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一种探索空间相互作用和抗原识别在针对实体瘤的免疫反应中的作用的随机个体基础模型。

A stochastic individual-based model to explore the role of spatial interactions and antigen recognition in the immune response against solid tumours.

机构信息

School of Mathematics and Statistics, University of St Andrews, St Andrews, KY16 9SS, United Kingdom.

School of Mathematics and Statistics, University of St Andrews, St Andrews, KY16 9SS, United Kingdom.

出版信息

J Theor Biol. 2019 Nov 7;480:43-55. doi: 10.1016/j.jtbi.2019.07.019. Epub 2019 Jul 30.

Abstract

Spatial interactions between cancer and immune cells, as well as the recognition of tumour antigens by cells of the immune system, play a key role in the immune response against solid tumours. The existing mathematical models generally focus only on one of these key aspects. We present here a spatial stochastic individual-based model that explicitly captures antigen expression and recognition. In our model, each cancer cell is characterised by an antigen profile which can change over time due to either epimutations or mutations. The immune response against the cancer cells is initiated by the dendritic cells that recognise the tumour antigens and present them to the cytotoxic T cells. Consequently, T cells become activated against the tumour cells expressing such antigens. Moreover, the differences in movement between inactive and active immune cells are explicitly taken into account by the model. Computational simulations of our model clarify the conditions for the emergence of tumour clearance, dormancy or escape, and allow us to assess the impact of antigenic heterogeneity of cancer cells on the efficacy of immune action. Ultimately, our results highlight the complex interplay between spatial interactions and adaptive mechanisms that underpins the immune response against solid tumours, and suggest how this may be exploited to further develop cancer immunotherapies.

摘要

肿瘤细胞与免疫细胞之间的空间相互作用,以及免疫系统细胞对肿瘤抗原的识别,在针对实体瘤的免疫反应中起着关键作用。现有的数学模型通常只关注这些关键方面之一。我们在这里提出了一个空间随机个体模型,它明确地捕捉了抗原的表达和识别。在我们的模型中,每个肿瘤细胞都有一个抗原特征,由于表观遗传突变或基因突变,这个特征会随时间而变化。树突状细胞识别肿瘤抗原并将其呈递给细胞毒性 T 细胞,从而引发针对肿瘤细胞的免疫反应。因此,T 细胞会针对表达这些抗原的肿瘤细胞被激活。此外,模型还明确考虑了免疫细胞的静息态和激活态之间在运动方面的差异。通过对模型进行计算模拟,可以阐明肿瘤清除、休眠或逃逸的出现条件,并评估肿瘤细胞的抗原异质性对免疫作用效果的影响。最终,我们的结果强调了空间相互作用和适应性机制之间的复杂相互作用,这些相互作用是针对实体瘤的免疫反应的基础,并提出了如何利用这些相互作用来进一步开发癌症免疫疗法。

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