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An agent-based model of avascular tumor growth: Immune response tendency to prevent cancer development

机译:基于药物的无血管肿瘤生长模型:免疫反应趋势可预防癌症发展

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Mathematical and computational models are of great help to study and predict phenomena associated with cancer growth and development. These models may lead to introduce new therapies or improve current treatments by discovering facts that may not be easily discovered in clinical experiments. Here, a new two-dimensional (2D) stochastic agent-based model is presented for the spatiotemporal study of avascular tumor growth based on the effect of the immune system. The simple decision-making rules of updating the states of each agent depend not only on its intrinsic properties but also on its environment. Tumor cells can interact with both normal and immune cells in their Moore neighborhood. The effect of hypoxia has been checked off by considering non-mutant proliferative tumor cells beside mutant ones. The recruitment of immune cells after facing a mass of tumor is also considered. Results of the simulations are presented before and after the appearance of immune cells in the studied tissue. The growth fraction and necrotic fraction are used as output parameters along with a 2D graphical growth presentation. Finally, the effect of input parameters on the output parameters generated by the model is discussed. The model is then validated by an in vivo study published in medical articles. The results show a multi-spherical tumor growth before the immune system strongly involved in competition with tumor cells. Besides, considering the immune system in the model shows more compatibility with biological facts. The effect of the microenvironment on the proliferation of cancer and immune cells is also studied.
机译:数学和计算模型对研究和预测与癌症生长和发展有关的现象有很大帮助。这些模型可能会发现一些在临床实验中不容易发现的事实,从而可能导致引入新的疗法或改善当前的治疗方法。在这里,基于免疫系统的影响,提出了一种新的基于二维(2D)随机代理的模型,用于时空研究血管肿瘤的生长。更新每个主体状态的简单决策规则不仅取决于其固有属性,还取决于其环境。肿瘤细胞可以在其摩尔附近与正常细胞和免疫细胞相互作用。通过考虑突变细胞以外的非突变增殖性肿瘤细胞,已经证实了低氧的作用。还考虑了面对大量肿瘤后免疫细胞的募集。模拟结果在研究的组织中出现免疫细胞之前和之后给出。增长分数和坏死分数与2D图形增长表示一起用作输出参数。最后,讨论了输入参数对模型生成的输出参数的影响。然后通过发表在医学文章中的体内研究验证该模型。结果显示,在免疫系统强烈参与与肿瘤细胞竞争之前,肿瘤呈多球形生长。此外,考虑到模型中的免疫系统显示出与生物学事实的更多兼容性。还研究了微环境对癌症和免疫细胞增殖的影响。

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