Abstract
BACKGROUND: Prostate cancer (PCa) is a prevalent malignancy and a leading cause of cancer-related death among men. Epithelial-mesenchymal transition (EMT) plays a crucial role in tumor progression, metastasis, and treatment. However, there are limited comprehensive studies on the EMT correlation with prognosis, tumor microenvironment, and therapeutic efficacy in PCa. METHODS: We obtained mRNA expression profiles and clinical data of PCa samples, along with 1,011 protein-coding EMT-related genes from public databases. Functional annotation and consensus clustering were performed based on differentially expressed genes. An EMT prognostic signature (EPS) was constructed in the TCGA dataset after a series of bioinformatics analyses and validated in the GSE116918 dataset. The signature was used to explore clinicopathological features, genomic heterogeneity, the immune landscape, and therapy responses. Finally, we examined the expression of key genes in clinical specimens. RESULTS: An EPS was established based on four key genes (MEN1, H2AFZ, UCKL1, and FUS). The patients were classified into low-risk and high-risk groups according to their median EPS risk scores. In both datasets, patients in the high-risk group exhibited significantly lower survival rates compared to those in the low-risk group. Furthermore, the EPS risk score proved to be an independent prognostic factor, and the prognostic nomogram based on the EPS risk score and T stage yielded high accuracy. Subsequent investigations found that the EPS risk score was correlated with both tumor mutation burden and genomic heterogeneity. Notably, the low-risk group displayed a higher proportion of tumor-infiltrating immune cells and exhibited better responses to chemotherapy and immunotherapy. As expected, the validation analysis confirmed substantial overexpression of MEN1, H2AFZ, UCKL1, and FUS in PCa tissues relative to adjacent normal prostate tissues. CONCLUSION: Our preliminary EPS represents a promising biomarker for predicting PCa prognosis and has great potential for clinical application.