Hu2019 - Modeling Pancreatic Cancer Dynamics with Immunotherapy

  public model
Model Identifier
BIOMD0000000792
Short description 
This is a mathematical model of pancreatic cancer that includes descriptions of pancreatic cancer cells, pancreatic stellate cells, effector cells and tumor-promoting and tumor-suppressing cytokines to investigate the effects of immunotherapies on patient survival.
Format
SBML (L2V4)
Related Publication
  • Modeling Pancreatic Cancer Dynamics with Immunotherapy.
  • Hu X, Ke G, Jang SR
  • Bulletin of mathematical biology , 6/ 2019 , Volume 81 , Issue 6 , pages: 1885-1915 , PubMed ID: 30843136
  • Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX, 79409-1042, USA.
  • We develop a mathematical model of pancreatic cancer that includes pancreatic cancer cells, pancreatic stellate cells, effector cells and tumor-promoting and tumor-suppressing cytokines to investigate the effects of immunotherapies on patient survival. The model is first validated using the survival data of two clinical trials. Local sensitivity analysis of the parameters indicates there exists a critical activation rate of pro-tumor cytokines beyond which the cancer can be eradicated if four adoptive transfers of immune cells are applied. Optimal control theory is explored as a potential tool for searching the best adoptive cellular immunotherapies. Combined immunotherapies between adoptive ex vivo expanded immune cells and TGF-[Formula: see text] inhibition by siRNA treatments are investigated. This study concludes that mono-immunotherapy is unlikely to control the pancreatic cancer and combined immunotherapies between anti-TGF-[Formula: see text] and adoptive transfers of immune cells can prolong patient survival. We show through numerical explorations that how these two types of immunotherapies are scheduled is important to survival. Applying TGF-[Formula: see text] inhibition first followed by adoptive immune cell transfers can yield better survival outcomes.
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 BIOMD0000000792
BioModels Database MODEL1908130001

isDescribedBy (1 statement)
PubMed 30843136

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

isDerivedFrom (1 statement)
Curation status
Curated
Tags

Connected external resources

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Name Description Size Actions

Model files
Hu2019.xml SBML L2V4 Representation of Hu2019 - Modeling Pancreatic Cancer Dynamics with Immunotherapy 54.79 KB Preview | Download

Additional files
Hu2019.cps COPASI file of Hu2019 - Modeling Pancreatic Cancer Dynamics with Immunotherapy 93.59 KB Preview | Download
Hu2019.sedml SED-ML file of Hu2019 - Modeling Pancreatic Cancer Dynamics with Immunotherapy 1.71 KB Preview | Download

  • Model originally submitted by : Johannes Meyer
  • Submitted: Aug 13, 2019 1:43:31 PM
  • Last Modified: Oct 5, 2021 9:29:38 AM
Revisions
  • Version: 4 public model Download this version
    • Submitted on: Oct 5, 2021 9:29:38 AM
    • Submitted by: Rahuman Sheriff
    • With comment: Automatically added model identifier BIOMD0000000792
  • Version: 2 public model Download this version
    • Submitted on: Aug 13, 2019 1:43:31 PM
    • Submitted by: Johannes Meyer
    • With comment: Automatically added model identifier BIOMD0000000792

(*) 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
w TPC

Interleukin-6 ; Transforming growth factor beta 1 ; Cytokine 		50000.0 item
R siRNA

Small Interfering RNA 		1.0 item
z Effector Cells

Effector Immune Cell 		1.9E8 item
x PCC

EFO:0002966 ; neoplastic cell 		1.0E9 item
v TSC

Interferon gamma ; Cytokine 		9.4 item
y PSC

pancreatic stellate cell 		5600000.0 item
Reactions
Reactions Rate Parameters
=> w_TPC; x_PCC, z_Effector_Cells compartment*v v=0.1
=> R_siRNA compartment*D_0 D_0 = 5.0E10
=> z_Effector_Cells; v_TSC, w_TPC compartment*beta_3*z_Effector_Cells*v_TSC/((k_3+v_TSC)*(m_3+w_TPC)) beta_3 = 124.5; m_3 = 1000000.0; k_3 = 2.0E10
w_TPC => compartment*mu_4*w_TPC mu_4 = 0.034
=> x_PCC; y_PSC compartment*(r_1+beta_1*y_PSC)*x_PCC*(1-b_1*x_PCC) r_1 = 0.0195; b_1 = 1.02E-11; beta_1 = 1.7857E-12
v_TSC => compartment*mu_5*v_TSC mu_5 = 0.034
y_PSC => compartment*mu_2*y_PSC mu_2 = 0.015
=> y_PSC; w_TPC compartment*(r_2+beta_2*w_TPC/(k_2+w_TPC))*y_PSC*(1-b_2*y_PSC) beta_2 = 0.125; r_2 = 0.00195; k_2 = 5.6E10; b_2 = 1.7857E-9
=> v_TSC; x_PCC, z_Effector_Cells compartment*beta_5*x_PCC*z_Effector_Cells/(k_5+x_PCC) k_5 = 1000000.0; beta_5 = 7.3
x_PCC => ; z_Effector_Cells, w_TPC compartment*delta_1*x_PCC*z_Effector_Cells/(m_1+w_TPC) delta_1 = 0.96; m_1 = 1.0E9
Curator's comment:
(added: 13 Aug 2019, 13:43:19, updated: 13 Aug 2019, 13:43:19)
Reproduced plot of Figure 4A (dashed blue line) in the original publication. Parameters and initial conditions are as specified in the paper. Model simulated and plot produced using COPASI 4.24 (Build 197).