Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension
Objective:. Pulmonary arterial hypertension (PAH) is a cardiovascular disease caused by primary proliferative lesions in pulmonary arterioles. Competing endogenous RNAs (ceRNAs) have been reported to act as sponges for microRNAs (miRNAs). To date, however, the mechanisms underlying ceRNA involvement...
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| Format: | Article |
| Language: | English |
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Wolters Kluwer Health/LWW
2023-06-01
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| Series: | Cardiology Discovery |
| Online Access: | http://journals.lww.com/10.1097/CD9.0000000000000091 |
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| _version_ | 1850265772416303104 |
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| author | Xiao Jin Ling Jin Li Han Shiping Zhu |
| author_facet | Xiao Jin Ling Jin Li Han Shiping Zhu |
| author_sort | Xiao Jin |
| collection | DOAJ |
| description | Objective:. Pulmonary arterial hypertension (PAH) is a cardiovascular disease caused by primary proliferative lesions in pulmonary arterioles. Competing endogenous RNAs (ceRNAs) have been reported to act as sponges for microRNAs (miRNAs). To date, however, the mechanisms underlying ceRNA involvement in PAH have not been investigated. This study aimed to construct a PAH-related ceRNA network to further explore the mechanisms of PAH.
Methods:. A probe reannotation was conducted to identify the long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in PAH. Based on the reannotation results, the “limma” package was used to identify the differentially expressed genes (DEGs) and lncRNAs. The miRcode database was used to predict the lncRNA–miRNA interactions. Then, the mRNAs targeted by the miRNAs were predicted by using TargetScan, miRTarBase, and miRDB. Based on the above interactions, a ceRNA network was constructed, which was mapped and visualized with Cytoscape 3.6.1 software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the database. To predict possible drugs or molecules that may mitigate PAH, C-Map analysis was applied to find relevant molecular compounds that can reverse the expression of DEGs in cell lines.
Results:. The ceRNA network consisted of 174 nodes and 304 links, which included 10 lncRNAs, 23 miRNAs, and 53 mRNAs. The hub genes of the ceRNA network for PAH included hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p. Calprotectin, irinotecan, and medrysone were found to be the 3 significant compounds.
Conclusion:. This study found that hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p maybe the underlying biomarkers and targets for diagnosis and treatment of PAH. |
| format | Article |
| id | doaj-art-687e6a22afdb4e42951cd75a79ce51d5 |
| institution | OA Journals |
| issn | 2096-952X 2693-8499 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | Wolters Kluwer Health/LWW |
| record_format | Article |
| series | Cardiology Discovery |
| spelling | doaj-art-687e6a22afdb4e42951cd75a79ce51d52025-08-20T01:54:19ZengWolters Kluwer Health/LWWCardiology Discovery2096-952X2693-84992023-06-0132859410.1097/CD9.0000000000000091202306000-00003Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial HypertensionXiao Jin0Ling Jin1Li Han2Shiping Zhu3Department of Traditional Chinese Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, China.Department of Traditional Chinese Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, China.Department of Traditional Chinese Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, China.Department of Traditional Chinese Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, China.Objective:. Pulmonary arterial hypertension (PAH) is a cardiovascular disease caused by primary proliferative lesions in pulmonary arterioles. Competing endogenous RNAs (ceRNAs) have been reported to act as sponges for microRNAs (miRNAs). To date, however, the mechanisms underlying ceRNA involvement in PAH have not been investigated. This study aimed to construct a PAH-related ceRNA network to further explore the mechanisms of PAH. Methods:. A probe reannotation was conducted to identify the long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in PAH. Based on the reannotation results, the “limma” package was used to identify the differentially expressed genes (DEGs) and lncRNAs. The miRcode database was used to predict the lncRNA–miRNA interactions. Then, the mRNAs targeted by the miRNAs were predicted by using TargetScan, miRTarBase, and miRDB. Based on the above interactions, a ceRNA network was constructed, which was mapped and visualized with Cytoscape 3.6.1 software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the database. To predict possible drugs or molecules that may mitigate PAH, C-Map analysis was applied to find relevant molecular compounds that can reverse the expression of DEGs in cell lines. Results:. The ceRNA network consisted of 174 nodes and 304 links, which included 10 lncRNAs, 23 miRNAs, and 53 mRNAs. The hub genes of the ceRNA network for PAH included hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p. Calprotectin, irinotecan, and medrysone were found to be the 3 significant compounds. Conclusion:. This study found that hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p maybe the underlying biomarkers and targets for diagnosis and treatment of PAH.http://journals.lww.com/10.1097/CD9.0000000000000091 |
| spellingShingle | Xiao Jin Ling Jin Li Han Shiping Zhu Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension Cardiology Discovery |
| title | Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension |
| title_full | Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension |
| title_fullStr | Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension |
| title_full_unstemmed | Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension |
| title_short | Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension |
| title_sort | bioinformatics analysis of the regulatory lncrna mirna mrna network and drug prediction in patients with pulmonary arterial hypertension |
| url | http://journals.lww.com/10.1097/CD9.0000000000000091 |
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