title: CD8(+) T cell response to adenovirus vaccination and subsequent suppression of tumor growth: modeling, simulation and analysis.
abstract: 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.
authors.affiliation: Department of Computer Sciences, Mathematics, and Engineering, Shepherd University, Shepherdstown, 25443, WV, USA. qwang@shepherd.edu.
authors.forename: Qing
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Department of Chemical Engineering and Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, 25606, WV, USA. david.klinke@mail.wvu.edu.|Department of Microbiology, Immunology, & Cell Biology, West Virginia University, Morgantown, 25606, WV, USA. david.klinke@mail.wvu.edu.
authors.forename: David J
authors.initials: DJ
authors.lastname: Klinke
authors.affiliation: Department of Computer Sciences, Mathematics, and Engineering, Shepherd University, Shepherdstown, 25443, WV, USA. zwang@shepherd.edu.
authors.forename: Zhijun
authors.initials: Z
authors.lastname: Wang
mesh_terms: D000256:Adenoviridae / Q000235:genetics / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D000951:Antigens, Neoplasm / Q000276:immunology; D018414:CD8-Positive T-Lymphocytes / Q000276:immunology* / Q000378:metabolism; D019496:Cancer Vaccines / Q000276:immunology*; D049109:Cell Proliferation; D006801:Humans; D007371:Interferon-gamma / Q000378:metabolism; D008546:Melanoma, Experimental / Q000276:immunology* / Q000473:pathology* / Q000517:prevention & control / Q000821:virology; D051379:Mice; D008954:Models, Biological; D059016:Tumor Microenvironment / Q000276:immunology; D014409:Tumor Necrosis Factor-alpha / Q000378:metabolism; D014611:Vaccination
chemical_list: D000951:Antigens, Neoplasm; D019496:Cancer Vaccines; D014409:Tumor Necrosis Factor-alpha; D007371:Interferon-gamma