scholarly journals Continued withdrawal from the cell cycle and regulation of cellular genes in mouse erythroleukemia cells blocked in differentiation by the c-myc oncogene.

1989 ◽  
Vol 9 (4) ◽  
pp. 1714-1720 ◽  
Author(s):  
J A Coppola ◽  
J M Parker ◽  
G D Schuler ◽  
M D Cole
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cell Cycle Control ◽  
Regulation Of Gene Expression ◽  
Constitutive Expression ◽  
Housekeeping Genes ◽  
Cell System ◽  
Myc Oncogene ◽  
Temporary Decrease ◽  
Mouse Erythroleukemia

Constitutive expression of the c-myc oncogene blocks dimethyl sulfoxide (DMSO)-induced differentiation of mouse erythroleukemia (MEL) cells. During the first 12 h of treatment with DMSO, MEL cells undergo a temporary decrease in the level of c-myc mRNA, followed by a temporary withdrawal from the cell cycle. We found the same shutoff of DNA synthesis during the first 12 to 30 h after DMSO induction in normal MEL cells (which differentiate) and in c-myc-transfected MEL cells (which do not differentiate). We also examined whether deregulated c-myc expression grossly interfered with the regulation of gene expression during MEL cell differentiation. We used run-on transcription assays to monitor the rate of transcription of four oncogenes (c-myc, c-myb, c-fos, and c-K-ras); all except c-K-ras showed a rapid but temporary decrease in transcription after induction in both c-myc-transfected and control cells. Finally, we found the same regulation of cytoplasmic mRNA expression in both types of cells for four oncogenes and three housekeeping genes associated with growth. We conclude that in the MEL cell system, the effects of deregulated c-myc expression do not occur through a disruption of cell cycle control early in induction, nor do they occur through gross deregulation of gene expression.

Continued withdrawal from the cell cycle and regulation of cellular genes in mouse erythroleukemia cells blocked in differentiation by the c-myc oncogene

1989 ◽  
Vol 9 (4) ◽  
pp. 1714-1720
Author(s):  
J A Coppola ◽  
J M Parker ◽  
G D Schuler ◽  
M D Cole
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cell Cycle Control ◽  
Regulation Of Gene Expression ◽  
Constitutive Expression ◽  
Housekeeping Genes ◽  
Cell System ◽  
Myc Oncogene ◽  
Temporary Decrease ◽  
Mouse Erythroleukemia

Constitutive expression of the c-myc oncogene blocks dimethyl sulfoxide (DMSO)-induced differentiation of mouse erythroleukemia (MEL) cells. During the first 12 h of treatment with DMSO, MEL cells undergo a temporary decrease in the level of c-myc mRNA, followed by a temporary withdrawal from the cell cycle. We found the same shutoff of DNA synthesis during the first 12 to 30 h after DMSO induction in normal MEL cells (which differentiate) and in c-myc-transfected MEL cells (which do not differentiate). We also examined whether deregulated c-myc expression grossly interfered with the regulation of gene expression during MEL cell differentiation. We used run-on transcription assays to monitor the rate of transcription of four oncogenes (c-myc, c-myb, c-fos, and c-K-ras); all except c-K-ras showed a rapid but temporary decrease in transcription after induction in both c-myc-transfected and control cells. Finally, we found the same regulation of cytoplasmic mRNA expression in both types of cells for four oncogenes and three housekeeping genes associated with growth. We conclude that in the MEL cell system, the effects of deregulated c-myc expression do not occur through a disruption of cell cycle control early in induction, nor do they occur through gross deregulation of gene expression.

scholarly journals STAU2 protein level is controlled by caspases and the CHK1 pathway and regulates cell cycle progression in the non-transformed hTERT-RPE1 cells

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lionel Condé ◽  
Yulemi Gonzalez Quesada ◽  
Florence Bonnet-Magnaval ◽  
Rémy Beaujois ◽  
Luc DesGroseillers
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Dna Damage ◽  
Steady State ◽  
Posttranscriptional Regulation ◽  
Cell Cycle Progression ◽  
Rna Binding ◽  
Regulation Of Gene Expression ◽  
Cycle Progression

