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Gene Expression Patterns That Predict Sensitivity To Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors In Lung Cancer Cell Lines And Human Lung Tumors, Justin M. Balko, Anil Potti, Christopher Saunders, Arnold J. Stromberg, Eric B. Haura, Esther P. Black

Statistics Faculty Publications

BACKGROUND: Increased focus surrounds identifying patients with advanced non-small cell lung cancer (NSCLC) who will benefit from treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI). EGFR mutation, gene copy number, coexpression of ErbB proteins and ligands, and epithelial to mesenchymal transition markers all correlate with EGFR TKI sensitivity, and while prediction of sensitivity using any one of the markers does identify responders, individual markers do not encompass all potential responders due to high levels of inter-patient and inter-tumor variability. We hypothesized that a multivariate predictor of EGFR TKI sensitivity based on gene expression data would offer a …