Department of Mathematics, Western University, London, On Canada.
Department of Mathematics, Western University, London, On Canada.
Math Biosci. 2023 Nov;365:109073. doi: 10.1016/j.mbs.2023.109073. Epub 2023 Sep 3.
We develop and analyze a mathematical model of oncolytic virotherapy in the treatment of melanoma. We begin with a special, local case of the model, in which we consider the dynamics of the tumour cells in the presence of an oncolytic virus at the primary tumour site. We then consider the more general regional model, in which we incorporate a linear network of lymph nodes through which the tumour cells and the oncolytic virus may spread. The modelling also considers the impact of hypoxia on the disease dynamics. The modelling takes into account both the effects of hypoxia on tumour growth and spreading, as well as the impact of hypoxia on oncolytic virotherapy as a treatment modality. We find that oxygen-rich environments are favourable for the use of adenoviruses as oncolytic agents, potentially suggesting the use of complementary external oxygenation as a key aspect of treatment. Furthermore, the delicate balance between a virus' infection capabilities and its oncolytic capabilities should be considered when engineering an oncolytic virus. If the virus is too potent at killing tumour cells while not being sufficiently effective at infecting them, the infected tumour cells are destroyed faster than they are able to infect additional tumour cells, leading less favourable clinical results. Numerical simulations are performed in order to support the analytic results and to further investigate the impact of various parameters on the outcomes of treatment. Our modelling provides further evidence indicating the importance of three key factors in treatment outcomes: tumour microenvironment oxygen concentration, viral infection rates, and viral oncolysis rates. The numerical results also provide some estimates on these key model parameters which may be useful in the engineering of oncolytic adenoviruses.
我们开发并分析了溶瘤病毒治疗黑色素瘤的数学模型。我们首先研究模型的一个特殊局部情况，即考虑原发性肿瘤部位存在溶瘤病毒时肿瘤细胞的动力学。然后，我们考虑更一般的区域模型，其中我们纳入了一个线性淋巴结网络，肿瘤细胞和溶瘤病毒可以通过该网络传播。该模型还考虑了缺氧对疾病动力学的影响。该模型考虑了缺氧对肿瘤生长和扩散的影响，以及缺氧对溶瘤病毒治疗作为一种治疗方式的影响。我们发现，富含氧气的环境有利于使用腺病毒作为溶瘤剂，这可能暗示了使用补充外部氧合作为治疗的关键方面。此外，在设计溶瘤病毒时，应考虑病毒的感染能力与其溶瘤能力之间的微妙平衡。如果病毒在杀死肿瘤细胞方面过于有效，而在感染它们方面不够有效，那么被感染的肿瘤细胞会比它们能够感染更多的肿瘤细胞更快地被破坏，导致不太理想的临床结果。为了支持分析结果并进一步研究各种参数对治疗结果的影响，我们进行了数值模拟。我们的模型提供了进一步的证据，表明在治疗结果中有三个关键因素非常重要：肿瘤微环境中的氧浓度、病毒感染率和病毒溶瘤率。数值结果还提供了这些关键模型参数的一些估计值，这些估计值可能对溶瘤腺病毒的工程设计有用。
