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Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database

OBJECTIVE: Long noncoding RNA (lncRNA) has received more and more attention in human tumor research. This study is aimed at clarifying the regulatory network of lncRNAs-microRNAs- (miRNAs-) mRNAs and at determining the relevant targets in the development of endometrial cancers. METHODS: Download the...

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Autores principales: Song, Yuchun, Chu, Ping, Li, Pan, Li, Fengling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273428/
https://www.ncbi.nlm.nih.gov/pubmed/35832124
http://dx.doi.org/10.1155/2022/1418232
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author Song, Yuchun
Chu, Ping
Li, Pan
Li, Fengling
author_facet Song, Yuchun
Chu, Ping
Li, Pan
Li, Fengling
author_sort Song, Yuchun
collection PubMed
description OBJECTIVE: Long noncoding RNA (lncRNA) has received more and more attention in human tumor research. This study is aimed at clarifying the regulatory network of lncRNAs-microRNAs- (miRNAs-) mRNAs and at determining the relevant targets in the development of endometrial cancers. METHODS: Download the miRNA, mRNA, and lncRNA expression profile data of endometrial cancer patients from TCGA; use the “DESeq2” package of R software to identify the differential expression of miRNAs, mRNAs, and lncRNAs; construct a network of ceRNA; and perform gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment assessment on mRNAs in the network of ceRNA; string and Cytoscape 3.7.2 perform PPI assessment on target genes and TOP 10 hub gene screening; Cytoscape 3.7.2 computer program was employed for constructing the lncRNA-miRNA-TOP10 hub mRNA network diagram to determine the signal axis; StarBase database to verify the Top10 hub mRNA expression; the “survival” package in R computer program was implemented to analyze the survival rate of all genes on the lncRNA-miRNA-Top10 hub mRNA network diagram; RT-qPCR to verify the expression level of genes on the signal axis. RESULTS: 1119 differential mRNAs, 14 differential lncRNAs, and 65 differential miRNAs were screened in TCGA; we constructed a ceRNA regulatory network composed of 5 DELs, 7 DEMs, and 90 DEGs; String combined with Cytoscape to screen out Top10 hub genes, namely: LEFTY1, LIN28A, LHX3, ST8SIA3, CEP55, FBXO32, DCN, ANGPTL1, ADRA1A, and KCNMA1; the StarBase database verification results show that ADRA1A, ANGPTL1, FBXO32, KCNMA1, and DCN are downregulated in endometrial cancer tissues; LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 are upregulated in endometrial cancer; the constructed lncRNA-miRNA-hub Top10 mRNA network map identified CTD-2314B22, RP11-89 K21/hsa-miR-143, hsa-miR-424/LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 signal axis; survival analysis results show that CTD-2314B22, RP11-89 K21, hsa-miR-96, hsa-miR-211, LHX3, ST8SIA3, and DCN are all related to survival; RT-qPCR results indicate CTD-2314B22, RP11-89 K21, LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 are upregulated in endometrial cancer cells, and hsa-miR-143 and hsa-miR-424 are downregulated in endometrial cancer cells. CONCLUSION: From the perspective of the lncRNA-miRNA-mRNA network, our study identified CTD-2314B22, RP11-89 K21/hsa-miR-143, hsa-miR-424/LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 signal axis, which can present considerably potent biomarkers and therapeutic targets for treating endometrial cancer.
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spelling pubmed-92734282022-07-12 Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database Song, Yuchun Chu, Ping Li, Pan Li, Fengling Comput Math Methods Med Research Article OBJECTIVE: Long noncoding RNA (lncRNA) has received more and more attention in human tumor research. This study is aimed at clarifying the regulatory network of lncRNAs-microRNAs- (miRNAs-) mRNAs and at determining the relevant targets in the development of endometrial cancers. METHODS: Download the miRNA, mRNA, and lncRNA expression profile data of endometrial cancer patients from TCGA; use the “DESeq2” package of R software to identify the differential expression of miRNAs, mRNAs, and lncRNAs; construct a network of ceRNA; and perform gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment assessment on mRNAs in the network of ceRNA; string and Cytoscape 3.7.2 perform PPI assessment on target genes and TOP 10 hub gene screening; Cytoscape 3.7.2 computer program was employed for constructing the lncRNA-miRNA-TOP10 hub mRNA network diagram to determine the signal axis; StarBase database to verify the Top10 hub mRNA expression; the “survival” package in R computer program was implemented to analyze the survival rate of all genes on the lncRNA-miRNA-Top10 hub mRNA network diagram; RT-qPCR to verify the expression level of genes on the signal axis. RESULTS: 1119 differential mRNAs, 14 differential lncRNAs, and 65 differential miRNAs were screened in TCGA; we constructed a ceRNA regulatory network composed of 5 DELs, 7 DEMs, and 90 DEGs; String combined with Cytoscape to screen out Top10 hub genes, namely: LEFTY1, LIN28A, LHX3, ST8SIA3, CEP55, FBXO32, DCN, ANGPTL1, ADRA1A, and KCNMA1; the StarBase database verification results show that ADRA1A, ANGPTL1, FBXO32, KCNMA1, and DCN are downregulated in endometrial cancer tissues; LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 are upregulated in endometrial cancer; the constructed lncRNA-miRNA-hub Top10 mRNA network map identified CTD-2314B22, RP11-89 K21/hsa-miR-143, hsa-miR-424/LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 signal axis; survival analysis results show that CTD-2314B22, RP11-89 K21, hsa-miR-96, hsa-miR-211, LHX3, ST8SIA3, and DCN are all related to survival; RT-qPCR results indicate CTD-2314B22, RP11-89 K21, LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 are upregulated in endometrial cancer cells, and hsa-miR-143 and hsa-miR-424 are downregulated in endometrial cancer cells. CONCLUSION: From the perspective of the lncRNA-miRNA-mRNA network, our study identified CTD-2314B22, RP11-89 K21/hsa-miR-143, hsa-miR-424/LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 signal axis, which can present considerably potent biomarkers and therapeutic targets for treating endometrial cancer. Hindawi 2022-07-04 /pmc/articles/PMC9273428/ /pubmed/35832124 http://dx.doi.org/10.1155/2022/1418232 Text en Copyright © 2022 Yuchun Song et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Song, Yuchun
Chu, Ping
Li, Pan
Li, Fengling
Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database
title Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database
title_full Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database
title_fullStr Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database
title_full_unstemmed Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database
title_short Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database
title_sort construction of endometrial carcinoma cerna network and screening of key genes based on tcga database
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273428/
https://www.ncbi.nlm.nih.gov/pubmed/35832124
http://dx.doi.org/10.1155/2022/1418232
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