解剖学报 ›› 2021, Vol. 52 ›› Issue (4): 601-608.doi: 10.16098/j.issn.0529-1356.2021.04.015

• 肿瘤生物学 • 上一篇    下一篇

唾液腺腺样囊性癌中相关微小RNAs及其靶基因的生物信息学分析

刘发煇1,2 侯婉云1,2 梁家东2 徐晶晶1 罗春英1,2*   

  1. 1.右江民族医学院附属医院病理科,广西 百色 533000; 2.右江民族医学院附属医院病理诊断与研究中心,广西 百色 533000
  • 收稿日期:2020-06-17 修回日期:2020-08-03 出版日期:2021-08-06 发布日期:2021-08-06
  • 通讯作者: 罗春英 E-mail:chun2005008@163.com
  • 基金资助:
    2015年度广西高校重点实验室开放课题;广西医疗卫生适宜技术开发与推广应用项目;百色市科技计划课题

Bioinformatics analysis of the microRNAs and target genes of microRNAs in salivary adenoid cystic carcinoma

LIU Fa-hui1,2  HOU Wan-yun1,2  LIANG Jia-dong2  XU Jin-jing1  LUO Chun-ying1, 2*   

  1. 1.Department of Pathology, the Affiliated Hospital of Youjiang Medical University of Nationalities, Guangxi Baise 533000, China; 2. Clinical Pathological Diagnosis and Research Centra, Youjiang Medical University of Nationalities, Guangxi Baise 533000, China
  • Received:2020-06-17 Revised:2020-08-03 Online:2021-08-06 Published:2021-08-06
  • Contact: LUO Chun-ying E-mail:chun2005008@163.com

摘要:

目的  探讨唾液腺腺样囊性癌(SACC)潜在的微小RNAs(miRNAs)分子标志物,构建miRNA-mRNA调控网络,并阐明其潜在的分子机制。   方法  从Gene Expression Omnibus(GEO)数据库下载2个SACC的微阵列芯片数据,通过R语言进行分析差异的miRNAs与mRNA。应用FunRich 3.1.3软件对差异miRNA进行转录因子富集分析以及预测差异miRNAs的靶基因。对SACC中差异miRNAs的靶基因进行基因本体论(GO)富集分析与京都基因与基因组百科全书(KEGG)通路富集分析以及蛋白互作分析。使用Cytoscape 3.7.0构建miRNA-mRNA调控网络。   结果  1. 共筛选出144个差异表达的miRNAs (DEMs)和1216个差异表达的mRNAs(DEGs);2. KEGG信号通路富集分析发现,靶基因主要参与Rap1信号通路、丝裂原活化蛋白激酶(MAPK)信号通路、磷脂酰肌醇-3激酶/蛋白激酶B(PI3K/Akt)信号通路以及肌动蛋白细胞骨架的调节;3. STRING蛋白相互作用分析发现,ACSL1、SCD、MGLL、FABP4在蛋白相互作用网络中处于核心地位。   结论  我们筛选出SACC与相对正常组织间差异明显的miRNA和mRNA,并分析发现了这些差异分子主要参与的信号通路和功能。

关键词: 唾液腺腺样囊性癌, 微小RNA, 生物信息学

Abstract:

Objective  To identify potential microRNAs(miRNAs) in salivary adenoid cystic carcinoma and to construct a miRNA-mRNA regulatory network to better understand its potential molecular mechanisms.    Methods  Two microarray datasets of SACC were downloaded from the database Gene Expression Omnibus(GEO), and the differentially expressed miRNAs and mRNA were analyzed by the R language. FunRich 3.1.3 software was used to enrich and analyze the transcription factors of differential miRNAs and to predict the target genes of differentially expressed miRNAs. The target genes of differential miRNAs in SACC were utilized to perform Gene Onotology(GO) and Kyoto Encyclopedia of Gene Genomes(KEGG) pathway enrichment analyses, and protein-protein interaction. The miRNA-mRNA regulatory network was constructed in Cytoscape 3.7.0.    Results  A total of 144 differentially expressed miRNA (DEMs) and 1216 differentially expressed mRNA (DEGs) were screened. The enrichment analysis of KEGG signaling pathway revealed that target genes were mainly involved in the regulation of Rap1 signaling pathway, mitogen active protein kinase(MAPK) signaling pathway, phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt) signaling pathway, and regulation of actin cytoskeleton. STRING protein interaction analysis shows that ACSL1, SCD, MGLL, FABP4 may be the key proteins in the protein interaction network.    Conclusion  Differentially expressed miRNA and mRNA between SACC tissues and normal tissues were screened out and the signaling pathways and functions of these differential molecules were found in our research.

Key words:  Salivary adenoid cystic carcinoma, MicroRNA, Bioinformatics

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