4.8 Article

Laser microdissection and microarray analysis of breast tumors reveal ER-α related genes and pathways

期刊

ONCOGENE
卷 25, 期 9, 页码 1413-1419

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/sj.onc.1209165

关键词

breast tumors; laser microdissection; DNA microarray; gene profiling; estrogen receptor

向作者/读者索取更多资源

About 70-80% of breast cancers express estrogen receptor alpha (ER-alpha), and estrogens play important roles in the development and growth of hormone-dependent tumors. Together with lymph node metastasis, tumor size, and histological grade, ER status is considered as one of the prognostic factors in breast cancer, and an indicator for hormonal treatment. To investigate genes and pathways that are associated with ER status and epithelial cells in breast tumor, we applied laser capture microdissection (LCM) technology to capture epithelial tumor cells from 28 lymph node-negative breast tumor samples, in which 17 patients had ER-alpha + tumors, and 11 patients have ER-alpha- tumors. Gene expression profiles were analysed on Affymetrix Hu133A GeneChip. Meanwhile, gene profiles using total RNA isolated from bulk tumors of the same 28 patients were also generated. In total, 146 ;genes and 112 genes with significant P-value and having significant differential expression between ER-alpha + and ER-alpha- tumors were identified from the LCM data set and bulk tissue data set, respectively. A total of 61 genes were found to be common in both data sets, while 85 genes were unique to the LCM data set and 51 genes were present only in the bulk tumor data set. Pathway analysis with the 85 genes using Gene Ontology suggested that genes involved in endocytosis, ceramide generation, Ras/ERK/Ark cascade, and JAT-STAT pathways may play roles related to ER. The gene pro. ling with LCM-captured tumor cells provides a unique approach to study epithelial tumor cells and to gain an insight into signaling pathways associated with ER.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据