Format

Send to

Choose Destination
Nat Commun. 2019 Jun 17;10(1):2674. doi: 10.1038/s41467-019-09799-2.

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.

Collaborators (328)

Abante J, Abecassis BS, Aben N, Aghamirzaie D, Aittokallio T, Akhtari FS, Al-Lazikani B, Alam T, Allam A, Allen C, de Almeida MP, Altarawy D, Alves V, Amadoz A, Anchang B, Antolin AA, Ash JR, Aznar VR, Ba-Alawi W, Bagheri M, Bajic V, Ball G, Ballester PJ, Baptista D, Bare C, Bateson M, Bender A, Bertrand D, Wijayawardena B, Boroevich KA, Bosdriesz E, Bougouffa S, Bounova G, Brouwer T, Bryant B, Calaza M, Calderone A, Calza S, Capuzzi S, Carbonell-Caballero J, Carlin D, Carter H, Castagnoli L, Celebi R, Cesareni G, Chang H, Chen G, Chen H, Chen H, Cheng L, Chernomoretz A, Chicco D, Cho KH, Cho S, Choi D, Choi J, Choi K, Choi M, Cock M, Coker E, Cortes-Ciriano I, Cserzö M, Cubuk C, Curtis C, Daele DV, Dang CC, Dijkstra T, Dopazo J, Draghici S, Drosou A, Dumontier M, Ehrhart F, Eid FE, ElHefnawi M, Elmarakeby H, van Engelen B, Engin HB, de Esch I, Evelo C, Falcao AO, Farag S, Fernandez-Lozano C, Fisch K, Flobak A, Fornari C, Foroushani ABK, Fotso DC, Fourches D, Friend S, Frigessi A, Gao F, Gao X, Gerold JM, Gestraud P, Ghosh S, Gillberg J, Godoy-Lorite A, Godynyuk L, Godzik A, Goldenberg A, Gomez-Cabrero D, Gonen M, de Graaf C, Gray H, Grechkin M, Guimera R, Guney E, Haibe-Kains B, Han Y, Hase T, He D, He L, Heath LS, Hellton KH, Helmer-Citterich M, Hidalgo MR, Hidru D, Hill SM, Hochreiter S, Hong S, Hovig E, Hsueh YC, Hu Z, Huang JK, Huang RS, Hunyady L, Hwang J, Hwang TH, Hwang W, Hwang Y, Isayev O, Don't Walk OB 4th, Jack J, Jahandideh S, Ji J, Jo Y, Kamola PJ, Kanev GK, Karacosta L, Karimi M, Kaski S, Kazanov M, Khamis AM, Khan SA, Kiani NA, Kim A, Kim J, Kim J, Kim K, Kim K, Kim S, Kim Y, Kim Y, Kirk PDW, Kitano H, Klambauer G, Knowles D, Ko M, Kohn-Luque A, Kooistra AJ, Kuenemann MA, Kuiper M, Kurz C, Kwon M, van Laarhoven T, Laegreid A, Lederer S, Lee H, Lee J, Lee YW, Lepp Aho E, Lewis R, Li J, Li L, Liley J, Lim WK, Lin C, Liu Y, Lopez Y, Low J, Lysenko A, Machado D, Madhukar N, Maeyer D, Malpartida AB, Mamitsuka H, Marabita F, Marchal K, Marttinen P, Mason D, Mazaheri A, Mehmood A, Mehreen A, Michaut M, Miller RA, Mitsopoulos C, Modos D, Moerbeke MV, Moo K, Motsinger-Reif A, Movva R, Muraru S, Muratov E, Mushthofa M, Nagarajan N, Nakken S, Nath A, Neuvial P, Newton R, Ning Z, Niz C, Oliva B, Olsen C, Palmeri A, Panesar B, Papadopoulos S, Park J, Park S, Park S, Pawitan Y, Peluso D, Pendyala S, Peng J, Perfetto L, Pirro S, Plevritis S, Politi R, Poon H, Porta E, Prellner I, Preuer K, Pujana MA, Ramnarine R, Reid JE, Reyal F, Richardson S, Ricketts C, Rieswijk L, Rocha M, Rodriguez-Gonzalvez C, Roell K, Rotroff D, de Ruiter JR, Rukawa P, Sadacca B, Safikhani Z, Safitri F, Sales-Pardo M, Sauer S, Schlichting M, Seoane JA, Serra J, Shang MM, Sharma A, Sharma H, Shen Y, Shiga M, Shin M, Shkedy Z, Shopsowitz K, Sinai S, Skola D, Smirnov P, Soerensen IF, Soerensen P, Song JH, Song SO, Soufan O, Spitzmueller A, Steipe B, Suphavilai C, Tamayo SP, Tamborero D, Tang J, Tanoli ZU, Tarres-Deulofeu M, Tegner J, Thommesen L, Tonekaboni SAM, Tran H, Troyer E, Truong A, Tsunoda T, Turu G, Tzeng GY, Verbeke L, Videla S, Vis D, Voronkov A, Votis K, Wang A, Wang HH, Wang PW, Wang S, Wang W, Wang X, Wang X, Wennerberg K, Wernisch L, Wessels L, van Westen GJP, Westerman BA, White SR, Willighagen E, Wurdinger T, Xie L, Xie S, Xu H, Yadav B, Yau C, Yeerna H, Yin JW, Yu M, Yu M, Yun SJ, Zakharov A, Zamichos A, Zanin M, Zeng L, Zenil H, Zhang F, Zhang P, Zhang W, Zhao H, Zhao L, Zheng W, Zoufir A, Zucknick M.

