BackgroundPolycystic ovary syndrome (PCOS) significantly affects women’s health and well-being. To explore the pharmacological basis of the Erxian decoction (EXD) action in PCOS therapy, a network interaction analysis was conducted at the molecular level.MethodsThe active elements of EXD were identified according to the oral bioavailability and drug-likeness filters from three databases: traditional Chinese medicine system pharmacology analysis platform, TCM@taiwan and TCMID, and their potential targets were also identified. Genes associated with PCOS and established protein–protein interaction networks were mined from the NCBI database. Finally, significant pathways and functions of these networks were identified using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to determine the mechanism of action of EXD.ResultsSeventy active compounds were obtained from 981 ingredients present in the EXD decoction, corresponding to 247 targets. In addition, 262 genes were found to be closely related with PCOS, of which 50 overlapped with EXD and were thus considered therapeutically relevant. Pathway enrichment analysis identified PI3k-Akt, insulin resistance, Toll-like receptor, MAPK and AGE-RAGE from a total of 15 significant pathways in PCOS and its treatment.ConclusionsEXD can effectively improve the symptoms of PCOS and our systemic pharmacological analysis lays the experimental foundation for further clinical applications of EXD.

Background:Nasopharyngeal carcinoma (NPC) is a common head and neck cancer epidemic in southern China and southeast Asia. LeiGongTeng has been widely used for the treatment of cancers. The purpose of this study was to determine the pharmacological mechanism of action of LeiGongTeng in the treatment of NPC using a network pharmacological approach. Material/Methods:The traditional Chinese medicine systems pharmacology (TCMSP) database was used to identify active ingredients and associated target proteins for LeiGongTeng. Cytoscape was utilized to create a drug-disease network and topology analysis was conducted to analyze the degree of each ingredient. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) online tool was applied for the construction and analysis of the protein-protein interaction (PPI) network, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) functional analyses were utilized to determine drug-disease common genes. Results:22 active ingredients including kaempferol, nobiletin, and beta-sitosterol, and 30 drug-disease common genes including VEGFA, CASP3, ESR1, and RELA were identified. GO analysis indicated that 94 biological processes, including RNA polymerase II, apoptotic process, response to drug, cell adhesion, and response to hypoxia, were found to be associated with NPC. The KEGG enrichment analysis showed that 58 pathways, including the PI3K-Akt signaling pathway, microRNAs in cancer, tumor necrosis factor (TNF) signaling pathway and pathways in cancer were found to be associated with NPC. Conclusions:LeiGongTeng exerts its therapeutic effect through various biological processes and signaling pathways since it acts on several target genes. Systematic pharmacology can be used to predict the underlying function of LeiGongTeng and its mechanism of action in NPC.

Background:Determination of the radiosensitivity of a specific tumor is essential to its precision tumor radiotherapy, but the measurement of cellular radiosensitivity with a routine colony forming assay is both labor- and time-consuming. An alternative option allowing rapid and precise prediction of radiosensitivity is necessary.Methods:In this study, we exposed 4 in vitro cultured cell lines to various doses of X-rays or carbon ions and then measured their radiosensitivities with a routine colony-forming assay, and monitored the kinetics of cell cycle distribution with routine propidium iodine staining and flow cytometry.Results:Based on the results, we correlated cellular radiosensitivity with a dynamic assay of cell cycle distribution, specifically, the negative correlation of cellular radiosensitivity with the accumulated G2/M arrested cells at 48 hours after exposure. The higher the proportion of accumulated G2/M arrested cells at 48 hours after exposure, the lower the radiosensitivity of the cell line, that is, the higher radioresistance of the cell line.Conclusion:These findings provide an optional application of regular cell cycle analysis for the prediction of tumor radiosensitivity.