Response prediction to a multitargeted kinase inhibitor in cancer cell lines and xenograft tumors using high-content tyrosine peptide arrays with a kinetic readout.

Multitargeted kinase inhibitors have shown clinical efficacy in a range of cancer types. However, two major problems associated with these drugs are the low fraction of patients for which these treatments provide initial clinical benefit and the occurrence of resistance during prolonged therapy. Several types of predictive biomarkers have been suggested, such as expression level and phosphorylation status of the major targeted kinase(s), mutational status of the kinases involved and of key components of the downstream signaling cascades, and gene expression signatures. In this work, we describe the development of a response prediction platform that does not require prior knowledge of the relevant kinases targeted by the inhibitor; instead, a phosphotyrosine peptide profile using peptide arrays with a kinetic readout is derived in lysates in the presence and absence of a kinase inhibitor. We show in a range of cell lines and in xenograft tumors that this approach allows for the stratification of responders and nonresponders to a multitargeted kinase inhibitor.