Author information

1
Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, SG8 6EH, UK.
2
European Bioinformatics Institute, European Molecular Biology Laboratory, Cambridge, CB10 1SD, UK.
3
Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Munich, D-85764, Germany.
4
Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2TN, UK.
5
Sage Bionetworks, Seattle, WA, 98121, USA.
6
Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, 1085, Hungary.
7
Laboratory of Molecular Physiology, Hungarian Academy of Sciences and Semmelweis University (MTA-SE), Budapest, 1085, Hungary.
8
RWTH Aachen University, Faculty of Medicine, Joint Research Center for Computational Biomedicine, Aachen, 52062, Germany.
9
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, 48109, USA.
10
Department of Computer Science and Engineering, Korea University, Seoul, 02841, Korea.
11
SAS Institute, Inc, Cary, NC, 27513, USA.
12
Department of Computer Science and Engineering, University of Nevada, Reno, 89557, USA.
13
Independent Consultant in Computational Biology, Owkin, Inc., New York, NY, 10022, USA.
14
IBM Thomas J. Watson Research Center, Yorktown Heights, New York, 10598, USA.
15
Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK.
16
Early Clinical Development, IMED Biotech Unit, AstraZeneca, Cambridge, SG8 6EH, UK.
17
Oncology, IMED Biotech Unit, AstraZeneca, R&D Boston, Waltham, MA, 02451, USA.
18
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, 10029, USA.
19
Sage Bionetworks, Seattle, WA, 98121, USA. justin.guinney@sagebionetworks.org.
20
Oncology, IMED Biotech Unit, AstraZeneca, R&D Boston, Waltham, MA, 02451, USA. jonathan.dry@astrazeneca.com.
21
European Bioinformatics Institute, European Molecular Biology Laboratory, Cambridge, CB10 1SD, UK. julio.saez@bioquant.uni-heidelberg.de.
22
RWTH Aachen University, Faculty of Medicine, Joint Research Center for Computational Biomedicine, Aachen, 52062, Germany. julio.saez@bioquant.uni-heidelberg.de.
23
Heidelberg University, Faculty of Medicine, Institute for Computational Biomedicine, Bioquant, 69120, Heidelberg, Germany. julio.saez@bioquant.uni-heidelberg.de.

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.

PMID:
31209238
PMCID:
PMC6572829
DOI:
10.1038/s41467-019-09799-2
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center