ArticleAngewandte Chemie (International ed. in English)2020
Untargeted Tumor Metabolomics with Liquid Chromatography-Surface-Enhanced Raman Spectroscopy.
Article in Angewandte Chemie (International ed. in English), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- Sugar Analysis Using Hydrophilic Liquid Chromatography Combined with Raman Spectroscopy.Analytical chemistry · 2025Article
- A surface chemistry perspective on SERS: revisiting the basics to push the field forward.Chemical Society reviews · 2025Review
- Coupling of chromatography with surface-enhanced Raman spectroscopy: trends and prospects.Frontiers in chemistry · 2025Review
- Longitudinal non-targeted metabolomic profiling of urine samples for monitoring of kidney transplantation patients.Renal failure · 2024Article
- Metabolomics reveals the implication of acetoacetate and ketogenic diet therapy in radioiodine-refractory differentiated thyroid carcinoma.The oncologist · 2024Article
- Digital surface enhanced Raman spectroscopy for quantifiable single molecule detection in flow.The Analyst · 2024Article
- Raman and Surface-Enhanced Raman Scattering Detection in Flowing Solutions for Complex Mixture Analysis.Annual review of analytical chemistry (Palo Alto, Calif.) · 2024Review
- Article
- Chemical conjugation to differentiate monosaccharides by Raman and surface enhanced Raman spectroscopy.The Analyst · 2023Article
- Deposition of hydrophilic TiJournal of nanobiotechnology · 2023Article
- Emerging nanosensor platforms and machine learning strategies toward rapid, point-of-need small-molecule metabolite detection and monitoring.Chemical science · 2022Review
- Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine.ACS photonics · 2022Review
- Human metabolite detection by surface-enhanced Raman spectroscopy.Materials today. Bio · 2022Article
- Probing metabolic alterations in breast cancer in response to molecular inhibitors with Raman spectroscopy and validated with mass spectrometry.Chemical science · 2020Article
- Cancer Diagnosis through SERS and Other Related Techniques.International journal of molecular sciences · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Metabolomics is a powerful systems biology approach that monitors changes in biomolecule concentrations to diagnose and monitor health and disease. However, leading metabolomics technologies, such as NMR and mass spectrometry (MS), access only a small portion of the metabolome. Now an approach is presented that uses the high sensitivity and chemical specificity of surface-enhanced Raman scattering (SERS) for online detection of metabolites from tumor lysates following liquid chromatography (LC). The results demonstrate that this LC-SERS approach has metabolite detection capabilities comparable to the state-of-art LC-MS but suggest a selectivity for the detection of a different subset of metabolites. Analysis of replicate LC-SERS experiments exhibit reproducible metabolite patterns that can be converted into barcodes, which can differentiate different tumor models. Our work demonstrates the potential of LC-SERS technology for metabolomics-based diagnosis and treatment of cancer.
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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.