M2 macrophage related genes predict prognosis and drug response in prostate cancer.

BACKGROUND: M2 macrophages significantly contribute to the advancement of prostate cancer (PCa). This research aims to pinpoint M2 macrophage-associated genes (M2RGs) by leveraging single-cell analyses, with a focus on evaluating their prognostic and therapeutic implications in PCa. METHODS: We utilized transcriptomic and scRNA-seq datasets sourced from GEO and TCGA, analyzing both PCa and nearby non-cancerous tissues. M2 macrophage infiltration levels were quantified through “Cibersort” and “xCell” algorithms, followed by assessing their relationship with PCa outcomes. We identified M2RGs using differential expression analysis from scRNA-seq data. A risk score model (M2GS) was subsequently developed using COX and LASSO regression to predict biochemical recurrence-free survival (BRFS) and drug sensitivity. ROC curve analysis and subgroup assessments were conducted to evaluate model performance. Additionally, a nomogram integrating M2GS and clinical parameters was created to refine prediction accuracy. RESULTS: Higher infiltration levels of M2 macrophages were linked to poorer outcomes in patients with prostate cancer (PCa). Using COX regression and LASSO analyses, we identified seven M2 macrophage-related genes (M2RGs) with prognostic significance: MTUS1, NFE2L2, CD9, NOP56, KIF22, RBM3, and RALGDS, which were incorporated into an M2-related gene signature (M2GS). ROC analysis affirmed the model’s predictive capabilities, yielding AUC values of 0.702, 0.752, and 0.831 for predicting 1-, 3-, and 5-year survival, respectively. Subgroup analysis and violin plot comparisons highlighted distinct drug sensitivity patterns between high- and low-risk groups defined by M2GS. Both M2GS and T stage were independently validated as prognostic indicators. The nomogram demonstrated consistent calibration and strong predictive performance. CONCLUSION: Our prognostic risk scoring model effectively predicts BRFS and drug responsiveness in prostate cancer, providing clinicians with valuable guidance for tailoring individualized treatment strategies and follow-up protocols for patients.