Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA244104 | ENA |
REPOSITORIES: ENA
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Project description:Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Ovarian cancer cells are known to have diminished response to TGF-beta, but it remains unclear whether TGF-beta can modulate ovarian cancer cell growth in an indirect manner through cancer-associated fibroblasts (CAFs). Using transcriptome profiling analyses on TGF-beta-treated ovarian fibroblasts, we identified a TGF-beta-responsive gene signature in ovarian fibroblasts. Identifying TGF-beta-regulated genes in the ovarian microenvironment helps in understanding the role of TGF-beta in ovarian cancer progression. The human telomerase-immortalized ovarian fibroblast line NOF151 was treated with 5ng/mL of either TGF-beta-1 or TGF-beta-2. Total RNA was isolated from control samples and TGF-beta-treated fibroblasts samples at 48 hours post-treatment, followed by cDNA synthesis, IVT and biotin labeling. Samples were then hybridized onto Affymetrix Human Genome U133 Plus 2.0 microarrays. For each treatment group, three independent samples were prepared for the microarray experiment.
2013-12-31 | E-GEOD-40266 | biostudies-arrayexpress
Project description:Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Ovarian cancer cells are known to have diminished response to TGF-beta, but it remains unclear whether TGF-beta can modulate ovarian cancer cell growth in an indirect manner through cancer-associated fibroblasts (CAFs). Using transcriptome profiling analyses on TGF-beta-treated ovarian fibroblasts, we identified a TGF-beta-responsive gene signature in ovarian fibroblasts. Identifying TGF-beta-regulated genes in the ovarian microenvironment helps in understanding the role of TGF-beta in ovarian cancer progression.
2013-12-31 | GSE40266 | GEO
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
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Project description:Expression data from TGF-beta-treated human ovarian fibroblasts
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