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Untargeted Metabolomic Characterization of Glioblastoma Intra-Tumor Heterogeneity Using OrbiSIMS

He, Wenshi; Edney, Max K.; Paine, Simon M. L.; Griffiths, Rian L.; Scurr, David J.; Rahman, Ruman; Kim, Dong-Hyun

Untargeted Metabolomic Characterization of Glioblastoma Intra-Tumor Heterogeneity Using OrbiSIMS Thumbnail


Authors

Wenshi He

Max K. Edney

Simon M. L. Paine

DAVID SCURR DAVID.SCURR@NOTTINGHAM.AC.UK
Principal Research Fellow



Abstract

Glioblastoma (GBM) is an incurable brain cancer with a median survival of less than two years from diagnosis. The standard treatment of GBM is multimodality therapy comprising surgical resection, radiation, and chemotherapy. However, prognosis remains poor, and there is an urgent need for effective anticancer drugs. Since different regions of a single GBM contain multiple cancer subpopulations (“intra-tumor heterogeneity”), this likely accounts for therapy failure as certain cancer cells can escape from immune surveillance and therapeutic threats. Here, we present metabolomic data generated using the Orbitrap secondary ion mass spectrometry (OrbiSIMS) technique to investigate brain tumor metabolism within its highly heterogeneous tumor microenvironment. Our results demonstrate that an OrbiSIMS-based untargeted metabolomics method was able to discriminate morphologically distinct regions (viable, necrotic, and non-cancerous) within single tumors from formalin-fixed paraffin-embedded tissue archives. Specifically, cancer cells from necrotic regions were separated from viable GBM cells based on a set of metabolites including cytosine, phosphate, purine, xanthine, and 8-hydroxy-7-methylguanine. Moreover, we mapped ubiquitous metabolites across necrotic and viable regions into metabolic pathways, which allowed for the discovery of tryptophan metabolism that was likely essential for GBM cellular survival. In summary, this study first demonstrated the capability of OrbiSIMS for in situ investigation of GBM intra-tumor heterogeneity, and the acquired information can potentially help improve our understanding of cancer metabolism and develop new therapies that can effectively target multiple subpopulations within a tumor.

Journal Article Type Article
Acceptance Date Mar 20, 2023
Online Publication Date Mar 30, 2023
Publication Date Apr 11, 2023
Deposit Date Apr 16, 2023
Publicly Available Date Apr 25, 2023
Journal Analytical Chemistry
Print ISSN 0003-2700
Electronic ISSN 1520-6882
Publisher American Chemical Society (ACS)
Peer Reviewed Peer Reviewed
Volume 95
Issue 14
Pages 5994-6001
DOI https://doi.org/10.1021/acs.analchem.2c05807
Keywords Cancer, Cells, Ions, Mass spectrometry, Metabolism
Public URL https://nottingham-repository.worktribe.com/output/19006255
Publisher URL https://pubs.acs.org/doi/10.1021/acs.analchem.2c05807

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