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克服低级质瘤中的化疗抵抗:一种计算方法

Thibault Delobel^1,2, Luis E Ayala-Hernández^1,3, Jesús J Bosque¹

¹Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain.

PLoS computational biology

|November 20, 2023

概括

数学建模显示,改变temozolomide (TMZ) 给药时间表可以延迟低度质瘤的耐药性. 在虚拟患者模型中,间歇性用量与休息时间显著改善了存活率.

科学领域:

神经瘤学神经瘤学
数学生物学数学生物学
计算医学是一种计算医学.

背景情况:

低度质瘤是主要的大脑瘤,通常用temozolomide (TMZ) 治疗.
患者经常对TMZ产生耐药性,从而限制了治疗的有效性.
进入休眠状态的持久细胞与TMZ抗药性发展有关.

研究的目的:

开发一个数学模型的低级质瘤对TMZ的反应,结合持久细胞.
调查新的TMZ管理协议来克服药物耐药性.
评估修改剂量计划对患者存活时间和毒性的影响.

主要方法:

在TMZ治疗下模拟低级质瘤动态的数学模型的构建.
在模型中包含一个持久细胞群体来表示休眠状态.
使用虚拟患者模型进行in silico临床试验,以测试各种TMZ给药协议.

主要成果:

该模型准确地描述了患有TMZ耐药性的患者的瘤体积变化.
与TMZ间歇剂量和休息时间的协议相比,与标准周期相比,延迟了耐药性的发展.
虚拟患者的平均生存时间超过15个月,休息期为2-3周.
适应性协议变化减少了毒性,但没有增加生存率.

结论:

数学建模为优化TMZ治疗低度质瘤提供了洞察力.
间歇性TMZ剂量策略在延迟耐药性和改善生存方面表现有前途.
需要进一步的临床试验来验证这些计算发现在现实世界患者群体中的有效性.

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