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16 pages, 11712 KiB  
Article
Oxymatrine Ameliorates Lupus Nephritis by Targeting the YY1-Mediated IL-6/STAT3 Axis
by Haoxing Yuan, Zheng Peng, Honglian Li, Yuzhen Rao, Kunyu Lu, Chan Yang, Chen Cheng and Shuwen Liu
Int. J. Mol. Sci. 2024, 25(22), 12260; https://doi.org/10.3390/ijms252212260 - 14 Nov 2024
Viewed by 866
Abstract
Lupus nephritis (LN) is a severe form of systemic lupus erythematosus (SLE), characterized by inflammation in the renal glomeruli and tubules. Previous research has demonstrated that dihydroartemisinin (DHA) can reduce inflammatory damage in LN mouse models. Oxymatrine, which has similar biological properties to [...] Read more.
Lupus nephritis (LN) is a severe form of systemic lupus erythematosus (SLE), characterized by inflammation in the renal glomeruli and tubules. Previous research has demonstrated that dihydroartemisinin (DHA) can reduce inflammatory damage in LN mouse models. Oxymatrine, which has similar biological properties to DHA, may also provide therapeutic benefits. This study aims to investigate the effects of oxymatrine on LN using a murine model and examines its molecular mechanisms through an analysis of microarray datasets from LN patients. The analysis identified differentially expressed genes (DEGs) in renal tissues, regulated by the transcription factor Yin Yang 1 (YY1), which was found to be significantly upregulated in LN patient kidneys. The results indicate that oxymatrine targets the YY1/IL-6/STAT3 signaling pathway. In cell models simulating renal inflammation, oxymatrine reduced YY1 expression and inhibited the secretion of inflammatory factors (IFs), thereby diminishing inflammation. YY1 is crucial in modulating IFs’ secretion and contributing to LN pathogenesis. Additionally, oxymatrine’s interaction with YY1, leading to its downregulation, appears to be a key mechanism in alleviating LN symptoms. These findings support oxymatrine as a promising therapeutic agent for LN, offering new avenues for treating this autoimmune kidney disorder. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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Figure 1
<p>Oxymatrine alleviates splenomegaly, proteinuria, and inflammation in mice with lupus nephritis (LN). (<b>A</b>) Schematic representation of the mouse study design. (<b>B</b>) Representative images of spleens from the mice. (<b>C</b>) Weight of the mice. (<b>D</b>) Spleen weight index (total spleen weight/body weight) of the mice. (<b>E</b>) 24 h proteinuria levels in the mice. (<b>F</b>) Proportion of T lymphocyte cells. (<b>G</b>) Levels of dsDNA in the serum of the mice. (<b>H</b>) Levels of IL-6, IL-1β, and TNF-α in the serum of the mice. Each bar represents the mean ± SEM. ns, no significance, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; one-way ANOVA was used to compare multiple groups.</p>
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<p>Oxymatrine improved the nephritis in mice with LN. (<b>A</b>) Serum levels of S-cr in mice. (<b>B</b>) Serum levels of BUN in mice. (<b>C</b>) Hematoxylin and eosin staining of kidney sections from the indicated groups. Scale bar = 20 μm. (<b>D</b>) Periodic Acid-Schiff staining of kidney sections from the indicated groups. Scale bar = 20 μm. (<b>E</b>) Immunoglobulin G (IgG) staining of kidney sections from the indicated groups. Scale bar = 10 μm. (<b>F</b>) Component 3 (C3) staining of kidney sections from the indicated groups. Scale bar = 10 μm. (<b>G</b>) Staining of IL-6, IL-1β, and TNF-α in kidney sections from the indicated groups. Scale bar = 20 μm. Black arrowheads indicate immune complexes, and red boxes indicate C3. Each bar represents the mean ± SEM. ns, no significance, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; one-way ANOVA was used to compare multiple groups.</p>
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<p>Oxymatrine modulates the YY1/IL-6/STAT3 pathway to alleviate inflammation in LN. (<b>A</b>) Volcano plots displaying differentially expressed genes (DEGs) in LN versus control (<span class="html-italic">n</span> = 28,439). (<b>B</b>) TRRUST analysis of DEGs from panel A. (<b>C</b>) GSEA of IL-6 Jak STAT3 signaling pathway. FDR, false discovery rate; NES, normalized enrichment score. (<b>D</b>) Relative protein levels of Yin Yang 1 (YY1) in the kidneys of LN patients assessed by IHC. Scale bar = 20 μm. (<b>E</b>,<b>F</b>) Western blot analysis of YY1 levels in the kidneys of wild-type mice and from MRL/lpr mice. The signal densities of YY1 were normalized to that of β-actin. (<b>G</b>) Quantitative real-time PCR (qRT–PCR) analysis of YY1 mRNA levels in the kidneys of wild-type mice and from MRL/lpr mice. (<b>H</b>) Western blot analysis of YY1 levels and phosphorylation levels of Stat3 in the kidneys of mice. The signal densities of YY1 were normalized to that of β-actin. Each bar represents the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; <span class="html-italic">t</span>-test and one-way ANOVA were employed to compare multiple groups.</p>
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<p>Oxymatrine inhibited the expression of YY1 and the secretion of inflammatory factors. (<b>A</b>) Western blot analysis of YY1 levels following the administration of lipopolysaccharide (LPS) and oxymatrine in HK-2 cells. The signal densities of YY1 were normalized to that of β-actin. (<b>B</b>) Western blot analysis of YY1 levels after the administration of LPS and oxymatrine in HMC cells. The signal densities of YY1 were normalized to that of β-actin. (<b>C</b>) The levels of IL-6, IL-1β, and TNF-α in the culture medium of THP-1 cells. (<b>D</b>) The levels of IL-6, IL-1β, and TNF-α in the culture medium of HK-2 and HMC cells. (<b>E</b>) The levels of IL-6, IL-1β, and TNF-α in the culture medium of HK-2, HMC, and THP-1 cells. Each bar represents the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; one-way ANOVA was used to compare multiple groups.</p>
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<p>YY1 promotes inflammatory factor secretion in LN. (<b>A</b>) Western blot analysis of YY1 levels following the administration of LPS in HK-2 cells. The signal densities of YY1 were normalized to that of β-actin. (<b>B</b>) Western blot analysis of YY1 levels following the administration of LPS in HMC cells. The signal densities of YY1 were normalized to that of β-actin. (<b>C</b>) The relative activity of IL-6, IL-1β, and TNF-α in HK-2 cells was measured by luciferase assay. (<b>D</b>) The relative activity of IL-6, IL-1β, and TNF-α in HMC cells was measured by luciferase assay. (<b>E</b>) The levels of IL-6, IL-1β, and TNF-α in the culture medium of HK-2 cells after YY1 overexpression. (<b>F</b>) The levels of IL-6, IL-1β, and TNF-α in the culture medium of HMC cells after YY1 overexpression. (<b>G</b>) Western blot analysis of YY1 levels following YY1 knockdown in HK-2 cells. The signal densities of YY1 were normalized to that of β-actin. (<b>H</b>) Western blot analysis of YY1 levels following YY1 knockdown in HMC cells. The signal densities of YY1 were normalized to that of β-actin. (<b>I</b>) Cell colony formation assays of HK-2 and HMC cells after YY1 knockdown. (<b>J</b>) The levels of IL-6, IL-1β, and TNF-α in the culture medium of HK-2 cells after YY1 knockdown. (<b>K</b>) The levels of IL-6, IL-1β, and TNF-α in the culture medium of HMC cells after YY1 knockdown. Each bar represents the mean ± SEM. ns, no significance, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; <span class="html-italic">t</span>-test and one-way ANOVA were used to compare multiple groups.</p>
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<p>The effect of oxymatrine on LN is attributed to the inhibition of YY1. (<b>A</b>) Chemical structure of oxymatrine. (<b>B</b>) Homology modeling of YY1. (<b>C</b>) Ramachandran plots were utilized to evaluate the YY1 model. (<b>D</b>) Representative images illustrating the binding mode of oxymatrine and YY1. (<b>E</b>) Sensorgrams of oxymatrine in the SPR assay at various concentrations. (<b>F</b>) Levels of IL-6, IL-1β, and TNF-α in the culture medium of HK-2 cells following YY1 knockdown. (<b>G</b>) Levels of IL-6, IL-1β, and TNF-α in the culture medium of HMC cells following YY1 knockdown. (<b>H</b>) Levels of IL-6, IL-1β, and TNF-α in the culture medium of HK-2 cells after YY1 overexpression. (<b>I</b>) Levels of IL-6, IL-1β, and TNF-α in the culture medium of HMC cells after YY1 overexpression. Each bar represents the mean ± SEM. ns, no significance, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; one-way ANOVA was used to compare multiple groups.</p>
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14 pages, 1784 KiB  
Article
The Role of PTEN in Chemoresistance Mediated by the HIF-1α/YY1 Axis in Pediatric Acute Lymphoblastic Leukemia
by Gabriela Antonio-Andres, Mario Morales-Martinez, Elva Jimenez-Hernandez and Sara Huerta-Yepez
Int. J. Mol. Sci. 2024, 25(14), 7767; https://doi.org/10.3390/ijms25147767 - 16 Jul 2024
Viewed by 1049
Abstract
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Current chemotherapy treatment regimens have improved survival rates to approximately 80%; however, resistance development remains the primary cause of treatment failure, affecting around 20% of cases. Some studies indicate that loss of the [...] Read more.
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Current chemotherapy treatment regimens have improved survival rates to approximately 80%; however, resistance development remains the primary cause of treatment failure, affecting around 20% of cases. Some studies indicate that loss of the phosphatase and tensin homolog (PTEN) leads to deregulation of the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway, increasing the expression of proteins involved in chemoresistance. PTEN loss results in deregulation of the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and induces hypoxia-inducible factor 1-alpha (HIF-1α) expression in various cancers. Additionally, it triggers upregulation of the Yin Yang 1 (YY1) transcription factor, leading to chemoresistance mediated by glycoprotein p-170 (Gp-170). The aim of this study was to investigate the role of the PTEN/NF-κB axis in YY1 regulation via HIF-1α and its involvement in ALL. A PTEN inhibitor was administered in RS4;11 cells, followed by the evaluation of PTEN, NF-κB, HIF-1α, YY1, and Gp-170 expression, along with chemoresistance assessment. PTEN, HIF-1α, and YY1 expression levels were assessed in the peripheral blood mononuclear cells (PBMC) from pediatric ALL patients. The results reveal that the inhibition of PTEN activity significantly increases the expression of pAkt and NF-κB, which is consistent with the increase in the expression of HIF-1α and YY1 in RS4;11 cells. In turn, this inhibition increases the expression of the glycoprotein Gp-170, affecting doxorubicin accumulation in the cells treated with the inhibitor. Samples from pediatric ALL patients exhibit PTEN expression and higher HIF-1α and YY1 expression compared to controls. PTEN/Akt/NF-κB axis plays a critical role in the regulation of YY1 through HIF-1α, and this mechanism contributes to Gp-170-mediated chemoresistance in pediatric ALL. Full article
(This article belongs to the Special Issue Molecular Insight into Leukemia)
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<p>SF1670 treatment decreases PTEN expression in RS4;11 cells. (<b>A</b>) Representative microphotograph of PTEN expression in RS4;11 cells treated with the inhibitor SF1670 at 1 µM. A decrease in the expression of PTEN is observed, although it is not statistically significant in RS4;11 cells treated with the inhibitor and an increase in the expression of pAkt, NF-κB, and PTEN (* <span class="html-italic">p</span> &lt; 0.05; * <span class="html-italic">p</span> &lt; 0.05) compared to untreated cells. (<b>B</b>) Expression of HIF-1α, YY1, and gp-170 in RS4 cells; 11 treated with the inhibitor, (HIF-1α * <span class="html-italic">p</span> &lt; 0.05; YY1 * <span class="html-italic">p</span> &lt; 0.05; Gp-170 * <span class="html-italic">p</span> &lt; 0.05; untreated vs. inhibitor). 400× magnification.</p>
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<p>Inhibition of PTEN with SF1670 promotes the expression of NF-κB, YY1, and Gp-170. (<b>A</b>) Western Blot representative of the amount of total protein in RS4;11 cells treated with SF1670; the results show differences in the expression of p-Akt and Gp-170 (** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001), after treatment with the inhibitor of PTEN. (<b>B</b>) The expression of NF-κB and YY1 in the cell line used is modified after treatment with the inhibitor (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01); PTEN does not show changes in the level of protein expression when using the PTEN inhibitor, and HIF-1α has no significant changes. (<b>C</b>) Expression of mRNA of YY1 is increased in RS4;11 cells after SF1670 treatment (*** <span class="html-italic">p</span> = 0.001 treatment vs. untreated).</p>
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<p>Inhibition of PTEN with SF1670 decreases cell death in RS4;11. (<b>A</b>) Western Blot analysis of active caspase-3 from RS4;11 cells treated with SF1670; the results show difference in expression after treatment (**** <span class="html-italic">p</span> &lt; 0.0001). (<b>B</b>) Doxorubicin accumulation analysis after treatment with the PTEN inhibitor shows a change in the intracellular levels of the drug in RS4;11 cells (** <span class="html-italic">p</span> &lt; 0.01). (<b>C</b>) Analysis of RS4;11 TUNEL positive cells treated with the inhibitor shows a decrease in TUNEL positive cells in the treatment with PTEN inhibitor and doxorubicin (** <span class="html-italic">p</span> &lt; 0.01). 400× magnification.</p>
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<p>Patients with ALL exhibit decreased expression of PTEN and elevated expression of pAkt, NF-κB, HIF-1α, and YY1. (<b>A</b>) PTEN expression in mononuclear cells from pediatric patients with ALL compared with cells from healthy controls showed lower expression of PTEN. An increase in the percentage of cells positive for pAkt, NF-κB, HIF-1, and YY1 was observed in cells from patients with ALL compared to healthy controls (PTEN **** <span class="html-italic">p</span> &lt; 0.0001; pAkt **** <span class="html-italic">p</span> &lt; 0.0001; NF-κB *** <span class="html-italic">p</span> &lt; 0.001; HIF-1α **** <span class="html-italic">p</span> &lt; 0.0001; YY1 ** <span class="html-italic">p</span> &lt; 0.01; control vs. ALL, respectively) 600× magnification. (<b>B</b>) Correlation between the expressions of PTEN and HIF-1α in pediatric ALL, showing a negative correlation between the expression of PTEN and HIF-1α in cells from patients with ALL (Pearson’s test. <span class="html-italic">r</span> = 0.3387, <span class="html-italic">p</span> = 0.047). (<b>C</b>) Correlation between the expressions of PTEN and YY1 in pediatric ALL, showing a negative correlation between the expression of PTEN and YY1 in cells from patients with ALL (Pearson’s test. <span class="html-italic">r</span> = 0.2646, <span class="html-italic">p</span> = 0.0292).</p>
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<p>Expression of PTEN, HIF-1α, and YY1 in the cellular immunophenotypes of pediatric ALL. The percentages of positive cells for PTEN, HIF-1α, and YY1 are shown in the different immunophenotypes of patients with ALL (<span class="html-italic">n</span> = 68) and control individuals (<span class="html-italic">n</span> = 50) in peripheral blood cells of each study subject. (<b>A</b>) Shows the expression of PTEN in the different immunophenotypes with a statistically significant increase in the percentage of positive PTEN cells in the samples of patients with ALL with immunophenotype Pro-B, Pre-B, B, and T vs. control (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01). (<b>B</b>) Indicates the expression of HIF-1α in the different immunophenotypes, with a statistically significant increase in the percentage of positive HIF-1α cells in the samples of patients with ALL with Pro-B, Pre-B, and B immunophenotype vs. control (*** <span class="html-italic">p</span> &lt; 0.001; *** <span class="html-italic">p</span> &lt; 0.001; *** <span class="html-italic">p</span> &lt; 0.001). (<b>C</b>) Shows the expression of YY1 in the different immunophenotypes, with a statistically significant increase in the percentage of positive YY1 cells in the samples of patients with ALL with immunophenotype Pro-B vs. control (** <span class="html-italic">p</span> &lt; 0.01). Comparison was made using unpaired two-tailed <span class="html-italic">t</span>-test.</p>
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<p>Involvement of PTEN in chemoresistance mediated by the HIF-1α/YY1 axis in pediatric ALL. Inhibition of PTEN through SF1670 promotes the activation of Akt, which leads to the activation of NF-κB, this results in the translocation of transcription factors such as HIF-1α and YY1, which exert their activity on their genes target, importantly in the expression of the glycoprotein Gp-170, which expels drugs and promotes chemoresistance in pediatric ALL.</p>
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20 pages, 3316 KiB  
Review
Therapeutic Implications of Targeting YY1 in Glioblastoma
by Inesa Navasardyan, Apostolos Zaravinos and Benjamin Bonavida
Cancers 2024, 16(11), 2074; https://doi.org/10.3390/cancers16112074 - 30 May 2024
Viewed by 1244
Abstract
The transcription factor Yin Yang 1 (YY1) plays a pivotal role in the pathogenesis of glioblastoma multiforme (GBM), an aggressive form of brain tumor. This review systematically explores the diverse roles of YY1 overexpression and activities in GBM, including its impact on the [...] Read more.
