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Apoptosis-related genes-based prognostic signature for osteosarcoma

Osteosarcoma (OS) is a common malignant primary tumor of skeleton, especially in children and adolescents, characterized by high lung metastasis rate. Apoptosis has been studied in various tumors, while the prognostic role of apoptosis-related genes in OS has been seldom studied. Three OS related da...

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Detalles Bibliográficos
Autores principales: Yang, Fei, Zhang, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9134960/
https://www.ncbi.nlm.nih.gov/pubmed/35504036
http://dx.doi.org/10.18632/aging.204042
Descripción
Sumario:Osteosarcoma (OS) is a common malignant primary tumor of skeleton, especially in children and adolescents, characterized by high lung metastasis rate. Apoptosis has been studied in various tumors, while the prognostic role of apoptosis-related genes in OS has been seldom studied. Three OS related datasets were downloaded from Gene Expression Omnibus (GEO) database. Univariate Cox and LASSO Cox regression analysis identified optimal genes, which were used for building prognostic Risk score. Subsequent multivariate Cox regression analysis and Kaplan-Meier survival analysis determined the independent prognostic factors for OS. The immune cell infiltration was analyzed in CIBERSORT. Basing on 680 apoptosis-related genes, the OS patients could be divided into 2 clusters with significantly different overall survival. Among which, 6 optimal genes were identified to construct Risk score. In both training set (GSE21257) and validation set (meta-GEO dataset), high risk OS patients had significantly worse overall survival compared with the low risk patients. Besides, high Risk score was an independent poor prognostic factor for OS with various ages or genders. Three immune cells were differentially infiltrated between high and low risk OS patients. In conclusion, a six-gene (TERT, TRAP1, DNM1L, BAG5, PLEKHF1 and PPP3CB) based prognostic Risk score signature is probably conducive to distinguish different prognosis of OS patients.