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:scRNA-seq analysis of patient-derived luminal breast cancer xenografts
| PRJNA561776 | ENA
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 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:Many Luminal breast cancers are heterogeneous, containing substantial numbers of estrogen (ER-) and progesterone (PR-) receptor-negative cells among the ER+PR+ ones. Currently, the Basal-like ER-PR- Luminobasal subpopulation in Luminal disease is not targeted for treatment. To address the relationships between ER+PR+ and ER-PR- cells in Luminal cancers and tightly control their ratios, we have generated isogenic pure Luminal (pLUM) and pure Luminobasal (pLB) cells from the same parental Luminal human breast cancer cell line. We show that pLUM suppress proliferation of pLB cells in mixed-cell 3D colonies in vitro and in pLUM:pLB mixed-cell xenografts in mice. High-throughput screening of FDA-approved oncology drugs reveal pLB cells are sensitive to the EGFR inhibitors Gefitinib and Erlotinib. In mixed-cell 3D colonies and mixed-cell solid mouse tumors, combination therapy with the antiestrogen Fulvestrant and the EGFRi Gefitinib constitutes a robust treatment strategy. We propose that response to combination endocrine/EGFRi therapies in heterogeneous Luminal cancers will improve long-term survival in patients whose primary tumors have been preselected for the appropriate biomarkers.
2014-07-14 | GSE55350 | GEO
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