Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gene Expression Profiling in progesterone-induced HGSC development.

ABSTRACT: Here we show that ovarian progesterone is a crucial endogenous factor inducing metastatic ovarian cancer in a mouse model of high-grade serous carcinoma (HGSC). To examine the molecular signaling pathways underlying progesterone (P4)-induced HGSC development, we performed gene-expression profiling using RNA sequencing.

ORGANISM(S): Mus musculus

PROVIDER: GSE157960 | GEO | 2020/12/29

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Profiles of genomic instability in high-grade serous ovarian cancer (HGSC) predict treatment outcome

Project description:Profiling of loss of heterozygosity (LOH) in HGSC, subcrouping HGSC by LOH-based clustering and comparing to the LOH profiles of triple-negative breast cancer [previously submitted; GSE19594]. Study for the correlation of LOH burdern and LOH-based subgroups to clinical response to platinum-based chemotherapy in patients suffered from HGSC. SNP data (Affymetrix GenChip 250K SNP Nsp) from 47 high grade serous ovarian cancer were generated and used for LOH and copy number analysis, LOH-based hierarchical clustering to subclassify HGSC, and comparison to the chromosomal alterations in high grade brest cancer. The associstion between LOH-based subgroups and LOH burden and clinical resposne to platinum-based chemotherapy was investigated. The results were validated in two independent public opening datasets.

2012-11-06 | E-GEOD-39130 | biostudies-arrayexpress

Expression data from high-grade serous ovarian carcinomas (HGSC), clear cell ovarian carcinomas (CCC) and ovarian surface epithelium (OSE)

Project description:Background: The aim of this study was to identify differentially expressed miRNAs in high-grade serous ovarian carcinoma (HGSC), clear cell ovarian carcinoma (CCC) and ovarian surface epithelium (OSE). Selected miRNAs were evaluated for association with clinical parameters including survival, and miRNA/mRNA interactions were mapped. Results: Differentially expressed miRNAs between HGSC, CCC and OSE were identified, of which 18 were validated (p<0.01) using RT-qPCR in an extended cohort. Compared with OSE, miR-205-5p was the most overexpressed miRNA in HGSC. miR-200 family members and miR-182-5p were the most overexpressed in HGSC and CCC compared with OSE, whereas miR-383 was the most underexpressed. miR-509-3-5p, miR-509-5p, miR-509-3p and miR-510 were among the strongest differentiators between HGSC and CCC, all being significantly overexpressed in CCC compared with HGSC. High miR-200c-3p expression was associated with poor progression-free (p=0.031) and overall (p=0.026) survival in HGSC. Interacting miRNAs and mRNA targets, including those of a TP53-related pathway presented previously, were identified in HGSC. Conclusions: Several miRNAs are overexpressed in HGSC and CCC compared with OSE, including the miR-200 family, among which miR-200c-3p is associated with survival in HGSC. A set of miRNAs differentiates CCC from HGSC, of which miR-509-3-5p and miR-509-5p are the strongest classifiers. Several interactions between miRNAs and mRNAs in HGSC were mapped. Methods: Differences in miRNA expression between HGSC, CCC and OSE scrapings were analyzed by global miRNA expression profiling (Affymetrix GeneChip miRNA 2.0 Arrays, n=30), validated by RT-qPCR (n=63), and evaluated for associations with clinical parameters. For HGSC, differentially expressed miRNAs were linked to differentially expressed mRNAs identified previously (GSE36668).

2014-02-13 | E-GEOD-47841 | biostudies-arrayexpress

Generation of low passage high grade serous ovarian cancer cell lines from primary tumors

Project description:High grade serous ovarian cancers (HGSC) are deadly malignancies that relapse despite carboplatin chemotherapy. Many commercially ovarian cancer cell lines are not good models for HGSC. Here we demonstrate that 3 low passage cell lines derived from HGSC have similar transcriptomes to their parental bulk tumors. These cell lines recapitulated tumor characteristics of the primary cancer and had responded to therapy in the same manner as primary HGSC cells, demonstrating they are accurate models for HGSCs. mRNA profiles of low passage high grade serous tumor cell lines and their parental tumors, generated by next generation sequencing, were compared.

2015-08-01 | E-GEOD-70073 | biostudies-arrayexpress

WashU Primary and Metastatic Tumors with Survival in High-Grade Serous Ovarian Cancer RNA-seq

Project description:High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late stage disease. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival.

2023-04-27 | GSE218939 | GEO

LC-MSMS of primary HGSC class I immunopeptidom

Project description:High-grade serous ovarian cancer (HGSC), the principal cause of death from gynecological malignancies in the world, has not significantly benefited from recent progress in cancer immunotherapy. While HGSC infiltration by lymphocytes correlates with superior survival, the nature of antigens that can elicit anti-HGSC immune responses is unknown. The goal of this study was to establish the global landscape of HGSC tumor-specific antigens (TSAs) using a mass spectrometry pipeline that interrogates all reading frames of all genomic regions. In 23 HGSC tumors, we identified 113 TSAs. Classic TSA discovery approaches focusing only on mutated exonic sequences would have uncovered only seven of these TSAs. Other mutated TSAs resulted from out-of-frame exonic translation or from non-exonic sequences. The most interesting group of TSAs (n = 94) derived from aberrantly expressed unmutated genomic sequences which are not expressed in normal tissues. These aberrantly expressed TSAs (aeTSAs) derived primarily from non-exonic sequences, in particular intronic (31%) and intergenic (22%). Their expression was regulated at the transcriptional level by variations in gene copy number and DNA methylation. While mutated TSAs were unique to individual tumors, aeTSAs were shared by a large proportion of HGSCs. We conclude that, in view of their number and the fact that they are shared by many tumors, aeTSAs may be the most attractive targets for HGSC immunotherapy.

2020-02-18 | PXD014062 | Pride

Expression data from high-grade serous ovarian carcinomas (HGSC), clear cell ovarian carcinomas (CCC) and ovarian surface epithelium (OSE)

2014-02-13 | GSE47841 | GEO

Gene Expression Profiling in progesterone-induced HGSC development.

Project description:Gene Expression Profiling in progesterone-induced HGSC development.

| PRJNA663551 | ENA

Molecular analysis of clinically defined subsets of high-grade serous ovarian cancer

Project description:The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. Comprehensive molecular analyses were performed including high-pass whole-genome sequencing, targeted deep DNA sequencing, RNA sequencing, reverse-phase protein arrays, mass spectrometry-based proteomics and phosphoproteomics, and immune profiling on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

2020-05-27 | PXD014980 | Pride

Biomarkers in older ovarian cancer patients

Project description:Identification and validation of potential prognostic biomarkers in older ovarian cancer patients with high-grade serous adenocarcinoma (HGSC)

2020-03-01 | GSE126308 | GEO

Genetically defined syngeneic mouse models of ovarian cancer as tools for the discovery of combination immunotherapy [scRNA-Seq]

Project description:Purpose: One of the goals of this study is to compare the transcriptome profiles of tumors from mice inoculated with specific engineered fallopian tube cells of high-grade serous tubo-ovarian cancer (HGSC) models (this study) using scRNA sequencing Methods: Tumors from mice inoculated with specific engineered fallopian tube cells of high-grade serous tubo-ovarian cancer (HGSC) models were compared using scRNA sequencing. Conclusions: We conclude that scRNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biological functions.

2020-11-17 | GSE158886 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data