大理大学学报 ›› 2023, Vol. 8 ›› Issue (2): 24-30.

• 基础医学 • 上一篇    下一篇

基于生物信息学分析筛选胰腺癌差异表达基因

李威倩1,陈奕明2,张文婷1,苏莹珍3,帅红艳1Yu Xin1*   

  1. 1.大理大学基础医学院,云南大理 6710002.大理大学临床医学院,云南大理 671000

    3.昆明学院医学院,昆明 650214

  • 收稿日期:2022-04-29 修回日期:2022-06-21 出版日期:2023-02-15 发布日期:2023-03-02
  • 通讯作者: Yu Xin,教授,博士,E-mail:dalahu.cool@qq.com。
  • 作者简介:李威倩,硕士研究生,主要从事胰腺疾病、糖尿病及其并发症研究。
  • 基金资助:
    云南省地方本科高校基础研究联合专项资金项目(202101BA070001-112202001BA070001-191);云南省基础研究计划项目(202101AT070017);云南省教育厅科学研究基金项目(2022Y813

Bioinformatics-ased Analysis and Screening of Differentially Expressed Genes in Pancreatic Cancer

Li Weiqian1 Chen Yiming2 Zhang Wenting1Su Yingzhen3 Shuai Hongyan1 Yu Xin1*   

  1. 1. Pre-clinical College Dali UniversityDali Yunnan 671000China 2. Clinical CollegeDali University Dali Yunnan 671000China3.Medical College of Kunming UniversityKunming 650214China

  • Received:2022-04-29 Revised:2022-06-21 Online:2023-02-15 Published:2023-03-02

摘要: 目的:利用生物信息学对GEO数据库信息进行分析,探索胰腺癌发生、发展的关键基因及信号通路。方法:下载胰腺癌基因表达谱芯片GSE107610,利用R语言对差异表达基因进行统计分析,研究相关生物学过程、信号通路和蛋白质相互作用关系;利用Cytoscape软件构建蛋白质-蛋白质相互作用网络图,利用苏木精-伊红染色验证样本差异性,实时荧光定量聚合酶链反应对筛选出的4个核心基因进行验证。结果:71个差异基因中上调基因17个,下调基因54个。这些基因主要参与蛋白质水解、酒精代谢、外源性代谢、消化、免疫系统的调节等过程。核心基因在mRNA水平的表达和GEO数据库分析结果一致。结论:利用生物信息学技术成功挖掘到与胰腺癌发生、发展相关的差异表达基因,经验证上述差异基因在人胰腺癌组织中的表达水平变化一致,为确定胰腺癌的早期诊断标志物与治疗靶点提供了新的思路。

关键词: font-family:Times New Roman, ">胰腺癌, 生物信息学, font-family:Times New Roman, ">GEOfont-family:Times New Roman, ">数据库, 差异表达基因

Abstract:  ObjectiveTo analyze the information of GEO database by bioinformatics and explore the key genes and signal pathways of pancreatic cancer. MethodsThe gene expression profile chip GSE107610 of pancreatic cancer was downloaded and the differentially expressed genes were statistically analyzed by R software so as to study the related biological processes signal pathways and protein-protein interaction. The protein-protein interaction network diagram was constructed by Cytoscape software the differences of samples were verified by hematoxylin and eosin staining and the four core genes screened out were verified by real-time fluorescence quantitative polymerase chain reaction. ResultsAmong 71 differentially expressed genes 17 were up-regulated and 54 were down-regulated. The functions of these genes were predominantly involved in protein hydrolysis alcohol metabolism exogenous metabolism digestion immune response regulation and other processes. The results of the GEO database analysis were consistent with the expression of key genes at the mRNA levels. ConclusionUsing bioinformatics technology the differentially expressed genes related to the occurrence and development of pancreatic cancer have been successfully discovered. It has been verified that the expression levels of the above differentially expressed genes are consistent in human pancreatic cancer tissues. This study provides a new idea for determining early diagnostic markers and therapeutic targets of pancreatic cancer.

Key words: font-family:Times New Roman, ">pancreatic cancerfont-family:Times New Roman, ">, font-family:Times New Roman, "> bioinformaticsfont-family:Times New Roman, ">, font-family:Times New Roman, "> GEO databasefont-family:Times New Roman, ">, font-family:Times New Roman, "> differentially expressed genes

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