High FGFR2 expression is associated with reduced breast cancer risk and represses the estrogen response
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Kerstin Meyer
PROVIDER: E-GEOD-74663 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2013-07-17 | E-GEOD-48931 | 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 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 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 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 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:Breast cancer (BC) is a commonly identified life-threatening type of cancer and a major cause of death among women worldwide. Several microRNAs (miRs), including miR-143-5p, have been reported to be vital for regulating hallmarks of cancer; however, the effect of miR-143-5p on BC requires further exploration. The present study performed bioinformatics analysis on GSE42072 and GSE41922 datasets from the National Center for Biotechnology Information Gene Expression Omnibus (GEO) database to identify miR-143-5p expression patterns. Furthermore, miR-143-5p expression was detected in BC cell lines and tissues via reverse transcription-quantitative PCR. Post-transfection with miR-143-5p mimics, Cell Counting Kit-8, colony formation and Transwell assays were performed to explore the effects of miR-143-5p on BC cell proliferation, colony formation, and migration. The association of miR-143-5p with the hypoxia-inducible factor-1α (HIF-1α)-associated glucose transporter 1 (GLUT1) pathway was explored via western blotting, immunofluorescence and dual-luciferase reporter assay. The present study detected high expression of miR-143-5p in BC tissue of the GSE42072 and serum of the GSE41922 datasets by GEO chip analysis. Additionally, the expression levels of miR-143-5p were decreased in BC tissues compared with those in adjacent healthy tissues, and low miR-143-5p expression was associated with a poorer prognosis and shorter survival time in patients with BC. In vitro, miR-143-5p expression levels were decreased in BC cells, and transfection with miR-143-5p mimics suppressed BC cell proliferation, colony formation, migration. Furthermore, miR-143-5p targeted the HIF-1α-related GLUT1 pathway, and inhibited HIF-1α and GLUT1 expression. Additionally, HIF-1α agonists reversed the miR-143-5p-induced inhibition during tumorigenesis. In conclusion, miR-143-5p exhibited low expression in BC tissues, and suppressed BC cell proliferation, colony formation, migration. Moreover, the antitumor effects of miR-143-5p targeted the HIF-1α-related GLUT1 pathway.
2022-02-26 | E-MTAB-11160 | biostudies-arrayexpress
Project description:Estrogen Receptor subtypes (ERα and ERβ) are transcription factors sharing similar structure, however, they often perform opposite roles in breast cancer’s cell proliferation and tumor progression. Besides the well-characterized genomic actions of ERs upon ligand binding, rapid non-genomic cytoplasmic changes together with the recently discovered ligand-free action of ERs are emerging as key regulators of tumorigenesis. The identification of cytoplasmic interaction partners of unliganded ERα and ERβ may help characterize the molecular basis of the extra-nuclear mechanism of action of these receptors, revealing novel mechanisms to explain their role in breast cancer response or resistance to endocrine therapy. To this aim, in this study, cytoplasmic extracts from stably expressing TAP-ERα and -ERβ MCF-7 cell clones were subjected to interaction proteomics in the absence of estrogen stimulation, leading to the identification of 84 and 142 proteins associated with unliganded ERα and ERβ, respectively. Functional analyses of ER subtype-specific interactomes revealed significant differences in the molecular pathways associated to each receptor in the cytoplasm. This work reports the first identification of the unliganded ERα and ERβ cytoplasmic interactomes in breast cancer cells, providing novel experimental evidence on the non-genomic effects of ERs in the absence of hormonal stimulus.
2015-03-11 | PXD001202 | Pride
Project description:Three quarters of all breast cancer cases express the estrogen receptor (ER, ESR1 gene), which promotes tumor growth and constitutes a direct target for endocrine therapies. ESR1 mutations have been implicated in therapy resistance in metastatic breast cancers, in particular to aromatase inhibitors. ESR1 mutations promote constitutive ER activity and affect other signaling pathways, allowing cancer cells to proliferate by employing mechanisms within and outwith direct regulation by the ER. Although subjected to extensive genetic and transcriptomic analyses, understanding of protein alterations remains poorly investigated. Towards this, we employed an integrated mass spectrometry (MS) based proteomic approach to profile the protein and phosphoprotein differences in breast cancer cell lines expressing the frequent Y537N and Y537S ER mutations. Global proteome analysis revealed enrichment of mitotic and immune signaling pathways in ER mutant cells, while phosphoprotein analysis evidenced enriched activity of proliferation associated kinases, in particular CDKs and MTOR. Integration of protein expression and phosphorylation data revealed pathway-dependent discrepancies (motility vs proliferation) that were observed at varying degrees across mutant and wt ER cells. Additionally, protein expression and phosphorylation patterns, while under different regulation, still recapitulated the estrogen-independent phenotype of ER mutant cells.
2024-03-26 | PXD046446 | Pride
Project description:Introduction: Breast radiotherapy is currently â??one size fits allâ?? regardless of breast cancer subtype (eg. luminal, basal). However, recent clinical data suggests that radiation response may vary significantly among subtypes. Therefore, current practice leads to over- or under-treatment of women whose tumors are more or less radiation responsive. We hypothesized that this clinical variability may be due, in part, to differences in cellular radiation response. Methods: We exposed 16 biologically-diverse breast tumor cell lines to 0 or 5GY radiation. Microarray analysis was performed on RNA harvested from those cell lines. Samples were run in triplicate. Following quality assessment, differential gene expression analysis was performed using a two-way multiplicative linear mixed-effects model. A candidate radiation response biomarkers with biologically plausible role in radiation response, were identified and confirmed at the RNA and protein level with qPCR and Western blotting assays. Induction in human breast tumors was confirmed in 32 patients with paired pre- and post-radiation tumor samples using IHC and microarray analysis. Quantification of protein was performed in a blinded manner and included positive and negative controls. The objective of our study was to identify genomic determinants of radiation sensitivity using clinical samples as well as breast tumor cell lines. In order to identify differences in the radiation response gene expression profiles of specific breast cancer subtypes, we exposed 16 biologically-diverse breast tumor cell lines to 0 or 5GY radiation. Microarray analysis was performed on RNA harvested from those cell lines. Samples were run in triplicate. Following quality assessment, differential gene expression analysis was performed using a two-way multiplicative linear mixed-effects model. Candidate radiation response biomarker with a biologically plausible role in radiation response, were identified and confirmed at the RNA and protein level with qPCR and Western blotting assays. Induction of the genes of interest were further evaluated and confirmed in human breast tumors in 32 breast cancer patients with paired pre- and post-radiation tumor samples using IHC and microarray analysis assays.
2015-10-31 | E-GEOD-59732 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-11-02 | E-GEOD-59734 | biostudies-arrayexpress