A novel mathematical model of AIDS-associated Kaposi's sarcoma: Analysis and optimal control

• Published in: BioSystems Vol. 200; p. 104318
• Main Authors: Kaondera-Shava, R.F., Lungu, E., Szomolay, B.
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier B.V 01.02.2021
• Subjects: cART; HIV-1; Kaposi's sarcoma; KSHV; Optimal control; Viral load; HIV-1; KSHV; cART; Viral load; Kaposi's sarcoma; Optimal control
• ISSN: 0303-2647; 1872-8324
• DOI: 10.1016/j.biosystems.2020.104318

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. •There are very few within-host mathematical models considering AIDS-associated Kaposi's sacoma (AIDS-KS).•The first model of AIDS-KS that includes viral load (VL) measures despite VL being a key determinant in treatment outcome.•By considering weak and strong viral terms the model is able to capture and predict potential outcomes of AIDS-KS.•The results suggest early treatment for HIV-1 in order to maintain low VL and hence preventing AIDS-KS.