High FGFR2 expression is associated with reduced breast cancer risk and represses the estrogen response
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA301107 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Genome-wide association studies have identified a locus within the second intron of the FGFR2 gene that is consistently the most strongly associated with estrogen receptor-poisive breast cancer risk. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Previously, a systems biology approach was adopted to elucidate the regulatory networks operating in MCF-7 breast cancer cells in order to examine the role of FGFR2 in mediating risk. Here, the same approach has been employed using a number of different estrogen receptor-positive breast cancer cell lines in order to see if the previous findings are reproducible and consistent in estrogen receptor-positive disease.
2015-10-05 | GSE70759 | GEO
Project description:Genome-wide association studies have identified a locus within the second intron of the FGFR2 gene that is consistently the most strongly associated with estrogen receptor-poisive breast cancer risk. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Previously, a systems biology approach was adopted to elucidate the regulatory networks operating in MCF-7 breast cancer cells in order to examine the role of FGFR2 in mediating risk. Here, the same approach has been employed using MCF-7 cells that have been treated with siRNA directed against FGFR2, in order to knock-down FGFR2 expression, to confirm that the differential gene expression that we see when FGF10 signalling is perturbed, on a background of estrogen signalling, is mediated via FGFR2 stimulation.
2016-02-01 | GSE74146 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-11-04 | E-GEOD-74663 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2015-11-04 | GSE74663 | GEO
Project description:Genome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
2013-07-17 | GSE48925 | GEO
Project description:Genome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways The data consists of 71 microarray samples from MCF-7 cells treated under different conditions, at 3 time points (0, 6 and 24 h) in order to perturb FGFR2 signalling using the iF2 construct system. The data have been pre-processed in R using the beadarray package, and are presented in the form of log2 expression values. The experiment was carried out on 6 Humanv4 BeadChips using 12 samples per BeadChip. The original arrays contain 48324 features, with a mean of 22 beads per feature (Standard Deviation of 5)
2013-07-17 | E-GEOD-48925 | biostudies-arrayexpress
Project description:Somatic hotspot mutations and structural amplifications and fusions affecting fibroblast growth factor receptor 2 (FGFR2) occur in multiple cancer types. However, clinical responses to FGFR inhibitors (FGFRi) have remained variable, emphasizing a need to better understand which FGFR2 alterations are oncogenic and targetable. Here we applied transposon-based screening and tumor modelling in mice to uncover truncation of exon (E) 18 of Fgfr2 as a potent driver mutation. Human oncogenomic datasets revealed a diverse set of FGFR2 alterations, including rearrangements (REs), E1-E17 partial amplifications, and E18 nonsense and frameshift mutations, each causing transcription of E18-truncated FGFR2 (FGFR2deltaE18). Somatic modelling in mice and human tumor cell lines using a compendium of FGFR2deltaE18 and full-length variants identified FGFR2deltaE18-truncation as potent single-driver alteration in cancer. Here we show the phosphoproteomic landscape of FGFR2 variants in murine epithelial cell (MEC) lines and mouse tumors. Global (STY) phosphoproteomics using IMAC and phosphotyrosine phosphoproteomics using pTyr IP’s are combined with DIA protein expression data to uncover oncogenic signaling of clinically-relevant FGFR2 variants.
2022-06-06 | PXD031711 | Pride
Project description:Mufudza2012 - Estrogen effect on the dynamics
of breast cancer
This deterministic model shows the
dynamics of breast cancer with immune response. The effects of
estrogen are incorporated to study its effects as a risk factor for
the disease.
This model is described in the article:
Assessing the effects of
estrogen on the dynamics of breast cancer.
Mufudza C, Sorofa W, Chiyaka
ET.
Comput Math Methods Med 2012; 2012:
473572
Abstract:
Worldwide, breast cancer has become the second most common
cancer in women. The disease has currently been named the most
deadly cancer in women but little is known on what causes the
disease. We present the effects of estrogen as a risk factor on
the dynamics of breast cancer. We develop a deterministic
mathematical model showing general dynamics of breast cancer
with immune response. This is a four-population model that
includes tumor cells, host cells, immune cells, and estrogen.
The effects of estrogen are then incorporated in the model. The
results show that the presence of extra estrogen increases the
risk of developing breast cancer.
This model is hosted on
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and identified by:
BIOMD0000000642.
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To the extent possible under law, all copyright and related or
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2024-09-02 | BIOMD0000000642 | BioModels
Project description:27 Hydroxycholesterol represses G9a expression via Estrogen Receptor alpha in breast cancer
| PRJNA974381 | ENA
Project description:Fibroblast Growth Factor (FGF) dependent signalling is frequently activated in cancer by a variety of different mechanisms. However, the downstream signal transduction pathways involved are poorly characterised. Here a quantitative differential phosphoproteomics approach, SILAC, is applied to identify FGF-regulated phosphorylation events in two triple- negative breast tumour cell lines, MFM223 and SUM52PE, that exhibit amplified expression of FGF receptor 2 (FGFR2) and are dependent on continued FGFR2 signalling for cell viability. Comparative Gene Ontology proteome analysis revealed that SUM52PE cells were enriched in proteins associated with cell metabolism and MFM223 cells enriched in proteins associated with cell adhesion and migration. FGFR2 inhibition by SU5402 impacts a significant fraction of the observed phosphoproteome of these cells. This study expands the known landscape of FGF signalling and identifies many new targets for functional investigation. FGF signalling pathways are found to be flexible in architecture as both shared, and divergent, responses to inhibition of FGFR2 kinase activity in the canonical RAF/MAPK/ERK/RSK and PI3K/AKT/PDK/mTOR/S6K pathways are identified. Inhibition of phosphorylation-dependent negative-feedback pathways is observed, defining mechanisms of intrinsic resistance to FGFR2 inhibition. These findings have implications for the therapeutic application of FGFR inhibitors as they identify both common and divergent responses in cells harbouring the same genetic lesion and pathways of drug resistance.
2020-05-20 | PXD016777 | Pride