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Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom

Intrahepatic cholangiocarcinoma (iCCA) patients had no obvious symptoms at early stage and poor postoperative survival. Therefore, the establishment of an iCCA prognostic prediction model to carry out refined management of iCCA patients is expected to improve the survival of the iCCA patient populat...

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Autores principales: Shi, Guodong, Wang, Junjie, Wang, Weiqi, Chen, Min, Liu, Xiaoxuan, Zheng, Yufan, Fu, Yi, Wang, Minghua, Zhang, Xiaojie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9493306/
https://www.ncbi.nlm.nih.gov/pubmed/36160000
http://dx.doi.org/10.3389/fgene.2022.982707
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author Shi, Guodong
Wang, Junjie
Wang, Weiqi
Chen, Min
Liu, Xiaoxuan
Zheng, Yufan
Fu, Yi
Wang, Minghua
Zhang, Xiaojie
author_facet Shi, Guodong
Wang, Junjie
Wang, Weiqi
Chen, Min
Liu, Xiaoxuan
Zheng, Yufan
Fu, Yi
Wang, Minghua
Zhang, Xiaojie
author_sort Shi, Guodong
collection PubMed
description Intrahepatic cholangiocarcinoma (iCCA) patients had no obvious symptoms at early stage and poor postoperative survival. Therefore, the establishment of an iCCA prognostic prediction model to carry out refined management of iCCA patients is expected to improve the survival of the iCCA patient population. In this paper, we analyzed the expression profiling data of patients from 32 iCCA tissues and eight paracancerous tissues in The Cancer Genome Atlas (TCGA) database. Perl software was used to separate M6A-related genes and lncRNAs from expression matrix files obtained from the TCGA database. The differentially expressed lncRNAs in the iCCA samples and the normal samples were screened out by differential analysis using the R package limma, and the m6A-related lncRNAs were further screened by Pearson correlation analysis. WGCNA clustering analysis constructs a random network to extract the module genes most related to iCCA, and take the intersection of differentially expressed lncRNAs related to m6A. Univariate Cox screening was performed for the intersection lncRNAs that had significant influence on the prognosis of iCCA patients, and further screening was performed by LASSO method and multivariate Cox regression analysis. Risk model was constructed and prognostic ability was evaluated according to risk score. In conclusion, we identified four m6A-related lncRNAs with potential prognostic value in iCCA, and established a novel m6A-related lncRNA-based prognostic model, which can be used as an independent prognostic factor to predict the prognosis of clinical patients.
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spelling pubmed-94933062022-09-23 Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom Shi, Guodong Wang, Junjie Wang, Weiqi Chen, Min Liu, Xiaoxuan Zheng, Yufan Fu, Yi Wang, Minghua Zhang, Xiaojie Front Genet Genetics Intrahepatic cholangiocarcinoma (iCCA) patients had no obvious symptoms at early stage and poor postoperative survival. Therefore, the establishment of an iCCA prognostic prediction model to carry out refined management of iCCA patients is expected to improve the survival of the iCCA patient population. In this paper, we analyzed the expression profiling data of patients from 32 iCCA tissues and eight paracancerous tissues in The Cancer Genome Atlas (TCGA) database. Perl software was used to separate M6A-related genes and lncRNAs from expression matrix files obtained from the TCGA database. The differentially expressed lncRNAs in the iCCA samples and the normal samples were screened out by differential analysis using the R package limma, and the m6A-related lncRNAs were further screened by Pearson correlation analysis. WGCNA clustering analysis constructs a random network to extract the module genes most related to iCCA, and take the intersection of differentially expressed lncRNAs related to m6A. Univariate Cox screening was performed for the intersection lncRNAs that had significant influence on the prognosis of iCCA patients, and further screening was performed by LASSO method and multivariate Cox regression analysis. Risk model was constructed and prognostic ability was evaluated according to risk score. In conclusion, we identified four m6A-related lncRNAs with potential prognostic value in iCCA, and established a novel m6A-related lncRNA-based prognostic model, which can be used as an independent prognostic factor to predict the prognosis of clinical patients. Frontiers Media S.A. 2022-09-08 /pmc/articles/PMC9493306/ /pubmed/36160000 http://dx.doi.org/10.3389/fgene.2022.982707 Text en Copyright © 2022 Shi, Wang, Wang, Chen, Liu, Zheng, Fu, Wang and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Shi, Guodong
Wang, Junjie
Wang, Weiqi
Chen, Min
Liu, Xiaoxuan
Zheng, Yufan
Fu, Yi
Wang, Minghua
Zhang, Xiaojie
Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom
title Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom
title_full Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom
title_fullStr Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom
title_full_unstemmed Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom
title_short Prognostic analysis of m6A-related lncRNAs as potential biomarkers in intrahepatic cholangiocarcinom
title_sort prognostic analysis of m6a-related lncrnas as potential biomarkers in intrahepatic cholangiocarcinom
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9493306/
https://www.ncbi.nlm.nih.gov/pubmed/36160000
http://dx.doi.org/10.3389/fgene.2022.982707
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