Using CellMiner 1.6 for Systems Pharmacology and Genomic Analysis of the NCI-60.
Using CellMiner 1.6 for Systems Pharmacology and Genomic Analysis of the NCI-60.
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DOI：
10.1158/1078-0432.ccr-15-0335
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发表时间：
2015-09-01
期刊：
影响因子：
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通讯作者：
Pommier Y
中科院分区：
文献类型：
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作者：
Reinhold WC;Sunshine M;Varma S;Doroshow JH;Pommier Y
NCI-60癌症细胞系面板提供了数据整合和系统药理学的首要模型，是最大的抗癌药物活性、基因组、分子和表型数据的公开数据库。它包括基因表达（25,722个转录本），microrna(360个mirna)，全基因组DNA拷贝数（23,413个基因），全外显子组测序（16,568个基因的变体），蛋白质水平（94个基因）和细胞毒性活性（20,861个化合物）。其中包括158种食品和药物管理局（FDA）批准的药物和79种处于临床试验阶段的药物。为了提高生物信息学家和非生物信息学家的数据可访问性，我们开发了基于网络的CellMiner工具。本文介绍了最新的CellMiner版本，包括与全外显子组测序和蛋白质表达相关的新数据库和工具的集成，并回顾了这些工具。包括i) DNA、RNA、蛋白质和药物的“细胞系签名”，ii)单个查询中多达150个输入基因、microRNA和化合物的“交叉相关性”，iii)“模式比较”以确定药物、基因表达、基因组变异、microRNA和蛋白质表达之间的联系，iv)“遗传变异与药物可视化”以确定潜在的新药：基因DNA变异关系，v)“遗传变异总和”。旨在为多达150个基因提供任何途径或基因组的突变负担概要。总之，这些工具允许用户灵活地查询NCI-60数据，以特定于用户专业领域的方式查询基因组、分子和药理学参数之间的潜在关系。提供了增益（RAS）和损失（PTEN）函数变化的示例。
The NCI-60 cancer cell line panel provides a premier model for data integration and systems pharmacology being the largest publicly available database of anticancer drug activity,, genomic, molecular, and phenotypic data. It comprises gene expression (25,722 transcripts), microRNAs (360 miRNAs), whole genome DNA copy number (23,413 genes), whole exome sequencing (variants for 16,568 genes), protein levels (94 genes), and cytotoxic activity (20,861 compounds). Included are 158 Food and Drug Administration (FDA)-approved drugs and 79 that are in clinical trials. To improve data accessibility to bioinformaticists and non-bioinformaticists alike, we have developed the CellMiner web-based tools. Here we describe the newest CellMiner version, including integration of novel databases and tools associated with whole exome sequencing and protein expression, and review the tools. Included are i) “Cell line signature” for DNA, RNA, protein and drugs, ii) “Cross correlations” for up to 150 input genes, microRNAs, and compounds in a single query, iii) “Pattern comparison” to identify connections among drugs, gene expression, genomic variants, microRNA and protein expressions, iv) “Genetic variation versus drug visualization” to identify potential new drug:gene DNA variant relationships, and v) “Genetic variant summation”, designed to provide a synopsis of mutational burden on any pathway or gene group for up to 150 genes. Together, these tools allow users to flexibly query the NCI-60 data for potential relationships between genomic, molecular and pharmacological parameters in a manner specific to the user’s area of expertise. Examples for both gain- (RAS) and loss- (PTEN) of-function alterations are provided.