An innovative risk index based on neutrophils and macrophages can effectively predict prognosis and immunotherapy response in patients with muscle-invasive bladder cancer.

Abstract

This study aimed to establish an innovative prognostic risk index based on tumor-infiltrating immune cells (TIICs) for patients with muscle-invasive bladder cancer (MIBC). We used the CIBERSORT algorithm to calculate the abundance of immune cells in MIBC samples from the The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and stepwise regression analysis were used to identify the included immune cells. Then, we constructed the risk index based on these cells through multivariate Cox regression analysis. By the risk index formula, we obtained the risk score of each patient and divided the patients into high-risk and low-risk groups. Kaplan-Meier (K-M) curve was used for survival analysis between groups. The receiver operating characteristic (ROC) curve was used to measure the prediction accuracy of the index. We validated the performance of the index in the IMvigor210 immunotherapy cohort. In addition, we established a nomogram combining the index and clinical characteristics. Finally, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differential genes between groups. The risk index we constructed consists of three variables, including M0 macrophages, M2 macrophages, and neutrophils. K-M curve showed that the risk score had good risk stratification performance. Moreover, the risk score correlates with the patient's response to chemotherapy and immunotherapy. The nomogram has good accuracy and clinical benefit. GO and KEGG enrichment analysis revealed the tumor-promoting molecular mechanism of the index. The risk index based on TIICs can facilitate individualized treatment of MIBC patients by predicting prognosis and immunotherapy response.