Prediction of Immune Infiltration and Prognosis for Patients with Urothelial Bladder Cancer Based on the DNA Damage Repair-related Genes Signature

Abstract Objectives To analyze the correlations between the expression and effect of DNA damage repair genes and the immune status and clinical outcomes of urothelial bladder cancer (BLCA) patients. In addition, we evaluate the value of utilizing DNA damage repair genes signatures as a prognosis model. Methods Two subtype groups (C1 and C2) were produced based on the varied expression of DNA damage repair genes. Significantly differentiated genes and predicted enriched pathways were obtained between the two subtypes. Through infiltrating and screening, 7 key genes were obtained and a 7-gene signature prognosis model was established based on the key genes. The efficacy and accuracy of this model in prognosis prediction was evaluated and verified in two independent databases. Also, the difference in biological functions, drug sensitivity, immune infiltration and affinity between the high-risk group and low-risk group was analyzed. Results DNA damage repair gene signature could significantly differentiate the BLCA into two molecular subgroups with varied genetic expression and enriched pathways. 7 key genes were screened out from the 232 candidate genes for prognosis prediction and helped establish a 7-gene signature prognosis model. Two independent patient cohorts (TCGA cohort and GEO cohort) were utilized to validate the efficacy of the prognosis model, which demonstrated an effective capability to differentiate and predict the overall survival of BLCA patients. Also, the high-risk group and low-risk group derived from the 7-gene model exhibited significantly difference in drug sensitivity, immune infiltration status and biological pathways enrichment. Conclusions Our established 7-gene signature model based on the DNA damage repair genes could serve as a novel prognosis predictive tool for BLCA. The differentiation of BLCA patients based on the 7-gene signature model may be of great value for the appropriate selection of specific chemotherapy agents and immune-checkpoint blockade therapy administration.