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22 pages, 3966 KiB  
Article
Chemical and Biological Mechanisms Relevant to the Rescue of MG-132-Treated Neurons by Cysteine
by Anna-Katharina Ückert, Ilinca Suciu, Anja Land, Anna-Sophie Spreng, Hannah Welte, Doreen Herzog, Michael Basler and Marcel Leist
Antioxidants 2025, 14(2), 128; https://doi.org/10.3390/antiox14020128 - 23 Jan 2025
Viewed by 71
Abstract
Proteasome dysfunctions are observed in many human pathologies. To study their role and potential treatment strategies, models of proteasome inhibition are widely used in biomedical research. One frequently used tool is the proteasome inhibitor MG-132. It triggers the degeneration of human neurons, and [...] Read more.
Proteasome dysfunctions are observed in many human pathologies. To study their role and potential treatment strategies, models of proteasome inhibition are widely used in biomedical research. One frequently used tool is the proteasome inhibitor MG-132. It triggers the degeneration of human neurons, and several studies show protection from pathological events by glutathione or its precursors. It has therefore been concluded that glutathione protects cells from proteasome dysfunction. However, an alternative explanation is that MG-132, which is a peptide aldehyde, is chemically inactivated by thiols, and the apparent protection by glutathione from proteasome dysfunction is an artefact. To clarify this issue, we examined the chemical inactivation of MG-132 by thiols and the role of such reactions for neuroprotection. Using mass spectrometry and nuclear magnetic resonance spectroscopy, we found that MG-132 reacted with L-cysteine to form a stable end product and with glutathione to form an unstable intermediate. Using a cell-free proteasome inhibition assay, we found that high concentrations of L-cysteine can scavenge a substantial fraction of MG-132 and thus reduce proteasome inhibition. Glutathione (or N-acetyl-cysteine) did not alter proteasome inhibition (even at high concentrations). In a final step, we studied human neuronal cultures. We exposed them to MG-132, supplemented the culture medium with various thiols, and assessed intracellular L-cysteine concentrations. The transcriptome response pattern also indicated an inhibition of the proteasome by MG-132 in the presence of L-cysteine. We conclude that thiol concentrations that can be reached in cells do not inactivate MG-132 in pathological models. They rather act in a cytoprotective way as antioxidants. Full article
(This article belongs to the Special Issue Glutathione and Health: From Development to Disease)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p><b>The role of L-cysteine in the prevention of proteasome inhibition by MG-132.</b> A cell-free proteasome inhibition assay was performed using isolated proteasome and a fluorogenic substrate. (<b>a</b>) Treatment scheme: MG-132 (1 µM) was pre-incubated with L-cysteine (L-Cys) for the indicated time spans to allow for a potential chemical reaction. Then, isolated proteasome was added. Thirty min later, the substrate (Suc-LLVY-AMC) was added. The fluorescence was measured 90 min later. (<b>b</b>) The proteasome inhibition was quantified for pre-incubations of MG-132 with L-Cys for 0.5–4 h. All data are normalized to proteasome activity in the absence of MG-132, but in the presence of the respective L-Cys concentration. For statistical analysis, the L-Cys co-treated samples were compared to the samples treated with MG-132 only for the respective pre-incubation time, using a 2-way ANOVA followed by Dunnett’s multiple comparisons post hoc test (ns: not significant; *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.001).</p>
