Journal of Oral Science Research ›› 2022, Vol. 38 ›› Issue (8): 768-772.DOI: 10.13701/j.cnki.kqyxyj.2022.08.014

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Differential Expression Profiles and Difference Analysis of MicroRNAs in Tissues of Patients with Oral Lichen Planus were Screened by High-throughput Sequencing

LIU Jian*, LI Tiancui, WU Jingjing, YAO Manman, XU Yanzhi, LI Jingzhe   

  1. Department of Stomatology, the Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China
  • Received:2021-12-16 Online:2022-08-28 Published:2022-08-24

Abstract: Objective: To explore the role of microRNAs (miRNAs) in the pathogenesis of oral lichen planus (OLP). Methods: The tissues of 3 OLP patients (experimental group) and 3 normal individual (control group) were collected in the Department of Stomatology of the Fourth Hospital of Hebei Medical University for illumina high-throughput sequencing to screen the differentially expressed miRNAs. The target genes were predicted and analyzed by bioinformatics analyses. Results: A total of 61 differentially expressed miRNAs were screened between the two groups by using DESeq software, including 23 up-regulated and 38 down-regulated miRNAs. Three of the most significantly up-regulated (miR-449c-5p, miR-663b, and miR-196a-5p) and down-regulated (miR-133b, miR-1-3p, and miR-133a-3p) miRNAs were selected for target gene prediction, and GO analysis revealed that these targets were mainly enriched in the cell membrane region and might be involved in biological processes such as cell migration, differentiation, metabolism, and secretion regulation. KEGG analysis revealed that these targets were significantly enriched in MAPK, Rap1, NF-κB, Ras, and other signaling pathways. Conclusion: There are differentially expressed miRNAs between OLP and normal oral mucosa, and these miRNAs can act on MAPK, NF-κB, Rap1 and other pathways through SEMA3F, HECW1, POLDIP and other target genes to participate in the development and progression of OLP.

Key words: oral lichen planus, high-throughput nucleotide sequencing, microRNAs, bioinformatics analyses