4.7 Article

Mathematical Modeling the Time-Delay Interactions between Tumor Viruses and the Immune System with the Effects of Chemotherapy and Autoimmune Diseases

Journal

MATHEMATICS
Volume 10, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/math10050756

Keywords

immune system; tumor virus; effector cell; autoimmune disease; time-delay virus-immune model; chemotherapy drug

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The immune system defends the body against pathogens and can recognize and kill abnormal and infected cells. Chemotherapy drugs can kill cancer cells but also affect immune cells and may stimulate cancer growth. This study introduces a tumor-immune model considering chemotherapy drugs and autoimmune disease, which can predict the progression of tumor cells and the state of healthy cells.
The immune system is the body's defense against pathogens, which are complex living organisms found in many parts in the body including organs, tissues, cells, molecules, and proteins. When the immune system works properly, it can recognize and kill the abnormal cells and the infected cells. Otherwise, it can attack the body's healthy cells even if there is no invader. Many researchers have developed immunotherapy (or cancer vaccines) and have used chemotherapy for cancer treatment that can kill fast-growing cancer cells or at least slow down tumor growth. However, chemotherapy drugs travel throughout the body and tend to kill both healthy cells and cancer cells. In this study, we consider the fact that chemotherapy can kill tumor cells and that the loss of the immune cells may at the same time stir up cancer growth. We present a dynamic time-delay tumor-immune model with the effects of chemotherapy drugs and autoimmune disease. The modeling results can be used to determine the progression of tumor cells in the human body with the effect of chemotherapy, autoimmune diseases, and time delays based on partial differential equations. It can also be used to predict when the tumor viruses' free state can be reached as time progresses, as well as the state of the body's healthy cells as time progresses. We also present a few numerical cases that illustrate that the model can be used to monitor the effects of chemotherapy drug treatment and the growth rate of tumor virus-infected cells and the autoimmune disease.

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