Cargando…

Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network

BACKGROUND: The purpose of this study was to investigate the regulatory mechanisms of ceRNAs in breast cancer (BC) and construct a new five-mRNA prognostic signature. METHODS: The ceRNA network was constructed by different RNAs screened by the edgeR package. The BC prognostic signature was built bas...

Descripción completa

Detalles Bibliográficos
Autores principales: Shi, Wenjie, Hu, Daojun, Lin, Sen, Zhuo, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486635/
https://www.ncbi.nlm.nih.gov/pubmed/32964046
http://dx.doi.org/10.1155/2020/9081852
_version_ 1783581362333155328
author Shi, Wenjie
Hu, Daojun
Lin, Sen
Zhuo, Rui
author_facet Shi, Wenjie
Hu, Daojun
Lin, Sen
Zhuo, Rui
author_sort Shi, Wenjie
collection PubMed
description BACKGROUND: The purpose of this study was to investigate the regulatory mechanisms of ceRNAs in breast cancer (BC) and construct a new five-mRNA prognostic signature. METHODS: The ceRNA network was constructed by different RNAs screened by the edgeR package. The BC prognostic signature was built based on the Cox regression analysis. The log-rank method was used to analyse the survival rate of BC patients with different risk scores. The expression of the 5 genes was verified by the GSE81540 dataset and CPTAC database. RESULTS: A total of 41 BC-adjacent tissues and 473 BC tissues were included in this study. A total of 2,966 differentially expressed lncRNAs, 5,370 differentially expressed mRNAs, and 359 differentially expressed miRNAs were screened. The ceRNA network was constructed using 13 lncRNAs, 267 mRNAs, and 35 miRNAs. Kaplan-Meier (K-M) methods showed that two lncRNAs (AC037487.1 and MIR22HG) are related to prognosis. Five mRNAs (VPS28, COL17A1, HSF1, PUF60, and SMOC1) in the ceRNA network were used to establish a prognostic signature. Survival analysis showed that the prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p = 0.0022). ROC analysis showed that this signature has a good diagnostic ability (AUC = 0.77). Compared with clinical features, this signature was also an independent prognostic factor (HR: 1.206, 95% CI 1.108−1.311; p < 0.001). External verification results showed that the expression of the 5 mRNAs differed between the normal and tumour groups at the chip and protein levels (p < 0.001). CONCLUSIONS: These ceRNAs may play a key role in the development of BC, and the new 5-mRNA prognostic signature can improve the prediction of survival for BC patients.
format Online
Article
Text
id pubmed-7486635
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-74866352020-09-21 Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network Shi, Wenjie Hu, Daojun Lin, Sen Zhuo, Rui Biomed Res Int Research Article BACKGROUND: The purpose of this study was to investigate the regulatory mechanisms of ceRNAs in breast cancer (BC) and construct a new five-mRNA prognostic signature. METHODS: The ceRNA network was constructed by different RNAs screened by the edgeR package. The BC prognostic signature was built based on the Cox regression analysis. The log-rank method was used to analyse the survival rate of BC patients with different risk scores. The expression of the 5 genes was verified by the GSE81540 dataset and CPTAC database. RESULTS: A total of 41 BC-adjacent tissues and 473 BC tissues were included in this study. A total of 2,966 differentially expressed lncRNAs, 5,370 differentially expressed mRNAs, and 359 differentially expressed miRNAs were screened. The ceRNA network was constructed using 13 lncRNAs, 267 mRNAs, and 35 miRNAs. Kaplan-Meier (K-M) methods showed that two lncRNAs (AC037487.1 and MIR22HG) are related to prognosis. Five mRNAs (VPS28, COL17A1, HSF1, PUF60, and SMOC1) in the ceRNA network were used to establish a prognostic signature. Survival analysis showed that the prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p = 0.0022). ROC analysis showed that this signature has a good diagnostic ability (AUC = 0.77). Compared with clinical features, this signature was also an independent prognostic factor (HR: 1.206, 95% CI 1.108−1.311; p < 0.001). External verification results showed that the expression of the 5 mRNAs differed between the normal and tumour groups at the chip and protein levels (p < 0.001). CONCLUSIONS: These ceRNAs may play a key role in the development of BC, and the new 5-mRNA prognostic signature can improve the prediction of survival for BC patients. Hindawi 2020-09-03 /pmc/articles/PMC7486635/ /pubmed/32964046 http://dx.doi.org/10.1155/2020/9081852 Text en Copyright © 2020 Wenjie Shi 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
Shi, Wenjie
Hu, Daojun
Lin, Sen
Zhuo, Rui
Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network
title Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network
title_full Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network
title_fullStr Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network
title_full_unstemmed Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network
title_short Five-mRNA Signature for the Prognosis of Breast Cancer Based on the ceRNA Network
title_sort five-mrna signature for the prognosis of breast cancer based on the cerna network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486635/
https://www.ncbi.nlm.nih.gov/pubmed/32964046
http://dx.doi.org/10.1155/2020/9081852
work_keys_str_mv AT shiwenjie fivemrnasignaturefortheprognosisofbreastcancerbasedonthecernanetwork
AT hudaojun fivemrnasignaturefortheprognosisofbreastcancerbasedonthecernanetwork
AT linsen fivemrnasignaturefortheprognosisofbreastcancerbasedonthecernanetwork
AT zhuorui fivemrnasignaturefortheprognosisofbreastcancerbasedonthecernanetwork