Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-31625 - Gene Expression Patterns that Predict Sensitivity to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Lung Cancer Cell Lines and Human Lung Tumors
Released on 31 August 2011, last updated on 13 August 2015
Global gene expression data were generated from cultured non small cell lung cancer cell lines (NSCLC), normalized using MAS 5.0, filtered and used to predict response of cells to EGFR inhibition Gene expression data from additional cell lines and tumors was used to validate the predictive algorithm Total RNA was prepared from NSCLC cell lines and applied to Affymetric U133 2.0 microarrays
transcription profiling by array
Esther P Black <firstname.lastname@example.org>, Justin M Balko
Gene expression patterns that predict sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors in lung cancer cell lines and human lung tumors. Balko JM, Potti A, Saunders C, Stromberg A, Haura EB, Black EP.