Integrated Analysis of Hub Genes and miRNAs in Dilated Cardiomyopathy

Purpose. The aim of this study is to identify hub genes and miRNAs by the miRNA-mRNA interaction network in dilated cardiomyopathy (DCM) disease. Methods. The differentially expressed miRNAs (DEMis) and mRNAs (DEMs) were selected using data of DCM patients downloaded from the GEO database (GSE112556 and GSE3585). Gene Ontology (GO) pathway analysis and transcription factor enrichment analysis were used for selecting DEMis, and the target mRNAs of DEMis were filtered by using miRDB, miRTarBase, and TargetScan. Cytoscape software was used to visualize the network between miRNAs and mRNAs and calculate the hub genes. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to analyze the mRNAs in the regulatory network. Results. A total of 9 DEMis and 281 DEMs were selected, from which we reconstructed the miRNA-mRNA network consisting of 7 miRNAs and 51 mRNAs. The top 10 nodes, miR-144-3p, miR-363-3p, miR-9-3p, miR-21-3p, miR-144-5p, miR-338-3p, ID4 (inhibitor of DNA binding/differentiation 4), miR-770-5p, PIK3R1 (p85α regulatory subunit of phosphoinositide 3-kinase (PI3K)), and FN1 (fibronectin 1), were identified as important regulators. Conclusions. The study uncovered several important hub genes and miRNAs involved in the pathogenesis of DCM, among which, the miR-144-3p/FN1 and miR-9-3p/FN1 pathways may play an important role in myocardial fibrosis, which can help identify the etiology of DCM, and provide potential therapeutic targets

Integrative identification of hub genes in development of atrial fibrillation related stroke

Background As the most common arrhythmia, atrial fibrillation (AF) is associated with a significantly increased risk of stroke, which causes high disability and mortality. To date, the underlying mechanism of stroke occurring after AF remains unclear. Herein, we studied hub genes and regulatory pathways involved in AF and secondary stroke and aimed to reveal biomarkers and therapeutic targets of AF-related stroke. Methods The GSE79768 and GSE58294 datasets were used to analyze AF- and stroke-related differentially expressed genes (DEGs) to obtain a DEG1 dataset. Weighted correlation network analysis (WGCNA) was used to identify modules associated with AF-related stroke in GSE66724 (DEG2). DEG1 and DEG2 were merged, and hub genes were identified based on protein–protein interaction networks. Gene Ontology terms were used to analyze the enriched pathways. The GSE129409 and GSE70887 were applied to construct a circRNA-miRNA-mRNA network in AF-related stroke. Hub genes were verified in patients using quantitative real-time polymerase chain reaction (qRT-PCR). Results We identified 3,132 DEGs in blood samples and 253 DEGs in left atrial specimens. Co-expressed hub genes of EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 were significantly associated with AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 pathway was explored as the regulating axis in AF-related stroke. The qRT-PCR results were consistent with the bioinformatic analysis. Conclusions Hub genes EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 have potential as novel biomarkers and therapeutic targets in AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 axis could play an important role regulating the development of AF-related stroke

Rad51 and Systemic Inflammatory Indicators as Novel Prognostic Markers in Esophageal Squamous Cell Carcinoma

Background RAD51 is a central protein involved in homologous recombination, which has been linked to cancer development and progression. systemic inflammatory indicator markers such as neutrophil-to-lymphocyte ratio and lymphocyte-to-monocyte ratio have also been implicated in cancer. However, the relationship between Rad51 and these inflammatory markers in esophageal cancer patients undergoing esophagectomy is not yet understood. Methods We retrospectively observed 320 esophageal cancer patients who underwent esophagectomy. We collected clinical characteristics, postoperative complications, and survival analysis data and analyzed the relationship between Rad51 expression, inflammatory markers, and prognosis. Results We found significant linear relationships among the inflammatory markers. There were also close relationships between Rad51 expression and neutrophil-to-lymphocyte ratio or C-reactive protein. Patients with low lymphocyte percentage were more likely to have low Rad51 expression ( P  = .026), high C-reactive protein ( P  = .007), and high neutrophil-to-lymphocyte ratio ( P  = .006). Low lymphocyte-to-monocyte ratio was associated with poor overall survival and was an independent prognostic factor (HR = 2.214; 95% confidence interval: 1.044-4.695, P  = .038). In patients without lymph node metastases, low albumin (HR= 0.131; 95% confidence interval: 0.025-0.687, P  = .016), high neutrophil-to-lymphocyte ratio (HR = 0.002; 95% confidence interval: 0.000-0.221, P  = .009), and high Rad51 expression (HR = 14.394; 95% confidence interval: 2.217-97.402, P  = .006) were associated with poor overall survival. Conclusions Our study found a close correlation between elevated Rad51 expression and inflammatory markers. High Rad51 expression, high neutrophil-to-lymphocyte ratio, and low lymphocyte-to-monocyte ratio are associated with lower survival rates. The combined assessment of Rad51 and inflammatory markers can be useful for preoperative assessment and prognostic evaluation in esophageal squamous cell carcinoma patients

Integrative identification of hub genes in development of atrial fibrillation related stroke.

BackgroundAs the most common arrhythmia, atrial fibrillation (AF) is associated with a significantly increased risk of stroke, which causes high disability and mortality. To date, the underlying mechanism of stroke occurring after AF remains unclear. Herein, we studied hub genes and regulatory pathways involved in AF and secondary stroke and aimed to reveal biomarkers and therapeutic targets of AF-related stroke.MethodsThe GSE79768 and GSE58294 datasets were used to analyze AF- and stroke-related differentially expressed genes (DEGs) to obtain a DEG1 dataset. Weighted correlation network analysis (WGCNA) was used to identify modules associated with AF-related stroke in GSE66724 (DEG2). DEG1 and DEG2 were merged, and hub genes were identified based on protein-protein interaction networks. Gene Ontology terms were used to analyze the enriched pathways. The GSE129409 and GSE70887 were applied to construct a circRNA-miRNA-mRNA network in AF-related stroke. Hub genes were verified in patients using quantitative real-time polymerase chain reaction (qRT-PCR).ResultsWe identified 3,132 DEGs in blood samples and 253 DEGs in left atrial specimens. Co-expressed hub genes of EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 were significantly associated with AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 pathway was explored as the regulating axis in AF-related stroke. The qRT-PCR results were consistent with the bioinformatic analysis.ConclusionsHub genes EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 have potential as novel biomarkers and therapeutic targets in AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 axis could play an important role regulating the development of AF-related stroke