Circular RNA expression pattern and competing endogenous RNA network involved in rotator cuff tendinopathy
10.7507/1002-1892.201911094
- Author:
Zilu GE
1
Author Information
1. Department of Orthopeadics/Sports Medicine Center, First Affiliated Hospital of the Army Medical University
- Publication Type:Journal Article
- Keywords:
circular RNA;
competing endogenous RNA;
profile;
RNA-sequence;
Rotator cuff tendinopathy
- From:
Chinese Journal of Reparative and Reconstructive Surgery
2020;34(5):608-614
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To detect the differentially expressed circular RNA (circRNA) in rotator cuff tendinopathy and analyze the potential molecular mechanism of these parental genes. Methods: Ten supraspinatus tendons donated from patients who underwent tendon repair surgery between June 2018 and June 2019 were used for RNA-sequence. All rotator cuff tendinopathy and normal tendon samples were confirmed by MRI, histological staining, and observation by arthroscopy. All pathological tendons were matched with tendon samples for patients' age, gender, body mass index, and Bonar score. The bioinformatic analysis was performed based on the differentially expressed circRNA and their parental genes, including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and competing endogenous RNA (ceRNA) network construction. Results: There were 94 differentially expressed circRNAs, including 31 up-regulated and 63 down-regulated, detected between the rotator cuff tendinopathy and normal tendon samples with |log2 fold change (FC)| >2, P<0.05. GO analysis showed that the genes were mostly enriched in response to cyclic adenosine monophosphate (cAMP). KEGG pathway analysis showed that the most genes were enriched in extracellular matrix-receptor interaction, protein digestion and absorption, cell cycle, and nuclear factor κB signaling pathway. ceRNA networks showed the interactions among circRNAs, mRNAs, and miRNAs. And circRNA.8951-has-miR-6089-DNMT3B was the most sum max energy. Conclusion: This bioinformatic study reveals several potential therapeutic targets for rotator cuff tendinopathy, which paves the way to better treatment and prevention of this disorder.
