The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease

Circulating Biomarkers and Risk of Hypertension: A Two-Sample Mendelian Randomisation Study

OBJECTIVE

This study systematically assessed circulating proteins to identify new serum biomarkers and risk of hypertension using Mendelian randomisation.

METHODS

The associations between 4,782 human circulating proteins and the risk of hypertension were evaluated using two-sample Mendelian randomisation. The FinnGen study demonstrated a link between genetic predisposition and hypertension in 85,438 cases and 223,663 controls.

RESULTS

Inverse variance weighted and sensitivity analysis revealed nine proteins in circulation that have a causative effect on hypertension. SMOC1 and TIE1 were determined to be causative factors in the decreased likelihood of developing hypertension, with odds ratios of 0.86 (95% CI 0.81-0.91; p=1.06e-06) and 0.96 (95% CI 0.94-0.98; p=9.39e-05), respectively. NDUFB4, ETHE1, POFUT2, TRIL, ADAM23, GXYLT1, OXT, TPST2, and TMCC3 showed a possible connection to hypertension.

CONCLUSIONS

This two-sample Mendelian randomisation study found that SMOC1 and TIE1 are causally linked to hypertension, making them a promising target for therapy.

Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes

Background

One of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors.

Methods

The AML-related data were collected from The Cancer Genome Atlas (TCGA; TCGA-AML) database and Gene Expression Omnibus (GEO; GSE9476, GSE71014, and GSE13159) database. The "limma" R package and Venn diagram were adopted to identify differentially expressed ERGs (DE-ERGs). The m6A related-DE-ERGs were obtained by Spearman analysis. Subsequently, univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) were used to construct an m6A related-ERGs risk signature for AML patients. The possibility of immunotherapy for AML was explored. The pRRophetic package was adopted to calculate the IC50 of drugs for the treatment of AML. Finally, the expression of characterized genes was validated by quantitative reverse transcription-PCR (qRT-PCR).

Results

Based on m6A related-DE-ERGs, a prognostic model with four characteristic genes (UCP2, DOCK1, SLC14A1, and SLC25A1) was constructed. The risk score of model was significantly associated with the immune microenvironment of AML, with four immune cell types, 14 immune checkpoints, 20 HLA family genes and, immunophenoscore (IPS) all showing differences between the high- and low-risk groups. A total of 56 drugs were predicted to differ between the two groups, of which Erlotinib, Dasatinib, BI.2536, and bortezomib have been reported to be associated with AML treatment. The qRT-PCR results showed that the expression trends of DOCK1, SLC14A1 and SLC25A1 were consistent with the bioinformatics analysis.

Conclusion

In summary, 4 m6A related- ERGs were identified and the corresponding prognostic model was constructed for AML patients. This prognostic model effectively stratified the risk of AML patients.

TMEM184B promotes proliferation, migration and invasion, and inhibits apoptosis in hypopharyngeal squamous cell carcinoma

Several members of the transmembrane protein family are associated with the biological processes of human malignancies; however, the expression pattern and biological function of one family member, TMEM184B, in hypopharyngeal squamous cell carcinoma (HPSCC) are not fully understood. The expression between HPSCC tumours and adjacent normal tissues was determined by the Immunohistochemistry (IHC). A bioinformatics analysis was performed to verify the expression pattern of TMEM184B in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Furthermore, in vitro assays on cell proliferation, invasion, migration and in vivo experiments on tumour growth and apoptosis of TMEM184B in HPSCC were performed. We found that the HPSCC tissues had a significantly higher expression of TMEM184B than the adjacent normal tissues. Bioinformatics analysis confirmed the different expression of TMEM184B expression in HPSCC. Furthermore, in vitro and in vivo experiments demonstrated that TMEM184B promotes HPSCC cell growth, cell invasion and migration in FaDu cells, whereas flow cytometry assay showed that TMEM184B inhibited cell apoptosis. Our study revealed for the first time that TMEM184B might serve an oncogenic function in HPSCC and could be a potential diagnostic biomarker and therapeutic target for HPSCC.

Identification of Biomarkers Associated With CD8+ T Cells in Coronary Artery Disease and Their Pan-Cancer Analysis

Purpose

To identify biomarkers associated with CD8+ T cells in coronary artery disease (CAD) and initially explore their potential role in the tumor immune microenvironment.

