T细胞耗竭动态对肿瘤-免疫相互作用和肿瘤生长的影响

IF 2 4区 数学 Q2 BIOLOGY
Nicholas Lai, Alexis Farman, Helen M Byrne
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引用次数: 0

摘要

肿瘤通过许多不同的免疫抑制机制逃避免疫监视。其中一种机制导致细胞毒性t细胞(免疫系统的主要驱动力)分化到一种“衰竭”状态,使它们杀死肿瘤细胞的效率降低。我们提出了一个结构化的数学模型,着重于t细胞耗竭及其对肿瘤生长的影响。我们根据细胞毒性t细胞的衰竭水平将它们划分为离散的亚群,这影响了它们杀死肿瘤细胞的能力。我们表明,该模型简化为一个更简单的常微分方程(ode)系统,它描述了t细胞总数、它们的平均衰竭水平和肿瘤细胞总数的时间演变。模型方程的数值模拟揭示了t细胞的衰竭分布如何随时间变化,以及它如何影响肿瘤的生长动态。互补分岔分析显示改变关键参数如何显著减少肿瘤负担,强调衰竭是免疫治疗的一个有希望的目标。最后,我们推导了离散ODE模型的连续统近似,该模型承认解析解,为t细胞耗竭动力学及其对肿瘤生长的影响提供了补充见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Impact of T-cell Exhaustion Dynamics on Tumour-Immune Interactions and Tumour Growth.

Tumours evade immune surveillance through a number of different immunosuppressive mechanisms. One such mechanism causes cytotoxic T-cells, a major driving force of the immune system, to differentiate to a state of 'exhaustion', rendering them less effective at killing tumour cells. We present a structured mathematical model that focuses on T-cell exhaustion and its effect on tumour growth. We compartmentalise cytotoxic T-cells into discrete subgroups based on their exhaustion level, which affects their ability to kill tumour cells. We show that the model reduces to a simpler system of ordinary differential equations (ODEs) that describes the time evolution of the total number of T-cells, their mean exhaustion level and the total number of tumour cells. Numerical simulations of the model equations reveal how the exhaustion distribution of T-cells changes over time and how it influences the tumour's growth dynamics. Complementary bifurcation analysis shows how altering key parameters significantly reduces the tumour burden, highlighting exhaustion as a promising target for immunotherapy. Finally, we derive a continuum approximation of the discrete ODE model, which admits analytical solutions that provide complementary insight into T-cell exhaustion dynamics and their effect on tumour growth.

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来源期刊
CiteScore
3.90
自引率
8.60%
发文量
123
审稿时长
7.5 months
期刊介绍: The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including: Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations Research in mathematical biology education Reviews Commentaries Perspectives, and contributions that discuss issues important to the profession All contributions are peer-reviewed.
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