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The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma

The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues...

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Autores principales: Hu, Bo, Ma, Xiaolu, Fu, Peiyao, Sun, Qiman, Tang, Weiguo, Sun, Haixiang, Yang, Zhangfu, Yu, Mincheng, Zhou, Jian, Fan, Jia, Xu, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9402792/
https://www.ncbi.nlm.nih.gov/pubmed/33741523
http://dx.doi.org/10.1016/j.gpb.2021.03.001
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author Hu, Bo
Ma, Xiaolu
Fu, Peiyao
Sun, Qiman
Tang, Weiguo
Sun, Haixiang
Yang, Zhangfu
Yu, Mincheng
Zhou, Jian
Fan, Jia
Xu, Yang
author_facet Hu, Bo
Ma, Xiaolu
Fu, Peiyao
Sun, Qiman
Tang, Weiguo
Sun, Haixiang
Yang, Zhangfu
Yu, Mincheng
Zhou, Jian
Fan, Jia
Xu, Yang
author_sort Hu, Bo
collection PubMed
description The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.
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spelling pubmed-94027922022-08-26 The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma Hu, Bo Ma, Xiaolu Fu, Peiyao Sun, Qiman Tang, Weiguo Sun, Haixiang Yang, Zhangfu Yu, Mincheng Zhou, Jian Fan, Jia Xu, Yang Genomics Proteomics Bioinformatics Original Research The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival. Elsevier 2021-12 2021-03-17 /pmc/articles/PMC9402792/ /pubmed/33741523 http://dx.doi.org/10.1016/j.gpb.2021.03.001 Text en © 2021 The Authors. Published by Elsevier B.V. and Science Press on behalf of Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Original Research
Hu, Bo
Ma, Xiaolu
Fu, Peiyao
Sun, Qiman
Tang, Weiguo
Sun, Haixiang
Yang, Zhangfu
Yu, Mincheng
Zhou, Jian
Fan, Jia
Xu, Yang
The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma
title The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma
title_full The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma
title_fullStr The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma
title_full_unstemmed The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma
title_short The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma
title_sort mrna–mirna–lncrna regulatory network and factors associated with prognosis prediction of hepatocellular carcinoma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9402792/
https://www.ncbi.nlm.nih.gov/pubmed/33741523
http://dx.doi.org/10.1016/j.gpb.2021.03.001
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