A compendium of mutational cancer driver genes

简编 癌变 基因 体细胞 癌症 生物 种系突变 突变 选择(遗传算法) 计算生物学 生物信息学 遗传学 鉴定(生物学) 基因组学 重要事件 癌症的体细胞进化 基因突变 癌症研究 基因组 机制(生物学)
作者
Francisco Martínez-Jiménez,Ferran Muiños,Inés Sentís,Jordi Deu-Pons,Iker Reyes-Salazar,Claudia Arnedo-Pac,Loris Mularoni,Oriol Pich,Jose Bonet,Hanna Kranas,Abel González-Pérez,Núria López-Bigas
出处
期刊:Nature Reviews Cancer [Nature Portfolio]
卷期号:20 (10): 555-572 被引量:1272
标识
DOI:10.1038/s41568-020-0290-x
摘要

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer. This Review provides a brief historical perspective of our understanding of the role of cancer genes before presenting the Integrative OncoGenomics (IntOGen) platform, a bioinformatics method of mutational driver identification, which is beginning to reveal the compendium of driver genes across many tumour types as well as alluding to their tumorigenic mechanisms.
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