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Updated: Nov 14, 2025
Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
Published on: January 9, 2019
Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities
Luciano Garofano1,2, Simona Migliozzi1, Young Taek Oh1
1Institute for Cancer Genetics, Columbia University Medical Center, New York, NY, USA.
Abstract:
The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed along neurodevelopmental and metabolic axes, classified as proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic. Each subtype was enriched with biologically coherent multiomic features. Mitochondrial GBM was associated with the most favorable clinical outcome. It relied exclusively on oxidative phosphorylation for energy production, whereas the glycolytic/plurimetabolic subtype was sustained by aerobic glycolysis and amino acid and lipid metabolism. Deletion of the glucose-proton symporter SLC45A1 was the truncal alteration most significantly associated with mitochondrial GBM, and the reintroduction of SLC45A1 in mitochondrial glioma cells induced acidification and loss of fitness. Mitochondrial, but not glycolytic/plurimetabolic, GBM exhibited marked vulnerability to inhibitors of oxidative phosphorylation. The pathway-based classification of GBM informs survival and enables precision targeting of cancer metabolism.
Insights
This study reveals four glioblastoma (GBM) subtypes based on cell states and metabolism. Mitochondrial GBM shows a favorable outcome and vulnerability to oxidative phosphorylation inhibitors, offering new therapeutic targets.
Area of Science:
- Oncology
- Cancer Biology
- Genomics
Background:
- Glioblastoma (GBM) transcriptomic classification has limitations in predicting patient survival and treatment response.
- A need exists for a more robust classification system that captures the biological heterogeneity of GBM.
Purpose of the Study:
- To computationally identify core biological traits and subtypes of glioblastoma (GBM) cells.
- To classify GBM subtypes along neurodevelopmental and metabolic axes for improved understanding of tumor biology and clinical outcomes.
Main Methods:
- Utilized a computational approach for unbiased identification of single-cell and bulk tumor traits.
- Analyzed multiomic features and metabolic pathways across identified GBM subtypes.
Main Results:
- Uncovered four GBM subtypes: proliferative/progenitor, neuronal, mitochondrial, and glycolytic/plurimetabolic.
- Mitochondrial GBM exhibited the most favorable prognosis, relying on oxidative phosphorylation, and showed vulnerability to its inhibitors.
- Deletion of SLC45A1 was linked to mitochondrial GBM, with its reintroduction impairing cell fitness.
Conclusions:
- A pathway-based classification of GBM refines understanding of tumor subtypes and clinical outcomes.
- Identified metabolic vulnerabilities in GBM subtypes, particularly mitochondrial GBM, suggesting potential for targeted therapies.
- This classification facilitates precision targeting of cancer metabolism in glioblastoma.
