ArticleFrontiers in oncology2024
Profiling of serum metabolome of breast cancer: multi-cancer features discriminate between healthy women and patients with breast cancer.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 8 citations in OpenAlex.
- NMR-based metabolomics analysis in breast cancer patients from Saudi Arabia: a pilot study.Scientific reports · 2026Article
- Leveraging untargeted metabolomics in combination with machine learning to uncover novel insights into bladder cancer.Cancer & metabolism · 2026Article
- Metabolomics-based exploration of the pathogenesis of breast cancer-related fatigue and progress of traditional Chinese medicine intervention.Frontiers in oncology · 2026Review
- Serum metabolomic profiles associated with psychoneurological symptoms in women with early-stage breast cancer over one year.Frontiers in oncology · 2026Article
- Machine learning-assisted quantitative metabolomics of West African patients with advanced breast cancer.Scientific reports · 2025Article
- Application of Metabolic Biomarkers in Breast Cancer: A Literature Review.Annals of laboratory medicine · 2025Review
- Review
- Identification of a Novel Biomarker Panel for Breast Cancer Screening.International journal of molecular sciences · 2024Article
- Challenges and recent advances in quantitative mass spectrometry-based metabolomics.Analytical science advances · 2024Review
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Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers. Methods: We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions. Results: Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95). Discussion: In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.
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