Modeling the Effect of Chemotaxis In Glioblastoma Tumor Progression

Tumor progression depends on the intricate interplay between biological processes that span the molecular and macroscopic scales. A mathematical agent-based model is presented to describe the 3-D (three-dimensional) progression of a brain tumor type (i.e., glioblastoma multiforme) as the collective behavior of individual tumor cells whose fate is determined by intracellular signaling pathways (i.e., MAPK pathway) that are governed by the temporal-spatial distribution of key biochemical cues (i.e., growth factors, nutrients). The model is used to investigate how tumor growth and invasiveness depend on the response of migrating tumor cells to chemoattractants. Simulation results suggest that individual cell sensitivity to chemical gradients is necessary to generate in silico tumors with the irregular shape and diffusive tumor-stroma interface characteristic of glioblastomas. In addition, vascular network damage influences tumor growth and invasiveness. The results quantitatively recapitulate the central role that nutrient availability and signaling proteins have on tumor invasive properties. © 2010 American Institute of Chemical Engineers AIChE J, 2011

[1]  L. Preziosi,et al.  Cell adhesion mechanisms and stress relaxation in the mechanics of tumours , 2009, Biomechanics and modeling in mechanobiology.

[2]  H Rieger,et al.  Vascular remodelling of an arterio-venous blood vessel network during solid tumour growth. , 2009, Journal of theoretical biology.

[3]  John A Butman,et al.  Phase II trial of single-agent bevacizumab followed by bevacizumab plus irinotecan at tumor progression in recurrent glioblastoma. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[4]  T. Deisboeck,et al.  Simulating brain tumor heterogeneity with a multiscale agent-based model: Linking molecular signatures, phenotypes and expansion rate , 2006, Math. Comput. Model..

[5]  A. Friedman,et al.  Bevacizumab Plus Irinotecan in Recurrent WHO Grade 3 Malignant Gliomas , 2008, Clinical Cancer Research.

[6]  P. Kelly,et al.  Feasibility of using bevacizumab with radiation therapy and temozolomide in newly diagnosed high-grade glioma. , 2008, International journal of radiation oncology, biology, physics.

[7]  R. Solé,et al.  Cancer stem cells as the engine of unstable tumor progression. , 2008, Journal of theoretical biology.

[8]  H. Frieboes,et al.  Three-dimensional multispecies nonlinear tumor growth--I Model and numerical method. , 2008, Journal of theoretical biology.

[9]  Christos Davatzikos,et al.  An image-driven parameter estimation problem for a reaction–diffusion glioma growth model with mass effects , 2008, Journal of mathematical biology.

[10]  Nicola Bellomo,et al.  On the foundations of cancer modelling: Selected topics, speculations, and perspectives , 2008 .

[11]  A. Anderson,et al.  A hybrid cellular automaton model of clonal evolution in cancer: the emergence of the glycolytic phenotype. , 2008, Journal of theoretical biology.

[12]  H. Frieboes,et al.  Computer simulation of glioma growth and morphology , 2007, NeuroImage.

[13]  M. Berens,et al.  Autocrine factors that sustain glioma invasion and paracrine biology in the brain microenvironment. , 2007, Journal of the National Cancer Institute.

[14]  L. Chin,et al.  Malignant astrocytic glioma: genetics, biology, and paths to treatment. , 2007, Genes & development.

[15]  R. Weissleder,et al.  Visualizing the dynamics of EGFR activity and antiglioma therapies in vivo. , 2007, Cancer research.

[16]  A. Gregory Sorensen,et al.  Angiogenesis in brain tumours , 2007, Nature Reviews Neuroscience.

[17]  K. Rejniak An immersed boundary framework for modelling the growth of individual cells: an application to the early tumour development. , 2007, Journal of theoretical biology.

[18]  G Powathil,et al.  Mathematical modeling of brain tumors: effects of radiotherapy and chemotherapy , 2007, Physics in medicine and biology.

[19]  Yi Jiang,et al.  A cell-based model exhibiting branching and anastomosis during tumor-induced angiogenesis. , 2007, Biophysical journal.

[20]  J. Lowengrub,et al.  Nonlinear simulation of the effect of microenvironment on tumor growth. , 2007, Journal of theoretical biology.

[21]  G. F. Webb,et al.  An age and spatially structured model of tumor invasion with haptotaxis , 2007 .

[22]  Neil G Burnet,et al.  A mathematical model of the treatment and survival of patients with high-grade brain tumours. , 2007, Journal of theoretical biology.

[23]  P. Maini,et al.  Mathematical modeling of cell population dynamics in the colonic crypt and in colorectal cancer , 2007, Proceedings of the National Academy of Sciences.

[24]  Bruce T. Murray,et al.  Adaptive finite element methodology for tumour angiogenesis modelling , 2007 .

[25]  Kristin R. Swanson,et al.  The Evolution of Mathematical Modeling of Glioma Proliferation and Invasion , 2007, Journal of neuropathology and experimental neurology.

