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The molecular basis of the cooperation between EGF, FGF and eCB receptors in the regulation of neural stem cell function.

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pm2The molecular basis of the cooperation between EGF, FGF and eCB receptors in the regulation of neural stem cell function.

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The Wolfson Centre for Age-Related Diseases, King’s College London, London SE1 9RT, UK.

Abstract

Adult neurogenesis relies on EGF and FGF receptor (EGFR/FGFR) function and endocannabinoid (eCB) signalling. Here we have used a neural stem cell (NSC) line to determine how these systems cooperate to regulate neurogenesis. The results show the EGFR to be solely responsible for maintaining PI3K activation explaining its dominant role in promoting NSC survival. The EGFR and FGFR synergistically regulate the ERK/MAPK pathway, and this explains the requirement for both for optimal cell proliferation. The eCB receptors did not contribute to activation of the PI3K or ERK/MAPK pathways, highlighting the importance of another major proliferation pathway. The EGFR plays the dominant role in maintaining the transcriptome, with significant changes in the expression of over 3500 transcripts seen within hours of inhibition or activation of this receptor. The FGFR has a more modest effect on transcription with evidence for nodal integration with EGFR signalling at the level of the ERK/MAPK pathway. A common set of transcripts are regulated by the CB1 and CB2 receptors, with cooperation between these receptors and the EGFR apparent in the regulation of a pool of transcripts, most likely representing signal integration downstream from an as yet to be identified node. Finally, a first level molecular analysis of the transcriptional response shows regulation of a number of key growth factors, growth factor receptors and GPCRs to be under the control of the EGFR.
Copyright © 2012 Elsevier Inc. All rights reserved.
PMID:

 23085403
[PubMed – indexed for MEDLINE]

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Fig. 1. Differential control of basal activity in the three canonical signalling pathways by the EGFR, FGFR and the eCB receptors. Cor-1 cells were grown in 6-well cell culture plates until near-confluent and then treated for up to 4 h with AG1478 at 100 nM (A), PD173074 at 500 nM (B), AM251 at 1 μM (C) or JTE907 at 1 μM (D). Total protein was harvested at the indicated times following drug application and the phosphorylation status of PLCγ, Akt and ERK1/2 determined by western blotting using phospho-specific antibodies. Total levels of Actin were also determined to serve as a control for protein loading. The results show a representative blot for each treatment.
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Fig. 2. Differential control of basal activity in the three canonical signalling pathways by the EGFR, FGFR and the cannabinoid receptors. Cor-1 cells were treated as in Fig. 1, with the blots scanned to quantitate the relative level of phosphorylation of Akt (A), PLCγ (B) or ERK1/2 (C) in drug treated (as indicated) relative to control cultures. Each data point represents at least three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001.
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Fig. 3. Volcano plots of the transcriptional responses to EGF, FGF and cannabinoid receptor antagonism. Volcano plots are scatter plots of the log2 fold change against the negative log2 probability calculated by Student’s t-test. The points in red correspond to those probe sets passing the p < 0.05 significance and 10% fold change thresholds. EGFR antagonism clearly elicits the biggest response (A), with 6904 probe sets passing the p < 0.05 threshold and 6828 of these having a greater than 10% fold change. The other antagonists have much smaller response magnitudes, with the FGFR inhibition resulting in 1077 probe sets passing the p < 0.05 threshold and 887 of these having a greater than 10% fold change (B). Inhibiting CB1 (C) and CB2 (D) receptors results in similar response profiles, with 1168/833 probes passing the p < 0.05 threshold and 991/666 of these having a greater than 10% fold change.
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Fig. 4. Pathway enrichment analysis for the EGFR, FGFR and eCB receptor inhibition transcription profiles. Sets of genes whose expression was significantly altered by receptor inhibition were scored for enrichment against the GSEA MSigDB pathway gene sets. Responder sets were taken to consist of transcripts with significant (p < 0.05) expression changes of more than 10%. Enrichment significance was defined as the probability of obtaining the same or better enrichment score with a random set of genes. The first few pathways are shown ranked according to the number of responder genes. EGFR antagonism modulates the largest set of pathways. Nearly all the pathways perturbed by FGFR antagonism are also perturbed by EGFR antagonism. There is no overlap in modulated pathways between eCB receptor antagonism and FGFR antagonism. However, more than half of the pathways perturbed by eCB receptor blockage are also perturbed by EGFR inhibition. N represents the number of genes that are associated with any given pathway, and n stands for the number of these whose expression is perturbed by any given treatment.
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Fig. 5. Global analysis of EGFR, FGFR and MAPK signalling by microarray profiling. Cor-1 cells were grown in 6-well cell culture plates until near-confluent and then treated for 4 h with various inhibitors and the microarray expression profiles compared. In each case significant fold changes (p < 0.05 by Student’s t-test) for one profile (x-axis) were plotted against the total response set for the other profile (y-axis) and a regression analysis performed. The transcriptional profiles resultant upon inhibition of CB1 and CB2 receptors are very well correlated, with a regression rvalue of 0.82 (p < 10− 337) between the pooled CB1 (AM251 and LY320135, both at 1 μM) and CB2 (AM630 and JTE907, both at 1 μM) responses (A). The pooled EGFR inhibitor (AG1478 and PD168393, both at 100 nM) transcriptional response shows a high degree of correlation with the FGFR inhibition (PD173074 at 500 nM) response (B), with r = 0.78 (p < 10− 247). In (C) the regression analysis between the MAPK inhibition (PD98059 20 μM) response set and the pooled EGFR response set is shown. In (D) the regression analysis between the FGFR response set and the MAPK response set is shown. The Pearson co-efficient r and statistical significance are indicated for each analysis.
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Fig. 6. The transcriptional response of EGF treated starved NSCs anti-correlates with EGFR antagonism of non-starved NSCs and eCB receptor inhibition has no effect on the EGF response of starved NSCs. The analysis is as presented in Fig. 5 except for the starved cells where EGF and FGF were withdrawn from Cor-1 cultures for 3 h and then treated with EGF (10 ng/ml) for a 3 h period. The transcriptional profiles for EGFR inhibitor (AG1478 at 100 nM) treatment of non-starved Cor-1 cells anti-correlates with the response of EGF-treated starved Cor-1 cells (A). In NSCs the eCB signalling pathway appears to be disconnected with the EGF pathway as inhibiting both CB1 and CB2 receptors (AM251 and AM630 both at 1 μM) has no effect on the EGF transcriptional response on the starved Cor-1 cells (B).
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Fig. 7. Validation of microarray responders by Taqman qPCR. Cor-1 cells were grown in 6-well cell culture plates until near-confluent, then starved in control media for 4 h and finally treated for a further 4 h with either EGF alone (10 ng/ml) or EGF together with the eCB receptor antagonists AM251 and AM630 (both at 1 μM). RNA was then harvested and qPCR performed as described in the Experimental methods. Treatment with EGF leads to a substantial increase in expression of all three genes investigated and co-application of eCB antagonists had no significant impact on this effect (for FGF1 combined treatments p < 0.001, for VEGFα combined p < 0.03, but no significance for the IL2Rb expression change). The data shown represent the mean for each target averaged from three independent samples and normalized against the expression levels of the housekeeping gene β-actin.
Table 1. Global analysis of eCB signalling by microarray profiling. Cor-1 cells were grown in 6-well cell culture plates until near-confluent and then treated for 4 h with the two CB1 or two CB2 antagonists (all at 1 μM, as indicated). RNA was then harvested with microarrays performed as described in the Experimental methods. The data for all four drugs were pooled to identify probe sets that were significantly (p < 0.05) altered by treatment with a cannabinoid receptor antagonist. We next determined to what extent these transcripts were also regulated by the EGFR (using data pooled from the two inhibitors), the FGFR or the MAPK pathway by determining the Pearson co-efficient r and statistical significance of the regression analysis as indicated. We also removed probes that were regulated by the MAPK pathway from the EGFR (EGFR-MAPK) and FGFR (FGFR-MAPK) response sets to determine if this impacted on the correlation.
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Table 2. The effect of EGFR inhibition (AG1478) on the expression levels of G protein coupled receptors (GPCRs), protein kinase (PK) receptors and growth factors. Probes are listed for which AG1478 treatment results in a significant fold change (Student’s t-test p < 0.05) of more than 50%. 14 probes, corresponding to 11 distinct GPCRs, significantly regulated by AG1478 are listed in (A). Four of these GPCRs are also regulated by FGFR inhibition (PD173074) with only one regulated by the pooled eCB antagonist treatments. The probes corresponding to regulated PK receptors are listed in (B). In total three PK receptor genes corresponding to seven probe sets are regulated. EGFR is also up-regulated under FGFR inhibition. The growth factor response is shown in (C). There are nine probes with significant fold changes corresponding to seven distinct genes. INHBB is also regulated by FGFR inhibition, but there is no overlap with eCB antagonism. Changes in expression that fall below the significance cut-off (p < 0.05) are marked ‘ns’.
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Corresponding author contact information
Corresponding author at: The Wolfson Centre for Age-Related Diseases, King’s College London, Wolfson Wing Hodgkin Building, London SE1, UK 9RT. Fax: + 44 207 848 6816.
Copyright © 2012 Elsevier Inc. All rights reserved.

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