Co-expression Network Analysis Identifies Four Hub Genes Associated With Prognosis in Soft Tissue Sarcoma

Abstract

BACKGROUD: Soft tissue sarcomas (STS) are heterogeneous tumors derived from mesenchymal cells that differentiate into soft tissues. The prognosis of patients who present with an STS is influenced by the regulation of a complex gene network. METHODS: Weighted gene co-expression network analysis (WGCNA) was performed to identify gene modules associated with STS (Samples = 156). RESULTS: Among the 11 modules identified, the black and blue modules were highly correlated with STS. However, using preservation analysis, the black module demonstrated low preservation, therefore the blue module was chosen as the module of interest. Furthermore, a total of 20 network hub genes were identified in the blue module, 12 of which were also hub nodes in the protein-protein interaction network of the module genes. Following additional verification, 4 of 12 genes (RRM2, BUB1B, CENPF and KIF20A) demonstrated poorer overall survival and disease-free survival rate in the test datasets. In addition, gene set enrichment analysis (GSEA) demonstrated that samples with a high level of blue module eigengene (ME) were enriched in cell cycle and metabolism associated signaling pathways. CONCLUSION: In summary, co-expression network analysis identified four hub genes associated with prognosis for STS, which may diminish the prognosis by influencing cell cycle and metabolism associated signaling pathways.