Tehran University of Medical Sciences Iranian Journal of Allergy, Asthma and Immunology 1735-1502 19 2 2020 04 16 172 182 Zahra Mirsanei Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Sima Habibi Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Nasim Kheshtchin Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Reza Mirzaei Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Samaneh Arab Nervous System Stem Cells Research Center, Semnan University of Medical Sciences, Semnan, Iran AND Department of Tissue Engineering and Applied Cell Sciences, School of Medicine, Semnan University of Medical Sciences, Semnan, Iran Bahareh Zand Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Farhad Jadidi-Niaragh Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran Aida Safvati Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Ehsan Sharif-Paghaleh Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran AND Division of Imaging Sciences and Biomedical Engineering, Faculty of Life Sciences and Medicine, St Thomas’ Hospital, King’s College London, London, England Abazar Arabameri Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran Davud Asemani Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran AND Division of Pediatrics, Liposomal Cancer Therapy, Medical University of South Carolina, Charleston, SC, USA Jamshid Hajati Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran AND Cancer Biology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran 2019 07 15 2019 08 13 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. https://ijaai.tums.ac.ir/index.php/ijaai/article/view/2462