Simulating brain tumor heterogeneity with a multiscale agent-based model: Linking molecular signatures, phenotypes and expansion rate

Le Zhang, Costas G. Strouthos, Zhihui Wang, Thomas S. Deisboeck

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

We have extended our previously developed 3D multi-scale agent-based brain tumor model to simulate cancer heterogeneity and to analyze its impact across the scales of interest. While our algorithm continues to employ an epidermal growth factor receptor (EGFR) gene-protein interaction network to determine the cells' phenotype, it now adds an implicit treatment of tumor cell adhesion related 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 'search precisions'. 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 results in the more aggressive clonal populations switching earlier from proliferation-dominated to a more migratory phenotype. Moreover, analyzing the dynamic molecular profile that triggers the phenotypic switch between proliferation and migration, our in silico oncogenomics data display spatial and temporal diversity in documenting the regional impact of tumorigenesis, and thus support the added value of multi-site and repeated assessments in vitro and in vivo. Potential implications from this in silico work for experimental and computational studies are discussed.

Original languageEnglish (US)
Pages (from-to)307-319
Number of pages13
JournalMathematical and Computer Modelling
Volume49
Issue number1-2
DOIs
StatePublished - Jan 1 2009

Keywords

  • Agent-based model
  • Cancer heterogeneity
  • Epidermal growth factor receptor
  • Glioma

ASJC Scopus subject areas

  • Computer Science Applications
  • Modeling and Simulation

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