Menden, M. P. and Wang, D. and Mason, M. J. and Szalai, Bence and Bulusu, K. C. and Turu, Gábor (2019) Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. NATURE COMMUNICATIONS, 10 (1). ISSN 2041-1723
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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. © 2019, The Author(s).
| Item Type: | Article |
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| Uncontrolled Keywords: | Humans; MUTATION; MUTATION; GENETICS; BIOLOGY; GENOMICS; GENOMICS; human; Treatment Outcome; Treatment Outcome; information processing; drug potentiation; drug effect; Drug Synergism; Cell Line, Tumor; Drug Resistance; Drug Antagonism; Drug Antagonism; antineoplastic agent; Neoplasms; neoplasm; phosphatidylinositol 3 kinase; Antineoplastic Combined Chemotherapy Protocols; Pharmacogenetics; Pharmacogenetics; tumor marker; Drug Resistance, Neoplasm; Computational Biology; Standards; tumor cell line; Molecular Targeted Therapy; molecularly targeted therapy; Benchmarking; Benchmarking; tumor necrosis factor alpha converting enzyme; antagonists and inhibitors; procedures; Biomarkers, Tumor; Datasets as Topic; Phosphatidylinositol 3-Kinases; ADAM17 protein, human; ADAM17 Protein; |
| Subjects: | R Medicine / orvostudomány > RC Internal medicine / belgyógyászat > RC0254 Neoplasms. Tumors. Oncology (including Cancer) / daganatok, tumorok, onkológia R Medicine / orvostudomány > RM Therapeutics. Pharmacology / terápia, gyógyszertan |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 27 Nov 2019 07:18 |
| Last Modified: | 27 Nov 2019 07:18 |
| URI: | http://real.mtak.hu/id/eprint/103845 |
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