Kogan2013 - A mathematical model for the immunotherapeutic control of the TH1 TH2 imbalance in melanoma

  public model
Model Identifier
BIOMD0000000881
Short description 
This is a mathematical model describing the imbalance between T helper (Th1/Th2) cell types in melanome patients, together with its regulation via IL-12 treatment. The model focuses on the interactions between the two T helper cell types as mediated by their respective key cytokines, interferon gamma and IL-10.
Format
SBML (L2V4)
Related Publication
  • A mathematical model for the immunotherapeutic control of the TH1/TH2 imbalance in melanoma
  • Kogan, Y., Agur, Z., Elishmereni, M.
  • Discrete and Continuous Dynamical Systems - Series B , 6/ 2016 , Volume 18 , Issue 4 , pages: 1017-1030 , DOI: 10.3934/dcdsb.2013.18.1017
  • 10 Hate'ena St., Bene Ataroth 60991, Israel
  • Aggressive cancers develop immune suppression mechanisms, allowing them to evade specific immune responses. Patients with active melanoma are polarized towards a T helper (Th) 2-type immune phenotype, which subverts effective anticancer Th1-type cellular immunity. The pro-inammatory factor, interleukin (IL)-12, can potentially restore Th1 responses in such patients, but still shows limited clinical efficacy and substantial side effects. We developed a model for the Th1/Th2 imbalance in melanoma patients and its regulation via IL-12 treatment. The model focuses on the interactions between the two Th cell types as mediated by their respective key cytokines, interferon (IFN)-γ and IL-10. Theoretical and numerical analysis showed a landscape consisting of a single, globally attracting steady state, which is stable under large ranges of relevant parameter values. Our results suggest that in melanoma, the cellular arm of the immune system cannot reverse tumor immunotolerance naturally, and that immunotherapy may be the only way to overturn tumor dominance. We have shown that given a toxicity threshold for IFNγ, the maximal allowable IL-12 concentration to yield a Th1-polarized state can be estimated. Moreover, our analysis pinpoints the IL-10 secretion rate as a significant factor inuencing the Th1:Th2 balance, suggesting its use as a personal immunomarker for prognosis.
Contributors
Submitter of the first revision: Johannes Meyer
Submitter of this revision: Johannes Meyer
Modellers: Johannes Meyer

Metadata information

hasProperty (3 statements)
Mathematical Modelling Ontology Ordinary differential equation model
NCIt Interferon Gamma
NCIt Interleukin-10

Curation status
Curated
Modelling approach(es)
ordinary differential equation model
Tags
Immuno-oncology

Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files
Kogan2013.xml SBML L2V4 Representation of Kogan2013 - A mathematical model for the immunotherapeutic control of the TH1 TH2 imbalance in melanoma 49.23 KB Preview | Download

Additional files
Kogan2013.cps COPASI file of Kogan2013 - A mathematical model for the immunotherapeutic control of the TH1 TH2 imbalance in melanoma 94.51 KB Preview | Download
Kogan2013.sedml SED-ML file of Kogan2013 - A mathematical model for the immunotherapeutic control of the TH1 TH2 imbalance in melanoma 6.13 KB Preview | Download

  • Model originally submitted by : Johannes Meyer
  • Submitted: Dec 2, 2019 10:02:35 AM
  • Last Modified: Dec 2, 2019 10:02:35 AM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Dec 2, 2019 10:02:35 AM
    • Submitted by: Johannes Meyer
    • With comment: Automatically added model identifier BIOMD0000000881
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
G

Interferon Gamma 		1.0 item
T 1

T-helper 1 cell 		500000.0 item
I

Interleukin-10 		1.0 item
T 2

T-helper 2 cell 		1000000.0 item
Reactions
Reactions Rate Parameters
G => compartment*mu_G*G mu_G = 0.6
=> G compartment*p_G*(1+c_G*L/(L+d_G)) c_G = 12.0; L = 0.0; d_G = 0.05; p_G = 0.016
T_1 => compartment*mu_T*T_1 mu_T = 0.001
=> I; G compartment*p_I*(a_I+(1-a_I)*b_I/(G+b_I)) a_I = 0.12; p_I = 0.5; b_I = 0.025
=> T_2; G compartment*(c_2+(1-c_2)*d_1/(L+d_1))*r_T*b_2/(b_2+G) c_2 = 0.1; L = 0.0; r_T = 1000.0; b_2 = 0.18; d_1 = 0.8
=> G; T_1, I compartment*q_G*T_1*(a_G+(1-a_G)*b_G/(I+b_G))*(1+e_G*L/(L+f_G)) L = 0.0; q_G = 1.0E-7; b_G = 0.13; f_G = 0.22; a_G = 0.59; e_G = 5.4
=> T_1; I compartment*(1+c_1*L/(L+d_1))*r_T*b_1/(b_1+I) c_1 = 30.0; L = 0.0; r_T = 1000.0; b_1 = 0.35; d_1 = 0.8
I => compartment*mu_I*I mu_I = 0.36
T_2 => compartment*mu_T*T_2 mu_T = 0.001
=> I; T_2 compartment*q_I*T_2 q_I = 1.0E-7
Curator's comment:
(added: 02 Dec 2019, 10:02:26, updated: 02 Dec 2019, 10:02:26)
Reproduced plot of Figure 3(B) in the original publication. Model simulated and plot produced using COPASI 4.24 (Build 197).