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  • Title: Establishment of patient-derived non-small cell lung cancer xenografts as models for the identification of predictive biomarkers.
    Author: Fichtner I, Rolff J, Soong R, Hoffmann J, Hammer S, Sommer A, Becker M, Merk J.
    Journal: Clin Cancer Res; 2008 Oct 15; 14(20):6456-68. PubMed ID: 18927285.
    Abstract:
    PURPOSE: It was the aim of our study to establish an extensive panel of non-small cell lung cancer (NSCLC) xenograft models useful for the testing of novel compounds and for the identification of biomarkers. EXPERIMENTAL DESIGN: Starting from 102 surgical NSCLC specimens, which were obtained from primarily diagnosed patients with early-stage tumors (T(2)/T(3)), 25 transplantable xenografts were established and used for further investigations. RESULTS: Early passages of the NSCLC xenografts revealed a high degree of similarity with the original clinical tumor sample with regard to histology, immunohistochemistry, as well as mutation status. The chemotherapeutic responsiveness of the xenografts resembled the clinical situation in NSCLC with tumor shrinkage obtained with paclitaxel (4 of 25), gemcitabine (3 of 25), and carboplatin (3 of 25) and lower effectiveness of etoposide (1 of 25) and vinorelbine (0 of 11). Twelve of 25 NSCLC xenografts were >50% growth inhibited by the anti-epidermal growth factor receptor (EGFR) antibody cetuximab and 6 of 25 by the EGFR tyrosine kinase inhibitor erlotinib. The response to the anti-EGFR therapies did not correlate with mutations in the EGFR or p53, but there was a correlation of K-ras mutations and erlotinib resistance. Protein analysis revealed a heterogeneous pattern of expression. After treatment with cetuximab, we observed a down-regulation of EGFR in 2 of 6 sensitive xenograft models investigated but never in resistant models. CONCLUSION: An extensive panel of patient-derived NSCLC xenografts has been established. It provides appropriate models for testing marketed as well as novel drug candidates. Additional expression studies allow the identification of stratification biomarkers for targeted therapies.
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