适应性免疫决定溶瘤病毒和抗pd -1治疗癌症的效果。

IF 2 4区 数学 Q2 BIOLOGY
Kang-Ling Liao, Kenton D Watt
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引用次数: 0

摘要

免疫检查点抑制剂抗程序性死亡蛋白-1 (anti-PD-1)增强适应性免疫杀死肿瘤细胞,溶瘤病毒(OV)触发先天免疫清除被感染的肿瘤细胞。我们创建了一个数学模型来研究OV和抗pd -1下适应性免疫和先天免疫之间的相互作用如何影响肿瘤的减少。针对不同的免疫强度,我们创建了相应的虚拟基线患者和队列患者,以破译决定治疗结果的主要因素。全局敏感性分析表明,适应性免疫比先天免疫对治疗结果的控制更大,抗pd -1是否抵消OV治疗效果取决于OV的剂量以及T细胞清除感染肿瘤细胞和OV之间的平衡。最佳OV感染率和剂量表明OV治疗对适应性免疫比先天免疫更敏感。我们的模型预测还表明,随着适应性免疫的增强,肿瘤缩小对抗pd -1疗效更加敏感,而随着先天免疫的增强,抗pd -1有抵消OV治疗疗效的趋势。根据这些结果,可以确定不同免疫强度患者的推荐治疗方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Immunity Determines the Cancer Treatment Outcome of Oncolytic Virus and Anti-PD-1.

The immune checkpoint inhibitor, anti-programmed death protein-1 (anti-PD-1), enhances adaptive immunity to kill tumor cells, and the oncolytic virus (OV) triggers innate immunity to clear the infected tumor cells. We create a mathematical model to investigate how the interaction between adaptive and innate immunities under OV and anti-PD-1 affects tumor reduction. For different immunity strength, we create the corresponding virtual baseline patients and cohort patients to decipher the major factors determining the treatment outcome. Global sensitivity analysis indicates that adaptive immunity has more control on the treatment outcome than innate immunity, and whether anti-PD-1 cancels out the OV treatment efficacy depends on the OV dosage and the balance between clearance of infected tumor cells and OV by T cells. The optimal OV infection rate and dosage suggest that OV treatment is more sensitive to adaptive immunity than innate immunity. Our model prediction also indicates that tumor reduction is more sensitive to anti-PD-1 efficacy as adaptive immunity becomes stronger, and anti-PD-1 trends to cancel out the OV treatment efficacy as innate immunity becomes stronger. Based on these results, the recommended treatment protocol for patients with different immunity strength can be determined.

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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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