Dataset Information

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.

SUBMITTER: Jarmusch AK

PROVIDER: S-EPMC4760779 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS.

Jarmusch Alan K AK Pirro Valentina V Baird Zane Z Hattab Eyas M EM Cohen-Gadol Aaron A AA Cooks R Graham RG

Proceedings of the National Academy of Sciences of the United States of America 20160119 6

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 be ...[more]

PMID: 26787885

Similar Datasets

Project description:Lipids are a naturally occurring group of molecules that not only contribute to the structural integrity of the lung preventing alveolar collapse but also play important roles in the anti-inflammatory responses and antiviral protection. Alteration in the type and spatial localization of lipids in the lung plays a crucial role in various diseases, such as respiratory distress syndrome (RDS) in preterm infants and oxidative stress-influenced diseases, such as pneumonia, emphysema, and lung cancer following exposure to environmental stressors. The ability to accurately measure spatial distributions of lipids and metabolites in lung tissues provides important molecular insights related to lung function, development, and disease states. Nanospray desorption electrospray ionization (nano-DESI) and other ambient ionization mass spectrometry techniques enable label-free imaging of complex samples in their native state with minimal to absolutely no sample preparation. However, lipid coverage obtained in nano-DESI mass spectrometry imaging (MSI) experiments has not been previously characterized. In this work, the depth of lipid coverage in nano-DESI MSI of mouse lung tissues was compared to liquid chromatography tandem mass spectrometry (LC-MS/MS) lipidomics analysis of tissue extracts prepared using two different procedures: standard Folch extraction method of the whole lung samples and extraction into a 90% methanol/10% water mixture used in nano-DESI MSI experiments. A combination of positive and negative ionization mode nano-DESI MSI identified 265 unique lipids across 20 lipids subclasses and 19 metabolites (284 in total) in mouse lung tissues. Except for triacylglycerols (TG) species, nano-DESI MSI provided comparable coverage to LC-MS/MS experiments performed using methanol/water tissue extracts and up to 50% coverage in comparison with the Folch extraction-based whole lung lipidomics analysis. These results demonstrate the utility of nano-DESI MSI for comprehensive spatially resolved analysis of lipids in tissue sections. A combination of nano-DESI MSI and LC-MS/MS lipidomics is particularly useful for exploring changes in lipid distributions during lung development, as well as resulting from disease or exposure to environmental toxicants.

Project description:Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is a molecular imaging method that can be used to elucidate the small-molecule composition of tissues and map their spatial information using two-dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI-MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for which are known to carry various nerve fiber types were harvested from a fresh cadaveric donor: mixed, motor and sensory (sciatic and femoral); cutaneous, sensory (sural); and autonomic (vagus). Tissue samples were harvested to include the nerve bundles in addition to surrounding connective tissue. Samples were flash-frozen, embedded in optimal cutting temperature compound in cross-section, and sectioned at 14 μm. Following DESI-MSI analysis, identical tissue sections were stained with hematoxylin and eosin. In this proof-of-concept study, a combination of multivariate and univariate statistical methods was used to evaluate molecular differences between the nerve and adjacent tissue and between nerve subtypes. The acquired mass spectral profiles of the peripheral nerve samples presented trends in ion abundances that seemed to be characteristic of nerve tissue and spatially corresponded to the associated histology of the tissue sections. Principal component analysis (PCA) supported the separation of the samples into distinct nerve and adjacent tissue classes. This classification was further supported by the K-means clustering analysis, which showed separation of the nerve and background ions. Differences in ion expression were confirmed using ANOVA which identified statistically significant differences in ion expression between the nerve subtypes. The PCA plot suggested some separation of the nerve subtypes into four classes which corresponded with the nerve types. This was supported by the K-means clustering. Some overlap in classes was noted in these two clustering analyses. This study provides emerging evidence that DESI-MSI is an effective tool for metabolomic profiling of peripheral nerves. Our results suggest that peripheral nerves have molecular profiles that are distinct from the surrounding connective tissues and that DESI-MSI may be able to discriminate between nerve subtypes. DESI-MSI of peripheral nerves may be a valuable technique that could be used to improve our understanding of peripheral nerve anatomy and physiology. The ability to utilize ambient mass spectrometry techniques in real time could also provide an unprecedented advantage for surgical decision making, including in nerve-sparing procedures in the future.

Project description:There has been a recent surge in applications of mass spectrometry (MS) to tissue analysis, particularly lipid-based tissue imaging using ambient ionization techniques. This recent growth highlights the need to examine the effects of sample handling, storage conditions, and experimental protocols on the quality of the data obtained. Variables such as time before freezing after organ removal, storage time at -80 °C, time stored at room temperature, heating, and freeze/thaw cycles were investigated for their effect on the data quality obtained in desorption electrospray ionization (DESI)-MS using mouse brain. In addition, analytical variables such as tissue thickness, drying times, and instrumental conditions were also examined for their impact on DESI-MS data. While no immediate changes were noted in the DESI-MS lipid profiles of the mouse brain tissue after spending 1 h at room temperature when compared to being frozen immediately following removal, minor changes were noted between the tissue samples after 7 months of storage at -80 °C. In tissue sections stored at room temperature, degradation was noted in 24 h by the appearance of fatty acid dimers, which are indicative of high fatty acid concentrations, while in contrast, those sections stored at -80 °C for 7 months showed no significant degradation. Tissue sections were also subjected to up to six freeze/thaw cycles and showed increasing degradation following each cycle. In addition, tissue pieces were subjected to 50 °C temperatures and analyzed at specific time points. In as little as 2 h, degradation was observed in the form of increased fatty acid dimer formation, indicating that enzymatic processes forming free fatty acids were still active in the tissue. We have associated these dimers with high concentrations of free fatty acids present in the tissue during DESI-MS experiments. Analytical variables such as tissue thickness and time left to dry under nitrogen were also investigated, with no change in the resulting profiles at thickness from 10 to 25 μm and with optimal signal obtained after just 20 min in the dessicator. Experimental conditions such as source parameters, spray solvents, and sample surfaces are all shown to impact the quality of the data. Inter-section (relative standard deviation (%RSD), 0.44-7.2%) and intra-sample (%RSD, 4.0-8.0%) reproducibility data show the high quality information DESI-MS provides. Overall, the many variables investigated here showed DESI-MS to be a robust technique, with sample storage conditions having the most effect on the data obtained, and with unacceptable sample degradation occurring during room temperature storage.

Dataset Information

Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS.

Publications

Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets