Transcription profiling of human MCF7 cells after EGF, HRG stimulation
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Mariko Hatakeyama
PROVIDER: E-GEOD-13009 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:ErbB receptor ligands, epidermal growth factor (EGF) and heregulin (HRG), induce dose-dependent transient and sustained intracellular signaling, proliferation and differentiation of MCF-7 breast cancer cells, respectively. In an effort to delineate the ligand-specific cell determination mechanism, we investigated time-course gene expressions induced by EGF and HRG that induce distinct cellular phenotypes in MCF-7 cells. To analyze the effects of ligand dosage and time for the gene expression independently, we developed a statistical method for decomposing the expression profiles into the two effects. Our results indicated that signal transduction pathways devotedly convey quantitative properties of the dose-dependent activation of ErbB receptor to early transcription. The results also implied that moderate changes in the expression levels of numbers of genes, not the predominant regulation of a few specific genes, might cooperatively work at the early stage of the transcription for determining the cell fate. However, the EGF- and HRG-induced distinct signal durations resulted in the ligand-oriented biphasic induction of proteins after 20 min. The selected gene list and HRG-induced prolonged signaling suggested that transcriptional feedback to the intracellular signaling results in a graded to biphasic response in the cell determination process, and that each ErbB receptor is inextricably responsible for the control of amplitude and duration of cellular biochemical reactions. MCF-7 human breast cancer cells were incubated from 5min to 90min after administration of different concentrations of the growth hormones (epidermal growth factor (EGF) and heregulin (HRG)). Control was set as growth hormone non-treated cells. For each growth hormone, one control was used.
2007-11-01 | E-GEOD-6462 | biostudies-arrayexpress
Project description:Sharing common ErbB/HER receptor signaling pathway, heregulin (HRG) induces differentiation of MCF-7 breast cancer cells while epidermal growth factor (EGF) elicits proliferation. Although the cell fate led by those two ligands was totally different, the gene expression profile in early transcription was unexpectedly qualitatively similar, suggesting that the gene expression in late transcription, not early transcription, may reflect a respect of ligand specificity. In this study, based on the data from time-course microarray of all human genes, we predicted and determined a series of transcription factors which may control HRG-specific timed-late transcription and cellular differentiation of MCF-7 cells. Validation analyses showed that one of activator protein 1 (AP-1) families appeared just after c-Fos expression, another AP-1 family partner, induced expression of another transcription factor through activation of AP-1 complex. Furthermore, expression of this transcription factors caused suppression of extracellular signal-regulated kinase (ERK) phosphorylation which is sustainedly regulated by HRG-initiated ErbB signaling. Overall, our analysis indicated an importance of formation of timed-transcriptional regulatory network and its function to control upstream signaling pathway through negative feedback for cellular differentiation. Keywords: growth hormone response, time course
2009-05-26 | GSE13009 | GEO
Project description:ErbB receptor ligands, epidermal growth factor (EGF) and heregulin (HRG), induce dose-dependent transient and sustained intracellular signaling, proliferation and differentiation of MCF-7 breast cancer cells, respectively. In an effort to delineate the ligand-specific cell determination mechanism, we investigated time-course gene expressions induced by EGF and HRG that induce distinct cellular phenotypes in MCF-7 cells. To analyze the effects of ligand dosage and time for the gene expression independently, we developed a statistical method for decomposing the expression profiles into the two effects. Our results indicated that signal transduction pathways devotedly convey quantitative properties of the dose-dependent activation of ErbB receptor to early transcription. The results also implied that moderate changes in the expression levels of numbers of genes, not the predominant regulation of a few specific genes, might cooperatively work at the early stage of the transcription for determining the cell fate. However, the EGF- and HRG-induced distinct signal durations resulted in the ligand-oriented biphasic induction of proteins after 20 min. The selected gene list and HRG-induced prolonged signaling suggested that transcriptional feedback to the intracellular signaling results in a graded to biphasic response in the cell determination process, and that each ErbB receptor is inextricably responsible for the control of amplitude and duration of cellular biochemical reactions. Keywords: time course, dose response
2006-12-09 | GSE6462 | GEO
