quantitative analysis of [11c]-erlotinib pet demonstrates specific binding for activating mutations of the egfr kinase domain

quantitative analysis of [11c]-erlotinib pet demonstrates specific binding for activating mutations of the egfr kinase domain

;J. Ryan Petrulli;Jenna M. Sullivan;Ming-Qiang Zheng;Daniel C. Bennett;Jonathan Charest;Yiyun Huang;Evan D. Morris;Joseph N. Contessa
ACS chemical neuroscience 2013 Vol. 15 pp. 1347-1353
272
petrulli2013neoplasia:quantitative

Abstract

Activating mutations of the epidermal growth factor receptor (EGFR) occur in multiple tumor types, including non-small cell lung cancer (NSCLC) and malignant glioma, and have become targets for therapeutic intervention. The determination of EGFR mutation status using a noninvasive, molecular imaging approach has the potential for clinical utility. In this study, we investigated [11C]-erlotinib positron emission tomography (PET) imaging as a tool to identify activating mutations of EGFR in both glioma and NSCLC xenografts. Radiotracer specific binding was determined for high and low specific activity (SA) [11C]-erlotinib PET scans in mice bearing synchronous human cancer xenografts with different EGFR expression profiles (PC9, HCC827, U87, U87 ΔEGFR, and SW620). Although xenograft immunohistochemistry demonstrated constitutive EGFR phosphorylation, PET scan analysis using the Simplified Reference Tissue Model showed that only kinase domain mutant NSCLC (HCC827 and PC9) had significantly greater binding potentials in high versus low SA scans. Xenografts with undetectable EGFR expression (SW620), possessing wild-type EGFR (U87), and expressing an activating extracellular domain mutation (U87 ΔEGFR) were indistinguishable under both high and low SA scan conditions. The results suggest that [11C]-erlotinib is a promising radiotracer that could provide a novel clinical methodology for assessing EGFR and erlotinib interactions in patients with tumors that harbor EGFR-activating kinase domain mutations.

Citation

ID: 136194
Ref Key: petrulli2013neoplasia:quantitative
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
136194
Unique Identifier:
10.1593/neo.131666
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet