The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
A single-cell-based model of tumor growth in vitro: monolayers and spheroids
Open accessAbstract
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 in vitro experiments. Within our model each cell is represented as an individual object and parametrized by cell-biophysical and cell-kinetic parameters that can all be experimentally determined. Hence our modeling strategy allows us 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 at 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.
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Cites
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Nonlinear modelling of cancer: bridging the gap between cells and tumours
Lowengrub, J. S., Frieboes, H. B., Jin, F., Chuang, Y.-L., Li, X., Macklin, P., Wise, S. M., & Cristini, V (2010) · Nonlinearity · doi:10.1088/0951-7715/23/1/r01 · Cited by 553
A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity
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A Review of Cell-Based Computational Modeling in Cancer Biology
Metzcar, J., Wang, Y., Heiland, R., & Macklin, P. (2019) · JCO Clinical Cancer Informatics · doi:10.1200/cci.18.00069 · Cited by 386
A continuum approach to modelling cell–cell adhesion
Armstrong, N. J., Painter, K. J., & Sherratt, J. A. (2006) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2006.05.030 · Cited by 355
Computational models for active matter
Shaebani, M. R., Wysocki, A., Winkler, R. G., Gompper, G., & Rieger, H. (2020) · Nature Reviews Physics · doi:10.1038/s42254-020-0152-1 · Cited by 355
Metadata
- Authors
- Drasdo, D., & Höhme, S.
- Venue
- Physical Biology
- Publisher
- IOP Publishing
- Published
- 2005-07-12
- Volume
- 2
- Issue
- 3
- Pages
- 133-147
- ISSN
- 1478-3967 (ISSN-L)
- 1478-3975
- OpenAlex
- W1996269383
- Cited by
- 421
- References
- 8
- FWCI
- 15.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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