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

<p>Abstract</p> <p>Background</p> <p>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 inve...

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Main Authors: Sun Xiaoqiang, Zhang Le, Tan Hua, Bao Jiguang, Strouthos Costas, Zhou Xiaobo
Format: Article
Language:English
Published: BMC 2012-08-01
Series:BMC Bioinformatics
Subjects:
Online Access:http://www.biomedcentral.com/1471-2105/13/218
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spelling doaj-425e1704def0401cb509bfe9476b6dbf2020-11-25T00:23:56ZengBMCBMC Bioinformatics1471-21052012-08-0113121810.1186/1471-2105-13-218Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesisSun XiaoqiangZhang LeTan HuaBao JiguangStrouthos CostasZhou Xiaobo<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p> http://www.biomedcentral.com/1471-2105/13/218Multi-scaleAgent-based modelingEGFR signaling pathwayAngiogenesisTKI treatment
collection DOAJ
language English
format Article
sources DOAJ
author Sun Xiaoqiang
Zhang Le
Tan Hua
Bao Jiguang
Strouthos Costas
Zhou Xiaobo
spellingShingle Sun Xiaoqiang
Zhang Le
Tan Hua
Bao Jiguang
Strouthos Costas
Zhou Xiaobo
Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis
BMC Bioinformatics
Multi-scale
Agent-based modeling
EGFR signaling pathway
Angiogenesis
TKI treatment
author_facet Sun Xiaoqiang
Zhang Le
Tan Hua
Bao Jiguang
Strouthos Costas
Zhou Xiaobo
author_sort Sun Xiaoqiang
title Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis
title_short Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis
title_full Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis
title_fullStr Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis
title_full_unstemmed Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis
title_sort multi-scale agent-based brain cancer modeling and prediction of tki treatment response: incorporating egfr signaling pathway and angiogenesis
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2012-08-01
description <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p>
topic Multi-scale
Agent-based modeling
EGFR signaling pathway
Angiogenesis
TKI treatment
url http://www.biomedcentral.com/1471-2105/13/218
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