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...

Full description

Saved in:
Bibliographic Details
Main Authors: Anna Rushin, Aleezeh Shaikh, Callie Hardin, Loic P. Deleyrolle, Matthew E. Merritt
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-02124-6
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2045-2322