Evidence map›Paper›PMID 40091629›Full record

ReviewAnnals of laboratory medicine2025

Application of Metabolic Biomarkers in Breast Cancer: A Literature Review.

Anbok Lee, Ching-Wan Lam

Abstract readReview
In one paragraph

Review in Annals of laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Resistance to neoadjuvant chemotherapy in breast cancers: a metabolic perspective.Journal of experimental & clinical cancer research : CR · 2025
    Review
  4. Article
  5. Article
  6. 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

2 authors.

Anbok LeeDepartment of Surgery, Chung-Ang University Gwangmyeong Hospital, Chung-Ang University College of Medicine, Gyeonggi-do, Korea.ORCID https://orcid.org/0000-0003-0860-3239
Ching-Wan LamDepartment of Pathology, Queen Mary Hospital, The University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0002-9600-4262

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the most common cancer and the second leading cause of cancer death in women worldwide. Novel biomarkers for early diagnosis, treatment, and prognosis in breast cancer are needed and extensively studied. Metabolites, which are small molecules produced during metabolic processes, provide links between genetics, environment, and phenotype, making them useful biomarkers for diagnosis, prognosis, and disease classification. With recent advancements in metabolomics techniques, metabolomics research has expanded, which has led to significant progress in biomarker research. In breast cancer, alterations in metabolic pathways result in distinct metabolomic profiles that can be harnessed for biomarker discovery. Studies using mass spectrometry and nuclear magnetic resonance spectroscopy have helped identify significant changes in metabolites, such as amino acids, lipids, and organic acids, in the tissues, blood, and urine of patients with breast cancer, highlighting their potential as biomarkers. Integrative analysis of these metabolite biomarkers with existing clinical parameters is expected to improve the accuracy of breast cancer diagnosis and to be helpful in predicting prognosis and treatment responses. However, to apply these findings in clinical practice, larger cohorts for validation and standardized analytical methods for QC are necessary. In this review, we provide information on the current state of metabolite biomarker research in breast cancer, highlighting key findings and their clinical implications.

Indexed as

Biomarkers, TumorBreast NeoplasmsFemaleHumansMass SpectrometryMetabolomeMetabolomicsPrognosisBiomarkers, TumorBiomarkerBreast cancerMetabolite

Identifiers

PMID40091629
PMCPMC11996688

What OpenQuestion 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 OpenQuestion graph.