We continue to maintain our Discover web-based tools (http://discover.nci.nih.gov/) for the scientific public. For data of the NCI-60 cancerous cell lines, our primary tool is CellMiner (http://discover.nci.nih.gov/cellminer/). Our main source of data comes from experiments in the 60 human cancer cells (the NCI-60), used by the NCI Developmental Therapeutics Program to screen 100,000 chemical compounds for anticancer activity since 1990. Our CellMiner """"""""NCI-60 Analysis Tools"""""""" section is providing a significant resource for pharmacogenomic integration, research, and discovery. In addition, we host the scholarly molecular interaction maps of K. Kohn et al. The CellMiner data and tools are creating major opportunities for progress in rational drug discovery, application, and individualization of therapy for cancer patients. As molecular alterations of many types can contribute to the outcome of that therapy, the Genomic and Bioinformatics Group (GBG) manages and integrate molecular and pharmacological data in such a way that enhances understanding, and facilitates the generate testable hypotheses in the context of pharmacology. The GBG thus provides access to high throughput data in an integrative context, in addition to providing software resources that facilitate the understanding, mining and exploitation of these data. Using our expertise in molecular biology, molecular pharmacology, biostatistics, bioinformatics, and computer science, we have generated public databases, and software to query and mine those data. The drug database is continuously expanded by the DTP as new drugs enter clinical trials. Largely through studies at the GBG with its collaborators, the NCI-60 is by far the most comprehensively profiled panel of mammalian cells anywhere. Currently our Discover and CellMiner sites have 6,000 individual users from 73 countries per month. It has lead to two translational discoveries within the last year (see Accomplishments).
|Luna, Augustin; Rajapakse, Vinodh N; Sousa, Fabricio G et al. (2016) rcellminer: exploring molecular profiles and drug response of the NCI-60 cell lines in R. Bioinformatics 32:1272-4|
|Reinhold, William C; Varma, Sudhir; Rajapakse, Vinodh N et al. (2015) Using drug response data to identify molecular effectors, and molecular ""omic"" data to identify candidate drugs in cancer. Hum Genet 134:3-11|
|Reinhold, William C; Sunshine, Margot; Varma, Sudhir et al. (2015) Using CellMiner 1.6 for Systems Pharmacology and Genomic Analysis of the NCI-60. Clin Cancer Res 21:3841-52|
|Varma, Sudhir; Pommier, Yves; Sunshine, Margot et al. (2014) High resolution copy number variation data in the NCI-60 cancer cell lines from whole genome microarrays accessible through CellMiner. PLoS One 9:e92047|
|Reinhold, William C; Varma, Sudhir; Sousa, Fabricio et al. (2014) NCI-60 whole exome sequencing and pharmacological CellMiner analyses. PLoS One 9:e101670|
|Abaan, Ogan D; Polley, Eric C; Davis, Sean R et al. (2013) The exomes of the NCI-60 panel: a genomic resource for cancer biology and systems pharmacology. Cancer Res 73:4372-82|
|Reinhold, William C; Sunshine, Margot; Liu, Hongfang et al. (2012) CellMiner: a web-based suite of genomic and pharmacologic tools to explore transcript and drug patterns in the NCI-60 cell line set. Cancer Res 72:3499-511|