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Development of a novel immune-related genes prognostic signature for osteosarcoma
Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Genera...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591524/ https://www.ncbi.nlm.nih.gov/pubmed/33110201 http://dx.doi.org/10.1038/s41598-020-75573-w |
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author | Wu, Zuo-long Deng, Ya-jun Zhang, Guang-zhi Ren, En-hui Yuan, Wen-hua Xie, Qi-qi |
author_facet | Wu, Zuo-long Deng, Ya-jun Zhang, Guang-zhi Ren, En-hui Yuan, Wen-hua Xie, Qi-qi |
author_sort | Wu, Zuo-long |
collection | PubMed |
description | Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases. IRGs were obtained from the ImmPort database. R software was used to screen differentially expressed IRGs (DEIRGs) and functional correlation analysis. DEIRGs were analyzed by univariate Cox regression and iterative LASSO Cox regression analysis to develop an optimal prognostic signature, and the signature was further verified by independent cohort (GSE39055) and clinical correlation analysis. The analyses yielded 604 DEIRGs and 10 hub IRGs. A prognostic signature consisting of 13 IRGs was constructed, which strikingly correlated with OS overall survival and distant metastasis (p < 0.05, p < 0.01), and clinical subgroup showed that the signature’s prognostic ability was independent of clinicopathological factors. Univariate and multivariate Cox regression analyses also supported its prognostic value. In conclusion, we developed an IRGs signature that is a prognostic indicator in OS patients, and the signature might serve as potential prognostic indicator to identify outcome of OS and facilitate personalized management of the high-risk patients. |
format | Online Article Text |
id | pubmed-7591524 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75915242020-10-28 Development of a novel immune-related genes prognostic signature for osteosarcoma Wu, Zuo-long Deng, Ya-jun Zhang, Guang-zhi Ren, En-hui Yuan, Wen-hua Xie, Qi-qi Sci Rep Article Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases. IRGs were obtained from the ImmPort database. R software was used to screen differentially expressed IRGs (DEIRGs) and functional correlation analysis. DEIRGs were analyzed by univariate Cox regression and iterative LASSO Cox regression analysis to develop an optimal prognostic signature, and the signature was further verified by independent cohort (GSE39055) and clinical correlation analysis. The analyses yielded 604 DEIRGs and 10 hub IRGs. A prognostic signature consisting of 13 IRGs was constructed, which strikingly correlated with OS overall survival and distant metastasis (p < 0.05, p < 0.01), and clinical subgroup showed that the signature’s prognostic ability was independent of clinicopathological factors. Univariate and multivariate Cox regression analyses also supported its prognostic value. In conclusion, we developed an IRGs signature that is a prognostic indicator in OS patients, and the signature might serve as potential prognostic indicator to identify outcome of OS and facilitate personalized management of the high-risk patients. Nature Publishing Group UK 2020-10-27 /pmc/articles/PMC7591524/ /pubmed/33110201 http://dx.doi.org/10.1038/s41598-020-75573-w Text en © The Author(s) 2020 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/. |
spellingShingle | Article Wu, Zuo-long Deng, Ya-jun Zhang, Guang-zhi Ren, En-hui Yuan, Wen-hua Xie, Qi-qi Development of a novel immune-related genes prognostic signature for osteosarcoma |
title | Development of a novel immune-related genes prognostic signature for osteosarcoma |
title_full | Development of a novel immune-related genes prognostic signature for osteosarcoma |
title_fullStr | Development of a novel immune-related genes prognostic signature for osteosarcoma |
title_full_unstemmed | Development of a novel immune-related genes prognostic signature for osteosarcoma |
title_short | Development of a novel immune-related genes prognostic signature for osteosarcoma |
title_sort | development of a novel immune-related genes prognostic signature for osteosarcoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591524/ https://www.ncbi.nlm.nih.gov/pubmed/33110201 http://dx.doi.org/10.1038/s41598-020-75573-w |
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