Cargando…
Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database
BACKGROUND: Wilms tumor (WT) was the most common malignant tumor of urinary system in children. With the advances in gene sequencing, research of molecular mechanism of WT tumor was gradually increasing. However, few studies have explored the influence of competing endogenous RNA (ceRNA) in WT. Acco...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214997/ https://www.ncbi.nlm.nih.gov/pubmed/32420153 http://dx.doi.org/10.21037/tau.2020.01.34 |
_version_ | 1783532089845481472 |
---|---|
author | Guan, Bo Qi, Feng Tian, Ye |
author_facet | Guan, Bo Qi, Feng Tian, Ye |
author_sort | Guan, Bo |
collection | PubMed |
description | BACKGROUND: Wilms tumor (WT) was the most common malignant tumor of urinary system in children. With the advances in gene sequencing, research of molecular mechanism of WT tumor was gradually increasing. However, few studies have explored the influence of competing endogenous RNA (ceRNA) in WT. Accordingly, we aimed to explore the mechanisms of ceRNA co-expression network in WT. METHODS: A total of 6 non-tumor controls and 127 WT patients’ RNA-seq data combined with clinical data was acquired from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Differentially expressed lncRNA, miRNA and mRNA between WT tissues and normal tissues were analyzed using “edgeR” package in R software. Weighted gene co-expression network analysis (WGCNA) was utilized to construct the ceRNA co-expression network while Molecular Complex Detection (MCODE) algorithm was used to extract the pivotal sub-network. Function annotation of mRNA was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Survival analysis was then conducted based on long-rank test and Kaplan-Meier curves using the survival package. RESULTS: By applying the “edgeR” package in R, the transcriptome expression data of 127 WT tissues with 6 normal tissues were normalized. Moreover, 146 DElncRNAs, 62 DEmiRNAs, 287 DEmRNAs of them were involved in ceRNA network after applying WGCNA. According to MCODE, we identified that the interactions between LINC002253 (lncRNA) and TRIM71 (mRNA) was mediated by hsa-mir-301a and hsa-mir-301b (miRNA). Furthermore, we detected 13 DElncRNAs which were significantly associated with the progression of WT. CONCLUSIONS: We used WGCNA method to construct the WT ceRNA network for the first time. TRIM71 was identified to be the most closely related genes involved in hub sub-network by MCDOE, suggesting it might act as a new drug target and prognostic factor based on our comprehensive results. |
format | Online Article Text |
id | pubmed-7214997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-72149972020-05-15 Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database Guan, Bo Qi, Feng Tian, Ye Transl Androl Urol Original Article BACKGROUND: Wilms tumor (WT) was the most common malignant tumor of urinary system in children. With the advances in gene sequencing, research of molecular mechanism of WT tumor was gradually increasing. However, few studies have explored the influence of competing endogenous RNA (ceRNA) in WT. Accordingly, we aimed to explore the mechanisms of ceRNA co-expression network in WT. METHODS: A total of 6 non-tumor controls and 127 WT patients’ RNA-seq data combined with clinical data was acquired from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Differentially expressed lncRNA, miRNA and mRNA between WT tissues and normal tissues were analyzed using “edgeR” package in R software. Weighted gene co-expression network analysis (WGCNA) was utilized to construct the ceRNA co-expression network while Molecular Complex Detection (MCODE) algorithm was used to extract the pivotal sub-network. Function annotation of mRNA was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Survival analysis was then conducted based on long-rank test and Kaplan-Meier curves using the survival package. RESULTS: By applying the “edgeR” package in R, the transcriptome expression data of 127 WT tissues with 6 normal tissues were normalized. Moreover, 146 DElncRNAs, 62 DEmiRNAs, 287 DEmRNAs of them were involved in ceRNA network after applying WGCNA. According to MCODE, we identified that the interactions between LINC002253 (lncRNA) and TRIM71 (mRNA) was mediated by hsa-mir-301a and hsa-mir-301b (miRNA). Furthermore, we detected 13 DElncRNAs which were significantly associated with the progression of WT. CONCLUSIONS: We used WGCNA method to construct the WT ceRNA network for the first time. TRIM71 was identified to be the most closely related genes involved in hub sub-network by MCDOE, suggesting it might act as a new drug target and prognostic factor based on our comprehensive results. AME Publishing Company 2020-04 /pmc/articles/PMC7214997/ /pubmed/32420153 http://dx.doi.org/10.21037/tau.2020.01.34 Text en 2020 Translational Andrology and Urology. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Guan, Bo Qi, Feng Tian, Ye Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database |
title | Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database |
title_full | Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database |
title_fullStr | Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database |
title_full_unstemmed | Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database |
title_short | Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database |
title_sort | comprehensive analysis of competing endogenous rna network in wilms tumor based on the target database |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214997/ https://www.ncbi.nlm.nih.gov/pubmed/32420153 http://dx.doi.org/10.21037/tau.2020.01.34 |
work_keys_str_mv | AT guanbo comprehensiveanalysisofcompetingendogenousrnanetworkinwilmstumorbasedonthetargetdatabase AT qifeng comprehensiveanalysisofcompetingendogenousrnanetworkinwilmstumorbasedonthetargetdatabase AT tianye comprehensiveanalysisofcompetingendogenousrnanetworkinwilmstumorbasedonthetargetdatabase |