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Modeling and Analyzing Stem-Cell Therapy toward Cancer: Evolutionary Game Theory Perspective

BACKGROUND: Immunotherapy is a recently developed method of cancer therapy, aiming to strengthen a patient’s immune system in different ways to fight cancer. One of these ways is to add stem cells into the patient’s body. METHODS: The study was conducted in Kermanshah, western Iran, 2016–2017. We fi...

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Detalles Bibliográficos
Autores principales: VEISI, Zahra, KHADEM, Heydar, RAVANSHADI, Samin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7152621/
https://www.ncbi.nlm.nih.gov/pubmed/32309233
Descripción
Sumario:BACKGROUND: Immunotherapy is a recently developed method of cancer therapy, aiming to strengthen a patient’s immune system in different ways to fight cancer. One of these ways is to add stem cells into the patient’s body. METHODS: The study was conducted in Kermanshah, western Iran, 2016–2017. We first modeled the interaction between cancerous and healthy cells using the concept of evolutionary game theory. System dynamics were analyzed employing replicator equations and control theory notions. We categorized the system into separate cases based on the value of the parameters. For cases in which the system converged to undesired equilibrium points, “stem-cell injection” was employed as a therapeutic suggestion. The effect of stem cells on the model was considered by reforming the replicator equations as well as adding some new parameters to the system. RESULTS: By adjusting stem cell-related parameters, the system converged to desired equilibrium points, i.e., points with no or a scanty level of cancerous cells. In addition to the theoretical analysis, our simulation results suggested solutions were effective in eliminating cancerous cells. CONCLUSION: This model could be applicable to different types of cancer, so we did not restrict it to a specific type of cancer. In fact, we were seeking a flexible mathematical framework that could cover different types of cancer by adjusting the system parameters.