Oncolysis by SARS-CoV-2: modeling and analysis

The relationship between cancer and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is controversial. While SARS-CoV-2 can worsen the status of a cancer patient, many remission cases after SARS-CoV-2 infection have been recorded. It has been suggested that SARS-CoV-2 could have oncolytic properties, which needs further investigations. Mathematical modeling is a powerful tool that can significantly enhance experimental and medical studies. Our objective was to propose and analyze a mathematical model for oncolytic SARS-CoV-2 with immunity. The basic properties of this model, including existence, uniqueness, nonnegativity, and boundedness of the solutions, were confirmed. The equilibrium points were computed, and their existence conditions were determined. The global stability of the equilibria was proven using the Lyapunov theory. Numerical simulations were implemented to validate the theoretical results. It was found that the model has thirteen equilibrium points that reflect different infection states. Based on the model's results, the infection of cancer cells by SARS-CoV-2 can lead to a reduction in the concentration of cancer cells. Additionally, the induction of cytotoxic T lymphocytes (CTLs) decreases the number of cancer cells, potentially resulting in cancer remission or an improvement in the overall health of cancer patients. This theoretical result aligns with numerous studies highlighting the oncolytic role of SARS-CoV-2. In addition, given the limited availability of real data, further studies are essential to better comprehend the role of immune responses and their impact on the oncolytic role of SARS-CoV-2.