目的 基于網(wǎng)絡(luò)藥理學(xué)研究香菇多糖抑制三陰乳腺癌（TNBC）的作用機(jī)制并采用細(xì)胞和動(dòng)物實(shí)驗(yàn)進(jìn)行驗(yàn)證。方法 通過GeneCards數(shù)據(jù)庫和DisGeNET數(shù)據(jù)庫篩選與TNBC相關(guān)基因靶點(diǎn)，利用TCMID、PubChem、SwissTargetPrediction和GeneCards數(shù)據(jù)庫查詢香菇多糖相關(guān)基因靶點(diǎn)。使用Sangerbox軟件進(jìn)行基因本體論（GO）富集和京都基因與基因組百科全書（KEGG）通路富集分析。結(jié)合STRING數(shù)據(jù)庫與Cytoscape 3.7.0軟件將共同靶點(diǎn)進(jìn)行可視化處理，篩選核心靶點(diǎn)，構(gòu)建"化合物-靶點(diǎn)-通路"網(wǎng)絡(luò)。利用Metascape軟件進(jìn)行轉(zhuǎn)錄因子及相關(guān)調(diào)控基因特異富集。體外培養(yǎng)小鼠TNBC細(xì)胞4T1和人TNBC細(xì)胞MDA-MB-231，磺酰羅丹明B染色法觀察香菇多糖（31.25、62.5、125、250、500、1 000μg·mL^-1）對(duì)細(xì)胞存活率的影響；健康雌性BABLC小鼠sc接種1×10⁶個(gè)4T1-Luc細(xì)胞構(gòu)建TNBC模型，通過小動(dòng)物活體成像系統(tǒng)觀察香菇多糖（100、200 mg·kg^-1）對(duì)腫瘤生長(zhǎng)的影響，實(shí)時(shí)熒光定量PCR （qRT-PCR）技術(shù)檢測(cè)腫瘤組織信號(hào)轉(zhuǎn)導(dǎo)和轉(zhuǎn)錄活化因子3（STAT3）和血管內(nèi)皮生長(zhǎng)因子A （VEGFA） mRNA表達(dá)。結(jié)果 數(shù)據(jù)庫及軟件分析得到香菇多糖治療TNBC關(guān)鍵靶點(diǎn)52個(gè)，靶點(diǎn)主要涉及PI3K-Akt、AGE-RAGE、HIF-1、MAPK信號(hào)通路和腫瘤蛋白多糖相關(guān)通路，PPI分析得到VEGFA、STAT3、MAPK1、IL2、TNF、RELA、AKT1、MAPK3、BCL2L1和HSP90AA1 10個(gè)hub基因。與對(duì)照組比較，香菇多糖對(duì)4T1和MDA-MB-231細(xì)胞存活率均有顯著抑制作用（P<0.05、0.01），且作用呈濃度相關(guān)性；在給藥14、21d后，與模型組比較，香菇多糖能夠劑量相關(guān)性地抑制小鼠TNBC腫瘤的生長(zhǎng)，高劑量組差異顯著（P<0.05、0.01），21 d抑制率達(dá)到（91.9±4.7）%；與對(duì)照組比較，香菇多糖給藥后能夠劑量相關(guān)性抑制STAT3和VEGFA的mRNA表達(dá)，高劑量組差異顯著（P<0.05、0.01）。結(jié)論 香菇多糖可通過多靶點(diǎn)、多途徑協(xié)同作用抑制TNBC的生長(zhǎng)。

Objective To study the mechanism of lentinan on inhibiting triple negative breast cancer(TNBC) based on network pharmacology and to verify it by animal and molecular biology experiments.Methods TNBC related genes were identified used Gene Cards database and DisGeNET database.Lentinan-related gene targets were inquired used TCMID, PubChem, SwissTargetPrediction and Gene Cards database.Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG)signal pathway was analysed by Sangerbox software.Core targets were visualized by combining STRING database and Cytoscape 3.7.0 software, and "chemicals-targets-pathways" network was established.The transcription factors and related regulatory genes were specifically enriched by Metascape software.Mouse TNBC cells 4T1 and human TNBC cells MDA-MB-231 were cultured in vitro.The effects of lentinan(31.25, 62.5, 125, 250, 500, 1 000 μg·mL^-1) on cell viability were observed by sulfoylrhodamine B staining.The TNBC model was constructed by inoculated with 1×10⁶ 4T1-Luc cells by sc of healthy female BABLC mice.The effect of lentinan(100 and 200 mg·kg^-1) on tumor growth was observed by in vivo small animal imaging system.The mRNA expressions of signal transducer and activator of transcription 3(STAT3) and vascular endothelial growth factor A(VEGFA) in tumor tissues were detected by real-time fluorescent quantitative PCR(qRT-PCR).Results Totally 52 key targets of lentinan related to TNBC were identified by database and software analysis, which mainly involving PI3K-Akt, AGE-RAGE, HIF-1, MAPK and proteoglycans related pathways.Totally 10 hub genes including VEGFA, STAT3, MAPK1, IL2, TNF, RELA, AKT1, MAPK3, BCL2 L1 and HSP90AA1 were identified by PPI analysis.Compared with the control group, lentinan significantly inhibited the survival rate of 4T1 and MDA-MB-231 cells(P<0.05, 0.01), and the effect was concentration dependent.After 14 and 21 days of administration, lendinan could inhibit the growth of TNBC tumor in mice dose-dependent compared with the model group, and the difference was significant in the high-dose group(P<0.05, 0.01), and the 21-day inhibition rate reached(91.9 ±4.7)%.Compared with the control group, lentinan administration could inhibit the mRNA expression of STAT3 and VEGFA in a dose-dependent manner, and the differences were significant in the high-dose group(P<0.05, 0.01).Conclusion Lentinan can inhibit the growth of TNBC through the synergistic effect of multiple targets and multiple pathways.

R285.5

浙江大學(xué)實(shí)驗(yàn)技術(shù)研究項(xiàng)目（SJS202016）