Analysis of tumor microenvironment characteristics in bladder cancer: implications for immune checkpoint inhibitor therapy

Abstract

Background The tumor microenvironment (TME) has a significant influence on prognosis and immunotherapy. There are no studies on the systematic analysis of bladder cancer TME and its effect on immune checkpoint inhibitor therapy. Methods We comprehensively evaluated the TME infiltration pattern of bladder cancer in 1,889 patients and conducted extensive immunogenomic analysis to explore the heterogeneity and prognostic significance of the TME of bladder cancer. The principal component analysis algorithm was used to calculate the immune cell (IC)score to quantify the level of IC infiltration. We used the receiver operating characteristic (ROC) curve, Tumor Immune Dysfunction and Exclusion (TIDE), and Subnetwork Mappings in Alignment of Pathways (SubMAP) algorithms to evaluate whether the ICscore can predict the benefits of immune checkpoint inhibitors in bladder cancer patients. Results We identified three different TME phenotypes using unsupervised clustering methods. To explore the potential biological pathways that drive the formation of these microenvironmental phenotypes, we demonstrated the clinical and pathological characteristics, biological signaling pathways, cancer immune circulation, copy number, and somatic mutation differences among the different subtypes. In addition, univariate and multivariate Cox regression analyses showed that the ICscore is a reliable and independent prognostic marker. The ICscore can also predict immune checkpoint inhibitor responsiveness as patients with higher ICscores showed a significant therapeutic advantage in immunotherapy. Conclusions This study increases our understanding of the characteristics of TME infiltration in bladder cancer and provides guidance on more effective personalized immunotherapeutic strategies.