ArticleBreast cancer research : BCR2024
Plasma metabolomics profiles and breast cancer risk.
Article in Breast cancer research : BCR, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Plasma metabolites, dietary intakes, and breast cancer incidence: a prospective case-cohort study in NutriNet-Santé.The American journal of clinical nutrition · 2026Article
- Untargeted metabolomics reveals organism specific biomarkers of carbapenem resistance in Klebsiella pneumoniae and Escherichia coli.NPJ systems biology and applications · 2026Article
- Applications of Metabolomics to the Clinical Management of Breast Cancer: New Perspectives for Diagnosis, Treatment and Prognosis.International journal of molecular sciences · 2026Review
- Metabolomic-driven prediction of the mutational status of healthy individuals with a family history of hereditary breast and ovarian cancer syndrome: the HRRmet study.Scientific reports · 2026Article
- Integrative Multi-Omics Analysis Reveals the Characteristic Metabolic Signature of Glioma and Enables Plasma-Based Liquid Biopsy.Research (Washington, D.C.) · 2026Article
- Review
- The plasma proteome and breast cancer risk.Breast cancer research : BCR · 2025Article
- Pre-diagnostic serum metabolome and breast cancer risk: a nested case-control study.Breast cancer research : BCR · 2025Article
- The treatment of breast cancer in the era of precision medicine.Cancer biology & medicine · 2025Review
- Gut microbial and functional signatures in breast cancer: an integrated metagenomic and machine learning approach to non-invasive detection.Frontiers in microbiology · 2025Article
- Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis.Computational and structural biotechnology journal · 2025Review
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Authors and funding
7 authors.
Funding
Abstract
backgroundBreast cancer (BC) is the most common cancer in women and incidence rates are increasing; metabolomics may be a promising approach for identifying the drivers of the increasing trends that cannot be explained by changes in known BC risk factors.
methodsWe conducted a nested case-control study (median followup 6.3 years) within the New York site of the Breast Cancer Family Registry (BCFR) (n = 40 cases and 70 age-matched controls). We conducted a metabolome-wide association study using untargeted metabolomics coupling hydrophilic interaction liquid chromatography (HILIC) and C
resultsWe found eight metabolic features associated with BC risk. For the four metabolites negatively associated with risk, the adjusted odds ratios (ORs) ranged from 0.31 (95% confidence interval (CI): 0.14, 0.66) (L-Histidine) to 0.65 (95% CI: 0.43, 0.98) (N-Acetylgalactosamine), and for the four metabolites positively associated with risk, ORs ranged from 1.61 (95% CI: 1.04, 2.51, (m/z: 101.5813, RT: 90.4, 1,3-dibutyl-1-nitrosourea, a potential carcinogen)) to 2.20 (95% CI: 1.15, 4.23) (11-cis-Eicosenic acid). These results were no longer statistically significant after adjusting for multiple comparisons. Adding the BC-related metabolic features to a model, including age, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk score improved the accuracy of BC prediction from an area under the curve (AUC) of 66% to 83%.
conclusionsIf replicated in larger prospective cohorts, these findings offer promising new ways to identify exposures related to BC and improve BC risk prediction.
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