Glioblastoma (GBM) remains the most aggressive primary brain cancer in adults.
Similar to other cancers, GBM cells undergo metabolic reprogramming to promote
proliferation and survival. Glycolytic inhibition is widely used to target such
reprogramming. However, the stability of glycolytic inhibition in GBM remains unclear
especially in a hypoxic tumor microenvironment. In this study, it was determined that
glucose-6-phosphatase-α (G6PC/G6Pase) expression is elevated in GBM when compared
to normal brain. Human-derived brain tumor initiating cells (BTICs) utilize this enzyme to
counteract glycolytic inhibition induced by 2-Deoxy-D-glucose (2DG) and sustain malignant
progression. Down-regulation of G6PC renders the majority of these cells unable to survive
glycolytic inhibition, and promotes glycogen accumulation through the activation of
glycogen synthase (GYS1) and inhibition of glycogen phosphorylase (PYGL). Moreover, BTICs
that survive G6PC knockdown are less aggressive (reduced migration, invasion,
proliferation, and increased astrocytic differentiation). Collectively, these findings
establish G6PC as a key enzyme with pro-malignant functional consequences that has not
been previously reported in GBM and identify it as a potential therapeutic target.
Studying the progression of the proliferative and differentiative patterns of neural stem cells at the individual cell level is crucial to the understanding of cortex development and how the disruption of such patterns can lead to malformations and neurodevelopmental diseases. However, our understanding of the precise lineage progression programme at single‐cell resolution is still incomplete due to the technical variations in lineage‐tracing approaches. One of the key challenges involves developing a robust theoretical framework in which we can integrate experimental observations and introduce correction factors to obtain a reliable and representative description of the temporal modulation of proliferation and differentiation. In order to obtain more conclusive insights, we carry out virtual clonal analysis using mathematical modelling and compare our results against experimental data. Using a dataset obtained with Mosaic Analysis with Double Markers, we illustrate how the theoretical description can be exploited to interpret and reconcile the disparity between virtual and experimental results.
<p>Supplementary Movie S1, related to Supplementary Figure 1: Brain tumor initiating cells (BTICs) escape glycolytic inhibition with an aggressive phenotype.</p>
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