Peptide Microarrays for Profiling of Serine/Threonine Kinase Activity of Recombinant Kinases and Lysates of Cells and Tissue Samples

  • Riet Hilhorst
  • Liesbeth Houkes
  • Monique Mommersteeg
  • Joyce Musch
  • Adriënne van den Berg
  • Rob Ruijtenbeek
Part of the Methods in Molecular Biology book series (MIMB, volume 977)


Peptide microarray technology can be used to identify substrates for recombinant kinases, to measure kinase activity and changes thereof in cell lysates and lysates from fresh frozen (tumor) tissue. The effect of kinase inhibitors on the kinase activities in relevant tissues can be investigated as well. The method for performing experiments on dynamic peptide microarrays with real-time readout is described, as well as the influence of assay parameters and suggestions for optimization of experiments.

Key words

Tyrosine kinase Serine/threonine kinase Kinase activity Peptide microarray Multiplex assay Kinase substrate identification Kinase activity profiling Kinase kinetics Kinase inhibition 


  1. 1.
    Thiele A, Stangl GI, Schutkowski M (2011) Deciphering enzyme function using peptide arrays. Mol Biotechnol 49:283–305PubMedCrossRefGoogle Scholar
  2. 2.
    Arsenault R, Griebel P, Napper S (2011) Peptide arrays for kinome analysis: new opportunities and remaining challenges. Proteomics 11:4595–4609PubMedCrossRefGoogle Scholar
  3. 3.
    Lemeer S, Jopling C, Naji F et al (2007) Protein-tyrosine kinase activity profiling in knock down zebrafish embryos. PLoS One 2:e581PubMedCrossRefGoogle Scholar
  4. 4.
    Versele M, Talloen W, Rockx C et al (2009) Response prediction to a multitargeted kinase inhibitor in cancer cell lines and xenograft tumors using high-content tyrosine peptide arrays with a kinetic readout. Mol Cancer Ther 8:1846–1855PubMedCrossRefGoogle Scholar
  5. 5.
    Hilhorst R, Houkes L, van den Berg A et al (2009) Peptide microarrays for detailed, high-throughput substrate identification, kinetic characterization, and inhibition studies on protein kinase A. Anal Biochem 387:150–161PubMedCrossRefGoogle Scholar
  6. 6.
    Sanz A, Ungureanu D, Pekkala T et al (2011) Analysis of Jak2 catalytic function by peptide microarrays: the role of the JH2 domain and V617F mutation. PLoS One 6:e18522PubMedCrossRefGoogle Scholar
  7. 7.
    Poot AJ, van Ameijde J, Slijper M et al (2009) Development of selective bisubstrate-based inhibitors against protein kinase C (PKC) isozymes by using dynamic peptide microarrays. Chembiochem 10:2042–2051PubMedCrossRefGoogle Scholar
  8. 8.
    Harmsen S, Dolman ME, Nemes Z et al (2011) Development of a cell-selective and intrinsically active multikinase inhibitor bioconjugate. Bioconjug Chem 22:540–545PubMedCrossRefGoogle Scholar
  9. 9.
    Sikkema AH, Diks SH, den Dunnen WF et al (2009) Kinome profiling in pediatric brain tumors as a new approach for target discovery. Cancer Res 69:5987–5995PubMedCrossRefGoogle Scholar
  10. 10.
    Bratland A, Boender PJ, Hoifodt HK et al (2009) Osteoblast-induced EGFR/ERBB2 signaling in androgen-sensitive prostate carcinoma cells characterized by multiplex kinase activity profiling. Clin Exp Metastasis 26: 485–496PubMedCrossRefGoogle Scholar
  11. 11.
    Plaza-Menacho I, Morandi A, Mologni L et al (2011) Focal adhesion kinase (FAK) binds RET kinase via its FERM domain, priming a direct and reciprocal RET-FAK transactivation mechanism. J Biol Chem 286:17292–17302PubMedCrossRefGoogle Scholar
  12. 12.
    Maat W, el Filali M, Dirks-Mulder A et al (2009) Episodic Src activation in uveal melanoma revealed by kinase activity profiling. Br J Cancer 101:312–319PubMedCrossRefGoogle Scholar
  13. 13.
    Saelen MG, Flatmark K, Folkvord S et al (2011) Tumor kinase activity in locally advanced rectal cancer: angiogenic signaling and early systemic dissemination. Angiogenesis 14:481–489PubMedCrossRefGoogle Scholar
  14. 14.
    Ter Elst A, Diks SH, Kampen KR et al (2011) Identification of new possible targets for leukemia treatment by kinase activity profiling. Leuk Lymphoma 52:122–130PubMedCrossRefGoogle Scholar
  15. 15.
    Jinnin M, Medici D, Park L et al (2008) Suppressed NFAT-dependent VEGFR1 expre­ssion and constitutive VEGFR2 signaling in infantile hemangioma. Nat Med 14: 1236–1246PubMedCrossRefGoogle Scholar
  16. 16.
    Folkvord S, Flatmark K, Dueland S et al (2010) Prediction of response to preoperative chemoradiotherapy in rectal cancer by multiplex kinase activity profiling. Int J Radiat Oncol Biol Phys 78:555–562PubMedCrossRefGoogle Scholar
  17. 17.
    Hilhorst R, Schaake E, van Pel R et al (2011) Application of kinase activity profiles to predict response to erlotinib in a neoadjuvant setting in early stage non-small cell lung cancer (NSCLC). J Clin Oncol 28: suppl. abstract 10566Google Scholar
  18. 18.
    Hilhorst R, Schaake E., van Pel R et al (2011) Blind prediction of response to erlotinib in early stage non-small cell lung cancer (NSCLC) in a neoadjuvant settin based on kinase activity profiles. J Clin Oncol 29: suppl abstract 10521Google Scholar
  19. 19.
    Lemeer S, Ruijtenbeek R, Pinkse MW et al (2007) Endogenous phosphotyrosine signaling in zebrafish embryos. Mol Cell Proteomics 6:2088–2099PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  • Riet Hilhorst
    • 1
  • Liesbeth Houkes
    • 1
  • Monique Mommersteeg
    • 1
  • Joyce Musch
    • 1
  • Adriënne van den Berg
    • 1
  • Rob Ruijtenbeek
    • 1
  1. 1.PamGene International BV’s-HertogenboschThe Netherlands

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