Division of Mathematics, University of Dundee, Dundee DD1 4HN, UK.
J Theor Biol. 2012 Sep 7;308:1-19. doi: 10.1016/j.jtbi.2012.05.015. Epub 2012 May 29.
The therapeutic control of a solid tumour depends critically on the responses of the individual cells that constitute the entire tumour mass. A particular cell's spatial location within the tumour and intracellular interactions, including the evolution of the cell-cycle within each cell, has an impact on their decision to grow and divide. They are also influenced by external signals from other cells as well as oxygen and nutrient concentrations. Hence, it is important to take these into account when modelling tumour growth and the response to various treatment regimes ('cell-kill therapies'), including chemotherapy. In order to address this multiscale nature of solid tumour growth and its response to treatment, we propose a hybrid, individual-based approach that analyses spatio-temporal dynamics at the level of cells, linking individual cell behaviour with the macroscopic behaviour of cell organisation and the microenvironment. The individual tumour cells are modelled by using a cellular automaton (CA) approach, where each cell has its own internal cell-cycle, modelled using a system of ODEs. The internal cell-cycle dynamics determine the growth strategy in the CA model, making it more predictive and biologically relevant. It also helps to classify the cells according to their cell-cycle states and to analyse the effect of various cell-cycle dependent cytotoxic drugs. Moreover, we have incorporated the evolution of oxygen dynamics within this hybrid model in order to study the effects of the microenvironment in cell-cycle regulation and tumour treatments. An important factor from the treatment point of view is that the low concentration of oxygen can result in a hypoxia-induced quiescence (G0/G1 arrest) of the cancer cells, making them resistant to key cytotoxic drugs. Using this multiscale model, we investigate the impact of oxygen heterogeneity on the spatio-temporal patterning of the cell distribution and their cell-cycle status. We demonstrate that oxygen transport limitations result in significant heterogeneity in HIF-1 α signalling and cell-cycle status, and when these are combined with drug transport limitations, the efficacy of the therapy is significantly impaired.
实体瘤的治疗控制主要取决于构成整个肿瘤块的单个细胞的反应。单个细胞在肿瘤中的空间位置及其细胞内相互作用，包括每个细胞内细胞周期的演变，都会影响其生长和分裂的决定。它们还受到来自其他细胞的外部信号以及氧气和营养浓度的影响。因此，在对肿瘤生长和对各种治疗方案（包括化疗的“细胞杀伤疗法”）的反应进行建模时，考虑这些因素非常重要。为了解决实体瘤生长及其对治疗反应的多尺度性质，我们提出了一种混合的基于个体的方法，该方法分析了细胞水平的时空动态，将个体细胞行为与细胞组织和微环境的宏观行为联系起来。使用细胞自动机（CA）方法对单个肿瘤细胞进行建模，其中每个细胞都有自己的内部细胞周期，使用 ODE 系统进行建模。内部细胞周期动力学决定了 CA 模型中的生长策略，使其更具预测性和生物学相关性。它还有助于根据细胞周期状态对细胞进行分类，并分析各种细胞周期依赖性细胞毒性药物的作用。此外，我们在混合模型中纳入了氧动力学的演变，以研究微环境对细胞周期调控和肿瘤治疗的影响。从治疗角度来看，一个重要因素是低氧浓度会导致癌细胞缺氧诱导静止（G0/G1 期阻滞），使它们对关键细胞毒性药物产生抗性。使用这种多尺度模型，我们研究了氧异质性对细胞分布时空模式及其细胞周期状态的影响。我们证明，氧传输限制会导致 HIF-1α信号和细胞周期状态的显著异质性，并且当这些与药物传输限制结合时，治疗效果会显著受损。
