Identification of Hub Genes and Pathways Associated with Follicular Lymphoma (FL) Via Bioinformatics Analysis

Background: This research aims to identify the hub genes associated with the prognosis of follicular lymphoma (FL), so as to provide new insights for its treatment.

Methods: The follicular lymphoma microarray data GSE32018 was downloaded from the Gene Expression Omnibus (GEO) database for bioinformatic analysis in this study. The differentially expressed genes (DEGs) were screened using the GEO2R online tool. Database for Annotation, Visualization, and Integrated Discovery (DAVID) was applied to assess the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the DEGs. Subsequently, the protein interaction network was constructed through the STRING database, and the CytoHubba plug-in in Cytoscape was used to screen hub genes. The expression and prognosis of the screened hubs were verified using clinical data from dataset GSE119214 (n = 137).

Results: A total of 1886 communal DEGs (559 up-regulated and 1327 down-regulated, adj.p < 0.05) were identified in FL samples compared with control samples. The GO analysis showed that DEGs mainly involved cytosol, cytoplasm, plasma membrane, extracellular exosome, extracellular region, extracellular space in cytology component (CC)； protein binding, structural constituent of ribosome, structural molecule activity, structural constituent of epidermis, serine-type endopeptidase inhibitor activity in molecular function (MF)； signal transduction, positive regulation of transcription from RNA polymerase II promoter, cell adhesion, innate immune response, immune response in biological processes (BP). The results of the KEGG analysis indicated that the DEGs mainly include Ribosome, Hematopoietic cell lineage, Leukocyte transendothelial migration, Staphylococcus aureus infection. The most 10 abundant core genes, UBB, UBA52, RPL35, RPS19, RPS15, RPS28, RPL28, RPL7A, RPL3 and RPL13 were identified via PPI analysis Combined with Cytoscape software cytoHubba plug-in. Survival analysis revealed that UBA52, RPL28 and RPL3 were associated with the survival of patients with follicular lymphoma.

Conclusions: UBA52, RPL28 and RPL3 may become potential therapeutic targets for FL. Furthermore, the most abundant signaling pathway in DEGs was the ribosome related pathways. This research may provide potential prognostic markers for follicular lymphoma.

No relevant conflicts of interest to declare.