ArticleInternational journal of molecular sciences2013
Mass spectrometry-based quantitative metabolomics revealed a distinct lipid profile in breast cancer patients.
Article in International journal of molecular sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed, 111 citations in OpenAlex.
- Smoking-Stratified Signal Decomposition and Feature Selection for Never-Smoker Cancer Classification in a Combined Lung-Breast Metabolomics Cohort.International journal of molecular sciences · 2026Article
- Fructose metabolism as an adaptive survival axis in pancreatic cancer: mechanistic insights and therapeutic implications.Frontiers in medicine · 2026Review
- Machine learning-assisted quantitative metabolomics of West African patients with advanced breast cancer.Scientific reports · 2025Article
- Lipids: Driving Forces in the Underlying Biology of Carcinogenesis.ACS pharmacology & translational science · 2025Review
- Infrared spectral analysis of gastrointestinal neuroendocrine tumors reveals diagnostic biomarkers.Scientific reports · 2025Article
- Proteomic and lipidomic analysis of low-density lipoprotein identifies potential biomarkers of early estrogen receptor-positive breast cancer.Cancer & metabolism · 2025Article
- Article
- Proteomic and metabolomic profiles of plasma-derived Extracellular Vesicles differentiate melanoma patients from healthy controls.Translational oncology · 2024Article
- Tumor Lipid Signatures Are Descriptive of Acquisition of Therapy Resistance in an Endocrine-Related Breast Cancer Mouse Model.Journal of proteome research · 2024Article
- Microbiota and metabolite alterations in pancreatic head and body/tail cancer patients.Cancer science · 2024Article
- Plasma Metabolome Signatures to Predict Responsiveness to Neoadjuvant Chemotherapy in Breast Cancer.Cancers · 2024Article
- Assessment of the potential risks in SD rats gavaged with genetically modified yeast containing theFrontiers in veterinary science · 2024Article
- Profiling of serum metabolome of breast cancer: multi-cancer features discriminate between healthy women and patients with breast cancer.Frontiers in oncology · 2024Article
- Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients.Metabolomics : Official journal of the Metabolomic Society · 2023Article
- Lipid Biomarkers in Liquid Biopsies: Novel Opportunities for Cancer Diagnosis.Pharmaceutics · 2023Review
- Multiomics insights on the onset, progression, and metastatic evolution of breast cancer.Frontiers in oncology · 2023Review
- Metabolomic profiles in night shift workers: A cross-sectional study on hospital female nurses.Frontiers in public health · 2023Article
- Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers.Biomolecules · 2022Article
- Metabolic differences among newborns born to mothers with a history of leukemia or lymphoma.The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians · 2022Article
- Non-Targeted Serum Lipidomics Analysis and Potential Biomarkers of Laryngeal Cancer Based on UHPLC-QTOF-MS.Metabolites · 2022Article
12 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 2 countries.
Funding
Abstract
Breast cancer accounts for the largest number of newly diagnosed cases in female cancer patients. Although mammography is a powerful screening tool, about 20% of breast cancer cases cannot be detected by this method. New diagnostic biomarkers for breast cancer are necessary. Here, we used a mass spectrometry-based quantitative metabolomics method to analyze plasma samples from 55 breast cancer patients and 25 healthy controls. A number of 30 patients and 20 age-matched healthy controls were used as a training dataset to establish a diagnostic model and to identify potential biomarkers. The remaining samples were used as a validation dataset to evaluate the predictive accuracy for the established model. Distinct separation was obtained from an orthogonal partial least squares-discriminant analysis (OPLS-DA) model with good prediction accuracy. Based on this analysis, 39 differentiating metabolites were identified, including significantly lower levels of lysophosphatidylcholines and higher levels of sphingomyelins in the plasma samples obtained from breast cancer patients compared with healthy controls. Using logical regression, a diagnostic equation based on three metabolites (lysoPC a C16:0, PC ae C42:5 and PC aa C34:2) successfully differentiated breast cancer patients from healthy controls, with a sensitivity of 98.1% and a specificity of 96.0%.
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Registered trials
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.