The purpose of this paper is to introduce a novel in silico platform for simulating early stage solid tumor growth and anti-tumor immune response. We present the model, test the sensitivity and robustness of its parameters, and calibrate it with clinical data from exercise oncology experiments which offer a natural biological backdrop for modulation of anti-tumor immune response. We then perform two virtual experiments with the model that demonstrate its usefulness in guiding pre-clinical and clinical studies of immunotherapy. The first virtual experiment describes the intricate dynamics in the tumor microenvironment between the tumor and the infiltrating immune cells. Such dynamics is difficult to probe during a pre-clinical study as it requires significant redundancy in lab animals and is prohibitively time-consuming and labor-intensive. The result is a series of spatiotemporal snapshots of the tumor and its microenvironment that can serve as a platform to test mechanistic hypotheses on the role and dynamics of different immune cells in anti-tumor immune response. The second virtual experiment shows how dosage and/or frequency of immunotherapy drugs can be optimized based on the aerobic fitness of the patient, so that possible adverse side effects of the treatment can be minimized.

中文翻译：

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终其一生：将运动肿瘤学纳入免疫疗法的集成虚拟组织平台

本文的目的是介绍一种新型的计算机模拟平台，用于模拟早期实体瘤的生长和抗肿瘤免疫反应。我们介绍了该模型，测试了其参数的敏感性和鲁棒性，并根据运动肿瘤学实验的临床数据对其进行了校准，这些实验数据为调节抗肿瘤免疫应答提供了自然的生物学背景。然后，我们对该模型进行两个虚拟实验，以证明其在指导免疫疗法的临床前和临床研究中的有用性。第一个虚拟实验描述了肿瘤与浸润的免疫细胞之间在肿瘤微环境中的复杂动态。这种动力学很难在临床前研究中探究，因为它需要大量的实验动物冗余，并且非常耗时且劳动强度大。结果是一系列肿瘤及其微环境的时空快照，可作为测试有关不同免疫细胞在抗肿瘤免疫反应中的作用和动力学的机制假设的平台。第二个虚拟实验显示了如何根据患者的有氧适应性来优化免疫治疗药物的剂量和/或频率，从而使治疗的可能不良副作用最小化。