Project description:ErbB receptor ligands, epidermal growth factor (EGF) and heregulin (HRG), induce dose-dependent transient and sustained intracellular signaling, proliferation and differentiation of MCF-7 breast cancer cells, respectively. In an effort to delineate the ligand-specific cell determination mechanism, we investigated time-course gene expressions induced by EGF and HRG that induce distinct cellular phenotypes in MCF-7 cells. To analyze the effects of ligand dosage and time for the gene expression independently, we developed a statistical method for decomposing the expression profiles into the two effects. Our results indicated that signal transduction pathways devotedly convey quantitative properties of the dose-dependent activation of ErbB receptor to early transcription. The results also implied that moderate changes in the expression levels of numbers of genes, not the predominant regulation of a few specific genes, might cooperatively work at the early stage of the transcription for determining the cell fate. However, the EGF- and HRG-induced distinct signal durations resulted in the ligand-oriented biphasic induction of proteins after 20 min. The selected gene list and HRG-induced prolonged signaling suggested that transcriptional feedback to the intracellular signaling results in a graded to biphasic response in the cell determination process, and that each ErbB receptor is inextricably responsible for the control of amplitude and duration of cellular biochemical reactions. Keywords: time course
2006-12-15 | GSE6521 | GEO
Project description:Quantitative phosphoproteome and transcriptome analysis of ligand-stimulated MCF-7 human breast cancer cells was performed to understand the mechanisms of tamoxifen resistance at a systems level. Phosphoproteome data revealed that wild type (WT) cells were more enriched with phospho-proteins than tamoxifen-resistant (TamR) cells after stimulation with ligands. Surprisingly, decreased phosphorylation after ligand perturbation was more common than increased phosphorylation. In particular, 17beta-estradiol (E2) induced down-regulation in WT cells at a very high rate. E2 and the ErbB ligand, heregulin (HRG) induced almost equal numbers of up-regulated phospho-proteins in WT cells. Pathway and motif activity analyses using transcriptome data additionally suggested that deregulated activation of GSK3B?(glycogen synthase kinase 3 beta) and MAPK1/3 signaling might be associated with altered activation of CREB and AP-1 transcription factors in TamR cells and this hypothesis was validated by reporter assays. An examination of clinical samples revealed that, inhibitory phosphorylation of GSK3B at serine 9 was significantly lower in tamoxifen-treated breast cancer patients that eventually had relapses, implying that activation of GSK3B may be associated with the tamoxifen resistant phenotype. Thus, the combined phosphoproteome and transcriptome dataset analyses revealed distinct signal-transcription programs in tumor cells and provided a novel molecular target to understand tamoxifen resistance. The MCF-7 human breast cancer cell line and tamoxifen-resistant MCF-7 cells were stimulated by the growth hormone heregulin (HRG) or 17beta-estradiol (E2) in the presence or absence of tamoxifen. Control was set as non-treated cells.
2010-11-03 | E-GEOD-21618 | biostudies-arrayexpress
Project description:Heregulin beta-1 (HRG) is an extracellular ligand that activates mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI3K)/Akt signaling pathways through ErbB receptors. MAPK and Akt have been shown to phosphorylate the estrogen receptor (ER) at Ser-118 and Ser-167, respectively, thereby mimicking the effects of estrogenic activity such as estrogen responsive element (ERE)-dependent transcription. In the current study, integrative analysis was performed using two tiling array platforms, comprising histone H3 lysine 9 (H3K9) acetylation and RNA mapping, together with array comparative genomic hybridization (CGH) analysis in an effort to identify HRG-regulated genes in ER-positive MCF-7 breast cancer cells. Through application of various threshold settings, 333 (326 up-regulated and 7 down-regulated) HRG-regulated genes were detected. Prediction of upstream transcription factors (TFs) and pathway analysis indicated that 21% of HRG-induced gene regulation may be controlled by the MAPK cascade, while only 0.6% of the gene expression is controlled by ERE. A comparison with previously reported estrogen (E2)-regulated gene expression data revealed that only 12 common genes were identified between the 333 HRG-regulated (3.6%) and 239 E2-regulated (5.0%) gene groups. However, with respect to enriched upstream TFs, 4 common TFs were identified in the 14 HRG-regulated (28.6%) and 13 E2-regulated (30.8%) gene groups. These results indicated that while E2 and HRG may induce common TFs, the regulatory mechanisms that govern HRG- and E2-induced gene expression differ. Experiment Overall Design: MCF-7 human breast cancer cells were incubated 2hour after administration of 10nM of the growth hormones (heregulin (HRG)). Control was set as growth hormone non-treated cells.
