2022, Vol. 26 ›› Issue (18): 2881-2887

Screening of differential genes and validation of key genes in synovial tissue of osteoarthritis

Yao Jiawei1, Xu Xiongfeng1, Yi Peng1, Qiu Bo2   

Abstract: BACKGROUND: Osteoarthritis is a common degenerative disease. Its occurrence is related to a variety of risk factors. At present, there is no effective treatment plan other than surgical treatment. The regulatory genes related to osteoarthritis are involved in the occurrence and development of osteoarthritis. However, the gene regulatory network of osteoarthritis has not been established completely.
OBJECTIVE: To carry out the bioinformatics analysis of osteoarthritis gene chip data set, so as to find new biomarkers of osteoarthritis and experimentally verify MYC and JUN genes.
METHODS: GEO database online analysis tool GEO2R was used to screen the differential genes of GSE55457 and GSE55235 chip data. The common differential genes of the two data sets were taken for GO function enrichment analysis and pathway enrichment analysis. String database was then used to construct protein interaction network, and Cytoscape3.8.0 software was applied to obtain the key genes. Finally RT-PCR and western blot were used to detect the mRNA and protein expression of MYC and JUN genes in osteoarthritic and normal synovial tissue. Synovial specimens were taken from the synovial tissues of three patients with osteoarthritis and three patients with meniscal injuries in the Renmin Hospital of Wuhan University.
RESULTS AND CONCLUSION: The GSE55457 dataset had 704 up-regulated genes and 113 down-regulated genes; the GSE55235 dataset had 492 up-regulated genes and 723 down-regulated genes; the two together had 89 up-regulated genes and 30 down-regulated genes. Functional enrichment showed that differential genes mainly played a role in response to macrophage colony stimulation and binding glucocorticoid receptors. Pathway enrichment analysis showed that differential genes were mainly involved in the MAPK signaling pathway and amino acid metabolism. Ten key target genes were identified based on the protein-protein interaction network, including MYC, JUN, MCL1, CDKN1A, HNRNPA1, VEGFA, NCOA3, ATF3, BTG2, and CD44. Two key genes, MYC and JUN, were obtained based on the higher score of the protein-protein interaction network graph algorithm and the number of protein interaction lines. The results of RT-PCR and western blot experiments showed that the expression of MYC and JUN at mRNA and protein levels was significantly increased in osteoarthritic synovial tissue compared with the control group (mRNA: MYC P=0.035 2, JUN P=0.015 6, protein: MYC P=0.027 2, JUN P=0.026 6). To conclude, the differential genes screened by comprehensive multiple biological information databases and R language analysis are involved in the occurrence and development of osteoarthritis. The 10 key genes identified are all involved in the key link of osteoarthritis. Up-regulation of MYC and JUN can promote the occurrence of osteoarthritis, which has been verified in the RT-PCR and western blot detections.
Key words: osteoarthritis, bioinformatics, biomarkers, synovial tissue, differential gene, key gene, MYC, JUN