Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, 812-8582, Japan.
Sci Rep. 2023 May 10;13(1):7593. doi: 10.1038/s41598-023-34452-w.
Recent studies have shown that some silent mutations can be harmful to various processes. In this study, we performed a comprehensive in silico analysis to elucidate the effects of silent mutations on cancer pathogenesis using exome sequencing data derived from the Cancer Genome Atlas. We focused on the codon optimality scores of silent mutations, which were defined as the difference between the optimality of synonymous codons, calculated using the codon usage table. The relationship between cancer evolution and silent mutations showed that the codon optimality score of the mutations that occurred later in carcinogenesis was significantly higher than of those that occurred earlier. In addition, mutations with higher scores were enriched in genes involved in the cell cycle and cell division, while those with lower scores were enriched in genes involved in apoptosis and cellular senescence. Our results demonstrate that some silent mutations can be involved in cancer pathogenesis.
最近的研究表明，一些沉默突变可能对各种过程有害。在这项研究中，我们使用癌症基因组图谱（Cancer Genome Atlas）中衍生的外显子组测序数据，进行了全面的计算机分析，以阐明沉默突变对癌症发病机制的影响。我们专注于沉默突变的密码子优化评分，该评分定义为使用密码子使用表计算的同义密码子优化度的差异。癌症进化与沉默突变之间的关系表明，在致癌发生过程中发生较晚的突变的密码子优化评分明显高于发生较早的突变。此外，得分较高的突变在参与细胞周期和细胞分裂的基因中富集，而得分较低的突变在参与细胞凋亡和细胞衰老的基因中富集。我们的研究结果表明，一些沉默突变可能参与癌症的发病机制。
