Deciphering the Novel Target Genes Involved in the Epigenetics of Hepatocellular Carcinoma Using Graph Theory Approach

Abstract

Background: Even after decades of research, cancer, by and large, remains a challenge and is one of the major causes of death worldwide. For a very long time, it was believed that cancer is simply an outcome of changes at the genetic level but today, it has become a well-established fact that both genetics and epigenetics work together resulting in the transformation of normal cells to cancerous cells. Objective: In the present scenario, researchers are focusing on targeting epigenetic machinery. The main advantage of targeting epigenetic mechanisms is their reversibility. Thus, cells can be reprogrammed to their normal state. Graph theory is a powerful gift of mathematics which allows us to understand complex networks. Methodology: In this study, graph theory was utilized for quantitative analysis of the epigenetic network of hepato-cellular carcinoma (HCC) and subsequently finding out the important vertices in the network thus obtained. Secondly, this network was utilized to locate novel targets for hepato-cellular carcinoma epigenetic therapy. Results: The vertices represent the genes involved in the epigenetic mechanism of HCC. Topological parameters like clustering coefficient, eccentricity, degree, etc. have been evaluated for the assessment of the essentiality of the node in the epigenetic network. Conclusion: The top ten novel epigenetic target genes involved in HCC reported in this study are cdk6, cdk4, cdkn2a, smad7, smad3, ccnd1, e2f1, sf3b1, ctnnb1, and tgfb1.

Platelet Mitochondrial DNA Methylation as Epigenetic Biomarker of Short-Term Air Pollution Exposure in Healthy Subjects

“…As a kind of non-nucleated cell, platelet mitochondrial DNA plays a crucial role in cell regulation. Epigenetic changes in genes, such as elevated levels of methylation, are associated with an increased risk of cardiovascular disease ( Roy et al, 2019 ). Usually, mitochondrial genomic DNA methylation levels are shallow.…”

Systems Genomics in the Age of Next Generation Sequencing (Part II)

“…Roy et al in their article entitled, "Deciphering the novel target genes involved in the epigenetics of hepatocellular carcinoma using graph theory approach" [1] applied graph theory approaches for drawing a network of genes in identifying novel targets for hepatocellular carcinoma epigenetic therapy. The candidates they found were statistically coherent for the therapeutic use.…”