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 endometriosis and ovarian cancer

ABSTRACT: Gene expression profiling in endometriosis and ovarian cancer

PROVIDER: PRJNA660284 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR12549333.fastq.gz	Fastqsanger.gz
	SRR12549334.fastq.gz	Fastqsanger.gz
	SRR12549335.fastq.gz	Fastqsanger.gz
	SRR12549336.fastq.gz	Fastqsanger.gz
	SRR12549337.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 66

Similar Datasets

Complement Roles Revealed by Immune Gene Profiling in Endometriosis and Endometriosis-Associated Ovarian Cancer

2015-01-07 | GSE57545 | GEO

Complement Roles Revealed by Immune Gene Profiling in Endometriosis and Endometriosis-Associated Ovarian Cancer

Project description:Mechanisms of immune dysregulation against established tumors are relatively well understood. Much less is known about the role of immune effectors against cancer precursor lesions. Endometrioid and clear cell ovarian tumors may partly derive from endometriosis, a commonly diagnosed chronic inflammatory disease. We performed here the most comprehensive immune gene expression analysis of pelvic inflammation in endometriosis and endometriosis-associated ovarian cancer (EAOC). RNA was extracted from 120 paraffin tissue blocks comprising of normal endometrium (n=32), benign endometriosis (n=30), atypical endometriosis (n=15) and EAOC (n=43). Serous tumors (n=15) were included as non-endometriosis associated controls. The immune microenvironment was profiled using Nanostring and the nCounterÂ® GX Human Immunology Kit, comprising probes for a total of 511 immune genes. Please note that 3 normal endometrium samples did not pass the array quality filtering and therefore excluded in the data analyses.

2015-01-07 | E-GEOD-57545 | biostudies-arrayexpress

Gene expression profiling in endometriosis and ovarian cancer

Project description:This study aimed to identify an essential gene in the malignant transformation of endometriosis to clear cell ovarian carcinoma and endometrioid ovarian carcinoma.

2021-04-01 | GSE157153 | GEO

Role of small extracellular-vesicle microRNA-302f in endometriosis-associated ovarian cancer

Project description:Background: Tumor microenvironment is well known to have a key role in tumor development. Extracellular vesicles are capable in cell signaling transduction and important in regulation of tumor microenvironment. Objective: To investigate whether peritoneal fluid–derived extracellular vesicles help regulate the tumor microenvironment in the malignant transformation of endometriosis. Methods: Samples of peritoneal fluid were taken from women with benign gynecological disease, endometriosis, or endometriosis-associated ovarian cancer. Small extracellular vesicles in the samples were isolated via ultracentrifugation and characterized by western blotting, transmission electron microscopy, and nanoparticle tracking. A global microRNA (miRNA) expression profile array was used to analyze miRNA abundance in peritoneal fluid–derived small extracellular vesicles. Candidate miRNAs were quantified by reverse transcription PCR to assess their potential role in cell migration. Results: A total of 22 miRNAs were identified from the analysis of miRNAs in peritoneal fluid–derived small extracellular vesicles from patients with endometriosis or endometriosis-associated ovarian cancer. We confirmed that each miRNA was expressed in various ovarian cell lines. The miRNA miR-302f was consistently highly expressed in both clinical specimens and ovarian cell lines from patients with endometriosis, yet expression was relatively low in specimens and cell lines from patients with endometriosis-associated ovarian cancer. A bio-functional assay revealed that miR-302f regulates cell migration. Finally, the possible target mRNAs of miR-302f were identified in the Gene Expression Omnibus database. Conclusions: These data may provide a basis for the development of novel therapeutic strategies for endometriosis-associated ovarian cancer patients by downregulating PDGFRA abundance in cancer cells via overexpression of miR-302f.

2026-01-14 | GSE307729 | GEO

MicroRNA Profiling in Ovarian Cancer

Project description:Deregulated expression of miRNAs contributes to ovarian cancer. This study is aimed to identify which miRNAs are differentially expressed in Ovarian cancer compared to endometriosis Paired ovarian cancer and endometriosis tissues from FFPE were used to isolate total RNA. miRNA expression were analyzed by miRNA microarray assay Please note that each sample represents 19 paired cases tissue samples of endometriosis and ovarian cancer pooled together and ran in quadruplicate with their group mean values, and the raw data for pooled tissue sample is provided in the 'Raw data.xls'.

2015-07-30 | E-GEOD-71477 | biostudies-arrayexpress

MicroRNA Profiling in Ovarian Cancer

2015-07-30 | GSE71477 | GEO

microRNA expression profilings in ectopic and eutopic endometria of ovarian endometriosis.

Project description:The etiology and pathophysiology of endometriosis remain unclear. Accumulating evidence suggests that aberrant microRNA (miRNA) expression may be involved in the pathogenesis and development of endometriosis. This study therefore aims to survey key miRNAs and further understand the mechanism of endometriosis. Paired expression profiling of miRNA in ectopic endometria compared with eutopic endometria were determined by high-throughput sequencing techniques in eight patients with ovarian endometriosis. Our study presents a unique insight into the regulatory network of this enigmatic disorder and possibly provides clues regarding replacement therapy of endometriosis.

2018-02-14 | GSE105765 | GEO

lncRNA expression profilings in ectopic and eutopic endometria of ovarian endometriosis.

Project description:The etiology and pathophysiology of endometriosis remain unclear. Accumulating evidence suggests that aberrant mRNA and lncRNA expressions may be involved in the pathogenesis and development of endometriosis. This study therefore aims to survey key TFs, genes and lncRNAs and further understand the mechanism of endometriosis. Paired expression profiling of mRNA and lncRNA in ectopic endometria compared with eutopic endometria were determined by high-throughput sequencing techniques in eight patients with ovarian endometriosis. Our study presents a unique insight into the regulatory network of this enigmatic disorder and possibly provides clues regarding replacement therapy of endometriosis.

2018-02-14 | GSE105764 | GEO

Transcriptome-wide m6A methylome of endometrioid ovarian cancer and ovarian endometriosis

Project description:Transcriptome-wide m6A methylome of endometrioid ovarian cancer and ovarian endometriosis

| PRJNA807156 | ENA

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Project description:Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg=0.71), endometrioid (rg=0.48) and high-grade serous (rg=0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identify 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.

2022-03-07 | GSE197928 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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