Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

LINC01094: A key long non-coding RNA in the regulation of cancer progression and therapeutic targets

LINC01094 is a long non-coding RNA that plays a crucial role in cancer progression by modulating key signaling pathways, such as PI3K/AKT, Wnt/β-catenin and TGF-β Signaling Pathway Feedback Loop. In this review we summarize the recent research on the functional mechanisms of LINC01094 in various cancers, including its impact on tumor growth, metastasis, and resistance to therapy. We also discuss the therapeutic potential of targeting LINC01094 and highlight the current strategies and challenges in this area. Perspectives on future development of LINC01094-based therapies are also provided.

Integrated bioinformatics analysis identified leucine rich repeat containing 15 and secreted phosphoprotein 1 as hub genes for calcific aortic valve disease and osteoarthritis

Calcific aortic valve disease (CAVD) and osteoarthritis (OA) are common diseases in the ageing population and share similar pathogenesis, especially in inflammation. This study aims to discover potential diagnostic and therapeutic targets in patients with CAVD and OA. Three CAVD datasets and one OA dataset were obtained from the Gene Expression Omnibus database. We used bioinformatics methods to search for key genes and immune infiltration, and established a ceRNA network. Immunohistochemical staining was performed to verify the expression of candidate genes in human and mice aortic valve tissues. Two key genes obtained, leucine rich repeat containing 15 (LRRC15) and secreted phosphoprotein 1 (SPP1), were further screened using machine learning and verified in human and mice aortic valve tissues. Compared to normal tissues, the infiltration of immune cells in CAVD tissues was significantly higher, and the expressions of LRRC15 and SPP1 were positively correlated with immune cells infiltration. Moreover, the ceRNA network showed extensive regulatory interactions based on LRRC15 and SPP1. The authors' findings identified LRRC15 and SPP1 as hub genes in immunological mechanisms during CAVD and OA initiation and progression, as well as potential targets for drug development.

Identification of pyroptosis-associated genes with diagnostic value in calcific aortic valve disease

Background

Calcific aortic valve disease (CAVD) is one of the most prevalent valvular diseases and is the second most common cause for cardiac surgery. However, the mechanism of CAVD remains unclear. This study aimed to investigate the role of pyroptosis-related genes in CAVD by performing comprehensive bioinformatics analysis.

Methods

Three microarray datasets (GSE51472, GSE12644 and GSE83453) and one RNA sequencing dataset (GSE153555) were obtained from the Gene Expression Omnibus (GEO) database. Pyroptosis-related differentially expressed genes (DEGs) were identified between the calcified and the normal valve samples. LASSO regression and random forest (RF) machine learning analyses were performed to identify pyroptosis-related DEGs with diagnostic value. A diagnostic model was constructed with the diagnostic candidate pyroptosis-related DEGs. Receiver operating characteristic (ROC) curve analysis was performed to estimate the diagnostic performances of the diagnostic model and the individual diagnostic candidate genes in the training and validation cohorts. CIBERSORT analysis was performed to estimate the differences in the infiltration of the immune cell types. Pearson correlation analysis was used to investigate associations between the diagnostic biomarkers and the immune cell types. Immunohistochemistry was used to validate protein concentration.

Results

We identified 805 DEGs, including 319 down-regulated genes and 486 up-regulated genes. These DEGs were mainly enriched in pathways related to the inflammatory responses. Subsequently, we identified 17 pyroptosis-related DEGs by comparing the 805 DEGs with the 223 pyroptosis-related genes. LASSO regression and RF algorithm analyses identified three CAVD diagnostic candidate genes (TREM1, TNFRSF11B, and PGF), which were significantly upregulated in the CAVD tissue samples. A diagnostic model was constructed with these 3 diagnostic candidate genes. The diagnostic model and the 3 diagnostic candidate genes showed good diagnostic performances with AUC values >0.75 in both the training and the validation cohorts based on the ROC curve analyses. CIBERSORT analyses demonstrated positive correlation between the proportion of M0 macrophages in the valve tissues and the expression levels of TREM1, TNFRSF11B, and PGF.

