Transforming growth factor beta receptor 2 single-nucleotide polymorphism association with oral cancer and In silico identification of small drug-like molecules as inhibitors to transforming growth factor Beta-2 receptor

Abstract

Objective: Oral cancer, in India, constitutes 26% of global oral cancer burden. The major risk factors include tobacco, areca nut, alcohol, and human papillomavirus 16/18; however, only 5%–10% of the high-risk individuals develop oral cancer, indicating the role of genomic variants in susceptibility to oral cancer. Conventional treatment options in oral cancer have resulted in relatively poor prognosis and an unmet need of treatment. In silico analysis, therefore, was performed to identify small drug-like molecules as potential inhibitors of transforming growth factor beta-2 receptor (TGFβRII). Materials and Methods: Seven single-nucleotide polymorphisms (SNPs) were analyzed in 500 histopathologically confirmed oral cancer samples and 500 long-term tobacco users (LTTUs) as controls using allelic discrimination real-time polymerase chain reaction or high-resolution melting analysis. The differential frequencies in oral cancer and LTTUs were calculated using SPSS software (version 19), and odds ratio (OR) to indicate risk to oral cancer using Hutchon.net. structure-based virtual screening of drug-like molecules was performed to identify lead inhibitor molecules to TGFβRII using Schrödinger Suite 2015-4. Results: Heterozygous GC genotype of TGFBR2 rs9843143 demonstrated increased risk ([P = 0.011; OR 1.61 [1.25–2.1]) while CC genotype showed decreased risk (P = 0.005; OR 0.61 [0.44–0.83]) to oral cancer. Increased/decreased risk to oral cancer was not observed for the other SNPs. In silico analysis identified six molecules as inhibitors of TGFβRII kinase domain from 17,723 conformers from Maybridge HitFinder library and 2685 conformers from MEGx AnalytiCon natural product library. Conclusion: SNP rs9843143 (TGFBR2) demonstrated a significant association (P < 0.05) with oral cancer and six potential inhibitors of TGFβRII kinase were identified using in silico analysis.