title: Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab.
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.
authors.affiliation: University of Edinburgh, Scotland, United Kingdom. d.faratian@ed.ac.uk
authors.forename: Dana
authors.initials: D
authors.lastname: Faratian
authors.forename: Alexey
authors.initials: A
authors.lastname: Goltsov
authors.forename: Galina
authors.initials: G
authors.lastname: Lebedeva
authors.forename: Anatoly
authors.initials: A
authors.lastname: Sorokin
authors.forename: Stuart
authors.initials: S
authors.lastname: Moodie
authors.forename: Peter
authors.initials: P
authors.lastname: Mullen
authors.forename: Charlene
authors.initials: C
authors.lastname: Kay
authors.forename: In Hwa
authors.initials: IH
authors.lastname: Um
authors.forename: Simon
authors.initials: S
authors.lastname: Langdon
authors.forename: Igor
authors.initials: I
authors.lastname: Goryanin
authors.forename: David J
authors.initials: DJ
authors.lastname: Harrison
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000911:Antibodies, Monoclonal / Q000627:therapeutic use*; D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000175:diagnosis / Q000188:drug therapy* / Q000235:genetics; D019008:Drug Resistance, Neoplasm / Q000235:genetics*; D005260:Female; D018734:Genes, erbB-2; D006801:Humans; D007206:Individuality; D008875:Middle Aged; D008954:Models, Biological; D008962:Models, Theoretical; D051059:PTEN Phosphohydrolase / Q000235:genetics / Q000502:physiology*; D011379:Prognosis; D049490:Systems Biology / Q000379:methods* / Q000639:trends; D000068878:Trastuzumab; D014407:Tumor Cells, Cultured
chemical_list: D000911:Antibodies, Monoclonal; D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents; D051059:PTEN Phosphohydrolase; C494929:PTEN protein, human; D000068878:Trastuzumab