Establishment Of Key Genes And Associated Outcomes In Osteosarcoma Patients Using Bioinformatics Methods

Background: Osteosarcoma (OS) is a highly malignant bone tumor with a poor prognosis and it mainly occurs in children and adolescents. This condition results from a series of molecular events, including somatic mutations, epigenetic alterations, and aberrant protein expression. Patients and methods: In this study, we obtained RNA sequencing and clinical characteristic data from OS patients from the TARGET database. EdgeR package was applied to identify differentially expressed RNAs. Thereafter, a COX regression model was established to identify the key genes correlated to survival. Based on the results of the multi-COX regression model, the risk model was established to assign OS patients to high-risk and low-risk groups. Lastly, the risk model was verified by the receiver operating characteristic curves involved in the development and progression of OS. Results: RNAs that were differentially expressed among 69 metastatic samples and 210 non-metastatic samples were evaluated using the edgeR model. The COX regression model (with high sensitivity and specificity) and Kaplan-Meier (K-M) analyses were used to establish a model of survival. Thereafter, 131 differentially expressed RNAs (DEGs) were detected in this study. Single and multiple factor COX analyses showed that 10 genes were involved in the prognosis of OS. The K-M analysis identified a total of six genes (ARX, DDN, MYC, NNAT, TAC4, and TRPM5) that were closely related to the prognosis of OS patients. Conclusion: This study found six genes related to the prognosis of OS through R Software analysis and further verified by COX regression models. The results of this study provide important information for further research in the direction of OS treatment.