ArticleLaboratory investigation; a journal of technical methods and pathology2021
Real-time lipid patterns to classify viable and necrotic liver tumors.
Article in Laboratory investigation; a journal of technical methods and pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 17 citations in OpenAlex.
- Integrating Rapid Evaporative Ionization Mass Spectrometry Classification with Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging and Liquid Chromatography-Tandem Mass Spectrometry to Unveil Glioblastoma Overall Survival Prediction.ACS chemical neuroscience · 2025Article
- Application of rapid evaporative ionization mass spectrometry in preclinical and clinical analyses of steatotic liver tissues and cells.Scientific reports · 2025Article
- Rapid evaporative ionization mass spectrometry: A survey through 15 years of applications.Journal of separation science · 2024Review
- Fast detection, a precise and sensitive diagnostic agent for breast cancer.Journal of experimental & clinical cancer research : CR · 2022Article
- Evaluation of the Sensitivity of Metabolic Profiling by Rapid Evaporative Ionization Mass Spectrometry: Toward More Radical Oral Cavity Cancer Resections.Analytical chemistry · 2022Article
- Towards real-time intraoperative tissue interrogation for REIMS-guided glioma surgery.Journal of mass spectrometry and advances in the clinical lab · 2022Article
- Identification and Comprehensive Co-Detection of Necrotic and Viable Aneuploid Cancer Cells in Peripheral Blood.Cancers · 2021Article
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Authors and funding
7 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real-time tissue classifiers based on molecular patterns are emerging tools for fast tumor diagnosis. Here, we used rapid evaporative ionization mass spectrometry (REIMS) and multivariate statistical analysis (principal component analysis-linear discriminant analysis) to classify tissues with subsequent comparison to gold standard histopathology. We explored whether REIMS lipid patterns can identify human liver tumors and improve the rapid characterization of their underlying metabolic features. REIMS-based classification of liver parenchyma (LP), hepatocellular carcinoma (HCC), and metastatic adenocarcinoma (MAC) reached an accuracy of 98.3%. Lipid patterns of LP were more similar to those of HCC than to those of MAC and allowed clear distinction between primary and metastatic liver tumors. HCC lipid patterns were more heterogeneous than those of MAC, which is consistent with the variation seen in the histopathological phenotype. A common ceramide pattern discriminated necrotic from viable tumor in MAC with 92.9% accuracy and in other human tumors. Targeted analysis of ceramide and related sphingolipid mass features in necrotic tissues may provide a new classification of tumor cell death based on metabolic shifts. Real-time lipid patterns may have a role in future clinical decision-making in cancer precision medicine.
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