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人类基因的差异可以通过分析黑色素瘤中由紫外线引起的沉默突变来估计其对紫外线的敏感性。

Human genes differ by their UV sensitivity estimated through analysis of UV-induced silent mutations in melanoma.

机构信息

Department of Medicine, Baylor College of Medicine, Houston, Texas.

Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.

出版信息

Hum Mutat. 2020 Oct;41(10):1751-1760. doi: 10.1002/humu.24078. Epub 2020 Jul 15.

Abstract

We hypothesized that human genes differ by their sensitivity to ultraviolet (UV) exposure. We used somatic mutations detected by genome-wide screens in melanoma and reported in the Catalog Of Somatic Mutations In Cancer. As a measure of UV sensitivity, we used the number of silent mutations generated by C>T transitions in pyrimidine dimers of a given transcript divided by the number of potential sites for this type of mutations in the transcript. We found that human genes varied by UV sensitivity by two orders of magnitude. We noted that the melanoma-associated tumor suppressor gene CDKN2A was among the top five most UV-sensitive genes in the human genome. Melanoma driver genes have a higher UV-sensitivity compared with other genes in the human genome. The difference was more prominent for tumor suppressors compared with oncogene. The results of this study suggest that differential sensitivity of human transcripts to UV light may explain melanoma specificity of some driver genes. Practical significance of the study relates to the fact that differences in UV sensitivity among human genes need to be taken into consideration whereas predicting melanoma-associated genes by the number of somatic mutations detected in a given gene.

摘要

我们假设人类基因对紫外线(UV)暴露的敏感性存在差异。我们使用黑色素瘤全基因组筛选中检测到的体细胞突变,并在癌症体细胞突变目录中进行了报道。作为对 UV 敏感性的衡量标准,我们使用给定转录本中嘧啶二聚体的 C>T 转换产生的沉默突变数量除以转录本中这种类型突变的潜在位点数量。我们发现人类基因的 UV 敏感性差异达到两个数量级。我们注意到,与人类基因组中的其他基因相比,黑色素瘤相关的肿瘤抑制基因 CDKN2A 是最敏感的前五个人类基因之一。与人类基因组中的其他基因相比,黑色素瘤驱动基因的 UV 敏感性更高。与癌基因相比,肿瘤抑制基因的差异更为明显。这项研究的结果表明,人类转录本对紫外线的敏感性差异可能解释了一些驱动基因对黑色素瘤的特异性。该研究的实际意义在于,需要考虑人类基因之间 UV 敏感性的差异,而不是根据给定基因中检测到的体细胞突变数量来预测与黑色素瘤相关的基因。

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本文引用的文献

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