ArticleProceedings of the National Academy of Sciences of the United States of America2016
Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.
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Who cites it
97 citing papers in PubMed, 207 citations in OpenAlex.
- Intraoperative assessment of tumor margins during glioma resection by desorption electrospray ionization-mass spectrometry.Proceedings of the National Academy of Sciences of the United States of America · 2017Trial
- Shining a light on brain tumors: a review of Raman spectroscopy in the operating room.Journal of biomedical optics · 2026Review
- Lipidomic profile of meningiomas harboring different NF2 mutation status.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Intraoperative Mass Spectrometry in Oncology: Technologies, Clinical Applications, and Challenges.Molecules (Basel, Switzerland) · 2026Review
- Metabolic Landscape and Emerging Therapeutic Potential in Pediatric and Adult Gliomas.International journal of molecular sciences · 2026Review
- Plasma lipidomics profiling to identify signatures of pediatric medulloblastoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Ambient ionization mass spectrometry in brain cancer diagnosis.Journal of mass spectrometry and advances in the clinical lab · 2025Review
- Spatial metabolomics atlas in the progression of oral squamous cell carcinoma.Journal of translational medicine · 2025Article
- [Plasma lipidomics-based exploration of potential biomarkers of metastasis in pediatric medulloblastoma].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025Article
- Nanoneedles enable spatiotemporal lipidomics of living tissues.Nature nanotechnology · 2025Article
- A Fast-Pass, Desorption Electrospray Ionization Mass Spectrometry Strategy for Untargeted Metabolic Phenotyping.Journal of the American Society for Mass Spectrometry · 2025Article
- The evolution and application of multi-omic analysis for pituitary neuroendocrine tumors.Frontiers in medicine · 2025Review
- Point-of-care mass spectrometry metabolomic analysis enabling intraoperative brain tumor diagnosis.Theranostics · 2025Article
- Tumor-Promoted Changes in Pediatric Brain Histology Can Be Distinguished from Normal Parenchyma by Desorption Electrospray Ionization Mass Spectrometry Imaging.Biomedicines · 2024Article
- PiDeeL: metabolic pathway-informed deep learning model for survival analysis and pathological classification of gliomas.Bioinformatics (Oxford, England) · 2023Article
- Desorption Electrospray Ionization Mass Spectrometry: 20 Years.Accounts of chemical research · 2023Review
- Mass spectrometry-based proteomics as an emerging tool in clinical laboratories.Clinical proteomics · 2023Review
- Characterisation of hepatic lipid signature distributed across the liver zonation using mass spectrometry imaging.JHEP reports : innovation in hepatology · 2023Article
- Article
- Advances in the intraoperative delineation of malignant glioma margin.Frontiers in oncology · 2023Review
37 more citing papers are in PubMed but not listed here.
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6 authors at 3 institutions in 1 country.
Funding
Abstract
Examination of tissue sections using desorption electrospray ionization (DESI)-MS revealed phospholipid-derived signals that differ between gray matter, white matter, gliomas, meningiomas, and pituitary tumors, allowing their ready discrimination by multivariate statistics. A set of lower mass signals, some corresponding to oncometabolites, including 2-hydroxyglutaric acid and N-acetyl-aspartic acid, was also observed in the DESI mass spectra, and these data further assisted in discrimination between brain parenchyma and gliomas. The combined information from the lipid and metabolite MS profiles recorded by DESI-MS and explored using multivariate statistics allowed successful differentiation of gray matter (n = 223), white matter (n = 66), gliomas (n = 158), meningiomas (n = 111), and pituitary tumors (n = 154) from 58 patients. A linear discriminant model used to distinguish brain parenchyma and gliomas yielded an overall sensitivity of 97.4% and a specificity of 98.5%. Furthermore, a discriminant model was created for tumor types (i.e., glioma, meningioma, and pituitary), which were discriminated with an overall sensitivity of 99.4% and a specificity of 99.7%. Unsupervised multivariate statistics were used to explore the chemical differences between anatomical regions of brain parenchyma and secondary infiltration. Infiltration of gliomas into normal tissue can be detected by DESI-MS. One hurdle to implementation of DESI-MS intraoperatively is the need for tissue freezing and sectioning, which we address by analyzing smeared biopsy tissue. Tissue smears are shown to give the same chemical information as tissue sections, eliminating the need for sectioning before MS analysis. These results lay the foundation for implementation of intraoperative DESI-MS evaluation of tissue smears for rapid diagnosis.
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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.