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Metabolic profiles of human brain parenchyma and glioma for rapid tissue diagnosis by targeted desorption electrospray ionization mass spectrometry

Abstract

Desorption electrospray ionization mass spectrometry (DESI-MS) is well suited for intraoperative tissue analysis since it requires little sample preparation and offers rapid and sensitive molecular diagnostics. Currently, intraoperative assessment of the tumor cell percentage of glioma biopsies can be made by measuring a single metabolite, N-acetylaspartate (NAA). The inclusion of additional biomarkers will likely improve the accuracy when distinguishing brain parenchyma from glioma by DESI-MS. To explore this possibility, mass spectra were recorded for extracts from 32 unmodified human brain samples with known pathology. Statistical analysis of data obtained from full-scan and multiple reaction monitoring (MRM) profiles identified discriminatory metabolites, namely gamma-aminobutyric acid (GABA), creatine, glutamic acid, carnitine, and hexane-1,2,3,4,5,6-hexol (abbreviated as hexol), as well as the established biomarker NAA. Brain parenchyma was readily differentiated from glioma based on these metabolites as measured both in full-scan mass spectra and by the intensities of their characteristic MRM transitions. New DESI-MS methods (5 min acquisition using full scans and MS/MS), developed to measure ion abundance ratios among these metabolites, were tested using smears of 29 brain samples. Ion abundance ratios based on signals for GABA, creatine, carnitine, and hexol all had sensitivities > 90%, specificities > 80%, and accuracies > 85%. Prospectively, the implementation of diagnostic ion abundance ratios should strengthen the discriminatory power of individual biomarkers and enhance method robustness against signal fluctuations, resulting in an improved DESI-MS method of glioma diagnosis.

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Data availability

All data analyzed during this study are included in this published article and its electronic supplementary information.

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Acknowledgements

The authors thank Dr. Eyas M. Hattab for providing evaluation of brain samples used in this and previous work. We thank Clint M. Alfaro for his assistance in writing custom MATLAB codes for data processing and Christina R. Ferreira for providing the scan library used in multiple reaction monitoring (MRM) profiling.

Code availability

The custom MATLAB codes used for data processing are available from the corresponding author upon request.

Funding

This work was funded by National Cancer Institute (IR33CA240181-01A1) and Waters Inc. (Grant #40002775).

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R. Chen and R.G. Cooks designed the research; R. Chen performed the research; R. Chen and H.M. Brown analyzed the data; R. Chen, H.M. Brown, and R.G. Cooks wrote the paper.

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Correspondence to R. Graham Cooks.

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Chen, R., Brown, H.M. & Cooks, R.G. Metabolic profiles of human brain parenchyma and glioma for rapid tissue diagnosis by targeted desorption electrospray ionization mass spectrometry. Anal Bioanal Chem 413, 6213–6224 (2021). https://doi.org/10.1007/s00216-021-03593-0

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Keywords

  • Metabolomics
  • Biomarker
  • Glioma
  • Ambient ionization
  • Multiple reaction monitoring
  • Tandem mass spectrometry