A transcriptional fingerprint of estrogen in human breast cancer predicts patient survival
A transcriptional fingerprint of estrogen in human breast cancer predicts patient survival
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DOI：
10.1593/neo.07859
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发表时间：
2008-01-01
期刊：
影响因子：
4.8
通讯作者：
Rae, James M.
中科院分区：
文献类型：
--
作者：
Chinnaiyan, Arul M.;Lippman, Marc E.;Rae, James M.
雌激素信号在乳腺癌进展中发挥着重要作用，雌激素受体 (ER) 状态长期以来一直是激素反应性的标志。然而，ER 状态本身并不能完全预测内分泌治疗，因为一些 ER+ 肿瘤的预后较差。在这里，我们试图利用 ER+ 乳腺癌细胞的表达谱来筛选强大的雌激素调节基因特征，该特征可以作为癌症结果的更好指标。我们鉴定了 532 个雌激素诱导基因，并进一步开发了 73 个基因特征，通过逐步交叉验证，该特征可以最好地将 286 个原发性乳腺癌训练集分为预后亚型。值得注意的是，该特征预测了 10 多个患者队列及其各自 ER+ 子队列的临床结果。此外，这一特征将接受内分泌治疗的患者分为两个预后亚组，表明其作为雌激素信号传导以及激素敏感性测量的特异性。 73 基因特征还为患者生存提供了额外的预测价值，独立于其他临床参数，并且优于之前报道的其他分子结果特征。总而言之，这些数据证明了使用细胞培养系统筛选具有临床相关性的强大基因特征的能力。
Estrogen signaling plays an essential role in breast cancer progression, and estrogen receptor (ER) status has long been a marker of hormone responsiveness. However, ER status alone has been an incomplete predictor of endocrine therapy, as some ER+ tumors, nevertheless, have poor prognosis. Here we sought to use expression profiling of ER+ breast cancer cells to screen for a robust estrogen-regulated gene signature that may serve as a better indicator of cancer outcome. We identified 532 estrogen-induced genes and further developed a 73-gene signature that best separated a training set of 286 primary breast carcinomas into prognostic subtypes by stepwise cross-validation. Notably, this signature predicts clinical outcome in over 10 patient cohorts as well as their respective ER+ subcohorts. Further, this signature separates patients who have received endocrine therapy into two prognostic subgroups, suggesting its specificity as a measure of estrogen signaling, and thus hormone sensitivity. The 73-gene signature also provides additional predictive value for patient survival, independent of other clinical parameters, and outperforms other previously reported molecular outcome signatures. Taken together, these data demonstrate the power of using cell culture systems to screen for robust gene signatures of clinical relevance.