Conclusion

Three pyroptosis-related genes (TREM1, TNFRSF11B and PGF) were identified as diagnostic biomarkers for CAVD. These pyroptosis genes and the pro-inflammatory microenvironment in the calcified valve tissues are potential therapeutic targets for alleviating CAVD.

CircRNA/lncRNA-miRNA-mRNA network and gene landscape in calcific aortic valve disease

BACKGROUND

Calcific aortic valve disease (CAVD) is a common valve disease with an increasing incidence, but no effective drugs as of yet. With the development of sequencing technology, non-coding RNAs have been found to play roles in many diseases as well as CAVD, but no circRNA/lncRNA-miRNA-mRNA interaction axis has been established. Moreover, valve interstitial cells (VICs) and valvular endothelial cells (VECs) play important roles in CAVD, and CAVD differed between leaflet phenotypes and genders. This work aims to explore the mechanism of circRNA/lncRNA-miRNA-mRNA network in CAVD, and perform subgroup analysis on the important characteristics of CAVD, such as key cells, leaflet phenotypes and genders.

RESULTS

We identified 158 differentially expressed circRNAs (DEcircRNAs), 397 DElncRNAs, 45 DEmiRNAs and 167 DEmRNAs, and constructed a hsa-circ-0073813/hsa-circ-0027587-hsa-miR-525-5p-SPP1/HMOX1/CD28 network in CAVD after qRT-PCR verification. Additionally, 17 differentially expressed genes (DEGs) in VICs, 9 DEGs in VECs, 7 DEGs between different leaflet phenotypes and 24 DEGs between different genders were identified. Enrichment analysis suggested the potentially important pathways in inflammation and fibro-calcification during the pathogenesis of CAVD, and immune cell patterns in CAVD suggest that M0 macrophages and memory B cells memory were significantly increased, and many genes in immune cells were also differently expressed.

CONCLUSIONS

The circRNA/lncRNA-miRNA-mRNA interaction axis constructed in this work and the DEGs identified between different characteristics of CAVD provide a direction for a deeper understanding of CAVD and provide possible diagnostic markers and treatment targets for CAVD in the future.

Shared gene characteristics and molecular mechanisms of macrophages M1 polarization in calcified aortic valve disease

Background

CAVD is a common cardiovascular disease, but currently there is no drug treatment. Therefore, it is urgent to find new and effective drug therapeutic targets. Recent evidence has shown that the infiltration of M1 macrophages increased in the calcified aortic valve tissues, but the mechanism has not been fully elucidated. The purpose of this study was to explore the shared gene characteristics and molecular mechanisms of macrophages M1 polarization in CAVD, in order to provide a theoretical basis for new drugs of CAVD.

Methods

The mRNA datasets of CAVD and M1 polarization were downloaded from Gene Expression Omnibus (GEO) database. R language, String, and Cytoscape were used to analyze the functions and pathways of DEGs and feature genes. Immunohistochemical staining and Western Blot were performed to verify the selected hub genes.

Results

CCR7 and GZMB were two genes appeared together in hub genes of M1-polarized and CAVD datasets that might be involved in the process of CAVD and macrophages M1 polarization. CCR7 and CD86 were significantly increased, while CD163 was significantly decreased in the calcified aortic valve tissues. The infiltration of M1 macrophages was increased, on the contrary, the infiltration of M2 macrophages was decreased in the calcified aortic valve tissues.

Conclusion

This study reveals the shared gene characteristics and molecular mechanisms of CAVD and macrophages M1 polarization. The hub genes and pathways we found may provide new ideas for the mechanisms underlying the occurrence of M1 polarization during CAVD process.

Identifying hub genes of calcific aortic valve disease and revealing the immune infiltration landscape based on multiple WGCNA and single-cell sequence analysis

BACKGROUND

Calcific aortic valve disease (CAVD) is a progressive fibrocalcific disease that can be treated only through valve replacement. This study aimed to determine the role of hub genes and immune cell infiltration in CAVD progression.