[26]  T. Deisboeck,et al.  Development of a three-dimensional multiscale agent-based tumor model: simulating gene-protein interaction profiles, cell phenotypes and multicellular patterns in brain cancer. , 2006, Journal of theoretical biology.

[27]  Michael Berens,et al.  A mathematical model of glioblastoma tumor spheroid invasion in a three-dimensional in vitro experiment. , 2007, Biophysical journal.

[28]  Tracy T Batchelor,et al.  AZD2171, a pan-VEGF receptor tyrosine kinase inhibitor, normalizes tumor vasculature and alleviates edema in glioblastoma patients. , 2007, Cancer cell.

[29]  M. Dragunow,et al.  The mitogen-activated/extracellular signal-regulated kinase kinase 1/2 inhibitor U0126 induces glial fibrillary acidic protein expression and reduces the proliferation and migration of C6 glioma cells , 2006, Neuroscience.

[30]  B Ribba,et al.  A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents. , 2006, Journal of theoretical biology.

[31]  Salvatore Torquato,et al.  Modeling the effects of vasculature evolution on early brain tumor growth. , 2006, Journal of theoretical biology.

[32]  Alissa M. Weaver,et al.  Tumor Morphology and Phenotypic Evolution Driven by Selective Pressure from the Microenvironment , 2006, Cell.

[33]  P. Wen,et al.  Glioma Therapy in Adults , 2006, The neurologist.

[34]  I. Jonassen,et al.  Angiogenesis-independent tumor growth mediated by stem-like cancer cells , 2006, Proceedings of the National Academy of Sciences.

[35]  F. Michor,et al.  Mathematical models of targeted cancer therapy , 2006, British Journal of Cancer.

[36]  C. Rhee,et al.  Ionizing radiation enhances matrix metalloproteinase-2 secretion and invasion of glioma cells through Src/epidermal growth factor receptor-mediated p38/Akt and phosphatidylinositol 3-kinase/Akt signaling pathways. , 2006, Cancer research.

[37]  S. McDougall,et al.  Mathematical modelling of dynamic adaptive tumour-induced angiogenesis: clinical implications and therapeutic targeting strategies. , 2006, Journal of theoretical biology.

[38]  F. M. Gabhann,et al.  Computational Model of Vascular Endothelial Growth Factor Spatial Distribution in Muscle and Pro-Angiogenic Cell Therapy , 2006, PLoS Comput. Biol..

[39]  K. Boushaba,et al.  A Mathematical Model for the Regulation of Tumor Dormancy Based on Enzyme Kinetics , 2006, Bulletin of mathematical biology.

[40]  S. McDougall,et al.  Mathematical modeling of tumor-induced angiogenesis. , 2006, Annual review of biomedical engineering.

[41]  B. Grammaticos,et al.  A cellular automaton model for the migration of glioma cells , 2006, Physical biology.

[42]  Helen M. Byrne,et al.  Modelling the response of spatially structured tumours to chemotherapy: Drug kinetics , 2006, Math. Comput. Model..

[43]  H. Frieboes,et al.  An integrated computational/experimental model of tumor invasion. , 2006, Cancer research.

[44]  David N Louis,et al.  Molecular pathology of malignant gliomas. , 2006, Annual review of pathology.

[45]  H Rieger,et al.  Vascular network remodeling via vessel cooption, regression and growth in tumors. , 2005, Journal of theoretical biology.

[46]  Alexander R. A. Anderson,et al.  Computational Methods and Results for Structured Multiscale Models of Tumor Invasion , 2005, Multiscale Model. Simul..

[47]  Thomas S Deisboeck,et al.  The effects of EGF-receptor density on multiscale tumor growth patterns. , 2005, Journal of theoretical biology.

[48]  A. Armaou,et al.  Multiscale optimization using hybrid PDE/kMC process systems with application to thin film growth , 2005 .

[49]  Jelena Pjesivac-Grbovic,et al.  A multiscale model for avascular tumor growth. , 2005, Biophysical journal.

[50]  C. Schaller,et al.  MATHEMATICAL MODELLING OF GLIOBLASTOMA TUMOUR DEVELOPMENT: A REVIEW , 2005 .

[51]  Leonard M. Sander,et al.  A model for glioma growth , 2005, Complex..

[52]  J. K. Smith,et al.  Vessel tortuosity and brain tumor malignancy: a blinded study. , 2005, Academic radiology.

[53]  Chi-Hwa Wang,et al.  Transient interstitial fluid flow in brain tumors: Effect on drug delivery , 2005 .

[54]  C. Please,et al.  A mathematical model of dynamic glioma-host interactions: receptor-mediated invasion and local proteolysis. , 2005, Mathematical medicine and biology : a journal of the IMA.

[55]  R. Heinrich,et al.  Control of MAPK signalling: from complexity to what really matters , 2005, Oncogene.

