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MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells
Targeted anticancer therapies represent the most effective pharmacological strategies in terms of clinical responses. In this context, genetic alteration of several oncogenes represents an optimal predictor of response to targeted therapy. Integration of large-scale molecular and pharmacological dat...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4770742/ https://www.ncbi.nlm.nih.gov/pubmed/26513174 |
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author | Taccioli, Cristian Sorrentino, Giovanni Zannini, Alessandro Caroli, Jimmy Beneventano, Domenico Anderlucci, Laura Lolli, Marco Bicciato, Silvio Del Sal, Giannino |
author_facet | Taccioli, Cristian Sorrentino, Giovanni Zannini, Alessandro Caroli, Jimmy Beneventano, Domenico Anderlucci, Laura Lolli, Marco Bicciato, Silvio Del Sal, Giannino |
author_sort | Taccioli, Cristian |
collection | PubMed |
description | Targeted anticancer therapies represent the most effective pharmacological strategies in terms of clinical responses. In this context, genetic alteration of several oncogenes represents an optimal predictor of response to targeted therapy. Integration of large-scale molecular and pharmacological data from cancer cell lines promises to be effective in the discovery of new genetic markers of drug sensitivity and of clinically relevant anticancer compounds. To define novel pharmacogenomic dependencies in cancer, we created the Mutations and Drugs Portal (MDP, http://mdp.unimore.it), a web accessible database that combines the cell-based NCI60 screening of more than 50,000 compounds with genomic data extracted from the Cancer Cell Line Encyclopedia and the NCI60 DTP projects. MDP can be queried for drugs active in cancer cell lines carrying mutations in specific cancer genes or for genetic markers associated to sensitivity or resistance to a given compound. As proof of performance, we interrogated MDP to identify both known and novel pharmacogenomics associations and unveiled an unpredicted combination of two FDA-approved compounds, namely statins and Dasatinib, as an effective strategy to potently inhibit YAP/TAZ in cancer cells. |
format | Online Article Text |
id | pubmed-4770742 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-47707422016-03-21 MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells Taccioli, Cristian Sorrentino, Giovanni Zannini, Alessandro Caroli, Jimmy Beneventano, Domenico Anderlucci, Laura Lolli, Marco Bicciato, Silvio Del Sal, Giannino Oncotarget Research Paper Targeted anticancer therapies represent the most effective pharmacological strategies in terms of clinical responses. In this context, genetic alteration of several oncogenes represents an optimal predictor of response to targeted therapy. Integration of large-scale molecular and pharmacological data from cancer cell lines promises to be effective in the discovery of new genetic markers of drug sensitivity and of clinically relevant anticancer compounds. To define novel pharmacogenomic dependencies in cancer, we created the Mutations and Drugs Portal (MDP, http://mdp.unimore.it), a web accessible database that combines the cell-based NCI60 screening of more than 50,000 compounds with genomic data extracted from the Cancer Cell Line Encyclopedia and the NCI60 DTP projects. MDP can be queried for drugs active in cancer cell lines carrying mutations in specific cancer genes or for genetic markers associated to sensitivity or resistance to a given compound. As proof of performance, we interrogated MDP to identify both known and novel pharmacogenomics associations and unveiled an unpredicted combination of two FDA-approved compounds, namely statins and Dasatinib, as an effective strategy to potently inhibit YAP/TAZ in cancer cells. Impact Journals LLC 2015-10-15 /pmc/articles/PMC4770742/ /pubmed/26513174 Text en Copyright: © 2015 Taccioli et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Taccioli, Cristian Sorrentino, Giovanni Zannini, Alessandro Caroli, Jimmy Beneventano, Domenico Anderlucci, Laura Lolli, Marco Bicciato, Silvio Del Sal, Giannino MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells |
title | MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells |
title_full | MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells |
title_fullStr | MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells |
title_full_unstemmed | MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells |
title_short | MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells |
title_sort | mdp, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit yap/taz in cancer cells |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4770742/ https://www.ncbi.nlm.nih.gov/pubmed/26513174 |
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