Losing balance: Hardy-Weinberg disequilibrium as a marker for recurrent loss-of-heterozygosity in cancer.
Losing balance: Hardy-Weinberg disequilibrium as a marker for recurrent loss-of-heterozygosity in cancer.
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失去平衡：哈迪-温伯格不平衡作为癌症中反复出现的杂合性丧失的标志。
DOI：
10.1093/hmg/ddr422
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发表时间：
2011
影响因子：
3.5
通讯作者：
LaFramboise,Thomas
中科院分区：
文献类型：
--
作者：
Wilkins,Katherine;LaFramboise,Thomas
鉴定肿瘤样本中的杂合性缺失（洛）区域是一个具有挑战性的问题。最先进的计算方法可以从单核苷酸多态性（SNP）阵列数据中推断出洛，但调用精确的边界是复杂的正常细胞污染和标记，是纯合的种系，因此没有信息。最近，焦点转移到精确定位多个肿瘤中反复受洛缺失事件影响的位点。复发性洛缺失区域通常含有对肿瘤抑制重要的基因。在这里，我们提出了一种方法，推断洛率在整个样本集上的SNP的SNP的基础上。我们的方法通过利用简单的原理来实现这一点，根据定义，洛缺失会耗尽杂合子，从而破坏Hardy-Weinberg平衡。我们应用这种LOH影响的中断的统计检验，并得出一个最大似然估计的洛率的基础上观察到的杂合子的数量。这解释了洛缺失和拷贝中性两种形式，并且没有利用匹配的正常基因型。功效模拟显示了统计检验的高灵敏度水平，并且应用于对照正常组织数据集表明了低错误发现率。我们将该方法应用于三个大型公开的肿瘤SNP阵列数据集，在那里它能够定位肿瘤抑制基因靶的洛事件。在不同平台/实验室之间以及细胞系和肿瘤之间，推断的洛率相当一致，但具有肿瘤类型依赖性。最后，我们得出的利率估计通常高于先前公布的，并提供证据表明后者可能被低估。
Identifying regions of loss-of-heterozygosity (LOH) in a tumor sample is a challenging problem. State-of-the-art computational approaches can infer LOH from single-nucleotide polymorphism (SNP) array data, but calling precise boundaries is complicated by normal-cell contamination and markers that are homozygous in the germline and therefore non-informative. More recently, the focus has shifted to pinpointing the loci recurrently affected by LOH events across multiple tumors. Recurrent LOH regions often harbor genes important for tumor suppression. Here, we propose a method that infers LOH rates across an entire sample set on an SNP-by-SNP basis. Our method achieves this by leveraging the straightforward principle that, by definition, LOH depletes heterozygotes, thereby disrupting Hardy–Weinberg equilibrium. We apply a statistical test for such LOH-influenced disruptions, and derive a maximum-likelihood estimator for the LOH rate based on the observed number of heterozygotes. This accounts for LOH in both its hemizygous deletion and copy-neutral forms, and does not make use of matched normal genotypes. Power simulations show high levels of sensitivity for the statistical test, and application to a control normal-tissue data set demonstrates a low false-discovery rate. We apply the method to three large publicly available tumor SNP array data sets, where it is able to localize tumor-suppressor gene targets of the LOH events. Inferred LOH rates are quite concordant across platforms/laboratories and between cell lines and tumors, but in a tumor type-dependent fashion. Finally, we produce rate estimates that are generally higher than previously published, and provide evidence that the latter are likely underestimates.
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影响因子：
3.3
作者：
J. K. Pritchard;Matthew Stephens;Peter Donnelly
通讯作者：
J. K. Pritchard;Matthew Stephens;Peter Donnelly
影响因子：
11.2
作者：
Solomon DA;Kim JS;Cronin JC;Sibenaller Z;Ryken T;Rosenberg SA;Ressom H;Jean W;Bigner D;Yan H;Samuels Y;Waldman T
通讯作者：
Waldman T
影响因子：
11.2
作者：
Koehler, Jacqueline A.;Harper, Will;Drucker, Daniel J.
通讯作者：
Drucker, Daniel J.
影响因子：
11.2
作者：
Burgoyne AM;Phillips-Mason PJ;Burden-Gulley SM;Robinson S;Sloan AE;Miller RH;Brady-Kalnay SM
通讯作者：
Brady-Kalnay SM