Hu2018 - Dynamics of tumor-CD4+-cytokine-host cells interactions with treatments

  public model
Model Identifier
BIOMD0000000797
Short description
This is a proposed mathematical model describing interactions between tumor cells, CD4+ T cells, cytokines, and host cells within the context of CD4+ T cells inducing tumor regression. A platform is provided to assess the effectiveness of single or combination therapy with CD4+ T cells and/or cytokines.
Format
SBML (L2V4)
Related Publication
  • Dynamics of tumor–CD4+–cytokine–host cells interactions with treatments
  • Hu, X., Jang, S.R.-J.
  • Applied Mathematics and Computation , 3/ 2018 , Volume 321 , pages: 1339-1351 , DOI: 10.1016/j.amc.2017.11.009
  • Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, United States
  • Mathematical models of interactions between tumor cells, CD4+ T cells, cytokines, and host cells are proposed to investigate the role of CD4+ on tumor regression. Our results suggest that host cells along with the mechanism of production of CD4+ T cells play important roles in driving tumor dynamics. Cancer cells can be eradicated if the tumor has a small growth rate and is also not competitive. Treatments by either CD4+, cytokines, or a combination of the two are applied to study their effectiveness. It is concluded that doses of treatments along with the tumor size are critical in determining the fate of the tumor. Tumor cells can be eliminated completely if doses of treatments by cytokine are large. The treatments are in general more effective if the tumor size is smaller. Bistability is observed in all of the models with or without the treatment strategies indicating that there is a window of opportunity for clearing off the tumor cells.
Contributors
Submitter of the first revision: Johannes Meyer
Submitter of this revision: Rahuman Sheriff
Modellers: Rahuman Sheriff, Johannes Meyer

Metadata information

is (2 statements)
BioModels Database MODEL1908150001
BioModels Database BIOMD0000000797

hasProperty (2 statements)
Mathematical Modelling Ontology Ordinary differential equation model
Gene Ontology immune response to tumor cell

isDescribedBy (1 statement)
isDerivedFrom (1 statement)

Curation status
Curated


Connected external resources

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Name Description Size Actions

Model files

Hu2018.xml SBML L2V4 Representation of Hu2018 - Dynamics of tumor–CD4+–cytokine–host cells interactions with treatments 52.23 KB Preview | Download

Additional files

Hu2018.cps COPASI file of Hu2018 - Dynamics of tumor–CD4+–cytokine–host cells interactions with treatments 82.50 KB Preview | Download
Hu2018.sedml SED-ML file of Hu2018 - Dynamics of tumor–CD4+–cytokine–host cells interactions with treatments 2.42 KB Preview | Download

  • Model originally submitted by : Johannes Meyer
  • Submitted: Aug 15, 2019 10:36:31 AM
  • Last Modified: Oct 5, 2021 1:07:59 PM
Revisions
  • Version: 6 public model Download this version
    • Submitted on: Oct 5, 2021 1:07:59 PM
    • Submitted by: Rahuman Sheriff
    • With comment: Automatically added model identifier BIOMD0000000797
  • Version: 3 public model Download this version
    • Submitted on: Aug 15, 2019 10:36:31 AM
    • Submitted by: Johannes Meyer
    • With comment: Automatically added model identifier BIOMD0000000797

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
z Cytokine

Interleukin-2 ; Cytokine
100000.0 item
x Tumor Cells

neoplastic cell
67700.0 item
y CD4 T Cells

CD4-positive helper T cell
1000000.0 item
Reactions
Reactions Rate Parameters
z_Cytokine => compartment*mu_2*z_Cytokine mu_2 = 34.0
=> z_Cytokine compartment*I_2 I_2 = 0.0
x_Tumor_Cells => ; w_Healthy_Tissue compartment*delta_1*x_Tumor_Cells*w_Healthy_Tissue delta_1 = 1.1E-10
x_Tumor_Cells => ; z_Cytokine compartment*c_1*x_Tumor_Cells*z_Cytokine/(a_1+x_Tumor_Cells) a_1 = 100000.0; c_1 = 0.2
=> y_CD4_T_Cells compartment*I_1 I_1 = 0.0
=> x_Tumor_Cells compartment*r_1*x_Tumor_Cells*(1-b_1*x_Tumor_Cells) r_1 = 0.514; b_1 = 1.02E-9
=> y_CD4_T_Cells; x_Tumor_Cells, z_Cytokine compartment*beta_1*x_Tumor_Cells*z_Cytokine/(alpha_1+x_Tumor_Cells) beta_1 = 0.835; alpha_1 = 1000.0
y_CD4_T_Cells => compartment*mu_1*y_CD4_T_Cells mu_1 = 0.1
=> z_Cytokine; x_Tumor_Cells, y_CD4_T_Cells compartment*beta_2*x_Tumor_Cells*y_CD4_T_Cells/(alpha_2+x_Tumor_Cells) beta_2 = 5.4; alpha_2 = 1000.0
y_CD4_T_Cells => ; x_Tumor_Cells compartment*delta_2*x_Tumor_Cells*y_CD4_T_Cells delta_2 = 1.0E-7
Curator's comment:
(added: 15 Aug 2019, 10:36:24, updated: 15 Aug 2019, 10:36:24)
Reproduced plot of Figure 1A in the original publication. Parameters and initial conditions are as indicated in the original figure caption. Model simulated and plot produced using COPASI 4.24 (Build 197).