Single-cell RNA-seq reveals T cell exhaustion and immune response landscape in osteosarcoma.
Front Immunol
; 15: 1362970, 2024.
Article
em En
| MEDLINE
| ID: mdl-38629071
ABSTRACT
Background:
T cell exhaustion in the tumor microenvironment has been demonstrated as a substantial contributor to tumor immunosuppression and progression. However, the correlation between T cell exhaustion and osteosarcoma (OS) remains unclear.Methods:
In our present study, single-cell RNA-seq data for OS from the GEO database was analysed to identify CD8+ T cells and discern CD8+ T cell subsets objectively. Subgroup differentiation trajectory was then used to pinpoint genes altered in response to T cell exhaustion. Subsequently, six machine learning algorithms were applied to develop a prognostic model linked with T cell exhaustion. This model was subsequently validated in the TARGETs and Meta cohorts. Finally, we examined disparities in immune cell infiltration, immune checkpoints, immune-related pathways, and the efficacy of immunotherapy between high and low TEX score groups.Results:
The findings unveiled differential exhaustion in CD8+ T cells within the OS microenvironment. Three genes related to T cell exhaustion (RAD23A, SAC3D1, PSIP1) were identified and employed to formulate a T cell exhaustion model. This model exhibited robust predictive capabilities for OS prognosis, with patients in the low TEX score group demonstrating a more favorable prognosis, increased immune cell infiltration, and heightened responsiveness to treatment compared to those in the high TEX score group.Conclusion:
In summary, our research elucidates the role of T cell exhaustion in the immunotherapy and progression of OS, the prognostic model constructed based on T cell exhaustion-related genes holds promise as a potential method for prognostication in the management and treatment of OS patients.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article