In silico identification of novel non-synonymous variants in metabolic pathway associated target genes of papillary thyroid carcinoma: A way towards future treatment of papillary thyroid carcinoma

Abstract Single nucleotide polymorphisms (SNPs) are regarded as one of the most common genetic variations in the human genome, which can affect the structural and functional characteristics of gene/ protein to cause diseases. Thus this study aims to identify the genetic abnormality of papillary thyroid cancer (PTC) which is a complicated stuff to play a role in the evaluation, diagnosis or treatment of PTC patients. This study followed the identified up and down-regulated genes, associated in PTC related metabolic pathways from previous study for single nucleotide polymorphism (SNP) analysis through dbSNP, SIFT, PredictSNP1 and PredictSNP2 which predicted 8 and 6 highly deleterious rsIDS of non-synonymous SNPs for 5 up and 3 down-regulated target genes of PTC respectively, out of which rsIDs rs187536858, rs201950989 of nsSNPs in up-regulated target genes LPAR5, ZMAT3 and nsSNPs with rsIDs rs121913523, rs142070930, rs372232192, rs372333099 in down-regulated genes KIT, GSTM3 respectively were identified as novel nsSNPs from UniProt data for papillary thyroid carcinoma. Hence this study will help to develop a novel biomarker for solving the genetic disruption in PTC patients.