Identification of AQP2 as a Prognostic Biomarker in Prostate Cancer through TCGA-Based Transcriptomic Analysis

Abstract

In this research, differentially expressed genes in prostate cancer have been studied through TCGA database with the aim of elucidating on their functional features and predictive value. Differentially expressed genes (DEGs) were obtained using DESeq2 while enrichment analysis using GO and KEGG was used to examine their biological features. Survival analysis was used to determine their predictive value. It was determined that there are 123 differentially expressed genes (5 upregulated, 118 downregulated) in this cancer type. Through the enrichment analysis, it was established that these genes are mainly involved in regulation of peptidase activity, reproduction, and neuroactive ligand-receptor interactions. The survival analysis found that there is a relationship between the levels of AQP2 gene expression and overall survival rate of patients (P = 0.0098). Therefore, AQP2 can be considered as an important marker for prognosis.