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Prediction of sensitivity of advanced non-small cell lung cancers to gefitinib (Iressa, ZD1839)
Authors:Kakiuchi Soji  Daigo Yataro  Ishikawa Nobuhisa  Furukawa Chiyuki  Tsunoda Tatsuhiko  Yano Seiji  Nakagawa Kazuhiko  Tsuruo Takashi  Kohno Nobuoki  Fukuoka Masahiro  Sone Saburo  Nakamura Yusuke
Affiliation:Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo 108-8639, Japan.
Abstract:Gefitinib (Iressa, ZD1839), an inhibitor of epidermal growth factor receptor-tyrosine kinase, has shown potent anti-tumor effects and improved symptoms and quality-of-life of a subset of patients with advanced non-small cell lung cancer (NSCLC). However, a large portion of the patients showed no effect to this agent. To establish a method to predict the response of NSCLC patients to gefitinib, we used a genome-wide cDNA microarray to analyze 33 biopsy samples of advanced NSCLC from patients who had been treated with an identical protocol of second to seventh line gefitinib monotherapy. We identified 51 genes whose expression differed significantly between seven responders and 10 non-responders to the drug. We selected the 12 genes that showed the most significant differences to establish a numerical scoring system (GRS, gefitinib response score), for predicting response to gefitinib treatment. The GRS system clearly separated the two groups without any overlap, and accurately predicted responses to the drug in 16 additional NSCLC cases. The system was further validated by the semi-quantitative RT-PCR, immunohistochemistry and ELISA for serological test. Moreover, we proved that the anti-apoptotic activity of amphiregulin, a protein that was significantly over-expressed in non-responders but undetectable in responders, leads to resistance of NSCLC cells to gefitinib in vitro. Our results suggested that sensitivity of a given NSCLC to gefitinib can be predicted according to expression levels of a defined set of genes that may biologically affect drug sensitivity and survival of lung cancer cells. Our scoring system might eventually lead to achievement of personalized therapy for NSCLC patients.
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