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长链非编码RNA HAGLROS在胃癌中的生物信息学分析

Bioinformatics analysis of long non-coding RNA HAGLROS in gastric cancer

    摘要
  • 摘要:
    目的 利用生物信息学方法分析长链非编码RNA HAGLROS在胃癌中的意义，对HAGLROS的靶基因及相关生物学过程和通路进行预测，并建立HAGLROS-miRNA-mRNA网络。
    方法 运用UCSC Xena、UALCAN、GEPIA数据库进行基因在胃癌中的差异表达分析; 癌症基因组图谱(TCGA)数据库结合R语言分析HAGLROS的共表达基因; STRING数据库结合Cytoscape软件进行蛋白质互作网络(PPI)分析及关键基因的筛选; miRDB、LncBase、RNAhybrid数据库预测与HAGLROS相互作用的微小RNA (miRNA); miRDB、miRTarBase、TargetScan数据库结合R语言进行miRNA下游靶基因的预测; R语言及WebGestalt、Metascape在线数据库进行基因本体论(GO)和京都基因和基因组百科全书(KEGG)富集分析; 运用R软件对结果进行绘图。
    结果 HAGLROS在胃癌中高表达，与胃癌患者的总生存期相关。HAGLROS在胃癌中的共表达基因有301个，可能与胚胎器官生长发育、神经生长等生物学过程以及Wnt、Notch、干细胞多能性调控等信号通路有关，其关键基因与胚胎生长发育及神经生长密切相关。NES、FGF8、FGF3可能是与HAGLROS联系最为密切的3个基因。HAGLROS-miR-1976-ORAI2轴可能参与调控胃癌发生发展的过程。
    结论 HAGLROS在胃癌中高表达，可能与胚胎生长发育和神经生长生物学过程以及Wnt、Notch、干细胞多能性调控等信号通路有关，其可能是通过调控关键基因NES、FGF8、FGF3以及HAGLROS-miR-1976-ORAI2轴促进胃癌的发生发展，影响胃癌患者的预后。

     

    Abstract:
    Objective To analyze the significance of long non-coding RNA HAGLROS in gastric cancer by using bioinformatics methods, predict the target genes, related biological processes and pathways of HAGLROS, and establish HAGLROS-miRNA-mRNA network.
    Methods UCSC Xena, UALCAN and GEPIA databases were used to analyze the differential expressions of genes in gastric cancer; the co-expression genes of HAGLROS were analyzed by the Cancer Genome Atlas (TCGA) databasein combination with R language; STRING database and Cytoscape software were used to establish protein-protein interaction network (PPI) and screen key genes; microRNA (miRNA) interacting with HAGLROS were predicted by miRDB, LncBase and RNAhybrid databases; miRNA downstream target gene prediction was performed by using miRDB, miRTarBase, TargetScan database and R language; gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were analyzed by R language, WebGestalt and Metascape online databases; results were drew by R software.
    Results HAGLROS was highly expressed in gastric cancer, and was related to the overall survival of patients with gastric cancer. There were 301 co-expressed genes of HAGLROS, which may be related to biological processes such as embryonic and organ growth and nerve growth, and signal pathways such as Wnt, Notch and stem cell pluripotency regulation, and its key genes were closely related to embryonic growth and nerve growth. NES, FGF8 and FGF3 might be the three genes most closely related to HAGLROS. HAGLROS-miR-1976-ORAI2 axis might be involved in regulating the occurrence and development of gastric cancer.
    Conclusion HAGLROS is highly expressed in gastric cancer and may be related to the biological processes of embryonic growth and nerve growth and the signal pathways such as Wnt, Notch and stem cell pluripotency regulation, which may promote the occurrence and development of gastric cancer and affect the prognosis of patients with gastric cancer by regulating the key genes such as NES, FGF8, FGF3 and HAGLROS-miR-1976-ORAI2 axis.

     

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