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Fan R, Hu D, Wang M, Zheng H, Zhou Y, Zhang L. Integrated analysis of circRNA-associated ceRNA network in ischemic stroke. Front Genet 2023; 14:1153518. [PMID: 37323662 PMCID: PMC10267749 DOI: 10.3389/fgene.2023.1153518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 05/18/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction: Stroke, of which ischemic stroke (IS) is the major type, is the second leading cause of disability and death worldwide. Circular RNAs (circRNAs) are reported to play important role in the physiology and pathology of IS. CircRNAs often act as competing endogenous RNA (ceRNA) to regulate gene expression by acting as miRNA sponges. However, whole transcriptome-wide screenings of circRNA-mediated ceRNA networks associated with IS are still lacking. In the present study, we constructed a circRNA-miRNA-mRNA ceRNA network by whole transcriptome-wide analysis. Methods: CircRNAs, miRNAs and mRNAs expression profiles were downloaded from the Gene Expression Omnibus (GEO) datasets. We identified differentially expressed (DE) circRNAs, miRNAs, and mRNAs in IS patients. StarBase and CircBank databases were used to predict the miRNA targets of DEcircRNAs, and mirDIP database was used to predict the mRNA targets of DEmiRNAs. CircRNA-miRNA pairs and miRNA-mRNA pairs were established. Then, we identified hub genes via protein-protein interaction analysis and constructed a core ceRNA sub-network. Results: In total, 276 DEcircRNAs, 43 DEmiRNAs, and 1926 DEmRNAs were explored. The ceRNA network included 69 circRNAs, 24 miRNAs, and 92 mRNAs. The core ceRNA subnetwork included hsa_circ_0011474, hsa_circ_0023110, CDKN1A, FHL2, RPS2, CDK19, KAT6A, CBX1, BRD4, and ZFHX3. Discussion: In conclusion, we established a novel hsa_circ_0011474 - hsa-miR-20a-5p/hsa-miR-17-5p - CDKN1A ceRNA regulatory axis associated with IS. Our findings provide new insights into the pathogenesis of IS and offer promising diagnostic and predictive biomarkers.
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Affiliation(s)
- Rongli Fan
- Zhejiang Provincial Key Laboratory for Chemical and Biological Processing Technology of Farm Products, Department of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
| | - Die Hu
- Zhejiang Provincial Key Laboratory for Chemical and Biological Processing Technology of Farm Products, Department of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
| | - Maiqiu Wang
- Zhejiang Provincial Key Laboratory for Chemical and Biological Processing Technology of Farm Products, Department of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
| | - Huilin Zheng
- Zhejiang Provincial Key Laboratory for Chemical and Biological Processing Technology of Farm Products, Department of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
| | - Yifeng Zhou
- Zhejiang Provincial Key Laboratory for Chemical and Biological Processing Technology of Farm Products, Department of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
| | - Lei Zhang
- Zhejiang Provincial Key Laboratory for Chemical and Biological Processing Technology of Farm Products, Department of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
- Department of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
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