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Molecular & Cellular Proteomics 7:853-863, 2008.
© 2008 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Eight-channel iTRAQ Enables Comparison of the Activity of Six Leukemogenic Tyrosine Kinases^*,S

Andrew Pierce^,, Richard D. Unwin^,, Caroline A. Evans, Stephen Griffiths, Louise Carney, Liqun Zhang, Ewa Jaworska, Chia-Fang Lee, David Blinco, Michal J. Okoniewski^¶, Crispin J. Miller^¶, Danny A. Bitton^¶, Elaine Spooncer and Anthony D. Whetton^,||

From the Stem Cell and Leukaemia Proteomics Laboratory, University of Manchester, Christie Hospital, Kinnaird House, Kinnaird Road, Manchester M20 4QL, United Kingdom and ^¶ Bioinformatics Group, Paterson Institute for Cancer Research, University of Manchester, Wilmslow Road, Manchester M20 4BX, United Kingdom

There are a number of leukemogenic protein-tyrosine kinases (PTKs) associated with leukemic transformation. Although each is linked with a specific disease their functional activity poses the question whether they have a degree of commonality in their effects upon target cells. Exon array analysis of the effects of six leukemogenic PTKs (BCR/ABL, TEL/PDGFRβ, FIP1/PDGFR, D816V KIT, NPM/ALK, and FLT3ITD) revealed few common effects on the transcriptome. It is apparent, however, that proteome changes are not directly governed by transcriptome changes. Therefore, we assessed and used a new generation of iTRAQ tagging, enabling eight-channel relative quantification discovery proteomics, to analyze the effects of these six leukemogenic PTKs. Again these were found to have disparate effects on the proteome with few common targets. BCR/ABL had the greatest effect on the proteome and had more effects in common with FIP1/PDGFR. The proteomic effects of the four type III receptor kinases were relatively remotely related. The only protein commonly affected was eosinophil-associated ribonuclease 7. Five of six PTKs affected the motility-related proteins CAPG and vimentin, although this did not correspond to changes in motility. However, correlation of the proteomics data with that from the exon microarray not only showed poor levels of correlation between transcript and protein levels but also revealed alternative patterns of regulation of the CAPG protein by different oncogenes, illustrating the utility of such a combined approach.

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