Abstract
Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.
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Anderson AR, Weaver AM, Cummings PT, Quaranta V (2006) Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment. Cell 127: 905–915
Swanson KR, Alvord EC Jr, Murray JD (2000) A quantitative model for differential motility of gliomas in grey and white matter. Cell Prolif 33: 317–329
Swanson KR, Alvord EC Jr, Murray JD (2002) Virtual brain tumours (gliomas) enhance the reality of medical imaging and highlight inadequacies of current therapy. Br J Cancer 86: 14–18
Swanson KR, Alvord EC Jr, Murray JD (2002) Quantifying efficacy of chemotherapy of brain tumors with homogeneous and heterogeneous drug delivery. Acta Biotheor 50: 223–237
Swanson KR, Bridge C, Murray JD, Alvord EC Jr (2003) Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion. J Neurol Sci 216: 1–10
Araujo RP, Petricoin EF, Liotta LA (2005) A mathematical model of combination therapy using the EGFR signaling network. Biosystems 80: 57–69
Armstrong NJ, Painter KJ, Sherratt JA (2006) A continuum approach to modelling cell–cell adhesion. J Theor Biol 243: 98–113
Zhang L, Dai W, Nassar R (2005) A numerical method for optimizing laser power in the irradiation of a 3D triple layered cylindrical skin structure. Numer Heat Tr A 48: 21–41
Zhang L, Dai W, Nassar R (2006) A numerical method for obtaining an optimal temperature distribution in a 3D triple-layered cylindrical skin structure embedded with a blood vessel. Numer Heat Tr A 49: 765–784
Chaplain M, Lolas G (2005) Mathematical modelling of cancer cell invasion of tissue: The role of the urokinase plasminogen activation system. Math Modell Methods Appl Sci 15: 1685–1734
Wolfram S (1994) Cellular automata and complexity: collected papers. Addison-Wesley, Reading, MA
Mansury Y, Deisboeck TS (2003) The impact of “search precision” in an agent-based tumor model. J Theor Biol 224: 325–337
Mansury Y, Deisboeck TS (2004) Simulating ‘structure-function’ patterns of malignant brain tumors. Physica A 331: 219–232
Mansury Y, Deisboeck TS (2004) Simulating the time series of a selected gene expression profile in an agent-based tumor model. Physica D 196: 193–204
Schofield P, Chaplain M, Hubbard S (2005) Evolution of searching and life history characteristics in individual-based models of host-parasitoid-microbe associations. J Theor Biol 237: 1–16
Orme ME, Chaplain MA (1997) Two-dimensional models of tumour angiogenesis and anti-angiogenesis strategies. IMA J Math Appl Med Biol 14: 189–205
Byrne HM, Alarcon T, Owen MR, Webb SD, Maini PK (2006) Modelling aspects of cancer dynamics: a review. Philos Transact A Math Phys Eng Sci 364: 1563–1578
Kansal AR, Torquato S, Harsh IG, Chiocca EA, Deisboeck TS (2000) Cellular automaton of idealized brain tumor growth dynamics. Biosystems 55: 119–127
Anderson AR, Chaplain MA (1998) Continuous and discrete mathematical models of tumor-induced angiogenesis. Bull Math Biol 60: 857–899
Anderson AR, Chaplain M, NewMan EL, Stelle RJC, Thompson AM (2000) Mathematical modelling of tumor invasion and metastasis. J Theor Med 2: 129–154
Athale C, Mansury Y, Deisboeck TS (2005) Simulating the impact of a molecular ‘decision-process’ on cellular phenotype and multicellular patterns in brain tumors. J Theor Biol 233: 469–481
Athale CA, Deisboeck TS (2006) The effects of EGF-receptor density on multiscale tumor growth patterns. J Theor Biol 238: 771–779
Zhang L, Athale CA, Deisboeck TS (2007) Development of a three-dimensional multiscale agent-based tumor model: simulating gene–protein interaction profiles, cell phenotypes and multicellular patterns in brain cancer. J Theor Biol 244: 96–107
Sanga S, Sinek JP, Frieboes HB, Ferrari M, Fruehauf JP, Cristini V (2006) Mathematical modeling of cancer progression and response to chemotherapy. Expert Rev Anticancer Ther 6: 1361–1376
Davidsson P (2002) Agent based social simulation: a computer science view. JASSS 5
Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci USA 99(Suppl 3): 7280–7287
Moreira N (2006) In pixels and in health: computer modeling pushes the threshold of medical research. Sci News 169: 40–41
Peirce SM, Van Gieson EJ, Skalak TC (2004) Multicellular simulation predicts microvascular patterning and in silico tissue assembly. FASEB J 18: 731–733
Kirschner D, Panetta JC (1998) Modeling immunotherapy of the tumor–immune interaction. J Math Biol 37: 235–252
Perrin D, Ruskin HJ, Crane M (2006) An agent-based approach to immune modelling: priming individual response. Trans Eng Comput Technol 17: 80–86
