MicroRNA profiling of ovarian cancer compared to normal ovary
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PROVIDER: PRJNA487948 | ENA |
REPOSITORIES: ENA
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Project description:To determine microRNA expression in chemoresistant ovarian cancer, we have employed whole microRNA microarray expression profiling as a discovery platform to identify genes with the potential to distinguish recurrent ovarian cancer. 8 recurrent ovarian cancer tissue and 8 primary ovarian cancer tissue and 4 normal ovarian tissue was used to identify miRNA profiling.
2017-06-01 | GSE83693 | GEO
Project description:Comparison of ovarian cancer tissue and normal ovarian tissue to identify miRNA profiling.
2019-03-20 | GSE119055 | GEO
Project description:Thiele2013 - Ovary ovarian stroma cells
The model of ovary ovarian stroma cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000
).
This model is described in the article:
A community-driven global reconstruction of human metabolism.
Thiele I, et al
.
Nature Biotechnology
Abstract:
Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven,
consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared
with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using
Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic
data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically
generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will
facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.
This model is hosted on BioModels Database
and identified by: MODEL1310110029
.
To cite BioModels Database, please use: BioModels Database: An enhanced,
curated and annotated resource for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer
to CC0 Public Domain Dedication
for more information.
2005-01-01 | MODEL1310110029 | BioModels
Project description:The etiology of ovarian cancer is poorly understood, mainly due to the lack of an appropriate experimental model for studying the onset and progression of this disease. We have created a mouse model termed ERalpha d/d in which a conditional deletion of estrogen receptor alpha (ERalpha) gene occurred in the anterior pituitary, but ERalpha expression remained intact in the hypothalamus and the ovary. The loss of negative-feedback regulation by estrogen (E) at the level of the pituitary led to elevated production of luteinizing hormone (LH) by this tissue. Hyperstimulation of ovarian cells by LH resulted in increased steroidogenesis, leading to high circulating levels of progesterone, testosterone and E. The ERalpha d/d mice exhibited formation of palpable ovarian epithelial tumors starting at 5 months of age, and by 12 months, most mice carrying these tumors died. Besides proliferating epithelial cells, these tumors also contained an expanded population of stromal cells, which express P450 aromatase suggesting that these cells acquired the ability to synthesize E. In ERalpha d/d mice, in response to the E produced by the stromal cells, the ERalpha signaling is accentuated in the ovarian epithelial cells, triggering increased ERalpha-dependent gene expression, abnormal cell proliferation, and tumorigenesis. The ERalpha d/d animal model of ovarian epithelial tumorigenesis will serve as a powerful tool for exploring the involvement of E-dependent signaling pathways in the etiology of ovarian cancer. To identify aberrantly regulated genes in epithelial ovarian tumors, we performed gene expression profling of ovarian tumor tissue isolated from ERaplha d/d mice and normal ovary tissue isolated from ERaplha f/f control mice.
2013-08-06 | GSE39402 | GEO
Project description:The etiology of ovarian cancer is poorly understood, mainly due to the lack of an appropriate experimental model for studying the onset and progression of this disease. We have created a mouse model termed ERalpha d/d in which a conditional deletion of estrogen receptor alpha (ERalpha) gene occurred in the anterior pituitary, but ERalpha expression remained intact in the hypothalamus and the ovary. The loss of negative-feedback regulation by estrogen (E) at the level of the pituitary led to elevated production of luteinizing hormone (LH) by this tissue. Hyperstimulation of ovarian cells by LH resulted in increased steroidogenesis, leading to high circulating levels of progesterone, testosterone and E. The ERalpha d/d mice exhibited formation of palpable ovarian epithelial tumors starting at 5 months of age, and by 12 months, most mice carrying these tumors died. Besides proliferating epithelial cells, these tumors also contained an expanded population of stromal cells, which express P450 aromatase suggesting that these cells acquired the ability to synthesize E. In ERalpha d/d mice, in response to the E produced by the stromal cells, the ERalpha signaling is accentuated in the ovarian epithelial cells, triggering increased ERalpha-dependent gene expression, abnormal cell proliferation, and tumorigenesis. The ERalpha d/d animal model of ovarian epithelial tumorigenesis will serve as a powerful tool for exploring the involvement of E-dependent signaling pathways in the etiology of ovarian cancer. To identify aberrantly regulated genes in epithelial ovarian tumors, we performed gene expression profling of ovarian tumor tissue isolated from ERaplha d/d mice and normal ovary tissue isolated from ERaplha f/f control mice. The ERalpha d/d mouse model was created via conditional deletion of ERalpha by employing the Cre-LoxP strategy. Transgenic mice expressing Cre recombinase under the control of progesterone receptor (PR) promoter, termed PR-cre mice, were crossed with mice harboring the M-bM-^@M-^XfloxedM-bM-^@M-^Y ERalpha gene (ERalpha f/f) to create the ERalpah d/d mice in which the ERalpha gene is deleted in cells expressing PR. Ovarian tumor tissue was isolated from ERalpha d/d mice and normal ovary tissue was isolated from ERalpha f/f mice at 5 months and 10 months of age. Tissues were snap frozen and total RNA was isolated. Total RNA was pooled from 3 mice for each sample subjected to microarray analysis.
2013-08-06 | E-GEOD-39402 | biostudies-arrayexpress
Project description:Ovarian cancer has a high mortality rate due, in part, to the lack of early detection and incomplete understanding of the origin of the disease. The hen is the only spontaneous model of ovarian cancer, and can therefore aid in the identification and testing of early detection strategies and therapeutics. To our knowledge, no studies to date have examined global gene expression in ovarian cancer of the hen. Our aim was to combine the use of the hen animal model and microarray technology to identify differentially expressed genes in ovarian tissue from normal hens compared to hens with ovarian cancer. Ovarian tissue samples from whole ovaries were collected from hens for RNA extraction and hybridization on Affymetrix microarrays. Hens were matched for age and laying status. Normal hens (n=3) showed no gross or histopathological evidence of ovarian cancer, while cancer specimens (n=3) had tumors that were stage 2 (restricted to the ovary and observable at necropsy) or 3 (ovarian tumor with abdominal seeding). Total RNA was extracted using TRIZOL according to the manufacturer's instructions.
2011-11-15 | E-GEOD-21706 | biostudies-arrayexpress
Project description:Transcriptional profiling of 4 SCCO tumors compared to age-matched normal ovary to investigate underlying tumor biology and potential therapeutic targets.
2014-01-17 | GSE49887 | GEO
Project description:99 individual ovarian tumors (37 endometrioid, 41 serous, 13 mucinous, and 8 clear cell carcinomas) and 4 individual normal ovary samples, each assayed on an Affymetrix HG_U133A array Keywords: Individual tumor comparisons
2007-04-09 | GSE6008 | GEO
Project description:microRNA counts from ovary (ENCSR854NNW)
| PRJNA909685 | ENA
Project description:99 individual ovarian tumors (37 endometrioid, 41 serous, 13 mucinous, and 8 clear cell carcinomas) and 4 individual normal ovary samples, each assayed on an Affymetrix HG_U133A array Experiment Overall Design: 99 individual ovarian tumors (37 endometrioid, 41 serous, 13 mucinous, and 8 clear cell carcinomas) and 4 individual normal ovary samples. RNA expression was analyzed using one Affymetrix HG_U133A array per sample.
2008-06-14 | E-GEOD-6008 | biostudies-arrayexpress