Abstract
7027 Background: Gefitinib (Iressa) and other EGFR inhibitors are active in 12–19% of NSCLC patients previously treated with chemotherapy. Currently, there are no selection criteria for determining which NSCLC patients will benefit from this treatment. EGFR expression does not predict Gefitinib sensitivity. Using a panel of NSCLC cell lines with varying sensitivity to Gefitinib we defined a panel of biomarkers that predict sensitivity or resistance. Methods: Gefitinib sensitivity was determined in 18 NSCLC cell lines using MTT assays. Cell lines were classified as Gefitinib sensitive (IC50<1μM), resistant (IC50>10μM) or intermediate sensitivity (IC50 1–10μM). Oligonucleotide microarray (Affymetrix HGU 133A, 22,000 genes) analysis was performed on 10 cell lines. Three distinct filtration and normalization algorithms were used to process the expression data and a list of genes was generated that was both statistically significant (unadjusted p=0.001 cutoff) and corrected for occurrence of false positives. This approach was used in combination with 5 distinct machine learning algorithms to build a test set for predictor genes that was successful in 100% of test cases. The best discriminators (>3 fold difference in expression between sensitive and resistant cell lines) were selected for quantitative real-time RT-PCR. Results: A list of 144 genes was generated from the Affymetric array analysis. By using the mathematical algorithm 16 candidate genes were selected for RT-PCR. Thirteen of the 16 genes were verified to discriminate between sensitive and resistant cell lines by quantitative real-time RT-PCR. Conclusions: Based on NSCLC cell line studies it was possible to identify 13 different genes, which strongly discriminated Gefitinib sensitive cell lines from the resistant ones. This biomarker panel may be of significant value for selecting NSCLC patients for Gefitinib treatment. Author Disclosure Employment or Leadership Consultant or Advisory Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Amgen; AstraZeneca Allos Therapeutics; AstraZeneca Eli Lilly
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
