Estrogen-regulated genes predict survival in hormone receptor-positive breast cancers
Estrogen-regulated genes predict survival in hormone receptor-positive breast cancers
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DOI：
10.1200/jco.2005.03.2755
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发表时间：
2006-04-10
影响因子：
45.3
通讯作者：
Perou, CM
中科院分区：
文献类型：
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作者：
Oh, DS;Troester, MA;Perou, CM
目的雌激素受体（ER）和/或孕激素受体（PR）阳性乳腺癌患者的预后是高度可变的。因此，我们开发了一个基于基因表达的结果预测ER+和/或PR+（即管腔）乳腺癌患者使用这些tumors.Materials和MethodsThe ER+ MCF-7乳腺癌细胞系的生物差异与17 β-雌二醇，以确定雌激素调节基因。这些基因被用来开发一个结果预测65管腔上皮原发性乳腺癌的训练集。结果预测，然后验证在三个独立的公布datasets.ResultsThe雌激素诱导的基因集确定在MCF-7细胞被用于分层聚类65肿瘤训练集成两组，这表明在生存显着差异（P =.0004）。监督分析确定了822个基因，最佳定义这两组，与预后不良组IIE显示高表达的细胞增殖和抗凋亡基因。预后良好的IE组显示雌激素和GATA 3调节基因的高表达。将为每组创建的平均表达谱（即质心）应用于来自三个已发表数据集的ER+和/或PR+肿瘤。对于所有数据集，Kaplan-Meier生存分析显示IE组和IIE组肿瘤的无复发生存率和总生存率存在显著差异。最大的测试数据集的多变量考克斯分析表明，这个预测增加了显着的预后信息独立的标准临床预测和其他基因表达为基础的predictors.ConclusionThis研究提供了新的生物信息，激素受体阳性乳腺癌内的差异和一种手段，预测长期的结果在他莫昔芬治疗的患者。
PurposeThe prognosis of a patient with estrogen receptor (ER) and/or progesterone receptor (PR) -positive breast cancer can be highly variable. Therefore, we developed a gene expression-based outcome predictor for ER+ and/or PR+ (ie, luminal) breast cancer patients using biologic differences among these tumors.Materials and MethodsThe ER+ MCF-7 breast cancer cell line was treated with 17 beta-estradiol to identify estrogen-regulated genes. These genes were used to develop an outcome predictor on a training set of 65 luminal epithelial primary breast carcinomas. The outcome predictor was then validated on three independent published data sets.ResultsThe estrogen-induced gene set identified in MCF-7 cells was used to hierarchically cluster a 65 tumor training set into two groups, which showed significant differences in survival (P =.0004). Supervised analyses identified 822 genes that optimally defined these two groups, with the poor-prognosis group IIE showing high expression of cell proliferation and antiapoptosis genes. The good prognosis group IE showed high expression of estrogen- and GATA3-regulated genes. Mean expression profiles (ie, centroids) created for each group were applied to ER+ and/or PR+ tumors from three published data sets. For all data sets, Kaplan-Meier survival analyses showed significant differences in relapse-free and overall survival between group IE and IIE tumors. Multivariate Cox analysis of the largest test data set showed that this predictor added significant prognostic information independent of standard clinical predictors and other gene expression-based predictors.ConclusionThis study provides new biologic information concerning differences within hormone receptor-positive breast cancers and a means of predicting long-term outcomes in tamoxifen-treated patients.