Evidence map›Paper›PMID 41375016›Full record

ReviewCancers2025

Metabolomics-Based Liquid Biopsy for Predicting Clinically Significant Prostate Cancer.

Yuan-Chi Lin, Chung-Hsin Chen, Ming-Shyue Lee, Cheng-Fan Lee, Pei-Wen Hsiao, Hsiang-Po Huang, Yeong-Shiau Pu

Abstract readReview
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yuan-Chi LinDepartment of Internal Medicine, National Taiwan University Hospital and College of Medicine, Taipei 100225, Taiwan.ORCID 0009-0001-7049-1728
Chung-Hsin ChenDepartment of Urology and Institute of Clinical Medicine, National Taiwan University College of Medicine and Hospital, Taipei 100233, Taiwan.
Ming-Shyue LeeDepartment of Biochemistry and Molecular Biology, College of Medicine, National Taiwan University, Taipei 100233, Taiwan.
Cheng-Fan LeeDepartment of Biochemistry and Molecular Cell Biology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.ORCID 0000-0002-5043-2560
Pei-Wen HsiaoAgricultural Biotechnology Research Center, Academia Sinica, Nankang, Taipei 11529, Taiwan.
Hsiang-Po HuangGraduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei 100233, Taiwan.ORCID 0000-0002-3382-305X
Yeong-Shiau PuDepartment of Urology and Institute of Clinical Medicine, National Taiwan University College of Medicine and Hospital, Taipei 100233, Taiwan.ORCID 0000-0002-2859-3966

Funding

the Ministry of Science and Technology, Executive Yuan, Taiwan; the Ministry of Health and Welfare, Executive Yuan, Taiwan MOST 107-2314-B-002-032-MY3, MOST 107-2321-B-002-065, MOST 108-2321-B-002-029, and MOST 109-2327-B-002-001; MOHW111-TDUB-221-114002, MOHW112-TDU-B-222-124002, MOHW113-TDU-B-222-134002, and MOHW114-TDU-B-222-144002
6 · The paper itself

Abstract

Prostate cancer (PC) remains a major cause of cancer deaths in men. The serum biomarker prostate-specific antigen (PSA) lacks specificity in distinguishing clinically significant PC (sPC) from insignificant PC (isPC), leading to overdiagnosis and overtreatment. Although magnetic resonance imaging (MRI) improves detection, it is expensive, is time-consuming, and may involve inter-reader discrepancies. Recently, metabolomics, which has a high analytical sensitivity and broad molecular-feature coverage, has emerged as a promising tool to risk-stratify PC. This review examined studies of blood and urine metabolomics for sPC biomarker identification. Significant metabolite changes in sPC patients often involved fatty acid metabolism, sphingolipid metabolism, glycolysis, the citric acid cycle, purine/pyrimidine metabolism, and tyrosine/phenylalanine metabolism. Specifically, more than one study reported increased lactate and phenylalanine levels, along with decreased tyrosine, xanthine, and histidine levels, in sPC patients. Several metabolic panels outperformed serum PSA in predicting sPC, particularly when combined with clinical factors. Among these, two urine-based tests may have higher accuracy in predicting sPC than most current commercially available assays. However, direct comparison between studies may be inappropriate due to methodological heterogeneity, the variability in biospecimen types, inconsistent use of digital rectal examinations, and different sPC definitions and predictive endpoints. Most relevant studies were of small sample size or lacked external validation. Despite these challenges, metabolomics-based liquid biopsies show strong potential for improving sPC detection. Future research should focus on protocol standardization, MRI integration, absolute metabolite quantification, and validation in large and independent cohorts to enhance model credibility.

Indexed as

clinically significant prostate cancerGleason scoremass spectrometrymetabolomicsNational Comprehensive Cancer Network risk groupingnuclear magnetic resonance

Identifiers

PMID41375016
PMCPMC12691023

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.