A Novel Overall Survival Prediction Signature Based on Cancer Stem Cell-Related Genes in Osteosarcoma - Xiao, Bo; Liu, Liyan; Chen, Zhuoyuan; Li, Aoyu; Xia, Yu; Wang, Pingxiao; Xiang, Cheng; Zeng, Yi; Li, Hui (Frontiers in Cell and Developmental Biology, 2021)
Background: Osteosarcoma is the most general bone malignancy that mostly affects children and adolescents. Numerous stem cells-related genes have been founded in distinct forms of cancer. This study aimed at identifying a stem cell-related gene model for the expected assessment of osteosarcoma patients' prognosis. Methods: We obtained the genes expression data and relevant clinical materials from TARGET and GEO databases. We identified differentially expressed genes (DEGs) from the GEO dataset, whereas prognostic stem cells-related genes were obtained from the TARGET database. Subsequently, univariate, LASSO and multivariate Cox regression analyses were applied to establish the stem cells-related signature. Finally, the prognostic value of the signature was validated in GEO dataset. Results: 25 genes were prognostic ferroptosis-related DEGs. Consequently, we identified eight stem cells-related genes as a signature of prognosis about osteosarcoma patients. Then, the K-M curve, the AUC value of ROC, Cox regression analysis verified that the eight stem cells-related genes model was a new and substantial prognostic marker independent of other clinical traits. Moreover, the nomogram on the foundation of risk score and other clinical traits was established for predicting the osteosarcoma patients’ survival rate. Biological functions analyses displayed that tumor-related and pathways were affluence. Conclusion: The expression level of stem cells-related genes offers novel prognostic markers as well as underlying therapeutic targets for the therapy and prevention of osteosarcoma.