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Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis

Xiaoqiang Sun12, Le Zhang34*, Hua Tan5, Jiguang Bao2, Costas Strouthos6 and Xiaobo Zhou1*

Author affiliations

1 Department of Radiology, The Methodist Hospital Research Institute, Weil Cornell Medical College, Houston, TX, 77030, USA

2 School of Mathematical Sciences, Beijing Normal University, Beijing, 100875, P R China

3 College of Computer and Information Science, Southwest University, Chongqing, 400715, P R China

4 Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, 49931, USA

5 College of Global Change and Earth System Science, Beijing normal University, Beijing, 100875, P R China

6 Computation-based Science and Technology Research Center, The Cyprus Institute, Nicosia, 1645, Cyprus

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Citation and License

BMC Bioinformatics 2012, 13:218  doi:10.1186/1471-2105-13-218

Published: 30 August 2012

Abstract

Background

The epidermal growth factor receptor (EGFR) signaling pathway and angiogenesis in brain cancer act as an engine for tumor initiation, expansion and response to therapy. Since the existing literature does not have any models that investigate the impact of both angiogenesis and molecular signaling pathways on treatment, we propose a novel multi-scale, agent-based computational model that includes both angiogenesis and EGFR modules to study the response of brain cancer under tyrosine kinase inhibitors (TKIs) treatment.

Results

The novel angiogenesis module integrated into the agent-based tumor model is based on a set of reaction–diffusion equations that describe the spatio-temporal evolution of the distributions of micro-environmental factors such as glucose, oxygen, TGFα, VEGF and fibronectin. These molecular species regulate tumor growth during angiogenesis. Each tumor cell is equipped with an EGFR signaling pathway linked to a cell-cycle pathway to determine its phenotype. EGFR TKIs are delivered through the blood vessels of tumor microvasculature and the response to treatment is studied.

Conclusions

Our simulations demonstrated that entire tumor growth profile is a collective behaviour of cells regulated by the EGFR signaling pathway and the cell cycle. We also found that angiogenesis has a dual effect under TKI treatment: on one hand, through neo-vasculature TKIs are delivered to decrease tumor invasion; on the other hand, the neo-vasculature can transport glucose and oxygen to tumor cells to maintain their metabolism, which results in an increase of cell survival rate in the late simulation stages.

Keywords:
Multi-scale; Agent-based modeling; EGFR signaling pathway; Angiogenesis; TKI treatment