Identification and validation of four hub genes involved in the plaque deterioration of atherosclerosis

Machine Learning Identifies a Signature of Nine Exosomal RNAs That Predicts Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Although alpha fetoprotein (AFP) remains a commonly used serological marker of HCC, the sensitivity and specificity of AFP in detecting HCC is often limited. Exosomal RNA has emerged as a promising diagnostic tool for various cancers, but its use in HCC detection has yet to be fully explored. Here, we employed Machine Learning on 114,602 exosomal RNAs to identify a signature that can predict HCC. The exosomal expression data of 118 HCC patients and 112 healthy individuals were stratified split into Training, Validation and Unseen Test datasets. Feature selection was then performed on the initial training dataset using permutation importance, and the predictive performance of the selected features were tested on the validation dataset using Support Vector Machine (SVM) Classifier. A minimum of nine features were identified to be predictive of HCC and these nine features were then evaluated across six different models in an unseen test set. These features, mainly in the immune, platelet/neutrophil and cytoskeletal pathways, exhibited good predictive performance with ROC-AUC from 0.79-0.88 in the unseen test set. Hence, these nine exosomal RNAs have potential to be clinically useful minimally invasive biomarkers for HCC.

Identification and Validation of Immune-Related Genes Diagnostic for Progression of Atherosclerosis and Diabetes

Background

Atherosclerosis and type 2 diabetes mellitus contribute to a large part of cardiovascular events, but the underlying mechanism remains unclear. In this study, we focused on identifying the linking genes of the diagnostic biomarkers and effective therapeutic targets associated with these two diseases.

Methods

The transcriptomic datasets of atherosclerosis and type 2 diabetes mellitus were obtained from the GEO database. Differentially expressed genes analysis was performed by R studio software, and differential analysis including functional enrichment, therapeutic small molecular agents prediction, and protein-protein interaction analysis were applied to the common shared differentially expressed genes. Hub genes were identified and further validated using an independent dataset and clinical samples. Furthermore, we measured the expression correlations, immune cell infiltration, and diagnostic capability of the three key genes.

Results

We screened out 28 up-regulated and six down-regulated common shared differentially expressed genes. Functional enrichment analysis showed that cytokines and immune activation were involved in the development of these two diseases. Six small molecules with the highest absolute enrichment value were identified. Three critical genes (CD4, PLEK, and THY1) were further validated both in validation sets and clinical samples. The gene correlation analysis showed that CD4 was strongly positively correlated with PLEK, and ROC curves confirmed the good discriminatory capacity of CD4 and PLEK in two diseases.

We have established the co-expression network between atherosclerosis lesions progressions and type 2 diabetes mellitus, and identified CD4 and PLEK as key genes in the two diseases, which may facilitate both development of diagnosis and therapeutic strategies.

MicroRNA-582-5p targeting Creb1 modulates apoptosis in cardiomyocytes hypoxia/reperfusion-induced injury

BACKGROUND

Myocardial ischemia-reperfusion injury (MIRI) caused by the reperfusion therapy of myocardial ischemic diseases is a kind of major disease that threatens human health and lives severely. There are lacking of effective therapeutic measures for MIRI. MicroRNAs (miRNAs) are abundant in mammalian species and play a critical role in the initiation, promotion, and progression of MIRI. However, the biological role and molecular mechanism of miRNAs in MIRI are not entirely clear.

METHODS

We used bioinformatics analysis to uncover the significantly different miRNA by analyzing transcriptome sequencing data from myocardial tissue in the mouse MIRI model. Multiple miRNA-related databases, including miRdb, PicTar, and TargetScan were used to forecast the downstream target genes of the differentially expressed miRNA. Then, the experimental models, including male C57BL/6J mice and HL-1 cell line, were used for subsequent experiments including quantitative real-time polymerase chain reaction analysis, western blot analysis, hematoxylin and eosin staining, flow cytometry, luciferase assay, gene interference, and overexpression.

RESULTS

MiR-582-5p was found to be differentially upregulated from the transcriptome sequencing data. The elevated levels of miR-582-5p were verified in MIRI mice and hypoxia/reperfusion (H/R)-induced HL-1 cells. Functional experiments revealed that miR-582-5p promoted apoptosis of H/R-induced HL-1 cells via downregulating cAMP-response element-binding protein 1 (Creb1). The inhibiting action of miR-582-5p inhibitor on H/R-induced apoptosis was partially reversed after Creb1 interference.

