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A chemical and phosphoproteomic characterization of dasatinib action in lung cancer

Nature Chemical Biology volume 6, pages 291299 (2010) | Download Citation

Abstract

We describe a strategy for comprehending signaling pathways that are active in lung cancer cells and that are targeted by dasatinib using chemical proteomics to identify direct interacting proteins combined with immunoaffinity purification of tyrosine-phosphorylated peptides corresponding to activated tyrosine kinases. We identified nearly 40 different kinase targets of dasatinib. These include SRC-family kinase (SFK) members (LYN, SRC, FYN, LCK and YES), nonreceptor tyrosine kinases (FRK, BRK and ACK) and receptor tyrosine kinases (Ephrin receptors, DDR1 and EGFR). Using quantitative phosphoproteomics, we identified peptides corresponding to autophosphorylation sites of these tyrosine kinases that are inhibited in a concentration-dependent manner by dasatinib. Using drug-resistant gatekeeper mutants, we show that SFKs (particularly SRC and FYN), as well as EGFR, are relevant targets for dasatinib action. The combined mass spectrometry–based approach described here provides a system-level view of dasatinib action in cancer cells and suggests both functional targets and a rationale for combinatorial therapeutic strategies.

  • Compound C22H26ClN7O2S

    Dasatinib

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Acknowledgements

We thank F. Lee (Bristol-Myers Squibb Oncology) for providing dasatinib, Genentech and OSI Pharmaceuticals for providing erlotinib, K. Rikova (Cell Signaling Technology) for providing NSCLC tumor spectral count data, Cell Signaling Technology for allowing reproduction of the kinome map, G. Durnberger for data uploading to PRIDE, J. Du (Broad Institute) and T. Golub (Broad Institute) for providing lentiviral constructs, T. Yoshida for helpful discussions and P. Johnston for administrative assistance. We thank W. Pao (Vanderbilt University) for the cDNA for L858R EGFR and L858R T790M EGFR and N. Mahajan (Moffitt Cancer Center) for the ACK. We thank J. Cheng (Moffitt Cancer Center) for the triciribine. The work was partially funded by grants from the US National Functional Genomics Center, the Moffitt Cancer Center SPORE in Lung Cancer (P50-CA119997), Joan's Legacy/LUNGevity Foundation (E.B.H.), the Austrian Federal Ministry of Science and Research within the GEN-AU program (GZ200.142/1-VI/I/2006 and GZ 200.145/1-VI/1/2006) and the Austrian Academy of Sciences. This work has been supported in part by the Proteomics Core, the Molecular Biology and Sequencing Core, and the Flow Cytometry Core at the H. Lee Moffitt Cancer Center & Research Institute.

Author information

Author notes

    • Jiannong Li
    •  & Uwe Rix

    These authors contributed equally to this work.

Affiliations

  1. Department of Thoracic Oncology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA.

    • Jiannong Li
    • , Yun Bai
    • , Arthur Edwards
    • , Jingchun Gao
    • , Lanxi Song
    •  & Eric B Haura
  2. CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.

    • Uwe Rix
    • , Jacques Colinge
    • , Keiryn L Bennett
    •  & Giulio Superti-Furga
  3. Proteomics and Molecular Oncology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA.

    • Bin Fang
    •  & John Koomen
  4. Bioinformatics Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA.

    • Steven Eschrich

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Contributions

J.L. designed and performed the experiments, analyzed and interpreted the data, performed statistical analyses, made the figures and wrote the manuscript. U.R. performed all chemical proteomics experiments, analyzed and interpreted the data, performed statistical analyses, made the figures and wrote the manuscript. B.F. performed all extracted ion chromatogram experiments, analyzed and interpreted the data, performed statistical analyses, made the figures and wrote the manuscript. A.E. provided statistical and bioinformatics support for interpreting LC-MS/MS data. S.E. advised on the research, performed statistical and bioinformatics support for interpreting LC-MS/MS data and critically read the manuscript. J.G. helped perform pY peptide purification from lung cancer cell lines. Y.B. provided technical assistance with cell lines. L.S. provided technical help with mutagenesis. K.L.B. analyzed chemical proteomics experiments and operated mass spectrometers. J.C. analyzed chemical proteomics experimental data and performed bioinformatics analyses. J.K. advised on the research, supervised all US-based proteomics experiments and critically read the manuscript. G.S.-F. supervised the chemical proteomics experiments, advised on the research and critically read the manuscript. E.B.H. had overall responsibility for this research and edited the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Giulio Superti-Furga or John Koomen or Eric B Haura.

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    Supplementary Methods, Supplementary Figures 1–11 and Supplementary Tables 1 and 2

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DOI

https://doi.org/10.1038/nchembio.332

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