Prediction of hormone sensitivity by DNA microarray
Prediction of hormone sensitivity by DNA microarray
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DOI：
10.1016/j.biopha.2003.09.005
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发表时间：
2004-01-01
影响因子：
7.5
通讯作者：
Hayashi，SI
中科院分区：
文献类型：
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作者：
Hayashi，SI
内分泌治疗继续被广泛开发用于乳腺癌的治疗，对这种激素相关癌症的准确治疗预测是非常必要的。此外，雌激素及其受体在乳腺癌细胞雌激素依赖性生长中的作用至今还不清楚。因此，为了开发一种新的内分泌治疗诊断工具，并研究雌激素依赖性乳腺癌发生的分子机制，我们利用DNA微阵列技术研究了乳腺癌中雌激素反应基因的基因表达谱。我们首先通过大规模的DNA微阵列全面分析了几种雌激素受体(ER)阳性的癌细胞株的雌激素反应性。根据所获得的信息，共筛选出138个在雌激素刺激下高诱导或高抑制表达的基因，并提供定制芯片。定制微阵列分析的结果与大规模微阵列分析的结果一致，并显示它们明确地被归类为早反应或晚反应类型。对这些基因的进一步分析可能会为阐明癌症的雌激素依赖生长机制提供新的线索。此外，对ER阳性乳腺癌组织的定制微阵列分析也显示出与细胞系相似但不完全相同的特征，表明这种定制微阵列有潜力预测乳腺癌内分泌治疗的反应。此外，为了寻找乳腺癌患者内分泌治疗的新预测因素，我们选择了几个候选基因，并用实时定量RT-PCR和免疫组织化学技术分析了它们在乳腺癌组织中的表达。这些研究可能为阐明癌症的雌激素依赖机制和为患者提供临床益处提供新的线索。
Endocrine-therapy continues to be extensively developed for treatment of breast cancer, and accurate therapeutic prediction of this hormone-associated cancer is strongly desired. Moreover, the role of estrogen and its receptor on the estrogen-dependent growth of breast cancer cells has not been clarified hitherto. Thus, to develop a new diagnostic tool for endocrine-therapy, and to address the molecular mechanism of estrogen-dependent breast carcinogenesis, we investigated the gene expression profile of estrogen-responsive genes in breast cancer using DNA microarray technique. We first comprehensively analyzed the profile of estrogen responsiveness among several estrogen receptor (ER)-positive cancer cell lines by a large-scale DNA microarray. Based on the obtained information, a total of 138 genes which showed high induction or repression of the expression by estrogen stimulation were selected and provided for custom microarray. The results of the custom microarray analysis were consistent with those of large-scale microarray analysis, and revealed that they were clearly categorized into early- or late-response types. Further analysis of these genes may provide new clues in the elucidation of the estrogen-dependent growth mechanisms of cancer. Furthermore, the custom microarray analysis of ER-positive breast cancer tissues also showed similar but not identical profiles to those of cell lines, indicating the potential of this custom microarray to predict the response to endocrine-therapy in the breast cancer. Moreover, in order to discover the new predictive factors for endocrine therapy in breast cancer patients, several candidate genes were selected and their expressions in breast cancer tissues were analyzed by real-time RT-PCR and by immunohistochemical technique. These studies could provide new clues for elucidation of the estrogen-dependent mechanisms of cancer and clinical benefit for patients.