Authors
Xuancai Chen, Wei Su, Qun Zhou, Yucheng Qi, Juanjuan Xie, Yachun Tang, Xin Tang, Hao Fu
Published in
PloS one. Volume 21. Issue 7. Pages e0354354. Epub Jul 31, 2026.
Abstract
Prostate cancer (PCa) is characterized by molecular heterogeneity and metabolic reprogramming, but the relationships among transcriptomic, proteomic, and metabolic signals remain incompletely defined. Here, we present a human-centered, cross-dataset analysis of public RNA, protein, and metabolomics data in PCa. We analyzed RNA and protein profiles from PC3 parental and drug-resistant cells together with an independent human matched tissue metabolomics dataset from Metabolomics Workbench (ST000784). RNA-protein overlap analysis identified seven genes that were significant at both layers, including five concordantly upregulated genes: UPP1, IGF2R, FLNC, DSP, and PLEC. Among these, UPP1 provided the most direct metabolic interpretation because it encodes uridine phosphorylase 1, an enzyme linked to pyrimidine salvage. Independent ST000784 matched prostate tissue metabolomics supported broader nucleotide metabolism remodeling, including significant changes in N-carbamoyl-L-aspartate, guanosine monophosphate, and adenosine 3,5-cyclic monophosphate. In contrast, uracil was not significantly altered and uridine 5'-monophosphate showed only a trend after multiple-testing correction. Repeated stratified cross-validation showed that UPP1-containing candidate gene sets achieved high within-layer AUC values in RNA and protein data, while nested statistical benchmark models also performed strongly. These results prioritize a UPP1-associated nucleotide remodeling hypothesis in PCa, but do not establish causal regulation of metabolite abundance or clinical diagnostic utility. Future matched multi-omics and perturbation experiments are required.
PMID:
42536695
Bibliographic data and abstract were imported from PubMed on 01 Aug 2026.
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