Identification of a cancer-associated fibroblast signature for predicting prognosis and immunotherapeutic responses in bladder urothelial carcinoma

Abstract

Background Cancer-associated fibroblasts (CAFs) are the most important cellular components in bladder urothelial carcinoma (BLCA) and are involved in the development and immunosuppression of BLCA. Therefore, we aimed to construct a CAF-associated signature for predicting the prognosis and immunotherapy response in patients with BLCA. Methods CAF infiltration and stromal score were quantified using two algorithms. Weighted gene co-expression network analysis (WGCNA) was performed to identify the CAF-associated modules and hub genes. Univariate Cox and Least Absolute Shrinkage and Selection Operator regression analyses were used for constructing CAF signatures and calculating CAF scores. The ability of the CAF signature to predict prognosis and response to immunotherapy was validated using the data from three cohorts. Results WGCNA identified two CAF-associated modules and constructed a CAF signature containing 27 genes. In all three cohorts, patients with high CAF scores had markedly worse prognoses than those with low CAF scores, and CAF scores were independent risk factors. In addition, patients with high CAF scores did not respond to immunotherapy, whereas those with lower CAF scores responded to immunotherapy. Conclusion CAF signature can be used to predict prognosis and immunotherapy response to guide individualized treatment planning in patients with BLCA.