Vimentin DNA Methylation Predicts Survival in Breast Cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE35629 | GEO | 2013/02/19
SECONDARY ACCESSION(S): PRJNA152475
REPOSITORIES: GEO
Similar Datasets
Project description:Purpose:The Vimentin gene plays a pivotal role in epithelial-to-mesenchymal transition (EMT) and is known to be over-expressed in the prognostically poor basal-like breast cancer subtype. Recent studies have reported Vimentin DNA methylation in association with poor clinical outcomes in other solid tumors, but not in breast cancer. We therefore quantified Vimentin DNA methylation in breast tumors and matched normal pairs in association with gene expression and survival in a cohort of 83 breast cancer patients. Materials and Methods:Vimentin methylation was quantified in 14 breast cell lines, 83 breast tumors, and 57 matched normal pairs using MALDI-TOF mass spectrometry. Gene expression data via qRT-PCR in cell lines, and oligo microarray data from breast tissues was correlated with percent methylation in the Vimentin promoter. A threshold of 20 percent average methylation was set for bivariate and multivariate tests of association between methylation and tumor subtype, tumor histopathology, and survival. Results:Vimentin was differentially methylated in luminal breast cancer cell lines, and in luminal A, luminal B and HER2+ breast tumor subtypes, but was rare in basal-like cell lines and tumors. Increased methylation was strongly correlated with decreased mRNA expression in cell lines, and had a moderate inverse correlation in breast tumors. Importantly, Vimentin methylation predicted poor overall survival independent of race, subtype, stage, nodal status or estrogen receptor positivity. Conclusion:Vimentin methylation predicts overall survival in breast cancer patients and holds promise as a prognostic biomarker for guiding treatment and prophylaxis. reference x sample
2013-02-19 | E-GEOD-35629 | biostudies-arrayexpress
Project description:A microarray targeting promoters of cancer-related genes was used to evaluate DNA methylation at 935 CpG sites in 517 invasive breast tumors from the Carolina Breast Cancer Study (CBCS), a population-based study of invasive breast cancer. Concensus clustering using methylation (β) values for the 167 most variant CpG loci defined 4 clusters differing most distinctly in hormone receptor (HR) status, intrinsic subtype (luminal versus basal-like) and p53 mutation status. Supervised analyses for HR status, subtype, and p53 status identified differentially methylated CpG loci with considerable overlap (n=266). Concensus clustering also defined a hypermethylated luminal-enriched tumor cluster 3; gene ontology analysis of cluster 3 hypermethylated loci revealed enrichment for developmental genes, including homeobox domain genes (HOXB13, PAX6, IPF1, EYA4, DLK1, IHH, ISL1, TBX1, SOX1, SOX17). The hypermethylated luminal-enriched cluster 3 independently predicted poorer survival in multivariate Cox proportional hazard analysis, and this finding was confirmed in analysis of luminal A tumors. This study demonstrates epigenetic heterogeneity among breast tumors of a single intrinsic subtype, and shows that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status. Among HR+ tumors, a gene signature characterized by hypermethylation of developmental genes may have prognostic value. Genes differentially methylated between clinically-important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to inducing and maintaining tumor phenotypes and clinical outcomes. 517 breast tumors, 9 normal breast tissues
2015-04-07 | E-GEOD-51557 | biostudies-arrayexpress
Project description:Breast cancer is a heterogeneous disease comprised of at least five major subtypes. Luminal subtype tumors confer a more favourable patient prognosis, which is in part, attributed to the Estrogen Receptor-alpha (ER) positivity and anti-hormone responsiveness of these tumors. Expression of the forkhead box transcription factor, FOXA1, also correlates with the luminal subtype and patient survival, but is present in a subset of ER-negative tumors. Similarly, FOXA1 is consistently expressed in luminal breast cancer cell lines even in the absence of ER. In contrast, basal breast cancer cell lines do not express FOXA1, and loss of FOXA1 in luminal cells increases migration and invasion, characteristics of the basal subtype. To delineate an ER-independent role for FOXA1 in maintaining the luminal phenotype, and hence a more favourable prognosis, we performed cDNA microarray analyses on luminal FOXA1-positive, ER-positive (MCF7, T47D) and FOXA1-positive, ER-negative (MDA-MB-453, SKBR3) cell lines in the presence or absence of transient FOXA1 silencing. This resulted in three FOXA1 transcriptomes: (1) a luminal-signature (consistent across cell lines), (2) an ER-positive signature (restricted to MCF7 and T47D) and (3) an ER-negative signature (restricted to MDA-MB-453 and SKBR3). Use of Gene Set Enrichment Analyses (GSEA) as a phenotyping tool revealed that FOXA1 silencing resulted in a transcriptome shift from luminal to basal gene expression signatures. FOXA1 binds to both luminal and basal genes within luminal breast cancer cells, suggesting that it not only transactivates luminal genes, but also represses basal-associated genes. From these results we conclude that FOXA1 controls plasticity between basal and luminal cells, playing a dominant role in repressing the basal phenotype, and thus tumor aggressiveness, in luminal breast cancer cells. Although it has been proposed that FOXA1-targeting agents may be useful for treating luminal tumors, these data suggest that this approach may promote transitions toward a more aggressive cancer. FOXA1 siRNA treated breast cell lines compared directly to nonspecific siRNA treated cell lines using Agilent 4X44 microarrays.
