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

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.

Automated summary

Tumors are heterogeneous and consist of various cell types in different microenvironments. The integration of mass spectrometry imaging (MSI), stable isotope labeling, and isotopologue spectral analysis enables the mapping of metabolite distributions and metabolic fluxes in the brains of mice with GL261 glioma. This approach reveals alterations in anabolic pathways, specifically an increase in de novo fatty acid synthesis and elongation fluxes in the glioma compared to surrounding healthy tissue.