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<p><b>Effect of thiol addition on transcriptome changes triggered by MG-132 in neurons.</b> (<b>a</b>) Differentiated LUHMES neurons (d6) were treated with MG-132 (100 nM) and the indicated thiol (100 µM; L-Cys: L-cysteine; GSH: glutathione; NAC: N-acetyl-cysteine). After 18 h, the cells were stained with calcein-AM and H-33342, and images were recorded on a high-content imaging system. Exemplary pictures of the calcein staining (= viable cellular structures) are shown. See <a href="#app1-antioxidants-14-00128" class="html-app">Figure S1</a> for larger images. (<b>b</b>,<b>c</b>) A transcriptome analysis was performed on differentiated LUHMES neurons (d6), treated with MG-132 (100 nM) in the presence or absence of thiols (100 µM; L-Cys, GSH, NAC). (<b>b</b>) The number of differentially expressed genes (DEGs) was quantified. Full data sets on the time course are in <a href="#app1-antioxidants-14-00128" class="html-app">Figure S3</a>. Detailed data on all genes are in <a href="#app1-antioxidants-14-00128" class="html-app">Supplement_DEG.xlsx</a>. (<b>c</b>) A principal component analysis of the full transcriptome of all samples was performed. For better overview, samples are visualized in 4 sub-plots, which are all scaled in the same way. The upper plot shows samples exposed to MG-132 for 0–18 h. The 3 lower plots show samples exposed to MG-132 plus thiols for 9 h. The arrows indicate the relative shift along principal component 1 of the thiol-treated samples relative to the MG-132-only treatment (circled).</p>
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<p><b>Chemical reaction of MG-132 with L-cysteine.</b> (<b>a</b>) Proposed chemical reaction of MG-132 (C1) and L-cysteine (L-Cys, green) via 2 intermediates (C2, C3) to the final product (C4). (<b>b</b>) MG-132 (100 µM) and L-Cys (200 µM) were incubated in DMEM (cell culture medium) for 24 h and sampled at the indicated time points. The intermediate (C2) and the product (C4) were quantified via MS. (<b>c</b>) MG-132 was incubated in DMEM alone or in the presence of L-Cys (200 µM) for 24 h, during which MG-132 (C1) was quantified via MS. (<b>d</b>) MG-132 (100 µM) was incubated in DMEM with an increasing abundance of L-Cys (200 µM–1000 mM) over 24 h and quantified via MS.</p>
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<p><b>NMR quantification of MG-132 reaction kinetics.</b> MG-132 (100 µM) was incubated with the indicated L-cysteine (L-Cys) concentrations for 19 h. <sup>1</sup>H-NMR spectra were obtained at short intervals; each point represents one measurement. (<b>a</b>) The <sup>1</sup>H-NMR spectra of MG-132 co-incubated with L-Cys (200 µM) taken after 0 h and 19 h are shown. (<b>b</b>,<b>c</b>) The integrals depicted in (<b>a</b>) were quantified and plotted over time to illustrate the reaction kinetics of MG-132 with L-Cys. Time points are given in black; the exponential fit is drawn in red.</p>
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<p><b>Chemical reaction of MG-132 with GSH.</b> (<b>a</b>) Scheme of the likely chemical reaction of MG-132 (C1) and glutathione (GSH; blue) to the product (C5). (<b>b</b>) The proteasome inhibition by MG-132 (1 µM), pre-incubated with GSH, was quantified as described in <a href="#antioxidants-14-00128-f001" class="html-fig">Figure 1</a>a. Data from 2 experiments are shown. All data are normalized to proteasome activity in the absence of MG-132, but in the presence of the respective GSH concentrations. (<b>c</b>) MG-132 (100 µM) was incubated in DMEM (cell culture medium) with increasing ratios of MG-132:GSH (GSH: 200 µM–100 mM) over 24 h, and MG-132 (C1) was quantified via MS. (<b>d</b>,<b>e</b>) MG-132 (100 µM) was incubated with GSH (200 µM) for 19 h. <sup>1</sup>H-NMR spectra were obtained at short intervals. (<b>d</b>) The <sup>1</sup>H-NMR spectra after 0 h and 19 h are shown. (<b>e</b>) The integrals depicted in (<b>d</b>) were quantified and plotted over time to illustrate the reaction kinetics. Time points are given in black; the exponential fit is drawn in red.</p>
