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

• Published in: BioMed research international 2018-01, Vol.2018 (2018), p.1-14
• Main Authors: Zhang, Liling, Liu, Tao, Zhu, Fang, Li, Xiaoqian, Meng, Jingshu, Liu, Zijian, Wu, Gang
• Format: Article
• Language: English
• Subjects: B cells; B-cell lymphoma; Bioinformatics; Biomarkers; Cancer; CD44 antigen; Computational Biology; Datasets; Forkhead protein; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Gene set enrichment analysis; Genes; Genes, Neoplasm; Genetic aspects; Humans; Identification; Interferon regulatory factor 4; Interleukin 2 receptors; Leukemia; Lymphocytes B; Lymphoma; Lymphoma, Large B-Cell, Diffuse - genetics; Medical research; Microarray Analysis; Molecular chains; NF-κB protein; Non-Hodgkin's lymphomas; Prognosis; Protein interaction; Protein-protein interactions; Proteins; Software; Stat3 protein; Therapeutic applications; Tumorigenesis
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2018/3574534

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-κB 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.