A mathematical model of glioblastoma tumor spheroid invasion in a three-dimensional in vitro experiment.

Glioblastoma, the most malignant form of brain cancer, is responsible for 23% of primary brain tumors and has extremely poor outcome. Confounding the clinical management of glioblastomas is the extreme local invasiveness of these cancer cells. The mechanisms that govern invasion are poorly understood. To gain insight into glioblastoma invasion, we conducted experiments on the patterns of growth and dispersion of U87 glioblastoma tumor spheroids in a three-dimensional collagen gel. We studied two different cell lines, one with a mutation to the EGFR (U87DeltaEGFR) that is associated with increased malignancy, and one with an endogenous (wild-type) receptor (U87WT). We developed a continuum mathematical model of the dispersion behaviors with the aim of identifying and characterizing discrete cellular mechanisms underlying invasive cell motility. The mathematical model quantitatively reproduces the experimental data, and indicates that the U87WT invasive cells have a stronger directional motility bias away from the spheroid center as well as a faster rate of cell shedding compared to the U87DeltaEGFR cells. The model suggests that differences in tumor cell dispersion may be due to differences in the chemical factors produced by cells, differences in how the two cell lines remodel the gel, or different cell-cell adhesion characteristics.

[1]  M. Westphal,et al.  Cost of migration: invasion of malignant gliomas and implications for treatment. , 2003, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[2]  M. Chaplain,et al.  Modelling the role of cell-cell adhesion in the growth and development of carcinomas , 1996 .

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

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

[5]  T. Deisboeck,et al.  Complex dynamics of tumors: modeling an emerging brain tumor system with coupled reaction–diffusion equations , 2003 .

[6]  S Torquato,et al.  Simulated brain tumor growth dynamics using a three-dimensional cellular automaton. , 2000, Journal of theoretical biology.

[7]  Conan K. N. Li The glucose distribution in 9l rat brain multicell tumor spheroids and its effect on cell necrosis , 1982, Cancer.

[8]  L. Sander,et al.  Dynamics and pattern formation in invasive tumor growth. , 2005, Physical review letters.

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

[10]  J. Sherratt,et al.  Intercellular adhesion and cancer invasion: a discrete simulation using the extended Potts model. , 2002, Journal of theoretical biology.

[11]  Stuart K. Williams,et al.  Migration of individual microvessel endothelial cells: stochastic model and parameter measurement. , 1991, Journal of cell science.

[12]  W. Cavenee,et al.  A mutant epidermal growth factor receptor common in human glioma confers enhanced tumorigenicity. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[13]  R. Nicholson,et al.  EGFR and cancer prognosis. , 2001, European journal of cancer.

[14]  R. Bjerkvig,et al.  Evidence for a secreted chemorepellent that directs glioma cell invasion. , 2004, Journal of neurobiology.

[15]  A Guha,et al.  Expression of activated epidermal growth factor receptors, Ras-guanosine triphosphate, and mitogen-activated protein kinase in human glioblastoma multiforme specimens. , 1999, Neurosurgery.

[16]  S. Torquato,et al.  Pattern of self‐organization in tumour systems: complex growth dynamics in a novel brain tumour spheroid model , 2001, Cell proliferation.

[17]  I. Whittle,et al.  The development of necrosis and apoptosis in glioma: experimental findings using spheroid culture systems* , 2001, Neuropathology and applied neurobiology.

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

[19]  M. Westphal,et al.  Glioblastoma and Cerebral Microvascular Endothelial Cell Migration in Response to Tumor-associated Growth Factors , 2003, Neurosurgery.

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

[21]  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.

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

[23]  Tanja Woyke,et al.  Gene expression profile of glioblastoma multiforme invasive phenotype points to new therapeutic targets. , 2005, Neoplasia.

[24]  José C. M. Mombach,et al.  The interplay between cell adhesion and environment rigidity in the morphology of tumors , 2003 .

[25]  D. Silbergeld,et al.  Assessment of brain tumor cell motility in vivo and in vitro. , 1995, Journal of neurosurgery.

[26]  Kenneth M. Yamada,et al.  Taking Cell-Matrix Adhesions to the Third Dimension , 2001, Science.

[27]  Michael E. Berens,et al.  Molecular Mechanisms of Glioma Cell Migration and Invasion , 2004, Journal of Neuro-Oncology.

[28]  Z Bajzer,et al.  Analysis of growth of multicellular tumour spheroids by mathematical models , 1994, Cell proliferation.

[29]  M. L. Martins,et al.  Reaction-diffusion model for the growth of avascular tumor. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

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

[32]  J P Freyer,et al.  Shedding of mitotic cells from the surface of multicell spheroids during growth , 1981, Journal of cellular physiology.

[33]  G. Riggins,et al.  Mutant epidermal growth factor receptor up-regulates molecular effectors of tumor invasion. , 2002, Cancer research.

[34]  Mauro Ferrari,et al.  Morphologic Instability and Cancer Invasion , 2005, Clinical Cancer Research.

[35]  K. Aldape,et al.  Contrasting in vivo and in vitro fates of glioblastoma cell subpopulations with amplified EGFR , 2004, Genes, chromosomes & cancer.

[36]  H. Wiley,et al.  The Enhanced Tumorigenic Activity of a Mutant Epidermal Growth Factor Receptor Common in Human Cancers Is Mediated by Threshold Levels of Constitutive Tyrosine Phosphorylation and Unattenuated Signaling* , 1997, The Journal of Biological Chemistry.

[37]  A. Czirók,et al.  Irradiation and Taxol Treatment Result in Non-Monotonous, Dose-Dependent Changes in the Motility of Glioblastoma Cells , 2004, Journal of Neuro-Oncology.

[38]  D. Grier,et al.  Methods of Digital Video Microscopy for Colloidal Studies , 1996 .

[39]  A. Bhushan,et al.  Inhibition of epidermal growth factor receptor-associated tyrosine kinase blocks glioblastoma invasion of the brain. , 1997, Neurosurgery.

[40]  D. Lauffenburger,et al.  Quantitative relationships between single-cell and cell-population model parameters for chemosensory migration responses of alveolar macrophages to C5a. , 1990, Cell Motility and the Cytoskeleton.

[41]  O. Bogler,et al.  A common mutant epidermal growth factor receptor confers enhanced tumorigenicity on human glioblastoma cells by increasing proliferation and reducing apoptosis. , 1996, Cancer research.

[42]  W. Cavenee,et al.  Aberrant receptor signaling in human malignant gliomas: mechanisms and therapeutic implications. , 2001, Cancer Letters.