1. Real-time lipid patterns to classify viable and necrotic liver tumors
- Author
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Ron M. A. Heeren, Mari F.C.M. van den Hout, Pierre-Maxence Vaysse, Heike I. Grabsch, Steven W.M. Olde Damink, Tiffany Porta Siegel, Marc H.A. Bemelmans, RS: M4I - Imaging Mass Spectrometry (IMS), Imaging Mass Spectrometry (IMS), RS: GROW - R2 - Basic and Translational Cancer Biology, Pathologie, MUMC+: DA Pat Pathologie (9), Surgery, MUMC+: MA Heelkunde (9), and RS: NUTRIM - R2 - Liver and digestive health
- Subjects
0301 basic medicine ,profiles ,medicine.medical_specialty ,Pathology ,Ceramide ,precision medicine ,Biology ,in-vivo ,Pathology and Forensic Medicine ,Metastasis ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,In vivo ,generation ,medicine ,Molecular Biology ,SPHINGOLIPID METABOLISM ,biology ,CERAMIDE ,Cancer ,Cell Biology ,CHEMOTHERAPY ,medicine.disease ,Phenotype ,Sphingolipid ,CANCER ,030104 developmental biology ,chemistry ,030220 oncology & carcinogenesis ,Hepatocellular carcinoma ,METASTASIS ,Histopathology - 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. Real-time lipid patterns can identify liver tumors and their inter-tumor and intra-tumor heterogeneity. Ceramides and related sphingolipids are a common feature of necrotic tumors and can characterize the tumor phenotype based on metabolic shifts relevant for cell death pathways. Lipid patterns have the potential to improve clinical decision-making in the near future.
- Published
- 2021