[56]  Mitsutoshi Nakada,et al.  EphB2/R-Ras signaling regulates glioma cell adhesion, growth, and invasion. , 2005, The American journal of pathology.

[57]  Dominik Wodarz,et al.  Drug resistance in cancer: principles of emergence and prevention. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[58]  Martin J. van den Bent,et al.  Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. , 2005, The New England journal of medicine.

[59]  V. Cristini,et al.  Nonlinear simulation of tumor necrosis, neo-vascularization and tissue invasion via an adaptive finite-element/level-set method , 2005, Bulletin of mathematical biology.

[60]  K. Jellinger,et al.  Glioblastoma multiforme: Morphology and biology , 2005, Acta Neurochirurgica.

[61]  Helen M. Byrne,et al.  A Multiple Scale Model for Tumor Growth , 2005, Multiscale Model. Simul..

[62]  Lei Xu,et al.  Kinetics of vascular normalization by VEGFR2 blockade governs brain tumor response to radiation: role of oxygenation, angiopoietin-1, and matrix metalloproteinases. , 2004, Cancer cell.

[63]  D L S McElwain,et al.  A history of the study of solid tumour growth: The contribution of mathematical modelling , 2004, Bulletin of mathematical biology.

[64]  M. Plank,et al.  A mathematical model of tumour angiogenesis, regulated by vascular endothelial growth factor and the angiopoietins. , 2004, Journal of theoretical biology.

[65]  R. Kodet,et al.  Extracellular matrix glycoproteins and diffusion barriers in human astrocytic tumours , 2004, Neuropathology and applied neurobiology.

[66]  U. Bhalla Models of cell signaling pathways. , 2004, Current opinion in genetics & development.

[67]  R. Christopher,et al.  Data‐Driven Computer Simulation of Human Cancer Cell , 2004, Annals of the New York Academy of Sciences.

[68]  H. Othmer,et al.  Mathematical modeling of tumor-induced angiogenesis , 2004, Journal of mathematical biology.

[69]  D. Lauffenburger,et al.  Self-organization of polarized cell signaling via autocrine circuits: computational model analysis. , 2004, Biophysical journal.

[70]  D. Sauner,et al.  Migratory activity of human glioma cell lines in vitro assessed by continuous single cell observation , 2004, Clinical & Experimental Metastasis.

[71]  J. Murray,et al.  Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion , 2003, Journal of the Neurological Sciences.

[72]  D. Kirschner,et al.  A mathematical model of tumor-immune evasion and siRNA treatment , 2003 .

[73]  Thomas S Deisboeck,et al.  The impact of "search precision" in an agent-based tumor model. , 2003, Journal of theoretical biology.

[74]  Tadashi Nagayama,et al.  Microvasculature of the human cerebral white matter: Arteries of the deep white matter , 2003, Neuropathology : official journal of the Japanese Society of Neuropathology.

[75]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[76]  K. Hoang-Xuan,et al.  Primary brain tumours in adults , 2003, The Lancet.

[77]  Daniel Tee,et al.  Simulation of tumor-induced angiogenesis and its response to anti-angiogenic drug treatment: mode of drug delivery and clearance rate dependencies , 2003, Journal of Cancer Research and Clinical Oncology.

[78]  L. Sander,et al.  Growth patterns of microscopic brain tumors. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[79]  J. Murray,et al.  Quantifying Efficacy of Chemotherapy of Brain Tumors with Homogeneous and Heterogeneous Drug Delivery , 2002, Acta biotheoretica.

[80]  V. Keshamouni,et al.  Temporal and quantitative regulation of mitogen-activated protein kinase (MAPK) modulates cell motility and invasion , 2001, Oncogene.

[81]  B. Sleeman,et al.  Mathematical modeling of capillary formation and development in tumor angiogenesis: Penetration into the stroma , 2001, Bulletin of mathematical biology.

[82]  B. Kholodenko,et al.  Negative feedback and ultrasensitivity can bring about oscillations in the mitogen-activated protein kinase cascades. , 2000, European journal of biochemistry.

[83]  A. Czirók,et al.  Locomotion and proliferation of glioblastoma cells in vitro: statistical evaluation of videomicroscopic observations. , 1999, Journal of neurosurgery.

[84]  N. Britton,et al.  Stochastic simulation of benign avascular tumour growth using the Potts model , 1999 .

[85]  A. Hudetz,et al.  Mathematical model of oxygen transport in the cerebral cortex , 1999, Brain Research.

[86]  M. Chaplain,et al.  Continuous and discrete mathematical models of tumor-induced angiogenesis , 1998, Bulletin of mathematical biology.

[87]  Stephen B. Pope,et al.  Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation , 1997 .

[88]  S. Coons,et al.  Dichotomy of astrocytoma migration and proliferation , 1996, International journal of cancer.

[89]  J P Freyer,et al.  In situ oxygen consumption rates of cells in V‐79 multicellular spheroids during growth , 1984, Journal of cellular physiology.