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Nat Commun. 2017 Mar 28;8:14864. doi: 10.1038/ncomms14864.

Proteogenomic integration reveals therapeutic targets in breast cancer xenografts.

Author information

1
Department of Medicine, Washington University in St. Louis, St. Louis, Missouri 63108, USA.
2
McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri 63108, USA.
3
The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
4
Department of Biochemistry &Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599, USA.
5
Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York 10016, USA.
6
Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599, USA.
7
Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas 77030, USA.
8
Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, Missouri 63108, USA.
9
Department of Genetics, Washington University in St. Louis, St. Louis, Missouri 63108, USA.
10
Department of Mathematics, Washington University in St. Louis, St. Louis, Missouri 63108, USA.
11
Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.
12
Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri 63108, USA.
13
Department of Anesthesiology, Washington University in St. Louis, St. Louis, Missouri 63108, USA.
14
National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.

Abstract

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities.

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