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Updated: Jan 9, 2026

miRNA Expression Analyses in Prostate Cancer Clinical Tissues
Published on: September 8, 2015
Multi-omics characterization of metabolic and immune interactions in prostate cancer
Yong-Qiang Fu1, Feng-Xia Wang1, Jin-Feng Wu1
1Department of Urology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, The Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, China.
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 ENO1 and CKB expression with clinical parameters [age, pathological tumor stage (T stage), node stage (N stage)] via multivariate Cox regression. Gene expression differences across N stages (N0 vs. N1) were assessed using the Wilcoxon rank-sum test.
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 ENO1 and CKB demonstrated significant involvement in both metabolic reprogramming and modulation of the immune microenvironment. Their expression levels were positively correlated with the infiltration of immune cells, including CD8+ T lymphocytes and macrophages. The prognostic nomogram demonstrated that CKB contributed substantially to the total points, indicating strong prognostic relevance. Stratified analysis revealed ENO1 was significantly upregulated in N1 tumors (P<0.01), while CKB was higher in N0 tumors (P<0.05).
Conclusions:
ENO1 and CKB serve as clinically meaningful markers-ENO1 indicating metastatic potential and CKB predicting overall prognosis-while also representing promising therapeutic targets. These findings bridge molecular metabolism-immune crosstalk with clinical outcomes, offering novel perspectives for integrating metabolic intervention and immunotherapy in PCa management.
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