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

Michaela Schwaiger-Haber, Ethan Stancliffe, Dhanalakshmi S. Anbukumar, Blake Sells, Jia Yi, Kevin Cho, Kayla Adkins-Travis, Milan G. Chheda, Leah P. Shriver and Gary J. Patti ()
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Michaela Schwaiger-Haber: Washington University in St. Louis
Ethan Stancliffe: Washington University in St. Louis
Dhanalakshmi S. Anbukumar: Washington University in St. Louis
Blake Sells: Washington University in St. Louis
Jia Yi: Washington University in St. Louis
Kevin Cho: Washington University in St. Louis
Kayla Adkins-Travis: Washington University in St. Louis
Milan G. Chheda: Washington University in St. Louis
Leah P. Shriver: Washington University in St. Louis
Gary J. Patti: Washington University in St. Louis

Nature Communications, 2023, vol. 14, issue 1, 1-17

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41467-023-38403-x

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