

Preprint 58/2005
A single cell based-model of tumor growth in-vitro: monolayers and speroids
Dirk Drasdo and Stefan Höhme
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Submission date: 15. Jun. 2005
Pages: 41
published in: Physical biology, 2 (2005) 3, p. 133-147
DOI number (of the published article): 10.1088/1478-3975/2/3/001
Bibtex
PACS-Numbers: 87.18.-h, 87.
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Abstract:
To what extent the growth dynamics of tumors is controlled by nutrients, biomechanical forces, and other factors at different stages and in different environments is still largely unknown. Here we present a biophysical model to study the spatio-temporal growth dynamics of two-dimensional tumor monolayers and three-dimensional tumor spheroids as a complementary tool to it in-vitro experiments. Within our model each cell is represented as an individual object and parameterized by cell-biophysical and cell-kinetic parameters that can all be experimentally determined. Hence our modeling strategy allows to study which mechanisms on the microscopic level of individual cells may affect the macroscopic properties of a growing tumor. We find the qualitative growth kinetics and patterns in early growth stages to be remarkably robust. Quantitative comparisons between computer simulations using our model and published experimental observations on monolayer cultures suggest a biomechanically-mediated form of growth inhibition during the experimentally observed transition from exponential to sub-exponential growth at sufficiently large tumor sizes. Our simulations show that the same transition during the growth of avascular tumor spheroids can be explained largely by the same mechanism. Glucose (or oxygen) depletion seems to determine mainly the size of the necrotic core but not the size of the tumor. We explore the consequences of the suggested biomechanical form of contact inhibition, in order to permit an experimental test of our model. Based on our findings we propose a phenomenological growth law in early expansion phases in which specific biological small-scale processes are subsumed in a small number of effective parameters.