The transcription factor Yin Yang 1 (YY1) plays a pivotal role in the pathogenesis of glioblastoma multiforme (GBM), an aggressive form of brain tumor. This review systematically explores the diverse roles of YY1 overexpression and activities in GBM, including its impact on the tumor microenvironment (TME) and immune evasion mechanisms. Due to the poor response of GBM to current therapies, various findings of YY1-associated pathways in the literature provide valuable insights into novel potential targeted therapeutic strategies. Moreover, YY1 acts as a significant regulator of immune checkpoint molecules and, thus, is a candidate therapeutic target in combination with immune checkpoint inhibitors. Different therapeutic implications targeting YY1 in GBM and its inherent associated challenges encompass the use of nanoparticles, YY1 inhibitors, targeted gene therapy, and exosome-based delivery systems. Despite the inherent complexities of such methods, the successful targeting of YY1 emerges as a promising avenue for reshaping GBM treatment strategies, presenting opportunities for innovative therapeutic approaches and enhanced patient outcomes. Full article
(This article belongs to the Collection Targeting Solid Tumors)
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<p>Immunosuppressive tumor microenvironment of glioblastoma multiforme. Various strategies have been employed by GBM cells in the TME to evade the host immune response. GBM cells are able to create an immunosuppressive microenvironment within the tumor through the release of immunosuppressive cytokines such as TGF-β and IL-10, which recruit regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), inhibiting host anti-tumor immune cell activity. Moreover, effector immune cells are inactivated by the presence of Tregs and MDSCs, allowing GBM cells to proliferate and evade immune surveillance. The interaction between programmed death-ligand 1 (PD-L1) on GBM cells and programmed cell death protein 1 (PD-1) receptors on anti-tumor CD8+ T cells results in T cell inactivation and exhaustion. Lastly, the downregulation of major histocompatibility complex (MHC) molecules on GBM cells compromises the interaction between T cell receptors (TCRs) and antigens presented alongside MHC molecules, inhibiting T cell activation and reducing CD8 T cell immune recognition.</p>
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<p><b>YY1-mediated immune evasion in GBM.</b> YY1 has a positive regulatory effect on immune checkpoint pathways, particularly PD-1/PD-L1. As a result of this upregulation, there is heightened interaction between PD-1 and its ligand PD-L1, stimulating the onset and perpetuation of T cell exhaustion. Consequently, T cells lose their effectiveness in initiating an immune response against tumors or pathogens, enabling immune evasion and facilitating tumor growth.</p>
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<p><b>Distribution of immune cell infiltration (CIBERSORT score) in GBM and normal tissues</b>. (<b>a</b>) Immune cell score heatmap. The different colors represent the expression distribution of CIBERSORT scores between GBM and normal tissue. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. The statistical difference was compared through the Wilcox test. (<b>b</b>) The percentage abundance of tumor-infiltrating immune cells in each sample. Different colors represent different types of immune cells. The abscissa represents the GBM samples, and the ordinate represents the percentage of immune cell content in each GBM sample. (<b>c</b>) Box plots show the CIBERSORT scores for each immune cell in GBM and normal brain samples. The analyses between normal tissues (n = 5) and GBM tissues (n = 153) demonstrated that there were significant differences in GBM tissues with regard to the frequency of immune cell infiltration. Namely, there were enrichments of the CD4+ T cell memory resting Tregs, NK resting cells, M1/M2 macrophages, eosinophils and neutrophils. In contrast, there were significantly lower levels of naïve B cells, plasma B cells, follicular helper T cells, activated NK cells, monocytes and resting mast cells.</p>
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<p><b>The expression distribution of immune checkpoints in GBM tissues and normal brain tissues (TCGA, n = 5; GTEx, n = 2642)</b>. The heatmap (<b>a</b>) and scatter plots (<b>b</b>) show the expression of 8 immune-checkpoint-related genes in GBM and normal brain samples. The analyses have demonstrated that the expressions of various immune checkpoints are upregulated in GBM tissues compared to the normal tissues. These higher expressions consisted of Sialic acid-binding immunoglobulin-like lectin 15 (SIGLEC15), T cell immunoreceptor with Ig and ITIM domains (TIGIT), Programmed cell death ligand 1 (CD274, PD-L1), Hepatitis A virus receptor 2 (HAVCR2), Programmed cell death 1 (PDCD1, PD1), Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), Lymphocyte activation gene-3 (LAG3) and Programmed cell death-ligand 2 (PDCD1LG2, PD-L2). *** <span class="html-italic">p</span> &lt; 0.001, asterisks. The statistical difference was compared using the Wilcox test.</p>
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<p>(<b>a</b>) Comparison of immune infiltration (EPIC scores) between GBM tumors with high levels of YY1 expression (YY1-high GBM) and low levels of YY1 expression (YY1-low GBM). (<b>b</b>) Comparison of the expressions of 8 immune checkpoints (CD274, CTLA4, HAVCR2, LAG3, PDCD1, PDCD1LG2, TIGI, SIGLEC15) in GBM tumors with high and low levels of YY1 expression. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. The statistical difference of two groups was compared through the Wilcox test.</p>
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<p><b>YY1 plays a central role in regulating multiple pathways involved in GBM pathogenesis.</b> YY1 activates the expression of SNAIL (repressor of E-cadherin), inducing epithelial–mesenchymal transition (EMT) and promoting invasion and metastasis. YY1 is also critical for the maintenance and self-renewal of glioma stem cells (GSCs), driving tumor initiation, progression, and resistance to therapies. Furthermore, YY1 regulates the expression of various miRNAs, lncRNAs, inflammatory cytokines and the c-Myc proto-oncogene, all of which contribute to cell proliferation and resistance and the pathogenesis of GBM. Conversely, YY1 inhibits pathways involving PARP (poly-ADP ribose polymerase), Fas/DR5 (cytotoxic receptors on CD8 T cells), p53, and FEN-1 (Flap structure specific endonuclease 1), leading to cell proliferation, decreased DNA repair, immune evasion, chemoresistance, genomic instability, and tumor progression. This multifaceted regulation by YY1 highlights its pivotal role in the various pathways that drive GBM pathogenesis.</p>
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23 pages, 12836 KiB  
Article
Integrated Transcriptomic and Proteomic Study of the Mechanism of Action of the Novel Small-Molecule Positive Allosteric Modulator 1 in Targeting PAC1-R for the Treatment of D-Gal-Induced Aging Mice
by Lili Liang, Shang Chen, Wanlin Su, Huahua Zhang and Rongjie Yu
Int. J. Mol. Sci. 2024, 25(7), 3872; https://doi.org/10.3390/ijms25073872 - 30 Mar 2024
Cited by 2 | Viewed by 1405
Abstract
Small-molecule positive allosteric modulator 1 (SPAM1), which targets pituitary adenylate cyclase-activating polypeptide receptor 1 (PAC1-R), has been found to have a neuroprotective effect, and the underlying mechanism was explored in this study. First, using a D-galactose (D-gal)-induced aging mouse model, we confirmed that [...] Read more.
Small-molecule positive allosteric modulator 1 (SPAM1), which targets pituitary adenylate cyclase-activating polypeptide receptor 1 (PAC1-R), has been found to have a neuroprotective effect, and the underlying mechanism was explored in this study. First, using a D-galactose (D-gal)-induced aging mouse model, we confirmed that SPAM1 improves the structure of the hippocampal dentate gyrus and restores the number of neurons. Compared with D-gal model mice, SPAM1-treated mice showed up-regulated expression of Sirtuin 6 (SIRT6) and Lamin B1 and down-regulated expression of YinYang 1 (YY1) and p16. A similar tendency was observed in senescent RGC-5 cells induced by long-term culture, indicating that SPAM1 exhibits significant in vitro and in vivo anti-senescence activity in neurons. Then, using whole-transcriptome sequencing and proteomic analysis, we further explored the mechanism behind SPAM1’s neuroprotective effects and found that SPAM is involved in the longevity-regulating pathway. Finally, the up-regulation of neurofilament light and medium polypeptides indicated by the proteomics results was further confirmed by Western blotting. These results help to lay a pharmacological network foundation for the use of SPAM1 as a potent anti-aging therapeutic drug to combat neurodegeneration with anti-senescence, neuroprotective, and nerve regeneration activity. Full article
(This article belongs to the Collection Feature Papers in Molecular Neurobiology)
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<p>SPAM1 attenuates the D-gal-induced reduction in the number of mouse hippocampal neurons. HE staining showed that D-gal treatment led to a reduction in mouse hippocampal neurons, which was most significantly reversed by SPAM1 at concentrations of 0.1 μmol/kg/day and 100 μmol/kg/day.</p>
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<p>SPAM1 ameliorated RGC cell senescence. (<b>a</b>) β-gal staining and (<b>b</b>) corresponding statistics showed that the number of β-gal-positive RGC-5 cells was significantly reduced by different concentrations of SPAM1. ** <span class="html-italic">p</span> &lt; 0.01 vs. 40 d. Data are presented as the mean ± SEM of three experiments.</p>
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<p>Effect of SPAM1 on the expression of SIRT6, YY1, Lamin B1, and p16 in RGC-5 cells. (<b>a</b>) WB images of Lamin B1 and p16 in RGC-5 whole cells (<b>left</b>) and the corresponding statistics (<b>right</b>) show that the expression of Lamin B1 was reduced and p16 expression was increased in RGC-5 cells after 40 days. ** <span class="html-italic">p</span> &lt; 0.01 vs. 10 d. (<b>b</b>) WB images (<b>left</b>) and corresponding statistics (<b>right</b>) of Lamin B1 in RGC-5 whole cells after 40 days show that a 10~100 μM concentration of SPAM1 significantly increased the expression of Lamin B1. ** <span class="html-italic">p</span> &lt; 0.01 vs. 40 d. (<b>c</b>) WB images (<b>left</b>) and corresponding statistics (<b>right</b>) of p16 in RGC-5 whole cells show that different concentrations of SPAM1 could down-regulate the expression of p16. # <span class="html-italic">p</span> &lt; 0.05 vs. 10 d; ** <span class="html-italic">p</span> &lt; 0.01 vs. 40 d. (<b>d</b>) WB images (<b>left</b>) and corresponding statistics (<b>right</b>) of YY1 and SIRT6 in RGC-5 whole cells show that a 100 μM concentration of SPAM1 decreased the expression of YY1 and 1 to 100 μM of SPAM1 up-regulated the expression of SIRT6. # <span class="html-italic">p</span> &lt; 0.05 vs. 10 d; * <span class="html-italic">p</span> &lt; 0.05 vs. 40 d; ** <span class="html-italic">p</span> &lt; 0.01 vs. 40 d. (<b>e</b>) WB images (<b>left</b>) and corresponding statistics (<b>right</b>) of YY1 and SIRT6 in RGC-5 whole cells (10 days) show that a 100 μM concentration of SPAM1 decreased the expression of YY1. ** <span class="html-italic">p</span> &lt; 0.01 vs. 10 d. Data are presented as the mean ± SEM of three experiments.</p>
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<p>Effect of SPAM1 treatment on the expression of SIRT6. (<b>a</b>) Immunohistochemical images of Lamin B1 expression in the hippocampus (<b>left</b>) and corresponding statistical chart (<b>right</b>) of Lamin B1 expression in the hippocampus. (<b>b</b>) Immunohistochemical images of p16 expression in the hippocampus (<b>left</b>) and corresponding statistical chart (<b>right</b>) of p16 expression in the hippocampus. (<b>c</b>) Immunohistochemical images of SIRT6 expression in the hippocampus (<b>left</b>) and corresponding statistical chart (<b>right</b>) of p16 expression in the hippocampus. (<b>d</b>) Immunohistochemical images of YY1 expression in the hippocampus (<b>left</b>) and corresponding statistical chart (<b>right</b>) of YY1 expression in the hippocampus. The data for the statistical graph were taken from the red + areas in the graph above. # <span class="html-italic">p</span> &lt; 0.05 vs. NOR; ## <span class="html-italic">p</span> &lt; 0.01 vs. NOR; * <span class="html-italic">p</span> &lt; 0.05 vs. saline; ** <span class="html-italic">p</span> &lt; 0.01 vs. saline. Data are presented as the mean ± SE, <span class="html-italic">n</span> = 8–10.</p>
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<p>Heatmaps of differentially expressed mRNAs, lncRNAs, circRNAs, and miRNAs in DA and SP groups. (<b>a</b>) Heatmap of differentially expressed mRNAs; (<b>b</b>) heatmap of differentially expressed lncRNAs; (<b>c</b>) heatmap of differentially expressed circRNAs; (<b>d</b>) heatmap of differentially expressed miRNAs.</p>
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<p>Volcano plots of differentially expressed mRNAs, lncRNAs, circRNAs, and miRNAs in DA and SP groups. (<b>a</b>) Volcano plot of 107 differentially expressed mRNAs; (<b>b</b>) volcano plot of 44 differentially expressed lncRNAs; (<b>c</b>) volcano plot of 85 differentially expressed circRNAs; (<b>d</b>) volcano plot of 16 differentially expressed miRNAs.</p>
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<p>GO enrichment analysis of differentially expressed mRNAs, differentially expressed LncRNA target genes, host genes that differentially express circRNAs, and differentially expressed miRNA target genes. GO biological functional analyses of (<b>a</b>) differentially expressed mRNAs; (<b>b</b>) differentially expressed LncRNA target genes; (<b>c</b>) host genes that differentially express circRNAs; (<b>d</b>) differentially expressed miRNA target genes.</p>
