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Coordinated epidermal growth factor receptor pathway gene overexpression predicts epidermal growth factor receptor inhibitor sensitivity in pancreatic cancer
Authors:Jimeno Antonio  Tan Aik Choon  Coffa Jordy  Rajeshkumar N V  Kulesza Peter  Rubio-Viqueira Belen  Wheelhouse Jenna  Diosdado Begoña  Messersmith Wells A  Iacobuzio-Donahue Christine  Maitra Anirban  Varella-Garcia Marileila  Hirsch Fred R  Meijer Gerrit A  Hidalgo Manuel
Affiliation:Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21231-1000, USA.
Abstract:
The epidermal growth factor receptor (EGFR) inhibitor erlotinib is approved for treatment of pancreatic cancer but the overall activity is minimal, and known predictive factors for EGFR inhibitor efficacy are infrequent in this disease. We tested the hypothesis that global activation of the EGFR pathway is predictive of EGFR inhibitor efficacy. Pancreatic cancer tumors directly xenografted at surgery were treated with the EGFR inhibitors erlotinib and cetuximab and analyzed for biological features. Two of 10 tumors were sensitive, and by global gene expression profiling with gene set enrichment analysis, the EGFR pathway was highly expressed in sensitive compared with resistant tumors. The core gene components driving EGFR pathway overexpression were pathway ligands and positive effectors. In a prospective validation, the EGFR pathway-based signature correctly predicted anti-EGFR treatment response in eight additional tumors and was not predictive of response to gemcitabine and CI1040 (a MEK inhibitor). Analysis of EGFR, KRAS, and PIK3CA mutations and gene amplification by fluorescence in situ hybridization and multiplex ligation-dependent probe amplification showed that none of these genetic abnormalities were neither predictive nor responsible for the EGFR pathway activation. Coordinated overexpression of the EGFR pathway predicts susceptibility to EGFR inhibitors in pancreatic cancer. These results suggest a phenomenon of pathway addiction and support the value of unbiased system biology approaches in drug development.
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