Inferring structural variant cancer cell fraction
Inferring structural variant cancer cell fraction
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DOI：
10.1038/s41467-020-14351-8
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发表时间：
2020-02-05
影响因子：
16.6
通讯作者：
Macintyre, Geoff
中科院分区：
文献类型：
--
作者：
Cmero, Marek;Yuan, Ke;Macintyre, Geoff
我们提出了SVclone，一种从全基因组测序数据中推断癌细胞结构变异（SV）断点分数的计算方法。SVclone准确地确定两个SV断裂端的变异等位基因频率，然后同时估计癌细胞分数和SV拷贝数。我们使用已知比例的真实的样本的计算机模拟混合物评估性能，这些样本是从同一患者的两个克隆转移瘤中产生的。我们发现，SVclone的性能与基于单核苷酸变体的方法相当，尽管数据点少了一个数量级。作为泛癌症全基因组分析（PCAWG）联盟的一部分，该联盟汇总了来自38种肿瘤类型的2658种癌症的全基因组测序数据，我们使用SVclone来揭示具有亚克隆富集拷贝数中性重排的肝癌，卵巢癌和胰腺癌的子集，这些重排显示总生存率降低。SVclone能够改善SV肿瘤内异质性的表征。
We present SVclone, a computational method for inferring the cancer cell fraction of structural variant (SV) breakpoints from whole-genome sequencing data. SVclone accurately determines the variant allele frequencies of both SV breakends, then simultaneously estimates the cancer cell fraction and SV copy number. We assess performance using in silico mixtures of real samples, at known proportions, created from two clonal metastases from the same patient. We find that SVclone's performance is comparable to single-nucleotide variant-based methods, despite having an order of magnitude fewer data points. As part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we use SVclone to reveal a subset of liver, ovarian and pancreatic cancers with subclonally enriched copy-number neutral rearrangements that show decreased overall survival. SVclone enables improved characterisation of SV intra-tumour heterogeneity.