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<p>KEGG pathway enrichment analysis of differentially expressed mRNAs, differentially expressed LncRNA target genes, host genes that differentially express circRNAs, and differentially expressed miRNA target genes. KEGG pathway analyses of (<b>a</b>) differentially expressed mRNAs; (<b>b</b>) differentially expressed LncRNA target genes; (<b>c</b>) host genes that differentially express circRNAs; (<b>d</b>) differentially expressed miRNA target genes. The signaling pathways in the orange boxes represent conventional pathways activated by PACAP, and those in the green boxes are strongly associated with anti-aging and longevity, but are not involved in the conventional PACAP pathways.</p>
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<p>Whole-transcriptome association analysis. (<b>a</b>) KEGG integrated pathway network. Each dot represents a gene, and lines represent the relationships among genes or between genes and pathways. The colors of the different lines represent relationships between genes and different pathways. The red dots are key genes. Combined analysis of differentially expressed RNA targeting relationships. (<b>b</b>) Analysis of host genes that differentially express circRNAs and their associated target RNAs; (<b>c</b>) analysis of target RNAs associated with differentially expressed miRNAs; (<b>d</b>) analysis of target RNAs associated with differentially expressed mRNAs. DE_circRNA: differentially expressed circRNAs; DE_Hostgene_circRNA: all circRNAs with differentially expressed genes as the host gene; DE_miRNA_TargetcircRNA: all circRNAs targeted by differentially expressed miRNAs; DE_miRNA: differentially expressed miRNAs; DE _mRNA_TargetmiRNA: all miRNAs targeted by differentially expressed mRNAs; DE_circRNA_TargetmiRNA: all miRNAs targeted by differentially expressed circRNAs; DE_mRNA: differentially expressed mRNAs; DE_miRNA_TargetmRNA: all target genes of differentially expressed miRNAs; DE_circRNA_Hostgene: differential expression of circRNAs for all host genes.</p>
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<p>Heatmaps and volcano plots of differentially expressed proteins in DA and SP groups. (<b>a</b>) Heatmap of differentially expressed proteins; (<b>b</b>) volcano plot of differentially expressed proteins. (<b>c</b>) Differentially expressed protein string network graph. Each node represents a protein, with thicker lines representing higher association confidence.</p>
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<p>GO and KEGG pathway enrichment analyses of differentially expressed proteins. (<b>a</b>) GO biological functional analyses of differentially expressed proteins; (<b>b</b>) KEGG pathway analyses of differentially expressed proteins. Signaling pathways marked with a red bar indicate an association with longevity, neuroprotection, or the PACAP-PAC1 signaling pathway.</p>
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<p>(<b>a</b>) Spearman correlation heatmap. The columns represent differential proteins, the rows represent differential genes, and the magnitude of the correlation is represented by the color. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. (<b>b</b>) Network diagram. The rectangles in the diagram are differential genes, the circles are differential proteins, the blue lines indicate negative correlations, and the red lines indicate positive correlations.</p>
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<p>Validation of differentially expressed proteins. (<b>a</b>) WB images (<b>left</b>) and corresponding statistics (<b>right</b>) of neurofilament light polypeptide (NEFL) in D-gal model mouse brain tissue show significant up-regulation of neurofilament light polypeptide (NEFL) expression at different concentrations of SPAM1. (<b>b</b>) WB images (<b>left</b>) and corresponding statistics (<b>right</b>) of neurofilament medium polypeptide (NEFM) in D-gal model mouse brain tissue show significant up-regulation of neurofilament medium polypeptide (NEFM) expression at different concentrations of SPAM1. ## <span class="html-italic">p</span> &lt; 0.01 vs. CON; ** <span class="html-italic">p</span> &lt; 0.01 vs. D-gal. Data are presented as the mean ± SEM of three experiments.</p>
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30 pages, 5770 KiB  
Review
Regulation of PD-L1 Expression by YY1 in Cancer: Therapeutic Efficacy of Targeting YY1
by Ana Dillen, Indy Bui, Megan Jung, Stephanie Agioti, Apostolos Zaravinos and Benjamin Bonavida
Cancers 2024, 16(6), 1237; https://doi.org/10.3390/cancers16061237 - 21 Mar 2024
Cited by 4 | Viewed by 3323
Abstract
During the last decade, we have witnessed several milestones in the treatment of various resistant cancers including immunotherapeutic strategies that have proven to be superior to conventional treatment options, such as chemotherapy and radiation. This approach utilizes the host’s immune response, which is [...] Read more.
During the last decade, we have witnessed several milestones in the treatment of various resistant cancers including immunotherapeutic strategies that have proven to be superior to conventional treatment options, such as chemotherapy and radiation. This approach utilizes the host’s immune response, which is triggered by cancer cells expressing tumor-associated antigens or neoantigens. The responsive immune cytotoxic CD8+ T cells specifically target and kill tumor cells, leading to tumor regression and prolongation of survival in some cancers; however, some cancers may exhibit resistance due to the inactivation of anti-tumor CD8+ T cells. One mechanism by which the anti-tumor CD8+ T cells become dysfunctional is through the activation of the inhibitory receptor programmed death-1 (PD-1) by the corresponding tumor cells (or other cells in the tumor microenvironment (TME)) that express the programmed death ligand-1 (PD-L1). Hence, blocking the PD-1/PD-L1 interaction via specific monoclonal antibodies (mAbs) restores the CD8+ T cells’ functions, leading to tumor regression. Accordingly, the Food and Drug Administration (FDA) has approved several checkpoint antibodies which act as immune checkpoint inhibitors. Their clinical use in various resistant cancers, such as metastatic melanoma and non-small-cell lung cancer (NSCLC), has shown significant clinical responses. We have investigated an alternative approach to prevent the expression of PD-L1 on tumor cells, through targeting the oncogenic transcription factor Yin Yang 1 (YY1), a known factor overexpressed in many cancers. We report the regulation of PD-L1 by YY1 at the transcriptional, post-transcriptional, and post-translational levels, resulting in the restoration of CD8+ T cells’ anti-tumor functions. We have performed bioinformatic analyses to further explore the relationship between both YY1 and PD-L1 in cancer and to corroborate these findings. In addition to its regulation of PD-L1, YY1 has several other anti-cancer activities, such as the regulation of proliferation and cell viability, invasion, epithelial–mesenchymal transition (EMT), metastasis, and chemo-immuno-resistance. Thus, targeting YY1 will have a multitude of anti-tumor activities resulting in a significant obliteration of cancer oncogenic activities. Various strategies are proposed to selectively target YY1 in human cancers and present a promising novel therapeutic approach for treating unresponsive cancer phenotypes. These findings underscore the distinct regulatory roles of YY1 and PD-L1 (CD274) in cancer progression and therapeutic response. Full article
(This article belongs to the Section Molecular Cancer Biology)
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Figure 1

Figure 1
<p>YY1 regulation of cellular processes and its role in cancer cells. YY1 is an activator or repressor in several cellular processes including gene expression, apoptosis, DNA repair, cellular metabolism, cell survival, cellular differentiation, and cell cycle regulation. Disruption of YY1 signaling and overexpression of YY1 in cancer is associated with metastasis, resistance to chemotherapy and immunotherapy in cancer patients, and poor prognosis in patients [<a href="#B55-cancers-16-01237" class="html-bibr">55</a>,<a href="#B56-cancers-16-01237" class="html-bibr">56</a>]. <a href="#cancers-16-01237-f001" class="html-fig">Figure 1</a>, <a href="#cancers-16-01237-f002" class="html-fig">Figure 2</a>, <a href="#cancers-16-01237-f003" class="html-fig">Figure 3</a>, <a href="#cancers-16-01237-f004" class="html-fig">Figure 4</a>, <a href="#cancers-16-01237-f005" class="html-fig">Figure 5</a> and <a href="#cancers-16-01237-f006" class="html-fig">Figure 6</a> were generated using <a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a> accessed on 12 January 2023.</p>
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<p>Effect of the PD-L1/PD-1 interaction on T-cell immune function and cytokines. The modulation of the immune T-cell system occurs when the immune checkpoint PD-L1, present on tumor cells, interacts with PD-1 on CD8 T cells. The interaction of PD-1 and PD-L1 blocks and suppresses T-cell function, including anti-tumor CD8 T cells. Additionally, PD-L1/PD-1 leads to a decrease in the cytokines TNF-α, IFN-γ, and IL-2, allowing for immune escape in tumor cells.</p>
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<p>Upregulation and downregulation of PD-L1 by YY1 through various factors. YY1 indirectly regulates the expression of PD-L1 through several factors. YY1 plays a dual role in positively or negatively regulating IFN-γ in different cancers. The downregulation of PD-L1 is achieved when YY1 inhibits IFN-γ or COX-2. YY1 activation of IFN-γ leads to the activation of the JAK1 and STAT1 pathways, contributing to the upregulation of PD-L1 expression. Moreover, YY1 inhibition of PTEN activates the PI3K/Akt pathway, and ultimately, mTOR upregulation increases the expression of PD-L1. IL-6 and TGF-β are activated and inhibited, respectively, by YY1, leading to STAT3 upregulation and increased PD-L1 expression.</p>
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<p>YY1 regulation of PD-L1: Epigenetic. Epigenetic regulation of PD-L1 through YY1 is achieved through various proposed mechanisms and relationships. YY1 directly activates EZH2 and, through histone methylation, inhibits PD-L1. Furthermore, YY1 and Stri-201, known inhibitors of STAT3, may indirectly downregulate PD-L1 expression. Next, YY1 has been found to interact with both HDAC5 and HDAC6 in many cancer cells. HDAC6 has a positive relationship with PD-L1, leading to the proposed mechanism between these factors.</p>
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<p>Post-translational regulation of PD-L1 expression. YY1 regulates PD-L1 via a post-translational mechanism. Firstly, miR-200 is negatively correlated with YY1, suggesting that miR-200 may decrease YY1 expression. YY1 is a known factor that inhibits p53, and p53 upregulates miR-34a. Ultimately this relationship leads to PD-L1 inhibition, and it is important to further identify ways to target PD-L1.</p>
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<p>YY1 regulation of PD-L1: Transcriptional. YY1 regulates PD-L1 transcriptionally through binding to the promoter region found on the PD-L1 <span class="html-italic">CD274</span> gene. It is also regulated via the p38/MAPK/JNK pathway which upregulates YY1. This causes increased YY1 binding to the PD-L1 promoter and an increase in PD-L1 expression. This interaction leads to cancer progression and T-cell exhaustion of tumor-infiltrating lymphocytes. The red and blue lines represent the DNA helix.</p>
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<p>YY1-mediated regulation of PD-L1 and EMT. YY1 is an important therapeutic target due to its role in the regulation of the EMT and PD-L1. Through the NF-κB/Snail/YY1/RKIP loop, YY1 can be targeted to modulate the EMT, an important factor for immune escape in cancer cells. Additionally, YY1 upregulates PD-L1, leading to an increase in the PD-L1/PD-1 interaction. This leads to T-cell exhaustion, immune tolerance of tumor cells, and cancer progression.</p>
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<p>Bioinformatic analysis of PAS between high- and low-YY1 (or <span class="html-italic">CD274</span>)-expressing tumors (<b>A</b>) The heat map shows the percentage of cancers in which the YY1 and <span class="html-italic">CD274</span> (PD-L1) genes have an activating (red) or inhibitory (blue) effect (FDR ≤ 0.05) on 10 cancer-related pathways, across 32 TCGA cancer types. The number in each cell indicates the corresponding percentage. (<b>B</b>) Two examples of the activity of the Cell Cycle pathway between high- and low-YY1-expressing breast cancers, as well as of the activity of the Apoptosis pathway between high- and low-<span class="html-italic">CD274</span> (PD-L1)-expressing breast cancers (TCGA-BRCA).</p>
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<p>Various targets that lead to the inhibition of YY1. Through the inhibition of YY1 and PD-L1 downregulation, oncogenic effects may decrease. Several targets are identified to achieve negative regulation of YY1. RKIP is a target that has a known inverse relationship with YY1 through the NF-κB/Snail/YY1/RKIP loop. NO is also implicated with the inhibition of YY1 through the repression of SNAIL, while NF-κB is also a promising factor to consider in the context of the NF-κB/SNAIL/YY1/RKIP/PTEN loop. ASOs also provide specificity in inhibiting YY1 through their ability to bind to specific RNA target sequences. Next, the use of miR-7, miR-34a, miR-489, or miR-193a-5p may have the ability to regulate YY1 gene expression negatively. The use of gRNAs through CRISPR/Cas9 may block YY1 gene function through disruption of the DNA sequence. The use of a novel synthetic small-molecule inhibitor, Inh-YY1, may directly inhibit the DNA-binding activity of YY1. Finally, YY1-targeted nanoparticle delivery is a promising selective method of YY1 inhibition. It is proposed to be used in combination with other methods of YY1 inhibition as previously mentioned.</p>
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16 pages, 5123 KiB  
Article
MiR-192-5p Ameliorates Hepatic Lipid Metabolism in Non-Alcoholic Fatty Liver Disease by Targeting Yy1
by Lina Ma, Huichen Song, Chen-Yu Zhang and Dongxia Hou
Biomolecules 2024, 14(1), 34; https://doi.org/10.3390/biom14010034 - 26 Dec 2023
Cited by 3 | Viewed by 1958
Abstract
Non-alcoholic fatty liver disease (NAFLD) is characterized by excessive lipid accumulation in the liver. Clarifying the molecular mechanism of lipid metabolism is crucial for the treatment of NAFLD. We examined miR-192-5p levels in the livers of mice in which NAFLD was induced via [...] Read more.
Non-alcoholic fatty liver disease (NAFLD) is characterized by excessive lipid accumulation in the liver. Clarifying the molecular mechanism of lipid metabolism is crucial for the treatment of NAFLD. We examined miR-192-5p levels in the livers of mice in which NAFLD was induced via a high-fat diet (HFD), as well as in mouse primary hepatocytes and human HepG2 cells treated with free fatty acids (FFAs). MiR-192-5p inhibitor was administered to NAFLD mice and hepatocytes to verify the specific function of miR-192-5p in NAFLD. We validated the target gene of miR-192-5p and further illustrated the effects of this miRNA on the regulation of triglyceride (TG) metabolism. We found that miR-192-5p was significantly increased in the livers of NAFLD mice and FFA-treated hepatocytes. Inhibition of miR-192-5p increased the accumulation of hepatic TGs and aggravated hepatic steatosis in NAFLD mice. In FFA-treated hepatocytes, miR-192-5p inhibitors markedly increased TG content, whereas overexpression of miR-192-5p reduced TG levels. Yin Yang 1 (Yy1) was identified as the target gene of miR-192-5p, which regulates TG synthesis via the YY1/fatty-acid synthase (FASN) pathway. Our results demonstrated that miR-192-5p should be considered a protective regulator in NAFLD that can inhibit hepatic TG synthesis by targeting Yy1. Full article
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Figure 1
<p>MiR-192-5p was dramatically increased in the livers of NAFLD mice. (<b>A</b>) Body weight of high-fat diet (HFD)-induced NAFLD mice and chow diet (CD)-fed control mice (<span class="html-italic">n</span> = 10). (<b>B</b>) H&amp;E staining (top) and Oil Red O staining (bottom) of liver tissues (Scale bar: 100 μm). (<b>C</b>) Weight of livers. (<b>D</b>) Hepatic triglyceride (TG) levels. (<b>E</b>) Serum TG levels. (<b>F</b>) Serum alanine aminotransferase (ALT) levels. (<b>G</b>) Serum aspartate aminotransferase (AST) levels. (<b>H</b>) Relative expression levels of de novo lipogenesis (DNL)-related genes in livers were measured by qRT-PCR. (<b>I</b>) Relative expression levels of miR-192-5p in liver tissues. The data are presented as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Inhibition of miR-192-5p aggravated hepatic steatosis in NAFLD mice. (<b>A</b>) Experimental scheme of NAFLD mice intravenously (i.v.) injected with lentivirus (LV)-Anti-miR-192-5p (<span class="html-italic">n</span> = 9) or Anti-NC (negative control) (<span class="html-italic">n</span> = 10). (<b>B</b>) The level of miR-192-5p in the livers of mice after two weeks of lentivirus injection. (<b>C</b>) Body weight. (<b>D</b>) Representative images of livers (<span class="html-italic">n</span> = 7). (<b>E</b>) Representative H&amp;E staining (top) and Oil Red O staining (bottom) of liver tissues (Scale bar: 100 μm). (<b>F</b>) Liver weight. (<b>G</b>) Hepatic TG levels. (<b>H</b>) Serum TG levels. (<b>I</b>) Serum ALT levels. (<b>J</b>) Serum AST levels. (<b>K</b>,<b>L</b>) Relative mRNA levels (<b>K</b>) and protein levels (<b>L</b>) of DNL-related genes in livers. The data are presented as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Knockdown of miR-192-5p promotes lipid deposition in hepatocytes. (<b>A</b>–<b>H</b>) Mouse primary hepatocyte (MPH) and HepG2 cells were transfected with miR-192-5p inhibitors or NC inhibitors and incubated with 0.4 mM free fatty acids (FFA, palmitic acid: oleic acid = 1:1) for 72 h (<span class="html-italic">n</span> = 3). The hepatocytes were treated with 0.5% bovine serum albumin (BSA) as a control (<b>A</b>–<b>F</b>). (<b>A</b>,<b>D</b>) The levels of miR-192-5p in MPH (<b>A</b>) and HepG2 cells (<b>D</b>). (<b>B</b>,<b>E</b>) TG levels in MPH (<b>B</b>) and HepG2 cells (<b>E</b>). (<b>C</b>,<b>F</b>) Lipid droplets stained with Nile Red (red) in MPH (<b>C</b>) and HepG2 cells (<b>F</b>) and DAPI (blue) for cell nuclei (Scale bar: 5 μm). (<b>G</b>,<b>H</b>) Relative expression levels of DNL-related genes in MPH (<b>G</b>) and HepG2 cells (<b>H</b>). The data are presented as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Overexpression of miR-192-5p decreased lipid accumulation in hepatocytes. (<b>A</b>–<b>H</b>) MPH and HepG2 cells were transfected with miR-192-5p mimics or NC mimics and incubated with 0.4 mM FFA for 72 h (<span class="html-italic">n</span> = 3). (<b>A</b>,<b>D</b>) The levels of miR-192-5p in MPH (<b>A</b>) and HepG2 cells (<b>D</b>). (<b>B</b>,<b>E</b>) TG levels in MPH (<b>B</b>) and HepG2 cells (<b>E</b>). (<b>C</b>,<b>F</b>) Lipid droplets stained with Nile Red (red) in MPH (<b>C</b>) and HepG2 cells (<b>F</b>) and DAPI (blue) for cell nuclei (Scale bar: 5 μm). (<b>G</b>,<b>H</b>) Relative expression levels of DNL-related genes in MPH (<b>G</b>) and HepG2 cells (<b>H</b>). Data are showed as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p><span class="html-italic">Yy1</span> was a potential target of miR-192-5p in hepatocytes. (<b>A</b>) Sequences of potential binding sites (BS) of miR-192-5p within the 3′-UTR of human and mouse <span class="html-italic">Yy1</span>. The miR-192-5p seed-recognition sites in the <span class="html-italic">Yy1</span> 3′-UTR are indicated in red, and the mutant (Mut) miR-192-5p binding sites in the <span class="html-italic">Yy1</span> 3′-UTR are indicated in blue. (<b>B</b>,<b>C</b>) Protein levels of YY1 in MPH and HepG2 cells treated with miR-192-5p mimics (<b>B</b>) or inhibitors (<b>C</b>) revealed by Western blotting (<span class="html-italic">n</span> = 3). (<b>D</b>) mRNA levels of <span class="html-italic">Yy1</span> in MPH and HepG2 cells. (<b>E</b>,<b>F</b>) Luciferase activities of HEK293T cells transfected with a reporter vector containing the wild-type (WT) 3′-UTR or the mutant of mouse (<b>E</b>) or human (<b>F</b>) <span class="html-italic">Yy1</span> together with miR-192-5p mimics or inhibitors. Data are showed as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>MiR-192-5p inhibited hepatic triglyceride synthesis in NAFLD mice by regulating the YY1/FASN pathway. (<b>A</b>,<b>B</b>) Protein levels of FASN in MPH and HepG2 cells transfected with miR-192-5p mimics (<b>A</b>) or inhibitors (<b>B</b>) for 48 h. NC mimics or inhibitors as a control (<span class="html-italic">n</span> = 3). (<b>C</b>,<b>D</b>) Protein levels of YY1 and FASN in MPH (<b>C</b>) and HepG2 cells (<b>D</b>) treated with miR-192-5p inhibitors and incubated with 0.4 mM FFA for 72 h. (<b>E</b>,<b>F</b>) Protein levels of YY1 and FASN in MPH (<b>E</b>) and HepG2 cells (<b>F</b>) treated with miR-192-5p mimics and incubated with 0.4 mM FFA for 72 h. (<b>G</b>) Protein levels of YY1 and FASN in the livers of NAFLD mice injected with LV-Anti-miR-192-5p or LV-Anti-NC for two weeks. Data are presented as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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27 pages, 5453 KiB  
Review
Zinc Ions Modulate YY1 Activity: Relevance in Carcinogenesis
by Małgorzata Figiel, Adam Kazimierz Górka and Andrzej Górecki
Cancers 2023, 15(17), 4338; https://doi.org/10.3390/cancers15174338 - 30 Aug 2023
Cited by 2 | Viewed by 1723
Abstract
YY1 is widely recognized as an intrinsically disordered transcription factor that plays a role in development of many cancers. In most cases, its overexpression is correlated with tumor progression and unfavorable patient outcomes. Our latest research focusing on the role of zinc ions [...] Read more.
YY1 is widely recognized as an intrinsically disordered transcription factor that plays a role in development of many cancers. In most cases, its overexpression is correlated with tumor progression and unfavorable patient outcomes. Our latest research focusing on the role of zinc ions in modulating YY1’s interaction with DNA demonstrated that zinc enhances the protein’s multimeric state and affinity to its operator. In light of these findings, changes in protein concentration appear to be just one element relevant to modulating YY1-dependent processes. Thus, alterations in zinc ion concentration can directly and specifically impact the regulation of gene expression by YY1, in line with reports indicating a correlation between zinc ion levels and advancement of certain tumors. This review concentrates on other potential consequences of YY1 interaction with zinc ions that may act by altering charge distribution, conformational state distribution, or oligomerization to influence its interactions with molecular partners that can disrupt gene expression patterns. Full article
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Graphical abstract

Graphical abstract
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<p>YY1 homology multiple sequence alignment shows its high evolutionary conservation. The alignment was performed using TranslatorX [<a href="#B120-cancers-15-04338" class="html-bibr">120</a>] and MAFFT [<a href="#B121-cancers-15-04338" class="html-bibr">121</a>]. Conserved residues are highlighted, using a modified Lesk color scheme (green—hydrophobic residues; yellow—small nonpolar; red—acidic; blue—basic; magenta—polar). Differences between the homologous sequences occur mainly outside the areas proposed in the further part of the work as molecular recognition features (MoRFs).</p>
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<p>Seven interaction regions (IRs) proposed for YY1 based on bioinformatic analyses and protein–protein interaction experiments as described in the text. From top: structural domains; sequence conservations (1 denoting most conserved and 0 least conserved); MoRFs and secondary structure predictions of YY1 (1 denoting highest probability and 0 lowest probability of regular structure arrangement); IDR predictions (1 denoting highest and 0 lowest disorder tendency); postulated Interaction Regions and fragments of YY1 interacting with partners (detailed data on interactions with partner proteins are provided in <a href="#cancers-15-04338-t002" class="html-table">Table 2</a>). The proposed interaction regions are characterized by high evolutionary conservation, high index of binding site prediction, and high tendency to form secondary structures, and have been experimentally shown to participate in interactions with molecular partners. The first five postulated regions are located in the area considered as intrinsically disordered and coincide with the postulated MoRFs, and the remaining two are elements with a stable spatial structure: first zinc finger and the remaining three zinc fingers.</p>
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24 pages, 2422 KiB  
Review
Role of YY1 in the Regulation of Anti-Apoptotic Gene Products in Drug-Resistant Cancer Cells
by Megan Jung, Indy Bui and Benjamin Bonavida
Cancers 2023, 15(17), 4267; https://doi.org/10.3390/cancers15174267 - 25 Aug 2023
Cited by 5 | Viewed by 2324
Abstract
Cancer is a leading cause of death among the various diseases encountered in humans. Cancer is not a single entity and consists of numerous different types and subtypes that require various treatment regimens. In the last decade, several milestones in cancer treatments were [...] Read more.
