Agent-based Modeling of Tumor and Immune System Interactions in Combinational Therapy with Low-dose 5-fluorouracil and Dendritic Cell Vaccine in Melanoma B16F10

Abstract

This study is designed to present an agent-based model (ABM) to simulate the interactions between tumor cells and the immune system in the melanoma model. The Myeloid-derived Suppressor Cells (MDSCs) and dendritic cells (DCs) are considered in this model as immunosuppressive and antigen-presenting agents respectively.The animal experiment was performed on 68 B16F10 melanoma tumor-bearing C57BL/6 female mice to collect dynamic data for ABM implementation and validation. Animals were divided into 4 groups; group 1 was control (no treatment) while groups 2 and 3 were treated with DC vaccine and low-dose 5- fluorouracil (5-FU) respectively and group 4 was treated with both DC Vaccine and low-dose of 5-FU. The tumor growth rate, number of MDSC, and presence of CD8+/CD107a+ T cells in the tumor microenvironment were evaluated in each group. Firstly, the tumor cells, the effector immune cells, DCs, and the MDSCs have been considered as the agents of the ABM model and their interaction methods have been extracted from the literatureand implemented in the model. Then, the model parameters were estimated by the dynamic data collected from animal experiments.To validate the ABM model, the simulation results were compared with the real data. The results show that the dynamics of the model agents can mimic the relations among considered immune system components to an emergent outcome compatible with real data. The simplicity of the proposed model can help to understand the results of the combinational therapy and make this model a useful tool for studying different scenarios and assessing the combinational results.Determining the role of each component helps to find critical times during tumor progression and change the tumor and immune system balance in favor of the immune system.

The effects of dendritic cell-based vaccines in the tumor microenvironment: Impact on myeloid-derived suppressor cells

“…5-FU in combination with a DC vaccine showed a greater MDSC reduction and improved survival rates in melanoma-bearing mice compared with DC vaccination alone (which maintained MDSC levels), and/or 5-FU alone (which significantly depleted MDSCs, although survival rates were lower compared to the combinatorial treatment) ( 50 ). Interestingly, these schedules were used in a melanoma-bearing mice to stablish an agent-based model to simulate the interactions between tumor and immune cells, as well as comparing different scenarios to determine the role of each component (including MDSCs) during tumor progression ( 69 ).…”

PhysiPKPD: A pharmacokinetics and pharmacodynamics module for PhysiCell

“…Many agent-based models (ABMs) have been developed to study diseases, including cancer [3, 4, 5, 6, 7, 8], COVID-19 [9], tuberculosis [10, 11], and more, with a core purpose being to determine the best means to treat a patient with the given disease. This involves modeling therapeutics alongside the cells in a given microenvironment.…”

Wireless sequential dual light delivery for programmed PDT in vivo

“…Here, we employed an agent-based digital simulation that could model the complex relationships among the factors based on our in vitro experimental results and calculate the priority of each factor for the PDT treatment efficacy, providing data for a clearer understanding of parameters that yield optimum PDT results. Agent-based simulation is a form of machine learning-based inference modeling that has been successfully used to predict brain cancer response to tyrosine kinase inhibitors (TKIs) and to simulate the dynamics between melanoma tumor cells and the immune system in their response to dendritic cell vaccine and 5-fluorouracil co-treatment 21 , 22 . In our PDT treatment strategy, agents execute various events based on the system they represent: cells, photosensitizers, and light.…”