Head & neck · 2013
Using computational strategies to predict potential drugs for nasopharyngeal carcinoma.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Lan Ming-Ying, Yang Wu-Lung R, Lin Kuan-Ting, Lin Jin-Ching, Shann Yih-Jyh, Ho Ching-Yin, Huang Chi-Ying F
Аннотация
BACKGROUND: Nasopharyngeal carcinoma (NPC) is a unique cancer. Refinement of current therapy by discovering potential drugs may be approached by several computational strategies.
METHODS: We collected NPC genes from published microarray data and the literature. The NPC disease network was constructed via a protein-protein interaction (PPI) network. The Connectivity Map (CMap) was used to predict potential chemicals, and support vector machines (SVMs) were further utilized to classify the effectiveness of tested drugs against NPC using their gene expression from CMap.
RESULTS: A highly interconnected network was obtained. Several chemically sensitive genes were identified and 87 drugs were predicted with the potential for treating NPC by SVM, in which nearly half of them have anticancer effects according to the literature. The 2 top-ranked drugs, thioridazine and vorinostat, were demonstrated to be effective in inhibiting NPC cells.
CONCLUSION: This in silico approach provides a promising strategy for screening potential therapeutic drugs for NPC treatment.
METHODS: We collected NPC genes from published microarray data and the literature. The NPC disease network was constructed via a protein-protein interaction (PPI) network. The Connectivity Map (CMap) was used to predict potential chemicals, and support vector machines (SVMs) were further utilized to classify the effectiveness of tested drugs against NPC using their gene expression from CMap.
RESULTS: A highly interconnected network was obtained. Several chemically sensitive genes were identified and 87 drugs were predicted with the potential for treating NPC by SVM, in which nearly half of them have anticancer effects according to the literature. The 2 top-ranked drugs, thioridazine and vorinostat, were demonstrated to be effective in inhibiting NPC cells.
CONCLUSION: This in silico approach provides a promising strategy for screening potential therapeutic drugs for NPC treatment.
Предметные рубрики MeSH
Antineoplastic AgentsCell Line, TumorDrug Screening Assays, AntitumorGene Expression Regulation, NeoplasticHumansHydroxamic AcidsInhibitory Concentration 50Molecular Targeted TherapyNasopharyngeal NeoplasmsProtein Array AnalysisProtein Interaction MappingProtein Interaction MapsSupport Vector MachineThioridazineVorinostat