[Objectives]To elucidate potential targets and mechanisms of action of Epimedium brevicornu in treating ovarian cancer.[Methods]The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was ...[Objectives]To elucidate potential targets and mechanisms of action of Epimedium brevicornu in treating ovarian cancer.[Methods]The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to screen active components of E.brevicornu for disease control and prevention,and potential targets were collected from the DisGeNET database.These sets of bioactive and targets were analyzed using Ingenuity Pathway Analysis(IPA)to predict molecular networks affected by E.brevicornu in ovarian cancer.Venny 2.1.0 software was used to screen for proteins affected by interactions between disease and active components,which were input into the STRING 11.0 platform to construct a protein-protein interaction network.Then IPA and STRING were used to analyze common targets which were obtained from the two data analysis platform.[Results]A total of 23 major active components of E.brevicornu and 200 potential human targets were screened.IPA analysis identified 363 pathways and 24 networks shared between the set of predicted Yinyanghuo targets and ovarian cancer-associated proteins.These pathways are involved mainly in molecular mechanisms of cancer,glucocorticoid receptor signaling pathways,pancreatic adenocarcinoma signaling pathways,aryl hydrocarbon receptor signaling pathways,and macrophage function.The 24 networks have been implicated mainly in cancer,endocrine system disorders,body damage and abnormality,cell growth and proliferation,connective tissue development and function,tissue development,and other biological functions.IPA and STRING combined analysis suggested that AKT1,CASP3,JUN,FOS and CCND1 are the most likely targets of Yinyanghuo in treating ovarian cancer.[Conclusions]Our network pharmacology analysis identified several pathways that Yinyanghuo may influence to reduce ovarian cancer risk;in particular,it identified specific protein targets,including AKT1,CASP3,JUN,FOS and CCND1.展开更多
基金National Natural Science Foundation of China(U1804179)Henan Science and Technology Innovation Team:Investigation on Plant。
文摘[Objectives]To elucidate potential targets and mechanisms of action of Epimedium brevicornu in treating ovarian cancer.[Methods]The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to screen active components of E.brevicornu for disease control and prevention,and potential targets were collected from the DisGeNET database.These sets of bioactive and targets were analyzed using Ingenuity Pathway Analysis(IPA)to predict molecular networks affected by E.brevicornu in ovarian cancer.Venny 2.1.0 software was used to screen for proteins affected by interactions between disease and active components,which were input into the STRING 11.0 platform to construct a protein-protein interaction network.Then IPA and STRING were used to analyze common targets which were obtained from the two data analysis platform.[Results]A total of 23 major active components of E.brevicornu and 200 potential human targets were screened.IPA analysis identified 363 pathways and 24 networks shared between the set of predicted Yinyanghuo targets and ovarian cancer-associated proteins.These pathways are involved mainly in molecular mechanisms of cancer,glucocorticoid receptor signaling pathways,pancreatic adenocarcinoma signaling pathways,aryl hydrocarbon receptor signaling pathways,and macrophage function.The 24 networks have been implicated mainly in cancer,endocrine system disorders,body damage and abnormality,cell growth and proliferation,connective tissue development and function,tissue development,and other biological functions.IPA and STRING combined analysis suggested that AKT1,CASP3,JUN,FOS and CCND1 are the most likely targets of Yinyanghuo in treating ovarian cancer.[Conclusions]Our network pharmacology analysis identified several pathways that Yinyanghuo may influence to reduce ovarian cancer risk;in particular,it identified specific protein targets,including AKT1,CASP3,JUN,FOS and CCND1.
