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Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data

BACKGROUND: The current study set out to identify the miRNA-mRNA regulatory networks that influence the radiosensitivity in esophageal cancer based on the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. METHODS: Firstly, esophageal cancer-related miRNA-seq and mRNA-se...

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Autores principales: Chen, Hongmin, Shi, Xiaoxiao, Ren, Li, Zhuo, Hongyu, Zeng, Li, Qin, Qing, Wan, Yuming, Sangdan, Wangmu, Zhou, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714096/
https://www.ncbi.nlm.nih.gov/pubmed/36456979
http://dx.doi.org/10.1186/s12920-022-01392-9
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author Chen, Hongmin
Shi, Xiaoxiao
Ren, Li
Zhuo, Hongyu
Zeng, Li
Qin, Qing
Wan, Yuming
Sangdan, Wangmu
Zhou, Lin
author_facet Chen, Hongmin
Shi, Xiaoxiao
Ren, Li
Zhuo, Hongyu
Zeng, Li
Qin, Qing
Wan, Yuming
Sangdan, Wangmu
Zhou, Lin
author_sort Chen, Hongmin
collection PubMed
description BACKGROUND: The current study set out to identify the miRNA-mRNA regulatory networks that influence the radiosensitivity in esophageal cancer based on the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. METHODS: Firstly, esophageal cancer-related miRNA-seq and mRNA-seq data were retrieved from the TCGA database, and the mRNA dataset of esophageal cancer radiotherapy was downloaded from the GEO database to analyze the differential expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) in radiosensitive and radioresistant samples, followed by the construction of the miRNA-mRNA regulatory network and Gene Ontology and KEGG enrichment analysis. Additionally, a prognostic risk model was constructed, and its accuracy was evaluated by means of receiver operating characteristic analysis. RESULTS: A total of 125 DEmiRNAs and 42 DEmRNAs were closely related to the radiosensitivity in patients with esophageal cancer. Based on 47 miRNA-mRNA interactions, including 21 miRNAs and 21 mRNAs, the miRNA-mRNA regulatory network was constructed. The prognostic risk model based on 2 miRNAs (miR-132-3p and miR-576-5p) and 4 mRNAs (CAND1, ZDHHC23, AHR, and MTMR4) could accurately predict the prognosis of esophageal cancer patients. Finally, it was verified that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR could affect the radiosensitivity in esophageal cancer. CONCLUSION: Our study demonstrated that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR were critical molecular pathways related to the radiosensitivity of esophageal cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01392-9.
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spelling pubmed-97140962022-12-02 Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data Chen, Hongmin Shi, Xiaoxiao Ren, Li Zhuo, Hongyu Zeng, Li Qin, Qing Wan, Yuming Sangdan, Wangmu Zhou, Lin BMC Med Genomics Research BACKGROUND: The current study set out to identify the miRNA-mRNA regulatory networks that influence the radiosensitivity in esophageal cancer based on the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. METHODS: Firstly, esophageal cancer-related miRNA-seq and mRNA-seq data were retrieved from the TCGA database, and the mRNA dataset of esophageal cancer radiotherapy was downloaded from the GEO database to analyze the differential expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) in radiosensitive and radioresistant samples, followed by the construction of the miRNA-mRNA regulatory network and Gene Ontology and KEGG enrichment analysis. Additionally, a prognostic risk model was constructed, and its accuracy was evaluated by means of receiver operating characteristic analysis. RESULTS: A total of 125 DEmiRNAs and 42 DEmRNAs were closely related to the radiosensitivity in patients with esophageal cancer. Based on 47 miRNA-mRNA interactions, including 21 miRNAs and 21 mRNAs, the miRNA-mRNA regulatory network was constructed. The prognostic risk model based on 2 miRNAs (miR-132-3p and miR-576-5p) and 4 mRNAs (CAND1, ZDHHC23, AHR, and MTMR4) could accurately predict the prognosis of esophageal cancer patients. Finally, it was verified that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR could affect the radiosensitivity in esophageal cancer. CONCLUSION: Our study demonstrated that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR were critical molecular pathways related to the radiosensitivity of esophageal cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01392-9. BioMed Central 2022-12-01 /pmc/articles/PMC9714096/ /pubmed/36456979 http://dx.doi.org/10.1186/s12920-022-01392-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Hongmin
Shi, Xiaoxiao
Ren, Li
Zhuo, Hongyu
Zeng, Li
Qin, Qing
Wan, Yuming
Sangdan, Wangmu
Zhou, Lin
Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data
title Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data
title_full Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data
title_fullStr Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data
title_full_unstemmed Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data
title_short Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data
title_sort identification of the mirna-mrna regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the tcga and geo data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714096/
https://www.ncbi.nlm.nih.gov/pubmed/36456979
http://dx.doi.org/10.1186/s12920-022-01392-9
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