NCI Genomics and Pharmacology Facility

Established Technologies

• The Miner Suite of Bioinformatic Applications
• These applications are freely available for public use. Our characterization and analysis of the NCI-60 cancer cell lines, the DNA, RNA, protein, epigenetic and pharmacological levels is accessible through CellMiner, with the expended version including additional cell line sets available through CellMinerCDB.
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• CellMinerCDB
• url:  https://discover.nci.nih.gov/rsconnect/cellminercdb/
• CellMiner Cross Database (CDB) is the first web application to allow translational researchers to conduct analyses across all major cancer cell line pharmacogenomic data sources from NCI-DTP NCI-60, Sanger GDSC, and Broad CCLE/CTRP. It provides matched molecular and drug activity profiling data. This data may be used to 1) assess molecular and drug data reproducibility, 2) determine repositioning opportunities for FDA-approved compounds, 3) identify potential drug response and gene regulatory determinants, and 4) identify and validate novel genes associated with phenotypic processes. This data is an important precision medicine resource.  
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• CellMinerCDB: Small Cell Lung Cancer (SCLC)
• url:  https://discover.nci.nih.gov/rsconnect/SclcCellMinerCDB/
• CellMinerCDB: Small Cell Lung Cancer is configured like CellMinerCDB with additional features and focuses on SCLC cell lines from various data sources.  
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• CellMinerCDB: Sarcoma
• url:  https://discover.nci.nih.gov/rsconnect/SarcomaCellMinerCDB/
• CellMinerCDB: Sarcoma is a specialized platform derived from CellMinerCDB, tailored for sarcoma research. It offers comprehensive data on 133 sarcoma cell lines, integrating various omics data sources. The platform ensures reproducibility and biological relevance, empowering researchers with tools to explore and test hypotheses in translational research. Its aim is to advance preclinical studies in sarcoma for improved understanding and treatment development.  
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• CellMinerCDB: Adenoid Cortical Carcinoma (ACC)
• url:  https://discover.nci.nih.gov/rsconnect/acc_cellminercdb/
• CellMinerCDB: Adrenal Cortical Carcinoma (ACC) is a substantive genomic and drug sensitivity database comprising ACC cell lines, patient-derived xenografts, surgical samples, and responses to more than 2,400 drugs examined by the NCI and National Center for Advancing Translational Sciences. This database exposes shared genomic pathways among ACC cell lines and surgical samples, thus authenticating the cell lines as research models. It also allows exploration of pertinent treatment markers such as MDR-1, SOAT1, MGMT, MMR, and SLFN11 and introduces the potential to repurpose agents like temozolomide for ACC therapy. CellMinerCDB:ACC provides the foundation for exploring larger preclinical ACC models.  
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• CellMinerCDB: National Center for Advancing Translational Sciences (NCATS)
• url:  https://discover.nci.nih.gov/rsconnect/cellminercdb_ncats/
• A powerful tool for precision medicine: CellMinerCDB: NCATS exposes relationships between cancer cells' molecular makeup and their response to potential therapies, using data on thousands of compounds screened at the National Center for Advancing Translational Sciences.
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• CellMiner (NCI-60)
• url:  https://discover.nci.nih.gov/cellminer/
• A database and query tool designed for the cancer research community to facilitate integration of the molecular datasets generated by the Genomics and Pharmacology Facility and its collaborators on the NCI-60.  
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• CIMMiner
• url:  https://discover.nci.nih.gov/cimminer/
• Generates color-coded Clustered Image Maps (CIMs) ("heat maps") to represent high-dimensional data sets such as gene expression profiles. We introduced CIMs in the mid-1990’s for data on drug activity, target expression, gene expression, and proteomic profiles. Clustering of the axes brings like together with like to create patterns of color.  
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• MIMminer
• url:  https://discover.nci.nih.gov/mim/
• A Molecular Interaction Map (MIM) is a diagram convention that is capable of unambiguous representation of networks containing multi-protein complexes, protein modifications, and enzymes that are substrates of other enzymes. This graphical representation makes it possible to view all of the many interactions in which a given molecule may be involved, and it can portray competing interactions, which are common in bioregulatory networks. In order to facilitate linkage to databases, each molecular species is represented only once in a diagram. A formal description of the.

Developing Technologies

We are currently developing clinical data versions of the data integration web-applications described above for the cell lines to enhance systems pharmacology analysis.