Integrated bioinformatics analysis identifies hub genes and pathways involved in the metastasis of synovial sarcoma.

Background: Synovial sarcoma (SS) is rare tumor with high mortality due to early metastasis. Intense efforts have been made to elucidate mechanisms underlying SS development and progress, however, the molecular mechanisms of SS remain poorly understood. Method: Publicly available databases of SS were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in SS are screened using the PERL programming language, and it was analyzed by gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG). Protein-protein interaction (PPI) network of DEGs was analyzed by STRING online database, and Cytoscape software was used for visualizing PPI network. We used CytoHubba in Cytoscape to screen out hub genes in DEGs. Survival analysis of hub genes was conducted using GEPIA and Kaplan-Meier Plotter online database. Result: 165 DEGs were identified, consisting of 102 upregulated genes and 63 downregulated genes. Functional analysis showed that: these DEGs are associated with nuclear division, mitotic nuclear division, chromosome segregation and other functions. These DEGs are mainly associated with cell cycle, staphylococcus aureus infection, p53 signaling pathway, Th1 and Th2 Cell differentiation, and cell adhesion molecules pathway. Through module analysis of PPI network, we identified 5 hub genes. Subsequently, the online database was used to further verify and analyze the expression and prognosis of the five hub genes in SS. Conclusion: This study analyzed the DEGs between SS and metastatic SS, which is helpful for us to systematically understand the pathogenesis of SS metastasis. CDK1, BUB1, BUB1B, KIF20A and TOP2A genes may be used as potential targets to improve diagnostic and immunotherapeutic biomarkers for SS.