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Essentiality andTranscriptome-Enriched Pathway ScoresPredictDrug-CombinationSynergy Jin LiYang HuoXue Wu2020 год

Essentiality and Transcriptome-Enriched Pathway Scores Predict Drug-Combination Synergy
статья из журнала

Полный текстСтраница публикацииПубликация в OpenAlex
Аннотация: In the prediction of the synergy of drug combinations, systems pharmacology models expand the scope of experiment screening and overcome the limitations of current computational models posed by their lack of mechanical interpretation and integration of gene essentiality. We therefore investigated the synergy of drug combinations for cancer therapies utilizing records in NCI ALMANAC, and we employed logistic regression to test the statistical significance of gene and pathway features in that interaction. We trained our predictive models using 43 NCI-60 cell lines, 165 KEGG pathways, and 114 drug pairs. Scores of drug-combination synergies showed a stronger correlation with pathway than gene features in overall trend analysis and a significant association with both genes and pathways in genome-wide association analyses. However, we observed little overlap of significant gene expressions and essentialities and no significant evidence that associated target and non-target genes and their pathways. We were able to validate four drug-combination pathways between two drug combinations, Nelarabine-Exemestane and Docetaxel-Vermurafenib, and two signaling pathways, PI3K-AKT and AMPK, in 16 cell lines. In conclusion, pathways significantly outperformed genes in predicting drug-combination synergy, and because they have very different mechanisms, gene expression and essentiality should be considered in combination rather than individually to improve this prediction.
Год издания: 2020
Авторы: Jin Li, Yang Huo, Xue Wu, Enze Liu, Zhi Jiang Zeng, Zhen Tian, Kunjie Fan, Daniel G. Stover, Lijun Cheng, Lang Li
Издательство: Multidisciplinary Digital Publishing Institute
Источник: Biology
Ключевые слова: Computational Drug Discovery Methods, Bioinformatics and Genomic Networks, Pharmacogenetics and Drug Metabolism
Другие ссылки: Biology (PDF)
Biology (HTML)
DOAJ (DOAJ: Directory of Open Access Journals) (HTML)
Purdue University Indianapolis (Indiana University) (PDF)
Purdue University Indianapolis (Indiana University) (HTML)
PubMed Central (HTML)