Bioinformatics analysis reveals the potential common genes and immune characteristics between atrial fibrillation and periodontitis

BACKGROUND AND OBJECTIVE

Atrial fibrillation (AF) and periodontitis, both classified under chronic inflammatory diseases, share common etiologies, including genetic factors and immune pathways. However, the exact mechanisms are still poorly understood. This study aimed to explore the potential common genes and immune characteristics between AF and periodontitis.

METHODS

Gene expression datasets for AF and periodontitis were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis was used to identify common genes in the training set. Functional analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, were conducted to elucidate the underlying mechanisms. Hub genes were further screened based on expression levels, receiver operating characteristic (ROC) curves, and least absolute shrinkage and selection operator (LASSO) regression. Then, based on the expression levels and ROC values of the hub genes in the validation set, the target genes were identified. Finally, immune cell infiltration analysis was performed on the AF and periodontitis datasets in the training set using the "CIBERSORT" R package. The relationships between target genes, infiltrating immune cells, and inflammatory factors were also investigated. In addition, AF susceptibility, atrial fibrosis, inflammatory infiltration, and RGS1 protein expression in rat models of periodontitis were assessed through in vivo electrophysiology experiments, Masson's trichrome staining, hematoxylin-eosin staining, immunohistochemistry, and western blotting, respectively.

RESULTS

A total of 21 common genes were identified between AF and periodontitis among the differentially expressed genes. After evaluating gene expression levels, ROC curves, and LASSO analysis, four significant genes between AF and periodontitis were identified, namely regulator of G-protein signaling 1 (RGS1), annexin A6 (ANXA6), solute carrier family 27 member 6 (SLC27A6), and ficolin 1 (FCN1). Further validation confirmed that RGS1 was the optimal shared target gene for AF and periodontitis. Immune cell infiltration analysis revealed that neutrophils and T cells play an important role in the pathogenesis of both diseases. RGS1 showed a significant positive correlation with activated memory CD4 T cells and gamma-delta T cells and a negative correlation with CD8 T cells and regulatory T cells in both training sets. Moreover, RGS1 was positively correlated with classical pro-inflammatory cytokines IL1β and IL6. In periodontitis rat models, AF susceptibility, atrial fibrosis, and inflammatory infiltration were significantly increased, and RGS1 expression in the atrial tissue was upregulated.

CONCLUSION

A common gene between AF and periodontitis, RGS1 appears central in linking the two conditions. Immune and inflammatory responses may underlie the interaction between AF and periodontitis.

Heme Metabolism-Related Gene TENT5C is a Prognostic Marker and Investigating Its Immunological Role in Colon Cancer

Background

There is a strong correlation between consuming high amounts of heme and an elevated risk of developing various types of cancer, including colorectal cancer. However, the role of heme metabolism-related genes (HRGs) in colorectal cancer remains unclear. Our study aimed to identify prognostic markers for colorectal cancer patients based on these genes.

Methods

The heme metabolism score was assessed using gene set variation analysis (GSVA). Potential prognostic HRGs were identified from the TCGA-COAD dataset using LASSO and COX regression analyses. The expression level of TENT5C was validated in the GEO database and clinical samples. To explore the association between TENT5C expression and immune cell infiltrations, we performed ESTIMATE and single-sample gene set enrichment analysis (ssGSEA).

Results

The low level of heme metabolism score was associated with a poor prognosis in colorectal cancer patients. TENT5C is a prognostic gene and an independent prognostic biomarker for overall survival. Its expression was confirmed in multiple datasets and clinical samples, showing a positive correlation with immune cells and immune score. GSEA results suggested TENT5C's significant role in regulating immune and inflammatory responses in colorectal cancer.

Conclusion

TENT5C can be used as a biomarker in colorectal cancer. Additionally, TENT5C is associated with both prognosis and immune infiltration. These findings lay a strong groundwork for future research to delve into the specific role of TENT5C in the development and advancement of colorectal cancer.

Decapping enzyme 2 is a novel immune-related biomarker that predicts poor prognosis in glioma

This study analyzed sequencing and clinical data from the Cancer Genome Atlas (TCGA) and gene expression synthesis, and used Chinese glioma Genome Atlas (CGGA) data for external validation. The expression of DCP2 in normal brain and tumor tissue was compared. We analyzed the clinical and molecular characteristics and prognostic value of DCP2 in glioma. In addition, DCP2 expression levels were evaluated in 30 glioma tissue samples and upregulated in glioma samples compared to normal brain tissue (p < 0.001). Multivariate data analysis from TCGA showed that increased DCP2 expression was an independent risk factor for overall survival and prognosis of glioma patients. As indicated by the analysis of the TCGA data set. The expression level of DCP2 is closely related to tumor immunity, including tumor immune cell infiltration, immune score, and co-expression of multiple immune-related genes. In addition, DCP2 was positively correlated with IL-6 and IL-7. Glioma cell proliferation and invasion were evaluated using cell viability, colony formation, wound healing, and transwell assays.Apoptosis and cell cycle were detected by flow cytometry. DCP2 promoted the proliferation, invasion and migration of glioma cells T98G and U251, inhibited apoptosis and blocked the S phase of the cell cycle. As a result of the altered expression of DCP2, a new prognostic biomarker may be identified that can improve patient survival.These findings suggest DCP2 as a potential biomarker for the prognosis of glioma and a candidate immunotherapy target.

WGCNA-based identification of potential targets and pathways in response to treatment in locally advanced breast cancer patients

Locally advanced breast cancer patients have a poor prognosis; however, the relationship between potential targets and the response to treatment is still unclear. The gene expression profiles of breast cancer patients with stages from IIB to IIIC were downloaded from The Cancer Genome Atlas. We applied weighted gene co-expression network analysis and differentially expressed gene analysis to identify the primary genes involved in treatment response. The disease-free survival between low- and high-expression groups was analyzed using Kaplan-Meier analysis. Gene set enrichment analysis was applied to identify hub genes-related pathways. Additionally, the CIBERSORT algorithm was employed to evaluate the correlation between the hub gene expression and immune cell types. A total of 16 genes were identified to be related to radiotherapy response, and low expression of SVOPL, EDAR, GSTA1, and ABCA13 was associated with poor overall survival and progression-free survival in breast cancer cases. Correlation analysis revealed that the four genes negatively related to some specific immune cell types. The four genes were downregulated in H group compared with the L group. Four hub genes associated with the immune cell infiltration of breast cancer were identified; these genes might be used as a promising biomarker to test the treatment in breast cancer patients.