2008-04-08 | E-GEOD-8471 | biostudies-arrayexpress
Project description:Heregulin beta-1 (HRG) is an extracellular ligand that activates mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI3K)/Akt signaling pathways through ErbB receptors. MAPK and Akt have been shown to phosphorylate the estrogen receptor (ER) at Ser-118 and Ser-167, respectively, thereby mimicking the effects of estrogenic activity such as estrogen responsive element (ERE)-dependent transcription. In the current study, integrative analysis was performed using two tiling array platforms, comprising histone H3 lysine 9 (H3K9) acetylation and RNA mapping, together with array comparative genomic hybridization (CGH) analysis in an effort to identify HRG-regulated genes in ER-positive MCF-7 breast cancer cells. Through application of various threshold settings, 333 (326 up-regulated and 7 down-regulated) HRG-regulated genes were detected. Prediction of upstream transcription factors (TFs) and pathway analysis indicated that 21% of HRG-induced gene regulation may be controlled by the MAPK cascade, while only 0.6% of the gene expression is controlled by ERE. A comparison with previously reported estrogen (E2)-regulated gene expression data revealed that only 12 common genes were identified between the 333 HRG-regulated (3.6%) and 239 E2-regulated (5.0%) gene groups. However, with respect to enriched upstream TFs, 4 common TFs were identified in the 14 HRG-regulated (28.6%) and 13 E2-regulated (30.8%) gene groups. These results indicated that while E2 and HRG may induce common TFs, the regulatory mechanisms that govern HRG- and E2-induced gene expression differ. Keywords: growth hormone response
2008-02-08 | GSE8471 | GEO
Project description:Heregulin beta-1 (HRG) is an extracellular ligand that activates mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI3K)/Akt signaling pathways through ErbB receptors. MAPK and Akt have been shown to phosphorylate the estrogen receptor (ER) at Ser-118 and Ser-167, respectively, thereby mimicking the effects of estrogenic activity such as estrogen responsive element (ERE)-dependent transcription. In the current study, integrative analysis was performed using two tiling array platforms, comprising histone H3 lysine 9 (H3K9) acetylation and RNA mapping, together with array comparative genomic hybridization (CGH) analysis in an effort to identify HRG-regulated genes in ER-positive MCF-7 breast cancer cells. Through application of various threshold settings, 333 (326 up-regulated and 7 down-regulated) HRG-regulated genes were detected. Prediction of upstream transcription factors (TFs) and pathway analysis indicated that 21% of HRG-induced gene regulation may be controlled by the MAPK cascade, while only 0.6% of the gene expression is controlled by ERE. A comparison with previously reported estrogen (E2)-regulated gene expression data revealed that only 12 common genes were identified between the 333 HRG-regulated (3.6%) and 239 E2-regulated (5.0%) gene groups. However, with respect to enriched upstream TFs, 4 common TFs were identified in the 14 HRG-regulated (28.6%) and 13 E2-regulated (30.8%) gene groups. These results indicated that while E2 and HRG may induce common TFs, the regulatory mechanisms that govern HRG- and E2-induced gene expression differ. Keywords: time course, dose response, transcript mapping
2008-02-08 | GSE8578 | GEO
Project description:Heregulin beta-1 (HRG) is an extracellular ligand that activates mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI3K)/Akt signaling pathways through ErbB receptors. MAPK and Akt have been shown to phosphorylate the estrogen receptor (ER) at Ser-118 and Ser-167, respectively, thereby mimicking the effects of estrogenic activity such as estrogen responsive element (ERE)-dependent transcription. In the current study, integrative analysis was performed using two tiling array platforms, comprising histone H3 lysine 9 (H3K9) acetylation and RNA mapping, together with array comparative genomic