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首页> 外文期刊>Human Molecular Genetics >Comparative analysis of somatic copy-number alterations across different human cancer types reveals two distinct classes of breakpoint hotspots
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Comparative analysis of somatic copy-number alterations across different human cancer types reveals two distinct classes of breakpoint hotspots

机译:跨不同人类癌症类型的体细胞拷贝数变化的比较分析揭示了两种截然不同的断点热点

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Somatic copy-number alterations (SCNAs) play a crucial role in the development of human cancer. However, it is not well understood what evolutionary mechanisms contribute to the global patterns of SCNAs in cancer genomes. Taking advantage of data recently available through The Cancer Genome Atlas, we performed a systematic analysis on genome-wide SCNA breakpoint data for eight cancer types. First, we observed a high degree of overall similarity among the SCNA breakpoint landscapes of different cancer types. Then, we compiled 19 genomic features and evaluated their effects on the observed SCNA patterns. We found that evolutionary indel and substitution rates between species (i.e. humans and chimpanzees) consistently show the strongest correlations with breakpoint frequency among all the surveyed features; whereas the effects of some features are quite cancer-type dependent. Focusing on SCNA breakpoint hotspots, we found that cancer-type-specific breakpoint hotspots and common hotspots show distinct patterns. Cancer-type-specific hotspots are enriched with known cancer genes but are poorly predicted from genomic features; whereas common hotspots show the opposite patterns. This contrast suggests that explaining high-frequency SCNAs in cancer may require different evolutionary models: positive selection driven by cancer genes, and non-adaptive evolution related to an intrinsically unstable genomic context. Our results not only present a systematic view of the effects of genetic factors on genome-wide SCNA patterns, but also provide deep insights into the evolutionary process of SCNAs in cancer.
机译:体细胞拷贝数改变(SCNA)在人类癌症的发展中起着至关重要的作用。但是,尚不清楚什么进化机制有助于癌症基因组中SCNA的整体模式。利用最近通过The Cancer Genome Atlas获得的数据,我们对八种癌症类型的全基因组SCNA断点数据进行了系统分析。首先,我们观察到了不同癌症类型的SCNA断点景观之间的高度相似性。然后,我们编辑了19个基因组特征,并评估了它们对观察到的SCNA模式的影响。我们发现,在所有调查的特征中,物种(即人类和黑猩猩)之间的进化插入/缺失率始终显示出与断点频率的最强相关性;而某些功能的效果则完全取决于癌症类型。着眼于SCNA断点热点,我们发现特定于癌症类型的断点热点和常见热点显示出不同的模式。特定于癌症类型的热点富含已知的癌症基因,但是从基因组特征上很难预测。而常见的热点则显示出相反的模式。这种对比表明,解释癌症中的高频SCNA可能需要不同的进化模型:由癌症基因驱动的阳性选择,以及与内在不稳定的基因组环境有关的非适应性进化。我们的结果不仅提供了遗传因素对全基因组SCNA模式影响的系统视图,而且还提供了对SCNA在癌症中进化过程的深刻见解。

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