PTM Knowledge Networks and LINCS Multi-Omics Data for Kinase Inhibitor Drug-Analytics in Lung Cancer

Kinase domain mutations in the Epidermal growth factor receptor (EGFR) are common drivers of lung adenocarcinoma. 1st generation EGFR tyrosine kinase inhibitors (TKIs), gefitinib and erlotinib, 2nd generation EGFR TKI, afatinib and 3rd generation EGFR TKIs osimertinib and rociletinib inhibit mutant EGFRs. While all the EGFR TKIs are active against TKI-sensitizing EGFR mutants, L858R and Del EGFR, only the 3rd generation TKIs are effective against EGFR T790M, the most common acquired resistance mechanism to 1st and 2nd generation TKIs. Patients often have a good initial response to these drugs, but resistance inevitably develops, due to either additional EGFR mutations or to activation of parallel signaling pathways. To understand the mechanisms of resistance to the 3rd generation EGFR TKIs, we conducted a mass spectrometry-based phosphoproteomic analysis comparing rociletinib-resistant and rociletinib-sensitive lung cancer cells. Using iPTMnet, a PTM resource that integrates data from text mining of the scientific literature and other PTM databases, we found that AKT and PKA kinases targeted many of the sites whose phosphorylation was up-regulated in resistant cells; these kinases may be part of signaling pathways that are aberrantly activated in these cells. Next, we used kinase-inhibitor target data (KinomeScan) and phosphoproteomic data (P100) from the NIH Library of Integrated Network-Based Cellular Signatures Program (LINCS; http://www.lincsproject.org/) to identify drugs that might overcome drug resistance. Our study demonstrated that PTM knowledge networks can be used in conjunction with phosphoproteomic data to identify aberrantly regulated kinase signaling pathways in drug resistant cells, and that LINCS data (KinomeScan and P100) can be used to identify candidate drugs to be used in combination therapy to overcome resistance. In our ongoing work, we are testing drugs identified by LINCS analysis in cell culture assays, extending the analysis to other TKIs, and automating our workflow for overlay of PTM knowledge maps, LINCS data, and cancer omics data.