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基于基因表达谱的整合生物信息学方法鉴定两种弥漫性大 B 细胞淋巴瘤亚型的枢纽基因和关键通路。

Identification of Hub Genes and Key Pathways Associated with Two Subtypes of Diffuse Large B-Cell Lymphoma Based on Gene Expression Profiling via Integrated Bioinformatics.

机构信息

Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

Biomed Res Int. 2018 May 24;2018:3574534. doi: 10.1155/2018/3574534. eCollection 2018.

Abstract

There is a significant difference in prognosis between the germinal center B-cell (GCB) and activated B-cell (ABC) subtypes of diffuse large B-cell lymphoma (DLBCL). However, the signaling pathways and driver genes involved in these disparate subtypes are ambiguous. This study integrated three cohort profile datasets, including 250 GCB samples and 250 ABC samples, to elucidate potential candidate hub genes and key pathways involved in these two subtypes. Differentially expressed genes (DEGs) were identified. After Gene Ontology functional enrichment analysis of the DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted using the STRING database and Cytoscape software. Subsequently, the Oncomine database and the cBioportal online tool were employed to verify the alterations and differential expression of the 8 hub genes (MME, CD44, IRF4, STAT3, IL2RA, ETV6, CCND2, and CFLAR). Gene set enrichment analysis was also employed to identify the intersection of the key pathways (JAK-STAT, FOXO, and NF-B pathways) validated in the above analyses. These hub genes and key pathways could improve our understanding of the process of tumorigenesis and the underlying molecular events and may be therapeutic targets for the precise treatment of these two subtypes with different prognoses.

摘要

生发中心 B 细胞(GCB)和活化 B 细胞(ABC)弥漫性大 B 细胞淋巴瘤(DLBCL)亚型之间的预后存在显著差异。然而,涉及这些不同亚型的信号通路和驱动基因尚不清楚。本研究整合了三个队列资料集,包括 250 个 GCB 样本和 250 个 ABC 样本,以阐明这两种亚型中涉及的潜在候选枢纽基因和关键途径。鉴定出差异表达基因(DEGs)。对 DEGs 进行基因本体论功能富集分析后,使用 STRING 数据库和 Cytoscape 软件进行蛋白质-蛋白质相互作用(PPI)网络和子 PPI 网络分析。随后,使用 Oncomine 数据库和 cBioportal 在线工具验证 8 个枢纽基因(MME、CD44、IRF4、STAT3、IL2RA、ETV6、CCND2 和 CFLAR)的改变和差异表达。还进行了基因集富集分析,以确定上述分析中验证的关键途径(JAK-STAT、FOXO 和 NF-B 途径)的交集。这些枢纽基因和关键途径可以帮助我们了解肿瘤发生过程以及潜在的分子事件,并可能成为针对这两种具有不同预后亚型的精准治疗的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9293/5994323/e56fd511d01d/BMRI2018-3574534.001.jpg

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