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)
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)
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)
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)
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.
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.
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.
Project description:The estrogen receptor-M-NM-1 (ERM-NM-1) is a transcription factor which plays a critical role in controlling cell proliferation and tumorigenesis by recruiting various cofactors to estrogen response elements (EREs) to induce or repress gene transcription. A deeper understanding of these transcriptional mechanisms may uncover novel therapeutic targets for ERM-NM-1-dependent cancers. Here we show for the first time that BRD4 regulates ERM-NM-1M-bM-^HM-^Rinduced gene expression by affecting elongation-associated phosphorylation of RNA Polymerase II (RNAPII P-Ser2) and histone H2B monoubiquitination (H2Bub1). Consistently, BRD4 activity is required for estrogen-induced proliferation of ER+ breast and endometrial cancer cells and uterine growth in mice. Genome-wide occupancy studies revealed an enrichment of BRD4 on transcriptional start sites as well as EREs enriched for H3K27ac and demonstrate a requirement for BRD4 for H2B monoubiquitination in the transcribed region of estrogen-responsive genes. Importantly, we further demonstrate that BRD4 occupancy correlates with active mRNA transcription and is required for the production of ERM-NM-1-dependent enhancer RNAs (eRNAs). These results uncover BRD4 as a central regulator of ERM-NM-1 function and potential therapeutic target. mRNA expression profiles of MCF7 cells treated with +/- estrogen treatment under negative control siRNA, BRD4 siRNA or JQ1 treatment, in duplicates.