Single-Cell and Bulk RNA Sequencing Highlights Intra-Tumoral Heterogeneity and Malignant Progression Mechanisms in Prostate Cancer.

Prostate cancer (PCa) is an extremely heterogeneous cancer and is highly prevalent in the older male population. Since intra-tumour heterogeneity (ITH) commonly results in PCa chemotherapy resistance and recurrence, it is critical to explore its effects on tumour behaviour. Prognostic genes related to ITH were identified, and a signature was constructed using Cox regression analyses and multiple machine learning algorithms. Single-cell RNA sequencing data extracted from PCa and CRPC samples were analysed via sub-clustering, pseudotime, cell communication and drug sensitivity approaches to elucidate their function. The oncogenic potential of hub genes was confirmed by immunohistochemistry and cell proliferation assays. An 11-gene signature underlying a prostate cancer meta-program (PCMP) was generated by selecting an optimal combination of machine learning methods. Survival assays and multivariate Cox regression analyses conducted in multiple cohorts revealed the superior prognostic value of the PCMP signature. Functional enrichment analyses indicated that it dysregulates the cell cycle. Using trajectory and cell-cell communication analyses, we illustrated that PCMP genes exert oncogenic effects by enhancing the proliferation and oxidative phosphorylation of epithelial cells. Intra-cellular assays also demonstrated that CENPA and CKS1B had promising malignant potential. In summary, our research not only establishes the association between the PCMP signature and reveals its malignant characteristics, but also deepens our understanding of the mechanisms underlying PCa progression and ITH. It holds promise for the development of targeted therapeutic interventions, thereby offering clinical benefits to patients.