ArticleProceedings of the National Academy of Sciences of the United States of America2022
Diagnosis and prognosis of breast cancer by high-performance serum metabolic fingerprints.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- A nomogram based on metabolic profiling to discriminate lung cancer among patients with lung nodules.The Journal of international medical research · 2023Trial
- Machine learning-driven cancer diagnostics with improved robustness and interpretability.Chemical science · 2026Review
- Engineering smart polymeric lipid nanoparticles for breast cancer: AI-guided formulation design, biological barriers, and translational constraints.Journal of nanobiotechnology · 2026Review
- The tryptophan-kynurenine pathway in cardiovascular diseases: mechanistic insights and therapeutic opportunities.Frontiers in cardiovascular medicine · 2026Review
- Serum and urine metabolic fingerprints enable diagnosis and prognosis for IgA nephropathy.Materials today. Bio · 2025Article
- A mass spectrometry-based strategy allows signature metabolite identification in tear fluid from people with diabetic cataracts.Nature communications · 2025Article
- Multi-modal single-cell platform for nanoparticle-enhanced time-series metabolic profiles of CD8Journal of nanobiotechnology · 2025Article
- Plasma Metabolic Profile with Machine Learning Reveals Distinct Diagnostic and Biological Signatures for Pathologic Myopia.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Serum metabolic patterns reveal the diagnostic and prognostic role of alanine abnormality in ocular adnexal lymphoma.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Metabolic fingerprinting enables rapid, label-free histopathology in gastric cancer diagnosis and prognostic prediction.Cell reports. Medicine · 2025Article
- Serum metabolic profiling enables diagnosis, prognosis, and monitoring for brainstem gliomas.Nature communications · 2025Article
- Molecular biomarkers for the prognosis of breast cancer: role of amino acid metabolism genes.Journal of physiology and biochemistry · 2025Article
- Application of Metabolic Biomarkers in Breast Cancer: A Literature Review.Annals of laboratory medicine · 2025Review
- Single Test-Based Diagnosis and Subtyping of Pulmonary Hypertension Caused by Fibrosing Mediastinitis Using Plasma Metabolic Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Abnormal changes in metabolites caused by mJournal of advanced research · 2025Review
- Metabolomic insights into pathogenesis and therapeutic potential in adult acute lymphoblastic leukemia.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Non-Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints and Machine Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Diagnosis and prognosis prediction of gastric cancer by high-performance serum lipidome fingerprints.EMBO molecular medicine · 2024Article
- Identification of a Novel Biomarker Panel for Breast Cancer Screening.International journal of molecular sciences · 2024Article
- Cervical mucus can be used for metabolite screening in cervical cancer.Cancer science · 2024Article
Corrections and comments
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Authors and funding
23 authors.
Funding
Abstract
High-performance metabolic analysis is emerging in the diagnosis and prognosis of breast cancer (BrCa). Still, advanced tools are in demand to deliver the application potentials of metabolic analysis. Here, we used fast nanoparticle-enhanced laser desorption/ionization mass spectrometry (NPELDI-MS) to record serum metabolic fingerprints (SMFs) of BrCa in seconds, achieving high reproducibility and low consumption of direct serum detection without treatment. Subsequently, machine learning of SMFs generated by NPELDI-MS functioned as an efficient readout to distinguish BrCa from non-BrCa with an area under the curve of 0.948. Furthermore, a metabolic prognosis scoring system was constructed using SMFs with effective prediction performance toward BrCa (P < 0.005). Finally, we identified a biomarker panel of seven metabolites that were differentially enriched in BrCa serum and their related pathways. Together, our findings provide an efficient serum metabolic tool to characterize BrCa and highlight certain metabolic signatures as potential diagnostic and prognostic factors of diseases including but not limited to BrCa.
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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.