School of Computing, Engineering and Information Sciences, Northumbria University, UK.
J Theor Biol. 2012 Nov 21;313:142-52. doi: 10.1016/j.jtbi.2012.07.026. Epub 2012 Aug 15.
The potential for the use of in-silico models of disease in progression monitoring is becoming increasingly recognised, as well as its contribution to the development of complete curative processes. In this paper we report the development of a hybrid cellular automaton model to mimic the growth of avascular tumours, including the infusion of a bioreductive drug to study the effects of protein binding on drug transportation. The growth model is operated within an extracellular tumour microenvironment. An artificial Neural Network based scheme was implemented that modelled the behaviours of each cell (proliferation, quiescence, apoptosis and/or movement) based on the complex heterogeneous microenvironment; consisting of oxygen, glucose, hydrogen ions, inhibitory factors and growth factors. To validate the growth model results, we conducted experiments with multicellular tumour spheroids. These results showed good agreement with the predicted growth dynamics. The outcome of the avascular tumour growth model suggested that tumour microenvironments have a strong impact on cell behaviour. To address the problem of cellular proteins acting as resistive factors preventing efficient drug penetration, a bioreactive drug (tirapazamine) was added to the system. This allowed us to study the drug penetration through multicellular layers of tissue after its binding to cellular proteins. The results of the in vitro model suggested that the proteins reduce the toxicity of the drug, reducing its efficacy for the most severely hypoxic fractions furthest from a functional blood vessel. Finally this research provides a unique comparison of in vitro tumour growth with an intelligent in silico model to measure bioreductive drug availability inside tumour tissue through a set of experiments.
疾病的计算机模型在进展监测中的应用潜力正逐渐得到认可，同时它也为完整治疗过程的发展做出了贡献。在本文中，我们报告了一种混合细胞自动机模型的开发，以模拟无血管肿瘤的生长，包括输注生物还原药物以研究蛋白质结合对药物输送的影响。该生长模型在细胞外肿瘤微环境中运行。我们实施了一种基于人工神经网络的方案，该方案根据复杂的异质微环境（包括氧气、葡萄糖、氢离子、抑制因子和生长因子）模拟每个细胞（增殖、静止、凋亡和/或运动）的行为。为了验证生长模型的结果，我们进行了多细胞肿瘤球体的实验。这些结果与预测的生长动态具有良好的一致性。无血管肿瘤生长模型的结果表明，肿瘤微环境对细胞行为有很大的影响。为了解决细胞蛋白作为抵抗因素，阻止有效药物渗透的问题，我们向系统中添加了一种生物反应性药物（替拉扎明）。这使我们能够研究药物在与细胞蛋白结合后穿透多细胞组织层的情况。体外模型的结果表明，蛋白质降低了药物的毒性，降低了其对距离功能性血管最远的最严重缺氧部位的疗效。最后，这项研究通过一系列实验，提供了一种独特的体外肿瘤生长与智能计算机模型的比较，以测量肿瘤组织内生物还原药物的可用性。
