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Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis

Patients with hepatocellular carcinoma (HCC) have different prognoses depending on whether or not they also have fibrosis. Since long non-coding RNAs (lncRNAs) affect tumor formation and progression, the present study aimed to investigate whether their expression might help predict the survival of p...

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Autores principales: Ye, Jiaxiang, Wu, Siyao, Pan, Shan, Huang, Junqi, Ge, Lianying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108035/
https://www.ncbi.nlm.nih.gov/pubmed/32323856
http://dx.doi.org/10.3892/or.2020.7528
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author Ye, Jiaxiang
Wu, Siyao
Pan, Shan
Huang, Junqi
Ge, Lianying
author_facet Ye, Jiaxiang
Wu, Siyao
Pan, Shan
Huang, Junqi
Ge, Lianying
author_sort Ye, Jiaxiang
collection PubMed
description Patients with hepatocellular carcinoma (HCC) have different prognoses depending on whether or not they also have fibrosis. Since long non-coding RNAs (lncRNAs) affect tumor formation and progression, the present study aimed to investigate whether their expression might help predict the survival of patients with HCC. Expression profiles downloaded from The Cancer Genome Atlas database were examined to identify lncRNAs differentially expressed (DElncRNAs) between HCC patients with or without fibrosis. These DElncRNAs were then used to develop a risk scoring system to predict overall survival (OS) or recurrence-free survival (RFS). A total of 142 significant DElncRNAs were identified using data from 135 patients with fibrosis and 72 without fibrosis. For HCC patients with fibrosis, a risk scoring system to predict OS was constructed based on five lncRNAs (AL359853.1, Z93930.3, HOXA-AS3, AL772337.1 and AC012640.3), while the risk scoring system to predict RFS was based on 12 lncRNAs (PLCE1-AS1, Z93930.3, LINC02273, TRBV11-2, HHIP-AS1, AC004687.1, LINC01857, AC004585.1, AP000808.1, CU638689.4, AC090152.1 and AL357060.1). For HCC patients without fibrosis, the risk scoring system to predict OS was established based on seven lncRNAs (LINC00239, AC104971.4, AP006285.2, HOXA-AS3, AC079834.2, NRIR and LINC01929), and the system to predict RFS was based on five lncRNAs (AC021744.1, NRIR, LINC00487, AC005858.1 and AC107398.3). Areas under the receiver operating characteristic curves for all risk scoring systems exceeded 0.7. Uni- and multivariate Cox analyses showed that the risk scoring systems were significant independent predictors of OS for HCC patients with fibrosis, or of OS and RFS for HCC patients without fibrosis, after adjusting for clinical factors. Functional enrichment analysis suggested that, depending on the risk scoring system, highly associated genes were involved in pathways mainly associated with the cell cycle, chemokines, Th17 cell differentiation or thermogenesis. The findings of the present study indicate that risk scoring systems based on lncRNA expression can effectively predict the OS of HCC patients with fibrosis as well as the OS or RFS of HCC patients without fibrosis.
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spelling pubmed-71080352020-04-03 Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis Ye, Jiaxiang Wu, Siyao Pan, Shan Huang, Junqi Ge, Lianying Oncol Rep Articles Patients with hepatocellular carcinoma (HCC) have different prognoses depending on whether or not they also have fibrosis. Since long non-coding RNAs (lncRNAs) affect tumor formation and progression, the present study aimed to investigate whether their expression might help predict the survival of patients with HCC. Expression profiles downloaded from The Cancer Genome Atlas database were examined to identify lncRNAs differentially expressed (DElncRNAs) between HCC patients with or without fibrosis. These DElncRNAs were then used to develop a risk scoring system to predict overall survival (OS) or recurrence-free survival (RFS). A total of 142 significant DElncRNAs were identified using data from 135 patients with fibrosis and 72 without fibrosis. For HCC patients with fibrosis, a risk scoring system to predict OS was constructed based on five lncRNAs (AL359853.1, Z93930.3, HOXA-AS3, AL772337.1 and AC012640.3), while the risk scoring system to predict RFS was based on 12 lncRNAs (PLCE1-AS1, Z93930.3, LINC02273, TRBV11-2, HHIP-AS1, AC004687.1, LINC01857, AC004585.1, AP000808.1, CU638689.4, AC090152.1 and AL357060.1). For HCC patients without fibrosis, the risk scoring system to predict OS was established based on seven lncRNAs (LINC00239, AC104971.4, AP006285.2, HOXA-AS3, AC079834.2, NRIR and LINC01929), and the system to predict RFS was based on five lncRNAs (AC021744.1, NRIR, LINC00487, AC005858.1 and AC107398.3). Areas under the receiver operating characteristic curves for all risk scoring systems exceeded 0.7. Uni- and multivariate Cox analyses showed that the risk scoring systems were significant independent predictors of OS for HCC patients with fibrosis, or of OS and RFS for HCC patients without fibrosis, after adjusting for clinical factors. Functional enrichment analysis suggested that, depending on the risk scoring system, highly associated genes were involved in pathways mainly associated with the cell cycle, chemokines, Th17 cell differentiation or thermogenesis. The findings of the present study indicate that risk scoring systems based on lncRNA expression can effectively predict the OS of HCC patients with fibrosis as well as the OS or RFS of HCC patients without fibrosis. D.A. Spandidos 2020-05 2020-02-18 /pmc/articles/PMC7108035/ /pubmed/32323856 http://dx.doi.org/10.3892/or.2020.7528 Text en Copyright: © Ye et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Ye, Jiaxiang
Wu, Siyao
Pan, Shan
Huang, Junqi
Ge, Lianying
Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis
title Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis
title_full Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis
title_fullStr Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis
title_full_unstemmed Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis
title_short Risk scoring based on expression of long non-coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis
title_sort risk scoring based on expression of long non-coding rnas can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108035/
https://www.ncbi.nlm.nih.gov/pubmed/32323856
http://dx.doi.org/10.3892/or.2020.7528
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