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Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors

BACKGROUND: Thymic epithelial tumors (TETs), originating from the thymic epithelial cells, are the most common primary neoplasms of the anterior mediastinum. Emerging evidence demonstrated that the competing endogenous RNAs (ceRNAs) exerted a crucial effect on tumor development. Hence, it is urgent...

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Autores principales: Chen, Kegong, Bai, Long, Ji, Lin, Wu, Libo, Li, Guanghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213305/
https://www.ncbi.nlm.nih.gov/pubmed/34128858
http://dx.doi.org/10.1097/MD.0000000000026271
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author Chen, Kegong
Bai, Long
Ji, Lin
Wu, Libo
Li, Guanghua
author_facet Chen, Kegong
Bai, Long
Ji, Lin
Wu, Libo
Li, Guanghua
author_sort Chen, Kegong
collection PubMed
description BACKGROUND: Thymic epithelial tumors (TETs), originating from the thymic epithelial cells, are the most common primary neoplasms of the anterior mediastinum. Emerging evidence demonstrated that the competing endogenous RNAs (ceRNAs) exerted a crucial effect on tumor development. Hence, it is urgent to understand the regulatory mechanism of ceRNAs in TETs and its impact on tumor prognosis. METHODS: TETs datasets were harvested from the UCSC Xena as the training cohort, followed by differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) at different pathologic type (A, AB, B, and TC) identified via DESeq2 package. clusterProfiler package was utilized to carry out gene ontology and Kyoto encyclopedia of genes and genomes functional analysis on the DEmRNAs. Subsequently, the lncRNA-miRNA-mRNA regulatory network was constructed to screen the key DEmRNAs. After the key DEmRNAs were verified in the external cohort from Gene Expression Omnibus database, their associated-ceRNAs modules were used to perform the K-M and Cox regression analysis to build a prognostic significance for TETs. Lastly, the feasibility of the prognostic significance was validated by receiver operating characteristic (ROC) curves and the area under the curve. RESULTS: Finally, a total of 463 DEmRNAs, 87 DElncRNAs, and 20 DEmiRNAs were obtained from the intersection of differentially expressed genes in different pathological types of TETs. Functional enrichment analysis showed that the DEmRNAs were closely related to cell proliferation and tumor development. After lncRNA-miRNA-mRNA network construction and external cohort validation, a total of 4 DEmRNAs DOCK11, MCAM, MYO10, and WASF3 were identified and their associated-ceRNA modules were significantly associated with prognosis, which contained 3 lncRNAs (lncRNA LINC00665, lncRNA NR2F1-AS1, and lncRNA RP11-285A1.1), 4 mRNAs (DOCK11, MCAM, MYO10, and WASF3), and 4 miRNAs (hsa-mir-143, hsa-mir-141, hsa-mir-140, and hsa-mir-3199). Meanwhile, ROC curves verified the accuracy of prediction ability of the screened ceRNA modules for prognosis of TETs. CONCLUSION: Our study revealed that ceRNAs modules might exert a crucial role in the progression of TETs. The mRNA associated-ceRNA modules could effectively predict the prognosis of TETs, which might be the potential prognostic and therapeutic markers for TETs patients.
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spelling pubmed-82133052021-06-21 Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors Chen, Kegong Bai, Long Ji, Lin Wu, Libo Li, Guanghua Medicine (Baltimore) 5700 BACKGROUND: Thymic epithelial tumors (TETs), originating from the thymic epithelial cells, are the most common primary neoplasms of the anterior mediastinum. Emerging evidence demonstrated that the competing endogenous RNAs (ceRNAs) exerted a crucial effect on tumor development. Hence, it is urgent to understand the regulatory mechanism of ceRNAs in TETs and its impact on tumor prognosis. METHODS: TETs datasets were harvested from the UCSC Xena as the training cohort, followed by differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) at different pathologic type (A, AB, B, and TC) identified via DESeq2 package. clusterProfiler package was utilized to carry out gene ontology and Kyoto encyclopedia of genes and genomes functional analysis on the DEmRNAs. Subsequently, the lncRNA-miRNA-mRNA regulatory network was constructed to screen the key DEmRNAs. After the key DEmRNAs were verified in the external cohort from Gene Expression Omnibus database, their associated-ceRNAs modules were used to perform the K-M and Cox regression analysis to build a prognostic significance for TETs. Lastly, the feasibility of the prognostic significance was validated by receiver operating characteristic (ROC) curves and the area under the curve. RESULTS: Finally, a total of 463 DEmRNAs, 87 DElncRNAs, and 20 DEmiRNAs were obtained from the intersection of differentially expressed genes in different pathological types of TETs. Functional enrichment analysis showed that the DEmRNAs were closely related to cell proliferation and tumor development. After lncRNA-miRNA-mRNA network construction and external cohort validation, a total of 4 DEmRNAs DOCK11, MCAM, MYO10, and WASF3 were identified and their associated-ceRNA modules were significantly associated with prognosis, which contained 3 lncRNAs (lncRNA LINC00665, lncRNA NR2F1-AS1, and lncRNA RP11-285A1.1), 4 mRNAs (DOCK11, MCAM, MYO10, and WASF3), and 4 miRNAs (hsa-mir-143, hsa-mir-141, hsa-mir-140, and hsa-mir-3199). Meanwhile, ROC curves verified the accuracy of prediction ability of the screened ceRNA modules for prognosis of TETs. CONCLUSION: Our study revealed that ceRNAs modules might exert a crucial role in the progression of TETs. The mRNA associated-ceRNA modules could effectively predict the prognosis of TETs, which might be the potential prognostic and therapeutic markers for TETs patients. Lippincott Williams & Wilkins 2021-06-18 /pmc/articles/PMC8213305/ /pubmed/34128858 http://dx.doi.org/10.1097/MD.0000000000026271 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/)
spellingShingle 5700
Chen, Kegong
Bai, Long
Ji, Lin
Wu, Libo
Li, Guanghua
Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors
title Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors
title_full Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors
title_fullStr Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors
title_full_unstemmed Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors
title_short Bioinformatics analysis of the key potential ceRNA biomarkers in human thymic epithelial tumors
title_sort bioinformatics analysis of the key potential cerna biomarkers in human thymic epithelial tumors
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213305/
https://www.ncbi.nlm.nih.gov/pubmed/34128858
http://dx.doi.org/10.1097/MD.0000000000026271
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