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<p><b>Chemical reaction of MG-132 with NAC.</b> (<b>a</b>) Scheme of the likely chemical reaction of MG-132 (C1) and N-acetyl-cysteine (NAC; purple) to the product (C6). (<b>b</b>) MG-132 (100 µM) was incubated in DMEM (cell culture medium) with increasing ratios of MG-132:NAC (NAC: 200 µM–1000 mM) over 24 h, and MG-132 (C1) was quantified via MS. (<b>c</b>) Proteasome inhibition by MG-132 (1 µM), pre-incubated with NAC, was quantified as described in <a href="#antioxidants-14-00128-f001" class="html-fig">Figure 1</a>a. Data are means ± SEM, n = 3. All data are normalized to proteasome activity in the absence of MG-132, but in the presence of the respective NAC concentrations. (<b>d</b>,<b>e</b>) Proteasome activity was assessed as in (<b>c</b>). All thiols were compared on the same plate in 3 separate experiments. The MG-132 only control is given in black. Data are means ± SEM, n = 3. (<b>d</b>) Proteasome activity after 4 h of pre-incubation of MG-132 (1 µM) with 0.1 mM, 1 mM, and 2.5 mM of the respective thiol. For statistical analysis, the thiol-co-treated samples were compared to the control samples treated with MG-132 only, using a 2-way ANOVA followed by Dunnett’s multiple comparisons post hoc test (*: <span class="html-italic">p</span> &lt; 0.0001). (<b>e</b>) Proteasome activity after 30 min, 2 h, and 4 h of pre-incubation of MG-132 (1 µM) with 2.5 mM of the respective thiol (L-Cys: L-cysteine; GSH: glutathione; NAC). The dotted line indicates the proteasome activity after incubation with MG-132 (1 µM) alone. For statistical analysis, the thiol-co-treated samples were compared to the control samples treated with MG-132 only, using a 2-way ANOVA followed by Dunnett’s multiple comparisons post hoc test (*: <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 7
<p><b>Partial reactivation of the MG-132-inhibited proteasome by L-cysteine.</b> A cell-free proteasome inhibition assay was used as in <a href="#antioxidants-14-00128-f001" class="html-fig">Figure 1</a>. (<b>a</b>) Treatment scheme: MG-132 (1 µM) was pre-incubated with the isolated proteasome for 30 min to allow for inhibition to occur. Then, L-cysteine (L-Cys) was added and incubated for the indicated time spans to allow a potential reactivation of the proteasome. Finally, substrate (Suc-LLVY-AMC) was added for 90 min before measurement of fluorescence. (<b>b</b>) The proteasome inhibition was quantified for reactivation times (post-treatment) with L-Cys for 1–4 h. Data were normalized to full proteasome activity (no MG-132) in the presence of the respective L-Cys concentrations. Data are means ± SEM, n = 3. For statistical analysis, the L-Cys-co-treated samples were compared to the control samples treated only with MG-132, using a 2-way ANOVA followed by Dunnett’s multiple comparisons post hoc test (*: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.001).</p>
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<p><b>Differential effects of thiols on gene expression changes by MG-132.</b> Differentiated LUHMES cells (d6) were incubated for 0–19 h with MG-132 (100 nM), as described in <a href="#antioxidants-14-00128-f002" class="html-fig">Figure 2</a> and <a href="#app1-antioxidants-14-00128" class="html-app">Figure S10</a>. The 9 h samples were in the presence or absence of thiols (100 µM; L-Cys: L-cysteine, GSH: glutathione, NAC: N-acetyl-cysteine). (<b>a</b>) The top 50 differentially expressed genes (DEGs) were identified. The color code indicates the row-wise z-score (full red: 1; white: 0; full blue: −2). The gene names (selected row numbers for orientation) are as follows, from top to bottom: <span class="html-italic">ME1</span> (1), <span class="html-italic">GSR</span>, <span class="html-italic">GCLM</span>, <span class="html-italic">NQO1</span>, <span class="html-italic">PSMA1</span> (5), <span class="html-italic">PSMD1</span>, <span class="html-italic">UFD1</span>, <span class="html-italic">PSMB4</span>, <span class="html-italic">PSMD12</span>, <span class="html-italic">NPLOC4</span> (10), <span class="html-italic">PSMD14</span>, <span class="html-italic">ANP32E</span>, <span class="html-italic">PLAA</span>, <span class="html-italic">PALM3</span>, <span class="html-italic">SCPEP1</span> (15), <span class="html-italic">BRF2</span>, <span