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Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer

Studies have shown the difference appearing among the prognosis of patients in different age groups. However, the molecular mechanism implicated in this disparity have not been elaborated. In this study, expression profiles of female breast cancer (BRCA) associated mRNAs, lncRNAs and miRNAs were dow...

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Autores principales: Liu, Zhi-Qin, Zhang, Gao-Tao, Jiang, Li, Li, Chun-Qing, Chen, Que-Ting, Luo, Du-Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097183/
https://www.ncbi.nlm.nih.gov/pubmed/33968126
http://dx.doi.org/10.3389/fgene.2021.603544
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author Liu, Zhi-Qin
Zhang, Gao-Tao
Jiang, Li
Li, Chun-Qing
Chen, Que-Ting
Luo, Du-Qiang
author_facet Liu, Zhi-Qin
Zhang, Gao-Tao
Jiang, Li
Li, Chun-Qing
Chen, Que-Ting
Luo, Du-Qiang
author_sort Liu, Zhi-Qin
collection PubMed
description Studies have shown the difference appearing among the prognosis of patients in different age groups. However, the molecular mechanism implicated in this disparity have not been elaborated. In this study, expression profiles of female breast cancer (BRCA) associated mRNAs, lncRNAs and miRNAs were downloaded from the TCGA database. The sample were manually classified into three groups according to their age at initial pathological diagnosis: young (age ≤ 39 years), elderly (age ≥ 65 years), and intermediate (age 40–64 years). lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network was respectively constructed for different age BRCA. Then, the biological functions of differentially expressed mRNAs (DEmRNAs) in ceRNA network were further investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, survival analysis was used to identify prognostic biomarkers for different age BRCA patients. We identified 13 RNAs, 38 RNAs and 40 RNAs specific to patients aged ≤ 39 years, aged 40–64 years, and aged ≥ 65 years, respectively. Furthermore, the unique pathways were mainly enriched in cytokine-cytokine receptor interaction in patients aged 40–64 years, and were mainly enriched in TGF-beta signaling pathway in patients aged ≥ 65 years. According to the survival analysis, AGAP11, has-mir-301b, and OSR1 were respectively functioned as prognostic biomarkers in young, intermediate, and elderly group. In summary, our study identified the differences in the ceRNA regulatory networks and provides an effective bioinformatics basis for further understanding of the pathogenesis and predicting outcomes for different age BRCA.
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spelling pubmed-80971832021-05-06 Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer Liu, Zhi-Qin Zhang, Gao-Tao Jiang, Li Li, Chun-Qing Chen, Que-Ting Luo, Du-Qiang Front Genet Genetics Studies have shown the difference appearing among the prognosis of patients in different age groups. However, the molecular mechanism implicated in this disparity have not been elaborated. In this study, expression profiles of female breast cancer (BRCA) associated mRNAs, lncRNAs and miRNAs were downloaded from the TCGA database. The sample were manually classified into three groups according to their age at initial pathological diagnosis: young (age ≤ 39 years), elderly (age ≥ 65 years), and intermediate (age 40–64 years). lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network was respectively constructed for different age BRCA. Then, the biological functions of differentially expressed mRNAs (DEmRNAs) in ceRNA network were further investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, survival analysis was used to identify prognostic biomarkers for different age BRCA patients. We identified 13 RNAs, 38 RNAs and 40 RNAs specific to patients aged ≤ 39 years, aged 40–64 years, and aged ≥ 65 years, respectively. Furthermore, the unique pathways were mainly enriched in cytokine-cytokine receptor interaction in patients aged 40–64 years, and were mainly enriched in TGF-beta signaling pathway in patients aged ≥ 65 years. According to the survival analysis, AGAP11, has-mir-301b, and OSR1 were respectively functioned as prognostic biomarkers in young, intermediate, and elderly group. In summary, our study identified the differences in the ceRNA regulatory networks and provides an effective bioinformatics basis for further understanding of the pathogenesis and predicting outcomes for different age BRCA. Frontiers Media S.A. 2021-04-21 /pmc/articles/PMC8097183/ /pubmed/33968126 http://dx.doi.org/10.3389/fgene.2021.603544 Text en Copyright © 2021 Liu, Zhang, Jiang, Li, Chen and Luo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Liu, Zhi-Qin
Zhang, Gao-Tao
Jiang, Li
Li, Chun-Qing
Chen, Que-Ting
Luo, Du-Qiang
Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer
title Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer
title_full Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer
title_fullStr Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer
title_full_unstemmed Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer
title_short Construction and Comparison of ceRNA Regulatory Network for Different Age Female Breast Cancer
title_sort construction and comparison of cerna regulatory network for different age female breast cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097183/
https://www.ncbi.nlm.nih.gov/pubmed/33968126
http://dx.doi.org/10.3389/fgene.2021.603544
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