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

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.

Citation

He, W., Edney, M. K., Paine, S. M. L., Griffiths, R. L., Scurr, D. J., Rahman, R., & Kim, D.-H. (2023). Untargeted Metabolomic Characterization of Glioblastoma Intra-Tumor Heterogeneity Using OrbiSIMS. Analytical Chemistry, 95(14), 5994-6001. https://doi.org/10.1021/acs.analchem.2c05807

• 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
• 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