Kohn, Kurt W.

Abstract High-throughput data is increasingly being integrated into the fields of biology, molecular biology, and pharmacology. However, a difficult problem has been the rapid and fluid access to and integration of the data, which tends to reside in huge unwieldy databases. One set of cell lines with substantial potential for benefit from this type of access and integration is the NCI-60 cancerous cell lines. We present here a set of tools within our CellMiner web-application designed to address this need for the areas of transcript expression, microRNA expression, gene DNA copy number, variant status, and drug activity. CellMiner allows the user to rapidly access data for relative levels of transcript expression for 26,065 genes, 360 microRNAs, and 20,602 compounds including 102 Food and Drug Administration (FDA)-approved drugs. These levels in turn create patterns across the NCI-60 that can be compared to one another using our “pattern match” tool. Together, these tools allow one to query the data for potential relationships between these parameters, in a manner specific to a users area of expertise and interest, in a rapid and flexible manner without the need for expertise in computer science or bioinformatics. Comparisons of transcript/drug will be demonstrated with SLFN11/topotecan; variant/drug with BRAF V600E/vemurafinib; colon tissue-of origin specific genes with TRIM15, RNF43, and VIL1; and DNA copy number change with CDKN2A (p16). The data are publicly available at http://discover.nci.nih.gov/cellminer. Citation Format: William C. Reinhold, Margot Sunshine, Sudir Varma, Hongfang Liu, Ogan Abaan, Paul Meltzer, Joel Morris, Kurt Kohn, James Doroshow, Yves Pommier. Web-based access using CellMiner for gene expression, DNA copy number, microRNA transcript levels, variant status, drug activity, and their pattern comparisons for the NCI-60. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3177. doi:10.1158/1538-7445.AM2013-3177

Abstract 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 U.S. National Cancer Institute, which has been extensively characterized across numerous genomic and pharmacologic response platforms. In this report, we introduce a CellMiner (http://discover.nci.nih.gov/cellminer/) web application designed to improve the use of this extensive database. CellMiner tools allowed rapid data retrieval of transcripts for 22,379 genes and 360 microRNAs along with activity reports for 20,503 chemical compounds including 102 drugs approved by the U.S. 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. Cancer Res; 72(14); 3499–511. ©2012 AACR.