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Identification of genotype-correlated sensitivity to selective kinase inhibitors by using high-throughput tumor cell line profiling

2007; National Academy of Sciences; Volume: 104; Issue: 50 Linguagem: Inglês

10.1073/pnas.0707498104

1091-6490

Ultan McDermott, Sreenath V. Sharma, Lori Dowell, Patricia Greninger, Clara Montagut, Jennifer Lamb, Heidi Archibald, Raul Raudales, Angela Tam, Diana Lee, S. Michael Rothenberg, Jeffrey G. Supko, Raffaella Sordella, Lindsey E. Ulkus, A. John Iafrate, Shyamala Maheswaran, Ching Ni Njauw, Hensin Tsao, Lisa Drew, Jeff H. Hanke, Xiaojun Ma, Mark G. Erlander, Nathanael S. Gray, Daniel A. Haber, Jeffrey Settleman,

Cell Image Analysis Techniques

Kinase inhibitors constitute an important new class of cancer drugs, whose selective efficacy is largely determined by underlying tumor cell genetics. We established a high-throughput platform to profile 500 cell lines derived from diverse epithelial cancers for sensitivity to 14 kinase inhibitors. Most inhibitors were ineffective against unselected cell lines but exhibited dramatic cell killing of small nonoverlapping subsets. Cells with exquisite sensitivity to EGFR, HER2, MET, or BRAF kinase inhibitors were marked by activating mutations or amplification of the drug target. Although most cell lines recapitulated known tumor-associated genotypes, the screen revealed low-frequency drug-sensitizing genotypes in tumor types not previously associated with drug susceptibility. Furthermore, comparing drugs thought to target the same kinase revealed striking differences, predictive of clinical efficacy. Genetically defined cancer subsets, irrespective of tissue type, predict response to kinase inhibitors, and provide an important preclinical model to guide early clinical applications of novel targeted inhibitors.