%0 Journal Article %J Nat Commun %D 2019 %T Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. %A Menden, Michael P %A Wang, Dennis %A Mason, Mike J %A Szalai, Bence %A Bulusu, Krishna C %A Guan, Yuanfang %A Yu, Thomas %A Kang, Jaewoo %A Jeon, Minji %A Wolfinger, Russ %A Nguyen, Tin %A Zaslavskiy, Mikhail %A Jang, In Sock %A Ghazoui, Zara %A Ahsen, Mehmet Eren %A Vogel, Robert %A Neto, Elias Chaibub %A Norman, Thea %A Tang, Eric K Y %A Garnett, Mathew J %A Veroli, Giovanni Y Di %A Fawell, Stephen %A Stolovitzky, Gustavo %A Guinney, Justin %A Dry, Jonathan R %A Saez-Rodriguez, Julio %K ADAM17 Protein %K Antineoplastic Combined Chemotherapy Protocols %K Benchmarking %K Biomarkers, Tumor %K Cell Line, Tumor %K Computational Biology %K Datasets as Topic %K Drug Antagonism %K Drug Resistance, Neoplasm %K Drug Synergism %K Genomics %K Humans %K Molecular Targeted Therapy %K mutation %K Neoplasms %K pharmacogenetics %K Phosphatidylinositol 3-Kinases %K Phosphoinositide-3 Kinase Inhibitors %K Treatment Outcome %X

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.

%B Nat Commun %V 10 %P 2674 %8 2019 06 17 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/31209238?dopt=Abstract %R 10.1038/s41467-019-09799-2 %0 Journal Article %J Drug Metab Pers Ther %D 2016 %T Progress in pharmacogenetics: consortiums and new strategies. %A Maroñas, Olalla %A Latorre, Ana %A Dopazo, Joaquin %A Pirmohamed, Munir %A Rodríguez-Antona, Cristina %A Siest, Gérard %A Carracedo, Ángel %A LLerena, Adrián %K Cooperative Behavior %K Genome-Wide Association Study %K High-Throughput Screening Assays %K Humans %K Patient Care Team %K pharmacogenetics %K Polymorphism, Single Nucleotide %K Precision Medicine %X

Pharmacogenetics (PGx), as a field dedicated to achieving the goal of personalized medicine (PM), is devoted to the study of genes involved in inter-individual response to drugs. Due to its nature, PGx requires access to large samples; therefore, in order to progress, the formation of collaborative consortia seems to be crucial. Some examples of this collective effort are the European Society of Pharmacogenomics and personalized Therapy and the Ibero-American network of Pharmacogenetics. As an emerging field, one of the major challenges that PGx faces is translating their discoveries from research bench to bedside. The development of genomic high-throughput technologies is generating a revolution and offers the possibility of producing vast amounts of genome-wide single nucleotide polymorphisms for each patient. Moreover, there is a need of identifying and replicating associations of new biomarkers, and, in addition, a greater effort must be invested in developing regulatory organizations to accomplish a correct standardization. In this review, we outline the current progress in PGx using examples to highlight both the importance of polymorphisms and the research strategies for their detection. These concepts need to be applied together with a proper dissemination of knowledge to improve clinician and patient understanding, in a multidisciplinary team-based approach.

%B Drug Metab Pers Ther %V 31 %P 17-23 %8 2016 Mar %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/26913460?dopt=Abstract %R 10.1515/dmpt-2015-0039