Segovia-Juarez JL, Ganguli S, Kirschner D (2004) Identifying control mechanisms of granuloma formation during M. tuberculosis infection using an agent-based model. J Theor Biol 231: 357–376
An G (2001) Agent-based computer simulation and sirs: building a bridge between basic science and clinical trials. Shock 16: 266–273
An G (2004) In silico experiments of existing and hypothetical cytokine-directed clinical trials using agent-based modeling. Crit Care Med 32: 2050–2060
Mansury Y, Kimura M, Lobo J, Deisboeck TS (2002) Emerging patterns in tumor systems: simulating the dynamics of multicellular clusters with an agent-based spatial agglomeration model. J Theor Biol 219: 343–370
Wodarz D, Komarova NL (2005) Computational biology of cancer. World Scientific Publishing Company, Singapore
Schaller G, Meyer-Hermann M (2005) Multicellular tumor spheroid in an off-lattice Voronoi-Delaunay cell model. Phys Rev E Stat Nonlin Soft Matter Phys 71: 051910
Engelberg J, Ganguli S, Hunt CA (2006) Agent-based simulations of in vitro multicellular tumor spheroid growth. In: Proceedings of the agent-directed simulation symposium, pp 141–48
Zhu JJ, Coakley S, Holcombe M, MacNeil S, Smallwood RH (2006) Individual cell-based simulation of 3D multicellular spheroid self-assembly. Eur Cells Mater 11(Suppl 3): 31
Spencer SL, Gerety RA, Pienta KJ, Forrest S (2006) Modeling somatic evolution in tumorigenesis. PLoS Comput Biol 2: e108
Buldyrev SV, Goldberger AL, Havlin S, Peng CK, Stanley HE, Stanley MH, Simons M (1993) Fractal landscapes and molecular evolution: modeling the myosin heavy chain gene family. Biophys J 65: 2673–2679
Hausdorff JM, Peng CK, Ladin Z, Wei JY, Goldberger AL (1995) Is walking a random walk? Evidence for long-range correlations in stride interval of human gait. J Appl Physiol 78: 349–358
Ossadnik SM, Buldyrev SV, Goldberger AL, Havlin S, Mantegna RN, Peng CK, Simons M, Stanley HE (1994) Correlation approach to identify coding regions in DNA sequences. Biophys J 67: 64–70
Peng CK, Buldyrev SV, Havlin S, Simons M, Stanley HE, Goldberger AL (1994) Mosaic organization of DNA nucleotides. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics 49: 1685–1689
Peng CK, Havlin S, Stanley HE, Goldberger AL (1995) Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos 5: 82–87
Barabasi AL, Stanley HE (1995) Fractal concepts in surface growth. Cambridge University Press, Cambridge
Giese A, Loo MA, Tran N, Haskett D, Coons SW, Berens ME (1996) Dichotomy of astrocytoma migration and proliferation. Int J Cancer 67: 275–282
Lund-Johansen M, Bjerkvig R, Humphrey PA, Bigner SH, Bigner DD, Laerum OD (1990) Effect of epidermal growth factor on glioma cell growth, migration, and invasion in vitro. Cancer Res 50: 6039–6044
Lund-Johansen M, Forsberg K, Bjerkvig R, Laerum OD (1992) Effects of growth factors on a human glioma cell line during invasion into rat brain aggregates in culture. Acta Neuropathol 84: 190–197
Schlegel J, Merdes A, Stumm G, Albert FK, Forsting M, Hynes N, Kiessling M (1994) Amplification of the epidermal-growth-factor-receptor gene correlates with different growth behaviour in human glioblastoma. Int J Cancer 56: 72–77
Westermark B, Magnusson A, Heldin CH (1982) Effect of epidermal growth factor on membrane motility and cell locomotion in cultures of human clonal glioma cells. J Neurosci Res 8: 491–507
Alarcon T, Byrne HM, Maini PK (2004) A mathematical model of the effects of hypoxia on the cell-cycle of normal and cancer cells. J Theor Biol 229: 395–411
Zhang L, Wang Z, Sagotsky JA, Deisboeck TS (2008) Simulating brain tumor heterogeneity with a multiscale agent-based model: linking molecular signatures, phenotypes and expansion rate. Math Comput Model. doi:10.1016/j.mcm.2008.05.011
Kleihues P, Ohgaki H (1999) Primary and secondary glioblastomas: from concept to clinical diagnosis. Neuro Oncol 1: 44–51
Lang FF, Miller DC, Koslow M, Newcomb EW (1994) Pathways leading to glioblastoma multiforme: a molecular analysis of genetic alterations in 65 astrocytic tumors. J Neurosurg 81: 427–436
Ohgaki H, Dessen P, Jourde B, Horstmann S, Nishikawa T, Di Patre PL, Burkhard C, Schuler D, Probst-Hensch NM, Maiorka PC, Baeza N, Pisani P, Yonekawa Y, Yasargil MG, Lutolf UM, Kleihues P (2004) Genetic pathways to glioblastoma: a population-based study. Cancer Res 64: 6892–6899
Bankes SC (2002) Agent-based modeling: a revolution. Proc Natl Acad Sci USA 99(Suppl 3): 7199–7200
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Zhang, L., Wang, Z., Sagotsky, J. et al. Multiscale agent-based cancer modeling. J. Math. Biol. 58, 545–559 (2009). https://doi.org/10.1007/s00285-008-0211-1
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DOI: https://doi.org/10.1007/s00285-008-0211-1