METHODS

In this study, bioinformatics analysis was used to identify hub genes involved in CAVD. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. Gene expression differences were evaluated via pathway and Gene Ontology analyses. Weighted gene co-expression network analysis (WGCNA) and differentially expressed genes were used to screen hub genes. The CIBERSORT algorithm was used to compare immune infiltration into the calcified aortic valve based on the hub genes between high- and low-expression groups. We also performed single-cell RNA sequencing based on six different human aortic valve leaflets. The expression of hub genes was identified in human and mouse samples through quantitative real-time polymerase chain reaction (qPCR), immunohistochemistry, immunofluorescence, and ELISA, and clinical features of the patients were investigated.

RESULTS

In total, 454 differentially expressed genes were obtained from the GEO database. WGCNA was used to find 12 co-expression modules in the Array Express database, of which one hub module (brown module) was most correlated with CAVD. Two hub genes were identified after combining the differentially expressed genes S100A8 and S100A9. Regarding these genes, the immune infiltration profiles varied between high- and low-expression groups. Compared with that in the low hub gene expression group, the high hub gene expression group had a higher proportion of activated NK cells (p < 0.01) and M1 macrophages (p < 0.05). The expression of S100A8 and S100A9 was consistent with single-gene RNA sequencing results, confirming that the expression levels of these two hub genes are significantly upregulated in patients with CAVD (p < 0.01). Furthermore, these results were verified using mouse and human samples by performing immunofluorescence, immunohistochemistry, qPCR, and ELISA analyses. Finally, the localization of S100A8 and S100A9 in monocytes and macrophages was confirmed via immunofluorescence using human aortic valves.

CONCLUSION

These results demonstrate that S100A8 and S100A9 are two hub genes involved in CAVD, which might play an important role in its development through immune-related signaling pathways.

Identification of potential regulatory long non-coding RNA-associated competing endogenous RNA axes in periplaque regions in multiple sclerosis

Slow-burning inflammation at the lesion rim is connected to the expansion of chronic multiple sclerosis (MS) lesions. However, the underlying processes causing expansion are not clearly realized. In this context, the current study used a bioinformatics approach to identify the expression profiles and related lncRNA-associated ceRNA regulatory axes in the periplaque region in MS patients. Expression data (GSE52139) from periplaque regions in the secondary progressive MS spinal cord and controls were downloaded from the Gene Expression Omnibus database (GEO), which has details on mRNAs and lncRNAs. Using the R software's limma package, the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were found. The RNA interactions were also found using the DIANA-LncBase, miRTarBase, and HMDD databases. The Pearson correlation coefficient was used to determine whether there were any positive correlations between DEmRNAs and DElncRNAs in the ceRNA network. Finally, lncRNA-associated ceRNA axes were created based on co-expression and connections between DElncRNA, miRNA, and DEmRNA. We used the Enrichr tool to enrich the biological process, molecular function, and pathways for DEmRNAs and DElncRNAs. A network of DEmRNAs' protein-protein interactions was developed, and the top five hub genes were found using Cytoscape and STRING. The current study indicates that 15 DEmRNAs, including FOS, GJA1, NTRK2, CTNND1, and SP3, are connected to the MS ceRNA network. Additionally, four DElncRNAs (such as TUG1, ASB16-AS1, and LINC01094) that regulated the aforementioned mRNAs by sponging 14 MS-related miRNAs (e.g., hsa-miR-145-5p, hsa-miR-200a-3p, hsa-miR-20a-5p, hsa-miR-22-3p, hsa-miR-23a-3p, hsa-miR-27a-3p, hsa-miR-29b-3p, hsa-miR-29c-3p, hsa-miR-34a-5p) were found. In addition, the analysis of pathway enrichment revealed that DEmRNAs were enriched in the pathways for the "MAPK signaling pathway", "Kaposi sarcoma-associated herpesvirus infection", "Human immunodeficiency virus one infection", "Lipid and atherosclerosis", and "Amphetamine addiction". Even though the function of these ceRNA axes needs to be investigated further, this study provides research targets for studying ceRNA-mediated molecular mechanisms related to periplaque demyelination in MS.