Simulating Brain Tumor Heterogeneity with a Multiscale Agent-Based Model:Linking Cell Signaling, Motility Bias & Expansion Rate

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  • 3 January 2007
Abstract
We have extended our previously developed 3D multi-scale agent-based brain tumor model to simulate tumor heterogeneity and to analyze its impact across the scales of interest. While our model continues to employ an epidermal growth factor receptor (EGFR) gene-protein interaction pathway to determine the cells' phenotype, it now adds an explicit treatment of biomechanical pressure to the model's biochemical microenvironment. We simulate a simplified tumor progression pathway that leads to the emergence of five distinct glioma cell clones with different EGFR density and cell adhesion patterns. The in silico results show that microscopic tumor heterogeneity can impact the tumor system's multicellular growth patterns. Our findings further confirm that EGFR density plays an important role in processing the chemotactic motility bias that results in increased persistence of the more aggressive clonal populations which also switch earlier from proliferation-dominated to a more migratory phenotype. However, while the EGFR density within each clone remains rather stable, it is the fluctuations in active phospholipase Cg (PLCg) that impact the clone's expansion rate changes the most. Intriguingly, in aggressive clones that exhibit a high EGFR density, the downstream signaling cascade appears to process signals more efficiently as indicated in a more sensitive PLCg-"switch". Potential implications from this in silico work for experimental and computational studies are discussed.

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