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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.
Nat. Commun. 10:2674 (2019)
The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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11.878
2.805
80
141
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Androgen Receptor; Breast-cancer; Gene; Cell; Inhibition; Resistance; Pathway; Mutations; Landscape; Resource
Language
english
Publication Year
2019
HGF-reported in Year
2019
ISSN (print) / ISBN
2041-1723
e-ISSN
2041-1723
Journal
Nature Communications
Quellenangaben
Volume: 10,
Issue: 1,
Article Number: 2674
Publisher
Nature Publishing Group
Publishing Place
London
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-554700-001
WOS ID
WOS:000471758500010
Scopus ID
85067453487
PubMed ID
31209238
Erfassungsdatum
2019-06-26