CD8 + T cell response to adenovirus vaccination and subsequent suppression of tumor growth: modeling, simulation and analysis

BMC Systems Biology

Zhijun Wang¹  David J Klinke II²  Qing Wang¹ 

[1] Department of Computer Sciences, Mathematics, and Engineering, Shepherd University, Shepherdstown 25443, WV, USA;Department of Microbiology, Immunology, & Cell Biology, West Virginia University, Morgantown 25606, WV, USA

关键词: Impulsive ordinary differential equation;    Modeling;    Vaccination;    Adenovirus;   

Others  :  1233561
DOI  :  10.1186/s12918-015-0168-9

 received in 2014-12-12, accepted in 2015-05-15,  发布年份 2015

【 摘 要 】

Background

Using immune checkpoint modulators in the clinic to increase the number and activity of cytotoxic T lymphocytes that recognize tumor antigens can prolong survival for metastatic melanoma. Yet, only a fraction of the patient population receives clinical benefit. In short, these clinical trials demonstrate proof-of-principle but optimizing the specific therapeutic strategies remains a challenge. In many fields, CAD (computer-aided design) is a tool used to optimize integrated system behavior using a mechanistic model that is based upon knowledge of constitutive elements. The objective of this study was to develop a predictive simulation platform for optimizing anti-tumor immunity using different treatment strategies.

Methods

To better understand the therapeutic role that cytotoxic CD8 ⁺ T cells can play in controlling tumor growth, we developed a multi-scale mechanistic model of the biology using impulsive differential equations and calibrated it to a self-consistent data set.

Results

The multi-scale model captures the activation and differentiation of naïve CD8 ⁺ T cells into effector cytotoxic T cells in the lymph node following adenovirus-mediated vaccination against a tumor antigen, the trafficking of the resulting cytotoxic T cells into blood and tumor microenvironment, the production of cytokines within the tumor microenvironment, and the interactions between tumor cells, T cells and cytokines that control tumor growth. The calibrated model captures the modest suppression of tumor cell growth observed in the B16F10 model, a transplantable mouse model for metastatic melanoma, and was used to explore the impact of multiple vaccinations on controlling tumor growth.

Conclusions

Using the calibrated mechanistic model, we found that the cytotoxic CD8 ⁺ T cell response was prolonged by multiple adenovirus vaccinations. However, the strength of the immune response cannot be improved enough by multiple adenovirus vaccinations to reduce tumor burden if the cytotoxic activity or local proliferation of cytotoxic T cells in response to tumor antigens is not greatly enhanced. Overall, this study illustrates how mechanistic models can be used for in silico screening of the optimal therapeutic dosage and timing in cancer treatment.

【 授权许可】

   
2015 Wang et al.; licensee BioMed Central.

【 图 表 】

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