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- Menden, MP, et al.
(author)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Journal article (peer-reviewed)abstract
- 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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2. |
- Muller, S, et al.
(author)
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Target 2035 - update on the quest for a probe for every protein
- 2022
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In: RSC medicinal chemistry. - : Royal Society of Chemistry (RSC). - 2632-8682. ; 13:1, s. 13-21
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Journal article (other academic/artistic)abstract
- Twenty years after the publication of the first draft of the human genome, our knowledge of the human proteome is still fragmented. Target 2035 aims to develop a pharmacological modulator for every protein in the human proteome to fill this gap.
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