studies are very limited in CCA. This study focusses on the identification of prognostic biomarkers using multi-omics data on DNA methylation and gene expression of CCA tumors from The Cancer Genome Atlas (TCGA). Method: We carried out a genome-wide analysis of differential DNA methylation and gene/miRNA expression using data from 36 CCA tumor and 9 normal samples from TCGA. The impact of DNA methylation in promoters and long-range distal enhancers on the regulation and expression of CCA-associated genes was examined using linear regression. Next, we conducted network analyses on genes that are controlled by DNA methylation as well as by miRNA. Finally, we performed Kaplan-Meier and Cox proportional hazards regression analyses in order to identify the role of selected methylation sites and specific genes and miRNAs in patient survival. Results: Altered DNA methylation was observed on 12,259 CpGs across all chromosomes, of which 78% were hypermethylated. We observed a strong negative correlation between promoter hypermethylation and corresponding gene expression in 92% of the CpGs. Differential expression analyses revealed altered expression patterns in 3,305 genes and 101 miRNAs. Finally, we identified 17 differentially methylated promoter CpGs, 72 differentially expressed genes, and two miRNAs that are likely associated with patient survival. Pathway analysis suggested that cell division, bile secretion, amino acid metabolism, PPAR signaling, hippo signaling were highly impacted by altered gene expression and DNA methylation. Conclusions: Based on the survival analysis, we conclude that DEPDC1, FUT4, MDK, PACS1, PIWIL4 genes, miR-22, miR-551b microRNAs, and cg27362525 and cg26597242 CpGs can strongly support their use as prognostic markers of CCA.