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对巨噬细胞异质性在非小细胞肺癌的时空动态中的作用的数学研究。

Mathematical investigation into the role of macrophage heterogeneity on the temporal and spatio-temporal dynamics of non-small cell lung cancers.

机构信息

Former address: Mathematics, University of Dundee, Dundee DD1 4HN, United Kingdom.

Former address: Mathematics, University of Dundee, Dundee DD1 4HN, United Kingdom; Laboratoire Mathématiques de Besançon, UMR-CNRS 6623, Université de Bourgogne Franche-Comté, 16 Route de Gray, 25000 Besançon, France.

出版信息

J Theor Biol. 2022 Sep 21;549:111207. doi: 10.1016/j.jtbi.2022.111207. Epub 2022 Jun 27.

Abstract

Non Small Cell Lung Cancer (NSCLC) is the most common type of lung cancer, and represents the leading cause of cancer-related deaths worldwide. Experimental studies have shown that these solid cancers are heavily infiltrated with macrophages: anti-tumour M1 macrophages, pro-tumour M2 macrophages, and macrophage subtypes sharing both M1 and M2 properties. In this study we aim to investigate qualitatively the role of macrophages with different functional phenotypes (especially those with mixed phenotypes) on cancer dynamics and the success of different immunotherapies for cancer. To this end, we start with two time-evolving mathematical models for cancer-immune interactions that consider: (i) the effect of the two extreme phenotypes, M1 and M2 cells; (ii) the effect of M1 and M2 cells, as well as a macrophage sub-population with a mixed phenotype (throughout this theoretical study we call these cells "M12 cells"). We compare the dynamics of the two models using computational approaches, paying particular attention to the effect of different anti-cancer immunotherapies that focus on macrophages. Since data available for NSCLC and macrophage interactions are incomplete, we perform a global sensitivity analysis to see the influence of input parameters on model outcomes. Finally, we consider extensions of the previous two models to include also the spatial movement of cells, and investigate the role of macrophages with extreme phenotypes and with mixed phenotypes, on the invasion of cancer cells into the surrounding extracellular matrix (ECM). We use numerical simulations to investigate the macrophages phenotypes at the tumour center versus the invasive margin. Again, we examine the impact of immunotherapies for cancer on the spatial dynamics of cancers and immune cells, and observe a shift in the phenotype of macrophages distributed at the tumour center and invasive margin.

摘要

非小细胞肺癌 (NSCLC) 是最常见的肺癌类型,也是全球癌症相关死亡的主要原因。实验研究表明,这些实体瘤中浸润了大量巨噬细胞:抗肿瘤 M1 巨噬细胞、促肿瘤 M2 巨噬细胞以及同时具有 M1 和 M2 特性的巨噬细胞亚型。在这项研究中,我们旨在定性研究具有不同功能表型(尤其是混合表型)的巨噬细胞在癌症动力学和不同癌症免疫疗法中的作用。为此,我们从两个考虑癌症-免疫相互作用的时变数学模型开始:(i) 两种极端表型 M1 和 M2 细胞的作用;(ii) M1 和 M2 细胞以及具有混合表型的巨噬细胞亚群(在整个理论研究中,我们将这些细胞称为“M12 细胞”)的作用。我们使用计算方法比较了这两个模型的动态特性,特别关注针对巨噬细胞的不同抗癌免疫疗法的效果。由于 NSCLC 和巨噬细胞相互作用的数据不完整,我们进行了全局敏感性分析,以了解不同输入参数对模型结果的影响。最后,我们考虑了前两个模型的扩展,以包括细胞的空间运动,并研究了具有极端表型和混合表型的巨噬细胞在癌细胞侵入周围细胞外基质 (ECM) 中的作用。我们使用数值模拟来研究肿瘤中心和浸润边缘的巨噬细胞表型。同样,我们检查了癌症免疫疗法对癌症和免疫细胞空间动力学的影响,并观察到分布在肿瘤中心和浸润边缘的巨噬细胞表型发生了转变。

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