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首页> 外文期刊>Mathematical modelling of natural phenomena >Evolutionary Dynamics of Cancer Cell Populations under Immune Selection Pressure and Optimal Control of Chemotherapy
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Evolutionary Dynamics of Cancer Cell Populations under Immune Selection Pressure and Optimal Control of Chemotherapy

机译：免疫选择压力和化学疗法的最佳控制下癌细胞群的进化动力学

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Increasing experimental evidence suggests that epigenetic and microenvironmental factors play a key role in cancer progression. In this respect, it is now generally recognized that the immune system can act as an additional selective pressure, which modulates tumor development and leads, through cancer immunoediting, to the selection for resistance to immune effector mechanisms. This may have serious implications for the design of effective anti-cancer protocols. Motivated by these considerations, we present a mathematical model for the dynamics of cancer and immune cells under the effects of chemotherapy and immunity-boosters. Tumor cells are modeled as a population structured by a continuous phenotypic trait, that is related to the level of resistance to receptor-induced cell death triggered by effector lymphocytes. The level of resistance can vary over time due to the effects of epigenetic modifications. In the asymptotic regime of small epimutations, we highlight the ability of the model to reproduce cancer immunoediting. In an optimal control framework, we tackle the problem of designing effective anti-cancer protocols. The results obtained suggest that chemotherapeutic drugs characterized by high cytotoxic effects can be useful for treating tumors of large size. On the other hand, less cytotoxic chemotherapy in combination with immunity-boosters can be effective against tumors of smaller size. Taken together, these results support the development of therapeutic protocols relying on combinations of less cytotoxic agents and immune-boosters to fight cancer in the early stages.
机译：越来越多的实验证据表明，表观遗传和微环境因素在癌症进展中起关键作用。在这方面，现在通常认为免疫系统可以作为附加的选择性压力，其调节肿瘤的发展并通过癌症免疫编辑导致对免疫效应器机制的抗性选择。这可能对有效的抗癌方案的设计产生严重影响。基于这些考虑，我们提出了化学疗法和免疫增强剂作用下癌症和免疫细胞动力学的数学模型。肿瘤细胞被建模为具有连续表型性状的种群，该性状与效应淋巴细胞对受体诱导的细胞死亡的抗性水平有关。由于表观遗传修饰的影响，抗性水平会随时间变化。在小突变的渐进方案中，我们强调了该模型复制癌症免疫编辑的能力。在最佳控制框架中，我们解决了设计有效的抗癌方案的问题。获得的结果表明，以高细胞毒性作用为特征的化学治疗药物可用于治疗大尺寸的肿瘤。另一方面，较少的细胞毒性化学疗法与免疫增强剂结合可以有效治疗较小的肿瘤。综上所述，这些结果支持了依靠较少细胞毒性剂和免疫促进剂的组合来在早期阶段对抗癌症的治疗方案的发展。

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