Abstract
Background: Ferroptosis is a new type of programmed cell death which has been reported to be involved in the development of various cancers. In this study, we attempted to explore the possible links between ferroptosis and prostate cancer (PCa), and a novel ferroptosis-related gene prognostic index (FGPI) was constructed to predict biochemical recurrence (BCR) and radiation resistance for PCa patients undergoing radical radiotherapy (RRT). Moreover, the tumor immune microenvironment (TME) of PCa was analyzed. Methods: We merged four GEO datasets by removing batch effects. All analyses were conducted with R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcriptional factor and competing endogenous RNA. Results: We established the FGPI based on ACSL3 and EPAS1. We observed that FGPI was an independent risk factor of BCR for PCa patients (HR: 3.03; 95% CI: 1.68-5.48), consistent with the result of internal validation (HR: 3.44; 95% CI: 1.68-7.05). Furthermore, FGPI showed high ability to identify radiation resistance (AUC: 0.963; 95% CI: 0.882-1.00). LncRNA PART1 was significantly associated with BCR and might modulate the mRNA expression of EPAS1 and ACSL3 through interactions with 60 miRNAs. Gene set enrichment analysis indicated that FGPI was enriched in epithelial-mesenchymal transition, allograft rejection, TGF beta signaling pathway, and ECM receptor interaction. Immune checkpoint and m6A analyses showed that PD-L2, CD96, and METTL14 were differentially expressed between BCR and no BCR groups, among which CD96 was significantly associated with BCR-free survival (HR: 1.79; 95% CI: 1.06-3.03). We observed that cancer-related fibroblasts (CAFs), macrophages, stromal score, immune score, estimate score, and tumor purity were differentially expressed between BCR and no BCR groups and closely related to BCR-free survival (HRs were 2.17, 1.79, 2.20, 1.93, 1.92, and 0.52 for cancer-related fibroblasts, macrophages, stromal score, immune score, estimate score, and tumor purity, respectively). Moreover, cancer-related fibroblasts (coefficient: 0.20), stromal score (coefficient: 0.14), immune score (coefficient: 0.14), estimate score (coefficient: 0.15), and tumor purity (coefficient: -0.15) were significantly related to FGPI, among which higher positive correlation between cancer-related fibroblasts and FGPI was observed. Conclusion: We found that FGPI based on ACSL3 and EPAS1 might be used to predict BCR and radiation resistance for PCa patients. CD96 and PD-L2 might be a possible target for drug action. Besides, we highlighted the importance of immune evasion in the process of BCR.