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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...

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Autores principales: Taccioli, Cristian, Sorrentino, Giovanni, Zannini, Alessandro, Caroli, Jimmy, Beneventano, Domenico, Anderlucci, Laura, Lolli, Marco, Bicciato, Silvio, Del Sal, Giannino
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2015
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.
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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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