Activation of FGFR2-kinase domain (iF2 construct)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE48925 | GEO | 2013/07/17
SECONDARY ACCESSION(S): PRJNA212324
REPOSITORIES: GEO
Similar Datasets
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: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 | GSE48928 | 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 | GSE48927 | 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 | GSE48924 | 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: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 18 microarray samples after knocking down PTTG1 and SPDEF in MCF-7 cells. 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 Humanv4 BeadChips arrays interrogating 48107 randomly-distributed bead-types, and in this experiment there was a mean of 22 beads per bead-type (Standard Deviation of 5)
2013-07-17 | E-GEOD-48928 | biostudies-arrayexpress
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 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 46 microarray samples from MCF-7 cells treated under different conditions, at 3 time points (0, 6 and 24 h) in order to perturb FGFR 1b and 2b signalling. 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 4 Humanv4 arrays using 12 samples per array. The original arrays contain 48324 features, with an average of 22 beads per feature (Standard Deviation of 5)
2013-07-17 | E-GEOD-48924 | biostudies-arrayexpress
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 125 microarray samples from MCF-7 cells treated under different conditions, at 5 time points (0, 3, 6, 12 and 24 h) in order to perturb FGFR2 signalling by overexpressing the full length FGFR2b from a tetracycline-inducible expression vector. 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 11 Humanv4 BeadChips using 12 samples per BeadChip. The original arrays contains 48324 features, with a mean of 22 beads per feature (Standard Deviation of 5)
2013-07-17 | E-GEOD-48927 | 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