Materials and Methods

CAD-related datasets GSE12288, GSE34198, and GSE66360, were downloaded from the GEO database. First, GSVA was performed based on the GSE12288 dataset. Then WGCNA analysis was performed to identify the most relevant module and candidate hub gene for CD8+ T cells, followed by GO and KEGG analysis of this module. Secondly, the relationship between candidate hub genes and CD8+ T cells was verified using GSE34198 and GSE66360, which led to the identification of hub genes. The relationship of hub genes with CD8+ T cells in cancer was analyzed using the TIMER database. Methylation analysis of hub genes was performed using the DiseaseMeth database. CAD, pan-cancer, pan-cell lines, and pan-normal tissues, correlations between hub genes. In addition, potential drugs and TFs associated with hub genes were predicted, and the ceRNA network was constructed. Finally, GSEA was performed separately for hub genes.

Results

CAD was shown to be associated with immune response by GSVA analysis. WGCNA identified the blue module as most related to CD8+ T cells and identified nine candidate hub genes. The relevance of CAD to immunity was further confirmed by GO and KEGG analysis of the module. Two additional datasets validated and identified three hub genes (FBXO7, RAD23A, and MKRN1) that significantly correlated with CD8+ T cells. In addition, we found that hub genes were positively associated with CD8+ T cells in TGCT, THCA, and KICH cancers by our analysis. Moreover, the hub gene was differentially methylated. We also analyzed the correlation between hub genes in CAD, different cancers, different cell lines, and different normal tissues. The results of all the analyses showed a positive correlation between them. Finally, we successfully constructed hub gene-associated TF-gene and ceRNA networks and predicted 11 drugs associated with hub genes. GSEA suggests that hub genes are related to multiple immune response processes.

Conclusion

FBXO7, RAD23A, and MKRN1 are significantly associated with CD8+ T cells in CAD and multiple cancers and may act through immune responses in CAD and cancer.

Expression of LINC00847 in Peripheral Blood Mononuclear Cells of Children with Asthma and Its Prediction between Asthma Exacerbation and Remission

Objective. Asthma is defined as a heterogeneous disease that is usually characterized by chronic airway inflammation. Long noncoding RNAs play important roles in various biological processes including inflammation. To know more about the relationships between lncRNAs and asthma, we sought to the role of LINC00847 in peripheral blood mononuclear cells (PBMCs) of children with asthma exacerbation or asthma remission. Methods. Microarray analysis was performed on GSE143192 and GSE165934 datasets to screen differentially expressed lncRNAs (DElncRNAs) in human PBMCs between asthma patients and normal controls. LINC00847 was selected from DElncRNAs in human PBMCs between asthma patients and normal controls for further investigation. The expression levels of LINC00847 were quantified in PBMCs collected from 54 children with asthma exacerbation, 54 children with asthma remission, and 54 healthy children by real-time qPCR. The forced expiratory volume in the first second in percent predicted values (FEV1%), ratio of forced expiratory volume in 1 second to forced vital capacity (FEV1/FVC), and peak expiratory flow rate (PEF%) were tested for evaluation of lung function. The concentration of immunoglobulin E (IgE) and eosinophil count was examined. The serum levels of interleukin-4 (IL-4), interferon-γ (IFN-γ), and IL-17A were determined by the ELISA method. Results. The expression level of LINC00847 in PBMCs of asthma exacerbation children was remarkably higher than that in PBMCs of asthma remission children and healthy children ( $p<0.001$ ); the expression level of LINC00847 in PBMCs of asthma remission children was notably higher than that in PBMCs of healthy children ( $p<0.001$ ). Pearson correlation analysis revealed that the expression levels of LINC00847 in PBMCs of asthma children were negatively correlated with FEV1% (r = −0.489), FEV1/FVC (r = −0.436), PEF% (r = −0.626), and IFN-γ level (r = −0.614) of asthma children, but positively correlated with IgE concentration (r = 0.680), eosinophil count (r = 0.780), IL-4 (r = 0.524), and IL-17A (r = 0.622) levels. When LINC00847 expression was used to distinguish asthma exacerbation from asthma remission, a 0.871 AUC (95% CI: 0.805–0.936) was yielded with sensitivity of 79.63% and specificity of 77.78%. Conclusion. The study demonstrates that increased LINC00847 expression may be associated with the development and progression of asthma, possibly serving as a novel biomarker for predicting asthma exacerbation from asthma remission.