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miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs

INTRODUCTION: Breast cancer is a genetically and phenotypically complex disease. To understand the role of miRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer cell lines to identify miRNAs associated with the m...

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Autores principales: Riaz, Muhammad, van Jaarsveld, Marijn TM, Hollestelle, Antoinette, Prager-van der Smissen, Wendy JC, Heine, Anouk AJ, Boersma, Antonius WM, Liu, Jingjing, Helmijr, Jean, Ozturk, Bahar, Smid, Marcel, Wiemer, Erik A, Foekens, John A, Martens, John WM
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3672661/
https://www.ncbi.nlm.nih.gov/pubmed/23601657
http://dx.doi.org/10.1186/bcr3415
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author Riaz, Muhammad
van Jaarsveld, Marijn TM
Hollestelle, Antoinette
Prager-van der Smissen, Wendy JC
Heine, Anouk AJ
Boersma, Antonius WM
Liu, Jingjing
Helmijr, Jean
Ozturk, Bahar
Smid, Marcel
Wiemer, Erik A
Foekens, John A
Martens, John WM
author_facet Riaz, Muhammad
van Jaarsveld, Marijn TM
Hollestelle, Antoinette
Prager-van der Smissen, Wendy JC
Heine, Anouk AJ
Boersma, Antonius WM
Liu, Jingjing
Helmijr, Jean
Ozturk, Bahar
Smid, Marcel
Wiemer, Erik A
Foekens, John A
Martens, John WM
author_sort Riaz, Muhammad
collection PubMed
description INTRODUCTION: Breast cancer is a genetically and phenotypically complex disease. To understand the role of miRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer cell lines to identify miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations. METHODS: Using a microarray carrying LNA™ modified oligonucleotide capture probes), expression levels of 725 human miRNAs were measured in 51 breast cancer cell lines. Differential miRNA expression was explored by unsupervised cluster analysis and was then associated with the molecular subtypes and genetic aberrations commonly present in breast cancer. RESULTS: Unsupervised cluster analysis using the most variably expressed miRNAs divided the 51 breast cancer cell lines into a major and a minor cluster predominantly mirroring the luminal and basal intrinsic subdivision of breast cancer cell lines. One hundred and thirteen miRNAs were differentially expressed between these two main clusters. Forty miRNAs were differentially expressed between basal-like and normal-like/claudin-low cell lines. Within the luminal-group, 39 miRNAs were associated with ERBB2 overexpression and 24 with E-cadherin gene mutations, which are frequent in this subtype of breast cancer cell lines. In contrast, 31 miRNAs were associated with E-cadherin promoter hypermethylation, which, contrary to E-cadherin mutation, is exclusively observed in breast cancer cell lines that are not of luminal origin. Thirty miRNAs were associated with p16(INK4 )status while only a few miRNAs were associated with BRCA1, PIK3CA/PTEN and TP53 mutation status. Twelve miRNAs were associated with DNA copy number variation of the respective locus. CONCLUSION: Luminal-basal and epithelial-mesenchymal associated miRNAs determine the subdivision of miRNA transcriptome of breast cancer cell lines. Specific sets of miRNAs were associated with ERBB2 overexpression, p16(INK4a )or E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of these genetic aberrations. Additionally, miRNAs, which are located in a genomic region showing recurrent genetic aberrations, may themselves play a driver role in breast carcinogenesis or contribute to a driver gene in their vicinity. In short, our study provides detailed molecular miRNA portraits of breast cancer cell lines, which can be exploited for functional studies of clinically important miRNAs.
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spelling pubmed-36726612013-06-06 miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs Riaz, Muhammad van Jaarsveld, Marijn TM Hollestelle, Antoinette Prager-van der Smissen, Wendy JC Heine, Anouk AJ Boersma, Antonius WM Liu, Jingjing Helmijr, Jean Ozturk, Bahar Smid, Marcel Wiemer, Erik A Foekens, John A Martens, John WM Breast Cancer Res Research Article INTRODUCTION: Breast cancer is a genetically and phenotypically complex disease. To understand the role of miRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer cell lines to identify miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations. METHODS: Using a microarray carrying LNA™ modified oligonucleotide capture probes), expression levels of 725 human miRNAs were measured in 51 breast cancer cell lines. Differential miRNA expression was explored by unsupervised cluster analysis and was then associated with the molecular subtypes and genetic aberrations commonly present in breast cancer. RESULTS: Unsupervised cluster analysis using the most variably expressed miRNAs divided the 51 breast cancer cell lines into a major and a minor cluster predominantly mirroring the luminal and basal intrinsic subdivision of breast cancer cell lines. One hundred and thirteen miRNAs were differentially expressed between these two main clusters. Forty miRNAs were differentially expressed between basal-like and normal-like/claudin-low cell lines. Within the luminal-group, 39 miRNAs were associated with ERBB2 overexpression and 24 with E-cadherin gene mutations, which are frequent in this subtype of breast cancer cell lines. In contrast, 31 miRNAs were associated with E-cadherin promoter hypermethylation, which, contrary to E-cadherin mutation, is exclusively observed in breast cancer cell lines that are not of luminal origin. Thirty miRNAs were associated with p16(INK4 )status while only a few miRNAs were associated with BRCA1, PIK3CA/PTEN and TP53 mutation status. Twelve miRNAs were associated with DNA copy number variation of the respective locus. CONCLUSION: Luminal-basal and epithelial-mesenchymal associated miRNAs determine the subdivision of miRNA transcriptome of breast cancer cell lines. Specific sets of miRNAs were associated with ERBB2 overexpression, p16(INK4a )or E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of these genetic aberrations. Additionally, miRNAs, which are located in a genomic region showing recurrent genetic aberrations, may themselves play a driver role in breast carcinogenesis or contribute to a driver gene in their vicinity. In short, our study provides detailed molecular miRNA portraits of breast cancer cell lines, which can be exploited for functional studies of clinically important miRNAs. BioMed Central 2013 2013-04-19 /pmc/articles/PMC3672661/ /pubmed/23601657 http://dx.doi.org/10.1186/bcr3415 Text en Copyright © 2013 Riaz et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Riaz, Muhammad
van Jaarsveld, Marijn TM
Hollestelle, Antoinette
Prager-van der Smissen, Wendy JC
Heine, Anouk AJ
Boersma, Antonius WM
Liu, Jingjing
Helmijr, Jean
Ozturk, Bahar
Smid, Marcel
Wiemer, Erik A
Foekens, John A
Martens, John WM
miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs
title miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs
title_full miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs
title_fullStr miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs
title_full_unstemmed miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs
title_short miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs
title_sort mirna expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific mirnas
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3672661/
https://www.ncbi.nlm.nih.gov/pubmed/23601657
http://dx.doi.org/10.1186/bcr3415
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