Faratian2009 - Role of PTEN in Trastuzumab resistance

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Short description
Faratian2009 - Role of PTEN in Trastuzumab resistance

This model is described in the article:

Faratian D, Goltsov A, Lebedeva G, Sorokin A, Moodie S, Mullen P, Kay C, Um IH, Langdon S, Goryanin I, Harrison DJ.
Cancer Res. 2009 Aug; 69(16): 6713-6720

Abstract:

Resistance to targeted cancer therapies such as trastuzumab is a frequent clinical problem not solely because of insufficient expression of HER2 receptor but also because of the overriding activation states of cell signaling pathways. Systems biology approaches lend themselves to rapid in silico testing of factors, which may confer resistance to targeted therapies. Inthis study, we aimed to develop a new kinetic model that could be interrogated to predict resistance to receptor tyrosine kinase (RTK) inhibitor therapies and directly test predictions in vitro and in clinical samples. The new mathematical model included RTK inhibitor antibody binding, HER2/HER3 dimerization and inhibition, AKT/mitogen-activated protein kinase cross-talk, and the regulatory properties of PTEN. The model was parameterized using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays. Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapy in silico, which was predictive of unseen experiments in vitro using the PTEN inhibitor bp(V). When measured in cancer cell lines, PTEN expression predicts sensitivity to anti-HER2 therapy; furthermore, this quantitative measurement is more predictive of response (relative risk, 3.0; 95% confidence interval, 1.6-5.5; P < 0.0001) than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of 122 breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalized therapy in cancer and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti-HER2 therapies.

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Format
SBML (L2V4)
Related Publication
  • Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab.
  • Faratian D, Goltsov A, Lebedeva G, Sorokin A, Moodie S, Mullen P, Kay C, Um IH, Langdon S, Goryanin I, Harrison DJ
  • Cancer research , 8/ 2009 , Volume 69 , pages: 6713-6720
  • University of Edinburgh, Scotland, United Kingdom. d.faratian@ed.ac.uk
  • Resistance to targeted cancer therapies such as trastuzumab is a frequent clinical problem not solely because of insufficient expression of HER2 receptor but also because of the overriding activation states of cell signaling pathways. Systems biology approaches lend themselves to rapid in silico testing of factors, which may confer resistance to targeted therapies. Inthis study, we aimed to develop a new kinetic model that could be interrogated to predict resistance to receptor tyrosine kinase (RTK) inhibitor therapies and directly test predictions in vitro and in clinical samples. The new mathematical model included RTK inhibitor antibody binding, HER2/HER3 dimerization and inhibition, AKT/mitogen-activated protein kinase cross-talk, and the regulatory properties of PTEN. The model was parameterized using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays. Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapy in silico, which was predictive of unseen experiments in vitro using the PTEN inhibitor bp(V). When measured in cancer cell lines, PTEN expression predicts sensitivity to anti-HER2 therapy; furthermore, this quantitative measurement is more predictive of response (relative risk, 3.0; 95% confidence interval, 1.6-5.5; P < 0.0001) than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of 122 breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalized therapy in cancer and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti-HER2 therapies.
Contributors
Galina Lebedeva

Metadata information

is
BioModels Database MODEL1108180000
BioModels Database BIOMD0000000424
isDerivedFrom
BioModels Database BIOMD0000000048
BioModels Database BIOMD0000000146
isDescribedBy
PubMed 19638581
hasTaxon
Taxonomy Homo sapiens
isVersionOf
occursIn
Brenda Tissue Ontology breast cancer cell line
hasProperty
Mathematical Modelling Ontology Ordinary differential equation model
Human Disease Ontology cancer
Curation status
Curated
  • Model originally submitted by : Galina Lebedeva
  • Submitted: Aug 18, 2011 1:13:07 PM
  • Last Modified: Jan 13, 2017 4:11:13 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Jan 13, 2017 4:11:13 PM
    • Submitted by: Galina Lebedeva
    • With comment: Current version of Faratian2009 - Role of PTEN in Trastuzumab resistance
  • Version: 1 public model Download this version
    • Submitted on: Aug 18, 2011 1:13:07 PM
    • Submitted by: Galina Lebedeva
    • With comment: Original import of BIOMD0000000424.xml.origin
Curator's comment:
(added: 01 Aug 2012, 14:47:16, updated: 01 Aug 2012, 14:47:16)
The model reproduces Figure S4 of the reference publication, that correspond to the effect of heregulin-beta (black). In order to reproduce the plot that correspond to the effect of pertuzumab (blue), the initial concentration of Per should be set as 300000. For more details about the scaling factor used in the concentration of Per, look in the notes of the "Per". The data were obtained by simulation the model using Copasi v4.8 (Build 35). The plots were made using Gnuplot.