Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA362877 | ENA |
REPOSITORIES: ENA
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Project description: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.
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Project description:Breast cancer is a common disease with distinct tumor subtypes which can be phenotypically characterized by estrogen receptor, progesterone receptor and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression. Altered miRNA expression has been demonstrated in a variety of cancer states to date presenting the potential for exploitation as cancer specific biomarkers. Blood presents an attractive medium biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. Blood samples were prospectively collected from consenting patients with Luminal A breast cancer (n=10) and controls (n=10). RNA was extracted, reverse transcribed and subjected to microarray analysis (n=10 Luminal A; n=10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms.
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