中山大学数学学院,广东 广州 510275
刘泽铭(1998年生),男;研究方向:数学肿瘤学;E-mail:liuzm7@mail2.sysu.edu.cn
孙小强(1988年生),男;研究方向:计算系统生物学;E-mail:sunxq6@mail.sysu.edu.cn
网络出版日期:2024-09-09,
收稿日期:2024-04-08,
录用日期:2024-05-02
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刘泽铭, 孙小强. 细胞微环境介导肿瘤耐药性的动力学建模研究进展[J/OL]. 中山大学学报(自然科学版)(中英文), 2024,1-18.
LIU Zeming, SUN Xiaoqiang. A survey on dynamic modeling of microenvironment-mediated cancer drug resistance[J/OL]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2024,1-18.
刘泽铭, 孙小强. 细胞微环境介导肿瘤耐药性的动力学建模研究进展[J/OL]. 中山大学学报(自然科学版)(中英文), 2024,1-18. DOI: 10.13471/j.cnki.acta.snus.ZR20240106.
LIU Zeming, SUN Xiaoqiang. A survey on dynamic modeling of microenvironment-mediated cancer drug resistance[J/OL]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2024,1-18. DOI: 10.13471/j.cnki.acta.snus.ZR20240106.
肿瘤耐药性是限制癌症疗效的最大障碍之一,肿瘤微环境在耐药性的发生发展过程中发挥着重要的作用. 为了深入探究微环境介导肿瘤耐药性的作用和机制,需要全面系统地研究药物治疗过程中肿瘤生态系统的动态演化. 数学模型可用于描述肿瘤微环境中的各种组分的相互作用和变化,进而揭示微环境介导肿瘤耐药性的机理和演化规律,并为设计更有效的治疗策略提供参考和依据. 本文首先介绍了微环境介导肿瘤耐药性的生物学知识和相关概念;随后分类介绍了几类典型数学模型的最新研究进展;之后以脑胶质瘤微环境为例,介绍了使用不同方法建立耐药性的演化动力学模型的流程;最后展望了进一步的研究方向.
Tumor drug resistance is one of the biggest obstacles limiting cancer treatment, and the tumor microenvironment plays an important role in the occurrence and development of drug resistance. In order to further explore the role and mechanism of microenvironment-mediated tumor drug resistance, it is necessary to comprehensively and systematically study the dynamic evolution of the tumor ecosystem during drug treatment. Mathematical models can be used to describe the interactions and changes of various components in the tumor microenvironment, thereby revealing the mechanism and evolution of tumor drug resistance mediated by the microenvironment, and providing a reference and theoretical basis for designing more effective treatment strategies. In this paper, we first introduce some concepts of microenvironment-mediated evolutionary dynamics modeling of tumor drug resistance, then classify and introduce the latest research progress of various mathematical models in this field. Furthermore, we introduce the process of developing mathematical models of drug resistance using various methods by taking glioma microenvironment as an example. At last, we look forward to further research directions.
数学肿瘤学演化动力学建模耐药性肿瘤微环境
mathematical oncologyevolutionary dynamics modelingdrug resistancetumor microenvironment
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