class="html-italic">XPOT</span>, <span class="html-italic">VCP</span>, <span class="html-italic">CYB5R1</span>, <span class="html-italic">BAG2</span> (20), <span class="html-italic">HSPA8</span> (21), <span class="html-italic">HMOX1</span> (22), <span class="html-italic">HSPD1</span>, <span class="html-italic">HSP90AA1</span>, <span class="html-italic">HSP90AB1</span> (25), <span class="html-italic">HSPH1</span>, <span class="html-italic">CHORDC1</span>, <span class="html-italic">IARS1</span>, <span class="html-italic">GARS1</span>, <span class="html-italic">ATF5</span> (30), <span class="html-italic">DDIT3</span>, <span class="html-italic">TRIB3</span>, <span class="html-italic">CHAC1</span>, <span class="html-italic">ASNS</span>, <span class="html-italic">GPT2</span> (35), <span class="html-italic">PSAT1</span>, <span class="html-italic">MTHFD2</span>, <span class="html-italic">SLC7A5</span>, <span class="html-italic">SLC3A2</span>, <span class="html-italic">FLNC</span> (40), <span class="html-italic">TNFRSF10B</span>, <span class="html-italic">PPP1R15A</span>, <span class="html-italic">CBS</span>, <span class="html-italic">CBX4</span>, <span class="html-italic">ZFAND2A</span> (45), <span class="html-italic">PEG10</span>, <span class="html-italic">PCP4</span>, <span class="html-italic">MYH3</span>, <span class="html-italic">NEFM</span>, <span class="html-italic">ABRACL</span> (50). The genes were classified as “affected” or “un-affected” by thiols, depending on whether the co-treatment with thiols significantly reverted the MG-132-induced deregulation (box) towards the untreated expression level. (<b>b</b>) Most of the genes from (<b>a</b>) fall into 4 groups: ubiquitin–proteasome system (UPS), ATF4 response, heat shock response, NRF2 response. Gene groups unaffected by thiols are given in blue boxes, gene groups fully affected by thiols are given in red boxes, gene groups partially affected by thiols are given in purple boxes. The proteasome is still inhibited in the presence of thiols, which is indicated by the UPS and NRF2 response also being (mostly) unaffected by thiols. Downstream damage pathways (ATF4 and heat shock response) are, however, attenuated by thiols, which explains the rescuing effect seen morphologically (<a href="#antioxidants-14-00128-f002" class="html-fig">Figure 2</a>).</p>
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22 pages, 16874 KiB  
Article
Comprehensive Analysis Reveals Midnolin as a Potential Prognostic, Therapeutic, and Immunological Cancer Biomarker
by Xin-Guo Zhang, Wen-Ting Li, Xin Jin, Chuang Fu, Wen Jiang, Jie Bai and Zhi-Zhou Shi
Biomedicines 2025, 13(2), 276; https://doi.org/10.3390/biomedicines13020276 - 23 Jan 2025
Viewed by 136
Abstract
Background/Objectives: MIDN (midnolin) is newly discovered method for critically regulating a ubiquitin-independent proteasomal degradation pathway. This study aims to examine the expression, prognostic value, genomic changes, interacting proteins, methylation status, and correlations with the tumor immune microenvironment of MIDN in various cancers. [...] Read more.
Background/Objectives: MIDN (midnolin) is newly discovered method for critically regulating a ubiquitin-independent proteasomal degradation pathway. This study aims to examine the expression, prognostic value, genomic changes, interacting proteins, methylation status, and correlations with the tumor immune microenvironment of MIDN in various cancers. Methods: The GTEx, Depmap, GEPIA2, and Kaplan–Meier Plotter databases are applied to evaluate the MIDN level in tumor and normal tissues and the MIDN prognostic value in cancers. The genetic alterations of MIDN in cancers are investigated using the cBioPortal database. The STRING, GeneMANIA, DAVID, and Human Protein Atlas are harnessed to identify and analyze MIDN-interacted proteins. The Sangerbox 3.0 platform (a pan-cancer analysis module) is used to measure the correlations between the MIDN level and the tumor immune microenvironment, stemness, immune cell infiltration, tumor mutational burden, immune checkpoint