Verification of hub genes in the expression profile of aortic dissection

Wang, Weitie; Liu, Qing; Wang, Yong; Piao, Hulin; Li, Bo; Zhu, Zhicheng; Li, Dan; Wang, Tiance; Xu, Rihao; Liu, Kexiang

doi:10.1371/journal.pone.0224922

Cited by 11 publications

(16 citation statements)

References 36 publications

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“…The top pathways associated with the DEGs were further analyzed. We had previously determined the mRNA profiles for six AD and normal tissues each ( Wang et al, 2019a ) that were used to compare within dataset GSE52093 to identify the DEGs.…”

Section: Methodsmentioning

confidence: 99%

“…This will help identify new modes of treatment, especially targeted drug therapy. Owing to advances in sequencing technology, differential genes expression between normal and damaged tissues have been widely used to identify candidate pathogenic genes ( Wang et al, 2019a ). Bioinformatics tools can analyze such high-throughput data, while omitting “junk” data to provide reliable analyses.…”

Section: Introductionmentioning

confidence: 99%

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Bioinformatics Analysis Reveals MicroRNA-193a-3p Regulates ACTG2 to Control Phenotype Switch in Human Vascular Smooth Muscle Cells

Wang

Piao

et al. 2021

Front. Genet.

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Aortic dissection (AD) is among the most fatal cardiovascular diseases. However, the pathogenesis of AD remains poorly understood. This study aims to integrate the microRNAs (miRNA) and mRNA profiles and use bioinformatics analyses with techniques in molecular biology to delineate the potential mechanisms involved in the development of AD. We used the human miRNA and mRNA microarray datasets GSE98770, GSE52093, and GEO2R, Venn diagram analysis, gene ontology, and protein–protein interaction networks to identify target miRNAs and mRNAs involved in AD. RNA interference, western blotting, and luciferase reporter assays were performed to validate the candidate miRNAs and mRNAs in AD tissues and human vascular smooth muscle cells (VSMCs). Furthermore, we studied vascular smooth muscle contraction in AD. In silico analyses revealed that miR-193a-3p and ACTG2 were key players in the pathogenesis of AD. miR-193a-3p was upregulated in the AD tissues. We also found that biomarkers for the contractile phenotype in VSMCs were downregulated in AD tissues. Overexpression and depletion of miR-193a-3p enhanced and suppressed VSMC proliferation and migration, respectively. Dual luciferase reporter assays confirmed that ACTG2 was a target of miR-193a-3p. ACTG2 was also downregulated in human AD tissues and VMSCs overexpressing miR-193a-3p. Taken together, miR-193a-3p may be a novel regulator of phenotypic switching in VSMCs and the miR-193a-3p/ACTG2 axis may serve as a promising diagnostic biomarker and therapeutic candidate for AD.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bioinformatics Analysis Reveals MicroRNA-193a-3p Regulates ACTG2 to Control Phenotype Switch in Human Vascular Smooth Muscle Cells

Wang

Piao

et al. 2021

Front. Genet.

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“…Therefore, advances in sequencing technology could help researchers in identifying candidate pathogenic genes that promote expansion and facilitate dissection. 5 LncRNAs are the largest class of noncoding RNAs, and most lncRNAs have not been confirmed in function so far. However, growing evidence suggests that lncRNAs may play a key role in transcriptional, post-transcriptional and epigenetic levels.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, advances in sequencing technology could help researchers in identifying candidate pathogenic genes that promote expansion and facilitate dissection. 5 …”

Section: Introductionmentioning

confidence: 99%

Construction and Integrated Analysis of Competitive Endogenous Long Non-Coding RNA Network in Thoracic Aortic Dissection

