CellMiner: a web-based suite of genomic and pharmacologic tools to explore transcript and drug patterns in the NCI-60 cell line set.
CellMiner: a web-based suite of genomic and pharmacologic tools to explore transcript and drug patterns in the NCI-60 cell line set.
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DOI：
10.1158/0008-5472.can-12-1370
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发表时间：
2012-07-15
期刊：
影响因子：
11.2
通讯作者：
Pommier Y
中科院分区：
文献类型：
--
作者：
Reinhold WC;Sunshine M;Liu H;Varma S;Kohn KW;Morris J;Doroshow J;Pommier Y
高通量、高内容的数据库是分子医学、系统生物学和药理学领域日益重要的资源。然而，信息通常驻留在笨重的数据库中，限制了现成的数据分析和集成。在这方面提供巨大改进潜力的一个资源是美国国家癌症研究所编制的 NCI-60 细胞系数据库，该数据库已在众多基因组和药理学反应平台上进行了广泛的表征。在本报告中，我们介绍了一个 CellMiner1 Web 应用程序，旨在改进这个广泛数据库的使用。 CellMiner 工具可以快速检索 22,217 个基因和 360 个 microRNA 的转录本数据，以及 18,549 种化合物的活性报告，其中包括美国食品和药物管理局批准的 91 种药物。使用新颖的模式匹配工具将这些差异水平转换为 NCI-60 中的定量模式，阐明数据组织和交叉比较。可以针对用户兴趣和专业知识以迭代方式进行对参数之间潜在关系的数据查询。 CellMiner 提供的计算机发现过程示例用于多药耐药性分析和阿霉素活性；结肠特异性基因、microRNA 和药物的鉴定；与 miR-17-92 簇相关的 microRNA；以及与厄洛替尼、吉非替尼、阿法替尼和拉帕替尼相匹配的药物识别模式。 CellMiner 通过创建快速、灵活且易于无需生物信息学专业知识的用户应用的基于 Web 的流程，极大地拓宽了广泛的 NCI-60 数据库的发现应用。
High-throughput and high-content databases are increasingly important resources in molecular medicine, systems biology, and pharmacology. However, the information usually resides in unwieldy databases, limiting ready data analysis and integration. One resource that offers substantial potential for improvement in this regard is the NCI-60 cell line database compiled by the US National Cancer Institute, which has been extensively characterized across numerous genomic and pharmacological response platforms. In this report we introduce a CellMiner1 web application designed to improve use of this extensive database. CellMiner tools allowed rapid data retrieval of transcripts for 22,217 genes and 360 microRNAs along with activity reports for 18,549 chemical compounds including 91 drugs approved by the US Food and Drug Administration. Converting these differential levels into quantitative patterns across the NCI-60 clarified data organization and cross comparisons using a novel pattern-match tool. Data queries for potential relationships among parameters can be conducted in an iterative manner specific to user interests and expertise. Examples of the in silico discovery process afforded by CellMiner were provided for multidrug resistance analyses and doxorubicin activity; identification of colon-specific genes, microRNAs and drugs; microRNAs related to the miR-17-92 cluster; and drug identification patterns matched to erlotinib, gefitinib, afatinib, and lapatinib. CellMiner greatly broadens applications of the extensive NCI-60 database for discovery by creating web-based processes that are rapid, flexible, and readily applied by users without bioinformatics expertise.