CONCLUSIONS

Collectively, the research findings reported that upregulation of miR-582-5p promoted H/R-induced cardiomyocyte apoptosis by inhibiting Creb1. The potential diagnostic and therapeutic strategies targeting miR-582-5p and Creb1 could be beneficial for the MIRI treatment.

The transcription factor RFX5 coordinates antigen-presenting function and resistance to nutrient stress in synovial macrophages

Tissue macrophages (Mϕ) are essential effector cells in rheumatoid arthritis (RA), contributing to autoimmune tissue inflammation through diverse effector functions. Their arthritogenic potential depends on their proficiency to survive in the glucose-depleted environment of the inflamed joint. Here, we identify a mechanism that links metabolic adaptation to nutrient stress with the efficacy of tissue Mϕ to activate adaptive immunity by presenting antigen to tissue-invading T cells. Specifically, Mϕ populating the rheumatoid joint produce and respond to the small cytokine CCL18, which protects against cell death induced by glucose withdrawal. Mechanistically, CCL18 induces the transcription factor RFX5 that selectively upregulates glutamate dehydrogenase 1 (GLUD1), thus enabling glutamate utilization to support energy production. In parallel, RFX5 enhances surface expression of HLA-DR molecules, promoting Mϕ-dependent expansion of antigen-specific T cells. These data place CCL18 at the top of a RFX5-GLUD1 survival pathway and couple adaptability to nutrient conditions in the tissue environment to antigen-presenting function in autoimmune tissue inflammation.

Comprehensive Analysis to Identify Key Genes Involved in Advanced Atherosclerosis

Background

The study was aimed at finding accurate and effective therapeutic targets and deepening our understanding of the mechanisms of advanced atherosclerosis (AA).

Methods

We downloaded the gene expression datasets GSE28829, GSE120521, and GSE43292 from Gene Expression Omnibus. Weighted gene coexpression network analysis (WGCNA) was performed for GSE28829, and functional enrichment analysis and protein–protein interaction network analysis were conducted on the key module. Significant genes in the key module were analyzed by molecular complex detection, and genes in the most important subnetwork were defined as hub genes. Multiple dataset analyses for hub genes were conducted. Genes that overlapped between hub genes and differentially expressed genes (DEGs) of GSE28829 and GSE120521 were defined as key genes. Further validation for key genes was performed using GSE28829 and GSE43292. Gene set enrichment analysis (GSEA) was applied to key genes.

Results

A total of 77 significant genes in the key module of GSE28829 were screened out that were mainly associated with inflammation and immunity. The subnetwork was obtained from significant genes, and 18 genes in this module were defined as hub genes, which were related to immunity and expressed in multiple diseases, particularly systemic lupus erythematosus. Some hub genes were regulated by SPI1 and associated with the blood, spleen, and lung. After overlapping with DEGs of GSE28829 and GSE120521, a total of 10 genes (HCK, ITGAM, CTSS, TYROBP, LAPTM5, FCER1G, ITGB2, NCF2, AIF1, and CD86) were identified as key genes. All key genes were validated and evaluated successfully and were related to immune response pathways.

Conclusion

Our study suggests that the key genes related to immune and inflammatory responses are involved in the development of AA. This may deepen our understanding of the mechanisms of and provide valuable therapeutic targets for AA.

Exploring the Pathogenesis of Psoriasis Complicated With Atherosclerosis via Microarray Data Analysis

Background

Although more and more evidence has supported psoriasis is prone to atherosclerosis, the common mechanism of its occurrence is still not fully elucidated. The purpose of this study is to further explore the molecular mechanism of the occurrence of this complication.

Methods

The gene expression profiles of psoriasis (GSE30999) and atherosclerosis (GSE28829) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis and atherosclerosis, three kinds of analyses were performed, namely functional annotation, protein‐protein interaction (PPI) network and module construction, and hub gene identification and co-expression analysis.

