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Stochastic stem cell models with mutation: A comparison of asymmetric and symmetric divisions
Zhijie Wu1, Yuman Wang1, Kun Wang1
1School of Mathematical Sciences, Xiamen University, Xiamen 361005, PR China.
Abstract:
In order to fulfill cell proliferation and differentiation through cellular hierarchy, stem cells can undergo either asymmetric or symmetric divisions. Recent studies pay special attention to the effect of different modes of stem cell division on the lifetime risk of cancer, and report that symmetric division is more beneficial to delay the onset of cancer. The fate uncertainty of symmetric division is considered to be the reason for the cancer-delaying effect. In this paper we compare asymmetric and symmetric divisions of stem cells via studying stochastic stem cell models with mutation. Specially, by using rigorous mathematical analysis we find that both the asymmetric and symmetric models show the same statistical average, but the symmetric model shows higher fluctuation than the asymmetric model. We further show that the difference between the two models would be more remarkable for lower mutation rates. Our work quantifies the uncertainty of cell division and highlights the significance of stochasticity for distinguishing between different modes of stem cell division.
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