Evidence mapPaperPMID 42449765Full record

ReviewDiagnostics (Basel, Switzerland)2026

Liquid Biopsy-Based Metabolomics in Epithelial Ovarian Cancer: Challenges, Methodological Advances and Translational Considerations.

Mariagrazia D'Agostino, Luna Laera, Martina Lanza, Doron Tolomeo, Monica Montopoli, Clelia Tiziana Storlazzi, Gennaro Cormio, Alessandra Castegna, Stefano Miglietta

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

9 authors.

Mariagrazia D'AgostinoDepartment of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Via Orabona 4, 70125 Bari, Italy.ORCID 0000-0001-6127-9656
Luna LaeraDepartment of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Via Orabona 4, 70125 Bari, Italy.ORCID 0000-0002-5266-1156
Martina LanzaDepartment of Experimental Medicine, University of Salento, Via per Monteroni, 73100 Lecce, Italy.ORCID 0000-0001-7608-4026
Doron TolomeoDepartment of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Via Orabona 4, 70125 Bari, Italy.
Monica MontopoliDepartment of Pharmaceutical and Pharmacological Sciences, University of Padova, 35131 Padova, Italy.ORCID 0000-0001-6182-4132
Clelia Tiziana StorlazziDepartment of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Via Orabona 4, 70125 Bari, Italy.ORCID 0000-0002-1696-0028
Gennaro CormioGynecologic Oncology Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Tumori "Giovanni Paolo II", Viale Orazio Flacco 65, 70124 Bari, Italy.ORCID 0000-0001-5745-372X
Alessandra CastegnaDepartment of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Via Orabona 4, 70125 Bari, Italy.
Stefano MigliettaDepartment of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Via Orabona 4, 70125 Bari, Italy.ORCID 0000-0002-7755-2028

Funding

Italian Association for Cancer Research IG-26340
6 · The paper itself

Abstract

Epithelial ovarian cancers (EOCs) histotypes are characterized by marked molecular heterogeneity and limited effectiveness of current screening and monitoring strategies. Earlier identification of tumor-associated alterations may support timely intervention, especially in genetically predisposed or early-onset patient populations. While liquid biopsy approaches have primarily focused on circulating DNA, RNA, and proteins, increasing evidence indicates that cancer-associated metabolic reprogramming generates measurable informative signals in peripheral biofluids. This review summarizes recent progress in liquid biopsy-derived metabolomics in EOCs, covering analytical platforms applied to serum, plasma, urine, and ascites. Recurrent metabolic signatures linked to tumor burden, disease stage, treatment response, and clinical outcome are described, and their significance in discriminating malignant and non-malignant conditions is critically discussed. Collectively, these findings suggest that metabolomics may provide complementary functional information alongside genomic and histopathological profiling. Although its clinical implementation still requires further validation and methodological standardization, ongoing advances in analytical technologies and the integration of high-dimensional metabolic data into machine learning-based frameworks may progressively support the identification of early tumor-associated alterations and contribute to more accurate disease stratification and biologically informed clinical management.

Indexed as

biomarkerscancer reprogrammingliquid biopsymetabolomicsovarian cancerprecision medicine

Identifiers

PMID42449765
PMCPMC13360296

What Socratic holds

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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 Socratic graph.