An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism

Liver cancer is a highly malignant tumor. Notably, recent studies have found that long non-coding RNAs (lncRNAs) play a prominent role in the prognosis of patients with liver cancer. Herein, we attempted to construct an lncRNA model to accurately predict the survival rate in liver cancer. Based on T...

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Autores principales:	Hao Zhang, Renzheng Liu, Lin Sun, Xiao Hu
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	lncRNA model prognosis hepatocellular carcinoma ceRNA Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/b5e3186a04644f96b886e2b7a762a67f
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spelling	oai:doaj.org-article:b5e3186a04644f96b886e2b7a762a67f2021-11-12T06:24:08ZAn lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism2296-889X10.3389/fmolb.2021.749313https://doaj.org/article/b5e3186a04644f96b886e2b7a762a67f2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmolb.2021.749313/fullhttps://doaj.org/toc/2296-889XLiver cancer is a highly malignant tumor. Notably, recent studies have found that long non-coding RNAs (lncRNAs) play a prominent role in the prognosis of patients with liver cancer. Herein, we attempted to construct an lncRNA model to accurately predict the survival rate in liver cancer. Based on The Cancer Genome Atlas (TCGA) database, we first identified 1066 lncRNAs with differential expression. The patient data obtained from TCGA were divided into the experimental group and the verification group. According to the difference in lncRNAs, we used single-factor and multi-factor Cox regression to select the genes needed to build the model in the experimental group, which were verified in the verification group. The results showed that the model could accurately predict the survival rate of patients in the high and low risk groups. The reliability of the model was also confirmed by the area under the receiver operating characteristic curve. Our model is significantly correlated with different clinicopathological features. Finally, we built a ceRNA network based on lncRNAs, which was used to display miRNAs and mRNAs related to lncRNAs. In summary, we constructed an lncRNA model to predict the survival rate of patients with hepatocellular carcinoma.Hao ZhangRenzheng LiuLin SunXiao HuFrontiers Media S.A.articlelncRNAmodelprognosishepatocellular carcinomaceRNABiology (General)QH301-705.5ENFrontiers in Molecular Biosciences, Vol 8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	lncRNA model prognosis hepatocellular carcinoma ceRNA Biology (General) QH301-705.5
spellingShingle	lncRNA model prognosis hepatocellular carcinoma ceRNA Biology (General) QH301-705.5 Hao Zhang Renzheng Liu Lin Sun Xiao Hu An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism
description	Liver cancer is a highly malignant tumor. Notably, recent studies have found that long non-coding RNAs (lncRNAs) play a prominent role in the prognosis of patients with liver cancer. Herein, we attempted to construct an lncRNA model to accurately predict the survival rate in liver cancer. Based on The Cancer Genome Atlas (TCGA) database, we first identified 1066 lncRNAs with differential expression. The patient data obtained from TCGA were divided into the experimental group and the verification group. According to the difference in lncRNAs, we used single-factor and multi-factor Cox regression to select the genes needed to build the model in the experimental group, which were verified in the verification group. The results showed that the model could accurately predict the survival rate of patients in the high and low risk groups. The reliability of the model was also confirmed by the area under the receiver operating characteristic curve. Our model is significantly correlated with different clinicopathological features. Finally, we built a ceRNA network based on lncRNAs, which was used to display miRNAs and mRNAs related to lncRNAs. In summary, we constructed an lncRNA model to predict the survival rate of patients with hepatocellular carcinoma.
format	article
author	Hao Zhang Renzheng Liu Lin Sun Xiao Hu
author_facet	Hao Zhang Renzheng Liu Lin Sun Xiao Hu
author_sort	Hao Zhang
title	An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism
title_short	An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism
title_full	An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism
title_fullStr	An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism
title_full_unstemmed	An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism
title_sort	lncrna model for predicting the prognosis of hepatocellular carcinoma patients and cerna mechanism
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/b5e3186a04644f96b886e2b7a762a67f
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An lncRNA Model for Predicting the Prognosis of Hepatocellular Carcinoma Patients and ceRNA Mechanism

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