Evidence mapPaperPMID 42397597Full record

ReviewMetabolomics : Official journal of the Metabolomic Society2026

Metabolomics in breast cancer: insights into treatment responses, disease progression, and prognostic assessment.

Dyah L Dewi, Elya Manik, Ema Damayanti, Muslih Anwar, Suratno, Syam Budi Iryanto

Abstract readReview
In one paragraph

Review in Metabolomics : Official journal of the Metabolomic Society, 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

6 authors.

Dyah L DewiDivision of Surgical Oncology, Department of Surgery, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia. dyah.laksmi.d@ugm.ac.id.
Elya ManikMaster's Program in Biomedical Sciences, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Ema DamayantiResearch Center for Food Technology and Processing, National Research and Innovation Agency, Gunungkidul, Yogyakarta, Indonesia.
Muslih AnwarResearch Center for Food Technology and Processing, National Research and Innovation Agency, Gunungkidul, Yogyakarta, Indonesia.
SuratnoResearch Center for Food Technology and Processing, National Research and Innovation Agency, Gunungkidul, Yogyakarta, Indonesia.
Syam Budi IryantoResearch Center for Computing, Research Organization for Life Sciences and Environment, National Research and Innovation Agency Republic of Indonesia, Bogor, Indonesia.

Funding

RIIM LPDP Grant and BRIN 172/IV/KS/11/2023 and 6815/UN1/DITLIT/Dit-Lit/KP.01.03/2023.
6 · The paper itself

Abstract

backgroundAlterations in metabolic pathways are a hallmark of cancer and play a pivotal role in breast cancer development and progression. The inherent metabolic heterogeneity of breast cancer contributes to differences in therapeutic response and patients' prognosis. Clinical metabolomics has emerged as a promising approach for identifying metabolic biomarkers that reflect tumor biology, treatment-related changes after diagnosis, and patients' outcomes. AIMS OF REVIEW: This review summarizes the metabolomic profiles of breast cancer patients, using various biological materials and analytical methods, to assess their potential role as biomarkers for monitoring therapeutic response, adverse treatment effects, tracking disease progression, and predicting prognosis. KEY SCIENTIFIC CONCEPT OF REVIEW: Metabolomic shifts generate unique signatures with promising potential as biomarkers for evaluating treatment response, monitoring therapeutic adverse effects, disease progression, and predicting clinical outcomes in breast cancer patients. Biological matrices, such as serum, plasma, and tumor tissue, were commonly used in both untargeted and targeted metabolomics approaches. Liquid chromatography-mass spectrometry is the most commonly used analytical method in clinical metabolomics studies. Altered metabolites were identified and linked to metabolic pathways, particularly amino acids, glucose, and fatty acids metabolism. When integrated with genomic and transcriptomic data, these metabolic fingerprints offer a multidimensional perspective on disease trajectory, thereby enhancing patient stratification and informing personalized therapeutic strategies.

Indexed as

Breast NeoplasmsMetabolomicsBiomarkers, TumorDisease ProgressionFemaleHumansMetabolomePrognosisBiomarkers, TumorBreast cancerDisease progressionMetabolomicsPrognosisTherapy responses

Identifiers

PMID42397597
PMCPMC13331929

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.