Yuyuan Hu, Zhenhao Liu, Yan Qin, Nan Wu, Tao Yang, Xinmeng Cheng, Chunyan Wang, Xuening Wang
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The ceRNA network (lncRNA-miRNA-mRNA) was constructed by bioinformatics analysis. The accuracy of hub genes as biomarkers for predicting TAAD was evaluated by receiver operating characteristic (ROC) curve. Finally, the biomarkers were verified by assessing their mRNA levels using real-time quantitative PCR (RT-qPCR).</p><p><strong>Results: </strong>This study revealed 161 DELs, 87 DEmiRs and 103 DEGs between TAAD and control. We constructed ceRNA networks based on the screened 1 lncRNA, 4 miRNAs and 7 mRNAs. We identified three lncRNA-miRNA-mRNA regulatory axes, namely the VCAN axis (LINC01355 - hsa-miR-186-5p / hsa-miR-30a-5p /hsa-miR-30c-5p - VCAN), LOX axis (LINC01355-hsa-miR-145-5p/hsa-miR-186-5p/ hsa-miR-30a-5p / hsa-miR-30c-5p - LOX), and CTSS axis (LINC01355 - hsa-miR-186-5p - CTSS) based on gene ontology, pathway enrichment and protein-protein interaction (PPI) network, which may play an important role in TAAD. The clinical performance of VCAN, CTSS, and LOX in TAAD diagnosis was evaluated, and the AUCs of VCAN, CTSS, and LOX were 0.920 (p<0.001), 0.880 (p=0.002) and 0.840 (p=0.011), respectively. Furthermore, mRNA expression of VCAN in human aortic tissue significantly overexpressed in the TAAD patients (p<0.001).</p><p><strong>Conclusion: </strong>This study identifies three ceRNA interaction axes, especially VCAN associated with TAAD pathogenesis, providing fundamentals of bioinformatics for understanding the molecular mechanisms of TAAD pathogenesis and developing potential therapeutic strategies for TAAD.</p>","PeriodicalId":14131,"journal":{"name":"International Journal of General Medicine","volume":"18 ","pages":"1509-1527"},"PeriodicalIF":2.1000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11927577/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification of Pivotal ceRNA Networks Associated with Stanford-A Aortic Dissection via Integrated Bioinformatics Analysis.\",\"authors\":\"Yuyuan Hu, Zhenhao Liu, Yan Qin, Nan Wu, Tao Yang, Xinmeng Cheng, Chunyan Wang, Xuening Wang\",\"doi\":\"10.2147/IJGM.S509177\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Stanford-A Aortic dissection (TAAD) is a rare and fatal disease, genetic factors remains poorly known. Study has confirmed that lncRNA play an important role in various physiological and pathological processes. This study attempts to elucidate the underlying molecular mechanisms of TAAD through lncRNA-associated competitive endogenous RNA (ceRNA) networks.</p><p><strong>Methods: </strong>In this study, aortic vascular of 5 TAAD and 5 control (ischemic heart disease) were subjected to lncRNA and mRNA microarray analysis, and differentially expressed mRNAs (DEGs) and differentially expressed lncRNAs (DELs) were identified. The differentially expressed miRNAs (DEmiR) were screened by GSE98770 dataset. The ceRNA network (lncRNA-miRNA-mRNA) was constructed by bioinformatics analysis. The accuracy of hub genes as biomarkers for predicting TAAD was evaluated by receiver operating characteristic (ROC) curve. Finally, the biomarkers were verified by assessing their mRNA levels using real-time quantitative PCR (RT-qPCR).</p><p><strong>Results: </strong>This study revealed 161 DELs, 87 DEmiRs and 103 DEGs between TAAD and control. We constructed ceRNA networks based on the screened 1 lncRNA, 4 miRNAs and 7 mRNAs. We identified three lncRNA-miRNA-mRNA regulatory axes, namely the VCAN axis (LINC01355 - hsa-miR-186-5p / hsa-miR-30a-5p /hsa-miR-30c-5p - VCAN), LOX axis (LINC01355-hsa-miR-145-5p/hsa-miR-186-5p/ hsa-miR-30a-5p / hsa-miR-30c-5p - LOX), and CTSS axis (LINC01355 - hsa-miR-186-5p - CTSS) based on gene ontology, pathway enrichment and protein-protein interaction (PPI) network, which may play an important role in TAAD. The clinical performance of VCAN, CTSS, and LOX in TAAD diagnosis was evaluated, and the AUCs of VCAN, CTSS, and LOX were 0.920 (p<0.001), 0.880 (p=0.002) and 0.840 (p=0.011), respectively. 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引用次数: 0