Cancer is a leading cause of death among the various diseases encountered in humans. Cancer is not a single entity and consists of numerous different types and subtypes that require various treatment regimens. In the last decade, several milestones in cancer treatments were accomplished, such as specific targeting agents or revitalizing the dormant anti-tumor immune response. These milestones have resulted in significant positive clinical responses as well as tumor regression and the prolongation of survival in subsets of cancer patients. Hence, in non-responding patients and non-responding relapsed patients, cancers develop intrinsic mechanisms of resistance to cell death via the overexpression of anti-apoptotic gene products. In parallel, the majority of resistant cancers have been reported to overexpress a transcription factor, Yin Yang 1 (YY1), which regulates the chemo-immuno-resistance of cancer cells to therapeutic anticancer cytotoxic agents. The relationship between the overexpression of YY1 and several anti-apoptotic gene products, such as B-cell lymphoma 2 protein (Bcl-2), B-cell lymphoma extra-large (Bcl-xL), myeloid cell leukemia 1 (Mcl-1) and survivin, is investigated in this paper. The findings demonstrate that these anti-apoptotic gene products are regulated, in part, by YY1 at the transcriptional, epigenetic, post-transcriptional and translational levels. While targeting each of the anti-apoptotic gene products individually has been examined and clinically tested for some, this targeting strategy is not effective due to compensation by other overexpressed anti-apoptotic gene products. In contrast, targeting YY1 directly, through small interfering RNAs (siRNAs), gene editing or small molecule inhibitors, can be therapeutically more effective and generalized in YY1-overexpressed resistant cancers. Full article
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<p>YY1′s activation and repression regions. Transcription factor YY1′s various regions. Made of 414 residues, its N terminal is responsible for transcriptional activation, consisting of two acidic regions and a cluster of histidine proteins. This is followed by a transcriptional repression portion containing a GK rich and REPO domain. Finally, its C-terminal, composed of 4 zinc fingers, is the DNA-binding domain as well as transcriptional repression. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>NF-κB/YY1/microRNA-10a regulatory circuit. TNF-α and IL-1Β are activators that cause the p65/p50 heterodimer of NF-κB. This further activates the production of YY1, which goes on to produce downstream effects. Its ability to inhibit miR-10a ultimately increases NF-κB levels in a feedback loop that causes further tissue damage and inflammation in patients with RA. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>Diagram of the post-translational regulation of YY1 through acetylation and deacetylation. YY1 is subject to deacetylation by the HDAC complex through a negative feedback mechanism in the same region of acetylation from the PCAF and p300 complex. The PCAF/p300 complex located on the DNA-binding domain also acetylates the N-terminal region of YY1, causing an increase in transcriptional repression. YY1′s association with HDAC also results in the formation of a repressor complex. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>YY1 leads to resistance in cancer cells. Overview detailing the role of YY1 in cellular processes relating to cancer. YY1 is involved with the regulation of several mechanisms regarding cell cycle, cell differentiation and cell proliferation. Specifically, it plays a large role in apoptosis due to its relationship with anti-apoptotic genes in cancer cells. This causes cancer cells to be resistant to apoptosis and, thus, resistant to chemotherapeutic treatments. Ultimately, it can lead to cancer proliferation. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>General overview of YY1 regulation of anti-apoptotic genes: Bcl-2, Bcl-xL, Mcl-1 and surviving through its interaction with p53. P53 normally inhibits Bcl-2, Bcl-xL and Mcl-1. YY1 inhibits p53, therefore causing upregulation of Bcl-2, Bcl-xL and Mcl-1. However, YY1 plays a repressive role in relation to survivin. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>YY1 regulation of Bcl-xL. YY1 regulates Bcl-xL through via different mechanisms. Through a direct transcriptional relationship, YY1 binds to a potential promoter region in the −425 position of the Bcl-xL gene. Another mechanism involves the stabilization of HIF-1α through binding with YY1, which ultimately upregulates Bcl-xL. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>KLF4 interaction and regulation of anti-apoptotic genes. There are two YY1-binding sites on the promoter region of KLF4, which may have implications with the expression of anti-apoptotic genes. Increased KLF4 expression has been known to reduce Bcl-2 and Mcl-1 expression. Therefore, it is proposed that YY1 acts as an activator, upregulating KFL4, which would downregulate Mcl-1 and Bcl-1. Additionally, in lapatinib-treated BT474 cells, Bcl-xL and Mcl-1 were found to be upregulated in a KLF4/5-dependent manner. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>YY1′s relationship with factors that influence T-cell exhaustion. Schematic diagram that depicts YY1′s implications with cytotoxicity in order to understand how to reverse chemotherapeutic resistance. YY1 is closely linked with T-cell exhaustion through its positive regulation of checkpoint inhibitors PD1, Tim3 and Lag 3 and its negative regulation of the type 1 cytokines IL-2 and IFN-ɣ. The downregulation of these cytokines is primarily related to a decline in cytotoxic functions, revealing elevated YY1 levels to be a biomarker in tumor-infiltrating lymphocytes. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>Summary of the different potential targets that can inhibit YY1 and its downstream effects. These targets include direct phosphorylation, ubiquitination by Smurf2, the axis miR-193a-5p/YY1/APC, miR-34A expression, betulinic acid and NO donors. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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<p>Summary of potential indirect and direct targets to YY1. Overview of the potential factors that may be targeted in order to inhibit YY1 and reverse cancer cell resistance to drug-induced apoptosis. The siRNA and Let-7aDNA, miR-7 and miR-181 are all potential targets that, when inhibited, downregulate YY1. The NO donor DETANONOate, along with the chemotherapeutic drug CDDP, can be targeted as well. The pathways involved in regulating YY1 include MAPK/ERK, P13K/AKT and NF-κB/YY1/Snail/RKIP and the transcription factors NF-κB and E2F may be the subject of the indirect inhibition of YY1. Finally, using gRNA, the CRSPR/Cas-9-mediated knockout or the novel synthetic Inh-YY1 can be utilized to directly and specifically target YY1. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 1 August 2023).</p>
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22 pages, 4193 KiB  
Article
YY1 Knockdown Relieves the Differentiation Block and Restores Apoptosis in AML Cells
by Nelida Ines Noguera, Serena Travaglini, Stefania Scalea, Caterina Catalanotto, Anna Reale, Michele Zampieri, Alessandra Zaza, Maria Rosaria Ricciardi, Daniela Francesca Angelini, Agostino Tafuri, Tiziana Ottone, Maria Teresa Voso and Giuseppe Zardo
Cancers 2023, 15(15), 4010; https://doi.org/10.3390/cancers15154010 - 7 Aug 2023
Viewed by 1499
Abstract
In this study we analyzed the expression of Yin and Yang 1 protein (YY1), a member of the noncanonical PcG complexes, in AML patient samples and AML cell lines and the effect of YY1 downregulation on the AML differentiation block. Our results show [...] Read more.
In this study we analyzed the expression of Yin and Yang 1 protein (YY1), a member of the noncanonical PcG complexes, in AML patient samples and AML cell lines and the effect of YY1 downregulation on the AML differentiation block. Our results show that YY1 is significantly overexpressed in AML patient samples and AML cell lines and that YY1 knockdown relieves the differentiation block. YY1 downregulation in two AML cell lines (HL-60 and OCI-AML3) and one AML patient sample restored the expression of members of the CEBP protein family, increased the expression of extrinsic growth factors/receptors and surface antigenic markers, induced morphological cell characteristics typical of myeloid differentiation, and sensitized cells to retinoic acid treatment and to apoptosis. Overall, our data show that YY1 is not a secondary regulator of myeloid differentiation but that, if overexpressed, it can play a predominant role in myeloid differentiation block. Full article
(This article belongs to the Section Molecular Cancer Biology)
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<p>Bortezomib downregulates YY1 expression in patient AML samples. (<b>A</b>) qRT-PCR showing <span class="html-italic">YY1</span> mRNA relative expression in 24 AML human samples and 5 AML cell lines compared with immature CD34+ and mature CD34- cells. (<b>B</b>) qRT-PCR showing <span class="html-italic">YY1</span> mRNA relative expression in the acute myeloid leukemia (AML) human sample compared with immature CD34+ and mature CD34- cells, successively treated with Bortezomib (Bor) alone or in association with 1 μM ATRA up to 72 h. (<b>C</b>) qRT-PCR and Western blot showing <span class="html-italic">YY1</span> mRNA relative expression and protein amount in the AML samples, untreated and Bor- and Bor+ATRA-treated. (<b>D</b>) qRT-PCR and Western blot showing <span class="html-italic">YY1</span> mRNA relative expression and protein amount of C/EBPε and C/EBPδ in the AML samples, untreated and Bor- and Bor+ATRA-treated. (<b>E</b>) qRT-PCR showing <span class="html-italic">YY1</span> mRNA relative expression of <span class="html-italic">CD11b</span> and <span class="html-italic">CD14</span> in the AML samples, untreated and Bor- and Bor+ATRA-treated. In qRT-PCR, the expression levels were normalized to <span class="html-italic">GAPDH</span> levels. Each sample was analyzed in triplicate. Statistical analysis was performed with the nonparametric Mann–Whitney test; * <span class="html-italic">p</span>-value ≤ 0.05; ** <span class="html-italic">p</span>-value ≤ 0.01. Error bars: SD, standard deviation.</p>
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<p>YY1 knockdown in HL-60 and OCI-AML3 cell lines induces expression of HOXA2 and HOXD13. (<b>A</b>) Western blot and quantitative analysis showing YY1 knockdown in HL-60 cells with shRNA. YY1 knockdown was achieved with lentiviral infection of a short hairpin RNA targeting YY1 cloned into a Tet-pLKO.1 puro vector. Infected HL-60 cells were maintained in culture with a low puromycin concentration and treated with doxycycline (300 ng/mL) to induce shRNA expression. sh: HL-60 cells carrying a short hairpin scrambled control sequence; sh-YY1: HL-60 cells carrying a short hairpin RNA targeting YY1; sh-doxy: HL-60 cells treated with doxycycline to induce scrambled shRNA expression; and sh-YY1-doxy: HL-60 cells treated with doxycycline to induce YY1 shRNA expression. (<b>B</b>) qRT-PCR measuring the relative expression of HOXA2 and HOXD13 mRNAs in HL-60 cells with YY1 knockdown. (<b>C</b>) Western blot and quantitative analysis showing YY1 knockdown in the OCI-AML3 cell line with siRNA. YY1 knockdown was achieved with transfection of an siRNA targeting YY1 (siYY1). YY1 expression in siYY1 cells was compared with the expression in OCI-AML3 cells transfected with a control siRNA (siSc-CT) sequence. Cells were collected after 48 h and 96 h following transfection. (<b>D</b>) qRT-PCR measuring the relative expression of HOXA2 and HOXD13 mRNAs in OCI-AML3 cells with YY1 knockdown. ** <span class="html-italic">p</span>-value ≤ 0.01. Error bars: SD, standard deviation.</p>
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<p>YY1 knockdown increases expression of C/EBP family transcription factors. (<b>A</b>) qRT-PCR and Western blots measuring CEBPα, CEBPε, and CEBPδ mRNA and protein expression levels performed in doxycycline-induced HL-60-sh-YY1-doxy cells compared with doxycycline-induced HL-60 control sh-doxy cells. mRNA expression levels were normalized to GAPDH levels and expressed as fold induction relative to the values of the control sh-doxy cells (=1). (<b>B</b>) qRT-PCR and Western blots assessing CEBPα, CEBPε, and CEBPδ expression in OCI-AML3 siYY1 cells compared with OCI-AML3 siSc-CT cells. mRNA expression levels were normalized to GAPDH levels and expressed as fold induction relative to the value of the control cells (=1). Each qRT-PCR amplification was performed in triplicate. Statistical analysis was performed with the nonparametric Mann–Whitney test. ** <span class="html-italic">p</span>-value ≤ 0.01. Error bars: SD, standard deviation.</p>
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<p>YY1 knockdown increases the sensitivity of HL-60 cells to ATRA treatment. (<b>A</b>) Western blot analysis of YY1 protein levels in sh and sh-YY1 cells, induced with doxycycline or not, collected at 24 h and 96 h of ATRA treatment. (<b>B</b>) qRT-PCR and Western blot to quantify <span class="html-italic">C/EBPα</span> in sh-YY1-doxy and control sh-doxy cells treated or untreated with 1 μM ATRA for the indicated time points. (<b>C</b>–<b>E</b>) qRT-PCR to quantify <span class="html-italic">C/EBPε, C/EBPδ,</span> and <span class="html-italic">RARα</span> in sh-YY1-doxy and control sh-doxy cells treated or untreated with 1 μM ATRA for the indicated time points. Expression levels were normalized to <span class="html-italic">GAPDH</span> levels and expressed as fold induction to the value for sh-doxy cells (=1). Each qRT-PCR amplification was performed in triplicate. Statistical analysis was performed in triplicate using with the nonparametric Mann–Whitney test. * <span class="html-italic">p</span> value ≤ 0.05; ** <span class="html-italic">p</span> value ≤ 0.01. Error bars: SD, standard deviation.</p>
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<p>YY1 knockdown does not sensitize the OCI-AML3 cell line to ATRA exposure. (<b>A</b>) Western blot analysis of YY1 protein level in siSc-CT and siYY1 cells, treated with ATRA or not, for 96 h. (<b>B</b>) qRT-PCR assessing C/EBPα, C/EBPɛ, and C/EBP-δ mRNA relative expression in siSc-CT and siYY1 cells, treated with ATRA or not, for 96 h. Each qRT-PCR amplification was performed in triplicate. Statistical analysis was performed with the nonparametric Mann–Whitney test. * <span class="html-italic">p</span>-value ≤ 0.05; Error bars: SD, standard deviation.</p>
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<p>YY1 binds 5′ promoter regions of C/EBPα, C/EBPε, C/EBPδ, and RARα genes. Chromatin immunoprecipitation showing the YY1 occupancy at the 5′ promoter regions of C/EBPα, C/EBPε, C/EBPδ, and RARα genes in 1 μM ATRA-treated or -untreated HL-60-YY1-sh-doxy and -sh-YY1-doxy cells. Experiments were conducted with two different preparations of HL-60 cells. Each qRT-PCR amplification was executed in triplicate three times, and the results of the two independent experiments were collected and used for calculation (two different experiments and a total of eighteen measurements for each sample). Rabbit anti-human IgG was used as the immunoprecipitation control. Statistical analyses were performed with the nonparametric Mann–Whitney test. ** <span class="html-italic">p</span>-value ≤ 0.01. Error bars: SD, standard deviation.</p>
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<p>YY1 knockdown induces differentiation immunophenotype in 1 μM ATRA-treated or -untreated HL-60 and OCI-AML3 cells with YY1 knockdown. (<b>A</b>) Flow cytometry plots showing the detection of CD11b and CD14 surface differentiation markers in HL-60-sh-doxy and sh-YY1-doxy cells treated with 1 μM ATRA for 72 h and 96 h. (<b>B</b>) Flow cytometry plots showing the detection of CD11b and CD14 surface differentiation markers in OCI-AML3 siSc-CT and siYY1 cells treated with 1 μM ATRA for 96 h.</p>
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<p>YY1 knockdown promotes expression of surface differentiation markers CD11b and CD14 in HL-60 and OCI-AML3 cells treated or untreated with 1 μM ATRA. (<b>A</b>) Relative mRNA expression of CD11b and CD14 surface differentiation markers in ATRA-untreated HL-60-sh-doxy and sh-doxy-YY1 cells over 96 h at 24 h intervals. (<b>B</b>) Relative mRNA expression of CD11b and CD14 surface differentiation markers in HL-60-sh-doxy and sh-doxy-YY1 cells untreated and treated with 1 μM ATRA over 96 h at 24 h intervals. (<b>C</b>) Relative mRNA expression of CD11b and CD14 surface differentiation markers in OCI-AML3-siSc-CT and siYY1 cells untreated and treated with 1 μM ATRA for 96 h. * <span class="html-italic">p</span>-value ≤ 0.05, ** <span class="html-italic">p</span>-value ≤ 0.01.</p>
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<p>YY1 knockdown induces differentiation morphology in 1 μM ATRA-treated or -untreated HL-60 and OCI-AML3 cells with YY1 knockdown. (<b>A</b>) Wright-Giemsa staining of HL-60-sh-doxy and sh-YY1-doxy cells treated and untreated with 1 μM ATRA for 72 h and 96 h. (<b>B</b>) Wright-Giemsa staining of siSc-CT and siYY1 cells treated or untreated with 1 μM ATRA for 96 h. (<b>C</b>) Table showing the percentage of blasts, myelocytes, metamyelocytes, band cells, and segmented neutrophils in HL-60-sh-doxy and sh-YY1 doxy, in OCI-AML3-siSC-CT and siYY1 cells treated or untreated with ATRA 1μM at indicated time points (50 cells analyzed per field).</p>
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<p>YY1 knockdown induces apoptosis in HL-60 cells. (<b>A</b>) Flow cytometry plots showing Annexin V and propidium iodide (PI) double staining in HL-60-sh-doxy (control) and sh-doxy-YY1 cells untreated and treated with 1 μM ATRA for 72 h and 96 h. (<b>B</b>) Western blots detecting PARP1, BAX, and caspase 3 protein levels in HL-60-sh-doxy (control) and HL-60-YY1 sh-YY1-doxy cells.</p>
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<p>YY1 knockdown induces apoptosis in OCI-AML3 cells. (<b>A</b>) Flow cytometry plots showing Annexin V and Live/Dead double staining in OCI-AML3-siSc-CT (control) and siYY1 cells untreated and treated with 1 μM ATRA for 96 h. (<b>B</b>) Western blots detecting PARP1 and caspase 3 protein levels in OCI-AML3 siSc-CT (control) and siYY1 cells untreated and treated with ATRA 1 μM for 96 h.</p>
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31 pages, 2549 KiB  
Review
Targeting Transcription Factor YY1 for Cancer Treatment: Current Strategies and Future Directions
by Rendy Hosea, Sharon Hillary, Shourong Wu and Vivi Kasim
Cancers 2023, 15(13), 3506; https://doi.org/10.3390/cancers15133506 - 5 Jul 2023
Cited by 20 | Viewed by 3661
Abstract
Cancer represents a significant and persistent global health burden, with its impact underscored by its prevalence and devastating consequences. Whereas numerous oncogenes could contribute to cancer development, a group of transcription factors (TFs) are overactive in the majority of tumors. Targeting these TFs [...] Read more.
Cancer represents a significant and persistent global health burden, with its impact underscored by its prevalence and devastating consequences. Whereas numerous oncogenes could contribute to cancer development, a group of transcription factors (TFs) are overactive in the majority of tumors. Targeting these TFs may also combat the downstream oncogenes activated by the TFs, making them attractive potential targets for effective antitumor therapeutic strategy. One such TF is yin yang 1 (YY1), which plays crucial roles in the development and progression of various tumors. In preclinical studies, YY1 inhibition has shown efficacy in inhibiting tumor growth, promoting apoptosis, and sensitizing tumor cells to chemotherapy. Recent studies have also revealed the potential of combining YY1 inhibition with immunotherapy for enhanced antitumor effects. However, clinical translation of YY1-targeted therapy still faces challenges in drug specificity and delivery. This review provides an overview of YY1 biology, its role in tumor development and progression, as well as the strategies explored for YY1-targeted therapy, with a focus on their clinical implications, including those using small molecule inhibitors, RNA interference, and gene editing techniques. Finally, we discuss the challenges and current limitations of targeting YY1 and the need for further research in this area. Full article
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Graphical abstract
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<p>Schematic diagram illustrating the mechanism of YY1 regulation in tumor drug resistance. YY1 promotes drug resistance through regulation of the DNA repair response, anti-apoptotic proteins, and drug efflux transporters. Bcl-2: B-cell lymphoma-2; Bcl-XL: B-cell lymphoma-extra large; Bim: Bcl-2 interacting mediator of cell death; BRCA1: Breast cancer-associated gene 1; MDR1: multidrug resistance protein 1.</p>
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<p>Targeting transcription factor YY1 for antitumor therapy. (<b>A</b>) DETA-NONOate inhibits YY1 binding to the promoter. (<b>B</b>) Betulinic acid inhibits YY1 through cannabinoid-receptor-dependent disruption of microRNA-27a:ZBTB10. (<b>C</b>) JAC1 targets YY1-mediated JWA/p38 signaling to inhibit tumor proliferation. (<b>D</b>) YY1BM inhibits the interaction between YY1 and the androgen receptor, which in turn decreases expression of <span class="html-italic">eEF2K</span> through the AR signaling pathway. (<b>E</b>) Synthetic peptides with the OPB domain disrupt the regulation of YY1 by competitive binding. (<b>F</b>) Antibody-based inhibition of YY1 through inhibition of the NF-κB signaling pathway. (<b>G</b>) Nucleic-acid-based inhibition of YY1. (<b>H</b>) CRISPR/Cas9 genome editing of YY1. (<b>I</b>) Role of YY1 in immunotherapy based on CAR-T cells. AKT: protein kinase B; AR: androgen receptor; BRD2/4: bromodomain-containing protein 2/4; CAR: chimeric antigen receptor; CAR-T cell: chimeric antigen receptor T cell; CB1: cannabinoid receptor 1; CB2: cannabinoid receptor 2; Cas9: CRISPR-associated protein 9; COX-2: cyclooxygenase 2; DETA-NONOate: diethylenetriamine NONOate; EGFR: epidermal growth factor receptor; eEF2K: eukaryotic elongation factor 2 kinase; ErbB2: erb-b2 receptor tyrosine kinase 2; Fas: Fas death receptor; HSF1: heat shock factor 1; IL-2: Interleukin 2; JWA: ADP ribosylation factor like GTPase 6 interacting protein 5 (ARL6IP5); LINC00278: Y-linked long noncoding RNA 278; NO: nitric oxide; OPB: oncoprotein binding domain; PD-1: programmed death 1; PD-L1: programmed death ligand 1; PFKP: phosphofructokinase, platelet; p38: p38 mitogen-activated protein kinase; sgRNA: single guide RNA; TSA: tumor-specific antigen; TRAIL: tumor necrosis factor related apoptosis-inducing ligand; YY1BM: YY1-blocking micropeptide; ZBTB10: zinc-finger and BTB domain containing 10.</p>
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<p>Overview of the current strategies and potential of targeting YY1 in antitumor therapy.</p>
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15 pages, 1521 KiB  
Article
Prognostic Implication of YY1 and CP2c Expression in Patients with Primary Breast Cancer
by Chihwan David Cha, Seung Han Son, Chul Geun Kim, Hosub Park and Min Sung Chung
Cancers 2023, 15(13), 3495; https://doi.org/10.3390/cancers15133495 - 4 Jul 2023
Cited by 1 | Viewed by 1475
Abstract
Yin Yang 1 (YY1) is a transcription factor that regulates epigenetic pathways and protein modifications. CP2c is a transcription factor that functions as an oncogene to regulate cell proliferation. YY1 is known to interact with CP2c to suppress CP2c’s transcriptional activity. This study [...] Read more.
Yin Yang 1 (YY1) is a transcription factor that regulates epigenetic pathways and protein modifications. CP2c is a transcription factor that functions as an oncogene to regulate cell proliferation. YY1 is known to interact with CP2c to suppress CP2c’s transcriptional activity. This study aimed to investigate YY1 and CP2c expression in breast cancer and prognostic implications. In this study, YY1 and CP2c expression was evaluated using immunohistochemical staining, Western blot and RT-PCR assays. Of 491 patients with primary breast cancer, 138 patients showed YY1 overexpression. Luminal subtype and early stage were associated with overexpression (p < 0.001). After a median follow-up of 68 months, YY1 overexpression was found to be associated with a better prognosis (disease-free survival rates of 92.0% vs. 79.2%, p = 0.014). In Cox proportional hazards model, YY1 overexpression functioned as an independent prognostic factor after adjustment of hormone receptor/HER2 status and tumor size (hazard ratio of 0.50, 95% CI 0.26–0.98, p = 0.042). Quantitative analysis of YY1 and CP2c protein expression in tumors revealed a negative correlation between them. In conclusion, YY1 overexpression is a favorable prognostic biomarker in patients with breast cancer, and it has a negative correlation with CP2c at the protein level. Full article
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<p>Representative microscopic images of YY1 and CP2c IHC staining. (<b>A</b>) high YY1 case (nuclear stain H-score = 180), (<b>B</b>) low YY1 case (nuclear stain H-score = 10), (<b>C</b>) high CP2c case (cytoplasmic stain H-score = 160), (<b>D</b>) low CP2c case (cytoplasmic stain H-score = 0). Rabbit monoclonal YY1 antibody (ab109237; Abcam, Cambridge, UK), and mouse polyclonal anti-CP2c antibody (610818, BD Biosciences) were used.</p>
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<p>Kaplan–Meier curves for overall survival and disease-free survival according to YY1 expression. (<b>A</b>) Overall survival (OS), (<b>B</b>) Disease-free survival (DFS). Log-rank test was performed to compare survival outcomes between two groups. <span class="html-italic">Y</span>-axis means survival probability (%) of OS and DFS.</p>
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<p>Kaplan–Meier curves for overall survival and disease-free survival according to CP2c expression. (<b>A</b>) Overall survival; (<b>B</b>) Disease-free survival. Log-rank test was performed to compare survival outcomes between two groups. <span class="html-italic">Y</span>-axis means survival probability (%) of OS and DFS.</p>
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<p>Expression profile of YY1 and CP2c from breast cancer patients’ tissue section. (<b>A</b>) YY1 mRNA expression; (<b>B</b>) CP2c mRNA expression; (<b>C</b>) YY1 protein expression; (<b>D</b>) CP2c protein expression. Student’s <span class="html-italic">t</span>-tests were employed to assess the statistical significance of differences between data sets.</p>
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<p>Correlation analysis between CP2c and YY1 expression.</p>
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<p>Kaplan–Meier curves for overall survival and disease-free survival according to YY1 and CP2c expression. (<b>A</b>) Overall survival; (<b>B)</b> Disease-free survival. Log-rank test was performed to compare survival outcomes between YY1 high and CP2c low group vs. YY1 low and CP2c high group. <span class="html-italic">Y</span>-axis means survival probability (%) of OS and DFS.</p>
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<p>Kaplan–Meier curves for overall survival and disease-free survival according to YY1 and CP2c expression. (<b>A</b>) Overall survival; (<b>B)</b> Disease-free survival. Log-rank test was performed to compare survival outcomes between YY1 high and CP2c low group vs. YY1 low and CP2c high group. <span class="html-italic">Y</span>-axis means survival probability (%) of OS and DFS.</p>
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17 pages, 2411 KiB  
Article
The Males Absent on the First (MOF) Mediated Acetylation Alters the Protein Stability and Transcriptional Activity of YY1 in HCT116 Cells
by Tingting Wu, Bingxin Zhao, Chengyu Cai, Yuyang Chen, Yujuan Miao, Jinmeng Chu, Yi Sui, Fuqiang Li, Wenqi Chen, Yong Cai, Fei Wang and Jingji Jin
Int. J. Mol. Sci. 2023, 24(10), 8719; https://doi.org/10.3390/ijms24108719 - 13 May 2023
Cited by 2 | Viewed by 2013
Abstract
Yin Yang 1 (YY1) is a well-known transcription factor that controls the expression of many genes and plays an important role in the occurrence and development of various cancers. We previously found that the human males absent on the first (MOF)-containing histone acetyltransferase [...] Read more.
Yin Yang 1 (YY1) is a well-known transcription factor that controls the expression of many genes and plays an important role in the occurrence and development of various cancers. We previously found that the human males absent on the first (MOF)-containing histone acetyltransferase (HAT) complex may be involved in regulating YY1 transcriptional activity; however, the precise interaction between MOF-HAT and YY1, as well as whether the acetylation activity of MOF impacts the function of YY1, has not been reported. Here, we present evidence that the MOF-containing male-specific lethal (MSL) HAT complex regulates YY1 stability and transcriptional activity in an acetylation-dependent manner. First, the MOF/MSL HAT complex was bound to and acetylated YY1, and this acetylation further promoted the ubiquitin–proteasome degradation pathway of YY1. The MOF-mediated degradation of YY1 was mainly related to the 146–270 amino acid residues of YY1. Further research clarified that acetylation-mediated ubiquitin degradation of YY1 mainly occurred through lysine 183. A mutation at the YY1K183 site was sufficient to alter the expression level of p53-mediated downstream target genes, such as CDKN1A (encoding p21), and it also suppressed the transactivation of YY1 on CDC6. Furthermore, a YY1K183R mutant and MOF remarkably antagonized the clone-forming ability of HCT116 and SW480 cells facilitated by YY1, suggesting that the acetylation–ubiquitin mode of YY1 plays an important role in tumor cell proliferation. These data may provide new strategies for the development of therapeutic drugs for tumors with high expression of YY1. Full article
(This article belongs to the Special Issue Novel Therapeutic Targets in Cancers)
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Figure 1
<p>Immunoprecipitation and GST-pulldown experiments confirmed the binding of MOF and YY1. (<b>A</b>,<b>B</b>) Endogenous MOF and YY1 were immunoprecipitated by overexpressed Flag-YY1 and Flag-MOF in HCT116 cells. Bound proteins were measured by Western blot analysis. GAPDH was used as an internal control. (<b>C</b>) Co-transfection and Flag IP confirmed the interaction between YY1 and MOF. HCT116 cells were co-transfected with Flag-YY1 and untagged MOF, and bound MOF was measured after a Flag IP. (<b>D</b>) The colocalization analysis of YY1 and MOF. Endogenous YY1 (green) and MOF (red) in SW480 cells were visualized by IF staining. DAPI staining showed the nuclei. Scale bar indicates 200 µm. (<b>E</b>) Different lengths of YY1. (<b>F</b>) A GST-pulldown assay was performed by mixing whole cell lysates of Flag-MOF overexpressing 293T cells and the GST-tagged deletion mutants of YY1 proteins. (<b>G</b>) The lack of the 146–270 region in YY1 decreased its binding to MOF. (<b>H</b>) The 146–270 region of YY1 competed for binding to MOF. HCT116 cells were transiently transfected with YY1 and MOF, as indicated; 48 h later, the MOF protein level was analyzed after a Flag IP. IB, immunoblot.</p>
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<p>Acetylation of YY1 by the MOF/MSL complex negatively regulated its protein stability in HCT116 cells. (<b>A</b>) YY1 may be modified by MOF. Endogenous YY1 was detected by a Western blot analysis after overexpressing MOFwt or the MOFG327E mutant in HCT116 cells. The red arrow indicates YY1 that may be modified. (<b>B</b>) Acetylation of YY1 by MOF facilitated its degradation. (<b>C</b>) Degradation of YY1, caused by MOF, was inhibited by the MOF enzyme activity inhibitor MG149. (<b>D</b>) The inactivated MOFG327E mutant inhibited the degradation of YY1. (<b>E</b>) The knockdown of <span class="html-italic">MOF</span> reduced YY1 degradation. (<b>F</b>) Elevated MOF decreased the endogenous YY1 protein level. Scale bar indicates 200 µm. (<b>G</b>,<b>H</b>) The MOF/MSL complex promoted YY1 degradation. HCT116 cells were transfected with YY1 alone or co-transfected with MSL2 or MSL1, and 48 h later, YY1 degradation was measured by Western blot using an anti-HA antibody. The red arrow in (<b>G</b>) indicates MSL2 protein. GAPDH was used as an internal control.</p>
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<p>MOF-mediated acetylation of YY1 is inhibited by HDAC1 in HCT116 cells. (<b>A</b>) The HDAC inhibitor, SAHA, increased YY1 degradation. (<b>B</b>) The degradation of YY1 without the 146–270 region was not affected by SAHA. (<b>C</b>) The interaction of MOF with the YY1/146–270 region controlled YY1 stability. (<b>D</b>) Both the SAHA and the HDAC1 inhibitor, MS275, promoted YY1 degradation. (<b>E</b>) YY1 and HDAC1 were bound to each other. (<b>F</b>) MOF and HDAC1 may competitively bind to YY1. (<b>G</b>) YY1 acetylation in cells was regulated by MOF and HDAC1.</p>
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<p>The YY1K183 site regulated the acetylation-mediated ubiquitin degradation of YY1. (<b>A</b>) There are three predicted potential ubiquitination sites (K183, K208, and K258 indicated by red color) in the 146–270 region of YY1. (<b>B</b>) Protein expression of the mutant plasmids. (<b>C</b>) The effect of mutations of lysine K183, K208, and K258 to arginine on YY1 ubiquitination. (<b>D</b>) Lysine K183 and K258 mutations suppressed YY1 ubiquitin degradation. (<b>E</b>) The effect of acetylation on ubiquitination of YY1 and mutants. (<b>F</b>) Protein stability of the YY1K183R mutant. (<b>G</b>) The effects of MOF-mediated acetylation on the ubiquitin-mediated degradation of the YY1K183R mutant.</p>
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<p>The YY1/146–270 region and the YY1K183 site play important roles in p53RE-mediated downstream target gene transactivation in HCT116 cells. (<b>A</b>) The schematic diagram of target genes up- or down-regulated by YY1. (<b>B</b>) The schematic diagram of a p53RE-Luc plasmid. Multiple response elements of <span class="html-italic">TP53</span> were inserted into the pp53-TA-Luc vector. (<b>C</b>,<b>D</b>) The effects of YY1 and its truncated mutants on p53RE-Luc luciferase activity and related protein levels. * <span class="html-italic">p</span> &lt; 0.05 or # <span class="html-italic">p</span> &lt; 0.05, compared to the p53RT-Luc group. (<b>E</b>) P53 and its downstream protein levels in <span class="html-italic">YY1</span> knockdown HCT116 cells. (<b>F</b>) Effects of YY1 and its point mutants on p21 protein levels. Increasing amounts of YY1wt, YY1K183R, and YY1K258R were transfected into HCT116 cells, and p21 protein levels were analyzed by a Western blot using the anti-p21 antibody. (<b>G</b>) The effects of YY1 and MOF on p53RE-Luc luciferase activity. * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01 compared to the p53RT-Luc group; ## <span class="html-italic">p</span> &lt; 0.01 or ### <span class="html-italic">p</span> &lt; 0.001 compared to the p53RT-Luc+MOF groups.</p>
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<p>YY1K183R/K258R mutants suppressed CDC6 transactivation and inhibited cell proliferation in HCT116 and SW480 cells. (<b>A</b>) A schematic diagram of YY1 in the promoter region of <span class="html-italic">CDC6</span>. (<b>B</b>) The effects of YY1wt and its mutants on CDC6 protein levels. (<b>C</b>) The effects of YY1wt and its mutants on CDC6-Luc luciferase activity. (<b>D</b>) The effects of YY1wt and its mutants on CDC6 protein expression levels. (<b>E</b>–<b>G</b>) The effects of YY1wt and YY1K183R on cell proliferation, as detected by an EdU proliferation assay. The proliferation rate is shown in (<b>F</b>) (** <span class="html-italic">p</span> &lt; 0.01 compared to the pcDNA3.1 group; ns, no significant difference between the pcDNA3.1 and YY1K183R groups), and the YY1 protein levels are revealed in (<b>G</b>). (<b>H</b>) MTT assays. * <span class="html-italic">p</span> &lt; 0.05 compared to the pcDNA3.1 group; # <span class="html-italic">p</span> &lt; 0.05 compared to the YY1wt group. (<b>I</b>) The effects of YY1 and mutants on cell clone formation. (<b>J</b>) Quantified colony numbers for the experimental results in. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 compared to the pcDNA3.1 group; ## <span class="html-italic">p</span> &lt; 0.01 or ### <span class="html-italic">p</span> &lt; 0.001 compared to the Flag-YY1 group.</p>
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18 pages, 10413 KiB  
Article
Expression of the Populus Orthologues of AtYY1, YIN and YANG Activates the Floral Identity Genes AGAMOUS and SEPALLATA3 Accelerating Floral Transition in Arabidopsis thaliana
by Xinying Liu, Qian Xing, Xuemei Liu and Ralf Müller-Xing
Int. J. Mol. Sci. 2023, 24(8), 7639; https://doi.org/10.3390/ijms24087639 - 21 Apr 2023
Cited by 3 | Viewed by 1726
Abstract
YIN YANG 1 (YY1) encodes a dual-function transcription factor, evolutionary conserved between the animal and plant kingdom. In Arabidopsis thaliana, AtYY1 is a negative regulator of ABA responses and floral transition. Here, we report the cloning and functional characterization [...] Read more.
YIN YANG 1 (YY1) encodes a dual-function transcription factor, evolutionary conserved between the animal and plant kingdom. In Arabidopsis thaliana, AtYY1 is a negative regulator of ABA responses and floral transition. Here, we report the cloning and functional characterization of the two AtYY1 paralogs, YIN and YANG (also named PtYY1a and PtYY1b) from Populus (Populus trichocarpa). Although the duplication of YY1 occurred early during the evolution of the Salicaceae, YIN and YANG are highly conserved in the willow tree family. In the majority of Populus tissues, YIN was more strongly expressed than YANG. Subcellular analysis showed that YIN-GFP and YANG-GFP are mainly localized in the nuclei of Arabidopsis. Stable and constitutive expression of YIN and YANG resulted in curled leaves and accelerated floral transition of Arabidopsis plants, which was accompanied by high expression of the floral identity genes AGAMOUS (AG) and SEPELLATA3 (SEP3) known to promote leaf curling and early flowering. Furthermore, the expression of YIN and YANG had similar effects as AtYY1 overexpression to seed germination and root growth in Arabidopsis. Our results suggest that YIN and YANG are functional orthologues of the dual-function transcription factor AtYY1 with similar roles in plant development conserved between Arabidopsis and Populus. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>Phylogenetic relationship of YY1 proteins from different plant species of the Rosids clade. The phylogenetic tree constructed with 25 <span class="html-italic">YY1</span> genes from 17 different species. The Salicaceae family is marked by a red box, while the Malpighiales clade is marked by a green box. Bootstrap support values are given at the nodes. The phylogenetic analyses were conducted with MEGA 7 using the neighbor-joining (NJ) method and 1000 repetitions of bootstrap tests. All YY1 Sequence were obtained from The Phytozome (<a href="https://phytozome-next.jgi.doe.gov" target="_blank">https://phytozome-next.jgi.doe.gov</a>, accessed on 27 May 2022 and 23 March 2023, see <a href="#sec4dot2-ijms-24-07639" class="html-sec">Section 4.2</a>). Gene IDs with the used versions and the Phytozome Genome IDs are listed in <a href="#app1-ijms-24-07639" class="html-app">Supplementary Table S1</a>.</p>
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<p>Sequence alignment and prediction of conserved domains in YY1 homologs of the Salicaceae family and <span class="html-italic">At</span>YY1. The amino acid sequences were aligned with DNAMAN, modified. The REPO domain [<a href="#B23-ijms-24-07639" class="html-bibr">23</a>] is marked in dark-blue, the Zn-finger domains (ZF) are marked by green lines, the CKII phosphorylation site (CKII) by a red line (the asterisk marks the phosphorylated amino acid), the NLS by a black line, and the C-terminal acid-stretch by a line in ultramarine. Identical and similar amino acid residues are shaded with dark-blue, pink, and light-blue, respectively. <span class="html-italic">At</span>YY1, <span class="html-italic">Arabidopsis thaliana</span>; YIN, YANG, Populus (<span class="html-italic">Populus trichocarpa</span>); <span class="html-italic">Pd</span>YY1a,b, <span class="html-italic">Populus deltoides</span>; <span class="html-italic">Sp</span>YY1a,b, <span class="html-italic">Salix purpurea</span>.</p>
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<p>Expression of <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> in different tissues of Populus (<span class="html-italic">Populus trichocarpa</span>). (<b>a</b>) Published expression data of <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> in leaf, stem, and root from the Website (<a href="http://phytozome-next.jgi.doe.gov" target="_blank">phytozome-next.jgi.doe.gov</a>, accessed on 4 August 2022). (<b>b</b>) RT-qPCR data of <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> expression in leaf, stem, and root of 30 days old Populus (wild-type) plants cultivated in bottles. Data represent the mean ± standard error (SE) from three biological replicates (N = 3), and <span class="html-italic">PtActin 7</span> was used as internal control. Note that the plants for the tissue samples continually grew on media with low IBA concentrations. The asterisks indicate significant differences between <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> expression (Student’s <span class="html-italic">t</span>-test: * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, and **** <span class="html-italic">p</span> ≤ 0.0001).</p>
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<p>Subcellular localization of YIN-GFP and YANG-GFP fusion proteins in Arabidopsis. Stable transgenic expression of the YIN-GFP and YANG-GFP fusion proteins in Arabidopsis root cells. Note that both fusion proteins are mainly localized in the nuclei (see details in close-ups). Scale bars, 10 μm.</p>
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<p>Vegetative phenotype of Arabidopsis <span class="html-italic">YIN_OE</span> and <span class="html-italic">YANG_OE</span> lines (T4 generation). The plants grew on soil for nine days (<b>a</b>–<b>c</b>; scale bars = 100 mm) or twenty days (<b>d</b>–<b>f</b>; scale bars = 1 cm), respectively. The overexpression of <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> caused up-curling of the primary leaves (arrowheads). Note that the leaf curling phenotype affected mainly juvenile leaves and was homogeneous mild in the T3 and T4 generation of all 10 transgenic lines (5 <span class="html-italic">YIN_OE</span> and 5 <span class="html-italic">YANG_OE</span> lines) which were used for all analyses in this study. However, some plants of the T1 generation showed stronger curling in almost all leaves (<a href="#app1-ijms-24-07639" class="html-app">Supplementary Figure S3</a>).</p>
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<p>Relative gene expression of <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> (<b>a</b>) and endogenous flowering-related genes (<b>b</b>–<b>f</b>) in 14-day-old seedlings of Arabidopsis wild-type (WT, Col-0) and transgenic lines (<span class="html-italic">YIN_OE</span> and <span class="html-italic">YANG_OE</span>). Dark-gray bars represent independent <span class="html-italic">YIN_OE</span> lines (#21, #26, #28, #32, and #34); light-gray bars represent independent <span class="html-italic">YIN_OE</span> lines (#6, #7, #11, #12, and #16). The RT-qPCR data represent the mean ± standard error (SE) from at least two biological replicates per transgenic line (N ≥ 2), and ten biological replicates for Col-0 (N = 10). <span class="html-italic">eIF4A1</span> was used as internal control, and the expression levels in the Col-0 control were set to 1. The asterisks indicate significant differences compared with the Col-0 plants (Student’s <span class="html-italic">t</span>-test: * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, and **** <span class="html-italic">p</span> ≤ 0.0001). Note the different expression scale ranges of the tested genes. Furthermore, note that there were no significant changes between the expression of <span class="html-italic">SOC1</span> and <span class="html-italic">LFY</span> in the transgenic lines and their expression in wild-type (Col-0).</p>
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<p>Expression of <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> accelerates flowering in Arabidopsis. (<b>a</b>–<b>c</b>) Arabidopsis plants, 30 DAG under the long-day conditions. <span class="html-italic">YIN_OE</span> (<b>b</b>) and <span class="html-italic">YANG_OE</span> lines (<b>c</b>) bolt earlier (arrowheads) than the wild-type control (<b>a</b>, Col-0). (<b>d</b>) Rosette leaf number in the wild-type and transgenic <span class="html-italic">YIN_OE</span> and <span class="html-italic">YANG_OE</span> lines. The rosette leaf number was measured in four independent experiments (biological replicates; N = 4; <span class="html-italic">YANG_OE #7</span>, N = 3). Red dots indicate the average in each biological replicate with at least 15 plants (N ≥ 15). Error bars represent the standard deviations. Statistical significance was determined by one-way ANOVA followed by a Tukey’s multiple comparisons test.</p>
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<p>Expression of <span class="html-italic">YIN</span> and <span class="html-italic">YANG</span> promotes root growth and accelerates seed germination in Arabidopsis. (<b>a</b>–<b>d</b>) Root growth among <span class="html-italic">yy1</span>, Col-0, and transgenic <span class="html-italic">YIN_OE</span> (<span class="html-italic">#34</span>) and <span class="html-italic">YANG</span> (<span class="html-italic">#7</span>) plants. Three-day-old seedlings grown on MS medium were transferred to MS medium containing 0 (<b>a</b>, Mock), 1 µM ABA (<b>b</b>), or 150 mM NaCl (<b>c</b>), and grown vertically for 5 days. Scale bars = 10 mm. (<b>d</b>) Root length in mm; N ≥ 6 plates with approximately 5–10 plants of each genotype. (<b>e</b>,<b>f</b>) Seed germination and cotyledon greening ratios of Col-0, <span class="html-italic">yy1</span>, and <span class="html-italic">YIN_OE</span> (<span class="html-italic">#34</span>) and <span class="html-italic">YANG</span> (<span class="html-italic">#7</span>) transgenic plants (N = 50). Seeds geminated on MS medium for 4 days. (<b>d</b>,<b>f</b>) Error bars represent the standard error of the mean; statistical significance (<span class="html-italic">p</span> ≤ 0.05) was determined by Student <span class="html-italic">t</span>-test and a-n mark groups of significant differences.</p>
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8 pages, 1543 KiB  
Case Report
First Reported Case of Gabriele-de Vries Syndrome with Spinal Dysraphism
by Nenad Koruga, Silvija Pušeljić, Marko Babić, Mario Ćuk, Andrea Cvitković Roić, Vjenceslav Vrtarić, Anamarija Soldo Koruga, Alen Rončević, Višnja Tomac, Tatjana Rotim, Tajana Turk, Domagoj Kretić, Nora Pušeljić, Rebeka Nađ and Ivana Serdarušić
Children 2023, 10(4), 623; https://doi.org/10.3390/children10040623 - 26 Mar 2023
Cited by 3 | Viewed by 2577
Abstract
Gabriele-de Vries syndrome is a rare autosomal dominant genetic disease caused by de novo pathogenic variants in the Yin Yang 1 (YY1) gene. Individuals with this syndrome present with multiple congenital anomalies, as well as a delay in development and intellectual disability. [...] Read more.
