Predicting treatment outcome using kinome activity profiling in HER2+ breast cancer biopsies
Donna O. Debets,
Erik L. de Graaf,
Marte C. Liefaard,
Gabe S. Sonke,
Esther H. Lips,
Anna Ressa,
Maarten Altelaar
Affiliations
Donna O. Debets
Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, 3584 CH Utrecht, the Netherlands
Erik L. de Graaf
Pepscope B.V, Nieuwe Kanaal 7, 6709 PA Wageningen, the Netherlands
Marte C. Liefaard
Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
Gabe S. Sonke
Department of Medical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Medical Oncology, University of Amsterdam, Amsterdam, the Netherlands
Esther H. Lips
Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
Anna Ressa
Pepscope B.V, Nieuwe Kanaal 7, 6709 PA Wageningen, the Netherlands
Maarten Altelaar
Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, 3584 CH Utrecht, the Netherlands; Corresponding author
Summary: In this study, we measured the kinase activity profiles of 32 pre-treatment tumor biopsies of HER2-positive breast cancer patients. The aim of this study was to assess the prognostic potential of kinase activity levels, to identify potential mechanisms of resistance and to predict treatment success of HER2-targeted therapy combined with chemotherapy. Indeed, our system-wide kinase activity analysis allowed us to link kinase activity to treatment response. Overall, high kinase activity in the HER2-pathway was associated with good treatment outcome. We found eleven kinases differentially regulated between treatment outcome groups, including well-known players in therapy resistance, such as p38a, ERK, and FAK, and an unreported one, namely MARK1. Lastly, we defined an optimal signature of four kinases in a multiple logistic regression diagnostic test for prediction of treatment outcome (AUC = 0.926). This kinase signature showed high sensitivity and specificity, indicating its potential as predictive biomarker for treatment success of HER2-targeted therapy.
