Abstract

Cancer-associated fibroblasts (CAFs) play an integral role in modulating the biological behavior of cancer cells through intricate and dynamic communication networks. However, the specific mechanism by which CAFs influence bladder cancer (BCa) remains elusive. This study integrated transcriptome data from multiple datasets to construct a gene ensemble associated with CAFs using a series of computational algorithms. This analysis identified two distinct molecular subtypes of BCa, characterized by varying levels of immune cell infiltration and immune-related features. CAMK4 was subsequently selected for further validation, revealing its role in enhancing the tumor-promoting functions of BCa, particularly in terms of proliferation, migration, invasion, and the induction of epithelial-mesenchymal transition (EMT). To sum up, the identified signature and its corresponding subtypes enable the identification of potential candidates for immunotherapy among BCa patients. Additionally, CAMK4 may emerge as a promising therapeutic target for BCa treatment.