Abstract
BackgroundProstate cancer (PCa) is a leading cause of cancer-related mortality among men, characterized by significant heterogeneity that complicates diagnosis and treatment.Methods and resultsTo enhance our understanding of PCa, we utilized single-cell RNA sequencing (scRNA-seq) data to identify distinct malignant epithelial cell subpopulations and their molecular characteristics. By integrating scRNA-seq data with bulk RNA-seq data, we constructed a prognostic risk score model. The influence of key genes identified in the risk score on PCa was validated through both in vitro and in vivo experiments. Our study revealed eight unique malignant epithelial cell clusters, each exhibiting distinct molecular characteristics and biological functions. KEGG and GO enrichment analyses highlighted their involvement in various pathways. The prognostic risk score model demonstrated strong predictive power for patient outcomes, particularly in predicting progression-free survival (PFS). Notably, KLHL17, identified as a high-risk gene, was found to significantly impact PCa cell proliferation, migration, invasion, and apoptosis upon knockdown. This finding was further validated in vivo using a subcutaneous xenograft tumor model, where reduced KLHL17 expression led to decreased tumor growth.ConclusionOur research provides a comprehensive analysis of PCa heterogeneity and highlights KLHL17 as a potential therapeutic target.
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