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

机译:拉帕替尼敏感性在肿瘤细胞系中的全基因组DNA拷贝数预测因子。

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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.
机译:在癌症研究小组中使用全基因组测定的药物基因组学研究的一个共同目标是无偏见地发现与临床结果和药物反应相关的基因组改变。拉帕替尼(一种表皮生长因子受体(EGFR)和HER2酪氨酸激酶的选择性双重激酶抑制剂)的先前研究表明,这些靶基因的活性与应答之间存在可预测的关系。在其他基因可能在药物敏感性中起作用的假设下,从24个癌细胞系的全基因组DNA拷贝数数据构建了拉帕替尼应答的预测模型。一个最佳的预测模型由9个不同的基因位点的畸变组成,包括HER2,EGFR的获得和CDKN2A的丧失。该模型在接收器工作特性曲线下获得了大约0.85(80%置信区间,0.70-0.98; P <0.01)的面积,并正确分类了10种头颈癌细胞系中的8种敏感性状态。这项研究表明,可以使用新型基因组测定法无偏见地发现可预测拉帕替尼敏感性的生物标志物,包括先前描述的EGFR和HER2拷贝数增加。此外,这些结果表明DNA拷贝数概况在药物基因组学研究中的实用性。

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