Research Paper Volume 13, Issue 1 pp 619—645
A three-gene signature based on tumour microenvironment predicts overall survival of osteosarcoma in adolescents and young adults
- 1 Department of Breast, Bone and Soft Tissue Oncology, the Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, China
- 2 Graduate School of Guangxi Medical University, Nanning 530021, China
- 3 Department of Bone and Soft Tissue Tumor Surgery, the Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, China
Received: June 9, 2020 Accepted: October 9, 2020 Published: December 3, 2020https://doi.org/10.18632/aging.202170
How to Cite
Copyright: © 2020 Wen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Evidences shows that immune and stroma related genes in the tumour microenvironment (TME) play a key regulator in the prognosis of Osteosarcomas (OSs). The purpose of this study was to develop a TME-related risk model for assessing the prognosis of OSs. 82 OSs cases aged ≤25 years from TARGET were divided into two groups according to the immune/stromal scores that were analyzed by the Estimate algorithm. The differentially expressed genes (DEGs) between the two groups were analyzed and 122 DEGs were revealed. Finally, three genes (COCH, MYOM2 and PDE1B) with the minimum AIC value were derived from 122 DEGs by multivariate cox analysis. The three-gene risk model (3-GRM) could distinguish patients with high risk from the training (TARGET) and validation (GSE21257) cohort. Furthermore, a nomogram model included 3-GRM score and clinical features were developed, with the AUC values in predicting 1, 3 and 5-year survival were 0.971, 0.853 and 0.818, respectively. In addition, in the high 3-GRM score group, the enrichment degrees of infiltrating immune cells were significantly lower and immune-related pathways were markedly suppressed. In summary, this model may be used as a marker to predict survival for OSs patients in adolescent and young adults.