癌症免疫编辑:一种博弈论方法。

Q2 Medicine
Fatemeh Tavakoli, Javad Salimi Sartakhti, Mohammad Hossein Manshaei, David Basanta
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引用次数: 8

摘要

免疫系统在肿瘤发展中的作用越来越多地包括癌症免疫编辑的想法。它包括三个阶段:消除、平衡和逃逸。在第一阶段,清除,转化细胞被免疫系统识别和破坏。在此阶段未被破坏的罕见肿瘤细胞可能会进入平衡阶段,在此阶段它们的生长被免疫机制阻止。逃逸阶段代表了这个过程的最后阶段,癌细胞开始不受免疫系统的约束生长。在这项研究中,我们首次描述和分析了增殖、静止和免疫细胞相互作用的进化博弈理论模型。用常数法和动态法对模型进行了评价。群体动态和免疫系统和癌细胞之间的相互作用进行了研究。应用代数分析方法对平衡点和临界点的稳定性进行了分析。这个模型使我们能够了解癌症发展的过程,并可能帮助我们设计更好的治疗策略来解释免疫编辑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Cancer immunoediting: A game theoretical approach.

Cancer immunoediting: A game theoretical approach.

Cancer immunoediting: A game theoretical approach.

Cancer immunoediting: A game theoretical approach.

The role of the immune system in tumor development increasingly includes the idea of cancer immunoediting. It comprises three phases: elimination, equilibrium, and escape. In the first phase, elimination, transformed cells are recognized and destroyed by immune system. The rare tumor cells that are not destroyed in this phase may then enter the equilibrium phase, where their growth is prevented by immunity mechanisms. The escape phase represents the final phase of this process, where cancer cells begin to grow unconstrained by the immune system. In this study, we describe and analyze an evolutionary game theoretical model of proliferating, quiescent, and immune cells interactions for the first time. The proposed model is evaluated with constant and dynamic approaches. Population dynamics and interactions between the immune system and cancer cells are investigated. Stability of equilibria or critical points are analyzed by applying algebraic analysis. This model allows us to understand the process of cancer development and might help us design better treatment strategies to account for immunoediting.

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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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