Modeling and evaluation of a stochastic multiscale glioma model: Integrating pharmacotherapy and psychological interventions

During cancer treatment, noise often affects signaling networks and spatiotemporal dynamics, while elevated psychological stress or anxiety in patients contributes to suboptimal treatment outcomes. In line with research findings on glioma pathogenesis, a novel hybrid multiscale agent-based model is presented, which couples stochastic differential equations, stochastic partial differential equations and a set of rules on cell phenotype switching together from micro and macro levels. The therapeutic effects of temozolomide (TMZ) alone, BKM120 alone, and the combination of TMZ with BKM120 are simulated in two dimensions. Subsequently, the impacts of different noise intensities and psychological pressure on the growth of glioma cells are separately investigated. Additionally, the impacts of different activation rates of AKT and PI3K on the size of glioma are analyzed, respectively. Ultimately, the three-dimensional (3D) tumor spheroid model is constructed to display the internal characteristics of the tumor. Results reveal that (1) the noise on the whole cuts down the growth and proliferation of glioma cells; (2) AKT, being closely related to cell cycle, greatly regulates tumor cell number; (3) the synergy of psychological intervention and drug therapy shows a significant improvement over drug therapy alone; (4) 3D simulations clearly demonstrate a treatment-proliferation game by angiogenesis. These results raise comprehension of the overall behavior of the glioma system and enable predictions of clinical treatment outcomes.