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A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction

View ORCID ProfileMichael P Menden, Dennis Wang, Yuanfang Guan, Mike J Mason, Bence Szalai, Krishna C Bulusu, Thomas Yu, Jaewoo Kang, Minji Jeon, Russ Wolfinger, Tin Nguyen, Mikhail Zaslavskiy, AstraZeneca-Sanger Drug Combination DREAM Consortium, Sock Jang, Zara Ghazoui, Mehmet Eren Ahsen, Robert Vogel, Elias Chaibub Neto, Thea Norman, Eric KY Tang, Mathew J Garnett, Giovanni Di Veroli, Stephen Fawell, Gustavo Stolovitzky, Justin Guinney, Jonathan R. Dry, View ORCID ProfileJulio Saez-Rodriguez
doi: https://doi.org/10.1101/200451
Michael P Menden
1Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UK
2European Bioinformatics Institute, European Molecular Biology Laboratory, Cambridge, UK
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Dennis Wang
1Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UK
3NIHR Sheffield Biomedical Research Centre, University of Sheffield, Sheffield, UK
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Yuanfang Guan
4Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USA
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Mike J Mason
5Sage Bionetworks, Seattle WA, USA AstraZeneca-Sanger Drug Combination DREAM Consorti
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Bence Szalai
6Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
7RWTH Aachen University, Faculty of Medicine, Joint Research Center for Computational Biomedicine, Aachen, Germany
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Krishna C Bulusu
1Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UK
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Thomas Yu
5Sage Bionetworks, Seattle WA, USA AstraZeneca-Sanger Drug Combination DREAM Consorti
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Jaewoo Kang
8Department of Computer Science and Engineering, Korea University, Seoul, Korea
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Minji Jeon
8Department of Computer Science and Engineering, Korea University, Seoul, Korea
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Russ Wolfinger
9SAS Institute, Inc., Cary, NC, USA
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Tin Nguyen
10Department of Computer Science and Engineering, University of Nevada, Reno, USA
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Mikhail Zaslavskiy
11Independent consultant in computational biology, Paris, France
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Sock Jang
5Sage Bionetworks, Seattle WA, USA AstraZeneca-Sanger Drug Combination DREAM Consorti
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Zara Ghazoui
1Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UK
16Current address: Qiagen Manchester, UK
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Mehmet Eren Ahsen
12IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA
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Robert Vogel
12IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA
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Elias Chaibub Neto
5Sage Bionetworks, Seattle WA, USA AstraZeneca-Sanger Drug Combination DREAM Consorti
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Thea Norman
5Sage Bionetworks, Seattle WA, USA AstraZeneca-Sanger Drug Combination DREAM Consorti
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Eric KY Tang
1Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UK
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Mathew J Garnett
13Wellcome Trust Sanger Institute, Hinxton, UK
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Giovanni Di Veroli
1Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UK
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Stephen Fawell
14Oncology, IMED Biotech Unit, AstraZeneca R&D Boston, Waltham MA, USA
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Gustavo Stolovitzky
12IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA
15Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
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Justin Guinney
5Sage Bionetworks, Seattle WA, USA AstraZeneca-Sanger Drug Combination DREAM Consorti
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Jonathan R. Dry
14Oncology, IMED Biotech Unit, AstraZeneca R&D Boston, Waltham MA, USA
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Julio Saez-Rodriguez
2European Bioinformatics Institute, European Molecular Biology Laboratory, Cambridge, UK
7RWTH Aachen University, Faculty of Medicine, Joint Research Center for Computational Biomedicine, Aachen, Germany
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  • ORCID record for Julio Saez-Rodriguez
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Abstract

The effectiveness of most cancer targeted therapies is short lived since tumors evolve and develop resistance. Combinations of drugs offer the potential to overcome resistance, however the number of possible combinations is vast necessitating data-driven approaches to find optimal treatments tailored to a patient’s tumor. AstraZeneca carried out 11,576 experiments on 910 drug combinations across 85 cancer cell lines, recapitulating in vivo response profiles. These data, the largest openly available screen, were hosted by DREAM alongside deep molecular characterization from the Sanger Institute for a Challenge to computationally predict synergistic drug pairs and associated biomarkers. 160 teams participated to provide the most comprehensive methodological development and subsequent benchmarking to date. Winning methods incorporated prior knowledge of putative drug target interactions. For >60% of drug combinations synergy was reproducibly predicted with an accuracy matching biological replicate experiments, however 20% of drug combinations were poorly predicted by all methods. Genomic rationale for synergy predictions were identified, including antagonism unique to combined PIK3CB/D inhibition with the ADAM17 inhibitor where synergy is seen with other PI3K pathway inhibitors. All data, methods and code are freely available as a resource to the community.

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Posted February 13, 2018.
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A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction
Michael P Menden, Dennis Wang, Yuanfang Guan, Mike J Mason, Bence Szalai, Krishna C Bulusu, Thomas Yu, Jaewoo Kang, Minji Jeon, Russ Wolfinger, Tin Nguyen, Mikhail Zaslavskiy, AstraZeneca-Sanger Drug Combination DREAM Consortium, Sock Jang, Zara Ghazoui, Mehmet Eren Ahsen, Robert Vogel, Elias Chaibub Neto, Thea Norman, Eric KY Tang, Mathew J Garnett, Giovanni Di Veroli, Stephen Fawell, Gustavo Stolovitzky, Justin Guinney, Jonathan R. Dry, Julio Saez-Rodriguez
bioRxiv 200451; doi: https://doi.org/10.1101/200451
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A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction
Michael P Menden, Dennis Wang, Yuanfang Guan, Mike J Mason, Bence Szalai, Krishna C Bulusu, Thomas Yu, Jaewoo Kang, Minji Jeon, Russ Wolfinger, Tin Nguyen, Mikhail Zaslavskiy, AstraZeneca-Sanger Drug Combination DREAM Consortium, Sock Jang, Zara Ghazoui, Mehmet Eren Ahsen, Robert Vogel, Elias Chaibub Neto, Thea Norman, Eric KY Tang, Mathew J Garnett, Giovanni Di Veroli, Stephen Fawell, Gustavo Stolovitzky, Justin Guinney, Jonathan R. Dry, Julio Saez-Rodriguez
bioRxiv 200451; doi: https://doi.org/10.1101/200451

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