Egr-1 Maintains NSC Proliferation and Its Overexpression Counteracts Cell Cycle Exit Triggered by the Withdrawal of Epidermal Growth Factor

2018 ◽  
Vol 40 (3) ◽  
pp. 223-233 ◽  
Author(s):  
Arcangela Anna Cera ◽  
Emanuele Cacci ◽  
Camilla Toselli ◽  
Silvia Cardarelli ◽  
Alessandra Bernardi ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Growth Factor ◽  
Target Genes ◽  
Kinase Inhibitors ◽  
Mammalian Brain ◽  
Cell Cycle Regulators ◽  
Egfr Signaling Pathway ◽  
Proliferation And Differentiation ◽  
Adult Nscs ◽  
Extracellular Stimuli

In adult mammals, neural stem cells (NSCs) reside in specialized niches at the level of selected CNS regions, such as the subventricular zone (SVZ). The signaling pathways that reg­ulate NSC proliferation and differentiation remain poorly understood. Early growth response protein 1 (Egr-1) is an important transcription factor, widely studied in the adult mammalian brain, mediating the activation of target genes by a variety of extracellular stimuli. In our study, we aimed at testing how Egr-1 regulates adult NSCs derived from mouse SVZ and, in particular, the interplay between Egr-1 and the proliferative factor EGF. We demonstrate that Egr-1 expression in NSCs is induced by growth factor stimulation, and its level decreases after EGF deprivation or by using AG1478, an inhibitor of the EGF/EGFR signaling pathway. We also show that Egr-1 overexpression rescues the cell proliferation decrease observed either after EGF removal or upon treatment with AG1478, suggesting that Egr-1 works downstream of the EGF pathway. To better understand this mechanism, we investigated targets downstream of both the EGF pathway and Egr-1, and found that they regulate genes involved in NSC proliferation, such as cell cycle regulators, cyclins, and cyclin-dependent kinase inhibitors.

scholarly journals Predicting cell-cycle expressed genes identifies canonical and non-canonical regulators of time-specific expression in Saccharomyces cerevisiae

2018 ◽  
Author(s):  
Nicholas L Panchy ◽  
John P. Lloyd ◽  
Shin-Han Shiu
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Cell Cycle ◽  
Target Genes ◽  
Specific Cell ◽  
Data Sets ◽  
Cell Cycle Regulators ◽  
Specific Expression ◽  
Regulatory Data ◽  
Time Specific ◽  
Cycle Regulation

AbstractThe collection all TFs, target genes and their interactions in an organism form a gene regulatory network (GRN), which underly complex patterns of transcription even in unicellular species. However, identifying which interactions regulate expression in a specific temporal context remains a challenging task. With multiple experimental and computational approaches to characterize GRNs, we predicted general and phase-specific cell-cycle expression in Saccharomyces cerevisiae using four regulatory data sets: chromatin immunoprecipitation (ChIP), TF deletion data (Deletion), protein binding microarrays (PBMs), and position weight matrices (PWMs). Our results indicate that the source of regulatory interaction information significantly impacts our ability to predict cell-cycle expression where the best model was constructed by combining selected TF features from ChIP and Deletion data as well as TF-TF interaction features in the form of feed-forward loops. The TFs that were the best predictors of cell-cycle expression were enriched for known cell-cycle regulators but also include regulators not implicated in cell-cycle regulation previously. In addition, ChIP and Deletion datasets led to the identification different subsets of TFs important for predicting cell-cycle expression. Finally, analysis of important TF-TF interaction features suggests that the GRN regulating cell cycle expression is highly interconnected and clustered around four groups of genes, two of which represent known cell-cycle regulatory complexes, while the other two contain TFs that are not known cell-cycle regulators (Ste12-Tex1 and Rap1-Hap1-Msn4), but are nonetheless important to regulating the timing of expression. Thus, not only do our models accurately reflect what is known about the regulation of the S. cerevisiae cell cycle, they can be used to discover regulatory factors which play a role in controlling expression during the cell cycle as well as other contexts with discrete temporal patterns of expression.

The Cdk and PCNA domains on p21Cip1 both function to inhibit G1/S progression during hyperoxia

2004 ◽  
Vol 286 (3) ◽  
pp. L506-L513 ◽  
Author(s):  
Christopher E. Helt ◽  
Rhonda J. Staversky ◽  
Yi-Jang Lee ◽  
Robert A. Bambara ◽  
Peter C. Keng ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Molecular Mechanisms ◽  
Kinase Inhibitors ◽  
Fluorescent Protein ◽  
Nuclear Antigen ◽  
Cell Cycle Regulators ◽  
Amino Terminal ◽  
Binding Domains ◽  
Green Fluorescent

This study investigates molecular mechanisms underlying cell cycle arrest when cells are exposed to high levels of oxygen (hyperoxia). Hyperoxia has previously been shown to increase expression of the cell cycle regulators p53 and p21. In the current study, we found that p53-deficient human lung adenocarcinoma H1299 cells failed to induce p21 or growth arrest in G1 when exposed to 95% oxygen. Instead, cells arrested in S and G2. Stable expression of p53 restored induction of p21 and G1 arrest without affecting mRNA expression of the other Cip or INK4 G1 kinase inhibitors. To confirm the role of p21 in G1 arrest, we created H1299 cells with tetracycline-inducible expression of enhanced green fluorescent protein (EGFP), EGFP fused to p21 (EGFp21), or EGFP fused to p27 (EGFp27), a related cell cycle inhibitor. The amino terminus of p21 and p27 bind cyclin-dependent kinases (Cdk), whereas the carboxy terminus of p21 binds the sliding clamp proliferating cell nuclear antigen (PCNA). EGFp21 or EGFp27, but not EGFP by itself, restored G1 arrest during hyperoxia. When separately overexpressed, the amino-terminal Cdk and carboxy-terminal PCNA binding domains of p21 each prevented cells from exiting G1 during exposure. These findings demonstrate that exposure in vitro to hyperoxia exerts G1 arrest through p53-dependent induction of p21 that suppresses Cdk and PCNA activity. Because PCNA also participates in DNA repair, these results raise the possibility that p21 also affects repair of oxidized DNA.

MicroRNA-155 Modulates Transforming Growth Factor-β Signaling In Chronic Lymphocytic Leukemia through Targeting of Casein Kinase γ Isoform 2

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3584-3584
Author(s):  
Jan K. Davidson-Moncada ◽  
Taotao Zhang ◽  
Piali Mukherjee ◽  
Paul Hakimpour ◽  
Richard R. Furman ◽  
...  
Keyword(s):  
Cell Cycle ◽  
B Cells ◽  
Growth Factor ◽  
Target Genes ◽  
Transforming Growth Factor ◽  
Signal Sequence ◽  
Transforming Growth Factor Β ◽  
Lymphocytic Leukemia ◽  
Mrna Levels ◽  
Tgfβ Signaling

