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Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma

Background: Circular RNAs (circRNAs) have been demonstrated to be closely related to the carcinogenesis of human cancer in recent years. However, the molecular mechanism of circRNAs in the pathogenesis of hepatocellular carcinoma (HCC) has not been fully elucidated. We aimed to identify critical cir...

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Autores principales: Mo, Meile, Liu, Bihu, Luo, Yihuan, Tan, Jennifer Hui Juan, Zeng, Xi, Zeng, Xiaoyun, Huang, Dongping, Li, Changhua, Liu, Shun, Qiu, Xiaoqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8819184/
https://www.ncbi.nlm.nih.gov/pubmed/35141281
http://dx.doi.org/10.3389/fmolb.2022.801478
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author Mo, Meile
Liu, Bihu
Luo, Yihuan
Tan, Jennifer Hui Juan
Zeng, Xi
Zeng, Xiaoyun
Huang, Dongping
Li, Changhua
Liu, Shun
Qiu, Xiaoqiang
author_facet Mo, Meile
Liu, Bihu
Luo, Yihuan
Tan, Jennifer Hui Juan
Zeng, Xi
Zeng, Xiaoyun
Huang, Dongping
Li, Changhua
Liu, Shun
Qiu, Xiaoqiang
author_sort Mo, Meile
collection PubMed
description Background: Circular RNAs (circRNAs) have been demonstrated to be closely related to the carcinogenesis of human cancer in recent years. However, the molecular mechanism of circRNAs in the pathogenesis of hepatocellular carcinoma (HCC) has not been fully elucidated. We aimed to identify critical circRNAs and explore their potential regulatory network in HCC. Methods: The robust rank aggregation (RRA) algorithm and weighted gene co-expression network analysis (WGCNA) were conducted to unearth the differentially expressed circRNAs (DEcircRNAs) in HCC. The expression levels of DEcircRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). A circRNA-miRNA-mRNA regulatory network was constructed by computational biology, and protein-protein interaction (PPI) network, functional enrichment analysis, survival analysis, and infiltrating immune cells analysis were performed to uncover the potential regulatory mechanisms of the network. Results: A total of 22 DEcircRNAs were screened out from four microarray datasets (GSE94508, GSE97332, GSE155949, and GSE164803) utilizing the RRA algorithm. Meanwhile, an HCC-related module containing 404 circRNAs was identified by WGCNA analysis. After intersection, only four circRNAs were recognized in both algorithms. Following qRT-PCR validation, three circRNAs (hsa_circRNA_091581, hsa_circRNA_066568, and hsa_circRNA_105031) were chosen for further analysis. As a result, a circRNA-miRNA-mRNA network containing three circRNAs, 17 miRNAs, and 222 mRNAs was established. Seven core genes (ESR1, BUB1, PRC1, LOX, CCT5, YWHAZ, and DDX39B) were determined from the PPI network of 222 mRNAs, and a circRNA-miRNA-hubgene network was also constructed. Functional enrichment analysis suggested that these seven hub genes were closely correlated with several cancer related pathways. Survival analysis revealed that the expression levels of the seven core genes were significantly associated with the prognosis of HCC patients. In addition, we also found that these seven hub genes were remarkably related to the infiltrating levels of immune cells. Conclusion: Our research identified three pivotal HCC-related circRNAs and provided novel insights into the underlying mechanisms of the circRNA-miRNA-mRNA regulatory network in HCC.
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spelling pubmed-88191842022-02-08 Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma Mo, Meile Liu, Bihu Luo, Yihuan Tan, Jennifer Hui Juan Zeng, Xi Zeng, Xiaoyun Huang, Dongping Li, Changhua Liu, Shun Qiu, Xiaoqiang Front Mol Biosci Molecular Biosciences Background: Circular RNAs (circRNAs) have been demonstrated to be closely related to the carcinogenesis of human cancer in recent years. However, the molecular mechanism of circRNAs in the pathogenesis of hepatocellular carcinoma (HCC) has not been fully elucidated. We aimed to identify critical circRNAs and explore their potential regulatory network in HCC. Methods: The robust rank aggregation (RRA) algorithm and weighted gene co-expression network analysis (WGCNA) were conducted to unearth the differentially expressed circRNAs (DEcircRNAs) in HCC. The expression levels of DEcircRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). A circRNA-miRNA-mRNA regulatory network was constructed by computational biology, and protein-protein interaction (PPI) network, functional enrichment analysis, survival analysis, and infiltrating immune cells analysis were performed to uncover the potential regulatory mechanisms of the network. Results: A total of 22 DEcircRNAs were screened out from four microarray datasets (GSE94508, GSE97332, GSE155949, and GSE164803) utilizing the RRA algorithm. Meanwhile, an HCC-related module containing 404 circRNAs was identified by WGCNA analysis. After intersection, only four circRNAs were recognized in both algorithms. Following qRT-PCR validation, three circRNAs (hsa_circRNA_091581, hsa_circRNA_066568, and hsa_circRNA_105031) were chosen for further analysis. As a result, a circRNA-miRNA-mRNA network containing three circRNAs, 17 miRNAs, and 222 mRNAs was established. Seven core genes (ESR1, BUB1, PRC1, LOX, CCT5, YWHAZ, and DDX39B) were determined from the PPI network of 222 mRNAs, and a circRNA-miRNA-hubgene network was also constructed. Functional enrichment analysis suggested that these seven hub genes were closely correlated with several cancer related pathways. Survival analysis revealed that the expression levels of the seven core genes were significantly associated with the prognosis of HCC patients. In addition, we also found that these seven hub genes were remarkably related to the infiltrating levels of immune cells. Conclusion: Our research identified three pivotal HCC-related circRNAs and provided novel insights into the underlying mechanisms of the circRNA-miRNA-mRNA regulatory network in HCC. Frontiers Media S.A. 2022-01-24 /pmc/articles/PMC8819184/ /pubmed/35141281 http://dx.doi.org/10.3389/fmolb.2022.801478 Text en Copyright © 2022 Mo, Liu, Luo, Tan, Zeng, Zeng, Huang, Li, Liu and Qiu. 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 Molecular Biosciences
Mo, Meile
Liu, Bihu
Luo, Yihuan
Tan, Jennifer Hui Juan
Zeng, Xi
Zeng, Xiaoyun
Huang, Dongping
Li, Changhua
Liu, Shun
Qiu, Xiaoqiang
Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma
title Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma
title_full Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma
title_fullStr Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma
title_full_unstemmed Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma
title_short Construction and Comprehensive Analysis of a circRNA-miRNA-mRNA Regulatory Network to Reveal the Pathogenesis of Hepatocellular Carcinoma
title_sort construction and comprehensive analysis of a circrna-mirna-mrna regulatory network to reveal the pathogenesis of hepatocellular carcinoma
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8819184/
https://www.ncbi.nlm.nih.gov/pubmed/35141281
http://dx.doi.org/10.3389/fmolb.2022.801478
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