title: Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: incorporating EGFR signaling pathway and angiogenesis.
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.
authors.affiliation: Department of Radiology, The Methodist Hospital Research Institute, Weil Cornell Medical College, Houston, TX 77030, USA.
authors.forename: Xiaoqiang
authors.initials: X
authors.lastname: Sun
authors.forename: Le
authors.initials: L
authors.lastname: Zhang
authors.forename: Hua
authors.initials: H
authors.lastname: Tan
authors.forename: Jiguang
authors.initials: J
authors.lastname: Bao
authors.forename: Costas
authors.initials: C
authors.lastname: Strouthos
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Zhou
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology* / Q000627:therapeutic use; D001932:Brain Neoplasms / Q000098:blood supply* / Q000188:drug therapy / Q000378:metabolism; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D066246:ErbB Receptors / Q000037:antagonists & inhibitors* / Q000378:metabolism; D006801:Humans; D008954:Models, Biological; D009389:Neovascularization, Pathologic / Q000378:metabolism*; D047428:Protein Kinase Inhibitors / Q000494:pharmacology* / Q000627:therapeutic use; D015398:Signal Transduction / Q000187:drug effects; D012984:Software
chemical_list: D000970:Antineoplastic Agents; D047428:Protein Kinase Inhibitors; D066246:ErbB Receptors