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基于红景天苷对三阴性乳腺癌关键差异基因作用机制的生物信息学和分子对接技术分析
朱紫嘉,陈霞,崔曼,文继红,王苹,宋东
PDF(2212 KB)
PDF(2212 KB)
基于红景天苷对三阴性乳腺癌关键差异基因作用机制的生物信息学和分子对接技术分析
Bioinformatics and molecular docking technology analysis on mechanism of salidroside on key differential genes of triple negative breast cancer
目的 通过生物信息学和网络药理学方法探讨红景天苷治疗三阴性乳腺癌(TNBC)的作用机制,阐明其产生治疗作用的主要靶点和信号通路。 方法 通过基因表达综合数据库(GEO)获取数据集 GSE45827,利用R软件包GSEABase进行基因集富集分析(GSEA),采用limma R软件包寻找相邻正常组织和TNBC组织之间的差异表达基因(DEGs),对DEGs进行基因本体论(GO)功能富集分析和京都基因与基因组百科全书(KEGG)信号通路富集分析,将DEGs与药物靶点结合,导入基因/蛋白相互作用检索搜查工具String数据库,形成蛋白-蛋白相互作用 (PPI)网络。使用MCODE插件对 PPI网络进行功能模块筛选,对SCORE值排名前2位的关键模块基因再次进行GO功能富集分析和KEGG信号通路富集分析。将2次KEGG富集分析所得通路与转录组数据GSEA富集分析结果取交集,获得红景天苷治疗TNBC的作用通路。使用CytoHubba插件计算出关键模块中最大团中心性(MCC)评分前 10 位的关键节点基因, 即为核心基因。 应用 AutoDock Vina 1.1.2 和PyMOL 2.3.0软件完成分子对接。 结果 KEGG与GSEA富集分析的结果取交集得到13条共同通路,涉及细胞周期、细胞衰老和p53信号通路等。GO功能富集分析结果中所涉及的有丝分裂、核分裂和姐妹染色单体分离等生物学过程与细胞周期有密切关联,与KEGG富集分析结果一致。SCORE值排名第1位的关键模块中包含5个红景天苷药物作用靶点,分别为重组人细胞周期蛋白A2(CCNA2)、细胞周期检查点激酶1(CHEK1)、驱动蛋白家族成员11(KIF11)、DNA拓扑异构酶2(TOP2A)和胸腺嘧啶酸合酶(TYMS),将上述蛋白与红景天苷进行分子对接,结果均表现出很强的结合能力(结合能<-7.0 kcal·mol-1)。 结论 红景天苷的紧密结合靶标位于TNBC的DEGs关键功能模块中,可以与CCNA2蛋白结合产生直接的调控作用,与KIF11、TOPA2、CHEK1和TYMS蛋白结合可针对TNBC的关键节点基因产生间接的调控作用,红景天苷有可能成为TNBC的临床治疗药物。
Objective To discuss the mechanism of salidroside in the treatment of triple negative breast cancer (TNBC) by using the bioinformatics and network pharmacology methods, and to clarify the main targets and signaling pathways involved in the therapeutic effect. Methods The dataset GSE45827 was obtained from the Gene Expression Omnibus (GEO) database; the gene set enrichment analysis (GSEA) was performed by using the R software package GSEABase;the differentially expressed genes (DEGs) between the adjacent normal tissue and TNBC tissue were identified by limma R software package;the Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis were performed on the DEGs, and the DEGs were integrated with the drug targets to import into gene/protein interaction retrieval tool String database, and the protein-protein interaction (PPI) networks were constructed;the functional module screening of the PPI network was conducted by MCODE plugin, and the top 2 modules ranked by SCORE value were further subjected to GO functional enrichment analysis and KEGG signaling pathway analysis. The pathways obtained from the two rounds of KEGG enrichment analysis were intersected with the results of GSEA enrichment analysis to identify the pathways involved in the therapeutic effect of salidroside on TNBC. The top 10 key node genes in the highest scoring module determined by the maximum clique centrality (MCC) score caculated by CytoHubba plugi were considered as the core genes; the molecular docking was performed by AutoDock Vina1.1.2 and PyMOL2.3.0 Software. Results The intersection of KEGG and GSEA