Abstract 3321: Using NLPs to study EGFR structure, activation, and inhibition

• Published in: Cancer research (Chicago, Ill.) Ill.), 2014-10, Vol.74 (19_Supplement), p.3321-3321
• Main Authors: Scharadin, Tiffany M., Saldana, Matthew, Schlein, Michael, Hoang-Phou, Steven, Trans, Denise, Chang, Dennis, He, Wei, Lam, Kit, Carraway, Kermit L., Coleman, Matthew A., Henderson, Paul T.
• Format: Article
• Language: English
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2014-3321

The mammalian ErbB receptor tyrosine kinase family is critical for the development and maintenance of a variety of tissues. Though not completely understood, the mechanism of ErbB receptor activation involves the binding of ligand to the extracellular domain leading to a conformational change that allows dimerization and phosphorylation to initiate downstream signaling pathways. Mutations, amplification, and aberrant activation of these receptors lead to oncogenesis and tumor progression in several cancer types, including lung, breast, and colon. Current ErbB-targeted therapies include monoclonal antibodies and tyrosine kinase inhibitors. These treatments are initially effective but many tumors develop resistance, necessitating the discovery of a more specific and efficient drug. Studying the ErbB receptors is often difficult because of their large size and poor water solubility. Here we report success in assembling EGFR into nanolipoprotein particles (NLPs) to study activation and inhibition of the correctly-folded, full-length, and active receptor. NLPs are ∼20 nm cell membrane analogs composed of an apolipoprotein surrounding a lipid bilayer. We produced a homogenous population of EGFR-NLPs, by FLAG-purification of EGFR from mammalian cells, which are of the correct size, phosphorylated, and can be quantified. Furthermore, these EGFR-NLPs can be utilized as a novel target in a one-bead-one-compound (OBOC) screen of small molecules and peptides to identify unique therapeutics. Studies of ligand binding, kinase activity, and EGFR structure are ongoing. Future directions are to incorporate disease-relevant EGFR mutations into NLPs. The T790M mutation is of particular interest because it is a treatment-induced mutation observed in half of all non small cell lung cancers and confers resistance to current ErbB-targeted therapies. Citation Format: Tiffany M. Scharadin, Matthew Saldana, Michael Schlein, Steven Hoang-Phou, Denise Trans, Dennis Chang, Wei He, Kit Lam, Kermit L. Carraway, Matthew A. Coleman, Paul T. Henderson. Using NLPs to study EGFR structure, activation, and inhibition. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3321. doi:10.1158/1538-7445.AM2014-3321