Results

A total of 94 common DEGs (24 downregulated genes and 70 upregulated genes) was selected for subsequent analyses. Functional analysis emphasizes the important role of chemokines and cytokines in these two diseases. In addition, lipopolysaccharide-mediated signaling pathway is closely related to both. Finally, 16 important hub genes were identified using cytoHubba, including LYN, CSF2RB, IL1RN, RAC2, CCL5, IRF8, C1QB, MMP9, PLEK, PTPRC, FYB, BCL2A1, LCP2, CD53, NCF2 and TLR2.

Conclusions

Our study reveals the common pathogenesis of psoriasis and atherosclerosis. These common pathways and hub genes may provide new ideas for further mechanism research.

Inflammatory Markers Related to Innate and Adaptive Immunity in Atherosclerosis: Implications for Disease Prediction and Prospective Therapeutics

Several lines of evidence have linked a dysregulated inflammatory setting to the pathogenesis of atherosclerosis, which is a form of chronic vascular inflammation. Various inflammatory biomarkers have been associated with inflammation and are recognized as potential tools to monitor the progression of atherosclerosis. A well-studied inflammatory marker in the context of cardiovascular diseases is C-reactive protein (CRP) or, more accurately, highly sensitive-CRP (hs-CRP), which has been established as an inflammatory biomarker for atherosclerotic events. In addition, a growing body of investigations has attempted to disclose the potential of inflammatory cytokines, enzymes, and genetic polymorphisms related to innate and adaptive immunity as biomarkers for predicting the development of atherosclerosis. In this review article, we clarify both traditional and novel inflammatory biomarkers related to components of the innate and adaptive immune system that may mirror the progression or phases of atherosclerotic inflammation/lesions. Furthermore, the contribution of the inflammatory biomarkers in developing potential therapeutics against atherosclerotic treatment will be discussed.

Identification of key pathways and core genes involved in atherosclerotic plaque progression

Background

Atherosclerosis leads to the occurrence of cardiovascular diseases. However, the molecular mechanisms that contribute to atherosclerotic plaque rupture are incompletely characterized. We aimed to identify the genes related to atherosclerotic plaque progression that could serve as novel biomarkers and interventional targets for plaque progression.

Methods

The datasets of GSE28829 in early vs. advanced atherosclerotic plaques and those of GSE41571 in stable vs. ruptured plaques from Gene Expression Omnibus (GEO) were analyzed by using bioinformatics methods. In addition, we used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the expression level of core genes in a mouse atherosclerosis model.

Results

There were 29 common differentially expressed genes (DEGs) between the GSE28829 and GSE41571 datasets, and the DEGs were mainly enriched in the chemokine signaling pathway and the Staphylococcus aureus infection pathway (P<0.05). We identified 6 core genes (FPR3, CCL18, MS4A4A, CXCR4, CXCL2, and C1QB) in the protein-protein interaction (PPI) network, 3 of which (CXCR4, CXCL2, and CCL18) were markedly enriched in the chemokine signaling pathway. qRT-PCR analysis showed that the messenger RNA levels of two core genes (CXCR4 and CXCL2) increased significantly during plaque progression in the mouse atherosclerosis model.

Conclusions

In summary, bioinformatics techniques proved useful for the screening and identification of novel biomarkers of disease. A total of 29 DEGs and 6 core genes were linked to atherosclerotic plaque progression, in particular the CXCR4 and CXCL2 genes.

Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome

Background

Acute coronary syndrome (ACS) has a high incidence and mortality rate. Early detection and intervention would provide clinical benefits. This study aimed to reveal hub genes, transcription factors (TFs), and microRNAs (miRNAs) that affect plaque stability and provide the possibility for the early diagnosis and treatment of ACS.

Methods

We obtained gene expression matrix GSE19339 for ACS patients and healthy subjects from public database. The differentially expressed genes (DEGs) were screened using Limma package in R software. The biological functions of DEGs were shown by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Protein-protein interaction (PPI) network was mapped in Cytoscape, followed by screening of hub genes based on the Molecular Complex Detection (MCODE) plug-in. Functional Enrichment analysis tool (FunRich) and Database for Annotation, Visualization and Integrated Discovery (DAVID) were used to predict miRNAs and TFs, respectively. Finally, GSE60993 expression matrix was chosen to plot receiver operating characteristic (ROC) curves with the aim of further assessing the reliability of our findings.

