TMET-02. CELL-INTRINSIC METABOLIC PHENOTYPES IDENTIFIED IN GLIOBLASTOMA PATIENTS USING MASS SPECTROMETRY IMAGING OF 13C-LABELED GLUCOSE METABOLISM

Abstract Glioblastoma (GB) is an inherently heterogeneous and invasive primary brain cancer. Genomic and transcriptomic studies have attempted to classify GB into subtypes that predict survival and that have different therapeutic vulnerabilities. An outstanding question and technical challenge is to visualize the metabolism of a tumour within its native microenvironment and understand to what extent its metabolism is driven by the microenvironment. Patients with GB tumours were infused with [U-13C]glucose and intra-operative multi-regional tumour samples were rapidly snap frozen for analysis using mass spectrometry imaging (MSI). Tissue microenvironment was assessed using multiplexed antibodies in immunocytochemistry (IMC) of contiguous sections. Isotope tracking in human-derived neurospheres and patient-derived xenografts were used to confirm the presence of metabolic phenotypes detected in the human samples and to test the susceptibility of each phenotype to a panel of drugs targeting cellular metabolism. Three metabolic signatures were identified in patient tumours: glycolytic, oxidative and a mixed glycolytic/oxidative phenotype. The phenotypes did not correlate with microenvironmental features, including proliferation rate, immune cell infiltration, and vascularisation. The phenotypes 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. The phenotypes also demonstrate differential drug sensitivities, suggesting imaging of these phenotypes may be used to stratify patients for personalised therapy trials. This is the first report to demonstrate high resolution imaging of metabolic fluxes in a human tumour in vivo and the presence of different metabolic phenotypes within GB that are tumour cell intrinsic and largely independent of the tumour microenvironment.