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A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma
Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5–10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6189101/ https://www.ncbi.nlm.nih.gov/pubmed/30323196 http://dx.doi.org/10.1038/s41598-018-33642-1 |
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author | Liu, Guancheng Zheng, Jinyang Zhuang, Liming Lv, Yunxia Zhu, Gangcai Pi, Leiming Wang, Junchen Chen, Changhan Li, Zhexuan Liu, Jiangyi Chen, liangjuan Cai, Gengming Zhang, Xin |
author_facet | Liu, Guancheng Zheng, Jinyang Zhuang, Liming Lv, Yunxia Zhu, Gangcai Pi, Leiming Wang, Junchen Chen, Changhan Li, Zhexuan Liu, Jiangyi Chen, liangjuan Cai, Gengming Zhang, Xin |
author_sort | Liu, Guancheng |
collection | PubMed |
description | Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5–10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile data for the patients with HNSCC were obtained from the TCGA database (GEO). A total of 500 samples with full clinical following-up were randomly divided into a training set and a validation set. The training set was used to screen for differentially expressed lncRNAs. Single-factor survival analysis was performed to obtain lncRNAs that associated with prognosis. A robust likelihood-based survival model was constructed to identify the lncRNAs that are essential for the prognosis of HNSCC. A co-expression network between genes and lncRNAs was also constructed to identify lncRNAs co-expressed with genes to serve as the final signature lncRNAs for prognosis. Finally, the prognostic effect of the signature lncRNAs was tested by multi-factor survival analysis and a scoring model for the prognosis of HNSCC was constructed. Moreover, the results of the validation set and the relative expression levels of the signature lncRNAs in the tumour and the adjacent tissue were consistent with the results of the training set. The 5 lncRNAs were distributed among 3 expression modules. Further KEGG pathway enrichment analysis showed that these 3 co-expressed modules participate in different pathways, and many of these pathways are associated with the development and progression of disease. Therefore, we proposed that the 5 validated lncRNAs can be used to predict the prognosis of HNSCC patients and can be applied in postoperative treatment and follow-up. |
format | Online Article Text |
id | pubmed-6189101 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61891012018-10-22 A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma Liu, Guancheng Zheng, Jinyang Zhuang, Liming Lv, Yunxia Zhu, Gangcai Pi, Leiming Wang, Junchen Chen, Changhan Li, Zhexuan Liu, Jiangyi Chen, liangjuan Cai, Gengming Zhang, Xin Sci Rep Article Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5–10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile data for the patients with HNSCC were obtained from the TCGA database (GEO). A total of 500 samples with full clinical following-up were randomly divided into a training set and a validation set. The training set was used to screen for differentially expressed lncRNAs. Single-factor survival analysis was performed to obtain lncRNAs that associated with prognosis. A robust likelihood-based survival model was constructed to identify the lncRNAs that are essential for the prognosis of HNSCC. A co-expression network between genes and lncRNAs was also constructed to identify lncRNAs co-expressed with genes to serve as the final signature lncRNAs for prognosis. Finally, the prognostic effect of the signature lncRNAs was tested by multi-factor survival analysis and a scoring model for the prognosis of HNSCC was constructed. Moreover, the results of the validation set and the relative expression levels of the signature lncRNAs in the tumour and the adjacent tissue were consistent with the results of the training set. The 5 lncRNAs were distributed among 3 expression modules. Further KEGG pathway enrichment analysis showed that these 3 co-expressed modules participate in different pathways, and many of these pathways are associated with the development and progression of disease. Therefore, we proposed that the 5 validated lncRNAs can be used to predict the prognosis of HNSCC patients and can be applied in postoperative treatment and follow-up. Nature Publishing Group UK 2018-10-15 /pmc/articles/PMC6189101/ /pubmed/30323196 http://dx.doi.org/10.1038/s41598-018-33642-1 Text en © The Author(s) 2018 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liu, Guancheng Zheng, Jinyang Zhuang, Liming Lv, Yunxia Zhu, Gangcai Pi, Leiming Wang, Junchen Chen, Changhan Li, Zhexuan Liu, Jiangyi Chen, liangjuan Cai, Gengming Zhang, Xin A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma |
title | A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma |
title_full | A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma |
title_fullStr | A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma |
title_full_unstemmed | A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma |
title_short | A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma |
title_sort | prognostic 5-lncrna expression signature for head and neck squamous cell carcinoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6189101/ https://www.ncbi.nlm.nih.gov/pubmed/30323196 http://dx.doi.org/10.1038/s41598-018-33642-1 |
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