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The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients.
Liu, Bin; Liu, Xiang-Yang; Wang, Guo-Ping; Chen, Yi-Xin.
Afiliación
  • Liu B; Department of Spine Surgery, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, 410005, Hunan, China.
  • Liu XY; Department of Spine Surgery, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, 410005, Hunan, China.
  • Wang GP; Department of Spine Surgery, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, 410005, Hunan, China.
  • Chen YX; Department of Rehabilitation Medicine, Xiangya Hospital of Central South University, No. 87, Xiangya Road, Changsha, 410008, Hunan, China. chenyxxy@csu.edu.cn.
Sci Rep ; 14(1): 5184, 2024 03 02.
Article en En | MEDLINE | ID: mdl-38431660
ABSTRACT
Host immune dysregulation involves in the initiation and development of osteosarcoma (OS). However, the exact role of immune cells in OS remains unknown. We aimed to distinguish the molecular subtypes and establish a prognostic model in OS patients based on immunocyte infiltration. The gene expression profile and corresponding clinical feature of OS patients were obtained from TARGET and GSE21257 datasets. MCP-counter and univariate Cox regression analyses were applied to identify immune cell infiltration-related molecular subgroups. Functional enrichment analysis and immunocyte infiltration analysis were performed between two subgroups. Furthermore, Cox regression and LASSO analyses were performed to establish the prognostic model for the prediction of prognosis and metastasis in OS patients. The subgroup with low infiltration of monocytic lineage (ML) was related to bad prognosis in OS patients. 435 DEGs were screened between the two subgroups. Functional enrichment analysis revealed these DEGs were involved in immune- and inflammation-related pathways. Three important genes (including TERT, CCDC26, and IL2RA) were identified to establish the prognostic model. The risk model had good prognostic performance for the prediction of metastasis and overall survival in OS patients. A novel stratification system was established based on ML-related signature. The risk model could predict the metastasis and prognosis in OS patients. Our findings offered a novel sight for the prognosis and development of OS.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Óseas / Osteosarcoma Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Óseas / Osteosarcoma Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: China