WHOLE EXOME SEQUENCE ANALYSIS TO PREDICT FUNCTIONAL BIOMARKERS FOR PANCREATIC CANCER

Abstract

NGS is commonly called as massive-parallel sequencing, a technology that enabled genome to be sequenced efficiently. One of the applications of NGS is Whole exome sequencing that proves to be an effective method to to detect disease-causing variants and discover gene targets. Using whole exome sequencing data it is possible to identify clinical interventions of differentially expressed genes, somatic variants and targeted pathways to develop and assess the efficacy of novel therapies. The current work used pancreatic cancer genome sequencing data to predict significant gene variants by using exome sequencing data analysis. Here predicted 934 gene mutations identified by Exome-seq were validated by mRNA-seq. Further focused on gene expression and predicted 914 genes are differentially expressed that covers mRNA-sequences. There are 20 mutations such as HRNR, MERTK, RPL14, GLT6D1, NEO1, ZNF208, ZNF226, DNAH9 and SEZ6L is significantly involved in different pathways that integrated insulin secretion with in islet cells of pancreas and also involved in diabetes mellitus. Based on gene mutations, it is possible to screen the drugs based on pharmacogenomic characters that are functionally involved in pancreatic cancer pathways. These observations provide genetic predictors of outcome in pancreatic cancer and have implications for new avenues of therapeutic intervention.