genes, and RNA modification genes. Immunofluorescence, qRT-PCR, and Western blotting assays were used to evaluate the biological roles of MIDN in breast and gastric cancer cells. Results: MIDN expression was dysregulated in many cancers and associated with prognosis in several cancers, such as esophageal cancer. MIDN was mutated in 1.7% of cancers, and deep deletion was the dominant mutation type. NR4A1, PSMC1, and EGR1 were selected as MIDN-interacted proteins, and these four molecules were co-expressed in pancreatic cancer, liver cancer, urothelial cancer, melanoma, and breast cancer. MIDN expression was significantly correlated with the infiltration of CD8+ T cell, CD4+ T cell, B cell, macrophage, neutrophil, and DC both in prostate adenocarcinoma and liver hepatocellular carcinoma. The MIDN level was correlated with several immune checkpoint genes, such as VEGFA, and RNA modification genes such as YTHDF1, YTHDF2, YTHDF3, and YTHDC1 in cancers. Furthermore, in breast cancer cells, the downregulation of MIDN suppressed the colony formation abilities and lessened cell-cycle-associated and stemness-associated genes; in gastric cancer, the knockdown of MIDN diminished the mRNA levels of Nanog and LDHA. Strikingly, silence of MIDN upregulated FTO protein expression in both breast and gastric cancer cells. Conclusions: Our findings demonstrate the expression, prognostic value, mutation status, interacting proteins, methylation status, and correlations with the tumor immune microenvironment of MIDN. MIDN will be developed as a potential therapeutic target and a prognosis biomarker. Full article
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Figure 1

Figure 1
<p>MIDN expression in normal and tumor tissues. (<b>A</b>) MIDN mRNA level in normal tissues in the GTEx database. (<b>B</b>) MIDN mRNA levels in cancer cell lines in the Depmap database. MIDN expression in tumor tissues and normal tissues in the Sangerbox 3.0 platform (<b>C</b>), TCGA, and GTEx data, and (<b>D</b>) TCGA data. -, not significant; *, <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.</p>
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<p>Correlation analysis of MIDN expression with cancer stages and prognosis. (<b>A</b>) The correlation (GEPIA2 database) between MIDN expression and stages of COAD, KIRP, OV, and UCEC. The correlation (Sangerbox 3.0 platform) between MIDN expression and OS (<b>B</b>), DSS (<b>C</b>), PFI (<b>D</b>), and DFI (<b>E</b>) in cancers.</p>
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<p>Correlation analysis of MIDN expression with cancer prognosis. (<b>A</b>) Survival map of MIDN expression in pan-cancer (GEPIA2 database). The correlation (GEPIA2 database) between MIDN expression and DFS in CESC (<b>B</b>), ESCA (<b>C</b>), and UVM (<b>D</b>), and the dotted line indicates the 95% confidence interval. The correlation (Kaplan–Meier Plotter database) between MIDN expression and OS in EAC (<b>E</b>) and ESCC (<b>F</b>), and RFS in EAC (<b>G</b>) and ESCC (<b>H</b>).</p>
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<p>Genomic changes in MIDN in cancers. (<b>A</b>) Summary of MIDN genetic alterations, and the asterisk indicates “not all samples are profiled”. (<b>B</b>) MIDN genetic alterations in TCGA pan-cancer data. (<b>C</b>) Copy number changes in MIDN in TCGA pan-cancer data. (<b>D</b>) Mutation information of MIDN genes. (<b>E</b>) The co-occurrence of gene alteration in the MIDN-altered group and unaltered group. Correlations of MIDN alterations with DFS (<b>F</b>), PFS (<b>G</b>), DSS (<b>H</b>), and OS (<b>I</b>) in TCGA pan-cancer data.</p>
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<p>Interacting proteins of MIDN in cancers. The PPI networks were created by the STRING (<b>A</b>) and GeneMANIA (<b>B</b>) programs. KEGG (<b>C</b>), biological process (<b>D</b>), cellular component (<b>E</b>), and molecular function (<b>F</b>) enrichment analyses were carried out by the DAVID software (<a href="https://david.ncifcrf.gov" target="_blank">https://david.ncifcrf.gov</a> (accessed on 28 October 2023)). (<b>G</b>) The protein levels of MIDN, NR4A1, PSMC1, and EGR1 in cancers were evaluated using the Human Protein Atlas database. (<b>H</b>) The immunohistochemistry staining of MIDN, NR4A1, PSMC1, and EGR1 in urothelial cancer (Human Protein Atlas database).</p>
