Ito2019 - gefitnib resistance of lung adenocarcinoma caused by MET amplification

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Model Identifier
BIOMD0000000827
Short description
The model is based on publication: Mathematical analysis of gefitinib resistance of lung adenocarcinoma caused by MET amplification Abstract: Gefitinib, one of the tyrosine kinase inhibitors of epidermal growth factor receptor (EGFR), is effective for treating lung adenocarcinoma harboring EGFR mutation; but later, most cases acquire a resistance to gefitinib. One of the mechanisms conferring gefitinib resistance to lung adenocarcinoma is the amplification of the MET gene, which is observed in 5–22% of gefitinib-resistant tumors. A previous study suggested that MET amplification could cause gefitinib resistance by driving ErbB3-dependent activation of the PI3K pathway. In this study, we built a mathematical model of gefitinib resistance caused by MET amplification using lung adenocarcinoma HCC827-GR (gefitinib resistant) cells. The molecular reactions involved in gefitinib resistance consisted of dimerization and phosphorylation of three molecules, EGFR, ErbB3, and MET were described by a series of ordinary differential equations. To perform a computer simulation, we quantified each molecule on the cell surface using flow cytometry and estimated unknown parameters by dimensional analysis. Our simulation showed that the number of active ErbB3 molecules is around a hundred-fold smaller than that of active MET molecules. Limited contribution of ErbB3 in gefitinib resistance by MET amplification is also demonstrated using HCC827-GR cells in culture experiments. Our mathematical model provides a quantitative understanding of the molecular reactions underlying drug resistance.
Format
SBML (L2V4)
Related Publication
  • Mathematical analysis of gefitinib resistance of lung adenocarcinoma caused by MET amplification.
  • Ito T, Kumagai Y, Itano K, Maruyama T, Tamura K, Kawasaki S, Suzuki T, Murakami Y
  • Biochemical and biophysical research communications , 4/ 2019 , Volume 511 , Issue 3 , pages: 544-550 , PubMed ID: 30824185
  • Division of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
  • Gefitinib, one of the tyrosine kinase inhibitors of epidermal growth factor receptor (EGFR), is effective for treating lung adenocarcinoma harboring EGFR mutation; but later, most cases acquire a resistance to gefitinib. One of the mechanisms conferring gefitinib resistance to lung adenocarcinoma is the amplification of the MET gene, which is observed in 5-22% of gefitinib-resistant tumors. A previous study suggested that MET amplification could cause gefitinib resistance by driving ErbB3-dependent activation of the PI3K pathway. In this study, we built a mathematical model of gefitinib resistance caused by MET amplification using lung adenocarcinoma HCC827-GR (gefitinib resistant) cells. The molecular reactions involved in gefitinib resistance consisted of dimerization and phosphorylation of three molecules, EGFR, ErbB3, and MET were described by a series of ordinary differential equations. To perform a computer simulation, we quantified each molecule on the cell surface using flow cytometry and estimated unknown parameters by dimensional analysis. Our simulation showed that the number of active ErbB3 molecules is around a hundred-fold smaller than that of active MET molecules. Limited contribution of ErbB3 in gefitinib resistance by MET amplification is also demonstrated using HCC827-GR cells in culture experiments. Our mathematical model provides a quantitative understanding of the molecular reactions underlying drug resistance.
Contributors
Submitter of the first revision: Szeyi Ng
Submitter of this revision: Szeyi Ng
Modellers: Szeyi Ng

Metadata information

is (2 statements)
BioModels Database BIOMD0000000827
BioModels Database MODEL1909300001

isDescribedBy (1 statement)
PubMed 30824185

hasProperty (3 statements)
NCIt Gefitinib
NCIt Lung
NCIt Adenocarcinoma

isPropertyOf (2 statements)
Mathematical Modelling Ontology Ordinary differential equation model
Experimental Factor Ontology cancer


Curation status
Curated


Tags

Connected external resources

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Model files

Ito2019 - gefitnib resistance of lung adenocarcinoma caused by MET amplification.xml SBML L2V4 file for the model 55.84 KB Preview | Download

Additional files

Fig 3.png PNG plot of the model simulation Figure 3 100.55 KB Preview | Download
Ito2019 - gefitnib resistance of lung adenocarcinoma caused by MET amplification.cps COPASI 4.24 (Build 197) file for the model 78.17 KB Preview | Download

  • Model originally submitted by : Szeyi Ng
  • Submitted: Sep 30, 2019 9:43:41 AM
  • Last Modified: Sep 30, 2019 9:43:41 AM
Revisions
  • Version: 3 public model Download this version
    • Submitted on: Sep 30, 2019 9:43:41 AM
    • Submitted by: Szeyi Ng
    • With comment: Automatically added model identifier BIOMD0000000827
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
X 10 p MET MET

Combination ; Met-Met
0.0 mmol
X 4 EGFR EGFR

Combination ; CCO:1956
0.0 mmol
X 8 p EGFR ErbB3

CCO:13867 ; CCO:1956 ; Combination
0.0 mmol
X 6 ErbB3 ErbB3

CCO:13867 ; Combination
0.0 mmol
X 1 EGFR

CCO:1956
3.6E-12 mmol
X 5 EGFR ErbB3

Combination ; CCO:1956 ; CCO:13867
0.0 mmol
X 2 ErbB3

CCO:13867
5.5E-14 mmol
X 3 MET

CCO:2065
7.4E-12 mmol
Reactions
Reactions Rate Parameters
X_7_MET_MET => X_10_p_MET_MET compartment*(k_p1*X_7_MET_MET-l_p1*X_10_p_MET_MET) k_p1 = 0.045; l_p1 = 0.028
X_1_EGFR => X_4_EGFR_EGFR compartment*(0.5*k_1*X_1_EGFR^2-l_1*X_4_EGFR_EGFR) l_1 = 1.24; k_1 = 2.3E10
X_8_p_EGFR_ErbB3 => X_5_EGFR_ErbB3 compartment*l_p2*X_8_p_EGFR_ErbB3 l_p2 = 0.028
X_2_ErbB3 => X_6_ErbB3_ErbB3 compartment*(0.5*k_2*X_2_ErbB3^2-l_2*X_6_ErbB3_ErbB3) k_2 = 1.9E12; l_2 = 1.08
X_9_p_ErbB3_ErbB3 => X_6_ErbB3_ErbB3 compartment*l_p3*X_9_p_ErbB3_ErbB3 l_p3 = 0.028
X_1_EGFR + X_2_ErbB3 => X_5_EGFR_ErbB3 compartment*(k_3*X_1_EGFR*X_2_ErbB3-l_3*X_5_EGFR_ErbB3) k_3 = 2.4E11; l_3 = 1.0
X_3_MET => X_7_MET_MET compartment*(0.5*k_4*X_3_MET^2-l_4*X_7_MET_MET) k_4 = 2.6E12; l_4 = 1.0
Curator's comment:
(added: 30 Sep 2019, 09:43:14, updated: 30 Sep 2019, 09:43:14)
I reproduced Fig 3 from the publication. I generated the data using COPASI file and plot the figures using matlab.