Soussi Thierry, Taschner Peter E M, Samuels Yardena
Sorbonne Université, UPMC Univ Paris 06, Paris, F-75005, France.
INSERM, U1138, Centre de Recherche des Cordeliers, Paris, France.
Hum Mutat. 2017 Apr;38(4):339-342. doi: 10.1002/humu.23163. Epub 2017 Feb 2.
Single-nucleotide variants (SNVs) are the most frequent genetic changes found in human cancer. Most driver alterations are missense and nonsense variants localized in the coding region of cancer genes. Unbiased cancer genome sequencing shows that synonymous SNVs (sSNVs) can be found clustered in the coding regions of several cancer oncogenes or tumor suppressor genes suggesting purifying selection. sSNVs are currently underestimated, as they are usually discarded during analysis. Furthermore, several public databases do not display sSNVs, which can lead to analytical bias and the false assumption that this mutational event is uncommon. Recent progress in our understanding of the deleterious consequences of these sSNVs for RNA stability and protein translation shows that they can act as strong drivers of cancer, as demonstrated for several cancer genes such as TP53 or BCL2L12. It is therefore essential that sSNVs be properly reported and analyzed in order to provide an accurate picture of the genetic landscape of the cancer genome.
单核苷酸变异（SNV）是人类癌症中最常见的基因变化。大多数驱动性改变是位于癌症基因编码区的错义变异和无义变异。无偏倚的癌症基因组测序表明，同义SNV（sSNV）可聚集在多个癌症原癌基因或肿瘤抑制基因的编码区，提示存在纯化选择。目前sSNV被低估了，因为它们在分析过程中通常被舍弃。此外，几个公共数据库并未显示sSNV，这可能导致分析偏差以及错误地认为这种突变事件不常见。我们对这些sSNV对RNA稳定性和蛋白质翻译的有害后果的理解取得了最新进展，结果表明它们可作为癌症的强大驱动因素，如TP53或BCL2L12等多个癌症基因的情况所示。因此，为了准确描绘癌症基因组的遗传格局，必须正确报告和分析sSNV。
