Abstract
Synovial sarcoma (SS) is a highly aggressive soft tissue tumor with high risk of local recurrence and metastasis. However, the mechanisms underlying SS metastasis are still largely unclear. The purpose of this study is to screen metastasis-associated biomarkers in SS by integrated bioinformatics analysis. Two mRNA datasets (GSE40018 and GSE40021) were selected to analyze the differentially expressed genes (DEGs). Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), functional and pathway enrichment analyses were performed for DEGs. Then, the protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. The module analysis of the PPI network and hub genes validation were performed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the hub genes were performed using WEB-based GEne SeT AnaLysis Toolkit (WebGestalt). The expression levels and survival analysis of hub genes were further assessed through Gene Expression Profiling Interactive Analysis (GEPIA) and the Kaplan-Meier plotter database. In total, 213 overlapping DEGs were identified, of which 109 were upregulated and 104 were downregulated. GO analysis revealed that the DEGs were predominantly involved in mitosis and cell division. KEGG pathways analysis demonstrated that most DEGs were significantly enriched in cell cycle pathway. GSEA revealed that the DEGs were mainly enriched in oocyte meiosis, cell cycle and DNA replication pathways. A key module was identified and 10 hub genes (CENPF, KIF11, KIF23, TTK, MKI67, TOP2A, CDC45, MELK, AURKB, and BUB1) were screened out. The expression and survival analysis disclosed that the 10 hub genes were upregulated in SS patients and could result in significantly reduced survival. Our study identified a series of metastasis-associated biomarkers involved in the progression of SS, and may provide novel therapeutic targets for SS metastasis.
Highlights
Synovial sarcoma (SS) ranks the fourth most common form of soft tissue sarcoma (STS), comprising nearly 10% of total STSs worldwide
We identified 213 differentially expressed genes (DEGs) that were associated with SS metastasis from the GSE40018 and GSE40021 datasets, including 109 upregulated and 104 downregulated genes
According to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the 213 DEGs, DEGs were found to be significantly enriched in mitosis, cell division and cell cycle pathway
Summary
Synovial sarcoma (SS) ranks the fourth most common form of soft tissue sarcoma (STS), comprising nearly 10% of total STSs worldwide. SS harbors the unique chromosomal translocation t(X;18) (p11.2; q11.2) which results in the formation of a fusion protein, SS18SSX (Svejstrup, 2013). It has been demonstrated that the SS18SSX fusion protein is the oncogenic driver in the development of SS (Nagai et al, 2001). The underlying mechanism is considered to be that this fusion protein preferentially affects the cell growth, cell proliferation, cell invasion and metastasis, TP53 pathway, and chromatin remodeling mechanisms (Przybyl et al, 2012). Despite the improvements in these treatments in the past two decades, about 49% of SS patients eventually develop local recurrence and/or distant metastasis (Krieg et al, 2011). It is urgent to identify the molecules that regulate SS metastasis, which would provide novel therapeutic targets for the treatment of SS
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