Identification of potential prognostic markers for osteosarcoma by integrated analysis

Abstract

Background: Osteosarcoma (OS) is the most common type of musculoskeletal malignant tumor, accounting for over 30% of primary skeletal sarcomas. Although great efforts have been made, the mechanism of OS still remains largely unknown. In this study, we aim to identify gene modules and representative candidate biomarkers for clinical diagnosis of patients with OS, and reveal the mechanisms of OS progression.Methods: Weighted gene co-expression network analysis (WGCNA) was conducted to construct a co-expression network and investigate the relationship between modules and clinical traits. Functional enrichment analysis was performed on module genes. Protein-protein interaction (PPI) network was constructed to identify the hub gene and the expression level of hub genes was validated based on another dataset.Results: A total of 9854 genes were included in WGCNA, and 17 gene modules were constructed. Gene module related with OS in sacrum was mainly enriched in skeletal system development, bone development and extracellular structure organization. Furthermore, we screened the top 10 hub genes and further validated 5 of the 10 (MMP13, DCN, GNG2, PCOLCE and RUNX2), the expression of which were upregulated as compared with normal tissues.Conclusion: The hub gene we identified show great promise as prognostic markers for the management of OS and our findings also provide new insight for molecular mechanism of OS.