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Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data

Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed...

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Autores principales: Zhao, Hongying, Zhang, Siwen, Yin, Xiangzhe, Zhang, Caiyu, Wang, Lixia, Liu, Kailai, Xu, Haotian, Liu, Wangyang, Bo, Lin, Lin, Shihua, Feng, Ke, Lin, Lin, Fei, Meiting, Ning, Shangwei, Wang, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9592759/
https://www.ncbi.nlm.nih.gov/pubmed/36304471
http://dx.doi.org/10.3389/fimmu.2022.990143
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author Zhao, Hongying
Zhang, Siwen
Yin, Xiangzhe
Zhang, Caiyu
Wang, Lixia
Liu, Kailai
Xu, Haotian
Liu, Wangyang
Bo, Lin
Lin, Shihua
Feng, Ke
Lin, Lin
Fei, Meiting
Ning, Shangwei
Wang, Li
author_facet Zhao, Hongying
Zhang, Siwen
Yin, Xiangzhe
Zhang, Caiyu
Wang, Lixia
Liu, Kailai
Xu, Haotian
Liu, Wangyang
Bo, Lin
Lin, Shihua
Feng, Ke
Lin, Lin
Fei, Meiting
Ning, Shangwei
Wang, Li
author_sort Zhao, Hongying
collection PubMed
description Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed an integrative approach to identify CNA-driven enhancers and their effect on expression of target genes in four breast cancer subtypes by integrating expression data, copy number data and H3K27ac data. We identified 672, 555, 531, 361 CNA-driven enhancer-gene pairs and 280, 189, 113 and 98 CNA-driven enhancer-lncRNA pairs in the Basal-like, Her2, LumA and LumB subtypes, respectively. We then reconstructed a CNV-driven enhancer-lncRNA-mRNA regulatory network in each subtype. Functional analysis showed CNA-driven enhancers play an important role in the progression of breast cancer subtypes by influencing P53 signaling pathway, PPAR signaling pathway, systemic lupus erythematosus and MAPK signaling pathway in the Basal-like, Her2, LumA and LumB subtypes, respectively. We characterized the potentially prognostic value of target genes of CNV-driven enhancer and lncRNA-mRNA pairs in the subtype-specific network. We identified MUM1 and AC016876.1 as prognostic biomarkers in LumA and Basal-like subtypes, respectively. Higher expression of MUM1 with an amplified enhancer exhibited poorer prognosis in LumA patients. Lower expression of AC016876.1 with a deleted enhancer exhibited poorer survival outcomes of Basal-like patients. We also identified enhancer-related lncRNA-mRNA pairs as prognostic biomarkers, including AC012313.2-MUM1 in the LumA, AC026471.4-PLK5 in the LumB, AC027307.2-OAZ1 in the Basal-like and AC022431.1-HCN2 in the Her2 subtypes. Finally, our results highlighted target genes of CNA-driven enhancers and enhancer-related lncRNA-mRNA pairs could act as prognostic markers and potential therapeutic targets in breast cancer subtypes.
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spelling pubmed-95927592022-10-26 Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data Zhao, Hongying Zhang, Siwen Yin, Xiangzhe Zhang, Caiyu Wang, Lixia Liu, Kailai Xu, Haotian Liu, Wangyang Bo, Lin Lin, Shihua Feng, Ke Lin, Lin Fei, Meiting Ning, Shangwei Wang, Li Front Immunol Immunology Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed an integrative approach to identify CNA-driven enhancers and their effect on expression of target genes in four breast cancer subtypes by integrating expression data, copy number data and H3K27ac data. We identified 672, 555, 531, 361 CNA-driven enhancer-gene pairs and 280, 189, 113 and 98 CNA-driven enhancer-lncRNA pairs in the Basal-like, Her2, LumA and LumB subtypes, respectively. We then reconstructed a CNV-driven enhancer-lncRNA-mRNA regulatory network in each subtype. Functional analysis showed CNA-driven enhancers play an important role in the progression of breast cancer subtypes by influencing P53 signaling pathway, PPAR signaling pathway, systemic lupus erythematosus and MAPK signaling pathway in the Basal-like, Her2, LumA and LumB subtypes, respectively. We characterized the potentially prognostic value of target genes of CNV-driven enhancer and lncRNA-mRNA pairs in the subtype-specific network. We identified MUM1 and AC016876.1 as prognostic biomarkers in LumA and Basal-like subtypes, respectively. Higher expression of MUM1 with an amplified enhancer exhibited poorer prognosis in LumA patients. Lower expression of AC016876.1 with a deleted enhancer exhibited poorer survival outcomes of Basal-like patients. We also identified enhancer-related lncRNA-mRNA pairs as prognostic biomarkers, including AC012313.2-MUM1 in the LumA, AC026471.4-PLK5 in the LumB, AC027307.2-OAZ1 in the Basal-like and AC022431.1-HCN2 in the Her2 subtypes. Finally, our results highlighted target genes of CNA-driven enhancers and enhancer-related lncRNA-mRNA pairs could act as prognostic markers and potential therapeutic targets in breast cancer subtypes. Frontiers Media S.A. 2022-10-11 /pmc/articles/PMC9592759/ /pubmed/36304471 http://dx.doi.org/10.3389/fimmu.2022.990143 Text en Copyright © 2022 Zhao, Zhang, Yin, Zhang, Wang, Liu, Xu, Liu, Bo, Lin, Feng, Lin, Fei, Ning and Wang 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 Immunology
Zhao, Hongying
Zhang, Siwen
Yin, Xiangzhe
Zhang, Caiyu
Wang, Lixia
Liu, Kailai
Xu, Haotian
Liu, Wangyang
Bo, Lin
Lin, Shihua
Feng, Ke
Lin, Lin
Fei, Meiting
Ning, Shangwei
Wang, Li
Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data
title Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data
title_full Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data
title_fullStr Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data
title_full_unstemmed Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data
title_short Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data
title_sort identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9592759/
https://www.ncbi.nlm.nih.gov/pubmed/36304471
http://dx.doi.org/10.3389/fimmu.2022.990143
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