Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement.
Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement.
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基于微阵列的乳腺癌分子分类的类别发现：观察者间一致性分析。
DOI：
10.1093/jnci/djr071
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发表时间：
2011-04-20
期刊：
影响因子：
--
通讯作者：
Reis-Filho JS
中科院分区：
文献类型：
--
作者：
Mackay A;Weigelt B;Grigoriadis A;Kreike B;Natrajan R;A'Hern R;Tan DS;Dowsett M;Ashworth A;Reis-Filho JS
乳腺癌可以通过使用“内在”基因列表的分级聚类分类为至少五种分子亚型之一：基底样、HER2、管腔A、管腔B和正常乳腺样。由不同数量的基因组成的五种不同的内在基因列表已用于乳腺癌的分子亚型鉴定和分类。本研究的目的是确定的客观性和观察者之间的重复性分配的分子亚型类别的分层聚类分析。三个公开的乳腺癌数据集（n = 779）进行双向平均连锁层次聚类分析，使用五个不同的内在基因列表。我们使用自由边际Kappa统计分析了五位乳腺癌研究人员之间的观察者一致性，根据每个乳腺癌数据集的每个内在基因列表，分别对整个分类和每个分子亚型进行分析。没有一个测试的分类系统在观察者之间产生几乎完美的一致性（Kappa ≥ 0.81）。然而，在四种分子亚型（管腔型、基底细胞样、HER2和正常乳腺样）的所有数据集中一致观察到大量观察者间一致性（70.8%至76.1%的样本和0.635至0.701的自由边缘Kappa评分）。当对管腔癌进行细分（管腔A、B和C）时，在所有分析的数据集中，没有一个分类系统产生实质一致性（Kappa ≥ 0.61）。对每种亚型的单独分析显示，只有两种（基底细胞样和HER2）可以由独立观察者重复鉴定（Kappa ≥ 0.81）。根据分层聚类分析获得的树状图分析，乳腺癌的分子亚型类别的分配是主观的，并显示出适度的观察者间重现性。为了发展分子分类学，需要对每种分子亚型进行客观定义，并对其鉴定方法进行标准化。
Breast cancers can be classified by hierarchical clustering using an “intrinsic” gene list into one of at least five molecular subtypes: basal-like, HER2, luminal A, luminal B, and normal breast-like. Five different intrinsic gene lists composed of varying numbers of genes have been used for molecular subtype identification and classification of breast cancers. The aim of this study was to determine the objectivity and interobserver reproducibility of the assignment of molecular subtype classes by hierarchical cluster analysis. Three publicly available breast cancer datasets (n = 779) were subjected to two-way average-linkage hierarchical cluster analysis using five distinct intrinsic gene lists. We used free-marginal Kappa statistics to analyze interobserver agreement among five breast cancer researchers for the whole classification and for each molecular subtype separately according to each intrinsic gene list for each breast cancer dataset. None of the classification systems tested produced almost perfect agreement (Kappa ≥ 0.81) among observers. However, substantial interobserver agreement (70.8% to 76.1% of the samples and free-marginal Kappa scores from 0.635 to 0.701) was consistently observed in all datasets for four molecular subtypes (luminal, basal-like, HER2, and normal breast-like). When luminal cancers were subdivided (luminal A, B, and C), none of the classification systems produced substantial agreement (Kappa ≥ 0.61) in all the datasets analyzed. Analysis of each subtype separately revealed that only two (basal-like and HER2) could be reproducibly identified by independent observers (Kappa ≥ 0.81). Assignment of molecular subtype classes of breast cancer based on the analysis of dendrograms obtained with hierarchical cluster analysis is subjective and shows modest interobserver reproducibility. For the development of a molecular taxonomy, objective definitions for each molecular subtype and standardized methods for their identification are required.
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影响因子：
2.7
作者：
BRENNAN, RL;PREDIGER, DJ
通讯作者：
PREDIGER, DJ
影响因子：
64.8
作者：
Alizadeh, AA;Eisen, MB;Staudt, LM
通讯作者：
Staudt, LM
DOI：
10.1073/pnas.0601231103
发表时间：
2006-04-11
影响因子：
11.1
作者：
Ein-Dor, L;Zuk, O;Domany, E
通讯作者：
Domany, E
影响因子：
4.4
作者：
Hu, Zhiyuan;Fan, Cheng;Perou, Charles M.
通讯作者：
Perou, Charles M.
影响因子：
7.5
作者：
Livasy, CA;Karaca, G;Perou, CM
通讯作者：
Perou, CM