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

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 cohor...

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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
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cited_by cdi_FETCH-LOGICAL-c499t-f63ff2b16ee106b1259e2443191ab306d138b5f9e52f438bcb0be01e31a4bfee3
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Liu, Tao
Zhu, Fang
Li, Xiaoqian
Meng, Jingshu
Liu, Zijian
Wu, Gang
description 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.
doi_str_mv 10.1155/2018/3574534
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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
title 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
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