Abstract
Background: While the immunomodulatory function of FAM174B in bladder cancer (BLCA) has yet to be fully elucidated, elucidating its biological mechanisms could potentially enhance immunotherapeutic outcomes for this malignancy. Methods: Bulk RNA-seq data from TCGA and GEO databases were analyzed to investigate FAM174B expression patterns and immune landscape characteristics in pan-cancer. The immunoregulatory role of FAM174B in BLCA was systematically evaluated through immune infiltration analysis, immunomodulator profiling, cancer-immunity cycle assessment, and immune checkpoint examination. Validation was performed using the IMvigor210 immunotherapy cohort and a combined GEO dataset (n=871). A machine learning-based immune-related signature was developed for prognostic and therapeutic response prediction. Results: FAM174B was highly expressed in cancer tissues across multiple human cancer types including BLCA. Specifically, FAM174B negatively correlated with various immunological features including immunoregulators and immune cell infiltration abundances, suggesting that FAM174B remodeled the microenvironment to a non-inflamed phenotype of BLCA. Besides, patients with high-FAM174B expression may process limited sensitivity to immunotherapy and increased likelihood of hyperprogression. Consensus molecular classification analysis indicated that elevated FAM174B is related to a luminal BLCA subtype which was characterized by reduced immune infiltration, inhibited immuno- and chemo-therapeutic responses, yet increased response to angiogenesis inhibitors and targeted therapy. Furthermore, the immune-related signature, formulated through a machine learning-integrated approach, is shown to be a dependable indicator for predicting cancer prognosis and the efficacy of immunotherapy responses for BLCA. Conclusion: Given the pivotal role of FAM174B in shaping the non-inflamed tumor microenvironment of BLCA, therapeutic targeting of FAM174B may represent a promising strategy for BLCA management. Furthermore, FAM174B expression could serve as a potential biomarker for predicting molecular subtypes and treatment responsiveness in BLCA patients.