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<p>Interacting proteins of MIDN in cancers. (<b>A</b>) Immunohistochemistry staining of MIDN, NR4A1, PSMC1, and EGR1 in liver cancer, pancreatic cancer, breast cancer, and melanoma (Human Protein Atlas database). (<b>B</b>) Subcellular locations of MIDN, NR4A1, PSMC1, and EGR1 in HPA database. (<b>C</b>) Summary of genetic alterations of MIDN, NR4A1, PSMC1, and EGR1, and the asterisk indicates “not all samples are profiled”. (<b>D</b>) The co-occurrence analysis among MIDN, NR4A1, PSMC1, and EGR1 in TCGA pan-cancer data.</p>
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<p>Methylation status and single-cell analysis of MIDN in cancers. The methylation status of the MIDN gene in KIRP (<b>A</b>) and LUSC (<b>B</b>). (<b>C</b>–<b>E</b>) The roles of MIDN in different biological processes were analyzed by the CancerSEA database, and *** indicates “<span class="html-italic">p</span> &lt; 0.001”.</p>
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<p>Correlation analysis of MIDN expression with the tumor immune microenvironment in cancers. The significant correlations between MIDN expression and immune infiltration (<b>A</b>), StromalScore; (<b>B</b>), ImmuneScore; (<b>C</b>), ESTIMATEScore.</p>
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<p>Correlation analysis of MIDN expression with the immune cell infiltration, stemness, and tumor mutational burden in cancers. (<b>A</b>) Correlations between MIDN expression and the immune cell infiltration in cancers. *, <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. (<b>B</b>) Correlations between MIDN expression and stemness in cancers. (<b>C</b>) Correlations between MIDN expression and tumor mutational burden in cancers.</p>
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<p>Correlation analysis of MIDN expression with the immune checkpoint genes in cancers. *, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Correlation analysis of MIDN expression with the RNA modification genes in cancers. *, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The knockdown of MIDN suppresses colony formation and declines the expression of cell cycle-associated and stemness-associated genes in breast cancer. (<b>A</b>) The immunofluorescence staining of MIDN in MCF-7 breast cancer cells. (<b>B</b>–<b>F</b>) qRT-PCR analysis of interested genes. (<b>G</b>) Colony formation ability after MIDN knockdown. (<b>H</b>,<b>I</b>) The protein levels of MIDN, FTO, and ALKBH5 were detected using a Western blotting assay. *, <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.</p>
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<p>The knockdown of MIDN upregulates FTO in gastric cancer. (<b>A</b>) The immunofluorescence staining of MIDN in SNU-216 gastric cancer cells. (<b>B</b>–<b>D</b>) qRT-PCR analysis of interested genes. (<b>E</b>) Protein levels of MIDN, AIFM2, and FTO were detected using a Western blotting assay. **, <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.</p>
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24 pages, 6534 KiB  
Review
Advancements in Multiple Myeloma Therapies: A Comprehensive Review by Disease Stage
by Hager Hisham El Khatib, Kanz Abdulla, Layla Khaled Nassar, Mariam Gouda Ellabban and Andreas Kakarougkas
Lymphatics 2025, 3(1), 2; https://doi.org/10.3390/lymphatics3010002 - 22 Jan 2025
Viewed by 282
Abstract
Multiple myeloma is an incurable hematologic malignancy arising from plasma cells. The uncontrolled growth of monoclonal plasma cells leads to an abnormal overproduction of immunoglobulins. The recommended course of treatment for MM is according to disease progression and responses to therapeutic intervention, highlighting [...] Read more.
