Optimal control application to a Kaposi's sarcoma treatment model

Obias M. Chimbola, Edward M. Lungu, Barbara Szomolay

Research output: Contribution to journalArticlepeer-review

Abstract

Kaposi's sarcoma (KS) is a malignant disorder of lymphatic endothelial origin that can have two main variants: AIDS-related KS (AKS) and non-AIDS related KS (NAKS) that all share a causal relationship with the human herpesvirus-8 (KSHV or HHV-8). We develop a mathematical model that accounts for B-cells latently and lytically infected with HHV-8 as well as the innate and adaptive arms of the immune system. As a sequel to numerous studies that have investigated the inhibition of HHV-8 endocytosis and reactivation of HHV-8 replication, we employ optimal control strategy to obtain treatment efficacies for these two therapeutic approaches. We have shown that when 90% of the B-cell infections result in latency, administration of high efficacy drugs that inhibit entry and reactivation of latently infected B-cells leads to the clearance of KS as the population of infected cells cannot be sustained. Our results also reveal that at 90% latency of B-cells, the therapy could produce similar results if the drug that targets viral entry is of moderate efficacy but the efficacy of the drug inhibiting reactivation is considerably more than 0.8. Administration of the same drugs but both at moderate efficacy levels leads to the depletion of both uninfected B- and progenitor cells, a scenario which can lead to the growth of KS variants. When 10% of the B-cell infections result in latency, administration with high efficacy drugs reduces the viral entry of HHV-8 but as 90% of the infected B-cells are productive, this event leads to production of HHV-8 which ultimately results in more progenitor cells getting infected and the growth of KS. Our findings have the potential to offer more effective therapeutic approaches in the treatment of NAKS.

Original languageEnglish
Article number2150081
JournalInternational Journal of Biomathematics
DOIs
Publication statusAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Applied Mathematics

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