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Dendritic cells (DCs), professional antigen-presenting cells that process and deliver antigens using MHC II/I molecules, can be enhanced in numerous ways. Exosomes derived from heat‐ shocked tumor cells (HS‐TEXs) contain high amounts of heat-shock proteins (HSPs). HSPs, as chaperons, can induce DC maturation. This study aimed to investigate whether HS‐TEXs can promote DC maturation. To generate DC, bone marrow-derived cells were treated with Interleukin-4 and GM-CSF. Exosomes were isolated from heat-treated CT-26 cells. The expression level of HSP in exosomes was checked by western blot and the increase in the expression of this protein was observed. Then, HS‐TEXs were co-cultured with iDCs to determine DC maturity, and then DCs were co-cultured with lymphocytes to determine DC activity. Our results showed that DCs treated with HS‐TEXs express high levels of molecules involved in DC maturation and function including MHCII, CD40, CD83, and CD86. HS‐TEXs caused phenotypic and functional maturation of DCs. In addition, flow cytometric results reflected a higher proliferative response of lymphocytes in the iDC / Tex + HSP group. HS‐TEXs could be used as a strategy to improve DC maturation and activation. [ABSTRACT FROM AUTHOR]

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 literature and 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. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated that maturation of dendritic cells (DCs) by pathogenic components through pathogen-associated molecular patterns (PAMPs) such as Listeria monocytogenes lysate (LML) or CpG DNA can improve cancer vaccination in experimental models. In this study, a mathematical model based on an artificial neural network (ANN) was used to predict several patterns and dosage of matured DC administration for improved vaccination. The ANN model predicted that repeated co-injection of tumor antigen (TA)-loaded DCs matured with CpG (CpG-DC) and LML (List-DC) results in improved antitumor immune response as well as a reduction of immunosuppression in the tumor microenvironment. In the present study, we evaluated the ANN prediction accuracy about DC-based cancer vaccines pattern in the treatment of Wehi164 fibrosarcoma cancer-bearing mice. Our results showed that the administration of the DC vaccine according to ANN predicted pattern, leads to a decrease in the rate of tumor growth and size and augments CTL effector function. Furthermore, gene expression analysis confirmed an augmented immune response in the tumor microenvironment. Experimentations justified the validity of the ANN model forecast in the tumor growth and novel optimal dosage that led to more effective treatment.