ArticleCell research2022
Comprehensive metabolomics expands precision medicine for triple-negative breast cancer.
Article in Cell research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 205 papers, 5 of them syntheses that pooled it.
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Who cites it
205 citing papers in PubMed, 5 syntheses or guidelines pooled it, 304 citations in OpenAlex.
- Pooled it
- The translational chasm in machine learning for triple-negative breast cancer: a quantitative landscape assessment.Frontiers in oncology · 2026Pooled it
- A bibliometric and text-mining analysis of lipidomics and metabolomics in human disease.Frontiers in physiology · 2026Pooled it
- Metabolomics and metabolites in cancer diagnosis and treatment.Molecular biomedicine · 2025Pooled it
- Application and prospect of organoid technology in breast cancer.Frontiers in immunology · 2024Pooled it
- Effect ofCancer science · 2023Trial
- Subtyping-based platform guides precision medicine for heavily pretreated metastatic triple-negative breast cancer: The FUTURE phase II umbrella clinical trial.Cell research · 2023Trial
- Modulation of the response to immunotherapy in triple-negative breast cancer: the role of the microbiota and microbial metabolites in the tumor microenvironment.Gut microbes · 2026Review
- Metabolic immune checkpoints (MICs) in cancer: from molecular mechanisms to challenges and opportunities in clinical translation.Signal transduction and targeted therapy · 2026Review
- Article
- Protein-protein interactions as therapeutic targets in breast cancer: integrated computational and experimental advances, mechanisms and clinical translation.Molecular biology reports · 2026Review
- Current and future therapies for triple-negative breast cancer.Journal of hematology & oncology · 2026Review
- Machine Learning-Integrated Metabolomics for Precision Pharmacotherapy: Advances, Challenges, and Clinical Translation.Metabolites · 2026Review
- Enzymatic activity-independent NANS stabilizes LATS2 to drive growth and therapeutic resistance in HR+/HER2- breast cancer.Nature communications · 2026Article
- ADSL drives fumarate mediated scrib-rictor complex formation to promote metastasis dissemination in triple-negative breast cancer.Molecular cancer · 2026Article
- BET inhibition unmasks a targetable glycolytic dependency through a HIF1α stabilization and driven transcriptional program in a defined subset of triple-negative breast Cancer.Cell death discovery · 2026Article
- Lipid Metabolism, Lipogenesis, and Resistance to Third Generation EGFR-TKIs.Journal of clinical laboratory analysis · 2026Review
- B.R.E.A.S.T. Breast canceR Enhanced AI-Supported Therapy: A New Interpretable Proteomics-Driven Machine Learning Framework for Therapy Response Prediction in Breast Cancer.International journal of molecular sciences · 2026Article
- Fingernail-based metabolomics reveals a stepwise decline in dodecanoic acid associated with Alzheimer's disease progression.Journal of advanced research · 2026Article
- Translating Pharmacology from Animal Models to Organoids: Advancing Predictive Human Biology in Drug Discovery.Stem cell reviews and reports · 2026Review
145 more citing papers are in PubMed but not listed here.
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Authors and funding
17 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolic reprogramming is a hallmark of cancer. However, systematic characterizations of metabolites in triple-negative breast cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal androgen receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.
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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.