AbstractBackgroundStaufen2 (STAU2) is an RNA binding protein involved in the posttranscriptional regulation of gene expression. In neurons, STAU2 is required to maintain the balance between differentiation and proliferation of neural stem cells through asymmetric cell division. However, the importance of controlling STAU2 expression for cell cycle progression is not clear in non-neuronal dividing cells. We recently showed that STAU2 transcription is inhibited in response to DNA-damage due to E2F1 displacement from theSTAU2gene promoter. We now study the regulation of STAU2 steady-state levels in unstressed cells and its consequence for cell proliferation.ResultsCRISPR/Cas9-mediated and RNAi-dependent STAU2 depletion in the non-transformed hTERT-RPE1 cells both facilitate cell proliferation suggesting that STAU2 expression influences pathway(s) linked to cell cycle controls. Such effects are not observed in the CRISPR STAU2-KO cancer HCT116 cells nor in the STAU2-RNAi-depleted HeLa cells. Interestingly, a physiological decrease in the steady-state level of STAU2 is controlled by caspases. This effect of peptidases is counterbalanced by the activity of the CHK1 pathway suggesting that STAU2 partial degradation/stabilization fines tune cell cycle progression in unstressed cells. A large-scale proteomic analysis using STAU2/biotinylase fusion protein identifies known STAU2 interactors involved in RNA translation, localization, splicing, or decay confirming the role of STAU2 in the posttranscriptional regulation of gene expression. In addition, several proteins found in the nucleolus, including proteins of the ribosome biogenesis pathway and of the DNA damage response, are found in close proximity to STAU2. Strikingly, many of these proteins are linked to the kinase CHK1 pathway, reinforcing the link between STAU2 functions and the CHK1 pathway. Indeed, inhibition of the CHK1 pathway for 4 h dissociates STAU2 from proteins involved in translation and RNA metabolism.ConclusionsThese results indicate that STAU2 is involved in pathway(s) that control(s) cell proliferation, likely via mechanisms of posttranscriptional regulation, ribonucleoprotein complex assembly, genome integrity and/or checkpoint controls. The mechanism by which STAU2 regulates cell growth likely involves caspases and the kinase CHK1 pathway.

Retinoblastoma Protein, Gene Expression, and Cell Cycle Control

Cancer Genes ◽  
1996 ◽  
pp. 177-191
Author(s):  
Jane Clifford Azizkhan ◽  
Shiaw Yih Lin ◽  
David Jensen ◽  
Dusan Kostic ◽  
Adrian R. Black
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Protein Gene ◽  
Cell Cycle Control ◽  
Retinoblastoma Protein

scholarly journals Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

2019 ◽  
Vol 116 (39) ◽  
pp. 19490-19499 ◽  
Author(s):  
Chenglong Xia ◽  
Jean Fan ◽  
George Emanuel ◽  
Junjie Hao ◽  
Xiaowei Zhuang
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Spatial Information ◽  
Detection Efficiency ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Rna Profiling ◽  
Spatially Resolved ◽  
Cycle Dependent

The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

Gene expression profiling of multiple myeloma reveals molecular portraits in relation to the pathogenesis of the disease

Blood ◽  
2003 ◽  
Vol 101 (12) ◽  
pp. 4998-5006 ◽  
Author(s):  
Florence Magrangeas ◽  
Valéry Nasser ◽  
Hervé Avet-Loiseau ◽  
Béatrice Loriod ◽  
Olivier Decaux ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Multiple Myeloma ◽  
Immune Response ◽  
Light Chain ◽  
Dna Microarrays ◽  
Chromosomal Abnormalities ◽  
Expression Profiles ◽  
Cell Cycle Control ◽  
Primary Tumors

AbstractAlthough multiple myeloma (MM) is a unique entity, a marked heterogeneity is actually observed among the patients, which has been first related to immunoglobulin (Ig) types and light chain subtypes and more recently to chromosomal abnormalities. To further investigate this genetic heterogeneity, we analyzed gene expression profiles of 92 primary tumors according to their Ig types and light chain subtypes with DNA microarrays. Several clusters of genes involved in various biologic functions such as immune response, cell cycle control, signaling, apoptosis, cell adhesion, and structure significantly discriminated IgA- from IgG-MM. Genes associated with inhibition of differentiation and apoptosis induction were up-regulated while genes associated with immune response, cell cycle control, and apoptosis were down-regulated in IgA-MM. According to the expression of the 61 most discriminating genes, BJ-MM represented a separate subgroup that did not express either the genes characteristic of IgG-MM or those of IgA-MM at a high level. This suggests that transcriptional programs associated to the switch could be maintained up to plasma cell differentiation. Several genes whose products are known to stimulate bone remodeling discriminate between κ- and λ-MM. One of these genes, Mip-1α, was overexpressed in the κ subgroup. In addition, we established a strong association (P = .0001) between κ subgroup expressing high levels of Mip-1α and active myeloma bone disease. This study shows that DNA microarrays enable us to perform a molecular dissection of the bioclinical diversity of MM and provide new molecular tools to investigate the pathogenesis of malignant plasma cells.

