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放疗与免疫疗法免疫原性及协同效应的计算机模拟机制探索:一项批判性综述

Mechanistic in silico explorations of the immunogenic and synergistic effects of radiotherapy and immunotherapy: a critical review.

作者信息

Ng Allison M, MacKinnon Kelly M, Cook Alistair A, D'Alonzo Rebecca A, Rowshanfarzad Pejman, Nowak Anna K, Gill Suki, Ebert Martin A

机构信息

School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, WA, Australia.

National Centre for Asbestos Related Diseases, The University of Western Australia, Crawley, WA, Australia.

出版信息

Phys Eng Sci Med. 2024 Dec;47(4):1291-1306. doi: 10.1007/s13246-024-01458-1. Epub 2024 Jul 17.

Abstract

Immunotherapy is a rapidly evolving field, with many models attempting to describe its impact on the immune system, especially when paired with radiotherapy. Tumor response to this combination involves a complex spatiotemporal dynamic which makes either clinical or pre-clinical in vivo investigation across the resulting extensive solution space extremely difficult. In this review, several in silico models of the interaction between radiotherapy, immunotherapy, and the patient's immune system are examined. The study included only mathematical models published in English that investigated the effects of radiotherapy on the immune system, or the effect of immuno-radiotherapy with immune checkpoint inhibitors. The findings indicate that treatment efficacy was predicted to improve when both radiotherapy and immunotherapy were administered, compared to radiotherapy or immunotherapy alone. However, the models do not agree on the optimal schedule and fractionation of radiotherapy and immunotherapy. This corresponds to relevant clinical trials, which report an improved treatment efficacy with combination therapy, however, the optimal scheduling varies between clinical trials. This discrepancy between the models can be attributed to the variation in model approach and the specific cancer types modeled, making the determination of the optimum general treatment schedule and model challenging. Further research needs to be conducted with similar data sets to evaluate the best model and treatment schedule for a specific cancer type and stage.

摘要

免疫疗法是一个快速发展的领域,有许多模型试图描述其对免疫系统的影响,尤其是与放射疗法联合使用时。肿瘤对这种联合治疗的反应涉及复杂的时空动态变化,这使得在由此产生的广阔解决方案空间内进行临床或临床前体内研究极为困难。在这篇综述中,研究了几种关于放射疗法、免疫疗法与患者免疫系统之间相互作用的计算机模拟模型。该研究仅纳入了以英文发表的数学模型,这些模型研究了放射疗法对免疫系统的影响,或免疫检查点抑制剂免疫放射疗法的效果。研究结果表明,与单独使用放射疗法或免疫疗法相比,同时给予放射疗法和免疫疗法时预计治疗效果会提高。然而,这些模型在放射疗法和免疫疗法的最佳给药方案和分割方式上并未达成一致。这与相关临床试验结果相符,临床试验报告联合治疗可提高治疗效果,然而,最佳给药方案在不同临床试验中有所不同。模型之间的这种差异可归因于模型方法的差异以及所模拟的特定癌症类型,这使得确定最佳总体治疗方案和模型具有挑战性。需要使用类似的数据集进行进一步研究,以评估针对特定癌症类型和阶段的最佳模型和治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9d/11666662/6f50652e53bc/13246_2024_1458_Fig1_HTML.jpg

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