A novel ferroptosis-related gene prognostic index for prognosis and response to immunotherapy in patients with prostate cancer.

ABSTRACT

Background: Prostate cancer (PCa) is among the leading causes of cancer death worldwide. Ferroptosis refers to an iron-dependent form of regulated cell death and is involved in prostate tumorigenesis. A few ferroptosis-related gene signatures have been developed to predict the prognosis for PCa patients. However, previous signatures were typically established based on biochemical recurrence-free survival, which has proven not to be a good surrogate for overall survival (OS). This study aimed to construct a novel ferroptosis-related gene prognostic index (FRGPI) to predict disease-free survival (DFS) and response to immunotherapy for PCa patients after radical prostatectomy. Methods: Gene expression and clinicopathological data on PCa patients were obtained from the TCGA database. Ferroptosis-related hub genes associated with DFS of PCa patients were identified by an in-depth bioinformatics analysis using a novel and comprehensive algorithm based on functional enrichment, consensus clustering, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network construction. The FRGPI was established on the basis of the genes selected using multivariate cox regression analysis and further validated in two additional PCa cohorts. Next, the clinicopathological, molecular, and immune profiles were characterized and compared between FRGPI-high and FRGPI-low subgroups. Finally, the predictive role of the FRGPI in response to immunotherapy was estimated using a metastatic urothelial cancer cohort treated with an anti-PD-L1 agent. Results: The FRGPI was constructed based on four genes (E2F1, CDC20, TYMS, and NUP85), and FRGPI-high patients had worse DFS than FRGPI-low patients. Multivariate cox regression analysis revealed that FRGPI could act as an independent prognostic factor for PCa patients after radical prostatectomy. A prognostic nomogram comprising the FRGPI and other clinicopathological parameters was established to predict the DFS for PCa patients quantitatively. In addition, comprehensive results demonstrated that high FRGPI scores showed a significantly positive correlation with worse clinicopathological features, higher mutation counts, increased frequency of copy number variations (CNVs), higher homologous recombination deficiency (HRD) and immune scores, higher mRNAsi, and more importantly, enhanced sensitivity to immunotherapy. Conclusions: FRGPI is not only a promising and robust prognostic biomarker, but also a potential indicator of immunotherapeutic outcomes for PCa patients after radical prostatectomy.