Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ 08873, USA.
Department of Genetics, Rutgers University, Piscataway, NJ 08854, USA.
Genes (Basel). 2022 Apr 27;13(5):778. doi: 10.3390/genes13050778.
Synonymous single nucleotide variants (sSNVs) are often considered functionally silent, but a few cases of cancer-causing sSNVs have been reported. From available databases, we collected four categories of sSNVs: germline, somatic in normal tissues, somatic in cancerous tissues, and putative cancer drivers. We found that screening sSNVs for recurrence among patients, conservation of the affected genomic position, and synVep prediction (synVep is a machine learning-based sSNV effect predictor) recovers cancer driver variants (termed ) and previously unknown putative cancer genes. Of the 2.9 million somatic sSNVs found in the COSMIC database, we identified 2111 proposed cancer driver sSNVs. Of these, 326 sSNVs could be further tagged for possible RNA splicing effects, RNA structural changes, and affected RBP motifs. This list of proposed cancer driver sSNVs provides computational guidance in prioritizing the experimental evaluation of synonymous mutations found in cancers. Furthermore, our list of novel potential cancer genes, galvanized by synonymous mutations, may highlight yet unexplored cancer mechanisms.
同义单核苷酸变异（sSNV）通常被认为是功能上沉默的，但也有少数报道称其可致癌。我们从现有的数据库中收集了四类 sSNV：种系、正常组织中的体细胞、癌组织中的体细胞和推定的癌症驱动因子。我们发现，对患者中 sSNV 的复发进行筛选、受影响基因组位置的保守性以及 synVep 预测（synVep 是一种基于机器学习的 sSNV 效应预测器）可恢复癌症驱动因子变异（称为）和以前未知的推定癌症基因。在 COSMIC 数据库中发现的 290 万个体细胞 sSNV 中，我们确定了 2111 个拟议的癌症驱动 sSNV。其中，326 个 sSNV 可进一步标记可能的 RNA 剪接效应、RNA 结构变化和受影响的 RBP 基序。这些拟议的癌症驱动 sSNV 列表为在癌症中发现的同义突变的实验评估提供了计算指导。此外，我们通过同义突变发现的新的潜在癌症基因列表可能突出了尚未探索的癌症机制。