Abstract Abstract 3584 Chronic lymphocytic leukemia (CLL) is typically characterized by defects in programmed cell death rather than alterations in cell cycle regulation. Transforming growth factor β (TGFβ), a ubiquitously expressed growth factor, regulates multiple normal cellular responses including proliferation, differentiation, migration and apoptosis. Loss of growth inhibition by TGFβ is thought to contribute to the development and progression of a variety of tumors including CLL (DeCoteau et al., PNAS 1997). Approximately 40% of patients contain mutations in the signal sequence of TGFβ receptor 1 (TBR-1) in the form of substitutions or deletions (Schiemann et al., Cancer Detect Prev 2004). In the wild type form, the signal sequence contains a nine alanine stretch, which if truncated has been shown to impair signaling through the receptor and specifically, a truncated, six alanine form is associated with increased cancer risk (Pasche et al., Cancer Res 1999). TGFβ signaling can regulate expression of micoRNAs (miRNA), which are ~22 nucleotide-long RNA gene regulators. Deregulated miRNA expression has been implicated in tumorigenesis, including CLL. Several miRNAs have been shown to be over-expressed in CLL as compared to normal B cells (Fulci et al., Blood 2007). This includes miR-155, which is part of a 13-miRNA signature that has prognostic implications, including a shorter need-for-treatment interval (Calin et al., N Engl J Med 2005). Interestingly, miR-155 has been shown to be upregulated by TGFβ in murine mammary gland cells (Kong et al., Mol Cell Biol 2008). The goals of our study are to investigate the link between TGFβ signaling and miR-155 in CLL and to determine how the interaction between the two may contribute to the pathogenesis of CLL. Here we show that miR-155 is in fact upregulated by TGFβ in mouse splenic B cells and in human peripheral blood B cells. In CLL, miR-155 expression inversely correlates with the proportion of CLL cells harboring signal sequence mutation in TBR-1, consistent with miR155 regulation by TGFβ in vivo. To understand the role of TGFβ-induced miR-155 in CLL pathobiology, identification of specific target genes in the context of this disease is essential. To this end, we compared the gene (cDNA) expression profile between CLL with high miR-155 vs. low miR-155 expression and identified putative miR-155 target genes by selecting those genes that are differentially expressed in SAM analysis with lower expression in the high miR-155 group, and which harbor predicted miR-155 binding sites in their 3’ untranslated region (UTR). Based on this algorithm, we have identified casein kinase 1 gamma 2 (CSK1γ2) as a target for miR155 in CLL. CSK1γ2 is a negative modulator of the TGFβ signaling pathway by targeting the phosphorylated form of SMAD3 for degradation (Guo et al., Oncogene 2008). MiR-155 represses luciferase reporter gene expression by specific binding to the miR-155 site in the CSK1γ2 3’UTR. In addition, we found that CSK1γ2 itself is upregulated in B cells upon TGFβ stimulation, and treatment of human B cells with PNA miR-155 inhibitor (Fabani et al., Nucleic Acids Research 2010) further increases CSK1γ2 mRNA levels. Surprisingly, comparison of CSK1γ2 protein levels between CLLs with high or low miR-155 by Western blotting revealed higher CSK1γ2 protein expression despite lower CSK1γ2 mRNA levels, suggesting that miR-155 may enhance CSK1γ2 translation in CLL cells and implying an intriguing regulatory interaction between miR-155 and CSK1γ2. In summary, our data indicates that the variation of miR-155 seen in CLL is primarily a function of TGFβ signaling activity. Moreover, miR-155 is an important player in a complex auto-regulatory network in TGFβ signaling by fine-tuning the negative feedback mechanism on TGFβ signaling mediated by CSK1γ2. In CLL cells harboring TBR-1 with wild-type signal sequence, higher miR-155 levels may help modulate the TGFβ signaling activity to a level optimal for the survival or other pathobiological functions of CLL. Furthermore, since CLL cells are predominantly non-proliferating, our findings that miR-155 may enhance translation of CSK1γ2 provide support to the model of cell cycle dependence of microRNA functions (Vasudevan et al., Cell Cycle 2008). Disclosures: No relevant conflicts of interest to declare.

scholarly journals Co-ordination of cell cycle and differentiation in the developing nervous system

2012 ◽  
Vol 444 (3) ◽  
pp. 375-382 ◽  
Author(s):  
Christopher Hindley ◽  
Anna Philpott
Keyword(s):  
Cell Cycle ◽  
Nervous System ◽  
Embryonic Development ◽  
Cell Fate ◽  
Cell Cycle Progression ◽  
Control Cell ◽  
Cell Cycle Regulators ◽  
Cyclin Dependent Kinases ◽  
Proliferation And Differentiation ◽  
Developing Nervous System

During embryonic development, cells must divide to produce appropriate numbers, but later must exit the cell cycle to allow differentiation. How these processes of proliferation and differentiation are co-ordinated during embryonic development has been poorly understood until recently. However, a number of studies have now given an insight into how the cell cycle machinery, including cyclins, CDKs (cyclin-dependent kinases), CDK inhibitors and other cell cycle regulators directly influence mechanisms that control cell fate and differentiation. Conversely, examples are emerging of transcriptional regulators that are better known for their role in driving the differentiated phenotype, which also play complementary roles in controlling cell cycle progression. The present review will summarise our current understanding of the mechanisms co-ordinating the cell cycle and differentiation in the developing nervous system, where these links have been, perhaps, most extensively studied.

