Yakimchuk2019 - Mathematical modeling of immune modulation by glucocorticoids

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Model Identifier
MODEL1912170005
Short description 
Mathematical modeling of immune modulation by glucocorticoids
Konstantin Yakimchuk
https://doi.org/10.1016/j.biosystems.2019.104066

Abstract

The cellular and molecular mechanisms of immunomodulatory actions of glucocorticoids (GC) remain to be identified. Using our experimental findings, a mathematical model based on a system of ordinary differential equations for characterization of the regulation of anti-tumor immune activity by the both direct and indirect GC effects was generated to study the effects of GC treatment on effector CD8+ T cells, GC-generated tolerogenic dendritic cells (DC), regulatory T cells and the growth of lymphoma cells. In addition, we compared the data from in vivo and in silico experiments. The mathematical simulations indicated that treatment with GCs may suppress anti-tumor immune response in a dose-dependent manner. The model simulations were in line with earlier experimental observations of inhibitory effects of GCs on T and NK cells and DCs. The results of this study might be useful for predicting clinical outcomes in patients receiving GC therapy.
Format
SBML (L2V4)
Related Publication
  • Mathematical modeling of immune modulation by glucocorticoids.
  • Yakimchuk K
  • Bio Systems , 11/ 2019 , Volume 187 , pages: 104066 , PubMed ID: 31734335
  • Department of Biosciences and Nutrition, Karolinska Institutet, Neo, SE-141 83 Huddinge, Sweden. Electronic address: konstantin.yakimchuk@ki.se.
  • The cellular and molecular mechanisms of immunomodulatory actions of glucocorticoids (GC) remain to be identified. Using our experimental findings, a mathematical model based on a system of ordinary differential equations for characterization of the regulation of anti-tumor immune activity by the both direct and indirect GC effects was generated to study the effects of GC treatment on effector CD8+ T cells, GC-generated tolerogenic dendritic cells (DC), regulatory T cells and the growth of lymphoma cells. In addition, we compared the data from in vivo and in silico experiments. The mathematical simulations indicated that treatment with GCs may suppress anti-tumor immune response in a dose-dependent manner. Our in silico results were in line with our earlier experimental findings of inhibitory effects of GCs on T, NK and dendritic cells. The model simulations were in line with earlier experimental observations of inhibitory effects of GCs on T and NK cells and DCs. The results of this study might be useful for predicting clinical outcomes in patients receiving GC therapy.
Contributors
Submitter of the first revision: Mohammad Umer Sharif Shohan
Submitter of this revision: Mohammad Umer Sharif Shohan
Modellers: Mohammad Umer Sharif Shohan

Metadata information

Curation status
Non-curated
Tags
Immuno-oncology

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Model files
Yakimchuk2019.xml SBML L2V4 Yakimchuk et al. 2019 Mathematical modeling of immune modulation by glucocorticoids 36.05 KB Preview | Download

Additional files
Yakimchuk2019.cps COPASI version 4.24 (Build 197) Yakimchuk et al. 2019 "Mathematical modeling of immune modulation by glucocorticoids" 85.64 KB Preview | Download

  • Model originally submitted by : Mohammad Umer Sharif Shohan
  • Submitted: Jan 6, 2020 10:27:07 AM
  • Last Modified: Jan 6, 2020 10:27:07 AM
Revisions
  • Version: 3 public model Download this version
    • Submitted on: Jan 6, 2020 10:27:07 AM
    • Submitted by: Mohammad Umer Sharif Shohan
    • With comment: Edited model metadata online.