摘要
目的:Stanford-A主动脉夹层(TAAD)是一种罕见的致死性疾病,其遗传因素尚不清楚。研究证实lncRNA在多种生理病理过程中发挥重要作用。本研究试图通过lncrna相关的竞争性内源性RNA (ceRNA)网络阐明TAAD的潜在分子机制。方法:本研究对5例TAAD患者和5例对照组(缺血性心脏病患者)的主动脉血管进行lncRNA和mRNA芯片分析,鉴定差异表达mRNA (DEGs)和差异表达lncRNAs (DELs)。通过GSE98770数据集筛选差异表达的mirna (DEmiR)。通过生物信息学分析构建了ceRNA网络(lncRNA-miRNA-mRNA)。采用受试者工作特征(ROC)曲线评价枢纽基因作为TAAD预测生物标志物的准确性。最后,通过实时定量PCR (RT-qPCR)评估其mRNA水平来验证生物标志物。结果:TAAD与对照组共发现161个DELs, 87个demir和103个deg。我们基于筛选到的1个lncRNA、4个mirna和7个mrna构建了ceRNA网络。我们确定了三个lncRNA-miRNA-mRNA监管的轴,即VCAN轴(LINC01355 - hsa - mir - 186 - 5 - p / hsa-miR-30a-5p / hsa-miR-30c-5p - VCAN),液态氧轴(LINC01355 - hsa - mir - 145 - 5 - p / hsa - mir - 186 - 5 - p / hsa-miR-30a-5p / hsa-miR-30c-5p - LOX),和CTSS轴(LINC01355 - hsa - mir - 186 - 5 - p - CTSS)基于基因本体,通路浓缩和蛋白质交互(PPI)网络,在TAAD可能发挥重要的作用。评价VCAN、CTSS和LOX在TAAD诊断中的临床表现,VCAN、CTSS和LOX的auc均为0.920 (p)。结论:本研究确定了三个ceRNA相互作用轴,特别是VCAN与TAAD发病机制相关,为了解TAAD发病的分子机制和制定潜在的TAAD治疗策略提供了生物信息学基础。
Identification of Pivotal ceRNA Networks Associated with Stanford-A Aortic Dissection via Integrated Bioinformatics Analysis.
Objective: Stanford-A Aortic dissection (TAAD) is a rare and fatal disease, genetic factors remains poorly known. Study has confirmed that lncRNA play an important role in various physiological and pathological processes. This study attempts to elucidate the underlying molecular mechanisms of TAAD through lncRNA-associated competitive endogenous RNA (ceRNA) networks.
Methods: In this study, aortic vascular of 5 TAAD and 5 control (ischemic heart disease) were subjected to lncRNA and mRNA microarray analysis, and differentially expressed mRNAs (DEGs) and differentially expressed lncRNAs (DELs) were identified. The differentially expressed miRNAs (DEmiR) were screened by GSE98770 dataset. The ceRNA network (lncRNA-miRNA-mRNA) was constructed by bioinformatics analysis. The accuracy of hub genes as biomarkers for predicting TAAD was evaluated by receiver operating characteristic (ROC) curve. Finally, the biomarkers were verified by assessing their mRNA levels using real-time quantitative PCR (RT-qPCR).
Results: This study revealed 161 DELs, 87 DEmiRs and 103 DEGs between TAAD and control. We constructed ceRNA networks based on the screened 1 lncRNA, 4 miRNAs and 7 mRNAs. We identified three lncRNA-miRNA-mRNA regulatory axes, namely the VCAN axis (LINC01355 - hsa-miR-186-5p / hsa-miR-30a-5p /hsa-miR-30c-5p - VCAN), LOX axis (LINC01355-hsa-miR-145-5p/hsa-miR-186-5p/ hsa-miR-30a-5p / hsa-miR-30c-5p - LOX), and CTSS axis (LINC01355 - hsa-miR-186-5p - CTSS) based on gene ontology, pathway enrichment and protein-protein interaction (PPI) network, which may play an important role in TAAD. The clinical performance of VCAN, CTSS, and LOX in TAAD diagnosis was evaluated, and the AUCs of VCAN, CTSS, and LOX were 0.920 (p<0.001), 0.880 (p=0.002) and 0.840 (p=0.011), respectively. Furthermore, mRNA expression of VCAN in human aortic tissue significantly overexpressed in the TAAD patients (p<0.001).
Conclusion: This study identifies three ceRNA interaction axes, especially VCAN associated with TAAD pathogenesis, providing fundamentals of bioinformatics for understanding the molecular mechanisms of TAAD pathogenesis and developing potential therapeutic strategies for TAAD.
期刊介绍:
The International Journal of General Medicine is an international, peer-reviewed, open access journal that focuses on general and internal medicine, pathogenesis, epidemiology, diagnosis, monitoring and treatment protocols. The journal is characterized by the rapid reporting of reviews, original research and clinical studies across all disease areas.
A key focus of the journal is the elucidation of disease processes and management protocols resulting in improved outcomes for the patient. Patient perspectives such as satisfaction, quality of life, health literacy and communication and their role in developing new healthcare programs and optimizing clinical outcomes are major areas of interest for the journal.
As of 1st April 2019, the International Journal of General Medicine will no longer consider meta-analyses for publication.