Journal of Hebei Medical University ›› 2023, Vol. 44 ›› Issue (11): 1260-1266.doi: 10.3969/j.issn.1007-3205.2023.11.004

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The expression profile analysis of microRNAs in oral lichen planus tissues and the serological expression of three miRNAs

  

  1. 1.Department of Stomatology, the First Hospital of Hebei Medical University, Shijiazhuang 
    050030, China; 2.Department of Stomatology, the Fourth Hospital of Hebei Medical 
    University, Shijiazhuang 050011, China

  • Online:2023-11-25 Published:2023-12-05

Abstract: Objective It has been found that microRNAs (miRNAs) play an important role in immune regulation of oral lichen planus(OLP). This study aimed to obtain the expression profile of miRNAs in OLP and to explore the possible role of miRNAs in the pathogenesis of OLP and whether they can be used as potential diagnostic markers of OLP. 
Methods Three pathologically confirmed OLP lesions(sequencing OLP group) and three normal oral mucosa(sequencing control group) were collected. The differentially expressed miRNAs between two groups were screened by Illumina high-throughput sequencing. Three miRNAs with large differential multiples and high expression abundance were selected for target gene prediction and functional enrichment analysis. Moreover, 30 patients with OLP (validation OLP group) and 20 healthy volunteers (validation control group) were recruited. The expression levels of three miRNAs in serum were detected by real-time quantitative PCR (RT-PCR). Then validation OLP group was divided into erosion group (n=20) and non-erosion group (n=10). The relationship between the expression of three miRNAs and the severity of OLP was analyzed. Pearson correlation coefficient was used to analyze the correlation of the three miRNAs, and receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of the three in OLP. 
Results A total of 61 differentially expressed miRNAs between two groups were screened by DESeq software, including 23 up-regulated and 38 down-regulated miRNAs. Eighty-seven target genes (LIMD1, MOB1B, and TEAD1) co-acted by miR-142-3p, miR-146a-5p and miR-150-5p were predicted by Miranda database. Gene ontology (GO) analysis showed that these target genes were closely related to intercellular connectivity components and signal transmission.Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these target genes were significantly enriched in the Hippo signaling pathway. Consistent with the sequencing results, the expressions of miR-142-3p, miR-146a-5p and miR-150-5p in the validation OLP group were higher than those of the validation control group (P<0.05). The validation OLP group was further divided into erosion group and non-erosion group. The expression levels of miR-146a-5p and miR-150-5p in the non-erosion group were higher than those in the validation control group, and the difference was statistically significant (P<0.05). There was no statistically significant difference in the expression levels of miR-142-3p between two groups (P>0.05). The expression levels of miR-142-3p, miR-146a-5p, and miR-150-5p in the erosion group were higher than those in the validation control group (P<0.05), and there was no significant difference in the expression levels of three miRNAs between the erosion group and the non-erosion group (P>0.05). Pearson analysis showed that there was a high positive correlation between the expression of the three (r=0.865, 0.822 and 0.875, respectively (P<0.01). The ROC curve analysis showed that the AUC under the ROC curve (AUC) of serum miR-142-3p, miR-146a-5p and miR-150-5p were 0.711, 0.818 and 0.767 respectively, and the AUC of combined diagnosis of OLP was 0.834. 
Conclusion Differentially expressed miRNAs are present between DLP and normal oral mucosa. The expressions of miR-142-3p, miR-146a-5p and miR-150-5p are up-regulated in OLP, and their expression levels are related to the severity of OLP. miR-142-3p, miR-146a-5p and miR-150-5p can be used as potential diagnostic markers of OLP. 


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