Identification of genes that influence poor prognosis in osteosarcoma

Objectives: Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. At present, the 5-year overall survival rate of OS patients is about 65%, and the long-term prognosis is still not ideal. The study was designed to screen genes that could contribute to the poor prognosis of OS and explore their potential pathogenic mechanisms. Methods: The gene expression profile of the GSE94805 dataset from the GEO database, containing data from 12 U2OS cell samples, including four control, four quiescent, and four senescent samples was obtained. Co-expressed differentially expressed genes (DEGs) in OS U2OS cells were selected using the GEO2R tool and Venn diagram analysis. Next, using the STRING, Cytoscap, and Molecular Complex Detection (MCODE) plug-in, the related protein-protein interaction network among upregulated genes was analyzed. Moreover, Kaplan-Meier plots were used to analyze the relationship between the identified genes and OS prognosis. Genes significantly associated with worse prognosis were evaluated using the Gene Expression Profiling Interactive Analysis. Results: Thirteen genes were confirmed to be significantly more expressed in OS than in normal tissues. Five genes ( AURKB, EXO1, KIF4A, KIF15, and MCM4 ) were found to influence OS prognosis. Conclusion: We identified five core genes related to the prognosis of OS and constructed a clinical prediction model for OS. Our data may provide a reference for future research on mechanisms, clinical diagnosis, and treatment of OS.