Abstract
BACKGROUND: The present study aims to identify immune-related RBPs signature to predict prognosis and therapy response in prostate cancer. METHODS: Differentially expressed RBPs were compared and visualized using R packages. Immune-related RBPs were selected by Pearson correlation analysis. The prognostic immune-related RBPs were identified using the Kaplan-Meier method and LASSO regression. A multivariable Cox regression model was used to construct immune-related RBPs signature. RESULTS: We constructed a prognostic predictive risk model of prostate cancer containing ten immune-related RBP genes. We found that high-risk prostate cancer patients presented poorer prognosis, higher tumor immune cell infiltration, higher rates of genomic alterations, and were more sensitive to targeted and immunotherapy than the low-risk group. CONCLUSIONS: The immune-related RBPs' signature is an independent prognostic marker that could help screen patients with advanced prostate cancer who are better suited for targeted and immunotherapy.