Abstract
Background
Several possible scenarios of cellular dynamics in human colonic crypts have been inferred from transgenic animal experiments. However, because of the discrepancy in size and physiology between humans and animals, quantitative predictions of tissue renewal and cancer development are difficult to execute.
Methods
A two-dimensional individual based model was developed for the first time to predict cellular dynamics in human colonic crypts. A simple scenario, in which stem cells were not fixed positionally, divide symmetrically and asymmetrically in a stochastic fashion in the lower part of the crypt, was proposed and implemented in the developed model. Numerical simulations of the model were executed in silico.
Results
By comparing the results of computational simulations with available experimental data, the presented scenario was consistent with various experimental evidence. Using this scenario, we simulated and visualized monoclonal conversion in the human colonic crypt. We also predicted that the propensity for monoclonal expansion of a mutant cell was largely dependent on the phenotype, the cell type, the position and the state of the crypt.
Conclusions
Using the computational framework developed in this study, model users can verify possible scenarios of stem cell dynamics occurring in human colonic crypts and quantitatively predict cell behavior. Its applicability in scenario verification and predictability makes it a valuable tool for elucidation of stem cell dynamics in human colonic crypts.
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Acknowledgments
We thank Takamasa Murano for his assistance with executing the simulation. This study is a part of the outcome of research performed under a Waseda University Grant for Special Research Projects (Project number: 2009B-212). We are also grateful for the helpful suggestions of three reviewers which greatly improved the manuscript.
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The authors declare that they have no conflict of interest.
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Kagawa, Y., Horita, N., Taniguchi, H. et al. Modeling of stem cell dynamics in human colonic crypts in silico. J Gastroenterol 49, 263–269 (2014). https://doi.org/10.1007/s00535-013-0887-x
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DOI: https://doi.org/10.1007/s00535-013-0887-x