Golestanifar Ahmad, Lajmiri Hossein, Saberiyan Mohammadreza
Department of Medical Genetics, Faculty of Medicine, School of Medical Sciences, Hormozgan University of Medical Sciences, P.O. Box 7919693116, Bandar Abbas, Iran.
Department of Medical Microbiology (Bacteriology and Virology), Afzalipour Faculty of Medicine, Kerman University of Medical Sciences, Kerman, Iran.
Clin Exp Med. 2025 May 3;25(1):138. doi: 10.1007/s10238-025-01677-0.
This study aims to dissect the complex molecular landscape of glioblastoma multiforme (GBM), focusing on identifying key regulatory non-coding RNAs and protein-coding genes that could serve as therapeutic targets and prognostic biomarkers. GBM is an aggressive form of brain cancer characterized by poor prognosis and limited treatment options. Recent advances in high-throughput genomic technologies have opened new avenues for understanding the molecular underpinnings of GBM, with a particular focus on the roles of ncRNAs. We utilized multiple datasets from the NCBI Gene Expression Omnibus (GEO) to analyze mRNA, miRNA, lncRNA, and circRNA expression profiles in GBM versus normal brain tissues. Differential expression analysis was conducted using GEO2R, followed by pathway enrichment and protein-protein interaction (PPI) network analyses using DAVID and STRING databases, respectively. Hub genes were identified and validated through GEPIA2, and a competing endogenous RNA (ceRNA) network was constructed to elucidate the interactions between non-coding RNAs (ncRNAs) and protein-coding genes. The study identified several differentially expressed genes and ncRNAs, highlighting complex interactions within the PPI network and significant pathway enrichments implicated in GBM progression. The ceRNA network analysis revealed potential regulatory axes mediated by ncRNAs. Validation of hub genes confirmed their differential expression and prognostic value. Additionally, correlations between gene expression, drug sensitivity, and immune cell infiltration were analyzed, offering insights into personalized therapeutic approaches. Our findings underscore the intricate molecular networks in GBM, emphasizing the role of ncRNAs in tumor biology and their potential as therapeutic targets. The study highlights the necessity for further experimental validation of bioinformatics predictions to bridge the gap between genomic insights and clinical application, ultimately aiming to enhance the prognosis and treatment strategies for GBM patients.
本研究旨在剖析多形性胶质母细胞瘤(GBM)复杂的分子格局,重点识别可作为治疗靶点和预后生物标志物的关键调控非编码RNA和蛋白质编码基因。GBM是一种侵袭性脑癌,其特征是预后不良且治疗选择有限。高通量基因组技术的最新进展为理解GBM的分子基础开辟了新途径,尤其关注非编码RNA的作用。我们利用来自NCBI基因表达综合数据库(GEO)的多个数据集,分析GBM与正常脑组织中的mRNA、miRNA、lncRNA和circRNA表达谱。使用GEO2R进行差异表达分析,随后分别使用DAVID和STRING数据库进行通路富集分析和蛋白质-蛋白质相互作用(PPI)网络分析。通过GEPIA2鉴定并验证了枢纽基因,并构建了竞争性内源性RNA(ceRNA)网络,以阐明非编码RNA(ncRNAs)与蛋白质编码基因之间的相互作用。该研究识别出了几个差异表达的基因和ncRNAs,突出了PPI网络内的复杂相互作用以及与GBM进展相关的显著通路富集。ceRNA网络分析揭示了由ncRNAs介导的潜在调控轴。枢纽基因的验证证实了它们的差异表达和预后价值。此外,还分析了基因表达、药物敏感性和免疫细胞浸润之间的相关性,为个性化治疗方法提供了见解。我们的研究结果强调了GBM中复杂的分子网络,强调了ncRNAs在肿瘤生物学中的作用及其作为治疗靶点的潜力。该研究强调了对生物信息学预测进行进一步实验验证的必要性,以弥合基因组见解与临床应用之间的差距,最终目标是改善GBM患者的预后和治疗策略。