Esophageal squamous cell carcinoma (ESCC) is the dominant histological type of esophageal cancer significantly reported in developing nations. There is an increasing evidence suggesting that single nucleotide polymorphisms (SNPs) in the untranslated regions of genes (3'-UTRs) targeted by microRNAs (miRNAs) can change the target gene's expression and thereby affect the individual's cancer risk. Thus, in support of the role of SNPs occurring in miRNA target sites (miR-TS-SNPs) in the cancer, we analyzed the next generation sequencing data of 10 ESCC patients. In each patient, about 3,000 SNPs in 3'-UTRs were obtained in their whole-exome sequencing profiles. We applied two separate methods, manual and computational in silico approaches, to predict the miR-TS-SNPs with more effects on the miRNA-target interactions. dbSNP, 1000G, ExAC, Iranome, miRandb, miRCancer, TargetScan, Human, miRNASNP2 and miRBase databases were used for positive selection of miR-TS-SNPs and DIANA-miRPath v3.0 for pathway analysis. We identified six rare germline miR-TS-SNPs and two other ones with unknown miR-TS-SNPs. We interestingly observed all of these variants in only one patient, which can be evidence of the relationship between miR-TS-SNPs and cancer incidence. The study of cancer genetics including miR-TS-SNPs reveals miRNAs and their related pathways, which will be greatly useful in cancer research from noninvasive biomarkers to new treatments.
Keywords: ESCC; NGS; in silico analysis; miR-TS-SNPs.
© 2019 Wiley Periodicals, Inc.