Database
CellMiner: a relational database and query tool for the NCI-60 cancer cell lines
-
* Corresponding author: Uma T Shankavaram Uma.Shankavaram@nih.hhs.gov
1 Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Centre for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
2 SRA International, Fairfax, VA, USA
3 Office of Information Technology, Center for Drug Evaluation and Research, Food and Drug Administration, Rockville, MD, USA
4 Department of Bioinformatics and Computational Biology, M. D. Anderson Cancer Center, Houston, TX, USA
5 Current address: Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
BMC Genomics 2009, 10:277 doi:10.1186/1471-2164-10-277
Published: 23 June 2009Abstract
Background
Advances in the high-throughput omic technologies have made it possible to profile cells in a large number of ways at the DNA, RNA, protein, chromosomal, functional, and pharmacological levels. A persistent problem is that some classes of molecular data are labeled with gene identifiers, others with transcript or protein identifiers, and still others with chromosomal locations. What has lagged behind is the ability to integrate the resulting data to uncover complex relationships and patterns. Those issues are reflected in full form by molecular profile data on the panel of 60 diverse human cancer cell lines (the NCI-60) used since 1990 by the U.S. National Cancer Institute to screen compounds for anticancer activity. To our knowledge, CellMiner is the first online database resource for integration of the diverse molecular types of NCI-60 and related meta data.
Description
CellMiner enables scientists to perform advanced querying of molecular information on NCI-60 (and additional types) through a single web interface. CellMiner is a freely available tool that organizes and stores raw and normalized data that represent multiple types of molecular characterizations at the DNA, RNA, protein, and pharmacological levels. Annotations for each project, along with associated metadata on the samples and datasets, are stored in a MySQL database and linked to the molecular profile data. Data can be queried and downloaded along with comprehensive information on experimental and analytic methods for each data set. A Data Intersection tool allows selection of a list of genes (proteins) in common between two or more data sets and outputs the data for those genes (proteins) in the respective sets. In addition to its role as an integrative resource for the NCI-60, the CellMiner package also serves as a shell for incorporation of molecular profile data on other cell or tissue sample types.
Conclusion
CellMiner is a relational database tool for storing, querying, integrating, and downloading molecular profile data on the NCI-60 and other cancer cell types. More broadly, it provides a template to use in providing such functionality for other molecular profile data generated by academic institutions, public projects, or the private sector. CellMiner is available online at http://discover.nci.nih.gov/cellminer/ webcite.