Title | Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. |
Publication Type | Journal Article |
Year of Publication | 2019 |
Authors | Menden, MP, Wang, D, Mason, MJ, Szalai, B, Bulusu, KC, Guan, Y, Yu, T, Kang, J, Jeon, M, Wolfinger, R, Nguyen, T, Zaslavskiy, M, Jang, ISock, Ghazoui, Z, Ahsen, MEren, Vogel, R, Neto, EChaibub, Norman, T, K Y Tang, E, Garnett, MJ, Di Veroli, GY, Fawell, S, Stolovitzky, G, Guinney, J, Dry, JR, Saez-Rodriguez, J |
Corporate Authors | AstraZeneca-Sanger Drug Combination DREAM Consortium |
Journal | Nat Commun |
Volume | 10 |
Issue | 1 |
Pagination | 2674 |
Date Published | 2019 06 17 |
ISSN | 2041-1723 |
Keywords | ADAM17 Protein; Antineoplastic Combined Chemotherapy Protocols; Benchmarking; Biomarkers, Tumor; Cell Line, Tumor; Computational Biology; Datasets as Topic; Drug Antagonism; Drug Resistance, Neoplasm; Drug Synergism; Genomics; Humans; Molecular Targeted Therapy; mutation; Neoplasms; pharmacogenetics; Phosphatidylinositol 3-Kinases; Phosphoinositide-3 Kinase Inhibitors; Treatment Outcome |
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. |
DOI | 10.1038/s41467-019-09799-2 |
Alternate Journal | Nat Commun |
PubMed ID | 31209238 |
PubMed Central ID | PMC6572829 |
Grant List | R01 CA204856 / CA / NCI NIH HHS / United States R25 CA180993 / CA / NCI NIH HHS / United States 204735/Z/16/Z / / Wellcome Trust / United Kingdom T32 ES007329 / ES / NIEHS NIH HHS / United States / / Wellcome Trust / United Kingdom MC_UU_00002/13 / / Medical Research Council / United Kingdom MC_UU_00002/2 / / Medical Research Council / United Kingdom |