Suppr超能文献

多组学分析预测纤连蛋白1是多形性胶质母细胞瘤的一种预后生物标志物。

Multi-omics analysis predicts fibronectin 1 as a prognostic biomarker in glioblastoma multiforme.

作者信息

Kabir Farzana, Apu Mohd Nazmul Hasan

机构信息

Department of Clinical Pharmacy and Pharmacology, Faculty of Pharmacy, University of Dhaka, Dhaka 1000, Bangladesh.

Department of Clinical Pharmacy and Pharmacology, Faculty of Pharmacy, University of Dhaka, Dhaka 1000, Bangladesh.

出版信息

Genomics. 2022 May;114(3):110378. doi: 10.1016/j.ygeno.2022.110378. Epub 2022 May 2.

Abstract

Glioblastoma (GBM) is one of the most malignant and intractable central nervous system tumors with high recurrence, low survival rate, and poor prognosis. Despite the advances of aggressive, multimodal treatment, a successful treatment strategy is still elusive, often leading to therapeutic resistance and fatality. Thus, it is imperative to search for and identify novel markers critically associated with GBM pathogenesis to improve the existing trend of diagnosis, prognosis, and treatment. Seven publicly available GEO microarray datasets containing 409 GBM samples were integrated and further data mining was conducted using several bioinformatics tools. A total of 209 differentially expressed genes (DEGs) were identified in the GBM tissue samples compared to the normal brains. Gene Ontology (GO) enrichment analysis of the DEGs revealed association of the upregulates genes with extracellular matrix (ECM), conceivably contributing to the invasive nature of GBM while downregulated DEGs were found to be predominantly related to neuronal processes and structures. Alongside, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway analyses described the involvement of the DEGs with various crucial contributing pathways (PI3K-Akt signaling pathway, p53 signaling pathway, insulin secretion, etc.) in GBM progression and pathogenesis. Protein-protein interaction (PPI) network containing 879 nodes and 1237 edges revealed 3 significant modules and consecutive KEGG pathway analysis of these modules showed a significant connection to gliomagenesis. Later, 10 hub genes were screened out based on degree and their expressions were externally validated. Surprisingly, only fibronectin 1 (FN1) high expression appeared to be related to poor prognosis. Subsequently, 109 transcription factors and 211 miRNAs were detected to be involved with the hub genes where FN1 demonstrated the highest number of interactions. Considering its high connectivity and potential prognostic value FN1 could be a novel biomarker providing new insights into the prognosis and treatment for GBM, although experimental validation is required.

摘要

胶质母细胞瘤(GBM)是最恶性且最难治疗的中枢神经系统肿瘤之一,具有高复发率、低生存率和不良预后。尽管积极的多模式治疗取得了进展,但成功的治疗策略仍然难以捉摸,常常导致治疗抵抗和死亡。因此,寻找和鉴定与GBM发病机制密切相关的新标志物以改善现有的诊断、预后和治疗趋势势在必行。整合了七个包含409个GBM样本的公开可用GEO微阵列数据集,并使用多种生物信息学工具进行了进一步的数据挖掘。与正常脑组织相比,在GBM组织样本中总共鉴定出209个差异表达基因(DEG)。对DEG进行基因本体(GO)富集分析发现,上调基因与细胞外基质(ECM)相关,这可能导致GBM的侵袭性,而下调的DEG主要与神经元过程和结构有关。同时,京都基因与基因组百科全书(KEGG)和Reactome通路分析描述了DEG参与GBM进展和发病机制中的各种关键促成通路(PI3K-Akt信号通路、p53信号通路、胰岛素分泌等)。包含879个节点和1237条边的蛋白质-蛋白质相互作用(PPI)网络揭示了3个重要模块,对这些模块进行连续的KEGG通路分析显示与胶质瘤发生有显著联系。随后,根据度数筛选出10个枢纽基因,并对其表达进行了外部验证。令人惊讶的是,只有纤连蛋白1(FN1)高表达似乎与不良预后相关。随后,检测到109个转录因子和211个miRNA与枢纽基因有关,其中FN1的相互作用数量最多。考虑到其高连接性和潜在的预后价值,尽管需要实验验证,但FN1可能是一种新的生物标志物,为GBM的预后和治疗提供新的见解。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验