1] Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona, Spain [2].
Sci Rep. 2013 Oct 2;3:2650. doi: 10.1038/srep02650.
With the ability to fully sequence tumor genomes/exomes, the quest for cancer driver genes can now be undertaken in an unbiased manner. However, obtaining a complete catalog of cancer genes is difficult due to the heterogeneous molecular nature of the disease and the limitations of available computational methods. Here we show that the combination of complementary methods allows identifying a comprehensive and reliable list of cancer driver genes. We provide a list of 291 high-confidence cancer driver genes acting on 3,205 tumors from 12 different cancer types. Among those genes, some have not been previously identified as cancer drivers and 16 have clear preference to sustain mutations in one specific tumor type. The novel driver candidates complement our current picture of the emergence of these diseases. In summary, the catalog of driver genes and the methodology presented here open new avenues to better understand the mechanisms of tumorigenesis.
通过全面测序肿瘤基因组/外显子，现在可以采用无偏倚的方式寻找癌症驱动基因。然而，由于疾病的分子异质性和现有计算方法的局限性，获得完整的癌症基因目录是困难的。在这里，我们表明，互补方法的结合可以确定全面可靠的癌症驱动基因列表。我们提供了一份由 291 个高可信度癌症驱动基因组成的清单，这些基因作用于来自 12 种不同癌症类型的 3205 个肿瘤。其中一些基因以前没有被确定为癌症驱动基因，16 个基因明显倾向于在一种特定的肿瘤类型中维持突变。这些新的候选驱动基因补充了我们目前对这些疾病发生的认识。总之，这里提供的驱动基因目录和方法为更好地理解肿瘤发生的机制开辟了新的途径。
