13 research outputs found
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
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.Peer reviewe
Microsecond time-resolved energy-dispersive EXAFS measurement and its application to film the thermolysis of (NH4)2[PtCl6]
FIBP knockdown attenuates growth and enhances chemotherapy in colorectal cancer via regulating GSK3β-related pathways
Feeding habits of the swordfish (Xiphias gladius Linnaeus, 1758) in the subtropical northeast Pacific
Математическое описание градуировочных кривых намагничивания и размагничивания феррорегистраторов
Описаны два способа упрощения обработки результатов измерений больших токов путем замены градуировочных кривых феррорегистраторов таблицами зависимости остаточной индукции от напряженности магнитного поля. Приведен порядок практического применения полученных способов