Construction of a circRNA-miRNA-mRNA regulatory network in glioblastoma multiforme based on bioinformatics analysis

基于生物信息学分析构建胶质母细胞瘤中circRNA-miRNA-mRNA调控网络

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Abstract

This study aimed to investigate the functional roles and molecular regulatory mechanisms of circular RNAs in the development of glioblastoma multiforme. Differentially expressed circular RNAs were identified by integrating RNA sequencing data and circular RNA microarray data from the Gene Expression Omnibus database. CircAtlas and CircInteractome databases were used to predict microRNAs (miRNAs) interacting with these circular RNAs. Survival analysis of the miRNAs was performed using data from the Chinese Glioma Genome Atlas. The miRTarBase database was used to predict miRNA target genes, followed by the construction of a circular RNA-miRNA-messenger RNA regulatory network specific to glioblastoma multiforme. Functional enrichment analysis was carried out using the DAVID website, and protein-protein interaction networks were created using the Search Tool for the Retrieval of Interacting Genes/Proteins website and Cytoscape. Hub genes were identified, and their expression and prognostic relevance in glioblastoma multiforme were further examined. Four differentially expressed circRNAs and 10 associated miRNAs related to glioblastoma multiforme prognosis were identified. Functional enrichment showed the miRNAs target genes were mainly involved in apoptosis, cell cycle regulation and enriched in cancer-related pathways like mitogen-activated protein kinase and PI3K-Akt. Through the circRNA-miRNA-messenger RNA regulatory network and survival analysis, 3 core genes (core hub genes: catenin beta 1, BCL2, nuclear factor kappa B subunit 1) were identified as significantly downregulated in glioblastoma multiforme and associated with patient survival. This study highlights the potential regulatory roles of circular RNAs in glioblastoma multiforme pathogenesis and their involvement in key molecular pathways. The findings offer a theoretical foundation for understanding glioblastoma multiforme development and may facilitate the identification of novel biomarkers for this aggressive cancer.

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