Identification of potential biomarkers of pigmented villonodular synovitis by bioinformatics and related transcriptome analysis
Authors: Liu Yuan , Liang Xuezhen , Xu Bo , Luo Di , Li Gang 
Published: June 2022

Purpose: The purpose of this study is to identify potential biomarkers in synovial tissues of patients with pigmented villonodular synovitis (PVNS) and osteoarthritis (OA) by bioinformatics for disease differential diagnosis.Method: The synovial tissue microarray data sets related to PVNS and OA were searched by Gene Expression Omnibus (GEO) database, and the differentially expressed genes between PVNS and OA were analyzed by NetworkAnalyst (DEGs,P < 0.05). The genes related to PVNS were retrieved by TTD, OMIM, GeneCard, DrugBank and DisGeNET databases, and the final DEGs was obtained by intersection with the DEGs obtained from the dataset. Tissue / organ localization of specific genes was carried out by BioGPS. Protein-protein interaction (PPI) network was constructed by STRING database. DEGs was enriched and analyzed by KOBAS3.0 and GSEA4.1.0 in order to understand the biological function and enrichment pathway of DEGS. Multiple computing method was used to identify HUB gene. mRNA-MicroRNA (miRNA) co-expression network and competitive endogenous RNA (ceRNA) network were constructed by Cytoscape software. The biomarkers with high diagnostic value were verified by GEO sequencing data set. The biomarkers were evaluated by the receiver operating characteristic curve (ROC) curve and statistically analyzed by IBM SPSS26.0. In addition, we used the xCell website to analyze the enrichment of 64 kinds of immune and stromal cells and calculate the abundance scores.Result: A total of 2546 DEGS were identified in the GSE175626 dataset, including 2317 DEmRNAs and 229 DElncRNAs. The genes related to PVNS were found in the databases of TTD, OMIM, GeneCard, DrugBank and DisGeNET, respectively. 539 genes were obtained after deweighting. 70 DEGs were obtained after intersection with the differential DEGs obtained from the data set, of which 60 genes were identified by tissue/organ specific expression. Compared with patients with OA, DEGs in patients with PVNS was mainly enriched in biological processes such as inflammation, cell proliferation, angiogenesis and immune response in gene ontology (GO). Enrichment analysis of Kyoto Encyclopedia of Gene and Genome (KEGG) showed that DEG was mainly enriched in inflammation, osteoclast differentiation, blood and immune-related signal pathways. Through Cytoscape software "CytoHubba" plug-in screened 15 HUB genes, MCODE identified 4 gene cluster modules. Fifteen HUB genes were screened and intersected with 31 bone / muscle and haematologic/immune system specific expression genes, and 12 specifically expressed HUB genes were obtained, which were verified by GEO data set. Immune and stromal cell deconvolution analysis showed that 12 hub genes were closely related to some immune cells. IL6, TNF, CD163, KRAS, FN1, HMOX1, GAPDH, IL1B, PTPRC, MAPK1, CCR2, and NFKBIA may be potential biomarkers for the diagnosis of PVNS. SNHG14-hsa-miR-206-FN1 and XIST-hsa-miR-107-HMOX1 /CD163 may be potential RNA regulatory pathways that regulate PVNS disease progression.Conclusion:Twelve bone/muscle and haematologic /immune system specific expression hub genes IL6, TNF, CD163, KRAS, FN1, HMOX1, GAPDH, IL1B, PTPRC, MAPK1, CCR2, and NFKBIA were identified as potential biomarkers for the diagnosis and treatment of PVNS. In addition, we proposed that SNHG14-hsa-miR-206-FN1 and XIST-hsa-miR-107-HMOX1 /CD163 may be potential RNA regulatory pathways that regulate PVNS disease progression.