Immunotherapy resistance is a significant obstacle in the treatment of prostate cancer (PCa), primarily due to immune evasion mechanisms. This study aims to explore cancer-intrinsic immune evasion-related genes (CIERGs) in PCa and develop a predictive signature for biochemical recurrence (BCR). Bulk RNA-seq data and single-cell RNA-sequencing (scRNA-seq) were obtained from TCGA and Gene Expression Omnibus database. The scRNA-seq data analysis revealed higher immune evasion scores in tumor cells compared to normal cells. Differentially expressed genes from TCGA-PRAD and GSE70769 cohorts were intersected with 182 core immune evasion genes, followed by univariate Cox regression, identifying 48 CIERGs significantly associated with BCR. Nonnegative matrix factorization (NMF) clustering revealed two immune evasion-related PCa subtypes. A risk signature based on CIERGs was developed using LASSO regression, and a nomogram was created to predict BCR-free survival. Among the 48 identified CIERGs, poly(C)-binding protein 2 (PCBP2) emerged as a key risk factor associated with poor prognosis in PCa, and its function was validated . NMF clustering identified two subtypes, with the C1 subtype having a poorer prognosis. Gene Set Variation Analysis highlighted enrichment in cell cycle, extracellular matrix receptor interaction, and transforming growth factor-beta signaling pathways in the C1 subtype. A CIERGs-based risk signature, including six key genes, was developed and validated, with the nomogram showing high predictive accuracy. experiments showed PCBP2 promotes PCa cell proliferation, migration, and invasion by inhibiting the cyclic GMP-AMP synthase-STING pathway. The CIERGs signature provides a precise prediction of BCR, with PCBP2 emerging as a potential therapeutic target due to its inhibition of the cGAS-STING pathway in PCa.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11884866PMC
http://dx.doi.org/10.1063/5.0250173DOI Listing

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