ArticleScientific reports2017
Serum Metabolomic Profiles for Breast Cancer Diagnosis, Grading and Staging by Gas Chromatography-Mass Spectrometry.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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Who cites it
50 citing papers in PubMed, 85 citations in OpenAlex.
- Pathological response and metabolites' prognostic role in HER2-positive breast cancer treated with neoadjuvant pyrotinib, trastuzumab, nab-paclitaxel, and carboplatin: a single-arm phase II trial.Breast cancer research : BCR · 2025Trial
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- Serum 1H NMR-Based Untargeted Metabolomics for Noninvasive Early Detection of Breast Cancer.Journal of proteome research · 2026Article
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- Quality of Life and Metabolomics Analysis in Response to Meal Kit Intervention During Perioperative Chemotherapy in Patients with Early-Stage Breast Cancer: Protocol for a Single-Center Phase Ⅱ Randomized Crossover Trial.JMIR research protocols · 2025Article
- Resistance to neoadjuvant chemotherapy in breast cancers: a metabolic perspective.Journal of experimental & clinical cancer research : CR · 2025Review
- Metabolomic Analysis of Breast Cancer in Colombian Patients: Exploring Molecular Signatures in Different Subtypes and Stages.International journal of molecular sciences · 2025Article
- SCNN1A expression in triple-negative breast cancer: clinical implications for prognosis and neoadjuvant therapy response.World journal of surgical oncology · 2025Article
- Utility of Volatile Organic Compounds and Electronic Nose Technology for Breast Cancer Detection: A Systematic Review.Breast cancer (Dove Medical Press) · 2025Review
- Metabolomics-Based Machine Learning Models Accurately Predict Breast Cancer Estrogen Receptor Status.International journal of molecular sciences · 2024Article
- Metabolomic Analysis and Biochemical Profiling of Cadmium-Induced Metabolic Impairment and Its Amelioration by Resveratrol.Bioengineering (Basel, Switzerland) · 2024Article
- Active Molecular Network Discovery Links Lifestyle Variables to Breast Cancer in the Long Island Breast Cancer Study Project.Environment & health (Washington, D.C.) · 2024Article
- Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer.Breast cancer research : BCR · 2024Article
- Machine learning of cellular metabolic rewiring.Biology methods & protocols · 2024Article
- Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Peripheral Blood Serum NMR Metabolomics Is a Powerful Tool to Discriminate Benign and Malignant Ovarian Tumors.Metabolites · 2023Article
- Identification of metabolic pathways contributing to ERScientific reports · 2023Article
- Review
- Metabolomic Signatures of Scarff-Bloom-Richardson (SBR) Grade in Non-Metastatic Breast Cancer.Cancers · 2023Article
- Circulating tumor biomarkers in early-stage breast cancer: characteristics, detection, and clinical developments.Frontiers in oncology · 2023Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Detection of metabolic signature for breast cancer (BC) has the potential to improve patient prognosis. This study identified potentially significant metabolites differentiating between breast cancer patients and healthy controls to help in diagnosis, grading, staging and determination of neoadjuvant status. Serum was collected from 152 pre-operative breast cancer (BC) patients and 155 healthy controls in this case-controlled study. Gas chromatography-mass spectrometry (GC-MS) was used to obtain metabolic profiles followed by chemometric analysis with the identification of significantly differentiated metabolites including 7 for diagnosis, 18 for grading, 23 for staging, 15 for stage III subcategory and 10 for neoadjuvant status (p-value < 0.05). Partial Least Square Discriminant Analysis (PLS-DA) model revealed a distinct separation between healthy controls and BC patients with a sensitivity of 96% and specificity of 100% on external validation. Models for grading, staging and neoadjuvant status were built with Decision Tree Algorithm with predictive accuracy of 71.5%, 71.3% and 79.8% respectively. Pathway analysis revealed increased glycolysis, lipogenesis, and production of volatile organic metabolites indicating the metabolic alterations in breast cancer.
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