Genome-wide DNA methylation analysis of breast cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE75067 | GEO | 2016/02/29
SECONDARY ACCESSION(S): PRJNA302431
REPOSITORIES: GEO
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Project description:Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized. Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The Cancer Genome Atlas data, incluing methylation profiles of 669 human breast tumors, was utilized for validation. The identified epitypes were characterized by integration with publicly available genome-wide data, including gene expression levels, DNA copy numbers, whole-exome sequencing data, and chromatin states. We identified seven breast cancer epitypes. One epitype was distinctly associated with basal-like tumors and with BRCA1 mutations, one epitype contained a subset of ERBB2-amplified tumors characterized by multiple additional amplifications and the most complex genomes, and one epitype displayed a methylation profile similar to normal epithelial cells. Luminal tumors were stratified into the remaining four epitypes, with differences in promoter hypermethylation, global hypomethylation, proliferative rates and genomic instability. We observed two dominant patterns of aberrant methylation in breast cancer. One pattern, constitutively methylated in both basal-like and luminal breast cancer, was linked to genes with promoters in a Polycomb-repressed state in normal epithelial cells and displayed no correlation to gene expression levels. The second pattern correlated with gene expression levels and was associated with methylation in luminal tumors and genes with active promoters in normal epithelial cells. Our results suggest that hypermethylation patterns in basal-like breast cancer may have limited influence on tumor progression and instead reflects the repressed chromatin state of the tissue of origin. On the contrary, hypermethylation patterns specific to luminal breast cancer influence gene expression, may contribute to tumor progression, and may present an actionable epigenetic alteration in some luminal breast cancers. Genome-wide DNA methylation analysis of 188 breast cancers using Illumina Human Methylation 450K Beadchips.
2016-02-29 | E-GEOD-75067 | biostudies-arrayexpress
Project description:Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer is not well studied. We performed whole-genome methylation analysis using 450K Illumina BeadArrays on 124 tumors including 83 adenocarcinomas, 23 squamous cell carcinomas, one adenosquamous cancer, five large cell carcinomas, nine large cell neuroendocrine carcinomas (LCNEC), three small cell carcinomas (SCLC) and 12 normal lung tissues. Unsupervised class discovery was performed to identify DNA methylation subgroups with clinicopathological and molecular features. Subgroups were validated in two independent NSCLC cohorts. Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, in both discovery and validation cohorts, remaining four epitypes were associated with differences in clinicopathological and molecular features, including global hypomethylation, promoter hypermethylation, copy number alterations, expression of proliferation-associated genes, association with unsupervised and supervised gene expression phenotypes, KRAS, TP53, KEAP1, SMARCA4, and STK11 mutations, smoking history, and patient outcome. Based on a multicohort approach we conducted a comprehensive survey of genome-wide DNA methylation in lung cancer, identifying a distinct neuroendocrine epitype and four adenocarcinoma epitypes associated with molecular and clinicopathological characteristics, and patient outcome. Our results bring further understanding of the epigenetic characteristics and molecular diversity in lung cancer generally and in adenocarcinoma specifically. Genome-wide DNA methylation analysis of 124 lung carcinomas and 12 normal lung tissues using Illumina Human Methylation 450K v1.0 Beadchips.
2014-10-05 | E-GEOD-56044 | biostudies-arrayexpress
Project description:Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer is not well studied. We performed whole-genome methylation analysis using 450K Illumina BeadArrays on 124 tumors including 83 adenocarcinomas, 23 squamous cell carcinomas, one adenosquamous cancer, five large cell carcinomas, nine large cell neuroendocrine carcinomas (LCNEC), three small cell carcinomas (SCLC) and 12 normal lung tissues. Unsupervised class discovery was performed to identify DNA methylation subgroups with clinicopathological and molecular features. Subgroups were validated in two independent NSCLC cohorts. Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, in both discovery and validation cohorts, remaining four epitypes were associated with differences in clinicopathological and molecular features, including global hypomethylation, promoter hypermethylation, copy number alterations, expression of proliferation-associated genes, association with unsupervised and supervised gene expression phenotypes, KRAS, TP53, KEAP1, SMARCA4, and STK11 mutations, smoking history, and patient outcome. Based on a multicohort approach we conducted a comprehensive survey of genome-wide DNA methylation in lung cancer, identifying a distinct neuroendocrine epitype and four adenocarcinoma epitypes associated with molecular and clinicopathological characteristics, and patient outcome. Our results bring further understanding of the epigenetic characteristics and molecular diversity in lung cancer generally and in adenocarcinoma specifically.