Multiple myeloma is an incurable hematologic malignancy arising from plasma cells. The uncontrolled growth of monoclonal plasma cells leads to an abnormal overproduction of immunoglobulins. The recommended course of treatment for MM is according to disease progression and responses to therapeutic intervention, highlighting the necessity for multiple treatment options that alleviate different parts of MM. This comprehensive review provides insights into the current treatments and how to take preventative and prognostic measures. In advanced MM, osteoporosis is a common symptom that originates from a lack of regulation in osteoclast activity and bone resorption. Bisphosphonates such as zoledronic acid and pamidronate along with monoclonal antibodies such as denosumab hinder osteoclast function and aid in reducing the risk of fractures in patients with advanced MM. For targeted therapy approaches, proteasome inhibitors impede protein degradation pathways that cause an accumulation of misfolded proteins promoting cancer cell proliferation in patients with MM. CAR-T is another targeted therapy that can utilize T cells to target and isolate MM cells. Overall, this review highlights the frontrunners of treatments for those diagnosed with MM. Full article
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Figure 1

Figure 1
<p>Action of bisphosphonates and denosumab against MM-induced hypercalcemia. Note: Osteoporosis in multiple myeloma (MM) occurs when the Notch receptor on MM cells binds to Jagged, triggering RANKL production. RANKL promotes osteoclast formation, leading to bone degradation and the release of factors that fuel MM growth. Bisphosphonates inhibit bone resorption by targeting osteoclasts, while denosumab binds to RANKL, preventing osteoclast activation.</p>
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<p>Mechanism of Action of Proteasome Inhibitors in Myeloma Cells. Note: Proteasome inhibition leads to ER stress, disrupting cell regulation and triggering apoptosis through JNK and p53 activation, which upregulates NOXA and Bax, causing mitochondrial dysfunction [<a href="#B42-lymphatics-03-00002" class="html-bibr">42</a>,<a href="#B43-lymphatics-03-00002" class="html-bibr">43</a>]. Bortezomib reversibly inhibits β5 and β1 activities, affecting NF-κB and cell adhesion [<a href="#B44-lymphatics-03-00002" class="html-bibr">44</a>], while carfilzomib irreversibly blocks chymotrypsin-like activity [<a href="#B45-lymphatics-03-00002" class="html-bibr">45</a>]. (Adapted from [<a href="#B43-lymphatics-03-00002" class="html-bibr">43</a>].)</p>
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<p>Mechanism of Action of Monoclonal Antibodies Daratumumab and Elotuzumab on Myeloma Cells. Note: Daratumumab, a CD38-targeting antibody, acts against myeloma cells via immune and apoptotic pathways, including ADCC, ADCP, CDC, and suppression of CD38-positive immune suppressor cells. Elotuzumab targets SLAMF7 on myeloma cells, inducing NK cell-mediated ADCC. (Adapted from [<a href="#B49-lymphatics-03-00002" class="html-bibr">49</a>].)</p>
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<p>Allogeneic and Autologous Adoptive Transfer of CAR-based Immune Cells. (Adapted from [<a href="#B56-lymphatics-03-00002" class="html-bibr">56</a>].)</p>
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<p>The Current Development Stages of Major Types of Anti-BCMA CAR-based Immune Cells. Note: Overview of the development stages of BCMA-targeting CAR therapies in multiple myeloma (MM). The figure illustrates the progress of various BCMA CAR therapies, including both autologous and allogeneic approaches, across different immune cell types (αβT, γδT, NK, iNKT, etc.) in the treatment pipeline. Conventional autologous BCMA CAR-T therapies have reached post-marketing stages, while several allogeneic BCMA-targeting CAR-T therapies (including ALLO-715) are in clinical trials (such as NCT04093596). Other CAR therapies using natural killer (NK) and invariant natural killer T cells (iNKT) are still in pre-clinical stages but demonstrate promising in vitro and in vivo results against MM. (Adapted from [<a href="#B56-lymphatics-03-00002" class="html-bibr">56</a>].)</p>
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<p>Mechanism of Action of BsAbs. Note: Illustration of the MM cell expressing BCMA, GPRC5D, and FcRH5 with BsAbs converging between BCMA and T cell, leading to the cytotoxic response of CD3. (Adapted from [<a href="#B70-lymphatics-03-00002" class="html-bibr">70</a>].)</p>
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<p>Mechanism of Action of Immunocytokine Therapy. Note: This diagram illustrates how immunocytokines function to combine the immune-stimulating qualities of cytokines with the targeting efficacy of antibodies. Immunocytokines boost the immune response against cancer by attaching to tumor cells and stimulating immune cells. This results in decreased tumor growth, higher tumor cell death, and a stronger immunological attack of the cancer cells. Immunocytokines are an effective therapeutic method in cancer treatment due to their dual mechanism. (Adapted from [<a href="#B71-lymphatics-03-00002" class="html-bibr">71</a>]).</p>
