Computational modeling demonstrates that glioblastoma cells can survive spatial environmental challenges through exploratory adaptation

Glioblastoma (GBM) is an aggressive type of brain cancer with remarkable cell migration and adaptation capabilities. Exploratory adaptation—utilization of random changes in gene regulation for adaptive benefits—was recently proposed as the process enabling organisms to survive unforeseen conditions. We investigate whether exploratory adaption explains how GBM cells from different anatomic regions of the tumor cope with micro-environmental pressures. We introduce new notions of phenotype and phenotype distance, and determine probable spatial-phenotypic trajectories based on patient data. While some cell phenotypes are inherently plastic, others are intrinsically rigid with respect to phenotypic transitions. We demonstrate that stochastic exploration of the regulatory network structure confers benefits through enhanced adaptive capacity in new environments. Interestingly, even with exploratory capacity, phenotypic paths are constrained to pass through specific, spatial-phenotypic ranges. This work has important implications for understanding how such adaptation contributes to the recurrence dynamics of GBM and other solid tumors. Glioblastoma cells are known to be able to adapt easily to different environments. The authors study the dynamic adaptation of glioblastoma cells to the heterogenous brain tumor microenvironment, showing that tumor cells demonstrate varying plasticity of their transcriptomic profiles and an ability to survive new stimuli, in part, by propagating stochastic perturbations over their gene-regulatory network.