Integrative analysis of hub genes and key pathway in two subtypes of diffuse large B-cell lymphoma by bioinformatics and basic experiments

Integrated Approach for Biomarker Discovery and Mechanistic Insights into the Co-Pathogenesis of Type 2 Diabetes Mellitus and Non-Hodgkin Lymphoma

Background

Type 2 diabetes mellitus (T2DM) is associated with an increased risk of non-Hodgkin lymphoma (NHL), but the underlying mechanisms remain unclear. This study aimed to identify potential biomarkers and elucidate the molecular mechanisms underlying the co-pathogenesis of T2DM and NHL.

Methods

Microarray datasets of T2DM and NHL were downloaded from the Gene Expression Omnibus database. Subsequently, a protein-protein interaction network was constructed based on the common differentially expressed genes (DEGs) between T2DM and NHL to explore regulatory interactions. Functional analyses were performed to explore underlying mechanisms. Topological analysis and machine learning algorithms were applied to refine hub gene selection. Finally, quantitative real-time polymerase chain reaction was performed to validate hub genes in clinical samples.

Results

Intersection analysis of DEGs from the T2DM and NHL datasets identified 81 shared genes. Functional analyses suggested that immune-related pathways played a significant role in the co-pathogenesis of T2DM and NHL. Topological analysis and machine learning identified three hub genes: GZMM, HSPG2, and SERPING1. Correlation analysis revealed significant correlations between these hub genes and immune cells, underscoring the importance of immune dysregulation in shared pathogenesis. The expression of these genes was successfully validated in clinical samples.

Conclusion

This study suggested the pivotal role of immune dysregulation in the co-pathogenesis of T2DM and NHL and identified and validated three hub genes as key contributors. These findings provide insight into the complex interplay between T2DM and NHL.

Identification and Functional Investigation of Hub Genes Associated with Follicular Lymphoma

Follicular lymphoma (FL), the most common type of indolent lymphoma, originates from germinal center B cells within the lymphoid follicle. However, the underlying mechanisms of this disease remain unclear. This study aimed to identify the potential hub genes for FL and evaluate their functional roles in clinical applications. Microarray data and clinical characteristics of patients with FL were obtained from the Gene Expression Omnibus database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to explore hub genes for FL. Functional enrichment analysis was performed to investigate the potential roles of these hub genes in FL. Mendelian randomization (MR) analysis was performed to verify the causal effect of the top genes on FL risk. In addition, gene set enrichment analysis (GSEA) and immune cell analysis were performed to elucidate the involved mechanisms of the crucial genes in FL. A total of 1363 differentially expressed genes and 157 central genes were identified by differential expression analysis and WGCNA, respectively, resulting in 117 overlapping genes considered as hub genes for FL. Functional enrichment analysis revealed significant correlations between immune-related pathways and FL. MR analysis revealed a significant association only between zeta chain of T-cell receptor-associated protein kinase 70 (ZAP70) and FL risk, with no significance observed for the other top genes. GSEA and immune cell analysis suggested that ZAP70 may be involved in the development and progression of FL through immune-related pathways. By integrating bioinformatics and MR analyses, ZAP70 was successfully identified and validated as a promising FL biomarker. Functional investigations indicated a significant correlation between immune-related pathways and FL. These findings have important implications for the identification of targets for the diagnosis and treatment of FL and provide valuable insights into the molecular mechanisms underlying FL.

Identification of Potential Therapeutic Targets for Plasmablastic Lymphoma Through Gene Expression Analysis: Insights into RAS and Wnt Signaling Pathways

Plasmablastic lymphoma (PBL) is a rare and aggressive B-cell lymphoma with overlapping characteristics with diffuse large B-cell lymphoma (DLBCL) and multiple myeloma. Hyperactive Wnt signaling derails homeostasis and promotes oncogenesis and chemoresistance in DLBCL and multiple myeloma. Evidence suggests active cross-talk between the Wnt and RAS pathways impacting metastasis in solid cancers in which combined targeted therapies show effective results. Recent genomic studies in PBL demonstrated a high frequency of mutations linked with the RAS signaling pathway. However, the role of RAS and Wnt signaling pathway molecule expression in PBL remained unknown. We examined the expression of Wnt and RAS pathway-related genes in a well-curated cohort of PBL. Because activated B cells are considered immediate precursors of plasmablasts in B cell development, we compared this data with activated B-cell type DLBCL (ABC-DLBCL) patients, employing NanoString transcriptome analysis (770 genes). Hierarchical clustering revealed distinctive differential gene expression between PBL and ABC-DLBCL. Gene set enrichment analysis labeled the RAS signaling pathway as the most enriched (37 genes) in PBL, including upregulating critical genes, such as NRAS, RAF1, SHC1, and SOS1. Wnt pathway genes were also enriched (n = 22) by gene set enrichment analysis. Molecules linked with Wnt signaling activation, such as ligands or targets (FZD3, FZD7, c-MYC, WNT5A, WNT5B, and WNT10B), were elevated in PBL. Our data also showed that, unlike ABC-DLBCL, the deranged Wnt signaling activity in PBL was not linked with hyperactive nuclear factor κB and B-cell receptor signaling. In divergence, Wnt signaling inhibitors (CXXC4, SFRP2, and DKK1) also showed overexpression in PBL. The high expression of RAS signaling molecules reported may indicate linkage with gain-in-function RAS mutations. In addition, high expression of Wnt and RAS signaling molecules may pave pathways to explore benefiting from combined targeted therapies, as reported in solid cancer, to improve prognosis in PBL patients.

