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

Riaz M, van Jaarsveld MT, Hollestelle A, Prager-van der Smissen WJ, Heine AA, Boersma AW, Liu J, Helmijr J, Ozturk B, Smid M, Wiemer EA, Foekens JA, Martens JW - Breast Cancer Res. (2013)

Bottom Line: Thirty miRNAs were associated with p16INK4 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.Specific sets of miRNAs were associated with ERBB2 overexpression, p16INK4a or E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of these genetic aberrations.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

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 p16INK4 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, p16INK4a 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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Molecular subtyping of 51 human breast cancer cell lines. Pearson correlation plot based on global mRNA expression of the top 10% variable genes. Breast cancer cell lines are depicted according to their overall similarity in gene expression. Yellow and blue, high and low overall similarity of samples in mRNA expression, respectively. Two main groups of 27 and 23 cell lines were apparent. Color codes for breast cancer subtypes based on intrinsic gene set: green, luminal-type cell lines; brown, luminal ERBB2-positive cell lines; black, normal-like/claudin-low cell lines; orange, basal-like cell lines; blue, estrogen receptor (ER)-negative/ERBB2-positive cell lines; pink, other subtype cell lines.
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Figure 1: Molecular subtyping of 51 human breast cancer cell lines. Pearson correlation plot based on global mRNA expression of the top 10% variable genes. Breast cancer cell lines are depicted according to their overall similarity in gene expression. Yellow and blue, high and low overall similarity of samples in mRNA expression, respectively. Two main groups of 27 and 23 cell lines were apparent. Color codes for breast cancer subtypes based on intrinsic gene set: green, luminal-type cell lines; brown, luminal ERBB2-positive cell lines; black, normal-like/claudin-low cell lines; orange, basal-like cell lines; blue, estrogen receptor (ER)-negative/ERBB2-positive cell lines; pink, other subtype cell lines.

Mentions: A Pearson correlation based on the top 10% of variably expressed genes classified the cell line cohort into two obvious groups (Figure 1). The first major group included 27 cell lines, of which 17 expressed ER protein. All cell lines in this group showed higher expression of luminal intrinsic genes as defined by Perou and colleagues [23]. We therefore defined this group of breast cancer cell lines as the luminal-group (Figure 1, left block). On the other hand, the second group included 23 breast cancer cell lines all of which were ER-negative and showed a predominant expression of basal intrinsic genes. We defined this group of breast cancer cell lines as "theER-negative/basal-group (Figure 1, right block). Moreover, according to classification using the intrinsic gene expressions [23], the luminal-group included nine ERBB2-overexpressing breast cancer cell lines, which did not cluster as a separate group. This result is in line with clustering of clinical specimens where the majority of luminal, ERBB2-positive tumors cluster with the luminal B tumors [27]. Within the ER-negative/basal-group, the basal-like and normal-like/claudin-low cell lines clustered distinctively into two subgroups (Figure 1). The DU4475 cell line could not be assigned to any subtype using the intrinsic gene set and was therefore designated as "the other" subtype.


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

Riaz M, van Jaarsveld MT, Hollestelle A, Prager-van der Smissen WJ, Heine AA, Boersma AW, Liu J, Helmijr J, Ozturk B, Smid M, Wiemer EA, Foekens JA, Martens JW - Breast Cancer Res. (2013)

Molecular subtyping of 51 human breast cancer cell lines. Pearson correlation plot based on global mRNA expression of the top 10% variable genes. Breast cancer cell lines are depicted according to their overall similarity in gene expression. Yellow and blue, high and low overall similarity of samples in mRNA expression, respectively. Two main groups of 27 and 23 cell lines were apparent. Color codes for breast cancer subtypes based on intrinsic gene set: green, luminal-type cell lines; brown, luminal ERBB2-positive cell lines; black, normal-like/claudin-low cell lines; orange, basal-like cell lines; blue, estrogen receptor (ER)-negative/ERBB2-positive cell lines; pink, other subtype cell lines.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3672661&req=5

Figure 1: Molecular subtyping of 51 human breast cancer cell lines. Pearson correlation plot based on global mRNA expression of the top 10% variable genes. Breast cancer cell lines are depicted according to their overall similarity in gene expression. Yellow and blue, high and low overall similarity of samples in mRNA expression, respectively. Two main groups of 27 and 23 cell lines were apparent. Color codes for breast cancer subtypes based on intrinsic gene set: green, luminal-type cell lines; brown, luminal ERBB2-positive cell lines; black, normal-like/claudin-low cell lines; orange, basal-like cell lines; blue, estrogen receptor (ER)-negative/ERBB2-positive cell lines; pink, other subtype cell lines.
Mentions: A Pearson correlation based on the top 10% of variably expressed genes classified the cell line cohort into two obvious groups (Figure 1). The first major group included 27 cell lines, of which 17 expressed ER protein. All cell lines in this group showed higher expression of luminal intrinsic genes as defined by Perou and colleagues [23]. We therefore defined this group of breast cancer cell lines as the luminal-group (Figure 1, left block). On the other hand, the second group included 23 breast cancer cell lines all of which were ER-negative and showed a predominant expression of basal intrinsic genes. We defined this group of breast cancer cell lines as "theER-negative/basal-group (Figure 1, right block). Moreover, according to classification using the intrinsic gene expressions [23], the luminal-group included nine ERBB2-overexpressing breast cancer cell lines, which did not cluster as a separate group. This result is in line with clustering of clinical specimens where the majority of luminal, ERBB2-positive tumors cluster with the luminal B tumors [27]. Within the ER-negative/basal-group, the basal-like and normal-like/claudin-low cell lines clustered distinctively into two subgroups (Figure 1). The DU4475 cell line could not be assigned to any subtype using the intrinsic gene set and was therefore designated as "the other" subtype.

Bottom Line: Thirty miRNAs were associated with p16INK4 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.Specific sets of miRNAs were associated with ERBB2 overexpression, p16INK4a or E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of these genetic aberrations.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

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 p16INK4 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, p16INK4a 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.

Show MeSH
Related in: MedlinePlus