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Updated: Jan 30, 2026

Isolation of CD133+ Liver Stem Cells for Clonal Expansion
Published on: October 10, 2011
QUANTITATIVE ANALYSIS OF THE POTENTIAL ROLE OF BASAL CELL HYPERPLASIA IN THE RELATIONSHIP BETWEEN CLONAL EXPANSION
Emese J Drozsdik1,2, Balázs G Madas2
1Department of Biological Physics, Doctoral School of Physics, ELTE Eötvös Loránd University, Budapest, Hungary.
Abstract:
Applying the two-stage clonal expansion model to epidemiology of lung cancer among uranium miners, it has been revealed that radon acts as a promoting agent facilitating the clonal expansion of already mutated cells. Clonal expansion rate increases non-linearly by radon concentration showing a plateau above a given exposure rate. The underlying mechanisms remain unclear. Earlier we proposed that progenitor cell hyperplasia may be induced upon chronic radon exposure. The objective of the present study is to test whether the induction of hyperplasia may provide a quantitative explanation for the plateau in clonal expansion rate. For this purpose, computational epithelium models were prepared with different number of basal cells. Cell nucleus hits were computed by an own-developed Monte-Carlo code. Surviving fractions were estimated based on the number of cell nucleus hits. Cell division rate was computed supposing equilibrium between cell death and cell division. It was also supposed that clonal expansion rate is proportional to cell division rate, and therefore the relative increase in cell division rate and clonal expansion rate are the same functions of exposure rate. While the simulation results highly depend on model parameters with high uncertainty, a parameter set has been found resulting in a cell division rate-exposure rate relationship corresponding to the plateau in clonal expansion rate. Due to the high uncertainty of the applied parameters, however, further studies are required to decide whether the induction of hyperplasia is responsible for the non-linear increase in clonal expansion rate or not. Nevertheless, the present study exemplifies how computational modelling can contribute to the integration of observational and experimental radiation protection research.
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