2014-10-05 | GSE56044 | GEO
Project description:Acute myeloid leukemia (AML) is a molecularly complex disease characterized by heterogeneous tumor genetic profiles and involving numerous pathogenic mechanisms and pathways. Integration of molecular data types across multiple patient cohorts may advance current genetic approaches for improved sub-classification and understanding of the biology of the disease. Here we analyzed genome-wide DNA methylation in 649 AML patients using Illumina arrays and identified a configuration of 13 subtypes (termed ‘epitypes’) using unbiased clustering. Integration of genetic data revealed that most epitypes were associated with a certain recurrent mutation (or combination) in a majority of patients, yet other epitypes were largely independent. Epitypes demonstrated developmental blockage at discrete stages of myeloid differentiation, revealing epitypes that retain arrested hematopoietic stem cell-like phenotypes. Detailed analyses of DNA methylation patterns identified unique patterns of aberrant hyper- and hypomethylation among epitypes, with variable involvement of transcription factors influencing promoter, enhancer and repressed regions. Patients in epitypes with stem cell-like methylation features showed inferior overall survival along with upregulated stem cell gene expression signatures. We further identified a DNA methylation signature involving STAT motifs associated with FLT3-ITD mutations. Finally, DNA methylation signatures were remarkably stable at relapse for the large majority of patients, and rare epitype switching accompanied loss of the dominant epitype mutations and reversion to stem cell-like methylation patterns. These results demonstrate that DNA methylation-based classification integrates important molecular features of AML to reveal the diverse pathogenic and biological aspects of the disease.
2021-03-09 | GSE159907 | 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. 517 breast tumors, 9 normal breast tissues
2015-04-07 | E-GEOD-51557 | biostudies-arrayexpress
Project description:The purpose of the present study was to investigate the association of glutathione S-transferase P1 (GSTP1) expression with resistance to neoadjuvant paclitaxel followed by 5-fluorouracil/epirubicin/cyclophosphamide (P-FEC) in human breast cancers. The relationship of GSTP1 expression and GSTP1 promoter hypermethylation with intrinsic subtypes was also investigated. In this study, primary breast cancer patients (n = 123, stage II-III) treated with neoadjuvant P-FEC were analyzed. Tumor samples were obtained by vacuum-assisted core biopsy before P-FEC. GSTP1 expression was determined using immunohistochemistry, GSTP1 promoter methylation index (MI) using bisulfite methylation assay and intrinsic subtypes using DNA microarray. The pathological complete response (pCR) rate was significantly higher in GSTP1-negative tumors (80.0%) than GSTP1-positive tumors (30.6%) (P = 0.009) among estrogen receptor (ER)-negative tumors but not among ER-positive tumors (P = 0.267). Multivariate analysis showed that GSTP1 was the only predictive factor for pCR (P = 0.013) among ER-negative tumors. Luminal A, luminal B and HER2-enriched tumors showed a significantly lower GSTP1 positivity than basal-like tumors (P = 0.002, P < 0.001 and P = 0.009, respectively), while luminal A, luminal B and HER2-enriched tumors showed a higher GSTP1 MI than basal-like tumors (P = 0.076, P < 0.001 and P < 0.001, respectively). In conclusion, these results suggest the possibility that GSTP1 expression can predict pathological response to P-FEC in ER-negative tumors but not in ER-positive tumors. Additionally, GSTP1 promoter hypermethylation might be implicated more importantly in the pathogenesis of luminal A, luminal B and HER2-enriched tumors than basal-like tumors. Fresh frozen tumor samples obtained by vacuum-assisted core biopsy from one hundred and fifteen patients were subjected to RNA extraction and hybridization on Affymetrix microarrays.
