Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities

Garofano et al. use single-cell RNA-sequencing data to classify glioblastomas along a metabolic axis of mitochondrial and glycolytic/plurimetabolic states and a neurodevelopmental axis of proliferative/progenitor and neuronal states. 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.

Automated summary

Garofano et al. classified glioblastomas into subtypes along metabolic and neurodevelopmental axes using single-cell RNA-sequencing data. Mitochondrial GBM showed the most favorable clinical outcome and vulnerability to inhibitors of oxidative phosphorylation, while glycolytic/plurimetabolic GBM relied on aerobic glycolysis and other metabolic pathways for energy production. This pathway-based classification can inform survival and precision targeting of cancer metabolism.