Nazari2018 - IL6 mediated stem cell driven tumor growth and targeted treatment

  public model
Short description
This a model from the article: A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment Fereshteh Nazari, Alexander T. Pearson, Jacques Eduardo Nor, Trachette L. Jackson. PloS Computational Biology, 2018 Jan. Abstract: Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth. Author Summary: A small population of cancer stem cells that share many of the biological characteristics of normal adult stem cells are believed to initiate and sustain tumor growth for a wide variety of malignancies. Growth and survival of these cancer stem cells is highly influenced by tumor micro-environmental factors and molecular signaling initiated by cytokines and growth factors. This work focuses on quantifying the influence of IL-6, a pleiotropic cytokine secreted by a variety of cell types, on cancer stem cell self-renewal and survival. We present a mathematical model for IL-6 mediated, cancer stem cell driven tumor growth that operates at the following levels: (1) the molecular level—capturing cell surface dynamics of receptor-ligand binding and receptor activation that lead to intra-cellular signal transduction cascades; and (2) the cellular level—describing tumor growth, cellular composition, and response to treatments targeted against IL-6. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
Format
SBML (L2V4)
Related Publication
  • A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment.
  • Nazari F, Pearson AT, Nör JE, Jackson TL
  • PLoS computational biology , 1/ 2018 , Volume 14 , Issue 1 , pages: e1005920
  • Simon A. Levin Mathematical, Computational, and Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.
  • Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth.
Contributors
Szeyi Ng

Metadata information

is
BioModels Database MODEL1909230001
BioModels Database BIOMD0000000819
isDescribedBy
PubMed 29351275
hasProperty
Experimental Factor Ontology cancer
Mathematical Modelling Ontology Ordinary differential equation model
NCIt Interleukin-6
Experimental Factor Ontology head and neck squamous cell carcinoma
NCIt Head and Neck Squamous Cell Carcinoma
NCIt Cancer Stem Cell

Curation status
Curated


Tags
Name Description Size Actions

Model files

Nazari2018 - IL6 mediated stem cell driven tumor growth and targeted treatment.xml SBML L2V4 file for the model 153.67 KB Preview | Download

Additional files

Nazari2018 - IL6 mediated stem cell driven tumor growth and targeted treatment.cps COPASI 4.24 (Build 197) file for the model 194.06 KB Preview | Download
Figure 5.png PNG plot of the model simulation Figure 5 7.40 KB Preview | Download

  • Model originally submitted by : Szeyi Ng
  • Submitted: 23-Sep-2019 15:41:16
  • Last Modified: 02-Oct-2019 13:13:23
Revisions
  • Version: 6 public model Download this version
    • Submitted on: 02-Oct-2019 13:13:23
    • Submitted by: Szeyi Ng
    • With comment: Automatically added model identifier BIOMD0000000819
  • Version: 3 public model Download this version
    • Submitted on: 23-Sep-2019 15:41:16
    • Submitted by: Szeyi Ng
    • With comment: Automatically added model identifier BIOMD0000000819
Legends
: Variable used inside SBML models


Species
No records to display
Reactions
No records to display
Curator's comment:
(added: 23 Sep 2019, 15:40:47, updated: 23 Sep 2019, 15:40:47)
The figure is generated using the uploaded COPASI file data and plotted by Matlab. The red line is when rho=7x10^(-7) 1/day, and blue line is when rho=0 1/day