A PROGNOSTIC IMMUNOTHERAPY MODEL FOR 4T1 BREAST CANCER WITH COMBINED CYCLOPHOSPHAMIDE AND TLR AGONIST.

Based on experimental results of a mouse model provided in the literature, we develop a mathematical model by using system biology approach, aiming to investigate immunotherapy for 4T1 breast cancer. It is worth to mention that only 4 types of cells (tumor cells, CD8 + T cells, regular T cells (Tregs), and tumoricidal myeloid CD11b + Gr1dim cells) are quantitatively measured in experiments, which make the immunotherapy modelling more difficult since only limited system knowledge is available. To overcome the difficulty, the mathematical model is proposed by employing Evolutionary Computation to optimize the system parameters. Furthermore, with the mathematical model, analysis can be conducted to capture the inherent properties of the model, such as the number and stability of equilibria, and parameter sensitivity analysis, which disclose the nature of 4T1 breast cancer from a system biological perspective. Not limited to replication of experimental results, we further show that the mathematical model is in fact a prognostic immunotherapy model that can predict treatment outcomes of various cases; for instance, different combinations of drug delivery schedules. By virtue of computational convenience, it is relatively easy to intensively investigate most of the treatments that are impossible for animal models or clinical trials. In other words, a mathematical model based on system biology can provide meaningful reference when exploiting more effective treatment protocols. [ABSTRACT FROM AUTHOR]