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Metabolomics-Based Liquid Biopsy for Predicting Clinically Significant Prostate Cancer
Yuan-Chi Lin1, Chung-Hsin Chen2, Ming-Shyue Lee3
1Department of Internal Medicine, National Taiwan University Hospital and College of Medicine, Taipei 100225, Taiwan.
Metabolomics shows promise for detecting significant prostate cancer (PC) by analyzing blood and urine biomarkers. These novel metabolic panels may offer greater accuracy than prostate-specific antigen (PSA) testing.
Area of Science:
- Biochemistry
- Oncology
- Biomarker Discovery
Background:
- Prostate cancer (PC) is a leading cause of cancer death in men.
- Prostate-specific antigen (PSA) testing lacks specificity, leading to overdiagnosis and overtreatment of clinically insignificant PC (isPC).
- Magnetic resonance imaging (MRI) aids detection but is costly and has limitations.
Purpose of the Study:
- To review studies on blood and urine metabolomics for identifying biomarkers of significant PC (sPC).
- To assess the potential of metabolomics as a tool for risk stratification in PC.
- To compare the efficacy of metabolomic panels against traditional methods like PSA testing.
Main Methods:
- Systematic review of studies investigating metabolomics in PC.
- Analysis of metabolite changes in blood and urine samples from PC patients.
- Evaluation of identified metabolic panels for sPC prediction accuracy.
Main Results:
- Significant metabolite alterations in sPC involve fatty acid, sphingolipid, glycolysis, citric acid cycle, purine/pyrimidine, and tyrosine/phenylalanine metabolism.
- Increased lactate and phenylalanine, decreased tyrosine, xanthine, and histidine levels were noted in sPC patients.
- Metabolic panels, especially urine-based tests, demonstrated superior predictive performance compared to PSA, particularly when combined with clinical factors.
Conclusions:
- Metabolomics-based liquid biopsies hold significant potential for improving sPC detection.
- Standardization of protocols, integration with MRI, and validation in large cohorts are crucial for clinical translation.
- Further research is needed to overcome methodological heterogeneity and enhance model credibility for widespread adoption.
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