Figure 3 | Scientific Reports

Figure 3

From: Deep Phospho- and Phosphotyrosine Proteomics Identified Active Kinases and Phosphorylation Networks in Colorectal Cancer Cell Lines Resistant to Cetuximab

Figure 3

Identification of active kinase candidates as potential drug targets from the phosphoproteomic data. (a) Procedure for reconstruction of the kinase network. Active kinase candidates were predicted from increased phosphosites in deep pSTY or pY proteomic data by using the functional information for each phosphosite registered in the PhosphositePlus database or by KSEA prediction. By combining the active kinase candidates based on empirically validated KSRs in the PhosphositePlus database, the kinome networks were constructed. (b) Numbers of active kinase candidates obtained from two different approaches. Bar Graphs show the number of active kinase candidates in HCT116 cells and HT29 cells treated or untreated with Cetuximab. Purple: fraction of activated kinases identified by their phosphorylation statuses. Green: fraction of activated kinases predicted by KSEA. Gray: fraction of activated kinases identified by both methods. (c) Number of activated kinase candidates obtained from different proteomic data. Red: fraction of activated kinases identified from pSTY proteomic data. Cyan: fraction of activated kinases identified from pY proteomic data. (d) Verification of kinase activity by western blotting. The activation status of SRC in HCT116 and HT29 cells was analyzed by western blotting. GAPDH was used as an internal control.

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