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BIOMD0000000453
name: Bidkhori2012 - EGFR signalling in NSCLC
rule: repeatedAssignment mw9ad3b187 ae05 4fe5 b1b0 26291d323afa
curated: true
notes: Bidkhori2012 - EGFR signalling in NSCLC The paper describes and compares two models on EGFR signalling between normal and NSCLC cells. Moreover, it is shown that ERK (MAPK), STAT and Akt factor's activation pattern are different between normal and NSCLA models. This model corresponds to EGFR signalling in NSCLA cells. Created by The MathWorks, Inc. SimBiology tool, Version 3.3 This model is described in the article: Modeling of tumor progression in NSCLC and intrinsic resistance to TKI in loss of PTEN expression. Bidkhori G, Moeini A, Masoudi-Nejad A PloS one [2012, 7(10):e48004] Abstract: EGFR signaling plays a very important role in NSCLC. It activates Ras/ERK, PI3K/Akt and STAT activation pathways. These are the main pathways for cell proliferation and survival. We have developed two mathematical models to relate to the different EGFR signaling in NSCLC and normal cells in the presence or absence of EGFR and PTEN mutations. The dynamics of downstream signaling pathways vary in the disease state and activation of some factors can be indicative of drug resistance. Our simulation denotes the effect of EGFR mutations and increased expression of certain factors in NSCLC EGFR signaling on each of the three pathways where levels of pERK, pSTAT and pAkt are increased. Over activation of ERK, Akt and STAT3 which are the main cell proliferation and survival factors act as promoting factors for tumor progression in NSCLC. In case of loss of PTEN, Akt activity level is considerably increased. Our simulation results show that in the presence of erlotinib, downstream factors i.e. pAkt, pSTAT3 and pERK are inhibited. However, in case of loss of PTEN expression in the presence of erlotinib, pAkt level would not decrease which demonstrates that these cells are resistant to erlotinib. This model is hosted on BioModels Database and identified by: MODEL1304020001 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published q…
is: MODEL1304020001
type: SBMLModel
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value: 1.0
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stoichiometry: 1.0
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value: 10.0
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stoichiometry: 1.0
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http://identifiers.org/biomodels.db/BIOMD0000000453#f700600d_38eb_493a_a93c_3bffc6a6b234
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reversible: true

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value: 0.033
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value: 20.0
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value: 1.0
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value: 3.114
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reversible: true
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value: 1.0
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value: 0.6
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http://identifiers.org/biomodels.db/BIOMD0000000453#_45042a8c_4349_4134_9983_a3c385ab71e3
value: 0.0426
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type: Reaction
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http://identifiers.org/biomodels.db/BIOMD0000000453#_2dc9c33b_1cd7_48cf_8826_4d3595d8f518
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