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Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem.

ABSTRACT: Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contributions, and metabolic turnover fluxes across the brains of mice harboring GL261 glioma, a widely used model for glioblastoma. When integrated with MSI, the combination of ion mobility, desorption electrospray ionization, and matrix assisted laser desorption ionization reveals alterations in multiple anabolic pathways. De novo fatty acid synthesis flux is increased by approximately 3-fold in glioma relative to surrounding healthy tissue. Fatty acid elongation flux is elevated even higher at 8-fold relative to surrounding healthy tissue and highlights the importance of elongase activity in glioma.

SUBMITTER: Schwaiger-Haber M

PROVIDER: S-EPMC10199024 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem.

Schwaiger-Haber Michaela M Stancliffe Ethan E Anbukumar Dhanalakshmi S DS Sells Blake B Yi Jia J Cho Kevin K Adkins-Travis Kayla K Chheda Milan G MG Shriver Leah P LP Patti Gary J GJ

Nature communications 20230519 1

Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contrib ...[more]

PMID: 37208361

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Project description:Transcriptomic studies have attempted to classify glioblastoma (GB) into subtypes that predict survival and that have different therapeutic vulnerabilities. Here we identified three metabolic subtypes: glycolytic, oxidative and a mixed glycolytic/oxidative by mass spectrometry imaging of rapidly excised tumour sections from two GB patients infused with [U-13C]glucose and from spatial transcriptomic analysis of contiguous sections. The phenotypes did not correlate with microenvironmental features, including proliferation rate, immune cell infiltration, and vascularisation, were retained when patient-derived cells were grown in vitro, or as orthotopically implanted xenografts, and were robust to changes in oxygen concentration, demonstrating their cell intrinsic nature. The spatial extent of the regions occupied by cells displaying these distinct metabolic phenotypes are large enough to be detected using clinically applicable metabolic imaging techniques. A limitation of the study is that it is based on only two patient tumours, albeit on multiple sections, and therefore represents a proof-of-concept study. Glioblastoma is the most common primary adult brain cancer. Transcriptomic analyses have attempted to classify GB into subtypes that could predict treatment response, with a recent study that used a pathway-based classification defining metabolism-associated subtypes with distinct therapeutic vulnerabilities. These included a mitochondrial subtype, which is associated with a more favourable clinical outcome and that is sensitive to inhibitors of oxidative phosphorylation, and a glycolytic/plurimetabolic subtype that is resistant to multiple treatment types. An important question is the extent to which the metabolism displayed by tumour cells in vivo are cell intrinsic and how much they are defined by the tumour microenvironment. We have addressed this question using mass spectrometry imaging of rapidly excised tumour sections from GB patients infused with [U-13C]glucose immediately prior to surgery to image tumour cell metabolic fluxes in vivo and from a spatial transcriptomic analysis of adjacent sections. To our knowledge, this is the first report demonstrating high resolution imaging of metabolic fluxes in a human tumour in vivo.

Dataset Information

Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem.

Publications

Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem.

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