2012-03-09 | E-GEOD-31003 | biostudies-arrayexpress
Project description:Summary: Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes (luminal A, luminal B, ERBB2-associated, basal-like and normal-like) with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. HEEBO oligonucleotide microarrays from the Stanford Functional Genomics Facility were used to perform gene expression profiling of 50 human breast epithelial cell lines, in comparison to a universal RNA reference. Expression data were analyzed by hierarchical clustering to identify subgroups, and gene set enrichment analysis to identify subgroup-specific gene pathways.
2010-06-24 | E-GEOD-15361 | biostudies-arrayexpress
Project description:Vimentin DNA Methylation Predicts Survival in Breast Cancer
| PRJNA152475 | ENA
Project description:Breast cancer is a heterogeneous disease comprised of at least five major subtypes. Luminal subtype tumors confer a more favorable patient prognosis, which is in part, attributed to the Estrogen Receptor-α (ER) positivity and anti-hormone responsiveness of these tumors. Expression of the forkhead box transcription factor, FOXA1, also correlates with the luminal subtype and patient survival, but is present in a subset of ER-negative tumors. Similarly, FOXA1 is consistently expressed in luminal breast cancer cell lines even in the absence of ER. In contrast, basal breast cancer cell lines do not express FOXA1, and loss of FOXA1 in luminal cells increases migration and invasion, characteristics of the basal subtype. To delineate an ER-independent role for FOXA1 in maintaining the luminal phenotype, and hence a more favorable prognosis, we performed cDNA microarray analyses on luminal FOXA1-positive, ER-positive (MCF7, T47D) and FOXA1-positive, ER-negative (MDA-MB-453, SKBR3) cell lines in the presence or absence of transient FOXA1 silencing. This resulted in three FOXA1 transcriptomes: (1) a luminal-signature (consistent across cell lines), (2) an ER-positive signature (restricted to MCF7 and T47D) and (3) an ER-negative signature (restricted to MDA-MB-453 and SKBR3). Use of Gene Set Enrichment Analyses (GSEA) as a phenotyping tool revealed that FOXA1 silencing resulted in a transcriptome shift from luminal to basal gene expression signatures. FOXA1 binds to both luminal and basal genes within luminal breast cancer cells, suggesting that it not only transactivates luminal genes, but also represses basal-associated genes. From these results we conclude that FOXA1 controls plasticity between basal and luminal cells, playing a dominant role in repressing the basal phenotype, and thus tumor aggressiveness, in luminal breast cancer cells. Although it has been proposed that FOXA1-targeting agents may be useful for treating luminal tumors, these data suggest that this approach may promote transitions toward a more aggressive cancer.
2012-03-09 | GSE31003 | GEO
Project description:A microarray targeting promoters of cancer-related genes was used to evaluate DNA methylation at 935 CpG sites in 517 invasive breast tumors from the Carolina Breast Cancer Study (CBCS), a population-based study of invasive breast cancer. Concensus clustering using methylation (β) values for the 167 most variant CpG loci defined 4 clusters differing most distinctly in hormone receptor (HR) status, intrinsic subtype (luminal versus basal-like) and p53 mutation status. Supervised analyses for HR status, subtype, and p53 status identified differentially methylated CpG loci with considerable overlap (n=266). Concensus clustering also defined a hypermethylated luminal-enriched tumor cluster 3; gene ontology analysis of cluster 3 hypermethylated loci revealed enrichment for developmental genes, including homeobox domain genes (HOXB13, PAX6, IPF1, EYA4, DLK1, IHH, ISL1, TBX1, SOX1, SOX17). The hypermethylated luminal-enriched cluster 3 independently predicted poorer survival in multivariate Cox proportional hazard analysis, and this finding was confirmed in analysis of luminal A tumors. This study demonstrates epigenetic heterogeneity among breast tumors of a single intrinsic subtype, and shows that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status. Among HR+ tumors, a gene signature characterized by hypermethylation of developmental genes may have prognostic value. Genes differentially methylated between clinically-important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to inducing and maintaining tumor phenotypes and clinical outcomes.
2015-04-07 | GSE51557 | GEO
Project description:Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes - luminal A, luminal B, ERBB2-associated, basal-like and normal-like - with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. cDNA microarrays from the Stanford Functional Genomics Facility were used to carry out array-based Comparative Genomic Hybridization (array CGH) analysis of 52 human breast epithelial cell lines, in comparison to normal female DNA. Three reference arrays of normal male vs. normal female DNA were also done. Map positions for arrayed cDNA clones were assigned using the NCBI genome assembly, accessed through the UCSC genome browser database (NCBI Build 36). The cghFLasso method was used to call DNA gains and losses.
2010-06-24 | E-GEOD-13914 | biostudies-arrayexpress
Project description:Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes - luminal A, luminal B, ERBB2-associated, basal-like and normal-like - with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.
2009-07-10 | GSE13914 | GEO
Project description:Summary: Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes (luminal A, luminal B, ERBB2-associated, basal-like and normal-like) with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.
2009-07-10 | GSE15361 | GEO