Combining serial analysis of gene expression and array technologies to identify genes differentially expressed in breast cancer.
Combining serial analysis of gene expression and array technologies to identify genes differentially expressed in breast cancer.
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发表时间：
1999-11
期刊：
影响因子：
11.2
通讯作者：
M. Nacht;A. Ferguson;Wen Zhang;J. Petroziello;B. Cook;Yu Hong Gao;Sharon Maguire;Deborah Riley;George Coppola;G. Landes;S. Madden;S. Sukumar
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作者：
M. Nacht;A. Ferguson;Wen Zhang;J. Petroziello;B. Cook;Yu Hong Gao;Sharon Maguire;Deborah Riley;George Coppola;G. Landes;S. Madden;S. Sukumar
最近已使用几种方法来确定细胞群的基因表达谱。在这里，我们展示了基因表达系列分析 (SAGE) 和 DNA 阵列这两种方法相结合的优势，通过寻找原发性乳腺癌、转移性乳腺癌和正常乳腺上皮细胞中不同水平一致表达的基因，帮助阐明乳腺癌进展的途径。将两种特征明确的乳腺肿瘤细胞系 21PT 和 21MT 的 SAGE 图谱与正常乳腺上皮细胞的 SAGE 图谱进行比较，以确定差异表达的基因。然后将这些候选物的子集放置在阵列上，并用临床乳腺肿瘤样本进行筛选，以找到在患病组织和正常组织中以不同水平一致表达的基因和表达序列标签。除了发现已知乳腺癌标志物 HER-2/neu 和 MUC-1 的预测过度表达之外，SAGE 和 DNA 阵列的强大耦合还导致了先前未涉及乳腺癌的基因和潜在途径的鉴定。此外，这些技术还生成了有关原发性和转移性乳腺肿瘤表达谱的差异和相似性的信息。因此，结合 SAGE 和定制阵列技术可以快速识别和验证许多可能参与乳腺癌进展的基因的临床相关性。这些差异表达的基因可用作肿瘤标志物和预后指标，并且可能是各种形式的治疗干预的合适靶标。
Several methods have been used recently to determine gene expression profiles of cell populations. Here we demonstrate the strength of combining two approaches, serial analysis of gene expression (SAGE) and DNA arrays, to help elucidate pathways in breast cancer progression by finding genes consistently expressed at different levels in primary breast cancers, metastatic breast cancers, and normal mammary epithelial cells. SAGE profiles of 21PT and 21MT, two well-characterized breast tumor cell lines, were compared with SAGE profiles of normal breast epithelial cells to identify differentially expressed genes. A subset of these candidates was then placed on an array and screened with clinical breast tumor samples to find genes and expressed sequence tags that are consistently expressed at different levels in diseased and normal tissues. In addition to finding the predicted overexpression of known breast cancer markers HER-2/neu and MUC-1, the powerful coupling of SAGE and DNA arrays resulted in the identification of genes and potential pathways not implicated previously in breast cancer. Moreover, these techniques also generated information about the differences and similarities of expression profiles in primary and metastatic breast tumors. Thus, combining SAGE and custom array technology allowed for the rapid identification and validation of the clinical relevance of many genes potentially involved in breast cancer progression. These differentially expressed genes may be useful as tumor markers and prognostic indicators and may be suitable targets for various forms of therapeutic intervention.