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Mingyi Yang,1,* Haishi Zheng,1,* Yani Su,2,* Ke Xu,1 Qiling Yuan,1 Yirixiati Aihaiti,1 Yongsong Cai,1 Peng Xu1 1Department of Joint Surgery, HongHui Hospital, Xi’an Jiaotong University, Xi’an, Shanxi, 710054, People’s Republic of China; 2Yan’an University Affiliated Hospital, Yan’an, Shanxi, 716000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Peng Xu, HongHui Hospital, Xi’an Jiaotong University, No. 555, Youyi East Road, Beilin District, Xi’an City, Shaanxi Province, 710054, People’s Republic of China, Tel +86 13772090019, Email sousou369@163.comObjective: Rheumatoid arthritis (RA) is a nonspecific, chronic, systemic autoimmune disease characterized by symmetric polyarticular synovitis. Bioinformatics analysis of potential biomarkers, mRNA–miRNA–lncRNA axes, and signaling pathways in the pathogenesis of RA provides potential targets and theoretical basis for further research on RA.Methods: The GSE1919 and GSE77298 datasets were downloaded from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo). Perl was used to perform data merging, and R was used to perform batch correction. The “limma” package of R was used to screen differentially expressed genes, and the “clusterProfiler” package was used to perform enrichment analysis of the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Search Tool for the Retrieval of Interacting Genes/Proteins was used to construct the protein–protein interaction network, Cytoscape was used for module analysis, and R was used to screen for hub genes. GraphPad Prism was used to plot the receiver operating characteristic curve of the hub genes. Gene set enrichment analysis and competitive endogenous RNA network analysis were performed on hub genes with the greatest diagnostic values. The hub gene with the greatest diagnostic value was verified using immunohistochemical staining.Results: We obtained nine hub genes (ITGB2, VAMP8, HLA-A, PTAFR, SYK, FCER1G, HLA-DPB1, LCP2, and ACTR2) and four mRNA–miRNA–lncRNA axes (ITGB2-hsa-miR-486-3p-SNHG3, ITGB2-hsa-miR-338-5p-XIST, ITGB2-hsa-miR-5581-3p-XIST, and ITGB2-hsa-miR-1226-5p-XIST) related to the pathogenesis of RA. The nine hub genes were highly expressed, and ITGB2 had the highest diagnostic value for RA. We also identified signaling pathways related to the pathogenesis of RA: Fc epsilon Rl and chemokine signaling pathways. The immunohistochemical results showed that ITGB2 expression was significantly upregulated in RA.Conclusion: The hub genes, mRNA–miRNA–lncRNA axes, and signaling pathways related to RA pathogenesis identified in this study provide a new research direction for the mechanism, diagnosis, and treatment of RA.Keywords: rheumatoid arthritis, synovial, genes, lncRNA

Purpose This article aimed to investigate the mechanism by which MALAT1 and miR-129 affected the development of osteosarcoma. Methods Tumor tissues and adjacent tissues of 23 osteosarcoma patients were collected. Normal osteoblasts hFOB1.19 and osteosarcoma cells MG63 were cultured. MG63 cells were transfected and grouped: si-negative control (NC) group, si-MALAT1 group, miR-129 NC group, miR-129 mimics group, p-Empty vector group, p-MALAT1 group, p-MALAT1+ miR-129 mimics group, and p-MALAT1+ si-TGIF2 group. Luciferase reporter assay, Cell Counting Kit-8 assay, Transwell assay, quantitative reverse transcription PCR, Western blot, and Pearson correlation analysis were performed. Results MALAT1 expression in tumor tissues and MG63 cells was increased (P