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Cancer Research 69, 6713, August 15, 2009. Published Online First July 28, 2009;
doi: 10.1158/0008-5472.CAN-09-0777
© 2009 American Association for Cancer Research

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Systems Biology and Emerging Technologies

Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab

Dana Faratian1, Alexey Goltsov2, Galina Lebedeva2, Anatoly Sorokin2, Stuart Moodie2, Peter Mullen1, Charlene Kay1, In Hwa Um1, Simon Langdon1, Igor Goryanin2,3 and David J. Harrison1

1 Edinburgh Breakthrough Research Unit and Division of Pathology, 2 Centre for Systems Biology at Edinburgh, and 3 School of Informatics, Informatics Forum, University of Edinburgh, Edinburgh, Scotland, United Kingdom

Requests for reprints: Dana Faratian, Edinburgh Breakthrough Research Unit and Division of Pathology, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XR, Scotland, United Kingdom. Phone: 44-131-537-1763; Fax: 44-131-537-3159; E-mail: d.faratian{at}ed.ac.uk.

Key Words: systems biology • molecular pathology • phosphatidylinositol 3-kinase • trastuzumab • therapeutic resistance

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. [Cancer Res 2009;69(16):6713–20]




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Y. Nagumo, D. Faratian, P. Mullen, D. J. Harrison, M. Hasmann, and S. P. Langdon
Modulation of HER3 Is a Marker of Dynamic Cell Signaling in Ovarian Cancer: Implications for Pertuzumab Sensitivity
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[Abstract] [Full Text] [PDF]




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Copyright © 2009 by the American Association for Cancer Research.