The Signature of Glycometabolism-Related Genes in Predicting the Prognosis of Patients with Osteosarcoma

Background Osteosarcoma is a primary malignant bone tumor with high metastatic potential and an inferior prognosis. Glycometabolism also plays a role in the disease. However, the clinical significance of glycometabolism-related genes in patients with osteosarcoma has been unclear. Methods We downloaded the expression profile and corresponding clinical data of osteosarcoma samples from database. Glycometabolism-related gene sets were obtained. Regression analyses were performed to construct a glycometabolism-related prognostic gene signature. The. independent prognostic value of the signature was further assessed by univariate and multivariate Cox regression analysis, and the correlation between immune cells and the signature was investigated. The regulatory mechanism of the prognostic genes was explored by constructing a ceRNA network. Results A glycometabolism-related prognostic gene signature based on PRKACB, SEPHS2, GPX7, and PFKFB3 was constructed, and the survival and receiver operating characteristic curves showed that the glycometabolism-related gene signature had a good performance in predicting the overall survival of patients with osteosarcoma. Univariate and multivariate Cox regression analyses confirmed that the glycometabolism-related gene signature was an independent prognostic factor among patients. Correlation analysis revealed that SEPHS2, PRKACB, and GPX7 were correlated with immune cells. A ceRNA network comprised of four genes, 148 miRNAs, and 91 lncRNAs was constructed. Conclusions A novel signature based on four glycometabolism-related genes, was constructed, which may facilitate the prognosis and treatment of osteosarcoma in clinical practice.