dePillis2005 - A validated mathematical model of cell-mediated immune response to tumor growth

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Model Identifier
MODEL1907260001
Short description 
This model describes interactions between a tumour and the immune system, with specific emphasis on the role of natural killer and CD8-positive T cells in tumor surveillance. The model features descriptions of tumor-immune cell interactions using ODEs, which allow the prediction of tumor growth, response, and interaction rates.
Format
SBML (L2V4)
Related Publication
  • A validated mathematical model of cell-mediated immune response to tumor growth.
  • de Pillis LG, Radunskaya AE, Wiseman CL
  • Cancer research , 9/ 2005 , Volume 65 , Issue 17 , pages: 7950-7958 , PubMed ID: 16140967
  • Department of Mathematics, Harvey Mudd College, Claremont, California 91711, USA. depillis@hmc.edu
  • Mathematical models of tumor-immune interactions provide an analytic framework in which to address specific questions about tumor-immune dynamics. We present a new mathematical model that describes tumor-immune interactions, focusing on the role of natural killer (NK) and CD8+ T cells in tumor surveillance, with the goal of understanding the dynamics of immune-mediated tumor rejection. The model describes tumor-immune cell interactions using a system of differential equations. The functions describing tumor-immune growth, response, and interaction rates, as well as associated variables, are developed using a least-squares method combined with a numerical differential equations solver. Parameter estimates and model validations use data from published mouse and human studies. Specifically, CD8+ T-tumor and NK-tumor lysis data from chromium release assays as well as in vivo tumor growth data are used. A variable sensitivity analysis is done on the model. The new functional forms developed show that there is a clear distinction between the dynamics of NK and CD8+ T cells. Simulations of tumor growth using different levels of immune stimulating ligands, effector cells, and tumor challenge are able to reproduce data from the published studies. A sensitivity analysis reveals that the variable to which the model is most sensitive is patient specific, and can be measured with a chromium release assay. The variable sensitivity analysis suggests that the model can predict which patients may positively respond to treatment. Computer simulations highlight the importance of CD8+ T-cell activation in cancer therapy.
Contributors
Submitter of the first revision: Johannes Meyer
Submitter of this revision: Johannes Meyer
Modellers: Johannes Meyer

Metadata information

isDescribedBy (1 statement)
PubMed 16140967

hasTaxon (1 statement)
Taxonomy Mus musculus

isVersionOf (2 statements)
Curation status
Non-curated
Modelling approach(es)
ordinary differential equation model
Tags
Immuno-oncology

Connected external resources

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Model files
dePillis2005.xml SBML L2V4 Representation of dePillis2005 - A validated mathematical model of cell-mediated immune response to tumor growth 54.12 KB Preview | Download

Additional files
dePillis2005.cps COPASI file of dePillis2005 - A validated mathematical model of cell-mediated immune response to tumor growth 82.88 KB Preview | Download
dePillis2005.sedml SED-ML file of dePillis2005 - A validated mathematical model of cell-mediated immune response to tumor growth 1.84 KB Preview | Download

  • Model originally submitted by : Johannes Meyer
  • Submitted: Jul 26, 2019 11:18:41 AM
  • Last Modified: Jul 26, 2019 11:18:41 AM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Jul 26, 2019 11:18:41 AM
    • Submitted by: Johannes Meyer
    • With comment: Updated files with corrected initial condition for N.
Curator's comment:
(added: 26 Jul 2019, 11:17:32, updated: 26 Jul 2019, 11:17:32)
Reproduced plot of Figure 4, bottom left in the original publication. Coefficient used to transform tumor cell number to size was 3e-7. Initial conditions used were L(0) = 0 N(0) = 1000 T(0) = 1000000 (Red), 100 (Blue) Initial condition for blue curve differs from that of original publication (100000 in original).