Mathematical model that describes breast cancer and immune interactions were presented using system of differential equations to provide analytic and nnmeric framework of cancer-immune dynamics. Four types of immune c...Mathematical model that describes breast cancer and immune interactions were presented using system of differential equations to provide analytic and nnmeric framework of cancer-immune dynamics. Four types of immune cells-CTLs （cytotoxic T lymphocytes）, macrophages, NK （natural killer） and helper T cells-known to play the most significant roles in developing breast cancer immunity were modeled using differential equations. The model was then applied to different cancer growth rates and simulated using MATLAB software tool. The parameters of the model were based on experimental and clinical results from published articles. Results supported clinical studies that maximal breast cancer immunity depends mostly on each of the four immune cell types chosen. It was observed that for a given breast cancer growth rate, there was an optimal activation that maximized the response of the immune system. The effectiveness of the immune system resulted in the decrease in breast cancer killing rates. These results highlighted the importance of immune system activations in breast cancer development and treatment. Therefore, the model and its simulation provided a robust framework to better understand breast cancer progression and response to the immune system.展开更多
Objective The aim of the study was to explore the difference between immune cell subsets during the incubation of cytokine-induced kill cells （CIKs） from patients with and without hepatitis B virus （HBV）. Methods ...Objective The aim of the study was to explore the difference between immune cell subsets during the incubation of cytokine-induced kill cells （CIKs） from patients with and without hepatitis B virus （HBV）. Methods Peripheral blood samples were extracted from 50 tumor patients, and were divided into two groups according to the presence or absence of HBV. The proliferation rate and activity of CIK cells were examined based on counts on days 1, 5, 7, 9, 11, 13, and 15 of culture. Additionally, the CD3＋, CD4＋, CD8＋, CD3＋CD8＋, C＋）3＋CD4＋, and CD3＋CD56＋ T cell populations were analyzed by flow cytometry on days 5, 7, 10, 13, and 15 of culture. Results Proliferation over a 15-day period was higher in the HBV-positive group than in the negative group （280-fold vs. 180-fold increase, respectively）, but there was no significant difference between the two groups at each time point. The frequencies of CD3＋, CD8＋ T, CD3＋CD8＋, and CD3＋CD56＋T cells increased over time, while those of CD4＋ and CD3＋CD4＋ T cells decreased over time, and these changes were greater in the positive group than in the negative group. The differences in CD8＋ T cells and CD3＋CD4＋ T cells between the two groups were significant （P 〈 0.05）. Conclusion The proliferative capacity of CIK cells was higher for patients in the HBV-positive group than those in the HBV-negative group, and immune cell subsets were more favorable in the HBV-positive group than the neaative arouD.展开更多
文摘Mathematical model that describes breast cancer and immune interactions were presented using system of differential equations to provide analytic and nnmeric framework of cancer-immune dynamics. Four types of immune cells-CTLs （cytotoxic T lymphocytes）, macrophages, NK （natural killer） and helper T cells-known to play the most significant roles in developing breast cancer immunity were modeled using differential equations. The model was then applied to different cancer growth rates and simulated using MATLAB software tool. The parameters of the model were based on experimental and clinical results from published articles. Results supported clinical studies that maximal breast cancer immunity depends mostly on each of the four immune cell types chosen. It was observed that for a given breast cancer growth rate, there was an optimal activation that maximized the response of the immune system. The effectiveness of the immune system resulted in the decrease in breast cancer killing rates. These results highlighted the importance of immune system activations in breast cancer development and treatment. Therefore, the model and its simulation provided a robust framework to better understand breast cancer progression and response to the immune system.
文摘Objective The aim of the study was to explore the difference between immune cell subsets during the incubation of cytokine-induced kill cells （CIKs） from patients with and without hepatitis B virus （HBV）. Methods Peripheral blood samples were extracted from 50 tumor patients, and were divided into two groups according to the presence or absence of HBV. The proliferation rate and activity of CIK cells were examined based on counts on days 1, 5, 7, 9, 11, 13, and 15 of culture. Additionally, the CD3＋, CD4＋, CD8＋, CD3＋CD8＋, C＋）3＋CD4＋, and CD3＋CD56＋ T cell populations were analyzed by flow cytometry on days 5, 7, 10, 13, and 15 of culture. Results Proliferation over a 15-day period was higher in the HBV-positive group than in the negative group （280-fold vs. 180-fold increase, respectively）, but there was no significant difference between the two groups at each time point. The frequencies of CD3＋, CD8＋ T, CD3＋CD8＋, and CD3＋CD56＋T cells increased over time, while those of CD4＋ and CD3＋CD4＋ T cells decreased over time, and these changes were greater in the positive group than in the negative group. The differences in CD8＋ T cells and CD3＋CD4＋ T cells between the two groups were significant （P 〈 0.05）. Conclusion The proliferative capacity of CIK cells was higher for patients in the HBV-positive group than those in the HBV-negative group, and immune cell subsets were more favorable in the HBV-positive group than the neaative arouD.