Inhibition of the Epigenetic Modifier EZH2 Upregulates Cell Cycle Control Genes to Inhibit Myeloma Cell Growth and Overcome High-Risk Disease Features

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3289-3289 ◽  
Author(s):  
Charlotte Pawlyn ◽  
Michael Bright ◽  
Amy Buros ◽  
Caleb K. Stein ◽  
Zoe Walters ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
High Risk ◽  
Cell Lines ◽  
Research Funding ◽  
Cell Cycle Control ◽  
Myeloma Cell ◽  
Expression Arrays ◽  
Molecular Features ◽  
High Risk Disease

Abstract Introduction High expression of the H3K27 histone methyltransferase EZH2 mRNA in myeloma (MM) patient samples is associated with molecular features of high risk disease, including increased proliferation, and adverse outcomes (1). Mutations or deletions in the H3K27 demethylase KDM6A are associated with similar findings (2) and would be expected to have the same epigenetic effect, increasing H3K27me3 levels, a mark associated with repression of gene expression. We, therefore, sought to identify the role EZH2 plays in controlling myeloma cell proliferation. Methods A panel of MM cell lines and primary patient samples (CD138 selected from bone marrow with consent) representing a variety of different MM molecular subgroups were used. Cell viability (WST-1), cell cycle (PI) and apoptosis (AnnexinV/PI, Caspase-Glo 3/7) assays were performed. Affymetrix gene expression arrays followed by validation with RT-PCR were used to identify patterns of gene expression change with EZH2i. Western blotting confirmed changes at the protein level and Chip-PCR was performed using a validated antibody and isotype control to identify H3K27me3 changes at the relevant gene promotors. Affymetrix gene expression data for 1213 patients enrolled in the Total Therapy studies were used to investigate the relevance of our findings in myeloma patient samples. Results We confirmed a reduction in viability following EZH2i using two chemically distinct, specific small molecule inhibitors (EPZ005687 and UNC1999) and the negative control compound UNC2400. There was a reduction in viability in 6/8 cell lines and 5/6 patient samples. Response to inhibition was not related to molecular subgroup or the presence of high-risk molecular features including del17p. Global levels of H3K27me3 measured by Western blot were reduced in all cell lines regardless of response to EZH2i. In responding cell lines EZH2i induced cell cycle arrest at G1/S followed by induction of apoptosis. Gene expression arrays performed using mRNA from KMS11 and KMM1 cell lines highlighted a change in expression of cell cycle control genes associated with EZH2i. This finding was validated using qRT-PCR, which demonstrated upregulation of the cyclin dependent kinase inhibitors CDKN2B, CDKN1A or both. These findings were confirmed at the protein level by Western blotting. Chip-PCR experiment using cell lysates from KMS11 cells following incubation with EZH2i over 6 days identified changes in H3K27me3 at the promoter and transcriptional start site (PROM/TSS) regions of the CDKN2B and CDKN1A genes. The most specific changes occurred at the CDKN1A PROM/TSS, which were more heavily marked with H3K27me3 at baseline compared to a region approx. 5KB upstream. Given these results, which suggest that CDKN1A expression may be controlled by changes in H3K27me3, we explored the effect of CDKN1A mRNA expression in our patient datasets. We found the expression of EZH2 and CDKN1A to be inversely correlated (R=-0.170, p<0.0001) and that low expression of CDKN1A was associated with a significantly shorter progression free and overall survival (p<0.001). In order to confirm whether these gene expression changes could be used as a potential biomarker of response we looked at our panel of cell lines with variable responses to EZH2i. We identified a consistent increase in expression of CDKN1A only in responding cell lines suggesting it could be used as a biomarker of efficacy in the clinic. Conclusions These data support the hypothesis that CDKN1A expression is suppressed by increased H3K27me3, due to high expression of EZH2 and that this can be reversed with pharmacological EZH2 inhibition leading to a reduction in proliferation of myeloma cells. We provide data which supports the investigation of EZH2i in clinical trials of myeloma patients, which has the potential to be an effective therapeutic strategy even for those with high-risk disease, for whom current treatment approaches are ineffective.Pawlyn et al, EZH2 Overexpression in Myeloma Patients Shortens Survival and in-vitro Data Supports a Potential New Targeted Treatment Strategy. AACR and IMW abstracts, 2015Pawlyn et al, The Spectrum and Clinical Impact of Epigenetic Modifier Mutations in Myeloma. Clinical Cancer Research, 2016 Disclosures Pawlyn: Celgene: Consultancy, Honoraria, Other: Travel Support; Takeda Oncology: Consultancy. Kaiser:Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; BMS: Consultancy, Other: Travel Support; Takeda: Consultancy, Other: Travel Support; Chugai: Consultancy. Jones:Celgene: Honoraria, Research Funding. Jackson:Amgen: Consultancy, Honoraria, Speakers Bureau; Roche: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau. Bergsagel:Novartis: Research Funding; Amgen, BMS, Novartis, Incyte: Consultancy. Morgan:Univ of AR for Medical Sciences: Employment; Janssen: Research Funding; Bristol Meyers: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Davies:Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.

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