Emerging Patterns in Tumor Systems: Simulating the Dynamics of Multicellular Clusters with an Agent-based Spatial Agglomeration Model

Mansury, Yuri; Kimura, Mark; Lobo, José; Deisboeck, Thomas S.

doi:10.1006/jtbi.2002.3131

Cited by 116 publications

(95 citation statements)

References 46 publications

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“…In line with earlier studies, our model shows that increased migration drives the tumour progression (Betteridge et al, 2006), but in contrast to another model attributing similar results to patterned environments (Mansury et al, 2002), our study shows that complex dynamics and spatial agglomeration of tumour clusters can occur even when the environment is homogeneous and migration undirected. Although clusters can arise from gradated environments, this dependence should not be taken as absolute.…”

Section: Discussionsupporting

confidence: 92%

“…The authors reported that with increasing tumour carrying capacity because of increased vasculature, significant cell movement increases the rate of tumour growth and invasion. In another study, an agent-based approach was used to study emerging patterns in tumour systems (Mansury et al, 2002). In this model, heterogeneous nutrient concentrations and directed cell migration towards nutrient attractors were determined to be necessary for cluster formation.…”

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confidence: 99%

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Migration rules: tumours are conglomerates of self-metastases

2009

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Tumours are heterogeneous populations composed of different cells types: stem cells with the capacity for self-renewal and more differentiated cells lacking such ability. The overall growth behaviour of a developing neoplasm is determined largely by the combined kinetic interactions of these cells. By tracking the fate of individual cancer cells using agent-based methods in silico, we apply basic rules for cell proliferation, migration and cell death to show how these kinetic parameters interact to control, and perhaps dictate defining spatial and temporal tumour growth dynamics in tumour development. When the migration rate is small, a single cancer stem cell can only generate a small, self-limited clone because of the finite life span of progeny and spatial constraints. By contrast, a high migration rate can break this equilibrium, seeding new clones at sites outside the expanse of older clones. In this manner, the tumour continually 'self-metastasises'. Counterintuitively, when the proliferation capacity is low and the rate of cell death is high, tumour growth is accelerated because of the freeing up of space for self-metastatic expansion. Changes to proliferation and cell death that increase the rate at which cells migrate benefit tumour growth as a whole. The dominating influence of migration on tumour growth leads to unexpected dependencies of tumour growth on proliferation capacity and cell death. These dependencies stand to inform standard therapeutic approaches, which anticipate a positive response to cell killing and mitotic arrest.

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Section: Discussionsupporting

confidence: 92%

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confidence: 99%

Migration rules: tumours are conglomerates of self-metastases

2009

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“…Because a 1 mm tumor spheroid has over 500,000 cells, these methods can quickly become unwieldy when studying tumors of any significant size. For some examples of cellular automata modeling, see Anderson (2005), Alarcón et al (2003), and Mallett and de Pillis (2006), and see Mansury et al (2002) and Abbott et al (2006) for examples of agentbased modeling.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear simulation of the effect of microenvironment on tumor growth

Macklin

Lowengrub

2007

Journal of Theoretical Biology

176

190

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In this paper, we present and investigate a model for solid tumor growth that incorporates features of the tumor microenvironment. Using analysis and nonlinear numerical simulations, we explore the effects of the interaction between the genetic characteristics of the tumor and the tumor microenvironment on the resulting tumor progression and morphology. We find that the range of morphological responses can be placed in three categories that depend primarily upon the tumor microenvironment: tissue invasion via fragmentation due to a hypoxic microenvironment; fingering, invasive growth into nutrient-rich, biomechanically unresponsive tissue; and compact growth into nutrient-rich, biomechanically responsive tissue. We found that the qualitative behavior of the tumor morphologies was similar across a broad range of parameters that govern the tumor genetic characteristics. Our findings demonstrate the importance of the impact of microenvironment on tumor growth and morphology and have important implications for cancer therapy. In particular, if a treatment impairs nutrient transport in the external tissue (e.g., by anti-angiogenic therapy), increased tumor fragmentation may result, and therapy-induced changes to the biomechanical properties of the tumor or the microenvironment (e.g., antiinvasion therapy) may push the tumor in or out of the invasive fingering regime.

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“…Because a 1-mm tumor spheroid may have several hundred thousand cells, these methods could become unwieldy when studying tumors of any significant size. See [10,4,138] for examples of cellular automata modeling, and [139,1] for examples of agent-based modeling. In larger-scale systems where the cancer cell population is on the order of 1,000,000 or more, continuum methods may provide a more suitable modeling technique.…”

Section: Introductionmentioning

confidence: 99%