Evidence map›Paper›PMID 42029478›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2026

A Urinary Three-Metabolite Signature Enables Noninvasive Identification of Patients with High-Risk Ovarian Cancer.

Alexander Max Funk, Mareike Brieske, Franziska Maria Schwarz, Theresa Link, Sophie Jonas, Pauline Wimberger, Lisa Freitag, Anna Klimova, Triantafyllos Chavakis, Peter Mirtschink and 1 more

Abstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Alexander Max FunkInstitute for Clinical Chemistry and Laboratory Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0002-7248-4599
Mareike BrieskeNational Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between DKFZ, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.ORCID 0009-0005-6733-1669
Franziska Maria SchwarzNational Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between DKFZ, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.ORCID 0009-0001-9741-5784
Theresa LinkNational Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between DKFZ, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.ORCID 0000-0002-2229-7867
Sophie JonasInstitute for Clinical Chemistry and Laboratory Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0009-0001-2615-8637
Pauline WimbergerNational Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between DKFZ, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.ORCID 0000-0002-7380-577X
Lisa FreitagNational Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between DKFZ, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.ORCID 0009-0003-0741-6746
Anna KlimovaNational Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between DKFZ, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.ORCID 0000-0002-8745-8617
Triantafyllos ChavakisInstitute for Clinical Chemistry and Laboratory Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0002-1869-5141
Peter MirtschinkInstitute for Clinical Chemistry and Laboratory Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0009-0008-9815-1750
Jan Dominik KuhlmannNational Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between DKFZ, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.ORCID 0000-0003-3820-3017

Funding

intramural funding
6 · The paper itself

Abstract

purposeReliable prognostic tools in ovarian cancer are urgently needed to guide risk-adapted treatment decisions, yet the clinical utility of urinary metabolites for noninvasive risk stratification remains largely undefined. Here, we define a clinically relevant urinary metabolite signature that enables noninvasive prognostic risk stratification in ovarian cancer. EXPERIMENTAL

designWe used targeted 1H nuclear magnetic resonance spectroscopy to profile 149 metabolites related to energy metabolism, oxidative stress, mitochondrial function, nitrogen metabolism, amino acid degradation, gut microbiome activity, and inflammation. Metabolites were measured in preoperative urine samples from 199 consecutive patients with newly diagnosed ovarian cancer treated in routine clinical practice between 2013 and 2022.

resultsUnsupervised clustering revealed biologically heterogeneous subgroups but lacked prognostic resolution and alignment with overt clinical phenotypes. However, single-metabolite analysis identified a condensed three-metabolite prognostic signature comprising glycine, alanine, and citrate. A final parsimonious model integrating this metabolite signature with clinical covariates outperformed established risk factors alone (Fédération Internationale de Gynécologie et d'Obstétrique stage and surgical outcome), accurately predicted 60-month overall survival (AUC = 0.839), and stratified risk. Patients in the highest-risk quartile (Q4) had markedly shorter progression-free survival [Δmedian ≈ 56 months; HR, 2.63; 95% confidence interval (CI), 1.54-4.52; P < 0.001] and overall survival (Δmedian ≈ 86 months; HR, 2.49; 95% CI, 1.39-4.46; P = 0.009) compared with the lowest-risk group (Q1).

conclusionsWe define a urinary three-metabolite signature that enables noninvasive identification of patients with high-risk ovarian cancer beyond established clinical factors. This signature may support molecular stratification and risk-adapted clinical decisions, thereby underscoring the clinical scalability of urine as a matrix for metabolic risk profiling in ovarian cancer.

Indexed as

Biomarkers, TumorMetabolomeOvarian NeoplasmsAdultAgedAlanineFemaleGlycineHumansMetabolomicsMiddle AgedPrognosisRisk AssessmentRisk FactorsAlanineBiomarkers, TumorGlycine

Identifiers

PMID42029478
PMCPMC13376881

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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.