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The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC)
Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver. Although the RNA modification N6-methyladenine (m6A) has been reported to be involved in HCC carcinogenesis, early diagnostic markers and promising personalized therapeutic targets are still lacking. In this study, we...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9841875/ https://www.ncbi.nlm.nih.gov/pubmed/36655172 http://dx.doi.org/10.1177/11769343221142013 |
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author | Deng, Zhen Hou, Jiaxing Xu, Hongbo Lei, Zhao Li, Zhiqiang Zhu, Hongwei Yu, Xiao Yang, Zhi Jin, Xiaoxin Sun, Jichun |
author_facet | Deng, Zhen Hou, Jiaxing Xu, Hongbo Lei, Zhao Li, Zhiqiang Zhu, Hongwei Yu, Xiao Yang, Zhi Jin, Xiaoxin Sun, Jichun |
author_sort | Deng, Zhen |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver. Although the RNA modification N6-methyladenine (m6A) has been reported to be involved in HCC carcinogenesis, early diagnostic markers and promising personalized therapeutic targets are still lacking. In this study, we identified that 19 m6A regulators and 34 co-expressed lncRNAs were significantly upregulated in HCC samples; based on these factors, we established a prognostic signal of HCC associated with 9 lncRNAs and 19 m6A regulators using LASSO Cox regression analysis. Kaplan-Meier survival estimate revealed correlations between the risk scores and patients’ OS in the training and validation dataset. The ROC curve demonstrated that the risk score-based curve has satisfactory prediction efficiency for both training and validation datasets. Multivariate Cox’s proportional hazard regression analysis indicated that the risk score was an independent risk factor within the training and validation dataset. In addition, the risk score could distinguish HCC patients from normal non-cancerous samples and HCC samples of different pathological grades. Eventually, 232 mRNAs were co-expressed with these 9 lncRNAs according to GSE101685 and GSE112790; these mRNAs were enriched in cell cycle and cell metabolic activities, drug metabolism, liver disease-related pathways, and some important cancer related pathways such as p53, MAPK, Wnt, RAS and so forth. The expression of the 9 lncRNAs was significantly higher in HCC samples than that in the neighboring non-cancerous samples. Altogether, by using the Consensus Clustering, PCA, ESTIMATE algorithm, LASSO regression model, Kaplan-Meier survival assessment, ROC curve analysis, and multivariate Cox’s proportional hazard regression model analysis, we established a prognostic marker consisting of 9 m6A regulator-related lncRNAs that markers may have prognostic and diagnostic potential for HCC. |
format | Online Article Text |
id | pubmed-9841875 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-98418752023-01-17 The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC) Deng, Zhen Hou, Jiaxing Xu, Hongbo Lei, Zhao Li, Zhiqiang Zhu, Hongwei Yu, Xiao Yang, Zhi Jin, Xiaoxin Sun, Jichun Evol Bioinform Online Original Research Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver. Although the RNA modification N6-methyladenine (m6A) has been reported to be involved in HCC carcinogenesis, early diagnostic markers and promising personalized therapeutic targets are still lacking. In this study, we identified that 19 m6A regulators and 34 co-expressed lncRNAs were significantly upregulated in HCC samples; based on these factors, we established a prognostic signal of HCC associated with 9 lncRNAs and 19 m6A regulators using LASSO Cox regression analysis. Kaplan-Meier survival estimate revealed correlations between the risk scores and patients’ OS in the training and validation dataset. The ROC curve demonstrated that the risk score-based curve has satisfactory prediction efficiency for both training and validation datasets. Multivariate Cox’s proportional hazard regression analysis indicated that the risk score was an independent risk factor within the training and validation dataset. In addition, the risk score could distinguish HCC patients from normal non-cancerous samples and HCC samples of different pathological grades. Eventually, 232 mRNAs were co-expressed with these 9 lncRNAs according to GSE101685 and GSE112790; these mRNAs were enriched in cell cycle and cell metabolic activities, drug metabolism, liver disease-related pathways, and some important cancer related pathways such as p53, MAPK, Wnt, RAS and so forth. The expression of the 9 lncRNAs was significantly higher in HCC samples than that in the neighboring non-cancerous samples. Altogether, by using the Consensus Clustering, PCA, ESTIMATE algorithm, LASSO regression model, Kaplan-Meier survival assessment, ROC curve analysis, and multivariate Cox’s proportional hazard regression model analysis, we established a prognostic marker consisting of 9 m6A regulator-related lncRNAs that markers may have prognostic and diagnostic potential for HCC. SAGE Publications 2023-01-12 /pmc/articles/PMC9841875/ /pubmed/36655172 http://dx.doi.org/10.1177/11769343221142013 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Deng, Zhen Hou, Jiaxing Xu, Hongbo Lei, Zhao Li, Zhiqiang Zhu, Hongwei Yu, Xiao Yang, Zhi Jin, Xiaoxin Sun, Jichun The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC) |
title | The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC) |
title_full | The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC) |
title_fullStr | The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC) |
title_full_unstemmed | The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC) |
title_short | The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC) |
title_sort | prognostic value of a lncrna risk model consists of 9 m6a regulator-related lncrnas in hepatocellular carcinoma (hcc) |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9841875/ https://www.ncbi.nlm.nih.gov/pubmed/36655172 http://dx.doi.org/10.1177/11769343221142013 |
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