Modeling double strand break susceptibility to interrogate structural variation in cancer
Modeling double strand break susceptibility to interrogate structural variation in cancer
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DOI：
10.1186/s13059-019-1635-1
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发表时间：
2019-02-08
期刊：
影响因子：
12.3
通讯作者：
Semple, Colin A.
中科院分区：
文献类型：
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作者：
Ballinger, Tracy J.;Bouwman, Britta A. M.;Semple, Colin A.
背景已知结构变异（SV）在多种癌症中发挥重要作用，但其起源和功能后果仍知之甚少。许多 SV 被认为是由于 DNA 双链断裂 (DSB) 后修复过程中的错误而产生的。结果我们在具有匹配染色质和序列特征的细胞系中使用实验量化的 DSB 频率，得出了第一个 DSB 易感性的定量全基因组模型。这些模型非常准确，为生成 DSB 的突变机制提供了新颖的见解。在一种细胞类型中训练的模型可以成功应用于其他细胞类型，但很大一部分 DSB 似乎反映了细胞类型特定的过程。使用模型预测作为肿瘤中 DSB 敏感性的代理，许多 SV 富集区域似乎仅通过选择性中性突变偏差很难解释。鉴于预测的突变易感性，这些区域中的大量区域显示出出乎意料的高 SV 断点频率，因此是肿瘤中正选择的可靠目标。这些推定的阳性选择的 SV 热点富含先前显示致癌的基因。相比之下，基因组中的数百个区域显示出出乎意料的低水平的 SV，因为它们对突变的敏感性相对较高。这些新的冷点区域似乎受到肿瘤中纯化选择的影响，并且富含活性启动子和增强子。结论我们得出结论，DSB 易感性模型为推论推定受到肿瘤选择的 SV 提供了严格的方法。
BackgroundStructural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs).ResultsWe used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type-specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumors, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumors. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumors and are enriched for active promoters and enhancers.ConclusionsWe conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumors.