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The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer

Competing endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the tumorigenesis, metastasis, diagnosis, and predicting survival of various cancers. In this study, we constructed a ceRNA network in colorectal cancer (CRC). Then, we sought to develop a...

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Autores principales: Li, Wei, Yu, Weifang, Jiang, Xia, Gao, Xian, Wang, Guiqi, Jin, Xiaojing, Zhao, Zengren, Liu, Yuegeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344331/
https://www.ncbi.nlm.nih.gov/pubmed/32714366
http://dx.doi.org/10.3389/fgene.2020.00583
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author Li, Wei
Yu, Weifang
Jiang, Xia
Gao, Xian
Wang, Guiqi
Jin, Xiaojing
Zhao, Zengren
Liu, Yuegeng
author_facet Li, Wei
Yu, Weifang
Jiang, Xia
Gao, Xian
Wang, Guiqi
Jin, Xiaojing
Zhao, Zengren
Liu, Yuegeng
author_sort Li, Wei
collection PubMed
description Competing endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the tumorigenesis, metastasis, diagnosis, and predicting survival of various cancers. In this study, we constructed a ceRNA network in colorectal cancer (CRC). Then, we sought to develop and validate a composite clinicopathologic–genomic nomogram using The Cancer Genome Atlas (TCGA) database. To construct the ceRNA network in CRC, we analyzed the mRNAseq, miRNAseq data, and clinical information from TCGA database. LncRNA, miRNA, and mRNA signatures were identified to construct risk score as independent indicators of the prognostic value in CRC patients. A composite clinicopathologic–genomic nomogram was developed to predict the overall survival (OS). One hundred sixty-one CRC-specific lncRNAs, 97 miRNAs, and 161 mRNAs were identified to construct the ceRNA network. Multivariate Cox proportional hazards regression analysis indicated that nine-lncRNA signatures, eight-miRNA signatures, and five-mRNA signatures showed a significant prognostic value for CRC. Furthermore, a clinicopathologic–genomic nomogram was constructed in the primary cohort, which performed well in both the primary and validation sets. This study presents a nomogram that incorporates the CRC-specific ceRNA expression profile, clinical features, and pathological factors, which demonstrate its excellent differentiation and risk stratification in predicting OS in CRC patients.
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spelling pubmed-73443312020-07-24 The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer Li, Wei Yu, Weifang Jiang, Xia Gao, Xian Wang, Guiqi Jin, Xiaojing Zhao, Zengren Liu, Yuegeng Front Genet Genetics Competing endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the tumorigenesis, metastasis, diagnosis, and predicting survival of various cancers. In this study, we constructed a ceRNA network in colorectal cancer (CRC). Then, we sought to develop and validate a composite clinicopathologic–genomic nomogram using The Cancer Genome Atlas (TCGA) database. To construct the ceRNA network in CRC, we analyzed the mRNAseq, miRNAseq data, and clinical information from TCGA database. LncRNA, miRNA, and mRNA signatures were identified to construct risk score as independent indicators of the prognostic value in CRC patients. A composite clinicopathologic–genomic nomogram was developed to predict the overall survival (OS). One hundred sixty-one CRC-specific lncRNAs, 97 miRNAs, and 161 mRNAs were identified to construct the ceRNA network. Multivariate Cox proportional hazards regression analysis indicated that nine-lncRNA signatures, eight-miRNA signatures, and five-mRNA signatures showed a significant prognostic value for CRC. Furthermore, a clinicopathologic–genomic nomogram was constructed in the primary cohort, which performed well in both the primary and validation sets. This study presents a nomogram that incorporates the CRC-specific ceRNA expression profile, clinical features, and pathological factors, which demonstrate its excellent differentiation and risk stratification in predicting OS in CRC patients. Frontiers Media S.A. 2020-06-23 /pmc/articles/PMC7344331/ /pubmed/32714366 http://dx.doi.org/10.3389/fgene.2020.00583 Text en Copyright © 2020 Li, Yu, Jiang, Gao, Wang, Jin, Zhao and Liu. http://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
Li, Wei
Yu, Weifang
Jiang, Xia
Gao, Xian
Wang, Guiqi
Jin, Xiaojing
Zhao, Zengren
Liu, Yuegeng
The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer
title The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer
title_full The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer
title_fullStr The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer
title_full_unstemmed The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer
title_short The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer
title_sort construction and comprehensive prognostic analysis of the lncrna-associated competitive endogenous rnas network in colorectal cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344331/
https://www.ncbi.nlm.nih.gov/pubmed/32714366
http://dx.doi.org/10.3389/fgene.2020.00583
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