Unknown,Transcriptomics,Genomics,Proteomics

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Genome-Wide Methylation Analysis of Breast Cancer Cell Lines

ABSTRACT: To evaluate the methylation profiles of breast cell lines, we performed methylation profiling of 55 well-characterized breast cancer cell lines on the Illumina HumanMethylation27 (HM27) platform and made use of publicly available methylation profiles of primary breast tumors for comparison. The available annotation for each cell line includes estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status, as well as the tumor type, and the age of each patient. Additionally, recent publications have described genome-wide mRNA expression profiles for most of these lines, and samples were classified on the basis of the expression profile into Basal A (BaA), Basal B/Claudin Low (BaB/CLDNlow) and Luminal (Lu) subtypes. Finally, GI50 has been calculated for these cell lines for 77 approved therapeutic agents. We find that the DNA methylation profiles of breast cancer cell lines largely retain the features that characterize primary tumors, although there are crucial differences as well. We assayed DNA methylation in 55 breast cancer cell lines. DNA extracted from breast cell lines was bisulfite treated and hybridized to Illumina HM27 arrays.

ORGANISM(S): Homo sapiens

SUBMITTER: leslie cope

PROVIDER: E-GEOD-42944 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:To better understand the biology of hormone receptor-positive and negative breast cancer and to identify methylated gene markers of disease progression, we performed a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen and/or progesterone receptor-positive tumors displayed more hypermethylated loci than ER-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared to ER-positive tumors. An ER-classifier set of CpG loci was identified, which independently partitioned primary tumors into ER-subtypes. Forty (32 novel, 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors. Each of the 40 ER-subtype-specific loci was validated in silico using an independent, publicly available methylome dataset from The Cancer Genome Atlas (TCGA). In addition, we identified 100 methylated CpG loci that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes. This pilot study demonstrates the robustness of the breast cancer methylome and illustrates its potential to stratify and reveal biological differences between ER-subtypes of breast cancer. Further, it defines candidate ER-specific markers and identifies potential markers predictive of outcome within ER subgroups. Frozen breast cancer tissues that were excised from patients with Stage 1-3 disease prior to treatment (n=103) were retrieved from Surgical Pathology at Johns Hopkins Hospital (Baltimore, Maryland) and confirmed to contain > 50% epithelial cells. Normal breast organoids were prepared by enzymatic digestion of reduction mammoplasty specimens (n=15; median patient age = 52 years, range 47 to 71). Normal ducts from breast tissue > 2 cm away from the tumor (n=6) were isolated from cryosections using laser-capture micro-dissection (PALM MicroBeam, Carl Zeiss Microimaging, North America). To determine the differences in breast cancer biology/behavior between ER subtypes, we characterized methylation patterns at 8376 selected CpG loci according to ER status. These loci met two criteria: 1) showed the most variation across primary tumors (SD >0.100) and 2) had probe detection p-values <0.0001. To develop an epigenomic signature that predicts outcome in patients with breast cancer, we conducted differential methylation analysis on primary tumors from recurrent versus non-recurrent breast cancers. We used a subgroup of 82 well-annotated, invasive breast tumors derived from the discovery set of 103 tumors that included 44 ER-positive (7 recurrences) and 38 ER-negative (11 recurrences) breast cancers and independently queried the ER-positive and ER-negative tumor groups

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Genome-Wide Methylation Analysis of Breast Cancer Cell Lines

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