ABSTRACT
In the bloodstream and in local tissues, most IGF molecules are associated with the one of the members of the IGF-binding protein (IGFBP) family, which are divided into six distinct types. IGF-binding proteins have been demonstrated to either decrease or increase the growth-promoting effects of IGFs on cell culture, by extending their half-life. They alter how IGFs interact with the receptors on their cell surfaces. IGFBP6 gene is associated with disease in-situ carcinoma. Upregulation or downregulation of IGFBP6 gene has been implicated in different types of cancer in humans. Nonsynonymous SNPs changes have the potential to affect the protein's structure and function. Potential functional SNPs can be assessed before undertaking studies in larger populations because validation of these functional SNPs can be a crucial problem. So, in this in-silico investigation, we used a variety of sequence- and structure-based bioinformatics methods to separate the potential nsSNPs of the IGFBP6 gene from the neutral ones. In total of 216 nsSNPs, 5 were found to have potential effects using 5 prediction tools. From which, 2 nsSNPs (R128G and R164H) were selected as potentially damaging due to their presence in highly conserved region and ability to decrease protein stability. Among these 2 nsSNPs, only R164H was found to be associated with Uterine corpus endometrial carcinoma. It was also found that both, upregulation or downregulation of IGFBP6 gene can lead to the different types of cancers. The findings of the present study will certainly be valuable in the future large population-based investigations as well as drug discovery, especially developing personalized medicine.Communicated by Ramaswamy H. Sarma.