Palbociclib enhances the effect of doxorubicin-induced apoptosis in activated B-cell-like diffuse large B-cell lymphoma cells

Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma around the world. While R-CHOP has significantly improved patient outcomes, a subset of patients still has poor outcome. Here, the oncogenic roles of cyclin dependent kinase 4/6 (CDK4/6)-Cyclin D (CCND) signaling axis in DLBCL and its potential mechanism were investigated to explore the possibility of targeting CDK4/6-CCND signaling axis for DLBCL therapy. The transcription levels, functional enrichment analysis, mutation analysis, and prognostic values were performed via the Oncomine, GEPIA, UALCAN, cBioPortal, and Metascape and GenomicScape databases. Expression of CDK4/6-CCND signaling axis in DLBCL patients and DLBCL cell lines was evaluated by qRT-PCR. Additionally, the impact of CDK4/6-CCND signaling axis on cell viability and apoptosis in DLBCL cell lines were evaluated in vitro . The transcription levels of CDK4/6-CCND signaling were increased in DLBCL patients. Meanwhile, in Gene Expression Omnibus dataset, the expression of CDK4 and CCND2 was higher in ABC-DLBCL, whereas the expression of CCND1 and CCND3 was higher in GCB-DLBCL. Moreover, according to the results of qRT-PCR, the expression of CDK4/6-CCND signaling axis in ABC-DLBCL cell line is higher than that in GCB-DLBCL cell lines. Prognostic analysis indicated that upregulation of CDK4, CCND2, and CCND3 was significantly associated with poor survival. Cell function experiments showed that palbociclib could enhance the apoptosis-promoting and cell viability-inhibiting effects of doxorubicin on ABC-DLBCL (SU-DHL-2) cells. Doxorubicin accumulation experiment showed that palbociclib promoted doxorubicin accumulation in ABC-DLBCL cells. Additionally, Western blot analysis demonstrated that palbociclib prevented antiapoptotic protein BCL2 expression in ABC-DLBCL cell line. Our study provides novel insights into targeted therapies for ABC-DLBCL patients.

Bioinformatics Analysis of miRNAs Targeting TRAF5 in DLBCL Involving in NF-κB Signaling Pathway and Affecting the Apoptosis and Signal Transduction

Background

Diffuse large B-cell lymphoma (DLBCL) is an aggressive B-cell lymphoma with high heterogeneity. There is an unmet need to investigate valid indicators for the diagnosis and therapy of DLBCL.

Methods

GEO database was utilized to screen for differentially expressed genes (DEGs) and differential miRNAs in DLBCL tissues. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were applied to analyse DEGs. Then multiple databases were searched for related miRNAs within DLBCL, TNF receptor-associated factor 5 (TRAF5) and NF-kappa B (NF-κB) signaling pathways. The KOBAS database was used to assist in the screening of miRNAs of interest and construct the regulatory network of miRNA-mRNA. Finally, the expression level and diagnostic performance of miRNAs were analyzed with GEO datasets, and DEGs were identified from the GEPIA database.

Results

DEGs were significantly concentrated in the NF-κB signaling pathway and cytokine-cytokine receptor interaction, and involved in the process of immune response and protein binding. MiR-15a-5p, miR-147a, miR-192-5p, miR-197-3p, miR-532-5p, and miR-650 were revealed to be targeting TRAF5 and participating in NF-κB signaling pathway and might impact the apoptosis and signal transduction of DLBCL. In the GEPIA database, TRAF5 was significantly overexpressed in DLBCL. The expression of miR-197-3p was upregulated within GEO datasets, while the rest of the miRNAs were downregulated in DLBCL.

Conclusions

Subsets of miRNAs may participate in the NF-κB signaling pathway by co-targeting TRAF5 and could be prospective biomarkers exploring the pathogenesis of DLBCL.