Qomlaqi Milad, Bahrami Fariba, Ajami Maryam, Hajati Jamshid
CIPCE, Human Motor Control and Computational Neuroscience Lab, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Department of immunology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Math Biosci. 2017 Oct;292:1-9. doi: 10.1016/j.mbs.2017.07.006. Epub 2017 Jul 14.
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.
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.
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.
化疗通常被认为是癌症治疗的主要方式。然而，大多数慢性癌症无法仅通过化疗进行治疗。免疫疗法是一种癌症治疗的新方式，对癌症早期有效，并且与化疗相比副作用更少，特别是对于那些对化疗耐药的癌症类型。
这项工作提出了一个扩展的数学模型来描述小鼠体内癌细胞与适应性免疫系统之间的相互作用。我们称该模型为扩展模型，因为我们将所有在对肿瘤的反应中起重要作用的区室都嵌入到了一个模型中。该模型包括肿瘤细胞、自然杀伤细胞、幼稚和成熟的细胞毒性T细胞、幼稚和成熟的辅助性T细胞、调节性T细胞、树突状细胞和白细胞介素2细胞因子。模型中还考虑了免疫细胞的整个细胞分裂程序周期。我们还基于所提出的数学模型优化了DC疫苗免疫疗法的方案。
所提出模型的模拟结果与德黑兰医科大学免疫学系从小鼠记录的实验数据以及文献中所解释的内容一致。我们的结果解释了从癌症生长和进展第一天起免疫细胞的动态变化。模拟结果表明，缩短免疫疗法注射之间的间隔，治疗效果将会提高，因为CD8 +细胞的增加更为迅速。免疫疗法的优化方案表明，如果DC疫苗对增加抗肿瘤免疫细胞数量的作用恰好在CD8 +细胞数量达到最大值之前，治疗效果将达到最大化。
