title: Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS.
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.
authors.affiliation: Department of Chemistry and Center for Analytical Instrumentation Development, Purdue University, West Lafayette, IN 47907;
authors.forename: Alan K
authors.initials: AK
authors.lastname: Jarmusch
authors.affiliation: Department of Chemistry and Center for Analytical Instrumentation Development, Purdue University, West Lafayette, IN 47907;
authors.forename: Valentina
authors.initials: V
authors.lastname: Pirro
authors.affiliation: Department of Chemistry and Center for Analytical Instrumentation Development, Purdue University, West Lafayette, IN 47907;
authors.forename: Zane
authors.initials: Z
authors.lastname: Baird
authors.affiliation: Department of Pathology and Laboratory Medicine, Indiana School of Medicine, Indianapolis, IN 46202;
authors.forename: Eyas M
authors.initials: EM
authors.lastname: Hattab
authors.affiliation: Department of Neurological Surgery, Indiana University School of Medicine, Indianapolis, IN 46202.
authors.forename: Aaron A
authors.initials: AA
authors.lastname: Cohen-Gadol
authors.affiliation: Department of Chemistry and Center for Analytical Instrumentation Development, Purdue University, West Lafayette, IN 47907; cooks@purdue.edu.
authors.forename: R Graham
authors.initials: RG
authors.lastname: Cooks
mesh_terms: D001224:Aspartic Acid / Q000031:analogs & derivatives / Q000378:metabolism; D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000378:metabolism*; D002454:Cell Differentiation; D005910:Glioma / Q000378:metabolism; D066128:Gray Matter / Q000473:pathology; D006801:Humans; D050356:Lipid Metabolism; D055432:Metabolomics; D025341:Principal Component Analysis; D021241:Spectrometry, Mass, Electrospray Ionization / Q000379:methods*; D066127:White Matter / Q000473:pathology
chemical_list: D001224:Aspartic Acid; C000179:N-acetylaspartate
keywords: MS imaging; ambient ionization; multivariate statistics; neurosurgery; pathology