Reliable detection of subclonal single-nucleotide variants in tumour cell populations
Reliable detection of subclonal single-nucleotide variants in tumour cell populations
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DOI：
10.1038/ncomms1814
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发表时间：
2012-05-01
影响因子：
16.6
通讯作者：
Beerenwinkel, Niko
中科院分区：
文献类型：
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作者：
Gerstung, Moritz;Beisel, Christian;Beerenwinkel, Niko
根据克隆进化模型，肿瘤生长是由体细胞进化癌细胞群中的竞争亚克隆驱动的，这导致了遗传异质性肿瘤的产生。在这里，我们提出了一种比较靶向深度测序方法，结合一种定制的统计算法，称为deepSNV，用于检测和定量混合群体中的亚克隆单核苷酸变异。我们在一项严格的实验评估中表明，我们的方法能够检测到频率低至1/10,000等位基因的变异。在从4例肾癌患者的匹配肿瘤和正常样本中分离的TP53和VHL基因的基因组位点中，我们检测到24个等位基因频率从0.0002到0.34不等的变异。此外，我们展示了如何利用已知单核苷酸多态性的等位基因频率来检测杂合性的丧失。我们的研究结果表明，基因组多样性在肾细胞癌中是常见的，并为克隆进化模型提供了定量证据。
According to the clonal evolution model, tumour growth is driven by competing subclones in somatically evolving cancer cell populations, which gives rise to genetically heterogeneous tumours. Here we present a comparative targeted deep-sequencing approach combined with a customised statistical algorithm, called deepSNV, for detecting and quantifying subclonal single-nucleotide variants in mixed populations. We show in a rigorous experimental assessment that our approach is capable of detecting variants with frequencies as low as 1/10,000 alleles. In selected genomic loci of the TP53 and VHL genes isolated from matched tumour and normal samples of four renal cell carcinoma patients, we detect 24 variants at allele frequencies ranging from 0.0002 to 0.34. Moreover, we demonstrate how the allele frequencies of known single-nucleotide polymorphisms can be exploited to detect loss of heterozygosity. Our findings demonstrate that genomic diversity is common in renal cell carcinomas and provide quantitative evidence for the clonal evolution model.