Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA362877 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Estrogen receptor dynamics in diverse patient-derived luminal breast cancer xenografts
| PRJNA151839 | ENA
Project description:Patient-derived luminal breast cancer xenografts with progestins
| PRJNA360064 | ENA
Project description:Most breast cancers are luminal, depending on estrogens for growth. The remainder lack estrogen receptors, are hormone-resistant and basal-like. It is thought that breast cancers arise from self-renewing normal stem cells that have undergone malignant transformation. However currently reported cancer stem cells are hormone insensitive and generate basal, rather than luminal tumors. We now describe true luminal hormone-responsive breast cancer stem cells that express estrogen and progesterone receptors. Their self-renewal capacity is protected by progesterone. Stem cell levels are depleted by estrogens as tumors transition into differentiated and homogeneous luminal states. But, if added to estrogens, progesterone promotes heterogeneity and “rescues” the stem cells. By keeping luminal cancer stem cells “safe”, progesterone, widely used for contraception and hormone replacement, could be harmful to breast cancer survivors or women with occult disease.
2016-01-31 | GSE65407 | GEO
Project description:ChIPseq analysis of patient-derived luminal breast cancer xenografts with progestins
| PRJNA360065 | ENA
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.
2013-03-01 | E-GEOD-42944 | biostudies-arrayexpress
Project description:Breast cancer is a heterogeneous disease encompassing a number of phenotypically diverse tumours. Expression levels of the estrogen, progesterone and HER2/neu receptors which characterise clinically distinct breast tumors have been shown to change during disease progression and in response to systemic therapies. Mi(cro)RNAs play critical roles in diverse biological processes and are aberrantly expressed in several human neoplasms including breast cancer, where they function as regulators of tumour behaviour and progression. The aims of this study were to identify miRNA signatures that accurately predict the oestrogen receptor (ER), progesterone receptor (PR) and HER2/neu receptor status of breast cancer patients to provide insight into the regulation of breast cancer phenotypes and progression. Expression profiling of 353 microRNAs was performed in 29 early stage breast cancer specimens. MiRNA signatures associated with ER, PR and HER2/neu status were generated using artificial neural networks (ANN) and expression of specific microRNAs was validated using RQ-PCR. Results: Stepwise artificial neural network (ANN) analysis identified predictive miRNA signatures corresponding with estrogen (miR-342, miR-299, miR-217, miR -190, miR-135b, miR-218), progesterone (miR-520g, miR-377, miR-527-518a, miR-520f-520c) and HER2/neu (miR-520d, miR-181c, miR-302c, miR-376b, miR-30e) receptor status. MiR-342 and miR-520g expression was further analysed in 95 breast tumours. MiR-342 expression was highest in ER and HER2/neu positive luminal B tumours and lowest in triple-negative tumours. MiR-520g expression was elevated in ER and PR negative tumours.
2010-05-18 | E-GEOD-15885 | biostudies-arrayexpress
Project description:RNAseq analysis of patient-derived luminal breast cancer xenografts treated with progestins
| PRJNA359750 | ENA
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.
2013-04-24 | GSE46355 | GEO
Project description:The prognosis of a patient with Estrogen Receptor (ER) and/or Progesterone Receptor (PR)-positive breast cancer is highly variable. Therefore, we developed a gene-expression based outcome predictor for ER+ and/or PR+ (i.e. Luminal) breast cancer patients using biological properties of the tumors. First, we identified estrogen-regulated genes using the ER+ MCF-7 breast cancer cell line treated with estrogen. The estrogen-induced gene set was then used to hierarchically cluster a training set of 65 ER+ and/or PR+ tumors into 2 group, which showed survival differences (p=0.0004). Next, supervised analyses based upon these two groups was performed and identified 822 genes that optimally defined these two groups, with the poor prognosis Group IIE tumors showing a proliferation signature and high expression of anti-apoptosis genes and the good outcome Group IE showing the high expression of estrogen and GATA3-induced genes. Centroids were created for each group and applied to ER+ and/or PR+ tumors from three published datasets. For all datasets, Kaplan-Meier survival analyses showed a statistically significant difference in Relapse-Free Survival (and Overall) between Group IE and IIE tumors. Multivariate Cox analysis of the largest test dataset also showed that this predictor was adding independent information. This study provides new biological information concerning differences within Luminal/ER+ breast cancers and a means of predicting long term outcomes in ER+ and/or PR+ breast cancer patients. Keywords: other
2005-12-01 | GSE2740 | GEO