Development and evaluation of an adenosine-to-inosine RNA editing-based prognostic model for survival prediction of bladder cancer patients

Abstract

Adenosine-to-inosine RNA editing (ATIRE) is a common form of ribonucleic acid (RNA) editing, which has highlighted the importance of ATIRE in tumors. However, its role in bladder cancer (BLCA) remains poorly understood. To study ATIRE impact on BLCA patient prognosis, we obtained ATIRE, gene expression, and clinical data from the Cancer Genome Atlas (TCGA) database for 251 patients, randomly dividing them into training and testing groups. Univariate proportional hazards model (COX) regression identified prognosis-associated ATIRE loci, while the least absolute shrinkage and selection operator (LASSO) selected final loci to construct prognostic models and generate ATIRE scores. We developed a nomogram to predict BLCA patients’ overall survival (OS) and analyzed the effect of ATIRE editing levels on host gene expression. We also compared immune cell infiltration and drug treatment between patients with high and low ATIRE scores. The ATIRE prognostic prediction model was constructed using ten ATIRE loci that are closely associated with BLCA survival. Patients with high ATIRE scores showed significantly worse OS than those with low ATIRE scores. Furthermore, the nomogram, which incorporates the ATIRE score, can better predict the prognosis of patients. Multiple functional and pathway changes associated with immune responses, as well as significant differences in immune cell infiltration levels and response to drug therapy were observed between patients with high and low ATIRE scores. This study represented the first comprehensive analysis of the role of ATIRE events in BLCA patient prognosis and provided new insights into potential prognostic markers for BLCA research.