Multi-omics characterization of metabolic and immune interactions in prostate cancer.

Background: Prostate cancer (PCa) is a common malignancy among men, marked by pronounced clinical and molecular heterogeneity. Metabolic reprogramming and immune evasion are recognized as critical factors in PCa progression; however, the underlying regulatory mechanisms remain insufficiently characterized. This study aimed to elucidate the interaction between metabolic reprogramming and the immune microenvironment in PCa through a multi-omics approach, and to identify key metabolic biomarkers with prognostic significance. Methods: A multi-omics analytical framework was used, integrating single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) data from publicly available datasets. Following quality control and clustering using Seurat and Signac, cell types were annotated. Key metabolic genes were identified through combined gene activity and chromatin accessibility analyses. Immune cell infiltration was estimated using Cell Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), and functional pathway enrichment was assessed using gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). Furthermore, using The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) cohort, a prognostic nomogram was constructed by integrating Results: Six distinct cell subtypes were delineated, along with enrichment of key metabolic pathways, particularly glycolysis and oxidative phosphorylation associated with tumor progression. The metabolic regulators Conclusions: