Construction and Analysis of the lncRNA-miRNA-mRNA Network Based on Competing Endogenous RNA in Atrial Fibrillation

Ke, Xiangyu; Zhang, Junguo; Huang, Xin; Li, Shuai; Leng, Meifang; Zebing, Ye; Li, Guowei

doi:10.3389/fcvm.2022.791156

Cited by 10 publications

(6 citation statements)

References 38 publications

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“…In our previous research, 12 by microarray analysis, a total of 120 DEcircRNAs were identified in AF and control samples based on predefined thresholds ( p ‐value <0.05 and |log 2 FC| ≥ 1), of which 65 were upregulated and 55 were downregulated; The top 10 upregulated circRNAs: hsa_circ_0039161, circRNA_0161, hsa_circ_0001947, hsa_circ_0003916, circRNA_6991, hsa_circ_0008021, hsa_circ_0001394, circRNA_7571, hsa_circ_0008699, hsa_circ_0072697. The top 10 down‐regulated circRNAs: circRNA_1834, circRNA_4184, circRNA_9064, hsa_circ_0004096, circRNA_8108, circRNA_4624, hsa_circ_0085438, hsa_circ_0006208, circRNA_3830, circRNA_1800.…”

Section: Resultsmentioning

confidence: 99%

“…Another comprehensive analysis by Sun HL et al revealed the role of miRNA, circRNA, and lncRNA in paroxysmal AF and persistent AF, and detected a protective factor against persistent AF 11 . Ke XY et al 12 identified differentially expressed RNAs and constructed LOC101928304/miR‐490‐3p/LRRC2 ceRNA network in AF and sinus rhythm subjects. Another study constructed AF‐associated lncRNA‐miRNA‐mRNA network and identified AF‐associated sensitive lncRNAs by WGCNA 13 .…”

Section: Introductionmentioning

confidence: 99%

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Construction of atrial fibrillation‐related circRNA/lncRNA‐miRNA‐mRNA regulatory network and analysis of potential biomarkers

Wen

Ruan

Wang

et al. 2023

Clinical Laboratory Analysis

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Background The specific pathogenesis of atrial fibrillation (AF) remains unclear. In this study, we examined the expression of differential messenger RNAs (mRNAs), circular RNAs (circRNAs), and long‐stranded noncoding RNAs (lncRNAs) from human peripheral blood mononuclear cells to initially construct a circRNA/lncRNA‐miRNA‐mRNA ceRNA regulatory network to explore the pathogenesis of AF and to screen for potential biomarkers. Methods A total of four pairs of AF cases and healthy subjects were selected to detect differentially expressed mRNAs, circRNAs, and lncRNAs in peripheral blood mononuclear cells by microarray analysis. And 20 pairs of peripheral blood from AF patients and healthy subjects were selected for validation of mRNA, circRNA, and lncRNA by quantitative real‐time PCR (qRT‐PCR).The relevant ceRNA networks were constructed by GO and KEGG and correlation analysis. Results The results showed that compared with healthy subjects, there were 813 differentially expressed mRNAs (DEmRNAs) in peripheral blood monocytes of AF, including 445 upregulated genes and 368 downregulated genes, 120 differentially expressed circRNAs (DEcircRNAs), including 65 upregulated and 55 downregulated, 912 differentially expressed lncRNAs (DElncRNAs), including 531 upregulated and 381 downregulated lncRNAs. GO and KEGG analysis of DERNA revealed the biological processes and pathways involved in AF. Based on microarray data and predicted miRNAs, a ceRNA network containing 34 mRNAs, 212 circRNAs, 108 lncRNAs, and 38 miRNAs was constructed. Conclusion We revealed a novel ceRNA network in AF and showed that downregulated XIST, circRNA_2773, and CADM1 were negatively correlated with miR‐486‐5p expression and had a potential targeting relationship with miR‐486‐5p.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Construction of atrial fibrillation‐related circRNA/lncRNA‐miRNA‐mRNA regulatory network and analysis of potential biomarkers

Wen

Ruan

Wang

et al. 2023

Clinical Laboratory Analysis

View full text Add to dashboard Cite

show abstract

“…For example, a study has shown the influence of LOC101928304/miR-490-3p/LRRC2, a lincRNA-miRNA-mRNA axis on Atrial Fibrillation (AF). The levels of LOC101928304 and LRRC were elevated whereas miR-490-3p exhibited a decreased expression in the myocardial tissue of AF patients [34]. However, there is not much experimental data available.…”

