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

机译:通过使用高通量肿瘤细胞系谱分析鉴定对选择性激酶抑制剂的基因型相关敏感性

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摘要

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 uns-elected cell lines but exhibited dramatic cell killing of small nonover-lapping 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.
机译:激酶抑制剂构成一类重要的新型癌症药物,其选择性功效在很大程度上取决于潜在的肿瘤细胞遗传学。我们建立了一个高通量的平台来分析500种衍生自多种上皮癌的细胞系对14种激酶抑制剂的敏感性。大多数抑制剂对未选出的细胞系无效,但对小的非重叠亚群表现出戏剧性的细胞杀伤作用。对EGFR,HER2,MET或BRAF激酶抑制剂具有极高敏感性的细胞通过激活突变或靶标扩增来标记。尽管大多数细胞系概括了已知的与肿瘤相关的基因型,但该筛查揭示了以前与药物敏感性无关的肿瘤类型中的低频药物致敏基因型。此外,比较被认为靶向相同激酶的药物发现了显着差异,可预测临床疗效。无论组织类型如何,遗传定义的癌症子集都能预测对激酶抑制剂的反应,并提供重要的临床前模型来指导新型靶向抑制剂的早期临床应用。

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