Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Private Bag 16, Palapye, Botswana.
Systems Immunity Research Institute, Cardiff University School of Medicine, Cardiff, CF14 4XN, United Kingdom.
Biosystems. 2021 Feb;200:104318. doi: 10.1016/j.biosystems.2020.104318. Epub 2020 Dec 10.
Kaposi's sarcoma (KS) has been the most common HHV-8 virus-induced neoplasm associated with HIV-1 infection. Although the standard KS therapy has not changed in 20 years, not all cases of KS will respond to the same therapy. The goal of current AIDS-KS treatment modalities is to reconstitute the immune system and suppress HIV-1 replication, but newer treatment modalities are on horizon. There are very few mathematical models that have included HIV-1 viral load (VL) measures, despite VL being a key determinant of treatment outcome. Here we introduce a mathematical model that consolidates the effect of both HIV-1 and HHV-8 VL on KS tumor progression by incorporating low or high VLs into the proliferation terms of the immune cell populations. Regulation of HIV-1/HHV-8 VL and viral reservoir cells is crucial for restoring a patient to an asymptomatic stage. Therefore, an optimal control strategy given by a combined antiretroviral therapy (cART) is derived. The results indicate that the drug treatment strategies are capable of removing the viral reservoirs faster and consequently, the HIV-1 and KS tumor burden is reduced. The predictions of the mathematical model have the potential to offer more effective therapeutic interventions based on viral and virus-infected cell load and support new studies addressing the superiority of VL over CD4 T-cell count in HIV-1 pathogenesis.
卡波济肉瘤(KS)是与 HIV-1 感染相关的最常见的 HHV-8 病毒诱导的肿瘤。尽管 20 年来 KS 的标准治疗方法没有改变,但并非所有 KS 病例都会对相同的治疗方法产生反应。目前 AIDS-KS 治疗方法的目标是重建免疫系统并抑制 HIV-1 复制,但新的治疗方法正在出现。尽管病毒载量(VL)是治疗结果的关键决定因素,但很少有数学模型包括 HIV-1 VL 测量。在这里,我们引入了一个数学模型,通过将低或高 VL 纳入免疫细胞群体的增殖项,整合了 HIV-1 和 HHV-8 VL 对 KS 肿瘤进展的影响。调节 HIV-1/HHV-8 VL 和病毒储存细胞对于将患者恢复到无症状阶段至关重要。因此,衍生出了一种联合抗逆转录病毒疗法(cART)的最佳控制策略。结果表明,药物治疗策略能够更快地清除病毒储存库,从而减少 HIV-1 和 KS 肿瘤负担。该数学模型的预测具有提供基于病毒和病毒感染细胞负荷的更有效治疗干预的潜力,并支持新的研究,以解决 VL 优于 HIV-1 发病机制中 CD4 T 细胞计数的优越性。