Concordance among gene-expression-based predictors for breast cancer
Concordance among gene-expression-based predictors for breast cancer
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DOI：
10.1056/nejmoa052933
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发表时间：
2006-08-10
影响因子：
158.5
通讯作者：
Perou, Charles M.
中科院分区：
文献类型：
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作者：
Fan, Cheng;Oh, Daniel S.;Perou, Charles M.
背景：不同实验室对原发性乳腺肿瘤进行的基因表达谱研究已经鉴定出许多不同的预后谱或基因集，在基因身份方面几乎没有重叠。方法：为了比较这些基因集对个体样本的预测，我们获得了295个样本的单一数据集，并应用了五种基于基因表达的模型：内在亚型、70个基因谱、伤口反应、复发评分和双基因比（用于接受他莫昔芬治疗的患者）。结果：我们发现大多数模型在个体样本的结果预测中有很高的一致性。特别是，几乎所有被确定为具有基底样、her2阳性和雌激素受体阴性或管腔B（与预后不良相关）的内在亚型的肿瘤也被归类为具有较差的70基因谱、激活的伤口反应和高复发评分。70个基因和复发评分模型开始在临床环境中使用，结果分类显示77%到81%的一致性。结论：尽管不同的基因组被用于乳腺癌患者的预后，但五项测试中的四项在个体患者的预后预测中显示出显著的一致性，并且可能跟踪一组共同的生物表型。
BACKGROUND:Gene-expression-profiling studies of primary breast tumors performed by different laboratories have resulted in the identification of a number of distinct prognostic profiles, or gene sets, with little overlap in terms of gene identity.METHODS:To compare the predictions derived from these gene sets for individual samples, we obtained a single data set of 295 samples and applied five gene-expression-based models: intrinsic subtypes, 70-gene profile, wound response, recurrence score, and the two-gene ratio (for patients who had been treated with tamoxifen).RESULTS:We found that most models had high rates of concordance in their outcome predictions for the individual samples. In particular, almost all tumors identified as having an intrinsic subtype of basal-like, HER2-positive and estrogen-receptor-negative, or luminal B (associated with a poor prognosis) were also classified as having a poor 70-gene profile, activated wound response, and high recurrence score. The 70-gene and recurrence-score models, which are beginning to be used in the clinical setting, showed 77 to 81 percent agreement in outcome classification.CONCLUSIONS:Even though different gene sets were used for prognostication in patients with breast cancer, four of the five tested showed significant agreement in the outcome predictions for individual patients and are probably tracking a common set of biologic phenotypes.