[1]谢成仁　康国钧　侯晓峰　王　丹.红花黄色素治疗颅脑损伤作用机制的生物信息学分析[J].中国临床神经外科杂志,2020,(12):841-843.[doi:10.13798/j.issn.1009-153X.2020.12.008]
　XIE Cheng-ren,KANG Guo-jun,HOU Xiao-feng,et al.Analysis of mechanism of safflower yellow in treatment of traumatic brain injury using bioinformatics methods[J].,2020,(12):841-843.[doi:10.13798/j.issn.1009-153X.2020.12.008]
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红花黄色素治疗颅脑损伤作用机制的生物信息学分析()
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《中国临床神经外科杂志》[ISSN:1009-153X/CN:42-1603/TN]

卷:
期数:
2020年12期
页码:
841-843
栏目:
论著
出版日期:
2020-12-25

文章信息/Info

Title:
Analysis of mechanism of safflower yellow in treatment of traumatic brain injury using bioinformatics methods
文章编号:
1009-153X（2020）12-0841-03
作者:
谢成仁　康国钧　侯晓峰　王　丹
733000 甘肃，武威市人民医院神经外科（谢成仁、康国钧、侯晓峰）；745000 甘肃，庆阳市人民医院神经病学（王　丹）
Author(s):
XIE Cheng-ren1;  KANG Guo-jun1;  HOU Xiao-feng1;  WANG Dan1.
1. Department of Neurosurgery, People’s Hospital of Wuwei City, Wuwei 733000, China; 2. department of Neurology, People’s Hospital of Qingyang City, Qingyang 745000, China
关键词:
颅脑损伤; 红花黄色素; 生物信息学; 作用机制
Keywords:
Traumatic brain injury;  Bioinformatics method;  Safflower yellow
分类号:
R 651.1+5
DOI:
10.13798/j.issn.1009-153X.2020.12.008
文献标志码:
A
摘要:
目的 应用生物信息学方法分析红花黄色素（YS）治疗颅脑损伤（TBI）的作用机制。方法 通过GEO数据库查询检索基因表达微阵列芯片数据集GSE21854，筛选差异表达基因（DEGs）， 并与YS靶点基因互相印射取交集。采用DAVID/String数据库对共同靶基因进行GO分析和KEGG通路分析，构建PPI网络。结果 筛选出140个DEGs，与YS靶点基因互相印射后得到26个共同靶基因；进一步GO分析前5个基因功能富集为信号转导、DNA 转录调节、血小板活化、信号与聚集、免疫系统及转录调控区 DNA 结合，KEGG通路途径分析筛选出前5条信号通路包括MAPK信号通路、趋化因子信号通路、PI3K/AKT信号通路、EGFR1信号通路和肿瘤信号通路。PPI分析筛选发现节点最高的中心蛋白编码基因是MAPK3。结论 应用生物信息学方法，可有效获取YS治疗TBI靶向基因的生物学功能、相关信号通路及核心关键蛋白，为后续研究和临床治疗提供了依据。
Abstract:
Objective To explore the mechanism of safflower yellow (YS) in the treatment of traumatic brain injury (TBI) using bioinformatics methods. Methods The GSE21854 microarray data set of gene expression of TBI patients and healthy controls were retrieved through GEO database, and differential expression genes (DEGs) were screened. The core genes and YS target genes were printed into each other to obtain the intersection. GO analysis and KEGG pathway analysis were carried out using DAVID/String database to construct PPI network. Results One hundred and forty DEGs were screened, and 26 common target genes were obtained. GO analysis of the first five gene functions were enriched in signal transduction, DNA transcription regulation, platelet activation, signal and aggregation, immune system and DNA binding in the transcriptional regulatory region. KEGG pathway analysis screened out the first five signal pathways including MAPK signal pathway, trend chemokine signaling pathway, PI3K/AKT signaling pathway, EGFR1 signaling pathway and tumor signaling pathway. PPI analysis and screening found that the highest central protein coding gene of the node was MAPK3. Conclusion The application of bioinformatics methods can effectively obtain the biological functions, related signal pathways and core key proteins of YS-treated TBI targeted genes, providing a basis for further research and clinical treatment.

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备注/Memo

备注/Memo:
基金项目：卫生部医药卫生科技项目（6203262016446）
更新日期/Last Update: 2020-12-25