Cancer-associated fibroblasts (CAFs) drive tumor progression through restructuring of the tumor microenvironment. This investigation aim to elucidate the function of molecular subtypes (MS) derived from cancer cells communication with CAFs, depicting the hallmarks of the tumor microenvironment and precise bladder cancer (BLCA) treatment. The BLCA data from TCGA and several external sources are utilized to generate a novel ligand, receptor, and transcription factor (LRT) associated molecular subtype and their corresponding score (LRT score). The LRT-mediated molecular subtype is identified via unsupervised clustering. LRT score is measured by principal component analysis. Then, the association of LRT clusters to established MS, immunophenotypes, and medical endpoints, together with BLCA treatment strategies is investigated. Two LRT clusters (A and B) are identified. LRT cluster (LRT score) can precisely propose immunophenotypes, classical MS, clinical outcomes, and BLCA therapeutic strategies. Cluster B (Low LRT score) represent a basal subtype and inflamed phenotype specified by high immunity against tumors and unfavorable clinical outcomes. Furthermore, it is highly sensitive to cancer immunotherapy
however, it has low sensitivity to antiangiogenic and targeted therapies. The novel LRT clusters with a strong association with biological characteristics and precise BLCA treatment strategies are derived from the communication between cancer cells and cancer-associated fibroblasts. The LRT may be a useful clinician tool for developing individualized treatment strategies.