研究动态
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基于网络药理学和生物信息学分析,在探索金鸡菊属植物高山玉儿治疗食管鳞状细胞癌的中心基因和机制方面。

Exploring the hub genes and mechanisms of Daphne altaica treating esophageal squamous cell carcinoma based on network pharmacology and bioinformatics analysis.

发表日期:2023 Apr 23
作者: Sendaer Hailati, Ziruo Talihati, Kayisaier Abudurousuli, Meng Yuan Han, Muhadaisi Nuer, Nawaz Khan, Nulibiya Maihemuti, Jimilihan Simayi, Dilihuma Dilimulati, Nuerbiye Nueraihemaiti, Wenting Zhou
来源: MOLECULAR & CELLULAR PROTEOMICS

摘要:

食管鳞状细胞癌(ESCC)是一种常见的消化道恶性肿瘤,病死率高。黑果花(Daphne altaica,D. altaica)是一种被广泛应用于哈萨克传统医学中的药用植物,传统上用于治疗癌症和呼吸疾病,但缺乏有关机制的研究。因此,我们研究并验证了黑果花治疗ESCC的关键基因和机制。通过TCMSP等数据库筛选了D. altaica的活性化合物和靶点,通过GeneCards等数据库筛选了ESCC的靶点,并构建了化合物-靶点网络和PPI网络。同时,利用R的limma程序包分析GEO数据库(GSE100942,GPL570)中组织和相邻非癌组织的数据集,获得差异表达基因(DEGs)。使用Kaplan-Meier绘图数据库、TIMER2.0和GEPIA2数据库验证了关键基因。最后,使用AutoDock软件通过分子对接预测结合位点。共获得了830个化合物靶点和17,710个疾病靶点。通过化合物-靶点网络和PPI网络得出了127个DEGs(82个上调基因和45个下调基因),筛选出了TOP2A、NUF2、CDKN2A、BCHE和NEK2等关键基因,并在多个公共数据库的帮助下进行了验证。最后,分子对接结果显示出五个关键基因和活性化合物之间的结合更加稳定。本研究筛选和验证了五个关键基因,并预测了潜在的作用机制,这有助于理论上了解使用D. altaica治疗ESCC的方法。© 2023作者,独家授权Springer-Verlag GmbH Germany,Springer Nature的一部分。
Esophageal squamous cell carcinoma (ESCC), is a frequent digestive tract malignant carcinoma with a high fatality rate. Daphne altaica (D. altaica), a medicinal plant that is frequently employed in Kazakh traditional medicine, and which has traditionally been used to cure cancer and respiratory conditions, but research on the mechanism is lacking. Therefore, we examined and verified the hub genes and mechanism of D. altaica treating ESCC.Active compounds and targets of D. altaica were screened by databases such as TCMSP, and ESCC targets were screened by databases such as GeneCards and constructed the compound-target network and PPI network. Meantime, data sets between tissues and adjacent non-cancerous tissues from GEO database (GSE100942, GPL570) were analyzed to obtain DEGs using the limma package in R. Hub genes were validated using data from the Kaplan-Meier plotter database, TIMER2.0 and GEPIA2 databases. Finally, AutoDock software was used to predict the binding sites through molecular docking.In total, 830 compound targets were obtained from TCMSP and other databases. In addition, 17,710 disease targets were acquired based on GeneCards and other databases. In addition, we constructed the compound-target network and PPI network. Then, 127 DEGs were observed (82 up-regulated and 45 down-regulated genes). Hub genes were screened including TOP2A, NUF2, CDKN2A, BCHE, and NEK2, and had been validated with the help of several publicly available databases. Finally, molecular docking results showed more stable binding between five hub genes and active compounds.In the present study, five hub genes were screened and validated, and potential mechanisms of action were predicted, which could provide a theoretical understanding of the treatment of ESCC with D. altaica.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.