Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines.

A common aim of pharmacogenomic studies that use genome-wide assays on panels of cancers is the unbiased discovery of genomic alterations that are associated with clinical outcome and drug response. Previous studies of lapatinib, a selective dual-kinase inhibitor of epidermal growth factor receptor (EGFR) and HER2 tyrosine kinases, have shown predictable relationships between the activity of these target genes and response. Under the hypothesis that additional genes may play a role in drug sensitivity, a predictive model for lapatinib response was constructed from genome-wide DNA copy number data from 24 cancer cell lines. An optimal predictive model which consists of aberrations at nine distinct genetic loci, includes gains of HER2, EGFR, and loss of CDKN2A. This model achieved an area under the receiver operating characteristic curve of approximately 0.85 (80% confidence interval, 0.70-0.98; P < 0.01), and correctly classified the sensitivity status of 8 of 10 head and neck cancer cell lines. This study shows that biomarkers predictive for lapatinib sensitivity, including the previously described copy number gains of EGFR and HER2, can be discovered using novel genomic assays in an unbiased manner. Furthermore, these results show the utility of DNA copy number profiles in pharmacogenomic studies.