Testing clonal relatedness of tumors using array comparative genomic hybridization: a statistical challenge.
Testing clonal relatedness of tumors using array comparative genomic hybridization: a statistical challenge.
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DOI：
10.1158/1078-0432.ccr-09-2398
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发表时间：
2010-03-01
期刊：
影响因子：
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通讯作者：
Begg CB
中科院分区：
文献类型：
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作者：
Ostrovnaya I;Begg CB
近年来，几个研究小组试图使用表征肿瘤体细胞改变的阵列技术，例如阵列比较基因组杂交（ACGH），将来自同一患者的一对肿瘤分类为独立的原发性癌症或转移瘤。人们提出了各种各样的策略。多个小组已尝试使用层次聚类来实现此目的。这项技术在基因组学中得到了普及，作为一种寻找具有相似基因表达模式的患者群的方法，以期找到具有不同临床特征的肿瘤子类别。不幸的是，这种方法不太适合将单个肿瘤对分类为克隆或独立的问题。在本文中，我们展示了为什么层次聚类不适合此目的，以及为什么这种方法具有自相矛盾的特性，即随着更多信息的积累（即更多患者），正确识别克隆肿瘤对的概率会下降。我们讨论了已经提出的基于更传统的统计测试和诊断概念表述的替代策略，并指出了为该问题构建有效且稳健的技术所面临的剩余挑战。
In recent years several investigative groups have sought to use array technologies that characterize somatic alterations in tumors, such as array comparative genomic hybridization (ACGH), to classify pairs of tumors from the same patients as either independent primary cancers or metastases. A wide variety of strategies have been proposed. Several groups have endeavored to use hierarchical clustering for this purpose. This technique was popularized in genomics as a means of finding clusters of patients with similar gene expression patterns with a view to finding sub-categories of tumors with distinct clinical characteristics. Unfortunately, this method is not well suited to the problem of classifying individual pairs of tumors as either clonal or independent. In this article we show why hierarchical clustering is unsuitable for this purpose, and why this method has the paradoxical property of producing a declining probability that clonal tumor pairs will be correctly identified as more information is accrued (i.e. more patients). We discuss alternative strategies that have been proposed that are based on more conventional conceptual formulations for statistical testing and diagnosis, and point to the remaining challenges in constructing valid and robust techniques for this problem.