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Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma

Osteosarcoma is the most common malignant bone tumor in children and adolescence. Multiple immune-related genes have been reported in different cancers. The aim is to identify an immune-related gene signature for the prospective evaluation of prognosis for osteosarcoma patients. In this study, we ev...

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Autores principales: Xiao, Bo, Liu, Liyan, Li, Aoyu, Xiang, Cheng, Wang, Pingxiao, Li, Hui, Xiao, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771722/
https://www.ncbi.nlm.nih.gov/pubmed/33384961
http://dx.doi.org/10.3389/fonc.2020.607622
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author Xiao, Bo
Liu, Liyan
Li, Aoyu
Xiang, Cheng
Wang, Pingxiao
Li, Hui
Xiao, Tao
author_facet Xiao, Bo
Liu, Liyan
Li, Aoyu
Xiang, Cheng
Wang, Pingxiao
Li, Hui
Xiao, Tao
author_sort Xiao, Bo
collection PubMed
description Osteosarcoma is the most common malignant bone tumor in children and adolescence. Multiple immune-related genes have been reported in different cancers. The aim is to identify an immune-related gene signature for the prospective evaluation of prognosis for osteosarcoma patients. In this study, we evaluated the infiltration of immune cells in 101 osteosarcoma patients downloaded from TARGET using the ssGSEA to the RNA-sequencing of these patients, thus, high immune cell infiltration cluster, middle immune cell infiltration cluster and low immune cell infiltration cluster were generated. On the foundation of high immune cell infiltration cluster vs. low immune cell infiltration cluster and normal vs. osteosarcoma, we found 108 common differentially expressed genes which were sequentially submitted to univariate Cox and LASSO regression analysis. Furthermore, GSEA indicated some pathways with notable enrichment in the high- and low-immune cell infiltration cluster that may be helpful in understanding the potential mechanisms. Finally, we identified seven immune-related genes as prognostic signature for osteosarcoma. Kaplan-Meier analysis, ROC curve, univariate and multivariate Cox regression further confirmed that the seven immune-related genes signature was an innovative and significant prognostic factor independent of clinical features. These results of this study offer a means to predict the prognosis and survival of osteosarcoma patients with uncovered seven-gene signature as potential biomarkers.
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spelling pubmed-77717222020-12-30 Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma Xiao, Bo Liu, Liyan Li, Aoyu Xiang, Cheng Wang, Pingxiao Li, Hui Xiao, Tao Front Oncol Oncology Osteosarcoma is the most common malignant bone tumor in children and adolescence. Multiple immune-related genes have been reported in different cancers. The aim is to identify an immune-related gene signature for the prospective evaluation of prognosis for osteosarcoma patients. In this study, we evaluated the infiltration of immune cells in 101 osteosarcoma patients downloaded from TARGET using the ssGSEA to the RNA-sequencing of these patients, thus, high immune cell infiltration cluster, middle immune cell infiltration cluster and low immune cell infiltration cluster were generated. On the foundation of high immune cell infiltration cluster vs. low immune cell infiltration cluster and normal vs. osteosarcoma, we found 108 common differentially expressed genes which were sequentially submitted to univariate Cox and LASSO regression analysis. Furthermore, GSEA indicated some pathways with notable enrichment in the high- and low-immune cell infiltration cluster that may be helpful in understanding the potential mechanisms. Finally, we identified seven immune-related genes as prognostic signature for osteosarcoma. Kaplan-Meier analysis, ROC curve, univariate and multivariate Cox regression further confirmed that the seven immune-related genes signature was an innovative and significant prognostic factor independent of clinical features. These results of this study offer a means to predict the prognosis and survival of osteosarcoma patients with uncovered seven-gene signature as potential biomarkers. Frontiers Media S.A. 2020-12-15 /pmc/articles/PMC7771722/ /pubmed/33384961 http://dx.doi.org/10.3389/fonc.2020.607622 Text en Copyright © 2020 Xiao, Liu, Li, Xiang, Wang, Li and Xiao http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Xiao, Bo
Liu, Liyan
Li, Aoyu
Xiang, Cheng
Wang, Pingxiao
Li, Hui
Xiao, Tao
Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma
title Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma
title_full Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma
title_fullStr Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma
title_full_unstemmed Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma
title_short Identification and Verification of Immune-Related Gene Prognostic Signature Based on ssGSEA for Osteosarcoma
title_sort identification and verification of immune-related gene prognostic signature based on ssgsea for osteosarcoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771722/
https://www.ncbi.nlm.nih.gov/pubmed/33384961
http://dx.doi.org/10.3389/fonc.2020.607622
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