Bioinformatics analysis of differentially expressed genes and their potentially interacting miRNAs in oral lichen planus

Background Oral lichen planus (OLP) was a common oral mucosal disease. However, the etiology and pathogenesis of OLP were still limited. This research was designed to identify the differentially expressed genes and relative miRNAs in OLP. Methods and Results The OLP microarray dataset (GSE52130) was download from the Gene Expression Omnibus (GEO) database. R software was used to identify differentially expressed genes between the OLP samples and normal oral mucosa. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway conducted. Protein–protein interaction (PPI) network analysis was performed in the STRING database. CytoHubba in the Cytoscape software was applied to determining the top 10 hub genes, whose relative miRNA was identied through RNA Interactome Database. Overall, 627 DEGs was identied in OLP samples, including 351 highly expressed genes and 276 lowly expressed genes. GO analysis indicated that the epidermal differentiation was mostly enriched. For the KEGG pathway, the DEGs in OLP samples were mostly involved in Staphylococcus aureus infection. Top 10 hub genes were identied from the PPI network. The miRNA (hsa-miR-98-5p) was regarded as the mostly possible miRNA involved in OLP. OLP


Introduction
Oral lichen planus (OLP) was a common oral mucosal disease, and it was a chronic autoimmune disease. [1] The disease occurred more often in middle-aged people, with more women than men. [2] The typical lesions were characterized by small papules the size of a needle connected into white or off-white ne streaks, which were intertwined into a network, dendritic or ring shape. [3] Most of the lesions were symmetrical, with congestive erosion ulcers, and the most frequent site was the cheek. [4] Patients often had no symptoms. Some patients may feel rough mucous membranes, burning sensation and dry mouth, which affected eating and speech. [5] It had been observed that the incidence of OLP in the population was about 2%. [6] A recent meta-analysis showed that the incidence of OLP was different in different regions, with a slightly higher incidence in European population (1.43%) and a slightly lower incidence in Asian population (0.49%). [7] OLP might develop into malignant lesions and was classi ed as a premalignant condition by the World Health Organization. [3] However, the etiology and pathogenesis of OLP were still limited, and they were believed to be related to various factors, such as immune factors, mental factors, and infectious factors. [8] Identi cation of biomarkers of oral lichen planus would help analyze the pathogenesis and in uencing factors of different patients, and provide a basis for clinical personalized and precise treatment. [9] Changes in the expression of various genes were considered to be related to the occurrence of oral lichen planus. [10,11] But there was no biomarker that can be used as the gold standard. Therefore, there was still a need to explore reliable biomarkers.
In recent years, the development of gene microarray had provided a new perspective for studying the pathogenesis of diseases. [12] It could e ciently and quickly nd abnormally expressed genes in diseased tissues and determine disease-related biomarkers.
[13] As an emerging research method, clinical bioinformatics could identify abnormally expressed genes in diseased tissues by analyzing data obtained from high-throughput microarray and sequencing technology, which was considered to be one of the promising and key methods to help achieve early diagnosis and effective treatment. [14] This study used bioinformatics methods to perform differential gene analysis and functional cluster analysis on OLP transcription microarray from public databases. Moreover, protein-protein interaction networks and related miRNA networks were established. The aim of this research was to identify the differentially expressed genes and their potentially interacting miRNAs in OLP to provide a possible explanation of the pathogenesis of OLP and therapeutic biomarkers.

Source of data
The OLP microarray dataset (GSE52130) was download from the GEO database through the GEO query package. [15] The dataset was based on GPL10558 Illumina HumanHT-12 V4.0 expression beadchip. Altogether 14 samples including 7 OLP samples and 7 normal oral epithelium samples were incorporated in this research.
Preprocessing of data Bioconductor package (3.13 version) of R software (4.1.0) was used to preprocess the data. The probes corresponding to multiple molecules were removed. When various probes corresponded to the same molecule, only the probe with the largest signal value was reserved. Then the box diagram was conducted through ggplot2 (3.3.3 version) to estimate the standardization of the samples, and the clustering analysis between the OLP group and the normal group was conducted by umap package (0.2.7.0 version).
Differentially expressed genes analysis Linear models were tted by limma package of R software (4.1.0) to further determine the differential expressed genes (DEGs) between the OLP group and normal group. [16] DEGs were de ned as genes with adjust P-value <0.05 and |log2(FC)|>1.0.

Functional enrichment analysis of DEGs
Gene Ontology (GO) database (http://www.geneontology.org/) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (https://www.genome.jp/kegg/) were analyzed for the DEGs. P-value < 0.05 was indispensable for the GO/KEGG terms, which were determined as signi cantly enriched.
Protein-protein interaction (PPI) network analysis STRING (https://string-db.org/), a database of known and predicted PPI, was applied to the identi cation of protein interactions. Cytoscape software (3.8.2 version) was used to visualize the PPI. In addition, CytoHubba, a plug-in of Cytoscape, was used to identify the top 10 hub genes through Maximal Clique Centrality algorithm. [17] MiRNA network of top 10 hub genes RNA Interactome Database (http://www.rnainter.org/) was screened for the relevant miRNAs of top 10 hub genes. [18] The interaction score should not be lower than 0.2. The top 30 relevant miRNAs were included. The miRNAs, targeting at least 3 hub genes, were identi ed.