Single Cell Network Profiling as a Platform to Reveal Leukemia-Specific Signaling Signatures and Sensitivity to Kinase Inhibitor Therapies

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2753-2753
Author(s):  
Todd M. Covey ◽  
Michael Gulrajani ◽  
Heiko Becker ◽  
Jason C. Chandler ◽  
Sebastian Schwind ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Clinical Trials ◽  
Growth Factor ◽  
Single Cell ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Employment Equity ◽  
Cell Network ◽  
Healthy Donors ◽  
Equity Ownership

Abstract Abstract 2753 Aberration in kinase activity by either the gain-of-function mutations or overexpression of the encoding genes plays a pivotal role in myeloid leukemogenesis. An increasing number of kinase inhibitors are being developed as “targeted therapies” for the treatment of acute myeloid leukemia (AML) and other myeloproliferative disorders. However, given the biologic and clinical heterogeneity inherent to these diseases, an unmet medical need exists for tools to guide the choice of inhibitor(s) most relevant for individual patients. With the aim of developing a platform for the biological characterization of patient-specific tumors, which could assist patient stratification strategies for clinical trials, we combined signaling pathway analysis and drug response profiling in AML samples using Single Cell Network Profiling (SCNP) assays. This technology allows for the simultaneous measurement of the activation state of multiple signaling proteins at the single cell level. Cryopreserved mononuclear cells from blood leukapheresis of patients with AML (N=6) were analyzed in two experimental arms. #1 Signaling Arm: A panel of kinase inhibitors targeting FLT3, cKit, PI3 kinase, mTor, MEK, and JAK proteins was added at varying concentrations to the AML cells followed by stimulation with G-CSF, IL-27, cKit ligand (SCF), FLT3 ligand (FLT3L), or a vehicle control. Using multiparameter flow cytometry, the phosphoylation status of AKT, ERK, S6 Ribosome, STAT1, STAT3, and STAT5 were measured in multiple leukemia cell subsets defined by expression of CD34, cKit, CD3, and light scatter properties. Per sample, there were a total of 68 treatments measuring 3 phospho-proteins in 3 cell subsets. #2 Apoptosis/Cytostasis Arm: The leukemic cells were driven into cell cycle by exposure to IL-3, SCF, and FLT3L, followed by a 48-hr incubation with a combination of 1 to 5 kinase inhibitors targeting the same pathways referred to previously. The kinase inhibitor impact was measured on distal functional readouts, including apoptosis (cleaved PARP) and cell cycle (CyclinB1-S/G2 phase; p-Histone H3-M phase). These results were compared with results using bone marrow samples from healthy donors (N=6). Results: Each patient's sample generated a unique signaling profile. A broad range of protein-specific phosphorylation status of AKT, ERK, S6 Ribosome, STAT1, STAT3, and STAT5 was observed in response to growth factor stimulation. Response was measured by setting a region gate that captures the overall percentage of cells with fluorescence above the unstimulated level. The percentage of SCF, G-CSF and FLT3L responsive cells ranged between 6%-49%, 3%-56%, and 3%-22%, respectively. Overall, patient samples could be grouped based on their signaling profile, proliferative potential, and sensitivity to kinase inhibitor treatment. Specifically, the 2 samples with the greatest SCF and G-CSF signaling response also showed the most robust in vitro proliferation and were most sensitive to the JAK inhibitor, CP-690,550 (1μM) (as measured by cytostasis readouts). Whereas, 2 other samples that displayed only modest SCF and G-CSF signaling, but robust FLT3L signaling expanded slowly in culture and were particularly sensitive to the cytostatic effects of the PI3K inhibitor, GDC-0941, (1uM) or the Flt3 inhibitor, tandutinib, (1uM). Finally, the last 2 AML samples had weak growth factor signaling and did not proliferate in culture and therefore could not be tested for kinase inhibitor-induced cytostasis. While the successfully tested patient samples showed variable sensitivity (as measured by cytostasis and apoptosis) to different drug combinations, the samples from healthy donors showed considerable similarity in response across all inhibitor combinations. Conclusions: This study provides preliminary proof-of-concept on the utility of SCNP to dissect the pathophysiologic heterogeneity of hematologic tumors and assess their differential response to single and combination therapies. Ultimately, this functional pathway profiling and drug sensitivity assay may be useful to stratify patients to different kinase combination treatments tested in clinical trials. Disclosures: Covey: Nodality Inc.: Employment, Equity Ownership. Gulrajani:Nodality Inc.: Employment, Equity Ownership. Cesano:Nodality Inc.: Employment, Equity Ownership.

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