Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Genome-wide DNA methylation analysis of different cell types

ABSTRACT: We performed whole-genome methylation analysis using 450K Illumina BeadArrays on different human cell types. In total 24 experiments were performed. Dermal fibroblasts, three different epidermal melanocytes (dark, medium and light pigmentation), epidermal keratinocytes, mammary fibroblasts, mammary epithelial cells, mammary endothelial cells and mesenchymal stem cells were analyzed in technical duplicates. Unmethylated DNA were analyzed in technical duplicates. Two different normal breast tissue samples were analyzed. Finally peripheral blood leukocytes and an enzymatically methylated sample were analyzed. Genome-wide DNA methylation analysis of different cell types using Illumina Human Methylation 450K Beadchips.

ORGANISM(S): Homo sapiens

SUBMITTER: Markus Ringner

PROVIDER: E-GEOD-74877 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells.

Holm Karolina K Staaf Johan J Lauss Martin M Aine Mattias M Lindgren David D Bendahl Pär-Ola PO Vallon-Christersson Johan J Barkardottir Rosa Bjork RB Höglund Mattias M Borg Åke Å Jönsson Göran G Ringnér Markus M

Breast cancer research : BCR 20160229 1

<h4>Background</h4>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.<h4>Methods</h4>Whole-genome DNA methylation analysis using Illumina Infinium HumanMethylation450 BeadChip arrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The ...[more]

PMID: 26923702

Similar Datasets

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.

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.

Project description:Germ cell tumors (GCT) originate from germ cells at different developmental stages (GCT type I – V) They are thought to inherit their methylation profile from (early embryonic) germ cells which undergo a characteristic epigenetic “reset” during maturation. This study aims to provide insight into the developmental timing and underlying biology of the various subtypes of GCTs and their (embryonic) cells of origin by identifying specific and global methylation differences between GCT subtypes. In total, 91 type I-IV GCTs and four cell lines were profiled using the Illumina HumanMethylation450 BeadChip (450K) platform. The data were pre-processed using a validated pipeline and analyzed using an in-house generated extension of the annotation manifest. Marked methylation differences were identified between GCT subtypes both on the global and local level (i.e. differentially methylated regions, imprinting control regions, promoters, etc). GCT subtypes indeed show major similarities to specific stages of (early) developing embryonic germ cells with regard to their methylation profile. The extended annotation manifest for the Illumina 450K platform and methylation datasets are readily available on GEO (GEO accession: GSE58538, GPL18809), providing an integrated hypothesis generating data source for future research. 91 germ cell tumors of various histologies were investigated for their methylation profile. Methylation detection was performed using Illumina’s HumanMethylation450 BeadChip. 14 type I teratomas (TE) were included of which 6 were located sacral (3 male: I.TE.s.m; 3 female: I.TE.s.f), 4 were located in the testis (I.TE.t) and 3 were located in the ovary (I.TE.o). 30 pure embryonal carcinomas (EC) were included as well as 21 mixed non seminomas (mNS). 12 seminomas of the testis (SE) were included as well as 4 dysgerminomas (their couterpart in the ovary). Finally, 4 spermatocytic seminomas (SS) and three dermoid cysts were analyzed. For a detailed overview the histological classification of germ cell tumors please see the publication linked to this data or associated literature [1-3]. Four cell lines were included, al modelling type II GCTs. Cell lines derived from EC include NT2[4-8], NCCIT [5, 9] and 2102EP[4-8]. TCam-2 closely resembles SE [10-12]. 1. Oosterhuis, J.W. and L.H. Looijenga, Testicular germ-cell tumours in a broader perspective. Nat Rev Cancer, 2005. 5(3): p. 210-22. 2. Looijenga, L.H., Human testicular (non)seminomatous germ cell tumours: the clinical implications of recent pathobiological insights. J Pathol, 2009. 218(2): p. 146-62. 3. Woodward, P.J., et al., Testicular germ cell tumors, in World Health Organization Classification of Tumours Pathology and Genetics of the Urinary System and Male Genital Organs., J.N. Eble, et al., Editors. 2004, IARC Press: Lyon. p. 17-278. 4. Andrews, P.W., et al., A comparative study of eight cell lines derived from human testicular teratocarcinoma. Int J Cancer, 1980. 26(3): p. 269-80. 5. Andrews, P.W., et al., Comparative analysis of cell surface antigens expressed by cell lines derived from human germ cell tumours. Int J Cancer, 1996. 66(6): p. 806-16. 6. Wang, N., et al., Nonrandom abnormalities in chromosome 1 in human testicular cancers. Cancer Res, 1980. 40(3): p. 796-802. 7. Fogh, J. and G. Trempe, New Human Tumor Cell Lines, in Human Tumor Cells in Vitro, J. Fogh, Editor. 1975, Springer US. p. 115-159. 8. Fogh, J., Cultivation, characterization, and identification of human tumor cells with emphasis on kidney, testis, and bladder tumors. Natl Cancer Inst Monogr, 1978(49): p. 5-9. 9. Teshima, S., et al., Four new human germ cell tumor cell lines. Lab Invest, 1988. 59(3): p. 328-36. 10. Eckert, D., et al., TCam-2 but not JKT-1 cells resemble seminoma in cell culture. Cell Tissue Res, 2008. 331(2): p. 529-38. 11. de Jong, J., et al., Further characterization of the first seminoma cell line TCam-2. Genes Chromosomes Cancer, 2008. 47(3): p. 185-96. 12. Mizuno, Y., et al., [Establishment and characterization of a new human testicular germ cell tumor cell line (TCam-2)]. Nihon Hinyokika Gakkai Zasshi, 1993. 84(7): p. 1211-8.

Dataset Information

Genome-wide DNA methylation analysis of different cell types

Publications

An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure