Upon emergence of modern anticancer therapy,medical community is divided into two opposite camps,one of them claiming absolute necessity of using isolated or synthesized chemical compounds for efficient patient treatm...Upon emergence of modern anticancer therapy,medical community is divided into two opposite camps,one of them claiming absolute necessity of using isolated or synthesized chemical compounds for efficient patient treatment and another one advocating alternative cancer therapies,in particular those based on natural sources,including extracts from plants.It seems,in reality,that the two camps are reconcilable:while natural sources,plant extracts or juices play both curative and protective role,drugs represent the ultimate possibility to inhibit or reverse tumor development.In this paper we tried to analyze anti-breast cancer potencies of quite a few extracts from different plant sources and to compare their anti-proliferative efficiency of crude extracts with actions of their purified ingredients.展开更多
Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Ab...Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.展开更多
[Objectives]To investigate the effects of quercetin extracted from flower buds of Sophora japonica cv.jinhuai on the proliferation,apoptosis and migration of human breast cancer MCF-7 cells.[Methods]MTT assay,inverted...[Objectives]To investigate the effects of quercetin extracted from flower buds of Sophora japonica cv.jinhuai on the proliferation,apoptosis and migration of human breast cancer MCF-7 cells.[Methods]MTT assay,inverted microscope observation,hoechst33342 staining,flow cytometry(FCM)and wound healing assay were adopted to investigate the proliferation,morphological changes,apoptosis level and cell migration ability of human breast cancer MCF-7 cells,respectively.[Results]The morphological changes of cells in the treatment groups included gradually decreased number,reduced volume,vague cell contour,loose intercellular connection,uneven cytoplasm distribution and increased cell debris.With the increase of drug concentration,quercetin significantly inhibited the proliferation of human breast cancer MCF-7 cells(P<0.05).The number of apoptotic bodies increased gradually.When the concentration reached 100μmol/L,a large number of nuclear fragments appeared,and the level of apoptosis was statistically different(P<0.05).The mobility and migration ability of cells showed a decreasing trend,and the differences were statistically significant(P<0.05).[Conclusions]This study can provide experimental basis for clinical application of quercetin against breast cancer.展开更多
目的:探讨血清抗着丝粒蛋白F抗体(anti-centromere protein F antibody,anti-CENPF)在乳腺癌中的临床价值。方法:收集100例初诊乳腺癌(breast cancer,BC)患者、40例乳腺良性疾病(non breast cancer,non-BC)患者和40名健康体检者(healthy...目的:探讨血清抗着丝粒蛋白F抗体(anti-centromere protein F antibody,anti-CENPF)在乳腺癌中的临床价值。方法:收集100例初诊乳腺癌(breast cancer,BC)患者、40例乳腺良性疾病(non breast cancer,non-BC)患者和40名健康体检者(healthy control,HC)血清,采用酶联免疫吸附试验检测血清中的anti-CENPF水平,同时化学发光法测定血清糖类抗原153(carbohydrate antigen 153,CA153)的水平。结果:BC组血清anti-CENPF水平高于non-BC组和HC组,差异有统计学意义(P<0.05)。anti-CENPF和CA153诊断乳腺癌中的曲线下面积(area under the curve,AUC)分别为0.714和0.672,两者联合检测的AUC为0.739。有淋巴结转移、远处转移或者人表皮生长因子受体2(human epidermal growth factor receptor-2,HER-2)阴性的乳腺癌患者血清anti-CENPF浓度明显升高(P<0.05)。不同肿瘤大小、临床分期、分子分型乳腺癌患者血清anti-CENPF水平比较,差异有统计学意义(P<0.05)。组间比较显示Ⅳ期和Ⅲ期血清anti-CENPF浓度高于Ⅰ期和Ⅱ期,HER-2过表达型、Luminal B型血清anti-CENPF水平低于三阴性乳腺癌(triple negative breast cancer,TNBC)患者。雌激素受体(receptors estrogen,ER)阳性的乳腺癌患者中,HER-2阴性组的anti-CENPF浓度高于HER-2阳性组,差异有统计学意义(P=0.026)。结论:血清antiCENPF在乳腺癌的诊断、临床分期及分子分型中发挥了重要作用,其水平可能与乳腺癌预后呈负相关,有望成为乳腺癌潜在的疾病标志物。展开更多