enrichment analysis results showed 13 singaling pathways, including the cell cycle, cellular senescence, and p53 signaling pathways,and so on. The biological processes involved in the GO functional analysis, such as mitosis, nuclear division, and sister chromatid separation, were closely related to the cell cycle and consistented with the results of the KEGG signaling pathway enrichment analysis. The top ranked module based on the SCORE value contained 5 drug target genes of Rhodiola glycoside,such as cyclin A2 (CCNA2), checkpoint kinase 1 (CHEK1), kinesin family member 11 (KIF11), DNA topoisomerase 2-alpha (TOP2A), and thymidylate synthase (TYMS). The molecular docking results demonstrated strong binding affinities between the above proteins and Rhodiola glycoside (binding energy<-7.0 kcal·mol-1). Conclusion The tightly binding target of salidroside is located in the key functional modules of DEGs of TNBC, which can directly regulate by binding with CCNA2 and protein, and indirectly regulate the key differentially genes of TNBC by binding with KIF11, TOPA2, CHEK1 and TYMS proteins. Therefore, salidroside may be a potential clinical therapeutic drug for TNBC.
红景天苷 / 三阴性乳腺癌 / 生物信息学 / 网络药理学 / 分子对接
Salidroside / Triple negative breast cancer / Bioinformatics / Network pharmacology / Molecular docking
R737.9
| 1 | 李清平, 王心强. 三阴型和非三阴型乳腺癌的临床病理特征及无瘤生存率对比[J]. 中国地方病防治杂志, 2017, 32(3): 342-343. |
| 2 | 冷茹冰, 张新阁, 周红艳, 等. 不同分子分型乳腺癌的临床病理特征及预后危险因素分析[J]. 临床医学, 2021, 41(5): 8-10. |
| 3 | MA W D, WANG Z Y, ZHAO Y, et al. Salidroside suppresses the proliferation and migration of human lung cancer cells through AMPK-dependent NLRP3 inflammasome regulation[J]. Oxid Med Cell Longev, 2021, 2021: 6614574. |
| 4 | HU X L, ZHANG X Q, QIU S F, et al. Salidroside induces cell-cycle arrest and apoptosis in human breast cancer cells[J]. Biochem Biophys Res Commun, 2010, 398(1): 62-67. |
| 5 | RONG L, LI Z D, LENG X, et al. Salidroside induces apoptosis and protective autophagy in human gastric cancer AGS cells through the PI3K/Akt/mTOR pathway[J]. Biomedecine Pharmacother, 2020, 122: 109726. |
| 6 | 龚 舒, 段承刚, 陶忠桦, 等. 红景天苷对人乳腺癌MDA-MB-435细胞功能的作用[J]. 泸州医学院学报, 2016, 39(2): 118-123. |
| 7 | KANG D Y, SP N, KIM D H, et al. Salidroside inhibits migration, invasion and angiogenesis of MDA?MB 231 TNBC cells by regulating EGFR/Jak2/STAT3 signaling via MMP2[J]. Int J Oncol, 2018, 53(2): 877-885. |
| 8 | SUN A Q, JU X L. Inhibitory effects of salidroside on MCF-7 breast cancer cells in vivo [J]. J Int Med Res, 2020, 48(11): 300060520968353. |
| 9 | 何思怡, 李 贺, 曹毛毛, 等. 全球及我国女性乳腺癌疾病负担年龄分布及变化趋势[J]. 中国肿瘤, 2023, 32(1): 1-7. |
| 10 | LI X X, YANG J, PENG L M, et al. Triple-negative breast cancer has worse overall survival and cause-specific survival than non-triple-negative breast cancer[J].Breast Cancer Res Treat,2017,161(2):279-287. |
