利用缺氧衍生基因特征预测前列腺癌的临床结果和免疫检查点阻断治疗反应

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.