Nature2013-10-20 11:14 PM

Mutational landscape and significance across 12 major cancer types 12种主要癌症典型的突变景观图和其意义

Abstract
The Cancer Genome Atlas (TCGA) has used the latest sequencing and analysis methods to identify somatic variants across thousands of tumours. Here we present data and analytical results for point mutations and small insertions/deletions from 3,281 tumours across 12 tumour types as part of the TCGA Pan-Cancer effort. We illustrate the distributions of mutation frequencies, types and contexts across tumour types, and establish their links to tissues of origin, environmental/carcinogen influences, and DNA repair defects. Using the integrated data sets, we identified 127 significantly mutated genes from well-known (for example, mitogen-activated protein kinase, phosphatidylinositol-3-OH kinase, Wnt/β-catenin and receptor tyrosine kinase signalling pathways, and cell cycle control) and emerging (for example, histone, histone modification, splicing, metabolism and proteolysis) cellular processes in cancer. The average number of mutations in these significantly mutated genes varies across tumour types; most tumours have two to six, indicating that the number of driver mutations required during oncogenesis is relatively small. Mutations in transcriptional factors/regulators show tissue specificity, whereas histone modifiers are often mutated across several cancer types. Clinical association analysis identifies genes having a significant effect on survival, and investigations of mutations with respect to clonal/subclonal architecture delineate their temporal orders during tumorigenesis. Taken together, these results lay the groundwork for developing new diagnostics and individualizing cancer treatment. 摘要翻译: 癌症基因组图谱(TCGA )采用了最新的测序和分析的方法来识别成千上万肿瘤中体细胞变异体。我们在这里展现了对12种肿瘤种类中的3281个肿瘤的结点突变和微小插入和删除的数据和分析结果作为对TCGA泛癌症计划中一部分的努力。我们揭示了不同肿瘤类型的突变频率,类型和内容的分布,建立了他们与源头组织之间,环境性或致癌性影响之间以及DNA缺陷修复之间的联系。通过使用这些综合的数据集合,我们从广泛所知的(例如:丝裂原活化蛋白激酶,磷脂酰肌醇3激酶, WNT / β-catenin和受体酪氨酸激酶信号通路,细胞周期调控)和新浮现的(例如,组蛋白,组蛋白修饰,剪接,代谢和蛋白水解)癌症的细胞周期中发现了127种显著的突变基因。不同肿瘤类型之间的这些显著变异基因的平均数量不尽相同;通常有2到6个,这表明肿瘤形成时只需很少驱动突变的变异基因。转录因子和转录调节基因的变异揭示了组织特异性,而组蛋白修饰常横跨几种癌症类型发生变异。临床关联性分析识别了对存活有显著影响的基因,对克隆/亚克隆架构相关的变异的调查则描绘出他们在肿瘤发生过程中可能遵循的时间顺序。综合上述,这些所做的研究为开发新的诊断方法和个体化癌症治疗奠定了基础。

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