OncoTargets and Therapy (Oct 2017)
Identification of key pathways and genes with aberrant methylation in prostate cancer using bioinformatics analysis
Abstract
Anshika N Singh, Neeti Sharma Symbiosis School of Biological Sciences, Symbiosis International University, Gram – Lavale, Taluka – Mulshi, Pune, India Abstract: Prostate cancer (PCa), a multifocal clinically heterogeneous disease, is the most commonly diagnosed non-cutaneous neoplasm in men worldwide. The epigenome of PCa is a typical representation of catastrophic model of epigenetic alterations during tumorigenesis and its progression. Alterations in methylation patterns in tumor suppressors, cell cycle, oncogenes and metabolism-related genes are the most commonly observed epigenetic alterations in PCa. In this study, we have developed a computational strategy to identify methylated biomarker signature panels as potential targets of PCa by screening >160 genes reported to be epigenetically dysregulated, and shortlisted 26 differentially methylated genes (DMGs) that significantly contribute to oncogenesis. The gene ontology and functional enrichment analysis were performed, which showed that identified DMGs contribute to cellular and metabolic processes such as cell communication, cell cycle, response to drugs, apoptosis and p53 signaling. The top hub genes AR, CDH13, CDKN2A, DAPK1, GSTP1, CD44 and RASSF1 identified from protein–protein interaction network construction using Search Tool for the Retrieval of Interacting Genes contributed to hormonal response, inflammatory response, cell cycle, reactive oxygen species activity and receptor kinase activity, which are related to hallmarks of cancer as revealed by their functional enrichment analysis by Cytoscape. These genes were further scrutinized for CpG islands, transcription start sites and positions of methylated cytosines to study their methylation profiles. Our analysis revealed high negative correlation values between methylation frequencies and gene expressions of the hub genes, namely, AR, CDH13, CDKN2A, DAPK1, CD44, GSTP1 and RASSF1, which can be used as potential diagnostic biomarkers for PCa. Keywords: prostate cancer, CpG islands, epigenetic modification, DNA methylation
