Aromatase inhibitors - Gene discovery
Aromatase inhibitors - Gene discovery
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DOI：
10.1016/j.jsbmb.2007.05.013
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发表时间：
2007-08-01
影响因子：
4.1
通讯作者：
Dixon, J. Michael
中科院分区：
文献类型：
--
作者：
Miller, William R.;Larionov, Alexey;Dixon, J. Michael
肿瘤RNA的微阵列分析是一种非常强大的工具，可以测量全局基因表达。当与新辅助治疗方案联合使用时，其中对乳房内的原发性肿瘤给予治疗，可以分析连续活检，并将结果与临床和病理学反应相关联。在本研究中，使用了新辅助方案，给予第三代抑制剂来曲唑3个月，并对治疗前和治疗后10-14天从活检中提取的RNA进行微阵列分析。目的是发现：（i）随着雌激素缺乏而改变的基因（来曲唑唯一已知的生物学作用是抑制芳香酶活性并减少绝经后妇女的内源性雌激素）和（ii）其基础，在对治疗有反应或有抗性的肿瘤之间，（以便制定反应/抗性的预测指数）基因表达的早期变化是通过比较58名患者在14天治疗前后采用三种不同的方法进行的配对肿瘤核心活检来确定的。变化、变化幅度和SAM分析。所有三种方法都显示了更多数量的基因被下调而不是上调。合并的数据产生的143个基因，这是基因本体论和聚类分析。91个下调基因的本体论表明，它们在功能上与细胞周期进程，特别是有丝分裂相关。相比之下，上调基因与器官发育和细胞外基质的周转和regulation.Clinical反应是在52例患者进行评估，37（71%）肿瘤被归类为临床反应（在3个月体积减少>50%）。前和14天活检的微阵列分析确定了291个协变量（84个基线，72个14天和135个变化）高度预测反应状态。使用协变量的相似性矩阵显示，响应肿瘤具有相似的遗传特征，这与非响应癌症不同，而非响应病例彼此不同。预测缓解的基因变化与整个组中治疗显著变化的基因不一致。(C)2007爱思唯尔有限公司版权所有。
Microarray analysis of tumour RNA is an extremely powerful tool which allows global gene expression to be measured. When used in combination with neoadjuvant treatment protocols in which therapy is given with the primary tumour within the breast, sequential biopsies may be analysed and results correlated with clinical and pathological response. In the present study, a neoadjuvant protocol has been used, administering the third generation inhibitor, letrozole, for 3 months and subjecting RNA extracted from biopsies taken before and after 10-14 days of treatment to microarray analysis. The objectives were to discover: (i) genes that change with estrogen deprivation (the only known biological effect of letrozole is to inhibit aromatase activity and reduce endogenous estrogens in postmenopausal women) and (ii) genes whose basal, on treatment or change in expression differ between tumours which are either responsive or resistant to treatment (so that predictive indices of response/resistance may be developed).Early changes in gene expression were identified by comparing paired tumour core biopsies taken before and after 14 days treatment in 58 patients using three different approaches based on frequency of changes, magnitude of changes and SAM analysis. All three approaches showed a greater number of genes were down-regulated than up-regulated. Merging of the data produced a total of 143 genes which were subject to gene ontology and cluster analysis. The ontology of the 91 down-regulated genes showed that they were functionally associated with cell cycle progression, particularly mitosis. In contrast, up-regulated genes were associated with organ development and extra-cellular matrix turnover and regulation.Clinical response was assessable in 52 patients; 37 (71%) tumours were classified as clinical responders (>50% reduction in volume at 3 months). Microarray analysis of pre- and 14-day biopsies identified 291 covariates (84 baselines, 72 14-day and 135 changes) highly predictive of response status. A similarity matrix using the covariates showed responding tumours have a similar genetic profile which was dissimilar to non-responding cancers whereas non-responsive cases were distinctive from each other. Changed genes predicting for response showed no concordance with those changed significantly by treatment in the overall group. (C) 2007 Elsevier Ltd. All rights reserved.