2012-03-20 | E-GEOD-32646 | biostudies-arrayexpress
Project description:Introduction: Five different molecular subtypes of breast cancer have been identified through gene expression profiling. Each subtype has a characteristic expression pattern suggested to partly depend on cellular origin. We aimed to investigate whether the molecular subtypes also display distinct methylation profiles. Methods: We analysed methylation status of 807 cancer-related genes in 189 fresh frozen primary breast tumours and four normal breast tissue samples using an array-based methylation assay. Results: Unsupervised analysis revealed three groups of breast cancer with characteristic methylation patterns. The three groups were associated with the luminal A, luminal B and basal-like molecular subtypes of breast cancer, respectively, whereas cancers of the HER2-enriched and normal-like subtypes were distributed among the three groups. The methylation frequencies were significantly different between subtypes, with luminal B and basal-like tumours being most and least frequently methylated, respectively. Moreover, targets of the polycomb repressor complex in breast cancer and embryonic stem cells were more methylated in luminal B tumours than in other tumours. BRCA2-mutated tumours had a particularly high degree of methylation. Finally, by utilizing gene expression data, we observed that a large fraction of genes reported as having subtype-specific expression patterns might be regulated through methylation. Conclusions: We have found that breast cancers of the basal-like, luminal A and luminal B molecular subtypes harbour specific methylation profiles. Our results suggest that methylation may play an important role in the development of breast cancers. DNA methylation profiling of breast cancer samples and normal breast tissue samples. The Illumina GoldenGate Methylation Cancer Panel I was used to obtain DNA methylation profiles across approximately 1500 CpGs. Samples included 189 breast cancer samples and 4 normal breast tissue samples. Bisulphite converted DNA from the samples were hybridised to the Illumina GoldenGate Methylation Cancer Panel I
2010-06-09 | E-GEOD-22210 | biostudies-arrayexpress
Project description:The purpose of the present study was to investigate the association of glutathione S-transferase P1 (GSTP1) expression with resistance to neoadjuvant paclitaxel followed by 5-fluorouracil/epirubicin/cyclophosphamide (P-FEC) in human breast cancers. The relationship of GSTP1 expression and GSTP1 promoter hypermethylation with intrinsic subtypes was also investigated. In this study, primary breast cancer patients (n = 123, stage II-III) treated with neoadjuvant P-FEC were analyzed. Tumor samples were obtained by vacuum-assisted core biopsy before P-FEC. GSTP1 expression was determined using immunohistochemistry, GSTP1 promoter methylation index (MI) using bisulfite methylation assay and intrinsic subtypes using DNA microarray. The pathological complete response (pCR) rate was significantly higher in GSTP1-negative tumors (80.0%) than GSTP1-positive tumors (30.6%) (P = 0.009) among estrogen receptor (ER)-negative tumors but not among ER-positive tumors (P = 0.267). Multivariate analysis showed that GSTP1 was the only predictive factor for pCR (P = 0.013) among ER-negative tumors. Luminal A, luminal B and HER2-enriched tumors showed a significantly lower GSTP1 positivity than basal-like tumors (P = 0.002, P < 0.001 and P = 0.009, respectively), while luminal A, luminal B and HER2-enriched tumors showed a higher GSTP1 MI than basal-like tumors (P = 0.076, P < 0.001 and P < 0.001, respectively). In conclusion, these results suggest the possibility that GSTP1 expression can predict pathological response to P-FEC in ER-negative tumors but not in ER-positive tumors. Additionally, GSTP1 promoter hypermethylation might be implicated more importantly in the pathogenesis of luminal A, luminal B and HER2-enriched tumors than basal-like tumors.
2012-03-20 | GSE32646 | 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. 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:Recurrent mutations in histone modifying enzymes in multiple cancer types imply key roles in tumorigenesis. However, the functional relevance of these mutations remains unknown. Here we show that the JARID1B histone H3 lysine 4 demethylase is frequently amplified and overexpressed in luminal breast tumors and a somatic point mutation of JARID1B leads to the gain of luminal-specific gene expression programs. Downregulation of JARID1B in luminal breast cancer cells induces the expression of basal cell-specific genes and growth arrest, which is partially rescued by the inhibition of TGFBR thereby indicating a key role for TGFb signaling. Integrated genome-wide analysis of JARID1B chromatin binding, histone H3 lysine trimethyl (H3K4me3) and dimethyl (H3K4me2) patterns, and gene expression profiles in luminal and basal-like breast cancer cells suggest a key role for JARID1B in luminal cell-specific gene expression programs. A significant fraction of JARID1B binding-sites overlaps with CTCF in both luminal and basal-like breast cancer cells. CTCF also co-immunoprecipitates with JARID1B and it may influence its histone demethylase (HDM) activity as the H3K4me3/me2 ratio is lower at the CTCF-overlapping compared to JARID1B-unique sites. Additionally, a heterozygous JARID1B missense mutation (K1435R) in the HCC2157 basal-like breast cancer cell line is associated with unique JARID1B chromatin-binding and gene expression patterns implying gain of luminal features. In line with this, exogenous expression of this mutant in basal-like breast cancer cells leads to a gain of JARID1B binding at many luminal-specific genes. A PARADIGM score reflecting JARID1B activity in luminal breast cancer cells is associated with poor clinical outcome in patients with luminal breast tumors. Together, our data imply that JARID1B is a luminal lineage-driving oncogene and that its therapeutic targeting may represent a novel therapeutic strategy in treatment-resistant luminal breast tumors. RNA-Seq in breast cancer cell-lines transfected with JARID1B/CTCF/control siRNA. 50 cycles of sequencing on Illumina platform.
2014-06-17 | E-GEOD-45732 | biostudies-arrayexpress