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Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes
Cancer immunotherapy is a promising therapeutic approach, but the prognostic value of immune-related genes in osteosarcoma (OS) is unknown. Here, Target-OS RNA-seq data were analyzed to detect differentially expressed genes (DEGs) between OS subgroups, followed by functional enrichment analysis. Cox...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677796/ https://www.ncbi.nlm.nih.gov/pubmed/34916564 http://dx.doi.org/10.1038/s41598-021-03677-y |
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author | Guo, Junjie Li, Xiaoyang Shen, Shen Wu, Xuejian |
author_facet | Guo, Junjie Li, Xiaoyang Shen, Shen Wu, Xuejian |
author_sort | Guo, Junjie |
collection | PubMed |
description | Cancer immunotherapy is a promising therapeutic approach, but the prognostic value of immune-related genes in osteosarcoma (OS) is unknown. Here, Target-OS RNA-seq data were analyzed to detect differentially expressed genes (DEGs) between OS subgroups, followed by functional enrichment analysis. Cox proportional risk regression was performed for each immune-related gene, and a risk score model to predict the prognosis of patients with OS was constructed. The risk scores were calculated using the risk signature to divide the training set into high-risk and low-risk groups, and validation was performed with GSE21257. We identified two immune-associated clusters, C1 and C2. C1 was closely related to immunity, and the immune score was significantly higher in C1 than in C2. Furthermore, we validated 6 immune cell hub genes related to the prognosis of OS: CD8A, KIR2DL1, CD79A, APBB1IP, GAL, and PLD3. Survival analysis revealed that the prognosis of the high-risk group was significantly worse than that of the low-risk group. We also explored whether the 6-gene prognostic risk model was effective for survival prediction. In conclusion, the constructed a risk score model based on immune-related genes and the survival of patients with OS could be a potential tool for targeted therapy. |
format | Online Article Text |
id | pubmed-8677796 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86777962021-12-20 Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes Guo, Junjie Li, Xiaoyang Shen, Shen Wu, Xuejian Sci Rep Article Cancer immunotherapy is a promising therapeutic approach, but the prognostic value of immune-related genes in osteosarcoma (OS) is unknown. Here, Target-OS RNA-seq data were analyzed to detect differentially expressed genes (DEGs) between OS subgroups, followed by functional enrichment analysis. Cox proportional risk regression was performed for each immune-related gene, and a risk score model to predict the prognosis of patients with OS was constructed. The risk scores were calculated using the risk signature to divide the training set into high-risk and low-risk groups, and validation was performed with GSE21257. We identified two immune-associated clusters, C1 and C2. C1 was closely related to immunity, and the immune score was significantly higher in C1 than in C2. Furthermore, we validated 6 immune cell hub genes related to the prognosis of OS: CD8A, KIR2DL1, CD79A, APBB1IP, GAL, and PLD3. Survival analysis revealed that the prognosis of the high-risk group was significantly worse than that of the low-risk group. We also explored whether the 6-gene prognostic risk model was effective for survival prediction. In conclusion, the constructed a risk score model based on immune-related genes and the survival of patients with OS could be a potential tool for targeted therapy. Nature Publishing Group UK 2021-12-16 /pmc/articles/PMC8677796/ /pubmed/34916564 http://dx.doi.org/10.1038/s41598-021-03677-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Guo, Junjie Li, Xiaoyang Shen, Shen Wu, Xuejian Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes |
title | Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes |
title_full | Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes |
title_fullStr | Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes |
title_full_unstemmed | Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes |
title_short | Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes |
title_sort | expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677796/ https://www.ncbi.nlm.nih.gov/pubmed/34916564 http://dx.doi.org/10.1038/s41598-021-03677-y |
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