Data from: Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics

Glioblastomas are aggressive brain tumors with dismal prognosis. One of
the main bottlenecks for developing more effective therapies for
glioblastoma stems from their histologic and molecular heterogeneity,
leading to distinct tumor microenvironments and disease phenotypes.
Effectively characterizing these features would improve the clinical
management of glioblastoma. Glucose flux rates through glycolysis and
mitochondrial oxidation have been recently shown to quantitatively depict
glioblastoma proliferation in mouse models (GL261 and CT2A tumors) using
dynamic glucose-enhanced (DGE) deuterium spectroscopy. However, the
spatial features of tumor microenvironment phenotypes remain hitherto
unresolved. Here, we develop a DGE Deuterium Metabolic Imaging (DMI)
approach for profiling tumor microenvironments through glucose conversion
kinetics. Using a multimodal combination of tumor mouse models, novel
strategies for spectroscopic imaging and noise attenuation, and
histopathological correlations, we show that tumor lactate turnover
mirrors phenotype differences between GL261 and CT2A mouse glioblastoma,
whereas recycling of the peritumoral glutamate-glutamine pool is a
potential marker of invasion capacity in pooled cohorts, linked to
secondary brain lesions. These findings were validated by
histopathological characterization of each tumor, including cell density
and proliferation, peritumoral invasion and distant migration, and immune
cell infiltration. Our study bodes well for precision neuro-oncology,
highlighting the importance of mapping glucose flux rates to better
understand the metabolic heterogeneity of glioblastoma and its links to
disease phenotypes.