The established chemokine-related prognostic gene signature in prostate cancer: Implications for anti-androgen and immunotherapies - Chen, Lei; Zheng, Yi; Jiang, Changqin; Yang, Cheng; Zhang, Li; Liang, Chaozhao (Frontiers in Immunology, 2022)
Background Prostate cancer (PCa) was one of the most common malignancies among men, while the prognosis for PCa patients was poor, especially for patients with recurrent and advanced diseases. Materials and Methods Six PCa cohorts were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, and the biochemical recurrence (BCR)-related chemokine genes were identified by LASSO-Cox regression. The chemokine-related prognostic gene signature (CRPGS) was established, and its association with PCa patients’ clinical, pathological and immune characteristics was analyzed. The association between CRPGS and PCa patients’ responses to androgen deprivation therapy (ADT) and immunotherapy was analyzed. The CRPGS was compared with other previously published molecular signatures, and the CRPGS was externally validated in our real-world AHMU-PC cohort. Results Four recurrence-free survival (RFS)-related chemokine genes (CXCL14, CCL20, CCL24, and CCL26) were identified, and the CRPGS was established based on the four identified chemokine genes, and TCGA-PRAD patients with high riskscores exhibited poorer RFS, which was validated in the GSE70768 cohort. The CRPGS was associated with the clinical, pathological, and immune characteristics of PCa patients. Low-risk PCa patients were predicted to respond better to ADT and immunotherapy. By comparing with other molecular signatures, the CRPGS could classify PCa patients into two risk groups well, and the CRPGS was associated with the m6A level, as well as TP53 and SPOP mutation status of PCa patients. In the AHMU-PC cohort, the CRPGS was associated with advanced pathology stage and Gleason score, which performed well in RFS prediction. Conclusions The identified chemokine genes and CRPGS were associated with the prognosis of PCa, which could predict PCa patients’ responses to anti-androgen therapy and immunotherapy.