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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...

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Autores principales: Chen, Li-Ping, Wang, Hong, Zhang, Yi, Chen, Qiu-Xiang, Lin, Tie-Su, Liu, Zong-Qin, Zhou, Yang-Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
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.
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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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