Tumor associated neutrophils promote prostate cancer progression by mediating neutrophil trap secretion through...

Prostate cancer (PCa) is a common and deadly cancer in men, and despite its low specificity, PSA testing is the main method that is used to predict prognosis. Effective methods for predicting prognosis in clinical practice are lacking. Here, ① in this retrospective analysis of clinical data of PCa patients, we discovered that patients with PCa have elevated neutrophil levels and a greater risk of complications than patients with prostatic hyperplasia. ② We integrated LASSO regression analysis and machine learning analyses to create a prognostic prediction model involving 6 genes, and this model effectively categorized patients into high-risk and low-risk groups, with higher risk scores indicating a poorer prognosis. Furthermore, we used multivariate regression analysis to confirm that the risk score was an independent prognostic factor and created nomograms on the basis of clinical characteristics. Notably, the deconvolution algorithm revealed different compositions of the tumor microenvironment, with a greater proportion of neutrophils observed in the high-risk group. ③ Finally, we conducted single-cell sequencing analysis and established a prostate cancer organoid model to confirm that TANs may exacerbate the TME in PCa via neutrophil trap formation, which is mediated by the PSMA1-NF-κB-HIF-1α signaling axis. Overall, this novel NET-related signature of PCa provides new insights for in-depth understanding and prediction of PCa prognosis.