癌细胞和溶瘤病毒之间相互作用的数学模型：对治疗方案影响的见解
Mathematical modelling of the interaction between cancer cells and an oncolytic virus: insights into the effects of treatment protocols
摘要：
溶瘤病毒疗法是一种实验性癌症治疗方法，使用基因工程病毒靶向并杀死癌细胞。这种治疗的一个主要限制是病毒颗粒被免疫系统迅速清除，阻止它们到达肿瘤部位。为了提高病毒的存活率和感染性，用聚合物聚乙二醇（PEG）和单克隆抗体赫赛汀修饰病毒颗粒。虽然PEG修饰似乎改善了血浆保留和初始感染性，但它也增加了病毒颗粒到达时间。我们推导出一个描述肿瘤细胞和溶瘤病毒之间相互作用的数学模型。我们调整我们的模型来表示Kim等人的实验数据。（2011）并获得优化的参数。我们的模型提供了一个平台，可以预测癌症生长对实验之外的其他治疗方案的反应。通过模型模拟，我们发现，治疗方案的影响显着的结果。我们量化剂量策略作为肿瘤细胞复制和肿瘤携带能力的函数对溶瘤病毒疗法作为一种治疗的结果的影响。探讨了病毒修饰的相对重要性及其在优化治疗效果方面所起的关键作用。
英文摘要：
Oncolytic virotherapy is an experimental cancer treatment that uses genetically engineered viruses to target and kill cancer cells. One major limitation of this treatment is that virus particles are rapidly cleared by the immune system, preventing them from arriving at the tumour site. To improve virus survival and infectivity modified virus particles with the polymer polyethylene glycol (PEG) and the monoclonal antibody herceptin. While PEG modification appeared to improve plasma retention and initial infectivity it also increased the virus particle arrival time. We derive a mathematical model that describes the interaction between tumour cells and an oncolytic virus. We tune our model to represent the experimental data by Kim et al. (2011) and obtain optimised parameters. Our model provides a platform from which predictions may be made about the response of cancer growth to other treatment protocols beyond those in the experiments. Through model simulations we find that the treatment protocol affects the outcome dramatically. We quantify the effects of dosage strategy as a function of tumour cell replication and tumour carrying capacity on the outcome of oncolytic virotherapy as a treatment. The relative significance of the modification of the virus and the crucial role it plays in optimising treatment efficacy is explored.
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