Data from Interactions between Ploidy and Resource Availability Shape Clonal Evolution in Glioblastoma

Glioblastoma (GBM) is the most aggressive form of primary brain tumor. The infiltrative nature of GBM makes complete surgical resection impossible. The selective forces that govern gliomagenesis are strong, shaping the composition of tumor cells during the initial progression to malignancy with late consequences for invasiveness and therapy response. Here, we developed a mathematical model that incorporates ploidy level and the nature of the brain tissue microenvironment to simulate the growth and invasion of GBM and used the model to make inferences about GBM initiation and response to the standard-of-care treatment. The spatial distribution of resource access in the brain was approximated through integration of in silico modeling, multiomics data, and image analysis of primary and recurrent GBM. The in silico results suggested that high-ploidy cells transition faster from oxidative phosphorylation to glycolysis than low-ploidy cells because they are more sensitive to hypoxia. Between surgeries, simulated tumors with different ploidy compositions progressed at different rates; however, whether higher ploidy predicted fast recurrence was a function of the brain microenvironment. Historical data supported the dependence on available resources in the brain, as shown by a significant correlation between the median oxygen levels in human tissues and the median ploidy of cancers that arise in the respective tissues. Taken together, these findings suggest that the availability of metabolic substrates in the brain drives different cell fate decisions for cells with different ploidy, thereby modulating both gliomagenesis and GBM recurrence.

Significance: Ploidy viewed in the context of the resources in the microenvironment has the potential to inform whether modulation of energetic availability can delay tumor progression and could help guide clinical decision making.