目的利用UPLC-Q-TOF-MS/MS技术和网络药理学探讨尖尾芋抗乳腺癌物质基础及作用机制。方法结合MassBank等数据库及现有文献研究,鉴定尖尾芋醇提物的化学成分,通过TCMSP、GeneCards等数据库筛选尖尾芋抗乳腺癌的作用靶点,使用STRING数据库...目的利用UPLC-Q-TOF-MS/MS技术和网络药理学探讨尖尾芋抗乳腺癌物质基础及作用机制。方法结合MassBank等数据库及现有文献研究,鉴定尖尾芋醇提物的化学成分,通过TCMSP、GeneCards等数据库筛选尖尾芋抗乳腺癌的作用靶点,使用STRING数据库和Cytoscape 3.9.0构建关键靶点蛋白相互作用(protein-protein interaction,PPI)网络;通过DAVID数据库对关键靶点进行基因本体论(gene ontology,GO)功能与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)信号通路富集分析,最后借助Cytoscape 3.9.0构建“成分-基因-通路”互作网络图。结果从尖尾芋醇提物中共鉴定18个成分,包括生物碱类(1,3,10,12)、苯丙素类(2,8,18)、黄酮类(6,7,9,11,15)等;基于鉴定出的化合物通过网络药理学得到429个潜在作用靶点;PPI分析发现PIK3CA、PIK3R1、MAPK1等10个核心靶点,富集分析发现核心靶点可能通过调控癌症通路发挥抗乳腺癌作用,“成分-基因-通路”互作网络图显示生物碱类成分小檗碱及黄酮类成分山柰酚、木犀草素可能是尖尾芋醇提物发挥药效的主要活性成分,其机制与凋亡相关。结论本研究初步探究了尖尾芋醇提物抗乳腺癌活性成分为生物碱及黄酮类成分,其作用机制与细胞凋亡相关,为进一步开展尖尾芋醇提物抗乳腺癌的药效物质基础及作用机制研究提供了新的思路和线索。展开更多
文摘Upon emergence of modern anticancer therapy,medical community is divided into two opposite camps,one of them claiming absolute necessity of using isolated or synthesized chemical compounds for efficient patient treatment and another one advocating alternative cancer therapies,in particular those based on natural sources,including extracts from plants.It seems,in reality,that the two camps are reconcilable:while natural sources,plant extracts or juices play both curative and protective role,drugs represent the ultimate possibility to inhibit or reverse tumor development.In this paper we tried to analyze anti-breast cancer potencies of quite a few extracts from different plant sources and to compare their anti-proliferative efficiency of crude extracts with actions of their purified ingredients.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_0082)
文摘Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.
基金Guilin Scientific Research and Technology Development Program(20210202-120220104-4)Special Project of the Central Government in Guidance of Local Science and Technology Development(ZY20230102).
文摘[Objectives]To investigate the effects of quercetin extracted from flower buds of Sophora japonica cv.jinhuai on the proliferation,apoptosis and migration of human breast cancer MCF-7 cells.[Methods]MTT assay,inverted microscope observation,hoechst33342 staining,flow cytometry(FCM)and wound healing assay were adopted to investigate the proliferation,morphological changes,apoptosis level and cell migration ability of human breast cancer MCF-7 cells,respectively.[Results]The morphological changes of cells in the treatment groups included gradually decreased number,reduced volume,vague cell contour,loose intercellular connection,uneven cytoplasm distribution and increased cell debris.With the increase of drug concentration,quercetin significantly inhibited the proliferation of human breast cancer MCF-7 cells(P<0.05).The number of apoptotic bodies increased gradually.When the concentration reached 100μmol/L,a large number of nuclear fragments appeared,and the level of apoptosis was statistically different(P<0.05).The mobility and migration ability of cells showed a decreasing trend,and the differences were statistically significant(P<0.05).[Conclusions]This study can provide experimental basis for clinical application of quercetin against breast cancer.
