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Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer
BACKGROUND: ceRNAs have emerged as pivotal players in the regulation of gene expression and play a crucial role in the physiology and development of various cancers. Nevertheless, the function and underlying mechanisms of ceRNAs in esophageal cancer (EC) are still largely unknown. METHODS: In this s...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6312067/ https://www.ncbi.nlm.nih.gov/pubmed/30643460 http://dx.doi.org/10.2147/CMAR.S183310 |
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author | Chen, Li-Ping Wang, Hong Zhang, Yi Chen, Qiu-Xiang Lin, Tie-Su Liu, Zong-Qin Zhou, Yang-Yang |
author_facet | Chen, Li-Ping Wang, Hong Zhang, Yi Chen, Qiu-Xiang Lin, Tie-Su Liu, Zong-Qin Zhou, Yang-Yang |
author_sort | Chen, Li-Ping |
collection | PubMed |
description | BACKGROUND: ceRNAs have emerged as pivotal players in the regulation of gene expression and play a crucial role in the physiology and development of various cancers. Nevertheless, the function and underlying mechanisms of ceRNAs in esophageal cancer (EC) are still largely unknown. METHODS: In this study, profiles of DEmRNAs, DElncRNAs, and DEmiRNAs between normal and EC tumor tissue samples were obtained from the Cancer Genome Atlas database using the DESeq package in R by setting the adjusted P<0.05 and |log(2)(fold change)|>2 as the cutoff. The ceRNA network (ceRNet) was initially constructed to reveal the interaction of these ceRNAs during carcinogenesis based on the bioinformatics of miRcode, miRDB, miRTarBase, and TargetScan. Then, independent microarray data of GSE6188, GSE89102, and GSE92396 and correlation analysis were used to validate molecular biomarkers in the initial ceRNet. Finally, a least absolute shrinkage and selection operator logistic regression model was built using an oncogenic ceRNet to diagnose EC more accurately. RESULTS: We successfully constructed an oncogenic ceRNet of EC, crosstalk of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1. In addition, the risk-score model −0.0053*log(2)(CADM2)+0.0168*log(2)(SERPINE1)-0.0073*log(2)(ADAMTS9-AS2)+0.0905*log(2)(PVT1)+0.0047*log(2)(hsa-miR372)–0.0193*log(2)(hsa-miR145), (log(2)[gene count]) could improve diagnosis of EC with an AUC of 0.988. CONCLUSION: We identified two novel pairs of ceRNAs in EC and its role of diagnosis. The pairs of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1 were likely potential carcinogenic mechanisms of EC, and their joint detection could improve diagnostic accuracy. |
format | Online Article Text |
id | pubmed-6312067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63120672019-01-14 Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer Chen, Li-Ping Wang, Hong Zhang, Yi Chen, Qiu-Xiang Lin, Tie-Su Liu, Zong-Qin Zhou, Yang-Yang Cancer Manag Res Original Research BACKGROUND: ceRNAs have emerged as pivotal players in the regulation of gene expression and play a crucial role in the physiology and development of various cancers. Nevertheless, the function and underlying mechanisms of ceRNAs in esophageal cancer (EC) are still largely unknown. METHODS: In this study, profiles of DEmRNAs, DElncRNAs, and DEmiRNAs between normal and EC tumor tissue samples were obtained from the Cancer Genome Atlas database using the DESeq package in R by setting the adjusted P<0.05 and |log(2)(fold change)|>2 as the cutoff. The ceRNA network (ceRNet) was initially constructed to reveal the interaction of these ceRNAs during carcinogenesis based on the bioinformatics of miRcode, miRDB, miRTarBase, and TargetScan. Then, independent microarray data of GSE6188, GSE89102, and GSE92396 and correlation analysis were used to validate molecular biomarkers in the initial ceRNet. Finally, a least absolute shrinkage and selection operator logistic regression model was built using an oncogenic ceRNet to diagnose EC more accurately. RESULTS: We successfully constructed an oncogenic ceRNet of EC, crosstalk of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1. In addition, the risk-score model −0.0053*log(2)(CADM2)+0.0168*log(2)(SERPINE1)-0.0073*log(2)(ADAMTS9-AS2)+0.0905*log(2)(PVT1)+0.0047*log(2)(hsa-miR372)–0.0193*log(2)(hsa-miR145), (log(2)[gene count]) could improve diagnosis of EC with an AUC of 0.988. CONCLUSION: We identified two novel pairs of ceRNAs in EC and its role of diagnosis. The pairs of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1 were likely potential carcinogenic mechanisms of EC, and their joint detection could improve diagnostic accuracy. Dove Medical Press 2018-12-27 /pmc/articles/PMC6312067/ /pubmed/30643460 http://dx.doi.org/10.2147/CMAR.S183310 Text en © 2019 Chen et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Chen, Li-Ping Wang, Hong Zhang, Yi Chen, Qiu-Xiang Lin, Tie-Su Liu, Zong-Qin Zhou, Yang-Yang Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer |
title | Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer |
title_full | Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer |
title_fullStr | Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer |
title_full_unstemmed | Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer |
title_short | Robust analysis of novel mRNA–lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer |
title_sort | robust analysis of novel mrna–lncrna cross talk based on cerna hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6312067/ https://www.ncbi.nlm.nih.gov/pubmed/30643460 http://dx.doi.org/10.2147/CMAR.S183310 |
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