In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities

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• dc.contributor.author Rubio Pérez, Carlota, 1990-ca
• dc.contributor.author Tamborero Noguera, Davidca
• dc.contributor.author Schroeder, Michael Philipp, 1986-ca
• dc.contributor.author Antolín Hernández, Albert, 1984-ca
• dc.contributor.author Déu Pons, Jordica
• dc.contributor.author Pérez Llamas, Christian, 1976-ca
• dc.contributor.author Mestres i López, Jordica
• dc.contributor.author González-Pérez, Abelca
• dc.contributor.author López Bigas, Núriaca
• dc.date.accessioned 2017-10-25T10:54:16Z
• dc.date.available 2017-10-25T10:54:16Z
• dc.date.issued 2015
• dc.description.abstract Large efforts dedicated to detect somatic alterations across tumor genomes/exomes are expected to produce significant improvements in precision cancer medicine. However, high inter-tumor heterogeneity is a major obstacle to developing and applying therapeutic targeted agents to treat most cancer patients. Here, we offer a comprehensive assessment of the scope of targeted therapeutic agents in a large pan-cancer cohort. We developed an in silico prescription strategy based on identification of the driver alterations in each tumor and their druggability options. Although relatively few tumors are tractable by approved agents following clinical guidelines (5.9%), up to 40.2% could benefit from different repurposing options, and up to 73.3% considering treatments currently under clinical investigation. We also identified 80 therapeutically targetable cancer genes.
• dc.description.sponsorship We acknowledge funding from the Spanish Ministry of Economy and Competitiveness (grant number SAF2012-36199), La Fundació la Marató de TV3, and the Spanish National Institute of Bioinformatics (INB). C.R.-P. and M.P.S. are supported by an FPI fellowship. D.T. is supported by the People Programme (Marie Curie Actions) of the Seventh Framework Programme of the European Union (FP7/2007-2013) under REA grant agreement number 600388 and by the Agency of Competitiveness for Companies of the Government of Catalonia, ACCIÓ. A.G.-P. is supported by a Ramón y Cajal contract.
• dc.format.mimetype application/pdfca
• dc.identifier.citation Rubio-Perez C, Tamborero D, Schroeder MP, Antolín AA, Deu-Pons J, Perez-Llamas C et al. In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities. Cancer Cell. 2015 Mar 9;27(3):382-96. DOI: 10.1016/j.ccell.2015.02.007
• dc.identifier.doi http://dx.doi.org/10.1016/j.ccell.2015.02.007
• dc.identifier.issn 1535-6108
• dc.identifier.uri http://hdl.handle.net/10230/33093
• dc.language.iso eng
• dc.publisher Elsevierca
• dc.relation.ispartof Cancer Cell. 2015 Mar 9;27(3):382-96
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/600388
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/SAF2012-36199
• dc.rights © Elsevier This is the published version of an article http://dx.doi.org/10.1016/j.ccell.2015.02.007 that appeared in the journal Cancer Cell. It is published in an Open Archive under an Elsevier user license. Details of this licence are available here: https://www.elsevier.com/about/our-business/policies/open-access-licenses/elsevier-user-license
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://www.elsevier.com/about/our-business/policies/open-access-licenses/elsevier-user-license
• dc.subject.keyword Antineoplastic Agents
• dc.subject.keyword Carcinogenesis/genetics
• dc.subject.keyword Clinical Protocols
• dc.subject.keyword Clinical Trials as Topic
• dc.subject.keyword Cohort Studies
• dc.subject.keyword Computational Biology
• dc.subject.keyword DNA Mutational Analysis
• dc.subject.keyword Drug Repositioning
• dc.subject.keyword Decision Making, Computer-Assisted
• dc.subject.keyword Neoplasms/drug therapy
• dc.subject.keyword Neoplasms/genetics
• dc.subject.keyword Precision Medicine/methods
• dc.title In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunitiesca
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion