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用多个CAR T细胞产物进行组合抗原向的数学建模,用于质母细胞瘤治疗

Runpeng Li¹, Michael Barish², Margarita Gutova²

¹Department of Mathematics, University of California Riverside, Riverside, CA, USA.

NPJ systems biology and applications

|January 7, 2026

概括

图形抗原受体 (CAR) T细胞治疗质母细胞瘤的数学建模表明,早期干预和向治疗改善了瘤的减少. 像顺序或同时给予和空间向注射这样的策略优化了CAR T细胞对异质脑瘤的疗效.

科学领域:

在瘤学瘤学.
免疫治疗是一种免疫疗法.
计算生物学计算生物学

背景情况:

质母细胞瘤是一种抗常规治疗的侵袭性脑癌.
化学抗原受体 (CAR) T细胞疗法显示出前景,但面临着诸如瘤异质性和微环境等挑战.
优化CAR T细胞治疗需要了解空间抗原表达和T细胞相互作用.

研究的目的:

开发CAR T细胞治疗质母细胞瘤的数学模型.
探索组合抗原向和患者特异性治疗策略.
研究空间抗原异质性对治疗疗效的影响.

主要方法:

使用PhysiCell平台开发了一种混合数学模型.
结合了瘤微环境的部分微分方程与质母细胞瘤和CAR T细胞的基因模型.
模拟了针对IL-13Rα2,HER2和EGFR的CAR T细胞相互作用,考虑了空间抗原表达模式.

主要成果:

早期干预是最有效的,特别是在混合抗原表达的瘤中.
顺序的CAR T细胞给药可以像对集群抗原模式的同时给药一样有效.
与基线相比,空间向的分娩和多地点的管理显著增加了瘤的减少.

结论:

数学建模为优化患者特异性CAR T细胞治疗质母细胞瘤提供了一个平台.
治疗时间安排和注射位置可以根据个体瘤抗原资料量身定制.
结合性和空间向的CAR T细胞策略有可能改善质母细胞瘤治疗结果.

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