DEGs of OLP
The median of each sample was basically on a horizontal line, and it indicated that the degree of normalization between samples was good. (Figure 1A) The samples of each group are separated in the UMAP gure, showing that the difference between the groups was obvious. (Figure 1B Figure 4) For example, the miRNA (hsa-miR-98-5p) was found to interact with 5 hub genes (LOR, SPRR2G, LCE2B, CDSN and LCE2A). The miRNA (hsa-let-7e-5p, hsa-let-7f-5p, hsa-let-7d-5p, hsa-miR-135a-5p, hsa-miR-202-3p, hsa-miR-326, hsa-miR-708-5p, hsa-miR-330-5p, hsa-miR-28-5p) was found to interact with 3 different hub genes. (Figure 5) Discussion OLP was a common oral mucosal disease. However, the pathogenesis of OLP was unclear, and it was believed to be related to various factors. Notably, there was still a lack of effective treatment for OLP. The molecular mechanisms of OLP remained to be investigated for further identifying the potentially effective therapeutic targets. Bioinformatics was one of the promising methods to nd the abnormally expressed genes for further identi cation of therapeutic targets. In this research, we used a gene series of OLP from GEO database to nd 627 DEGs was identi ed in OLP samples, including 351 highly expressed genes and 276 lowly expressed genes. Functional enrichment analysis found the DEGs enrich in epidermis development and enzyme inhibitor activity. The function of hub genes was almost related to the corni ed cell envelope formation and epidermal barrier integrity. [19][20][21] Loricrin corni ed envelope precursor protein (LOR) encoded loricrin, which was one of major proteins in the envelope of terminally differentiated epidermal keratinocytes. [22] Mutations in LOR were related to Vohwinkel syndrome, which was de ned as palmoplantar keratoderma. [23] LOR had been found to be associated with corni ed cell envelope formation, which resulted in keratinization in the OLP lesions. [20] It was consistent with our results. However, another study had indicated that loricrin was not detected in OLP samples through immunohistochemical technique. [24] Whether LOR could be regarded as a biomarker for OLP needed more researches.
Late corni ed envelope (LCE) family included multiple genes, which encoded stratum-corneum proteins. [25] LCE genes had been found to be important in skin and upregulate under the UV light. [20] They were the precursors of the corni ed envelope of the stratum corneum. [26] Therefore, they participated in the keratinization pathway, which was involved in the pathology of OLP. [27] Moreover, LCE proteins were identi ed with antimicrobial activator to be closely connected with the innate host defense, indicating their potential function in the pathogenesis of OLP. [28] The LCE genes not only correlate to keratinization, but also involved the immune response, both of which were the possibly major etiology of OLP. Nevertheless, up to now, few studies focused on the function of LCE in the development of OLP.
Small proline rich protein (SPRR) genes encoded small proline rich proteins, which participated the epidermal differentiation complex to further constitutes the corni ed cell envelope. [29] In addition, repetin (RPTN) gene, belonging to S100 protein family, was also involved in the corni ed cell envelope formation. The LOR, LCE, SPRR and RPTN were parts of human epidermal differentiation complex (EDC). [20] The GO analysis in this study enriched the epidermal differentiation. It was indicated that upregulated or activated EDC might play a role in the pathogenesis of OLP, and the LOR, LCE, SPRR and RPTN could be further investigated.
Another bioinformatic study had indicated that high expression of laggrin (FLG) gene was related to hyperkeratosis, and ALOX12B gene could aggravate wound in the oral mucosa. [30] Moreover, FLG and ALOX12B were found to be involved in OLP. [31] FRAS1 gene was indicated to be related to separation between lamina propria and epithelium in a bioinformatic research. [31] The identi ed hub genes of OLP in previous studies were different from that in our study. [9,10] More basic researches and clinical researches were urged to prove the function of these genes in the pathogenesis of OLP.
MiRNA was a kind of endogenous non-coding RNA, extensively participating in gene post-transcriptional regulation activities. [32] MiRNA could inhibit target gene expression at protein translation level and induce the degradation of target mRNA. [33] MiR-164a and miR-21 were found to be upregulated over 2fold in the OLP samples. [34] MiR-155 targeted suppressor of cytokine signaling 1 (SOCS1) to relieve the inhibition of phosphorylated janus kinase (JAK), then signal transducer and activator of transcription (STAT) was activated to M1 polarization and Treg differentiation, which might be involved in the pathogenesis of OLP . [35] In the present study, the miRNAs related to the hub genes remained to be investigated.
Our study provided a new direction for mechanism research of OLP. The role of EDC relevant genes and corresponding miRNAs in OLP remained to be studied. Nonetheless, there were some limitations in the present research. (1) The function of hub genes and miRNAs in OLP was less studied; (2) The interaction between hub genes and miRNAs was not investigated. However, the results of this research were still meaningful, as potential biomarkers for diagnosis and treatment of OLP were provided.

Conclusions
Compared to the normal oral mucosa, genes, including LOR, LCE3D, LCE3E, LCE1B, LCE2B, SPRR2E, SPRR2G, LCE2A, RPTN and CDSN, were signi cantly highly expressed in OLP samples. These genes were parts of the EDC, referring to the potential role of EDC in the pathogenesis of OLP. Possibly functional miRNAs (hsa-miR-98-5p, hsa-let-7e-5p, hsa-let-7f-5p, etc) were also identi ed. Our results might help to identify the biomarkers of OLP. However, more basic and clinical experiments were needed to validate the role of above molecules in OLP.

Con icts of interests
No con ict of interest was involved in the present research. This research did not receive any speci c grant from funding agencies in the public, commercial, or not-for-pro t sectors.    MiRNA network of top 10 hub genes.