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Nucleic Acids Res. 2016 Jan 4;44(D1):D932-7. doi: 10.1093/nar/gkv1283. Epub 2015 Nov 20.

CancerResource--updated database of cancer-relevant proteins, mutations and interacting drugs.

Author information

1
Charité - University Medicine Berlin, Structural Bioinformatics Group, Institute of Physiology & Experimental Clinical Research Center, Berlin 13125, Germany German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
2
Charité - University Medicine Berlin, Structural Bioinformatics Group, Institute of Physiology & Experimental Clinical Research Center, Berlin 13125, Germany.
3
Charité - University Medicine Berlin, Structural Bioinformatics Group, Institute of Physiology & Experimental Clinical Research Center, Berlin 13125, Germany German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg 69120, Germany robert.preissner@charite.de.

Abstract

Here, we present an updated version of CancerResource, freely available without registration at http://bioinformatics.charite.de/care. With upcoming information on target expression and mutations in patients' tumors, the need for systems supporting decisions on individual therapy is growing. This knowledge is based on numerous, experimentally validated drug-target interactions and supporting analyses such as measuring changes in gene expression using microarrays and HTS-efforts on cell lines. To enable a better overview about similar drug-target data and supporting information, a series of novel information connections are established and made available as described in the following. CancerResource contains about 91,000 drug-target relations, more than 2000 cancer cell lines and drug sensitivity data for about 50,000 drugs. CancerResource enables the capability of uploading external expression and mutation data and comparing them to the database's cell lines. Target genes and compounds are projected onto cancer-related pathways to get a better overview about how drug-target interactions benefit the treatment of cancer. Features like cellular fingerprints comprising of mutations, expression values and drug-sensitivity data can promote the understanding of genotype to drug sensitivity associations. Ultimately, these profiles can also be used to determine the most effective drug treatment for a cancer cell line most similar to a patient's tumor cells.

PMID:
26590406
PMCID:
PMC4702908
DOI:
10.1093/nar/gkv1283
[Indexed for MEDLINE]
Free PMC Article

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