文摘目的:探讨血清抗着丝粒蛋白F抗体(anti-centromere protein F antibody,anti-CENPF)在乳腺癌中的临床价值。方法:收集100例初诊乳腺癌(breast cancer,BC)患者、40例乳腺良性疾病(non breast cancer,non-BC)患者和40名健康体检者(healthy control,HC)血清,采用酶联免疫吸附试验检测血清中的anti-CENPF水平,同时化学发光法测定血清糖类抗原153(carbohydrate antigen 153,CA153)的水平。结果:BC组血清anti-CENPF水平高于non-BC组和HC组,差异有统计学意义(P<0.05)。anti-CENPF和CA153诊断乳腺癌中的曲线下面积(area under the curve,AUC)分别为0.714和0.672,两者联合检测的AUC为0.739。有淋巴结转移、远处转移或者人表皮生长因子受体2(human epidermal growth factor receptor-2,HER-2)阴性的乳腺癌患者血清anti-CENPF浓度明显升高(P<0.05)。不同肿瘤大小、临床分期、分子分型乳腺癌患者血清anti-CENPF水平比较,差异有统计学意义(P<0.05)。组间比较显示Ⅳ期和Ⅲ期血清anti-CENPF浓度高于Ⅰ期和Ⅱ期,HER-2过表达型、Luminal B型血清anti-CENPF水平低于三阴性乳腺癌(triple negative breast cancer,TNBC)患者。雌激素受体(receptors estrogen,ER)阳性的乳腺癌患者中,HER-2阴性组的anti-CENPF浓度高于HER-2阳性组,差异有统计学意义(P=0.026)。结论:血清antiCENPF在乳腺癌的诊断、临床分期及分子分型中发挥了重要作用,其水平可能与乳腺癌预后呈负相关,有望成为乳腺癌潜在的疾病标志物。
文摘目的利用UPLC-Q-TOF-MS/MS技术和网络药理学探讨尖尾芋抗乳腺癌物质基础及作用机制。方法结合MassBank等数据库及现有文献研究,鉴定尖尾芋醇提物的化学成分,通过TCMSP、GeneCards等数据库筛选尖尾芋抗乳腺癌的作用靶点,使用STRING数据库和Cytoscape 3.9.0构建关键靶点蛋白相互作用(protein-protein interaction,PPI)网络;通过DAVID数据库对关键靶点进行基因本体论(gene ontology,GO)功能与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)信号通路富集分析,最后借助Cytoscape 3.9.0构建“成分-基因-通路”互作网络图。结果从尖尾芋醇提物中共鉴定18个成分,包括生物碱类(1,3,10,12)、苯丙素类(2,8,18)、黄酮类(6,7,9,11,15)等;基于鉴定出的化合物通过网络药理学得到429个潜在作用靶点;PPI分析发现PIK3CA、PIK3R1、MAPK1等10个核心靶点,富集分析发现核心靶点可能通过调控癌症通路发挥抗乳腺癌作用,“成分-基因-通路”互作网络图显示生物碱类成分小檗碱及黄酮类成分山柰酚、木犀草素可能是尖尾芋醇提物发挥药效的主要活性成分,其机制与凋亡相关。结论本研究初步探究了尖尾芋醇提物抗乳腺癌活性成分为生物碱及黄酮类成分,其作用机制与细胞凋亡相关,为进一步开展尖尾芋醇提物抗乳腺癌的药效物质基础及作用机制研究提供了新的思路和线索。
