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12 种主要癌症类型的突变特征及意义。

Mutational landscape and significance across 12 major cancer types.

机构信息

The Genome Institute, Washington University in St Louis, Missouri 63108, USA.

Department of Computer Science, Brown University, Providence, Rhode Island 02912, USA.

出版信息

Nature. 2013 Oct 17;502(7471):333-339. doi: 10.1038/nature12634.

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

癌症基因组图谱(TCGA)利用最新的测序和分析方法,在数千个肿瘤中鉴定出体细胞变异。在这里,我们展示了 12 种肿瘤类型的 3281 个肿瘤的点突变和小插入/缺失的数据分析结果,这是 TCGA 泛癌研究的一部分。我们说明了突变频率、类型和上下文在肿瘤类型中的分布,并建立了它们与起源组织、环境/致癌因素以及 DNA 修复缺陷的联系。通过使用整合数据集,我们从已知(例如,丝裂原活化蛋白激酶、磷脂酰肌醇 3-OH 激酶、Wnt/β-catenin 和受体酪氨酸激酶信号通路以及细胞周期控制)和新兴(例如,组蛋白、组蛋白修饰、剪接、代谢和蛋白水解)细胞过程中确定了 127 个显著突变的基因。这些显著突变基因中的突变数量在肿瘤类型之间存在差异;大多数肿瘤有两到六个,表明致癌过程中所需的驱动突变数量相对较少。转录因子/调节剂的突变具有组织特异性,而组蛋白修饰剂通常在几种癌症类型中发生突变。临床关联分析确定了对生存有显著影响的基因,并且对克隆/亚克隆结构的突变进行调查可以描绘它们在肿瘤发生过程中的时间顺序。总的来说,这些结果为开发新的诊断方法和个体化癌症治疗奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62a9/7449522/1d403859639d/41586_2013_BFnature12634_Fig1_HTML.jpg

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