Metabolic flux analysis of glioblastoma neural stem cells reveals distinctive metabolic phenotypes in ketogenic conditions

Abstract

Glioblastomas (GBM) are the most prevalent primary brain tumors, affecting 5 in every 100,000 people. GBMs optimize proliferation through adaptive cellular metabolism, frequently exploiting the Warburg effect by increasing aerobic glycolysis and glucose utilization to facilitate rapid cell growth. This disproportionate reliance on glucose has driven interest in using the ketogenic diet (KD) as a treatment for GBM. In this study, we explored metabolic flux in three primary human GBM cell samples using a media simulating a KD. Flux analysis using a detailed metabolic modeling approach revealed three unique metabolic phenotypes in the patient GBMs that correlated with cell viability. Notably, these phenotypes are apparent in the flux modeling, but were not evidenced by changes in the metabolite pool sizes. This variability in metabolic flux may underlie the inconsistent results observed in preclinical and clinical studies using the KD as a treatment paradigm.