hybridization (CGH) analysis in an effort to identify HRG-regulated genes in ER-positive MCF-7 breast cancer cells. Through application of various threshold settings, 333 (326 up-regulated and 7 down-regulated) HRG-regulated genes were detected. Prediction of upstream transcription factors (TFs) and pathway analysis indicated that 21% of HRG-induced gene regulation may be controlled by the MAPK cascade, while only 0.6% of the gene expression is controlled by ERE. A comparison with previously reported estrogen (E2)-regulated gene expression data revealed that only 12 common genes were identified between the 333 HRG-regulated (3.6%) and 239 E2-regulated (5.0%) gene groups. However, with respect to enriched upstream TFs, 4 common TFs were identified in the 14 HRG-regulated (28.6%) and 13 E2-regulated (30.8%) gene groups. These results indicated that while E2 and HRG may induce common TFs, the regulatory mechanisms that govern HRG- and E2-induced gene expression differ. Keywords: time course, dose response, ChIP-chip
2008-02-08 | GSE8577 | GEO
Project description:This model describes the activation of immediate early genes such as cFos after EGF or heregulin (HRG) stimulation of the MAPK pathway. Phosphorylated cFos is a key transcription factor triggering downstream cascades of cell fate determination. The model can explain how the switch-like response of p-cFos emerges from the spatiotemporal dynamics. The model comprises lumped reaction kinetics of the signal transduction pathway, the transcriptional and the posttranslational feedback and feedforward loops. The parameter set implemented here corresponds to that used for generating Figs. 4 B,C,D (red curves for 10nM HRG) of the below article in Cell (2010). Moreover, we found that the same model described well the dynamics in different cell types (MCF-7 and PC-12), of different ligands (EGF and HRG) and at different doses (0.1nM, 1nM, 10nM) for a unique set of parameter values (as implemented here and reported in Table SD4_1 of the article) except for four parameters characterising the input, cytoplasmic ppERK. These four parameters K1, K2, tau1 and tau2 are used in the two equations involving species x1 and x2. These two equations define a phenomenological input module to describe the ligand-, dose- and cell type-dependent dynamics of ppERKc which are not modelled in mechanistic detail here. The four parameter values can be adjusted to model a specific ligand, dose and cell type. 8 parameter sets for different experiments are given in Table SD4_2 of the article. This SBML file, however, carries just one such parameter set. We have chosen that of MCF-7 cells stimulated by 10nM of HRG. To reproduce all simulations from the article, please replace the parameter values for K1, K2, tau1, tau2 as needed.
Ligand-specific c-Fos expression emerges from the spatiotemporal control of ErbB network dynamics.
Takashi Nakakuki(1), Marc R. Birtwistle(2,3,4), Yuko Saeki(1,5), Noriko Yumoto(1,5), Kaori Ide(1), Takeshi Nagashima(1,5), Lutz Brusch(6), Babatunde A. Ogunnaike(3), Mariko Hatakeyama(1,5), and Boris N. Kholodenko(2,4); Cell In Press, online 20 May 2010, doi:10.1016/j.cell.2010.03.054
(1) RIKEN Advanced Science Institute, Computational Systems Biology Research Group, Advanced Computational Sciences Department, 1-7-22 Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
(2) Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland
(3) University of Delaware, Department of Chemical Engineering, 150 Academy St., Newark, DE 19716, USA
(4) Thomas Jefferson University, Department of Pathology, Anatomy, and Cell Biology, 1020 Locust Street, Philadelphia, PA 19107, USA
(5) RIKEN Research Center for Allergy and Immunology, Laboratory for Cellular Systems Modeling, 1-7-22 Tsurumi-ku, Yokohama, 230-0045, Japan
(6) Dresden University of Technology, Center for Information Services and High Performance Computing, 01062 Dresden, Germany
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2024-09-02 | BIOMD0000000251 | BioModels