目的 利用網(wǎng)絡(luò)藥理學(xué)結(jié)合GEO基因芯片分析的方法以及細(xì)胞實(shí)驗(yàn)研究小白菊內(nèi)酯治療宮頸癌的分子機(jī)制。方法 首先利用GEO數(shù)據(jù)庫(kù)獲取宮頸癌芯片數(shù)據(jù),再通過(guò)R軟件獲得其差異基因,同時(shí)繪制火山圖。利用Swiss Target Prediction、SuperPred和HERB數(shù)據(jù)庫(kù)收集小白菊內(nèi)酯的作用靶點(diǎn)。通過(guò)GEO差異基因、Malacards、PharmGkb、CTD、DrugBank和DisGeNET數(shù)據(jù)庫(kù)收集宮頸癌的疾病靶基因,利用Cytoscape 3.7.2軟件制作藥物-活性成分-靶點(diǎn)-疾病網(wǎng)絡(luò)圖,通過(guò)String數(shù)據(jù)庫(kù)和Cytoscape3.7.2軟件對(duì)交集基因進(jìn)行蛋白相互作用(PPI)網(wǎng)絡(luò)富集分析。利用R語(yǔ)言的clusterfiler程序包對(duì)小白菊內(nèi)酯治療宮頸癌的潛在作用靶標(biāo)進(jìn)行基因本體(GO)富集分析和京都基因與基因組百科全書(shū)(KEGG)信號(hào)通路富集分析。最后,通過(guò)人宮頸癌He La細(xì)胞模型驗(yàn)證小白菊內(nèi)酯的作用機(jī)制。結(jié)果 獲取88個(gè)小白菊內(nèi)酯靶基因,8 167個(gè)宮頸癌的疾病靶點(diǎn),26個(gè)差異基因,3個(gè)在宮頸癌中表達(dá)上調(diào),23個(gè)在宮頸癌中表達(dá)下調(diào)。PPI網(wǎng)絡(luò)以及拓?fù)浞治鼋Y(jié)果顯示,Toll樣受體4(TLR4)、前列腺素內(nèi)過(guò)氧化物酶2(PTGS2)、人細(xì)胞色素p450家族成員2C9(CYP2C9)、細(xì)胞色素P450 3A4酶(CYP3A4)、組蛋白脫乙?；?(HDAC2)、溴結(jié)構(gòu)域包含蛋白2(BRD2)和溴結(jié)構(gòu)域包含蛋白4(BRD4)是小白菊內(nèi)酯治療宮頸癌的7個(gè)核心基因。GO富集分析得出小白菊內(nèi)酯影響的生物學(xué)過(guò)程(BP)有452個(gè),包括對(duì)外源性刺激的反應(yīng)、雌激素代謝過(guò)程等,作用的細(xì)胞組合(CC)有43個(gè),包括組蛋白脫乙酰酶復(fù)合物、組蛋白甲基轉(zhuǎn)移酶復(fù)合物等,作用的分子功能(MF)有41個(gè);KEGG通路富集分析結(jié)果顯示小白菊內(nèi)酯治療宮頸癌可能涉及藥物代謝-細(xì)胞色素P450、細(xì)胞色素P450對(duì)異種物質(zhì)的代謝及Toll樣受體信號(hào)通路等信號(hào)通路。MTT實(shí)驗(yàn)證明,小白菊內(nèi)酯以劑量相關(guān)的方式抑制HeLa細(xì)胞的增殖,IC₅₀值為6μmol/L。結(jié)論 小白菊內(nèi)酯能夠明顯抑制Hela細(xì)胞增殖,作用機(jī)制可能涉及多個(gè)靶點(diǎn)和多條通路。

Objective To study the molecular mechanism of parthenolide in treatment of cervical cancer based on network pharmacology combined with GEO gene chip analysis and cell experiment.Methods GEO database was used to obtain cervical cancer chip data, and then R software was used to obtain its differential genes, and the volcano map was drawn at the same time. Swiss Target Prediction, SuperPred, and HERB databases were used to collect the action targets of parthenolide. The target genes of cervical cancer were collected through GEO differential genes, Malacards, PharmGkb, CTD, DrugBank, and DisGeNET databases, and the drug-active ingredient-target-disease network map was made using Cytoscape 3.7.2 software. The protein interaction(PPI) network enrichment analysis of intersection genes was performed using the String database and Cytoscape3.7.2 software. The gene ontology(GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes(KEGG) signaling pathway enrichment analysis of the potential targets of parthenolide in treatment of cervical cancer were conducted using the clusterfiler package in R language. The mechanism of parthenolide was verified by HeLa cell model of human cervical cancer.Results A total of 88 parthenolide target genes,8 167 disease targets of cervical cancer, and 26 differentially expressed genes with 3 up-regulated and 23 down-regulated in cervical cancer were chosen. PPI network and topology analysis results show that TLR4, PTGS2, CYP2C9, CYP3A4, HDAC2, BRD2, and BRD4 are the seven core genes of parthenolide in treatment of cervical cancer. GO enrichment analysis showed that there were 452biological processes(BP) affected by parthenolide, including response to exogenous stimuli and estrogen metabolism, 43 cell combinations(CC) affected by parthenolide, including histone deacetylase complex and histone methyltransferase complex, and 41molecular functions(MF) affected by parthenolide. The results of KEGG pathway enrichment analysis showed that the treatment of cervical cancer by parthenolide may involve drug metabolism, cytochrome P450, cytochrome P450 metabolism of heterogeneous substances and toll-like receptor signaling pathway. MTT assay demonstrated that parthenolide inhibited HeLa cell proliferation in a dose-dependent manner with IC₅₀ of 6 μmol/L.Conclusion Parthenolide can significantly inhibit the proliferation of Hela cells, and the mechanism of action may be that parthenolide can treat cervical cancer through multiple targets and multiple pathways.

R979.1; R285

國(guó)家自然科學(xué)基金面上項(xiàng)目(8207091525,81872236)