Optimized Dose of Dendritic Cell-based Vaccination in Experimental Model of Tumor Using Artificial Neural Network

  • 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 Mail 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
Keywords:
Cancer, Cancer vaccines, Dendritic cells, Listeria monocytogenes

Abstract

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.

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Published
2020-04-16
How to Cite
1.
Mirsanei Z, Habibi S, Kheshtchin N, Mirzaei R, Arab S, Zand B, Jadidi-Niaragh F, Safvati A, Sharif-Paghaleh E, Arabameri A, Asemani D, Hajati J. Optimized Dose of Dendritic Cell-based Vaccination in Experimental Model of Tumor Using Artificial Neural Network. Iran J Allergy Asthma Immunol. 19(2):172-182.
Section
Original Article(s)