Ontology highlight
ABSTRACT:
PROVIDER: PRJNA929551 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR23299945.fastq.gz | Fastqsanger.gz | |||
| SRR23299946.fastq.gz | Fastqsanger.gz | |||
| SRR23299947.fastq.gz | Fastqsanger.gz | |||
| SRR23299948.fastq.gz | Fastqsanger.gz | |||
| SRR23299949.fastq.gz | Fastqsanger.gz |
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Project description:Deregulation of the transforming growth factor-? (TGF?) signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGF? signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate genome-wide screening of TGF?-induced SMAD4 binding in epithelial ovarian cancer. Following TGF? stimulation of the A2780 epithelial ovarian cancer cell line, we identified 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci, revealed four distinct binding patterns: 1) Basal; 2) Shift; 3) Stimulated Only; 4) Unstimulated Only. SMAD4-bound loci were primarily classified as either Stimulated only (74%) or Shift (25%), indicating that TGF?-stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells compared to normal epithelial cells. Furthermore, based on gene regulatory network analysis, we determined that the TGF?-induced SMAD4-dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGF?/SMAD4 target genes identified in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient data bases. In conclusion, our data highlight the utility of next generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer. The results link aberrant TGF?/SMAD signaling to ovarian tumorigenesis. Furthermore, the identified SMAD4 binding loci, combined with gene expression profiling and in silico data mining of patient cohorts, may provide a powerful approach to determine potential gene signatures with biological and future translational research in ovarian and other cancers. ChIP-Seq: 1 control lane. 4 unstimulated lanes 4 stimulated lanes Gene expression: 3 technical replicates each of SMAD4 stimulated and SMAD4 unstimulated cells
2011-06-30 | E-GEOD-27526 | biostudies-arrayexpress
Project description:Deregulation of the transforming growth factor-β (TGFβ) signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGFβ signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate genome-wide screening of TGFβ-induced SMAD4 binding in epithelial ovarian cancer. Following TGFβ stimulation of the A2780 epithelial ovarian cancer cell line, we identified 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci, revealed four distinct binding patterns: 1) Basal; 2) Shift; 3) Stimulated Only; 4) Unstimulated Only. SMAD4-bound loci were primarily classified as either Stimulated only (74%) or Shift (25%), indicating that TGFβ-stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells compared to normal epithelial cells. Furthermore, based on gene regulatory network analysis, we determined that the TGFβ-induced SMAD4-dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGFβ/SMAD4 target genes identified in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient data bases. In conclusion, our data highlight the utility of next generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer. The results link aberrant TGFβ/SMAD signaling to ovarian tumorigenesis. Furthermore, the identified SMAD4 binding loci, combined with gene expression profiling and in silico data mining of patient cohorts, may provide a powerful approach to determine potential gene signatures with biological and future translational research in ovarian and other cancers.
2011-07-01 | GSE27526 | GEO
Project description:Background: MicroRNAs (miRNAs) are small regulatory RNAs that are implicated in cancer pathogenesis and have recently shown promise as blood-based biomarkers for cancer detection. Epithelial ovarian cancer is a deadly disease for which improved outcomes could be achieved by successful early detection and enhanced understanding of molecular pathogenesis that leads to improved therapies. A critical step toward these goals is to establish a comprehensive view of miRNAs expressed in epithelial ovarian cancer tissues as well as in normal ovarian surface epithelial cells. Methodology: We used massively parallel pyrosequencing (i.e., M-bM-^@M-^\454 sequencingM-bM-^@M-^]) to discover and characterize novel and known miRNAs expressed in primary cultures of normal human ovarian surface epithelium (HOSE) and in tissue from three of the most common histotypes of ovarian cancer. Deep sequencing of small RNA cDNA libraries derived from normal HOSE and ovarian cancer samples yielded a total of 738,710 high-quality sequence reads, generating comprehensive digital profiles of miRNA expression. Expression profiles for 498 previously annotated miRNAs were delineated and we discovered six novel miRNAs and 39 candidate miRNAs. A set of 124 miRNAs was differentially expressed in normal versus cancer samples and 38 miRNAs were differentially expressed across histologic subtypes of ovarian cancer. Taqman qRT-PCR performed on a subset of miRNAs confirmed results of the sequencing-based study.
2009-03-12 | E-GEOD-15190 | biostudies-arrayexpress
Project description:Single cell RNA sequencing of macrophages harvested from omentum of mice 10 weeks after intra peritoneal inoculation of epithelial ovarian cancer cells.
