TY - JOUR
T1 - An extended mathematical model of tumor growth and its interaction with the immune system, to be used for developing an optimized immunotherapy treatment protocol
AU - Qomlaqi, Milad
AU - Bahrami, Fariba
AU - Ajami, Maryam
AU - Hajati, Jamshid
N1 - Publisher Copyright:
© 2017 Elsevier Inc.
PY - 2017/10
Y1 - 2017/10
N2 - Background Chemotherapy is usually known as the main modality for cancer treatment. Nevertheless, most of chronic cancers could not be treated with chemotherapy alone. Immunotherapy is a new modality for cancer treatment that is effective for early stages of cancer and it has fewer side effects compared to chemotherapy, specifically for those types of cancer that are resistant to it. Method This work presents an extended mathematical model to depict interactions between cancerous and adaptive immune system in mouse. We called the model an extended model, because we embedded all those compartments that have important roles in response to tumor in one model. The model includes tumor cells, natural killers, naïve and mature cytotoxic T cells, naïve and mature helper T cells, regulatory T cells, dendritic cells and interleukin 2 cytokine. Whole cycle of cell division program of immune cells is also considered in the model. We also optimized protocol of immunotherapy with DC vaccine based on the proposed mathematical model. Result Simulation results of the proposed model are in conformity with the experimental data recorded from mouse in immunology department of Tehran University of Medical Science as well as what has been explained in the literature. Our results explain dynamics of the immune cells from the first day of cancer growth and progression. Simulation result shows that reducing intervals between immunotherapy injections, efficacy of the treatment will be increased because CD8+ cells are boosted more rapidly. Optimized protocol for immunotherapy suggests that if the effect of DC vaccines on increasing number of anti-tumor immune cells be just before the maximum number of CD8+ cells, the effect of treatment will be maximized.
AB - Background Chemotherapy is usually known as the main modality for cancer treatment. Nevertheless, most of chronic cancers could not be treated with chemotherapy alone. Immunotherapy is a new modality for cancer treatment that is effective for early stages of cancer and it has fewer side effects compared to chemotherapy, specifically for those types of cancer that are resistant to it. Method This work presents an extended mathematical model to depict interactions between cancerous and adaptive immune system in mouse. We called the model an extended model, because we embedded all those compartments that have important roles in response to tumor in one model. The model includes tumor cells, natural killers, naïve and mature cytotoxic T cells, naïve and mature helper T cells, regulatory T cells, dendritic cells and interleukin 2 cytokine. Whole cycle of cell division program of immune cells is also considered in the model. We also optimized protocol of immunotherapy with DC vaccine based on the proposed mathematical model. Result Simulation results of the proposed model are in conformity with the experimental data recorded from mouse in immunology department of Tehran University of Medical Science as well as what has been explained in the literature. Our results explain dynamics of the immune cells from the first day of cancer growth and progression. Simulation result shows that reducing intervals between immunotherapy injections, efficacy of the treatment will be increased because CD8+ cells are boosted more rapidly. Optimized protocol for immunotherapy suggests that if the effect of DC vaccines on increasing number of anti-tumor immune cells be just before the maximum number of CD8+ cells, the effect of treatment will be maximized.
KW - Cancer
KW - Immune system
KW - Immunotherapy
KW - Mathematical model
KW - Optimization
KW - Tumor
UR - http://www.scopus.com/inward/record.url?scp=85024485951&partnerID=8YFLogxK
U2 - 10.1016/j.mbs.2017.07.006
DO - 10.1016/j.mbs.2017.07.006
M3 - Article
C2 - 28713023
AN - SCOPUS:85024485951
SN - 0025-5564
VL - 292
SP - 1
EP - 9
JO - Mathematical Biosciences
JF - Mathematical Biosciences
ER -