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

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 kn...

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Autores principales: Gohlke, Bjoern-Oliver, Nickel, Janette, Otto, Raik, Dunkel, Mathias, Preissner, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702908/
https://www.ncbi.nlm.nih.gov/pubmed/26590406
http://dx.doi.org/10.1093/nar/gkv1283
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author Gohlke, Bjoern-Oliver
Nickel, Janette
Otto, Raik
Dunkel, Mathias
Preissner, Robert
author_facet Gohlke, Bjoern-Oliver
Nickel, Janette
Otto, Raik
Dunkel, Mathias
Preissner, Robert
author_sort Gohlke, Bjoern-Oliver
collection PubMed
description 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.
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spelling pubmed-47029082016-01-07 CancerResource—updated database of cancer-relevant proteins, mutations and interacting drugs Gohlke, Bjoern-Oliver Nickel, Janette Otto, Raik Dunkel, Mathias Preissner, Robert Nucleic Acids Res Database Issue 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. Oxford University Press 2016-01-04 2015-11-20 /pmc/articles/PMC4702908/ /pubmed/26590406 http://dx.doi.org/10.1093/nar/gkv1283 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Gohlke, Bjoern-Oliver
Nickel, Janette
Otto, Raik
Dunkel, Mathias
Preissner, Robert
CancerResource—updated database of cancer-relevant proteins, mutations and interacting drugs
title CancerResource—updated database of cancer-relevant proteins, mutations and interacting drugs
title_full CancerResource—updated database of cancer-relevant proteins, mutations and interacting drugs
title_fullStr CancerResource—updated database of cancer-relevant proteins, mutations and interacting drugs
title_full_unstemmed CancerResource—updated database of cancer-relevant proteins, mutations and interacting drugs
title_short CancerResource—updated database of cancer-relevant proteins, mutations and interacting drugs
title_sort cancerresource—updated database of cancer-relevant proteins, mutations and interacting drugs
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702908/
https://www.ncbi.nlm.nih.gov/pubmed/26590406
http://dx.doi.org/10.1093/nar/gkv1283
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