Identification of hub genes associated with the pathogenesis of diffuse large B-cell lymphoma subtype one characterized by host response via integrated bioinformatic analyses

SLC27A2 is a potential immune biomarker for hematological tumors and significantly regulates the cell cycle progression of diffuse large B-cell lymphoma

BACKGROUND

Research on the fatty acid metabolism related gene SLC27A2 is currently mainly focused on solid tumors, and its mechanism of action in hematological tumors has not been reported.

METHOD

This study aims to explore the pathological and immune mechanisms of the fatty acid metabolism related gene SLC27A2 in hematological tumors and verify its functional role in hematological tumors through cell experiments to improve treatment decisions and clinical outcomes of hematological tumors.

RESULT

This study identified the fatty acid metabolism related gene SLC27A2 as a common differentially expressed gene between DLBCL and AML. Immune microenvironment analysis showed that SLC27A2 was significantly positively correlated with T cell CD4 + , T cell CD8 + , endothelial cells, macrophages, and NK cells in DLBCL. In AML, there is a significant negative correlation between SLC27A2 and B cells, T cell CD8 + , and macrophages. SLC27A2 participates in the immune process of hematological tumors through T cell CD8 + and macrophages. The GESA results indicate that high expression of SLC27A2 is mainly involved in the fatty acid pathway, immune pathway, and cell cycle pathway of DLBCL. The low expression of SLC27A2 is mainly involved in the immune pathway of AML. Therefore, SLC27A2 is mainly involved in the pathological mechanisms of hematological tumors through immune pathways, and cell experiments have also confirmed that SLC27A2 is involved in the regulation of DLBCL cells.

CONCLUSION

In summary, our research results comprehensively report for the first time the mechanism of action of SLC27A2 in the immune microenvironment of DLBCL and AML, and for the first time verify the cycle and apoptotic effects of the fatty acid related gene SLC27A2 in DLBCL cells through cell experiments. Research can help improve the treatment of AML and DLBCL patients.

Identification of immune-related hub genes contributing to the pathogenesis, diagnosis, and remission of ulcerative colitis by integrated bioinformatic analyses

The inflammatory disease ulcerative colitis (UC) is multifaceted, immune-mediated, chronic, and relapsing, which is considered to be mainly driven by dysregulated mucosal immune response. The remission of the inflammatory response is a marker of mucosal healing, relating to the low risk of hospitalizations, colorectal cancer, and colectomy. In spite of this, it is still unclear what the key immunological mechanism is which contributes to UC. Here, we explored the immune mechanism and related key genes underlying the state of inflammation in UC. Co-expression networks were constructed based on the expression profiles of immune-related genes in GSE179285. Using Weighted Gene Co-expression Network Analysis and Protein-protein interactions analysis, common hub genes were identified in the module of interest. Then, screening of real hub genes, significantly differentially expressing in inflamed UC, was carried out by Differential Expression Genes Analysis of GSE75214, GSE53306, and GSE6731datasets and immunohistochemistry of clinical samples. The diagnosis Capacity of the hub gene was identified by "glm" function in R. The potential key immune-related mechanisms were investigated using functional enrichment analysis and gene set enrichment analysis (GSEA). Bioinformatics tools were used to predict potential upstream transcription factors (TF), including the UCSC genome browser, correlation analyses, and JASPAR browser. The analysis revealed the blue module, consisting of 227 immune-related genes, showed the highest correlation with inflamed UC. And then, forty-three common candidates were distinguished. S100A9 was identified within the key module as a real hub gene with good diagnostic performance. The immune genes in the blue module were markedly enriched in the Cytokine-Cytokine receptor interaction. S100A9 most likely gets involved NOD-like receptor (NLR) signaling pathway. SPI1 showed the strongest likelihood to be the regulator. S100A9 was identified as the real immune-related hub gene for inflamed UC. Both diagnosis and remission may be aided by its high expression in the inflamed UC.

Investigation of the anti-tumor mechanism of tirabrutinib, a highly selective Bruton's tyrosine kinase inhibitor, by phosphoproteomics and transcriptomics

Tirabrutinib is a highly selective Bruton's tyrosine kinase (BTK) inhibitor used to treat hematological malignancies. We analyzed the anti-tumor mechanism of tirabrutinib using phosphoproteomic and transcriptomic methods. It is important to check the drug's selectivity against off-target proteins to understand the anti-tumor mechanism based on the on-target drug effect. Tirabrutinib's selectivity was evaluated by biochemical kinase profiling assays, peripheral blood mononuclear cell stimulation assays, and the BioMAP system. Next, in vitro and in vivo analyses of the anti-tumor mechanisms were conducted in activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL) cells followed by phosphoproteomic and transcriptomic analyses. In vitro kinase assays showed that, compared with ibrutinib, tirabrutinib and other second-generation BTK inhibitors demonstrated a highly selective kinase profile. Data from in vitro cellular systems showed that tirabrutinib selectively affected B-cells. Tirabrutinib inhibited the cell growth of both TMD8 and U-2932 cells in correlation with the inhibition of BTK autophosphorylation. Phosphoproteomic analysis revealed the downregulation of ERK and AKT pathways in TMD8. In the TMD8 subcutaneous xenograft model, tirabrutinib showed a dose-dependent anti-tumor effect. Transcriptomic analysis indicated that IRF4 gene expression signatures had decreased in the tirabrutinib groups. In conclusion, tirabrutinib exerted an anti-tumor effect by regulating multiple BTK downstream signaling proteins, such as NF-κB, AKT, and ERK, in ABC-DLBCL.

Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma

Background

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous malignancy with varied outcomes. However, the fundamental mechanisms remain to be fully defined.

Aim

We aimed to identify core differentially co-expressed hub genes and perturbed pathways relevant to the pathogenesis and prognosis of DLBCL.

Methods

We retrieved the raw gene expression profile and clinical information of GSE12453 from the Gene Expression Omnibus (GEO) database. We used integrated bioinformatics analysis to identify differentially co-expressed genes. The CIBERSORT analysis was also applied to predict tumor-infiltrating immune cells (TIICs) in the GSE12453 dataset. We performed survival and ssGSEA (single-sample Gene Set Enrichment Analysis) (for TIICs) analyses and validated the hub genes using GEPIA2 and an independent GSE31312 dataset.

Results

We identified 46 differentially co-expressed hub genes in the GSE12453 dataset. Gene expression levels and survival analysis found 15 differentially co-expressed core hub genes. The core genes prognostic values and expression levels were further validated in the GEPIA2 database and GSE31312 dataset to be reliable (p < 0.01). The core genes’ main KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichments were Ribosome and Coronavirus disease-COVID-19. High expressions of the 15 core hub genes had prognostic value in DLBCL. The core genes showed significant predictive accuracy in distinguishing DLBCL cases from non-tumor controls, with the area under the curve (AUC) ranging from 0.992 to 1.00. Finally, CIBERSORT analysis on GSE12453 revealed immune cells, including activated memory CD4⁺ T cells and M0, M1, and M2-macrophages as the infiltrates in the DLBCL microenvironment.

Conclusion

Our study found differentially co-expressed core hub genes and relevant pathways involved in ribosome and COVID-19 disease that may be potential targets for prognosis and novel therapeutic intervention in DLBCL.