Gabriele-de Vries syndrome is a rare autosomal dominant genetic disease caused by de novo pathogenic variants in the Yin Yang 1 (YY1) gene. Individuals with this syndrome present with multiple congenital anomalies, as well as a delay in development and intellectual disability. Herein, we report the case of a newborn male patient with a novel de novo pathogenic variant in the Guanine Nucleotide-Binding Protein, Alpha Stimulating (GNAS) gene, which was identified by whole-exome sequencing. Our patient suffered from a large open spinal dysraphism which was treated surgically immediately after birth. During the follow-up, facial dysmorphism, bladder and bowel incontinence, and mildly delayed motor and speech development were observed. Congenital central nervous system disorders were also confirmed radiologically. In this case report, we present our diagnostic and treatment approaches to this patient. To our knowledge, this is the first reported case of Gabriele-de Vries syndrome presenting with spinal dysraphism. Extensive genetic evaluation is the cornerstone in treatment of patients with suspected Gabriele-de Vries syndrome. However, in cases with potentially life-threatening conditions, surgery should be strongly considered. Full article
(This article belongs to the Special Issue Neurological Diseases in Children and Adolescent)
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<p>Intraoperative image of the large lumbosacral meningomyelocele.</p>
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<p>Non-enhanced sagittal MRI T1-weighted scan revealed a Chiari malformation type 2 (up arrow), hypoplasia of the corpus callosum (down arrow), and dysgenesis of the lamina tecti (left arrow).</p>
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<p>Sagittal MRI T2-weighted scan revealed spinal cysts in the thoracic (left arrows) and lumbar regions (right arrow), syringomyelia (up arrow) and tethered cord (down arrow).</p>
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24 pages, 22764 KiB  
Article
ERVWE1 Reduces Hippocampal Neuron Density and Impairs Dendritic Spine Morphology through Inhibiting Wnt/JNK Non-Canonical Pathway via miR-141-3p in Schizophrenia
by Wei Yao, Ping Zhou, Qiujin Yan, Xiulin Wu, Yaru Xia, Wenshi Li, Xuhang Li and Fan Zhu
Viruses 2023, 15(1), 168; https://doi.org/10.3390/v15010168 - 5 Jan 2023
Cited by 9 | Viewed by 2218
Abstract
Human endogenous retroviruses (HERVs) are remnants of ancestral germline infections by exogenous retroviruses. Human endogenous retroviruses W family envelope gene (HERV-W env, also called ERVWE1), located on chromosome 7q21-22, encodes an envelope glycoprotein from the HERV-W family. Mounting evidence suggests that aberrant expression [...] Read more.
Human endogenous retroviruses (HERVs) are remnants of ancestral germline infections by exogenous retroviruses. Human endogenous retroviruses W family envelope gene (HERV-W env, also called ERVWE1), located on chromosome 7q21-22, encodes an envelope glycoprotein from the HERV-W family. Mounting evidence suggests that aberrant expression of ERVWE1 involves the etiology of schizophrenia. Moreover, the genetic and morphological studies indicate that dendritic spine deficits may contribute to the onset of schizophrenia. Here, we reported that ERVWE1 changed the density and morphology of the dendritic spine through inhibiting Wingless-type (Wnt)/c-Jun N-terminal kinases (JNK) non-canonical pathway via miR-141-3p in schizophrenia. In this paper, we found elevated levels of miR-141-3p and a significant positive correlation with ERVWE1 in schizophrenia. Moreover, serum Wnt5a and actin-related protein 2 (Arp2) levels decreased and demonstrated a significant negative correlation with ERVWE1 in schizophrenia. In vitro experiments disclosed that ERVWE1 up-regulated miR-141-3p expression by interacting with transcription factor (TF) Yin Yang 1 (YY1). YY1 modulated miR-141-3p expression by binding to its promoter. The luciferase assay revealed that YY1 enhanced the promoter activity of miR-141-3p. Using the miRNA target prediction databases and luciferase reporter assays, we demonstrated that miR-141-3p targeted Wnt5a at its 3’ untranslated region (3′ UTR). Furthermore, ERVWE1 suppressed the expression of Arp2 through non-canonical pathway, Wnt5a/JNK signaling pathway. In addition, ERVWE1 inhibited Wnt5a/JNK/Arp2 signal pathway through miR-141-3p. Finally, functional assays showed that ERVWE1 induced the abnormalities in hippocampal neuron morphology and spine density through inhibiting Wnt/JNK non-canonical pathway via miR-141-3p in schizophrenia. Our findings indicated that miR-141-3p, Wnt5a, and Arp2 might be potential clinical blood-based biomarkers or therapeutic targets for schizophrenia. Our work also provided new insight into the role of ERVWE1 in schizophrenia pathogenesis. Full article
(This article belongs to the Special Issue Endogenous Retroviruses)
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<p>The correlation among miR-141-3p, Wnt5a, Arp2, and ERVWE1 in schizophrenia patients. (<b>A</b>) The miR-141-3p level in schizophrenia patients (n = 18) was higher than that in control groups (n = 25). (<b>B</b>,<b>E</b>,<b>H</b>) Respectively represent the mRNA levels of Wnt5a, Arp2, and ERVWE1 in schizophrenia patients (n = 18) and the control groups (n = 25) using RT-qPCR. (<b>C</b>,<b>F</b>,<b>I</b>) Respectively represent the protein expression of Wnt5a, Arp2, and ERVWE1 in the schizophrenia patients (n = 48) and in the control groups (n = 36) using ELISA. (<b>D</b>) MiR-141-3p was negatively correlated with Wnt5a mRNA in patients with schizophrenia. Where X was the miR-141-3p expression value for each sample and Y was the mRNA level for Wnt5a. (<b>G</b>) Wnt5a was positively correlated with Arp2 in patients with schizophrenia. Where X was the Wnt5a protein expression level and Y was the Arp2 protein level for each sample. (<b>J</b>) ERVWE1 was positively correlated miR-141-3p in patients with schizophrenia, where X was the ERVWE1 mRNA value and Y was the miR-141-3p level for each sample. (<b>K</b>) ERVWE1 was negatively correlated with Wnt5a in schizophrenia patients, Where X was the ERVWE1 protein value and Y was the Wnt5a protein level for each sample. (<b>L</b>) ERVWE1 was negatively correlated with Arp2 in schizophrenia patients, where X was the ERVWE1 protein value and Y was the Arp2 protein expression for each sample. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.05, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>ERVWE1 promoted the expression of miR-141-3p through binding with TF YY1. (<b>A</b>) The upregulation of miR-141-3p in ERVWE1-transfected SH-SY5Y cells was validated by RT-qPCR. (<b>B</b>) The results showed that in SH-SY5Y cells containing different amounts of ERVWE1 expression plasmids (0 μg, 0.5 μg, 1 μg, 1.5 μg, 2 μg), miR-141-3p expression levels increased with the concentration of plasmid. (<b>C</b>) Prediction results showed that four TFs (ELK1, JUN, SP1, and YY1) might regulate the expression of miR-141-3p. (<b>D</b>) Analyzed the effects of various TFs on the promoter of miR-141-3p by dual-luciferase reporter assay, only YY1 could stimulate the activity of the promoter of miR-141-3p. (<b>E</b>) Increased level of miR-141-3p was detected by RT-qPCR in SH-SY5Y cells. (<b>F</b>) There were two binding sites of YY1 on the promoter of miR-141-3p, through which YY1 regulated the activity of the promoter of miR-141-3p. (<b>G</b>) ERVWE1 increased the expression of YY1 mRNA by regulating the YY1 promoter in SH-SY5Y cells; (<b>H</b>) ERVWE1 upregulated the expression level of YY1 protein. (<b>I</b>) Knockdown of YY1 substantially decreased ERVWE1-induced expression of miR-141-3p; (<b>J</b>) Specific bands were detected for Flag-tagged proteins pulled down with Myc-tagged antibody and Myc-tagged proteins pulled down with Flag-tagged antibody, which demonstrated the interaction between ERVWE1 and YY1. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, “ns” means no significance (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>ERVWE1 reduced the expression of Wnt5a through miR-141-3p. (<b>A</b>) The prediction results showed that CCNL2, ACOT7, and Wnt5a might be the potential target genes of miR-141-3p. (<b>B</b>) RT-qPCR indicated that miR-141-3p mimic inhibited the mRNA expression of Wnt5a. (<b>C</b>,<b>D</b>) miR-141-3p mimic decreased the protein level of Wnt5a, and miR-141-3p inhibitor up-regulated the expression of Wnt5a in SH-SY5Y cells and rat hippocampal neurons. (<b>E</b>) MiR-141-3p down-regulated the expression of Wnt5a through its 3′ UTR. (<b>F</b>) The decreased level of Wnt5a was determined by RT-qPCR in SH-SY5Y cells. (<b>G</b>) ERVWE1 down-regulated the expression of Wnt5a in SH-SY5Y cells, the protein level was detected by western blot. (<b>H</b>) Knockdown of miR-141-3p substantially elevated the ERVWE1-induced protein expression of Wnt5a, the protein level was detected by western blot in SH-SY5Y cells. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>ERVWE1 lessen the expression of Arp2 via JNK-mediated non-canonical signaling pathway. (<b>A</b>,<b>B</b>) ERVWE1 down-regulated the protein levels of p-JNK but had no effects on the level of total-JNK in SH-SY5Y cells and rat hippocampal neurons. (<b>C</b>,<b>D</b>) Elevated level of Wnt5a could increase the ERVWE1-induced protein expression of p-JNK in SH-SY5Y cells and rat hippocampal neurons. (<b>E</b>,<b>F</b>) ERVWE1 down-regulated the protein level of RAC1, WAVE1, and Arp2 in SH-SY5Y cells and rat hippocampal neurons. (<b>G</b>,<b>H</b>) Elevated of Wnt5a could increase the ERVWE1-induced protein level of RAC1, WAVE1, and Arp2 in SH-SY5Y cells and rat hippocampal neurons. (<b>I</b>,<b>J</b>) Anisomycin elevated the ERVWE1-induced protein level of RAC1, WAVE1, and Arp2 in SH-SY5Y cells and rat hippocampal neurons. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>MiR-141-3p mediated the inhibition of the JNK non-canonical signal pathway induced by ERVWE1. (<b>A</b>,<b>B</b>) Western blot results showed that knockdown of miR-141-3p substantially elevated the ERVWE1-induced protein expression of p-JNK in SH-SY5Y cells. (<b>C</b>,<b>D</b>) In rat hippocampal neurons, miR-141-3p knockdown resulted in an increase in p-JNK proteins induced by ERVWE1. (<b>E</b>,<b>F</b>) In SH-SY5Y cells, miR-141-3p knockdown significantly increased the expression of RAC1, WAVE1, and Arp2 induced by ERVWE1. (<b>G</b>,<b>H</b>) The knockdown of miR-141-3p significantly increased the expression of RAC1, WAVE1, and Arp2 in rat hippocampal neurons induced by ERVWE1. *** <span class="html-italic">p</span> &lt; 0.001, ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>ERVWE1 changed the density of dendritic spine through miR-141-3p in rat hippocampal neurons. (<b>A</b>,<b>E</b>,<b>I</b>,<b>M</b>) Primary rat hippocampal neurons were transfected with ERVWE1, ERVWE1 and miR-141-3p inhibitor, Wnt5a, ERVWE1 and Wnt5a, then imaged at DIV14 and were immunostained with MAP2. High-magnification images were obtained by confocal microscopy. (<b>B</b>,<b>F</b>,<b>J</b>,<b>N</b>) The sholl analysis of dendrites from rat hippocampal neurons. (<b>C</b>,<b>G</b>,<b>K</b>,<b>O</b>) The total length of dendrites was measured by ImageJ software. (<b>D</b>,<b>H</b>,<b>L</b>,<b>P</b>) The soma area was measured by ImageJ software. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>ERVWE1 altered dendritic spine morphology through miR-141-3p/Wnt5a in rat hippocampal neurons. (<b>A</b>) Fluorescence micrographs revealed that a decreased number of spines in rat hippocampal neurons with ERVWE1. (<b>B</b>) The statistics for the total and classified spine numbers per 40 μm dendrite for A, quantification of spine morphology reveals a decreased number of stubby and long-thin spines. (<b>C</b>) The number of spines might be recovered by miR-141-3p by fluorescence images of neurons labeled with phalloidin. (<b>D</b>) The statistics for the total and classified number of spines per 40 μm dendrite were calculated for C. (<b>E</b>) Fluorescence micrographs revealed that an increased number of spines in rat hippocampal neurons with Wnt5a. (<b>F</b>) The statistics for the total and classified number of spines per 40 μm dendrite were calculated for E, quantification of spine morphology reveals an increased number of stubby and long-thin spines. (<b>G</b>) A phalloidin-labeled neuron showed that Wnt5a might restore spine number. (<b>H</b>) The statistics for the total and classified number of spines per 40 μm dendrite were calculated for G. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>A possible hypothesis that ERVWE1 reduces dendritic spine density and alters dendritic spine morphology. The elevated ERVWE1 increased the expression of miR-141-3p through binding with TF YY1 and inhibited the Wnt/JNK non-canonical signaling pathway, then leading to impaired neuronal morphology and reduced dendritic spine density in rat hippocampal neurons, which played a critical role in the etiopathogenesis of schizophrenia.</p>
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