Division of Hematology and Oncology, Department of Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
J Hum Genet. 2018 Sep;63(9):941-943. doi: 10.1038/s10038-018-0481-4. Epub 2018 Jun 15.
Extensive sequencing efforts of cancer genomes such as The Cancer Genome Atlas (TCGA) have been undertaken to uncover bona fide cancer driver genes which has enhanced our understanding of cancer and revealed therapeutic targets. However, the number of driver gene mutations is bounded, indicating that there must be a point when further sequencing efforts will be excessive. We found that there was a significant positive correlation between sample size and identified driver gene mutations across 33 cancers sequenced by the TCGA, which is expected if additional sequencing is still leading to the identification of more driver genes. However, the rate of new cancer driver genes being discovered with larger samples is declining rapidly. Our analysis provides a general guide for determining which cancer types would likely benefit from additional sequencing efforts, particularly those with relatively high rates of cancer driver gene discovery. Our results argue that past strategies of indiscriminately sequencing as many specimens as possible for all cancer types is becoming inefficient. In addition, without significant investments into applying our knowledge of cancer genomes, we risk sequencing more cancer genomes for the sake of sequencing rather than meaningful patient benefit.
癌症基因组的广泛测序工作，如癌症基因组图谱（TCGA），已经被用来发现真正的癌症驱动基因，这增强了我们对癌症的理解，并揭示了治疗靶点。然而，驱动基因突变的数量是有限的，这表明在某个时候，进一步的测序工作将是多余的。我们发现，在 TCGA 测序的 33 种癌症中，样本量与鉴定出的驱动基因突变之间存在显著的正相关，这是合理的，因为额外的测序仍然可以发现更多的驱动基因。然而，随着样本量的增加，新的癌症驱动基因的发现率迅速下降。我们的分析为确定哪些癌症类型可能受益于额外的测序工作提供了一个一般的指导，特别是那些具有相对较高的癌症驱动基因发现率的癌症类型。我们的结果表明，过去对所有癌症类型不加区分地对尽可能多的标本进行测序的策略已经变得效率低下。此外，如果不投入大量资金来应用我们对癌症基因组的知识，我们就有可能为了测序而测序，而不是为了给患者带来有意义的获益。
