Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma

Abstract Dysregulation of mRNAs and long non-coding RNAs (lncRNAs) is one of the most important features of carcinogenesis and cancer development. However, studies integrating the expression of mRNAs and lncRNAs to predict the survival of head and neck squamous cell carcinoma (HNSC) are still limite...

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Autores principales:	Zhi-Li Zhang, Li-jing Zhao, Liang Chai, Shui-Hong Zhou, Feng Wang, Yan Wei, Ya-Ping Xu, Peng Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8990b6311c574b478186689be9e2abfc
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spelling	oai:doaj.org-article:8990b6311c574b478186689be9e2abfc2021-12-02T16:06:08ZSeven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma10.1038/s41598-017-00252-22045-2322https://doaj.org/article/8990b6311c574b478186689be9e2abfc2017-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-00252-2https://doaj.org/toc/2045-2322Abstract Dysregulation of mRNAs and long non-coding RNAs (lncRNAs) is one of the most important features of carcinogenesis and cancer development. However, studies integrating the expression of mRNAs and lncRNAs to predict the survival of head and neck squamous cell carcinoma (HNSC) are still limited, hitherto. In current work, we identified survival related mRNAs and lncRNAs in three datasets (TCGA dataset, E-TABM-302, GSE41613). By random forest, seven gene signatures (six mRNAs and lncRNA) were further selected to develop the risk score model. The risk score was significantly associated with survival in both training and testing datasets (E-TABM-302, GSE41613, and E-MTAB-1324). Furthermore, correlation analyses showed that the risk score is independent from clinicopathological features. According to Cox multivariable hazard model and nomogram, the risk score contributes the most to survival than the other clinical information, including gender, age, histologic grade, and alcohol taking. The Gene Set Enrichment Analysis (GSEA) indicates that the risk score is associated with cancer related pathways. In summary, the lncRNA-mRNA based risk score model we developed successfully predicts the survival of 755 HNSC samples in five datasets and two platforms. It is independent from clinical information and performs better than clinical information for prognosis.Zhi-Li ZhangLi-jing ZhaoLiang ChaiShui-Hong ZhouFeng WangYan WeiYa-Ping XuPeng ZhaoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zhi-Li Zhang Li-jing Zhao Liang Chai Shui-Hong Zhou Feng Wang Yan Wei Ya-Ping Xu Peng Zhao Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma
description	Abstract Dysregulation of mRNAs and long non-coding RNAs (lncRNAs) is one of the most important features of carcinogenesis and cancer development. However, studies integrating the expression of mRNAs and lncRNAs to predict the survival of head and neck squamous cell carcinoma (HNSC) are still limited, hitherto. In current work, we identified survival related mRNAs and lncRNAs in three datasets (TCGA dataset, E-TABM-302, GSE41613). By random forest, seven gene signatures (six mRNAs and lncRNA) were further selected to develop the risk score model. The risk score was significantly associated with survival in both training and testing datasets (E-TABM-302, GSE41613, and E-MTAB-1324). Furthermore, correlation analyses showed that the risk score is independent from clinicopathological features. According to Cox multivariable hazard model and nomogram, the risk score contributes the most to survival than the other clinical information, including gender, age, histologic grade, and alcohol taking. The Gene Set Enrichment Analysis (GSEA) indicates that the risk score is associated with cancer related pathways. In summary, the lncRNA-mRNA based risk score model we developed successfully predicts the survival of 755 HNSC samples in five datasets and two platforms. It is independent from clinical information and performs better than clinical information for prognosis.
format	article
author	Zhi-Li Zhang Li-jing Zhao Liang Chai Shui-Hong Zhou Feng Wang Yan Wei Ya-Ping Xu Peng Zhao
author_facet	Zhi-Li Zhang Li-jing Zhao Liang Chai Shui-Hong Zhou Feng Wang Yan Wei Ya-Ping Xu Peng Zhao
author_sort	Zhi-Li Zhang
title	Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma
title_short	Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma
title_full	Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma
title_fullStr	Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma
title_full_unstemmed	Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma
title_sort	seven lncrna-mrna based risk score predicts the survival of head and neck squamous cell carcinoma
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/8990b6311c574b478186689be9e2abfc
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Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma

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