Objectives: Glioblastoma multiforme (GBM), the most aggressive glial brain tumors, can metabolize glucose through glycolysis and mitochondrial oxidation pathways. While specific dependencies on those pathways are increasingly associated with treatment response, detecting such GBM subtypes in vivo remains elusive. Here, we develop a dynamic glucose-enhanced deuterium spectroscopy (DGE H-MRS) approach for differentially assessing glucose turnover rates through glycolysis and mitochondrial oxidation in mouse GBM and explore their association with histologic features of the tumor and its microenvironment.

Materials And Methods: GL261 and CT2A glioma allografts were induced in immunocompetent mice and scanned in vivo at 9.4 Tesla, harnessing DGE H-MRS with volume selection and Marchenko-Pastur PCA (MP-PCA) denoising to achieve high temporal resolution. Each tumor was also classified by histopathologic analysis and assessed for cell proliferation (Ki67 immunostaining), while the respective cell lines underwent in situ extracellular flux analysis to assess mitochondrial function.

Results: MP-PCA denoising of in vivo DGE H-MRS data significantly improved the time-course detection (~2-fold increased Signal-to-Noise Ratio) and fitting precision (-19 ± 1 % Cramér-Rao Lower Bounds) of H-labelled glucose, and glucose-derived glutamate-glutamine (Glx) and lactate pools in GL261 and CT2A orthotopic tumors. Kinetic modeling further indicated inter-tumor heterogeneity of glucose consumption rate for glycolysis and oxidation during a defined epoch of active proliferation in both cohorts (19 ± 1 days post-induction), with consistent volumes (38.3 ± 3.4 mm) and perfusion properties prior to marked necrosis. Histopathologic analysis of these tumors revealed clear differences in tumor heterogeneity between the two GBM models, aligned with metabolic differences of the respective cell lines monitored in situ. Importantly, glucose oxidation (i.e. Glx synthesis and elimination rates: 0.40 ± 0.08 and 0.12 ± 0.03 mM min, respectively) strongly correlated with cell proliferation across the pooled cohorts (R = 0.82, p = 0.001; and R = 0.80, p = 0.002, respectively), regardless of tumor morphologic features or in situ metabolic characteristics of each GBM model.

Conclusions: Our fast DGE H-MRS enables the quantification of glucose consumption rates through glycolysis and mitochondrial oxidation in mouse GBM, which is relevant for assessing their modulation in vivo according to tumor microenvironment features such as cell proliferation. This novel application augurs well for non-invasive metabolic characterization of glioma or other cancers with mitochondrial oxidation dependencies.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760481PMC
http://dx.doi.org/10.1016/j.nicl.2021.102932DOI Listing

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