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

Author:

Chen Yu1ORCID,Yan Wei2ORCID,Wang Hongqing3ORCID,Ou Zhiliang1ORCID,Chen Huihong1ORCID,Huang Zhenhua4ORCID,Yang Jinlian5ORCID,Liu Biqiong6ORCID,Ou Fanjie6ORCID,Zhang Huang1ORCID

Affiliation:

1. The Third Department of Surgery, Xianyou County General Hospital, Putian, Fujian, China

2. Xianyou County General Hospital, Putian, Fujian, China

3. The Second Orthopedic Rehabilitation Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China

4. The Department of Neurosurgery, Xianyou County General Hospital, Putian, Fujian, China

5. Pulmonary and Critical Care Medicine, Xianyou County General Hospital, Putian, Fujian, China

6. Department of Nephrology, Xianyou County General Hospital, Putian, Fujian, China

Abstract

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.

Publisher

Hindawi Limited

Subject

Cell Biology,Immunology

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