Mathematical modeling of the synergetic effect between radiotherapy and immunotherapy.

IF 2.6 4区 工程技术 Q1 Mathematics
Yixun Xing, Casey Moore, Debabrata Saha, Dan Nguyen, MaryLena Bleile, Xun Jia, Robert Timmerman, Hao Peng, Steve Jiang
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Abstract

The synergy between radiotherapy and immunotherapy plays a pivotal role in enhancing tumor control and treatment outcomes. To explore the underlying mechanisms of synergy, we investigated a novel treatment approach known as personalized ultra-fractionated stereotactic adaptive radiation (PULSAR) therapy, which emphasizes the impact of radiation timing. Unlike conventional daily treatments, PULSAR delivers high-dose radiation in spaced intervals over weeks or months, enabling tumors to adapt and potentially enhancing synergy with immunotherapy. Drawing on insights from small-animal radiation studies, we developed a discrete-time model based on multiple difference equations to elucidate the temporal dynamics of tumor control driven by both radiation and the adaptive immune response. By accounting for the migration and infiltration of T cells within the tumor microenvironment, we established a quantitative link between radiation therapy and immunotherapy. Model parameters were estimated using a simulated annealing algorithm applied to training data, and our model achieved high accuracy for the test data with a root mean square error of 287 mm3. Notably, our framework replicated the PULSAR effect observed in animal studies, revealing that longer intervals between radiation treatments in the context of immunotherapy yielded enhanced tumor control. Specifically, mice receiving immunotherapy alongside radiation pulses delivered at extended intervals, ten days, showed markedly improved tumor responses, whereas those treated with shorter intervals did not achieve comparable benefits. Moreover, our model offers an in-silico tool for designing future personalized ultra-fractionated stereotactic adaptive radiation trials. Overall, these findings underscore the critical importance of treatment timing in harnessing the synergy between radiotherapy and immunotherapy and highlight the potential of our model to optimize and individualize treatment protocols.

放射治疗与免疫治疗协同效应的数学模型。
放疗与免疫治疗的协同作用对提高肿瘤控制和治疗效果起着关键作用。为了探索协同作用的潜在机制,我们研究了一种新的治疗方法,即个性化超分割立体定向适应性放射(PULSAR)治疗,该治疗方法强调放射时间的影响。与传统的日常治疗不同,PULSAR在数周或数月的间隔时间内提供高剂量辐射,使肿瘤能够适应并潜在地增强与免疫治疗的协同作用。根据小动物辐射研究的见解,我们建立了一个基于多个差分方程的离散时间模型,以阐明辐射和适应性免疫反应驱动的肿瘤控制的时间动态。通过考虑肿瘤微环境中T细胞的迁移和浸润,我们建立了放射治疗和免疫治疗之间的定量联系。模型参数估计采用模拟退火算法应用于训练数据,我们的模型对测试数据取得了较高的精度,均方根误差为287 mm3。值得注意的是,我们的框架复制了在动物研究中观察到的PULSAR效应,揭示了在免疫治疗背景下较长的放射治疗间隔可以增强肿瘤控制。具体来说,接受免疫治疗的小鼠与间隔较长(10天)的放射脉冲一起,显示出明显改善的肿瘤反应,而间隔较短的小鼠则没有获得类似的益处。此外,我们的模型为设计未来个性化超分割立体定向自适应辐射试验提供了一种计算机工具。总的来说,这些发现强调了治疗时机在利用放疗和免疫治疗之间的协同作用方面的重要性,并强调了我们的模型在优化和个性化治疗方案方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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