Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
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DOI：
10.1158/0008-5472.can-09-1133
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发表时间：
2009-08-15
期刊：
影响因子：
11.2
通讯作者：
Karchin R
中科院分区：
文献类型：
--
作者：
Carter H;Chen S;Isik L;Tyekucheva S;Velculescu VE;Kinzler KW;Vogelstein B;Karchin R
癌症基因组的大规模测序已经发现了数千种DNA改变，但这些突变中的大多数与肿瘤发生的功能相关性尚不清楚。我们开发了一种称为CHASM（癌症特异性高通量体细胞突变注释）的计算方法，以识别和优先考虑那些最有可能产生增强肿瘤细胞增殖的功能变化的错义突变。该方法在区分已知的驱动错义突变和随机产生的错义突变时具有高灵敏度和特异性（ROC曲线下的面积> 0.91，精确-召回曲线下的面积> 0.79）。CHASM在区分TP 53和酪氨酸激酶EGFR中的已知致癌突变方面显著优于先前描述的错义突变功能预测方法。我们将该方法应用于最近的多形性胶质母细胞瘤测序（GBM）研究中发现的607个错义突变。基于假设GBM突变是驾驶员和乘客的混合物的模型，我们估计这些突变中有8%是驾驶员，导致肿瘤发生。
Large-scale sequencing of cancer genomes has uncovered thousands of DNA alterations, but the functional relevance of the majority of these mutations to tumorigenesis is unknown. We have developed a computational method, called CHASM (Cancer-specific High-throughput Annotation of Somatic Mutations), to identify and prioritize those missense mutations most likely to generate functional changes that enhance tumor cell proliferation. The method has high sensitivity and specificity when discriminating between known driver missense mutations and randomly generated missense mutations (area under ROC curve > 0.91, area under Precision-Recall curve > 0.79). CHASM substantially outperformed previously described missense mutation function prediction methods at discriminating known oncogenic mutations in TP53 and the tyrosine kinase EGFR. We applied the method to 607 missense mutations found in a recent glioblastoma multiforme sequencing (GBM) study. Based on a model that assumed the GBM mutations are a mixture of drivers and passengers, we estimate that 8% of these mutations are drivers, causally contributing to tumorigenesis.