Abstract
The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has clarified its clinical significance in predicting outcomes and efficacy. However, there are no studies on the systematic analysis of TME characteristics in bladder cancer. In this study, we comprehensively evaluated the TME invasion pattern of bladder cancer in 1,889 patients, defined three different TME phenotypes, and found that different subtypes were associated with the clinical prognosis and pathological characteristics of bladder cancer. We further explored the signaling pathways, cancer-immunity cycle, copy number, and somatic mutation differences among the different subtypes and used the principal component analysis algorithm to calculate the immune cell (IC) score, a tool for comprehensive evaluation of TME. Univariate and multivariate Cox regression analyses showed that ICscore is a reliable and independent prognostic biomarker. In addition, the use of anti-programmed death-ligand (PD-L1) treatment cohort, receiver operating characteristic (ROC) curve, Tumor Immune Dysfunction and Exclusion (TIDE), Subnetwork Mappings in Alignment of Pathways (SubMAP), and other algorithms confirmed that ICscore is a reliable prognostic biomarker for immune checkpoint inhibitor response. Patients with higher ICscore showed a significant therapeutic advantage in immunotherapy. In conclusion, this study improves our understanding of the characteristics of TME infiltration in bladder cancer and provides guidance for more effective personalized immunotherapy strategies.
Highlights
Bladder cancer is the ten most common cancer worldwide, is difficult to diagnose early, metastasizes rapidly, but currently has ineffective treatments [1, 2]
The clustering results are in line with the immunological principles reported in a previous article: clusters A and B were similar to cold tumors, but they had different microenvironment composition phenotypes, and cluster C was a similar hot tumor
We found that CD8 T effector, immune checkpoint, epithelial-mesenchymal transition (EMT), and antigen processing machinery were significantly higher in cluster A and lowest in cluster C, while nucleotide excision repair, DNA damage response, DNA replication, and base excision repair were the lowest in cluster B (Figure 3A and Supplementary Table 5)
Summary
Bladder cancer is the ten most common cancer worldwide, is difficult to diagnose early, metastasizes rapidly, but currently has ineffective treatments [1, 2]. Immune checkpoint therapy (ICT) is an immunotherapy that targets cytotoxic lymphocyte antigen-4 (CTLA-4), programmed cell death protein 1 (PD-1), or programmed death ligand 1 (PD-L1) [3,4,5]. Immunotherapeutics for PD-1 or Analysis of TME in Bladder Cancer. PD-L1 have greatly improved the survival of some patients and changed the intervention measures for advanced bladder cancer. Most patients gain little to no clinical benefits from these immunotherapeutics [6, 7]. Previous studies have found that PD-1 and PD-L1 expression, microsatellite instability status, and mutation load are not the best biomarkers for predicting immune checkpoint inhibitor responsiveness [8, 9]. It is necessary to establish new predictive indicators for checkpoint immunotherapy
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