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The herb Radix Ophiopogonis (RO) has been used effectively to treat nasopharyngeal carcinoma (NPC) as an adjunctive therapy. Due to the complexity of the traditional Chinese herbs, the pharmacological mechanism of RO’s action on NPC remains unclear. To address this problem, an integrative approach bridging proteome experiments with bioinformatics prediction was employed. First, differentially expressed protein profile from NPC serum samples was established using isobaric tag for relative and absolute quantification (iTRAQ) coupled 2-D liquid chromatography (LC)-MS/MS analysis. Second, the RO putative targets were predicted using Traditional Chinese Medicines Integrated Database and known therapeutic targets of NPC were collected from Drugbank and OMIM databases. Then, a network between RO putative targets and NPC known therapeutic targets was constructed. Third, based on pathways enrichment analysis, an integrative network was constructed using DAVID and STRING database in order to identify potential candidate targets of RO against NPC. As a result, we identified 13 differentially expressed proteins from clinical experiments compared with the healthy control. And by bioinformatics investigation, 12 putative targets of RO were selected. Upon interactions between experimental and predicted candidate targets, we identified three key candidate targets of RO against NPC: VEGFA, TP53, and HSPA8, by calculating the nodes’ topological features. In conclusion, this integrative pharmacology-based analysis revealed the anti-NPC effects of RO might be related to its regulatory impact via the PI3K-AKT signaling pathway, the Wnt signaling pathway, and the cAMP signaling pathway by targeting VEGFA, TP53, and HSPA8. The findings of potential key targets may provide new clues for NPC’s treatments with the RO adjunctive therapy.

The herb Radix Ophiopogonis (RO) has been used effectively to treat nasopharyngeal carcinoma (NPC) as an adjunctive therapy. Due to the complexity of the traditional Chinese herbs, the pharmacological mechanism of RO's action on NPC remains unclear. To address this problem, an integrative approach bridging proteome experiments with bioinformatics prediction was employed. First, differentially expressed protein profile from NPC serum samples was established using isobaric tag for relative and absolute quantification (iTRAQ) coupled 2-D liquid chromatography (LC)-MS/MS analysis. Second, the RO putative targets were predicted using Traditional Chinese Medicines Integrated Database and known therapeutic targets of NPC were collected from Drugbank and OMIM databases. Then, a network between RO putative targets and NPC known therapeutic targets was constructed. Third, based on pathways enrichment analysis, an integrative network was constructed using DAVID and STRING database in order to identify potential candidate targets of RO against NPC. As a result, we identified 13 differentially expressed proteins from clinical experiments compared with the healthy control. And by bioinformatics investigation, 12 putative targets of RO were selected. Upon interactions between experimental and predicted candidate targets, we identified three key candidate targets of RO against NPC: VEGFA, TP53, and HSPA8, by calculating the nodes' topological features. In conclusion, this integrative pharmacology-based analysis revealed the anti-NPC effects of RO might be related to its regulatory impact via the PI3K-AKT signaling pathway, the Wnt signaling pathway, and the cAMP signaling pathway by targeting VEGFA, TP53, and HSPA8. The findings of potential key targets may provide new clues for NPC's treatments with the RO adjunctive therapy. [ABSTRACT FROM AUTHOR]