2020-01-06 | E-MTAB-8593 | biostudies-arrayexpress
Project description:RNA-sequencing was performed to gain insight into the mechanism responsible for the mesenchymal-to-epithelial transition (MET) induced by loss of long non-coding RNA (lncRNA) DNM3OS in SKOV3 ovarian cancer cells. Following siRNA-mediated knockdown of DNM3OS or non-targeting control, RNA-sequencing was performed. This high-throughput data revealed knockdown of DNM3OS down-regulated the expression of genes and pathways known to induce EMT in ovarian cancer.
2018-02-13 | GSE104295 | GEO
Project description:The transcriptomes of three immortalized ovarian surface epithelial cell lines (iOSE, PMID: 17266044) and primary OSE cells (Innoprot, Derio, Spain) and four immortalized fallopian tube secretory epithelial (iFTE) cell lines (PMID: 21502498, 22936217) were compared. RNA-sequencing was done from rRNA depleted total RNA (Ribo-Zero rRNA Removal Kit) to approx. 20 million 50 bp paired end reads per sample. A discriminative gene expression signature comprised of 211 genes was developed and used to classify isolated and EpCAM enriched primary ovarian cancer cells (PMID: 25991672). Impact of this signature on overall survival was assessed from several publicly available ovarian cancer gene expression data sets. Background: High grade serous ovarian cancer (HGSOC) is characterized by extensive local, i.e. peritoneal, tumor spread, manifested in two different clinical presentations, miliary (many millet sized peritoneal implants) and non-miliary (few large exophytically growing peritoneal nodes), and an overall unfavorable outcome. HGSOC is thought to arise from fallopian tube secretory epithelial cells, via so called serous tubal intraepithelial carcinomas (STICs) but an ovarian origin was never ruled out for at least some cases. Comparative transcriptome analyses of isolated tumor cells from fresh HGSOC tissues and (immortalized) ovarian surface epithelial and fallopian tube secretory epithelial cell lines revealed a close relation between putative origin and tumor spread characteristic, i.e. miliary from tubes and non-miliary from ovaries.
2016-12-15 | E-MTAB-5240 | biostudies-arrayexpress
Project description:The Urine RNA from 5 ovarian cancer and 5 healthy control were analyzed with the Human miRNA Microarray and then validated with a quantitative reverse-transcription PCR assay with 29 individual samples, 20 benign gynecological disease and 26 age/sex-matched healthy control. This study determines the clinical value of urine miRNAs as biomarker for epithelial ovarian cancer. Results: The miRNA microarray results demonstrate that the original 38 were identified that were significantly differentially expression in epithelial ovarian cancer compared with healthy control (P<0.01). A total of 1 miRNA was up-regulated in ovarian cancer, while 37 miRNA were down-regulated.
2015-06-17 | GSE58517 | GEO
Project description:Ovarian cancer is also known as a silent killer as women are usually diagnosed in advanced stages when the disease has already spread to vital peritoneal organs leading to poor survival. Therefore, improving outcomes for this disease would require a greater understanding of the earliest stages, where the disease can be cured with current treatments. Fallopian tubes (FTs) are a site of origin of ovarian cancer. Here, by combining gene sequencing, proteomics, organoids, mouse genetics, lineage tracing, and quantitative modeling, we showed that mutant Pax8+ FT progenitor cells gain clonal growth advantage over their wild-type neighbors and expand over time, colonizing large areas of FT epithelium, resulting in the formation of pre-cancerous lesions. The growth of these precursor lesions is modulated by ovarian hormones, where estrogen promotes and progesterone suppresses their growth. Collectively, this study provides insight into how a single mutant FT epithelial cell leads to early ovarian cancer evolution.
2024-01-10 | MSV000093831 | GNPS
Project description:Unlike ovarian cancer, normal ovarian epithelium response to TGFb1 induced growth inhibition. This study tried to idenify promoters that showed Smad4 binding after additionof TGFb1 in immortalized ovarian surface epithelial cells (IOSE) which is derived from normal ovarian epithelial cells Keywords: ChIP-chip
2007-01-13 | GSE6727 | GEO
Project description:The Urine RNA from 5 ovarian cancer and 5 healthy control were analyzed with the Human miRNA Microarray and then validated with a quantitative reverse-transcription PCR assay with 29 individual samples, 20 benign gynecological disease and 26 age/sex-matched healthy control. This study determines the clinical value of urine miRNAs as biomarker for epithelial ovarian cancer. Results: The miRNA microarray results demonstrate that the original 38 were identified that were significantly differentially expression in epithelial ovarian cancer compared with healthy control (P<0.01). A total of 1 miRNA was up-regulated in ovarian cancer, while 37 miRNA were down-regulated. the urine RNA from 5 ovarian cancer and 5 healthy women were analysised with Human mirRNA microarry
2015-06-17 | E-GEOD-58517 | biostudies-arrayexpress