Utilization of Hypoxia-Derived Gene Signatures to Predict Clinical Outcomes and Immune Checkpoint Blockade Therapy Responses in Prostate Cancer.

Background: Increasing evidences show a clinical significance in the interaction between hypoxia and prostate cancer. However, reliable prognostic signatures based on hypoxia have not been established yet. Methods: We screened hypoxia-related gene modules by weighted gene co-expression network analysis (WGCNA) and established a hypoxia-related prognostic risk score (HPRS) model by univariate Cox and LASSO-Cox analyses. In addition, enriched pathways, genomic mutations, and tumor-infiltrating immune cells in HPRS subgroups were analyzed and compared. HPRS was also estimated to predict immune checkpoint blockade (ICB) therapy response. Results: A hypoxia-related 22-gene prognostic model was established. Furthermore, three independent validation cohorts showed moderate performance in predicting biochemical recurrence-free (BCR-free) survival. HPRS could be a useful tool in selecting patients who can benefit from ICB therapy. The CIBERSORT results in our study demonstrated that hypoxia might act on multiple T cells, activated NK cells, and macrophages M1 in various ways, suggesting that hypoxia might exert its anti-tumor effects by suppressing T cells and NK cells. Conclusion: Hypoxia plays an important role in the progression of prostate cancer. The hypoxia-derived signatures are promising biomarkers to predict biochemical recurrence-free survival and ICB therapy responses in patients with prostate cancer.