PROTAC 工程化蛋白/DNA 纳米抗原是癌症免疫治疗中树突状细胞疫苗的有效增强剂
PROTAC-Engineered Protein/DNA Nanoantigen is a Potent Booster for Dendritic Cell Vaccines in Cancer Immunotherapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
在癌症免疫治疗中模拟 CD73 抑制剂与基于树突状细胞的疫苗的联合递送
英文原题：Modeling codelivery of CD73 inhibitor and dendritic cell-based vaccines in cancer immunotherapy.
查看英文原题
Modeling codelivery of CD73 inhibitor and dendritic cell-based vaccines in cancer immunotherapy.
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中文摘要
树突状细胞（DC）是人类中占主导地位的抗原呈递细胞；因此，已建立了一系列基于DC的方法来促进针对癌细胞的免疫反应。基于DC的免疫治疗方法的疗效明显受到与肿瘤微环境相关的免疫抑制因子的影响，例如腺苷。在本文中，基于免疫学理论和实验数据，设计了一个混合模型，为基于DC的免疫治疗联合腺苷抑制的效果提供了一些见解。该模型将用于描述肿瘤-免疫系统相互作用的基于个体的模型与用于腺苷建模的一组常微分方程相结合。对所提出模型的计算模拟阐明了针对癌细胞成功免疫反应发生的条件。模型的全局和局部敏感性分析突出了腺苷阻断对增强效应细胞的重要性。该模型用于确定腺苷引起的最有效抑制机制、合适的疫苗接种时间以及注射之间的适当时间间隔。
展开英文摘要原文
Dendritic cells (DCs) are the dominant class of antigen-presenting cells in humans; therefore, a range of DC-based approaches have been established to promote an immune response against cancer cells. The efficacy of DC-based immunotherapeutic approaches is markedly affected by the immunosuppressive factors related to the tumor microenvironment, such as adenosine. In this paper, based on immunological theories and experimental data, a hybrid model is designed that offers some insights into the effects of DC-based immunotherapy combined with adenosine inhibition.
The model combines an individual-based model for describing tumor-immune system interactions with a set of ordinary differential equations for adenosine modeling. Computational simulations of the proposed model clarify the conditions for the onset of a successful immune response against cancer cells.
Global and local sensitivity analysis of the model highlights the importance of adenosine blockage for strengthening effector cells. The model is used to determine the most effective suppressive mechanism caused by adenosine, proper vaccination time, and the appropriate time interval between injections.
论文信息
- 作者
- Arabameri A、Pourgholaminejad A
- 第一作者单位
- Department of Electrical Engineering, University of Zanjan, Zanjan, Iran. Electronic address: arabameri@znu.ac.ir.Iran
- 通讯作者单位
- Department of Immunology, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran. Electronic address: pourgholaminejad@gums.ac.ir.Iran
- 期刊
- Computational biology and chemistry2021 Dec
- 原文标识
- PubMed 34610532 · DOI 10.1016/j.compbiolchem.2021.107585