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Purpose: Osteosarcoma is one of the most prevalent malignancies, and despite significant advances in its treatment, patient prognosis remains poor and survival rates are low. It is undoubtedly important to explore the possible reasons for the low survival rates of patients and to reveal the differences.Methods and Results: We obtained RNA-Seq (HT seq) and clinical characteristics of osteosarcoma patients from the TCGA database and divided them into survival group and death group. We defined the differentially expressed genes (DEGs) between the two groups as death-related genes (DRGs) and used them to construct a prognostic signature for overall survival of patients with osteosarcoma. The results of the validation demonstrated satisfactory accuracy and predictive prognostic value of the model. In addition, we performed a series of bioinformatic analyses that identified two key genes and the regulatory networks they constituted that may play a role in the progression of osteosarcoma.Conclusion: Our DRGs signature represents a novel and clinically useful prognostic biomarker for patients with osteosarcoma, helping to aid clinical decision-making.

Osteosarcoma (OS) is one of the most prevalent malignancies with a bad prognosis. Oxidative stress is closely associated with various type of cancer. The present study aimed to establish an oxidative stress-related gene prognostic signature. Supported by The Cancer Genome Atlas and Gene Expression Omnibus, the least absolute shrinkage and selection operator regression, Cox regression, receiver operating characteristic curves and Kaplan-Meier survival analysis were used to construct and validate a prognostic signature and the derived risk score. Tumor microenvironment scores and immune infiltration levels in OS were calculated. Correlation between these parameters and risk score was analyzed. In addition, single analysis of each hub gene was performed. Finally, a series of molecular experiments was used to detect the role of MAP3K5 (one of the hub genes) in OS. A total of five genes most associated with OS prognosis were identified as independent predictors, namely catalase (CAT), mitogen-activated protein kinase 1 (MAPK1), glucose-6-phosphate dehydrogenase (G6PD), mitogen-activated protein kinase kinase kinase 5 (MAP3K5) and C-C motif chemokine ligand 2 (CCL2). Based on the signature, higher risk score indicated poorer prognosis. Nomogram performed well and reliably predicted 3-and 5-year survival rate in OS. Patients with increasing risk scores had higher tumor purity and lower immune infiltration levels. Compared with an osteoblast cell line, the expression of CAT, CCL2, MAPK1 and G6PD was upregulated and MAP3K5 was downregulated. MAP3K5 inhibited cellular proliferation and motility, promoted cellular apoptosis and induced reactive oxygen species generation. Overall, the signature could effectively predict the prognosis of patients with OS and were expected to be potential biomarkers. And it provided new ideas for understanding the interactions between oxidative stress and OS.