The Prognostic Model Established by the Differential Expression Genes Based on CD8+ T Cells to Evaluate the Prognosis and the Response to Immunotherapy in Osteosarcoma

• Published in: Mediators of inflammation Vol. 2023; pp. 6563609 - 11
• Main Authors: Chen, Yu, Yan, Wei, Wang, Hongqing, Ou, Zhiliang, Chen, Huihong, Huang, Zhenhua, Yang, Jinlian, Liu, Biqiong, Ou, Fanjie, Zhang, Huang
• Format: Journal Article
• Language: English
• Published: United States Hindawi 09.02.2023; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Analysis; Bone cancer; Bone Neoplasms; Brain cancer; CD8 antigen; CD8-Positive T-Lymphocytes; Cells; Cluster analysis; Datasets; Genes; Humans; Immune checkpoint inhibitors; Immunotherapy; Lymphocytes; Lymphocytes T; Medical prognosis; Monoclonal antibodies; Osteosarcoma; Prognosis; Risk factors; RNA sequencing; Sarcoma; T cells; Tumors; China; Taiwan
• ISSN: 0962-9351; 1466-1861
• DOI: 10.1155/2023/6563609

Osteosarcoma (OS) is a malignant tumor with an extremely poor prognosis, especially in progressive patients. Immunotherapy based on immune checkpoint inhibitors (ICIs) is considered to be a promising treatment option for OS. Due to tumor heterogeneity, only a minority of patients benefit from immunotherapy. Therefore, it is urgent to explore a model that can accurately assess the response of OS to immunotherapy. In this study, we obtained the single-cell RNA sequencing datasets of OS patients from public databases and defined 34 cell clusters by dimensional reduction and clustering analysis. PTPRC was applied to identify immune cell clusters and nonimmune cell clusters. Next, we performed clustering analysis on the immune cell clusters and obtained 25 immune cell subclusters. Immune cells were labeled with CD8A and CD8B to obtain CD8+ T cell clusters. Meanwhile, we extracted the differentially expressed genes (DEGs) of CD8+ T cell clusters and other immune cell clusters. Furthermore, we constructed a prognostic model (CD8-DEG model) based on the obtained DEGs of CD8+ T cells, and verified the excellent predictive ability of this model for the prognosis of OS. Moreover, we further investigated the value of the CD8-DEG model. The results indicated that the risk score of the CD8-DEG model was an independent risk factor for OS patients. Finally, we revealed that the risk score of the CD8-DEG model correlates with the immune profile of OS and can be used to evaluate the response of OS to immunotherapy. In conclusion, our study revealed the critical role of CD8 cells in OS. The risk score model based on CD8-DEGs can provide guidance for prognosis and immunotherapy of OS.