Shao¹,

Luo²,

Liu³

et al. 2021

IJGM

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Background: Long non-coding RNAs (lncRNAs) can act as a competitive endogenous RNA (ceRNA) to regulate gene expression by sequestering the microRNA (miRNA). However, the lncRNA-miRNA-mRNA ceRNA network in thoracic aortic dissection (TAD) has been rarely documented. Methods: Three Gene Expression Omnibus (GEO) datasets were used to detect differentially expressed mRNAs, miRNAs, and lncRNAs in TAD. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted for the differentially expressed mRNAs. A protein-protein interaction network for differentially expressed mRNAs was also constructed, and hub genes were identified. We established a ceRNA network of TAD based on the differentially expressed miRNAs, mRNAs and lncRNAs, and verified our results using an independent dataset and quantitative real-time PCR (qRT-PCR). Results: In TAD, 267 lncRNAs, 81 miRNAs, and 346 mRNAs were identified as differentially expressed. The established ceRNA network consisted of seven lncRNA nodes, three mRNA nodes, and three miRNA nodes, and the expression of miRNAs in TAD was opposite to that of lncRNAs and mRNAs. Subsequently, an independent GEO dataset and qRT-PCR were used to validate the expression of three mRNAs. In addition, the expression differences in SLC7A5, associated miRNA and lncRNA were verified. According to gene set enrichment analysis of SLC7A5, the most significant KEGG pathway was considerably enriched in spliceosome and pentose phosphate pathway. Conclusion:We established a novel ceRNA regulatory network in TAD, which provides valuable information for further research in the molecular mechanisms of TAD.

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“…In our research, by integrating different gene profiles, we removed DEGs that were expressed only in 1 gene profile ("junk information") [6]. This information might contain some bias due to the different basic parameters such as age, sex, race, and physical condition.…”

Section: Introductionmentioning

confidence: 99%

Multiple Bioinformatics Analyses of Integrated Gene Expression Profiling Data and Verification of Hub Genes Associated with Diabetic Retinopathy

You

et al. 2020

Med Sci Monit

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Background: Diabetic retinopathy (DR) is a serious complication of diabetes that can lead to blindness. This study aimed to identify the core genes and molecular functions involved in DR through multiple bioinformatics analyses. Material/Methods: The mRNA gene profiles of human DR tissues from the GSE60436 and GSE53257 datasets were assessed with R software and integrated to identify the co-expressed differentially expressed genes (DEGs). Multiple bioinformatics analyses were used: Gene Ontology (GO) analysis, signaling pathway analysis, and hub gene prediction. Quantitative reverse transcription-PCR (qRT-PCR) was used to verify the hub genes. Results: The Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool suggested that the biological processes of the DEGs focused on mitochondrial transport, the cellular components focused on mitochondria, and molecular functions focused on catalytic activity. The results provided by DAVID were consistent with those provided by STRING and the GeneMANIA online database. All the DEGs function in metabolic pathways, consistent with the g: Profiler online analysis results. The protein-protein interaction (PPI) networks forecasted by STRING and GeneMANIA were entered into Cytoscape for cytoHubba degree analysis. The hub genes predicted by cytoHubba suggested that fumarate hydratase (FH) might be relevant to DR. qRT-PCR suggested that the expression of FH was higher in DR retinal tissues than in normal control tissues. Conclusions: Multiple bioinformatics analyses verified that FH could be used as a potential diagnostic marker and new therapeutic target of DR.

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Verification of hub genes in the expression profile of aortic dissection

Cited by 11 publications

References 36 publications

Bioinformatics Analysis Reveals MicroRNA-193a-3p Regulates ACTG2 to Control Phenotype Switch in Human Vascular Smooth Muscle Cells

Bioinformatics Analysis Reveals MicroRNA-193a-3p Regulates ACTG2 to Control Phenotype Switch in Human Vascular Smooth Muscle Cells

Construction and Integrated Analysis of Competitive Endogenous Long Non-Coding RNA Network in Thoracic Aortic Dissection

Multiple Bioinformatics Analyses of Integrated Gene Expression Profiling Data and Verification of Hub Genes Associated with Diabetic Retinopathy

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