ANALYSIS AND ANNOTATION OF EXOME SEQUENCING DATA TO IDENTIFY AND PRIORITIZE GENES RESPONSIBLE FOR PROSTATE ADENOCARCINOMA

Abstract

After skin cancer prostate cancer is the second most prevalent cancer in men. Somatic mutations in Prostate Adenocarcinoma are revealed by processing of the next-generation DNA sequencing data of the exome region. Mutation in exome region directly effects the expression of the genes and sometimes inhibits the expression which can lead to several diseases. High throughput technologies and NGS analysis enable us to find out variations in the exome region that are involved in complex pathways of cancers. Biomarkers can be identified using NGS and exome sequencing analysis pipelines which can help in diagnosis, treatment and prognosis of the cancer. Exome play a major role in protein profiling so any change in this region affect the individual. PRAD exome data was used to analyze the variations in the exome region. Data for PRAD was downloaded from the TCGA web portal for tumor matched with normal types 17 samples on which exome sequence analysis pipeline were applied to predict and prioritize the genes involved for PRAD pathway. Perl programming language was used to prioritize and analyze the exome data. Perl script maf2vcf.pl, DisGeNET, Annovar software packages were used to find out 93 probable genes that were filtered from DisGeNET. Then 54 genes were found in conserved regions with phastconselements46way score > 400. 17 TCGA IDs samples showed sequence alignment errors which were filtered by matching with segmented duplications. Polyphen2 annotations were used to give scores about the deleterious effect of the variants. After these steps we got the most probable genes that might be responsible for the cause of Prostate Adenocarcinoma (PRAD). GSTT1, TP53, CYP19A1, BRAF genes were already involved in the pathway of occurrence of prostate cancer and these genes were also present in the filtered genes in this study. Using experimental validation methods on the filtered genes we may help in finding out the novel genes that are involved in the complex pathway of prostate cancer.