Abstract:
PTEN (phosphatase and tensin homolog) gene is located at chromosome 10 and is responsible for tumor suppression in a variety of tumors and cancers. PTEN is involved in signal transduction and its abnormal expression level has been associated with a number of diseases including tumor and different type of cancers particularly breast cancer. Studies have shown the correlation of tumor suppressor PTEN gene with brain metastasis in cancer patients as it plays an important role in oncogenic PI3K/Akt pathway and help the tumor cells to survive in brain microenvironment. The mutations in PTEN is the major cause of disturbance in its expression level. Single nucleotide polymorphism present in coding region of proteins (nsSNPs) has the potential to alter the expression level, primary structure as well as function of the protein. Hence, it becomes necessary to differentiate the potential harmful nsSNPs from the neutral ones. Bioinformatics tools are found to be very helping in finding deleterious SNPs. Most of SNPs in human body are common in a population. However, disease-causing variants are mostly private and typically rare and mostly occur in the protein coding region which consists of only 1% of the total genome. In the current study, 6 different bioinformatics tools including SIFT, Polyphen-2, Provean, PHD-SNP and SNPs & GO and Panther were used for the prediction of deleterious SNPs of PTEN involved in disease pathogenesis. By the use of these tools, 80 out of 133 SNPs of PTEN retrieved from dbSNP database were predicted as deleterious and pathogenic. Out of these 80 SNPs, 35 have already been reported in literature, 22 of them are under study and their clinical significance has been uncertain yet, while 23 of them are novel. These results provide a filtered data to explore the effect of uncharacterized SNPs and their association with the disease susceptibility and to design the target dependent drugs for therapeutics.