| 11 | BONOTTO M, GERRATANA L, POLETTO E,et al.Measures of outcome in metastatic breast cancer: insights from a real-world scenario[J]. Oncologist, 2014, 19(6): 608-615. |
| 12 | YIN L, DUAN J J, BIAN X W, et al. Triple-negative breast cancer molecular subtyping and treatment progress[J]. Breast Cancer Res, 2020, 22(1): 61. |
| 13 | HAHNEN E, LEDERER B, HAUKE J, et al. Germline mutation status, pathological complete response, and disease-free survival in triple-negative breast cancer: secondary analysis of the GeparSixto randomized clinical trial[J]. JAMA Oncol,2017,3(10): 1378-1385. |
| 14 | KORNILUK A, KOPER O, KEMONA H, et al. From inflammation to cancer[J]. Ir J Med Sci, 2017, 186(1): 57-62. |
| 15 | SILVA CORREIA J D A, MIRANDA Y, AUSTIN-BROWN N, et al. Nod1-dependent control of tumor growth[J]. Proc Natl Acad Sci U S A, 2006, 103(6): 1840-1845. |
| 16 | HUANG C K, YANG C Y, JENG Y M, et al. Autocrine/paracrine mechanism of interleukin-17B receptor promotes breast tumorigenesis through NF-κB-mediated antiapoptotic pathway[J]. Oncogene, 2014, 33(23): 2968-2977. |
| 17 | GOMES A L, TEIJEIRO A, BURéN S, et al. Metabolic inflammation-associated IL-17A causes non-alcoholic steatohepatitis and hepatocellular carcinoma[J]. Cancer Cell, 2016, 30(1): 161-175. |
| 18 | 赵媛媛, 张 楠, 孙维义, 等. 黄芪多糖对祼鼠结直肠癌移植瘤的抑制作用[J].郑州大学学报(医学版),2021,56(3):375-379. |
| 19 | SUNADA S, SAITO H, ZHANG D D, et al. CDK1 inhibitor controls G2/M phase transition and reverses DNA damage sensitivity[J]. Biochem Biophys Res Commun, 2021, 550: 56-61. |
| 20 | KAPANIDOU M, CURTIS N L, BOLANOS-GARCIA V M. Cdc20: At the crossroads between chromosome segregation and mitotic exit[J]. Trends Biochem Sci, 2017, 42(3): 193-205. |
| 21 | MA J L, CHEN C, LIU S, et al. Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis[J]. Cancer Gene Ther, 2022, 29(11): 1578-1589. |
| 22 | GUIDO B C, BRAND?O D C, BARBOSA A L A,et al.Exploratory comparisons between different anti-mitotics in clinically-used drug combination in triple negative breast cancer[J]. Oncotarget, 2021, 12(19):1920-1936. |
| 23 | 刘 蕾, 李席如, 胡蕴慧, 等. TOP2A、EGFR基因表达与三阴性乳腺癌TE方案新辅助化疗疗效的相关性[J]. 中华医学杂志, 2016, 96(12): 940-943. |
| 24 | WEI L M, LI X Y, WANG Z M, et al. Identification of hub genes in triple-negative breast cancer by integrated bioinformatics analysis[J]. Gland Surg, 2021, 10(2): 799-806. |
| 25 | THANKAMONY A P, MURALI R, KARTHIKEYAN N, et al. Targeting the Id1-Kif11 axis in triple-negative breast cancer using combination therapy[J]. Biomolecules, 2020, 10(9): 1295. |
| 26 | NOVITASARI D, JENIE R I, KATO J Y, et al. The integrative bioinformatic analysis deciphers the predicted molecular target gene and pathway from curcumin derivative CCA-1.1 against triple-negative breast cancer (TNBC)[J]. J Egypt Natl Canc Inst, 2021, 33(1): 19. |
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