Department of Molecular Medicine, Mayo Clinic, Rochester, MN, USA.
Department of Mathematics and Institute of Molecular Biophysics, Florida State University, Tallahassee, FL, USA.
FEBS J. 2021 Nov;288(21):6273-6285. doi: 10.1111/febs.16102. Epub 2021 Aug 29.
Cancer therapy remains challenging due to the myriad presentations of the disease and the vast genetic diversity of tumors that continuously evolve and often become resistant to therapy. Viruses can be engineered to specifically infect, replicate, and kill tumor cells (tumor virotherapy). Moreover, the viruses can be "armed" with therapeutic genes to enhance their oncolytic effect. Using viruses to treat cancer is exciting and novel and in principle can be used for a broad variety of tumors. However, the approach is distinctly different from other cancer therapies since success depends on establishment of an infection within the tumor and ongoing propagation of the oncolytic virus within the tumor itself. Therefore, the target itself amplifies the therapy. This introduces complex dynamics especially when the immune system is taken into consideration as well as the physical and other biological barriers to virus growth. Understanding these dynamics not only requires mathematical and computational models but also approaches for the noninvasive monitoring of the virus and tumor populations. In this perspective, we discuss strategies and current results to achieve this important goal of understanding these dynamics in pursuit of optimization of oncolytic virotherapy.
由于疾病的多种表现形式和肿瘤的巨大遗传多样性,癌症治疗仍然具有挑战性,肿瘤不断进化,并且经常对治疗产生耐药性。病毒可以被设计为专门感染、复制和杀死肿瘤细胞(肿瘤病毒疗法)。此外,还可以为病毒“武装”治疗基因以增强其溶瘤作用。使用病毒治疗癌症是令人兴奋和新颖的,原则上可以用于多种肿瘤。然而,这种方法与其他癌症治疗方法明显不同,因为成功取决于在肿瘤内建立感染以及溶瘤病毒在肿瘤内的持续繁殖。因此,目标本身放大了治疗效果。当考虑到免疫系统以及病毒生长的物理和其他生物学障碍时,这会引入复杂的动力学。理解这些动力学不仅需要数学和计算模型,还需要用于非侵入性监测病毒和肿瘤群体的方法。在这篇观点文章中,我们讨论了实现这一重要目标的策略和当前结果,即了解这些动力学,以优化溶瘤病毒疗法。