Esophageal Cancer Epigenomics and Integrome Analysis of Genome-Wide Methylation and Expression in High Risk Northeast Indian Population.

Esophageal cancer is a major global health burden with a strong host-environment interaction component and epigenomics underpinnings that remain to be elucidated further. Certain populations such as the Northeast Indians suffer at a disproportionately higher rate from this devastating disease. Promoter methylation is correlated with transcriptional silencing of various genes in esophageal cancer. Very few studies on genome-wide methylation for esophageal cancer exist and yet, no one has carried out an integromics analysis of methylation and gene expression. In the present study, genome-wide methylation was measured in samples collected from the Northeast Indian population by Infinium 450k array, and integration of the methylation data was performed. To prepare a network of genes displaying enriched pathways, together with the list of genes exhibiting promoter hypermethylation or hypomethylation with inversely correlated expression, we performed an integrome analysis. We identified 23 Integrome network enriched genes with relevance to tumor progression and associated with the processes involved in metastasis such as cell adhesion, integrin signaling, cytoskeleton, and extracellular matrix organizations. These included four genes (PTK2, RND1, RND3, and UBL3) with promoter hypermethylation and downregulation, and 19 genes (SEMG2, CD97, CTNND2, CADM3, OMD, NEFM, FBN2, CTNNB1, DLX6, UGT2B4, CCDC80, PZP, SERPINA4, TNFSF13B, NPC1, COL1A1, TAC3, BMP8A, and IL22RA2) with promoter hypomethylation and upregulation. A Methylation Efficiency Index was further calculated for these genes; the top five gene with the highest index were COL1A1, TAC3, SERPINA4, TNFSF13B, and IL22RA2. In conclusion, we recommend that the circulatory proteins IL22RA2, TNFSF13B, SERPINA4, and TAC3 in serum of patients and disease-free healthy controls can be examined in the future as putative noninvasive biomarkers.

KEYWORDS: {{ getKeywords(articleDetailText.words) }}