论文标题

表型异构生长细胞种群的基于个体和连续模型

Individual-based and continuum models of phenotypically heterogeneous growing cell populations

论文作者

Macfarlane, Fiona R, Ruan, Xinran, Lorenzi, Tommaso

论文摘要

现有的研究比较了基于个体的细胞群体及其连续性对应物的基于个体的模型,主要集中在均匀种群上,其中所有细胞都具有相同的表型特征。但是,在细胞系统中通常观察到明显的细胞间表型变异性。因此,我们在这里开发了一种基于个人表型异质细胞群生长的模型。在此模型中,每个细胞的表型状态通过捕获细胞增殖和迁移速率的细胞间变异性的结构变量来描述。该模型跟踪单细胞的空间进化动力学,该动力学经历了压力依赖性增殖,可遗传的表型变化和响应压力差异的方向运动。我们正式表明,该模型的连续限制包括细胞种群密度的非本地部分微分方程,该方程概括了早期生长的细胞群体模型。基于个体的模型的结果说明了如何塑造单个细胞演变的增殖移民权衡如何导致在人口水平的行进波形成,在该人群水平上,高度移动的细胞在侵入性前沿局部在局部占主导地位,而在后方发现了更多增强的细胞。我们证明,当考虑到足够大的细胞数量时,这些结果与数值模拟的结果与数值模拟的结果和正式的旅行波分析之间存在出色的定量一致性。我们提供了场景的数值证据,其中两个模型的预测可能由于人口统计学的随机性而有所不同,这是连续模型无法捕获的。这表明在建模表型异构细胞群体的生长时,集成基于个体和连续的方法的重要性。

Existing studies comparing individual-based models of growing cell populations and their continuum counterparts have mainly focused on homogeneous populations, in which all cells have the same phenotypic characteristics. However, significant intercellular phenotypic variability is commonly observed in cellular systems. Therefore, we develop here an individual-based model for the growth of phenotypically heterogeneous cell populations. In this model, the phenotypic state of each cell is described by a structuring variable that captures intercellular variability in cell proliferation and migration rates. The model tracks the spatial evolutionary dynamics of single cells, which undergo pressure-dependent proliferation, heritable phenotypic changes and directional movement in response to pressure differentials. We formally show that the continuum limit of this model comprises a non-local partial differential equation for the cell population density, which generalises earlier models of growing cell populations. Results of the individual-based model illustrate how proliferation-migration tradeoffs shaping the evolution of single cells can lead to the formation of travelling waves at the population level where highly-mobile cells locally dominate at the invasive front, while more-proliferative cells are found at the rear. We demonstrate that there is an excellent quantitative agreement between these results and the results of numerical simulations and formal travelling-wave analysis of the continuum model, when sufficiently large cell numbers are considered. We provide numerical evidence of scenarios in which the predictions of the two models may differ due to demographic stochasticity, which cannot be captured by the continuum model. This indicates the importance of integrating individual-based and continuum approaches when modelling the growth of phenotypically heterogeneous cell populations.

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