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Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets

BACKGROUND: Hepatitis B virus, together with hepatitis C virus, has been recognized as the leading causes of hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) have been suggested in increasing studies to be the potential prognostic factors for HCC. However, the role of combined applicat...

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Autores principales: Huang, Zi-Lin, Li, Wang, Chen, Qi-Feng, Wu, Pei-Hong, Shen, Lu-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883184/
https://www.ncbi.nlm.nih.gov/pubmed/31798779
http://dx.doi.org/10.4251/wjgo.v11.i11.983
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author Huang, Zi-Lin
Li, Wang
Chen, Qi-Feng
Wu, Pei-Hong
Shen, Lu-Jun
author_facet Huang, Zi-Lin
Li, Wang
Chen, Qi-Feng
Wu, Pei-Hong
Shen, Lu-Jun
author_sort Huang, Zi-Lin
collection PubMed
description BACKGROUND: Hepatitis B virus, together with hepatitis C virus, has been recognized as the leading causes of hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) have been suggested in increasing studies to be the potential prognostic factors for HCC. However, the role of combined application of lncRNAs in estimating overall survival (OS) for hepatitis virus positive HCC (VHCC) is uncertain. AIM: To construct an lncRNA signature related to the OS of VHCC patients to enhance the accuracy of prognosis prediction. METHODS: The expression patterns of lncRNAs, as well as related clinical data were collected from 149 VHCC patients from The Cancer Genome Atlas database. The R package was adopted to obtain the differentially expressed lncRNAs (DElncRNAs). LncRNAs significantly associated with OS were screened by means of univariate Cox regression analysis, so as to construct a least absolute shrinkage and selection operator (LASSO) model. Subsequently, the constructed lncRNA signature was developed and validated. Afterwards, the prognostic nomogram was established, which combined the as-established lncRNA signature as well as the clinical features. Meanwhile, subgroup analysis stratified by the virus type was also performed. Finally, the above-mentioned lncRNAs were enriched to corresponding pathways according to the markedly co-expressed genes. RESULTS: A total of 1420 DElncRNAs were identified, among which 406 were significant in univariate Cox regression analysis. LASSO regression confirmed 8 out of the 406 lncRNAs, including AC005722.2, AC107959.3, AL353803.1, AL589182.1, AP000844.2, AP002478.1, FLJ36000, and NPSR1-AS1. Then, the prognostic risk score was calculated. Our results displayed a significant association between the risk model and the OS of VHCC [hazard ratio = 1.94, 95% confidence interval (CI): 1.61-2.34, log-rank P = 2e-10]. The inference tree suggested that the established lncRNA signature was useful in the risk stratification of VHCC. Furthermore, a nomogram was plotted, and the concordance index of internal validation was 0.763 (95%CI: 0.700-0.826). Moreover, the subgroup analysis regarding etiology confirmed this risk model. In addition, the Wnt signaling pathway, angiogenesis, the p53 pathway, and the PI3 kinase pathway were the remarkably enriched pathways. CONCLUSION: An eight-lncRNA signature has been established to predict the prognosis for VHCC, which contributes to providing a novel foundation for the targeted therapy of VHCC.
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spelling pubmed-68831842019-12-03 Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets Huang, Zi-Lin Li, Wang Chen, Qi-Feng Wu, Pei-Hong Shen, Lu-Jun World J Gastrointest Oncol Basic Study BACKGROUND: Hepatitis B virus, together with hepatitis C virus, has been recognized as the leading causes of hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) have been suggested in increasing studies to be the potential prognostic factors for HCC. However, the role of combined application of lncRNAs in estimating overall survival (OS) for hepatitis virus positive HCC (VHCC) is uncertain. AIM: To construct an lncRNA signature related to the OS of VHCC patients to enhance the accuracy of prognosis prediction. METHODS: The expression patterns of lncRNAs, as well as related clinical data were collected from 149 VHCC patients from The Cancer Genome Atlas database. The R package was adopted to obtain the differentially expressed lncRNAs (DElncRNAs). LncRNAs significantly associated with OS were screened by means of univariate Cox regression analysis, so as to construct a least absolute shrinkage and selection operator (LASSO) model. Subsequently, the constructed lncRNA signature was developed and validated. Afterwards, the prognostic nomogram was established, which combined the as-established lncRNA signature as well as the clinical features. Meanwhile, subgroup analysis stratified by the virus type was also performed. Finally, the above-mentioned lncRNAs were enriched to corresponding pathways according to the markedly co-expressed genes. RESULTS: A total of 1420 DElncRNAs were identified, among which 406 were significant in univariate Cox regression analysis. LASSO regression confirmed 8 out of the 406 lncRNAs, including AC005722.2, AC107959.3, AL353803.1, AL589182.1, AP000844.2, AP002478.1, FLJ36000, and NPSR1-AS1. Then, the prognostic risk score was calculated. Our results displayed a significant association between the risk model and the OS of VHCC [hazard ratio = 1.94, 95% confidence interval (CI): 1.61-2.34, log-rank P = 2e-10]. The inference tree suggested that the established lncRNA signature was useful in the risk stratification of VHCC. Furthermore, a nomogram was plotted, and the concordance index of internal validation was 0.763 (95%CI: 0.700-0.826). Moreover, the subgroup analysis regarding etiology confirmed this risk model. In addition, the Wnt signaling pathway, angiogenesis, the p53 pathway, and the PI3 kinase pathway were the remarkably enriched pathways. CONCLUSION: An eight-lncRNA signature has been established to predict the prognosis for VHCC, which contributes to providing a novel foundation for the targeted therapy of VHCC. Baishideng Publishing Group Inc 2019-11-15 2019-11-15 /pmc/articles/PMC6883184/ /pubmed/31798779 http://dx.doi.org/10.4251/wjgo.v11.i11.983 Text en ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
spellingShingle Basic Study
Huang, Zi-Lin
Li, Wang
Chen, Qi-Feng
Wu, Pei-Hong
Shen, Lu-Jun
Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
title Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
title_full Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
title_fullStr Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
title_full_unstemmed Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
title_short Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
title_sort eight key long non-coding rnas predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
topic Basic Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883184/
https://www.ncbi.nlm.nih.gov/pubmed/31798779
http://dx.doi.org/10.4251/wjgo.v11.i11.983
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