Section: Discussionmentioning

confidence: 99%

Comparative transcriptome of normal and cancer-associated fibroblasts

Abikar,

Mustafa,

Athalye

et al. 2024

Preprint

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The characteristics of a tumor are largely determined by its interaction with the surrounding micro-environment (TME). TME consists of both cellular and non-cellular components. Cancer associated fibroblasts (CAFs) are a major component of the TME. They are a source of many secreted factors that influence the survival and progression of tumors as well as their response to drugs. Identification of markers either overexpressed in CAFs or unique to CAFs would pave the way for novel therapeutic strategies that would combine conventional chemotherapy and TME-targeted therapy for a better outcome. We have used fibroblast derived from Benign Prostatic Hyperplasia (BPH) and prostate cancer to perform a transcriptome analysis in order to get a comparative profile of normal and cancer-associated fibroblasts. This has identified 818 differentially expressed mRNAs and 17 lincRNAs between normal and cancer-associated fibroblasts.

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“…The overlapped miRNAs of each lncRNA–mRNA pair were regarded as a miRNA cluster (miR-cluster), and the top-3 miRNAs of total confidence scores in each miR-cluster were selected to be presented. Topological network analysis was performed on the Cytoscape software ( 30 , 31 ).…”

Section: Methodsmentioning

confidence: 99%

Dominant Myocardial Fibrosis and Complex Immune Microenvironment Jointly Shape the Pathogenesis of Arrhythmogenic Right Ventricular Cardiomyopathy

Dai

et al. 2022

Front. Cardiovasc. Med.

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BackgroundArrhythmogenic right ventricular cardiomyopathy (ARVC) is a heritable life-threatening myocardial disease characterized by ventricular arrhythmias and sudden cardiac death. Few studies used RNA-sequencing (RNA-seq) technology to analyze gene expression profiles, hub genes, dominant pathogenic processes, immune microenvironment in ARVC. This study aimed to explore these questions via integrated bioinformatics analysis.MethodsRNA-sequencing datasets of GSE107475, GSE107311, GSE107156, and GSE107125 were obtained from the Gene Expression Omnibus database, including right and left ventricular myocardium from ARVC patients and normal controls. Weighted gene co-expression network analysis identified the ARVC hub modules and genes. Functional enrichment and protein-protein interaction analysis were performed by Metascape and STRING. Single-sample gene-set enrichment analysis (ssGSEA) was applied to assess immune cell infiltration. Transcription regulator (TF) analysis was performed by TRRUST.ResultsThree ARVC hub modules with 25 hub genes were identified. Functional enrichment analysis of the hub genes indicated that myocardial fibrosis was the dominant pathogenic process. Higher myocardial fibrosis activity existed in ARVC than in normal controls. A complex immune microenvironment was discovered that type 2 T helper cell, type 1 T helper cell, regulatory T cell, plasmacytoid dendritic cell, neutrophil, mast cell, central memory CD4 T cell, macrophage, CD56dim natural killer cell, myeloid-derived suppressor cell, memory B cell, natural killer T cell, and activated CD8 T cell were highly infiltrated in ARVC myocardium. The immune-related hub module was enriched in immune processes and inflammatory disease pathways, with hub genes including CD74, HLA-DRA, ITGAM, CTSS, CYBB, and IRF8. A positive linear correlation existed between immune cell infiltration and fibrosis activity in ARVC. NFKB1 and RELA were the shared TFs of ARVC hub genes and immune-related hub module genes, indicating the critical role of NFκB signaling in both mechanisms. Finally, the potential lncRNA–miRNA–mRNA interaction network for ARVC hub genes was constructed.ConclusionMyocardial fibrosis is the dominant pathogenic process in end-stage ARVC patients. A complex immune microenvironment exists in the diseased myocardium of ARVC, in which T cell subsets are the primary category. A tight relationship exists between myocardial fibrosis activity and immune cell infiltration. NFκB signaling pathway possibly contributes to both mechanisms.

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Construction and Analysis of the lncRNA-miRNA-mRNA Network Based on Competing Endogenous RNA in Atrial Fibrillation

Cited by 10 publications

References 38 publications

Construction of atrial fibrillation‐related circRNA/lncRNA‐miRNA‐mRNA regulatory network and analysis of potential biomarkers

Construction of atrial fibrillation‐related circRNA/lncRNA‐miRNA‐mRNA regulatory network and analysis of potential biomarkers

Comparative transcriptome of normal and cancer-associated fibroblasts

Dominant Myocardial Fibrosis and Complex Immune Microenvironment Jointly Shape the Pathogenesis of Arrhythmogenic Right Ventricular Cardiomyopathy

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