Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
Makaleler > Tam Makale · 2019
Yazarlar: Michael P. Menden, Dennis Wang, Mike J. Mason, Bence Szalai, Krishna C. Bulusu, Yuanfang Guan, Thomas Yu, Jaewoo Kang, Minji Jeon, Russ Wolfinger, Tin Nguyen, Mikhail Zaslavskiy, Jordi Abante, Barbara Schmitz Abecassis, Nanne Aben, Delasa Aghamirzaie, Tero Aittokallio, Farida S. Akhtari, Bissan Al-lazikani, Tanvir Alam, Amin Allam, Chad Allen, Mariana Pelicano de Almeida, Doaa Altarawy, Vinicius Alves, Alicia Amadoz, Benedict Anchang, Albert A. Antolin, Jeremy R. Ash, Victoria Romeo Aznar, Wail Ba-alawi, Moeen Bagheri, Vladimir Bajic, Gordon Ball, Pedro J. Ballester, Delora Baptista, Christopher Bare, Mathilde Bateson, Andreas Bender, Denis Bertrand, Bhagya Wijayawardena, Keith A. Boroevich, Evert Bosdriesz, Salim Bougouffa, Gergana Bounova, Thomas Brouwer, Barbara Bryant, Manuel Calaza, Alberto Calderone, Stefano Calza, Stephen Capuzzi, Jose Carbonell-Caballero, Daniel Carlin, Hannah Carter, Luisa Castagnoli, Remzi Celebi, Gianni Cesareni, Hyeokyoon Chang, Guocai Chen, Haoran Chen, Huiyuan Chen, Lijun Cheng, Ariel Chernomoretz, Davide Chicco, Kwang-Hyun Cho, Sunghwan Cho, Daeseon Choi, Jaejoon Choi, Kwanghun Choi, Minsoo Choi, Martine De Cock, Elizabeth Coker, Isidro Cortes-Ciriano, Miklós Cserzö, Cankut Cubuk, Christina Curtis, Dries Van Daele, Cuong C. Dang, Tjeerd Dijkstra, Joaquin Dopazo, Sorin Draghici, Anastasios Drosou, Michel Dumontier, Friederike Ehrhart, Fatma-Elzahraa Eid, Mahmoud ElHefnawi, Haitham Elmarakeby, Bo van Engelen, Hatice Billur Engin, Iwan de Esch, Chris Evelo, Andre O. Falcao, Sherif Farag, Carlos Fernandez-Lozano, Kathleen Fisch, Asmund Flobak, Chiara Fornari, Amir B. K. Foroushani, Donatien Chedom Fotso, Denis Fourches
Nature Communications, Uluslararası, Wos, 2019, cilt 10, ss 2674-2674
DOI: 10.1038/s41467-019-09799-2
Özet
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.