Abstract B49: Investigating kinase inhibitor resistance mechanisms through quantitative network mapping of the human kinase interactome

Abstract

Abstract The human kinases have become one of the most important classes of drug targets in the pharmaceutical industry. More than 20 drugs targeting one or more kinases have been approved for clinical use in a variety of cancers, including lung, breast, melanoma, colorectal, pancreatic, and prostate cancers. However, patients treated with those kinase inhibitors eventually develop resistance, and their prolong survivals are typically only a few months. So far, no general model has emerged to address the kinase inhibitor resistance. In this study, we constructed a systems biology-based framework to catalogue the human kinome (kinases and their interactions), including 538 kinase genes, in the broader context of the human interactome. Specifically, we constructed three networks: a kinase-substrate interaction network containing 7,346 pairs connecting 379 kinases to 36,576 phosphorylation sites in 1,961 substrates, a protein-protein interaction network (PPIN) containing 92,699 pairs, and an atomic resolution PPIN containing 4,278 pairs. We identified the conserved regulatory phosphorylation motifs (e.g., Ser/Thr-Pro) using a sequence logo analysis. We found the typical anticancer target selection strategy that uses network hubs as drug targets might lead to a high adverse drug reaction risk. Furthermore, we found the distinct network centrality of kinases creates a high anticancer drug resistance risk by feedback or crosstalk mechanisms within cellular networks. This notion is supported by the systematic network and pathway analyses that anticancer drug resistance genes are significantly enriched as hubs and heavily participate in multiple signaling pathways. Collectively, this comprehensive human kinome map sheds light on anticancer drug resistance mechanisms and provides an innovative resource for rational kinase inhibitor design. Note: This abstract was not presented at the conference. Citation Format: Feixiong Cheng, Zhongming Zhao. Investigating kinase inhibitor resistance mechanisms through quantitative network mapping of the human kinase interactome. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr B49.