Cited by 155Computational Drug Discovery MethodsCancer Genomics and DiagnosticsBiomedical Text Mining and Ontologies

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PharmacoDB: an integrative database for mining in vitro anticancer drug screening studies

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Smirnov, Petr, Kofia, Victor, Maru, Alexander, Freeman, Mark, Ho, Chantal, El-Hachem, Nehme, Adam, George-Alexandru, Ba-alawi, Wail, Safikhani, Zhaleh, Haibe-Kains, Benjamin·2018·Nucleic Acids Research

DOI 10.1093/nar/gkx911PMC PMC5753377

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Abstract

Recent cancer pharmacogenomic studies profiled large panels of cell lines against hundreds of approved drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbations, correlate these measures to genomic features, and thereby develop novel predictors of drug response. However, leveraging these valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale drug screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest cancer pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated cancer pharmacogenomic datasets that are otherwise disparate and difficult to integrate.

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Authors: Smirnov, P., Kofia, V., Maru, A., Freeman, M., Ho, C., El-Hachem, N., Adam, G.-A., Ba-alawi, W., Safikhani, Z., & Haibe-Kains, B.
Affiliations: University Health Network (CA)
ORCID: Smirnov, Petr
Kofia, Victor
Ba-alawi, Wail
Safikhani, Zhaleh
Venue: Nucleic Acids Research
Publisher: Oxford University Press (OUP)
Published: 2017-10-09
Volume: 46
Issue: D1
Pages: D994-D1002
ISSN: 0305-1048 (ISSN-L)
1362-4962
DOI: 10.1093/nar/gkx911
PMC: PMC5753377
OpenAlex: W2759360483
Cited by: 155
References: 39
Citations by year: 2026: 7 · 2025: 17 · 2024: 16 · 2023: 15 · 2022: 15 · 2021: 35 · 2020: 23 · 2019: 17 · 2018: 10
FWCI: 10.25
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by-nc
creativecommons.org/licenses/by-nc/4.0/ (vor)
Locations: Nucleic Acids Research (publishedVersion, cc-by-nc)
PubMed Central (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
Funders: Cancer Research Society
Princess Margaret Cancer Foundation
Ontario Institute for Cancer Research
Genentech
Stand Up To Cancer
Canadian Institutes of Health Research
Canadian Cancer Society Research Institute
Topics: Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
Keywords: cancer pharmacogenomics, anticancer drug screening, drug sensitivity, database curation, drug response prediction, data integration, in vitro drug sensitivity
MeSH terms: Pharmacogenomic Testing, Antineoplastic Agents, Dose-Response Relationship, Drug, Drug Screening Assays, Antitumor, Humans, User-Computer Interface, Cell Line, Tumor, Data Mining, Databases, Pharmaceutical

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PharmacoDB: an integrative database for mining in vitro anticancer drug screening studies

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