Cell lines recapitulate the kinase activity profiles of colorectal tumor tissue and predict drug response

[Background and Aims]: Colorectal cancer (CRC) is the 3rd most common cancer in the world. Various protein and genetic markers have been reported to predict chemotherapy efficacy. However, treatment response prediction poses a challenge because of CRC heterogeneity. Therefore, precise and individualized treatment strategies with approaches different from proteomics and genomics are needed. Given the kinase dysregulation during oncogenesis, a battery of kinase inhibitors has been developed and used in clinics. Since kinase network dysregulation is caused by a set of kinases and influenced by various mechanisms, direct measurement of global kinase activity represents a practical way to infer identify upstream kinases. We aimed to analyze to what extent the kinase activity profiles of CRC are maintained in established CRC cell lines and whether kinase activity reflects the drug response to kinase inhibitors.

[Methods]: Comprehensive kinase activity assay was conducted on six CRC cell lines, CRC tumors (n=16), and matched normal tissues (n=16) with a three-dimensional peptide array. Kinase-substrate enrichment analysis was performed to compare kinase activity values between tumor and normal tissues and to infer the relative activities of kinases. A drug sensitivity test was performed on the six CRC cell lines with 60 FDA-approved tyrosine kinase inhibitors. The kinase activity profiles and drug sensitivity data were integrated to identify and characterize target kinases and corresponding kinase inhibitors.

[Results]: A total of 43 tyrosine kinases were inferred through the phosphorylation intensity data from 181 substrate peptides. Increased kinase activity was found in tumors relative to their corresponding normal tissues. Six kinases including VEGFR1, PDGFRB, JAK3, SYK, MAP2K4, and INSR were aberrantly activated in the tumors. CRC cell lines mirrored the kinomic aberrations observed in tumor tissues. All the samples were grouped into two clusters depending on the overall kinase activity status, hyper-activated and lower-activated. This was also the case with the cell lines. Drug screening data indicated that nine drugs targeting 13 kinases strongly suppressed cell viability. Upon profiling the response of six CRC cell lines to 60 tyrosine kinase inhibitors, two clusters emerged that showed different degrees of drug sensitivity, responsive and non-responsive groups. Integrating the kinase activity profiles and the drug sensitivity data, global kinase activity was found to be relatively high in the responsive groups, while it was relatively low in the non-responsive groups.

[Conclusions]: Our pharmacokinomic approach revealed that kinase activity profiles of the cell lines recapitulate those of tumors. The kinase activity profile was able to predict sensitivity to tyrosine kinase inhibitors. Our integrative approach lends itself to personalized cancer medicine, demonstrating the potential of kinase activity profiling.