Results

We obtained 176 DEGs and further identified 16 hub genes by MCODE. The results of functional enrichment analysis showed that DEGs mediated inflammatory response and immune-related pathways. Among the predicted miRNAs, hsa-miR-4770, hsa-miR-5195, and hsa-miR-6088 all possessed two target genes, which might be closely related to the development of ACS. Moreover, we identified 11 TFs regulating hub gene transcriptional processes. Finally, ROC curves confirmed three genes with high confidence (area under the curve > 0.9), including VEGFA, SPP1, and VCAM1.

Conclusion

This study suggests that three genes (VEGFA, SPP1, and VCAM1) were involved in the molecular mechanisms of ACS pathogenesis and could serve as biomarkers of disease progression.

Intracellular calcium current disorder and disease phenotype in OBSCN mutant iPSC-based cardiomyocytes in arrhythmogenic right ventricular cardiomyopathy

Obscurin participates in the development of striated muscles and maintenance of the functional sarcoplasmic reticulum. However, the role of obscurin in arrhythmogenic right ventricular cardiomyopathy (ARVC) is not well understood. We aimed to study the novel obscurin mutations in the pathogenesis of ARVC and the underlying mechanisms. Methods: We generated induced pluripotent stem cells (iPSC) through retroviral reprogramming of peripheral blood mononuclear cells isolated from a 46-year-old female diagnosed with ARVC, carrying a mutation in OBSCN. The cells differentiated into functional iPSC-based cardiomyocytes (iPSC-CMs), whose phenotype was determined by transmission electron microscopy, electrophysiological description, immunofluorescence staining, and Oil Red O staining. Molecular characterization was performed by bioinformatic analyses, and identification by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. Results: ARVC-iPSC-CMs mutation in OBSCN showed significant accumulation of lipids, increased pleomorphism, irregular Z-bands, and increased L type calcium currents. Functional enrichment analysis identified pathways involved in focal adhesion and structure formation; the adipocytokines and PPAR signaling pathways were also activated in the ARVC group. Moreover, our results from ultra-high-resolution microscopy, qRT-PCR and Western blotting confirmed that the mutant OBSCN protein and its anchor protein, Ank1.5, showed structural disorder and decreased expression, but there was increased expression of junctional protein N-Cadherin. Further analysis revealed the gene expression of other desmosomal proteins in ARVC-iPSC-CMs was also decreased but some adipogenesis pathway-related proteins (PPARγ, C/EBPα, and FABP4) were increased. Conclusion: A novel frameshift mutation in OBSCN caused phenotypic alteration accompanied by disrupted localization and decreased expression of its anchoring protein Ank1.5. Furthermore, there was an accumulation of lipids with an increase in fatty fibrosis area and myocardial structural disorder, possibly leading to dysrhythmia in calcium channel-related myocardial contraction. These observations suggested the possibility of attenuating ARVC progression by therapeutic modulation of OBSCN expression.

Identification and validation of hub microRNAs dysregulated in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancers worldwide, and its morbidity is exacerbated by the lack of early symptoms. Bioinformatics analyses enable discovery of differentially expressed genes and non-protein-coding RNAs of potential prognostic and/or therapeutic relevance in ESCC and other cancers. Using bioinformatics tools, we searched for dysregulated miRNAs in two ESCC microarray datasets from the Gene Expression Omnibus (GEO) database. After identification of three upregulated and five downregulated miRNAs shared between databases, protein-protein interaction (PPI) network analysis was used to identify the top 10 hub-gene targets. Thereafter, a miRNA-gene interaction network predicted that most hub genes are regulated by miR-196a-5p and miR-1-3p, which are respectively upregulated and downregulated in ESCC. Functional enrichment analyses in the GO and KEGG databases indicated the potential involvement of these miRNAs in tumorigenesis-related processes and pathways, while both differential expression and correlation with T stage were demonstrated for each miRNA in a cohort of ESCC patients. Overexpression showed that miR-196a-5p increased, whereas miR-1-3p attenuated, proliferation and invasion in human ESCC cell lines grown in vitro. These findings suggest miR-196a-5p and miR-1-3p jointly contribute to ESCC tumorigenesis and are potential targets for diagnosis and treatment.