Urine and plasma metabolomic panels for non-invasive monitoring of prostate cancer progression and dietary response
1 Department of Nutrition and Ditetics, University of Nigeria, Nsukka.
2 Department Nutrition and Dietetics, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
3 Department of Biology, Georgia State University, United States
4 Nigerian Institute of Medical Research
5 Rostov State Medical University, Russia
6 Department of Public Health, Federal University of Technology Owerri Imo State, Nigeria
7 Department of Public Administration, Ambrose Alli University, Ekpoma, Nigeria
Review
International Journal of Life Science Research Archive, 2026, 10(01), 027-045.
Article DOI: 10.53771/ijlsra.2026.10.1.0014
Publication history:
Received on 14 December 2025; revised on 22 January 2026; accepted on 24 January 2026
Abstract:
Prostate cancer (PCa) is one of the most prevalent forms of cancer in men worldwide, and despite how much advances have been made in the area of genetics and imaging, non-invasive, dynamic, reasonably priced biomarkers for disease monitoring and treatment customization, are still urgently required. Urine and plasma metabolomics have become effective tools for identifying biochemical changes linked to the development of prostate cancer, the effectiveness of treatment, and dietary modification throughout the last five years. Recent developments (2020–2025) in the creation and use of urine and plasma metabolomic panels for non-invasive prostate cancer surveillance are summarized in this study. It examines how diagnostic and prognostic metabolite signatures, such as changes in polyamine metabolism, lipid dysregulation, branched-chain amino acids, and citrate cycle intermediate which distinguish localized from metastatic disease are being revealed by high-throughput liquid chromatography-mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and integrated multi-omic technologies. According to recent studies, clinical interpretability and prediction accuracy, are improved upon, when dietary data is integrated with plasma, and also urine metabolite profiles. The study also discusses how circulating metabolites, are connected to androgen metabolism, and even tumor growth. It also shows how systemic inflammation, are impacted by dietary patterns, including plant-based, Mediterranean, and also high-fat based diets. Deep neural networks and machine learning algorithms have been combined to enhance metabolite-based risk assessment and provide opportunities for tailored treatment improvement. Analytical standardization, data harmonization, external validation, and also, regulatory qualification are amongst the major translational obstacles, which are examined in detail. In general, the convergence of precision oncology, nutritional science, and then metabolomics, does represent a paradigm shift in the treatment of prostate cancer. Hence, Urine and plasma metabolomic profiling, do provide a new non-invasive window into tumor biology and host-diet interactions, thereby, allowing for early detection, real-time monitoring, and also, the introduction of well tailored dietary interventions, in order to improve treatment outcomes.
Keywords:
Prostate cancer; Metabolomics; Urine biomarkers; Plasma metabolomics; Dietary response; Liquid biopsy; Multi-omic integration; Precision oncology; Non-invasive diagnostics; Machine learning
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