Cited by 296Cancer Genomics and DiagnosticsLung Cancer Treatments and MutationsComputational Drug Discovery Methods

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

Open access
Rubio-Perez, Carlota, Tamborero, David, Schroeder, Michael P., Antolín, Albert A., Deu-Pons, Jordi, Perez-Llamas, Christian, Mestres, Jordi, Gonzalez-Perez, Abel +1 more·2015·Cancer Cell

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.

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Crossref · 10.1016/j.ccell.2015.02.007

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Authors
Rubio-Perez, C., Tamborero, D., Schroeder, M. P., Antolín, A. A., Deu-Pons, J., Perez-Llamas, C., Mestres, J., Gonzalez-Perez, A., & Lopez-Bigas, N.
Affiliations
Universitat Pompeu Fabra (ES)
Venue
Cancer Cell
Publisher
Elsevier BV
Published
2015-03
Volume
27
Issue
3
Pages
382-396
ISSN
1535-6108 (ISSN-L)
OpenAlex
W2082426444
Cited by
296
References
41
Citations by year
2026: 5 · 2025: 9 · 2024: 9 · 2023: 12 · 2022: 16 · 2021: 18 · 2020: 26 · 2019: 44 · 2018: 44 · 2017: 43 · 2016: 48 · 2015: 20 · 2014: 1 · 2012: 1
FWCI
17.07
Type
journal article
Language
en
Open access
Locations
  • Cancer Cell (publishedVersion)
  • PubMed (publishedVersion)
  • RECERCAT (Consorci de Serveis Universitaris de Catalunya) (publishedVersion, other-oa)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, other-oa)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Keywords
targeted therapy, pan-cancer cohort, driver alterations, druggability, drug repurposing, precision oncology, intertumoral heterogeneity, clinical trial drugs
MeSH terms
Antineoplastic Agents, Clinical Protocols, Clinical Trials as Topic, Decision Making, Computer-Assisted, DNA Mutational Analysis, Humans, Neoplasms, Cohort Studies, Computational Biology, Precision Medicine, Drug Repositioning, Carcinogenesis

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