Background: Epigenetics is gaining rapid recognition as it accounts for heritable changes that do not involve changes in the coding sequence, but influences change in gene expressions. DNA
methylation is the most extensively studied epigenetic mechanism and has been observed to play a significant role in gene regulation and silencing process.
Objective: In our present work, we focused on understanding the relationship between DNA
methylation and gene expression. As a proof of concept, Prostate Adenocarcinoma (PRAD), the second leading cause of death in men, was extensively studied to unravel the epigenetic abnormalities associated with disease pathogenesis which may contribute to better diagnosis and prevention of prostate cancer.
Method: DNA methylation data (level 1) and Gene expression data (level 3) was taken from The Cancer Genome Atlas (TCGA). A total of 36 samples comprising of 18 normal samples and 18 tumor samples were collected from a batch of 184 and matched with tumor samples and normal samples,
respectively. The differentially methylated regions were identified and statistical analysis was carried out for the gene expression data amongst the normal and tumor samples. Further, functional enrichment
analysis and pathway analysis were carried out for the filtered genes.
Results: Our analysis indicated 453 differentially methylated regions with p-value < 0.05, FDR (false discovery rate) value < 0.05 and beta value (methylation) > 0.2. The integration of gene expression data with methylation data resulted in 180 significant correlations from which 112 genes were filtered under
stringent conditions. Out of these 112 genes, 74 genes were filtered through visual inspection of results and their functional enrichment analysis resulted in total 27 clusters with a maximum enrichment score of ~1.86.
Conclusion: The genes "GSTP1" and "FGFR2" were present in our prioritized filtered significant
correlations, and it was discovered that these genes were known to play a primary role in prostate cancer
pathway and progression. Therefore, this approach may help to prioritize other novel genes and suggest their involvement in the prostate cancer pathway