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<p>SPEP test results example. Note: Illustration of the difference between the M-protein spikes in the normal SPEP result and the abnormal result (International Myeloma Foundation, 2021) [<a href="#B72-lymphatics-03-00002" class="html-bibr">72</a>].</p>
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<p>Graphical Representation of the Main Drugs with Direct and Indirect Anti-angiogenic Effects in MM. (<b>a</b>) monoclonal antibodies; (<b>b</b>) bispecific molecules and recombinant proteins; (<b>c</b>) tyrosin kinase inhibitors; (<b>d</b>) immunomodulatory drugs; (<b>e</b>) proteasome inhibitors; (<b>f</b>) bisphosphonates; (<b>g</b>) alkylating agents; and (<b>h</b>) glucocorticoids. (Adapted from [<a href="#B77-lymphatics-03-00002" class="html-bibr">77</a>]).</p>
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20 pages, 4631 KiB  
Article
Global Transcriptomic Analysis of Inbred Lines Reveal Candidate Genes for Response to Maize Lethal Necrosis
by Ann Murithi, Gayathri Panangipalli, Zhengyu Wen, Michael S. Olsen, Thomas Lübberstedt, Kanwarpal S. Dhugga and Mark Jung
Plants 2025, 14(2), 295; https://doi.org/10.3390/plants14020295 - 20 Jan 2025
Viewed by 457
Abstract
Maize lethal necrosis (MLN) is a significant threat to food security in Sub-Saharan Africa (SSA), with limited commercial inbred lines displaying tolerance. This study analyzed the transcriptomes of four commercially used maize inbred lines and a non-adapted inbred line, all with varying response [...] Read more.
Maize lethal necrosis (MLN) is a significant threat to food security in Sub-Saharan Africa (SSA), with limited commercial inbred lines displaying tolerance. This study analyzed the transcriptomes of four commercially used maize inbred lines and a non-adapted inbred line, all with varying response levels to MLN. RNA-Seq revealed differentially expressed genes in response to infection by maize chlorotic mottle virus (MCMV) and sugarcane mosaic virus (SCMV), the causative agents of MLN. Key findings included the identification of components of the plant innate immune system, such as differentially regulated R genes (mainly LRRs), and activation/deactivation of virus resistance pathways, including RNA interference (RNAi) via Argonaute (AGO), Dicer-like proteins, and the ubiquitin–proteasome system (UPS) via RING/U-box and ubiquitin ligases. Genes associated with redox signaling, WRKY transcription factors, and cell modification were also differentially expressed. Additionally, the expression of translation initiation and elongation factors, eIF4E and eIF4G, correlated with the presence of MLN viruses. These findings provide valuable insights into the molecular mechanisms of MLN resistance and highlight potential gene candidates for engineering or selecting MLN-resistant maize germplasm for SSA. Full article
(This article belongs to the Special Issue Crop Functional Genomics and Biological Breeding)
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Figure 1
<p>Phenotypic effect of MLN. Average field MLN phenotypic scores of five lines collected in Naivasha, Kenya.</p>
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<p>Heatmap clustering of 2503 differentially expressed genes based on their normalized counts. Each row of the heatmap represents the gene count in each genotype before and after inoculation. Red indicates high counts of a gene in a biological replicate, while green indicates lower counts of a gene. “Null” indicates the expression before inoculation, and “treated” indicates expression after MLN inoculation.</p>
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<p>Principal component analysis: Plot generated from normalized gene expression counts of each genotype under MLN.</p>
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<p>Differentially expressed genes (DEGs). (<b>A</b>) Venn diagram of the DEGs in five lines under MLN stress, (<b>B</b>) Venn diagram of the DEGs in CIMMYT lines, and (<b>C</b>) Venn diagram of the DEGs of the genotype vs. genotype comparison.</p>
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<p>Gene Ontology (GO) enrichment of differentially expressed genes (DEGs) after MLN. A Fisher’s exact test and Bonferroni correction were used to identify the significantly (<span class="html-italic">p</span>-value &lt; 0.05) enriched GO terms from the total DEGs across the CIMMYT lines relative to all genes in the maize genome. The first group represents enriched GO terms in each genotype, while the second group represents GO enrichment after contrasting expressions between the lines. The <span class="html-italic">Y</span>-axis represents the DEGs’ biological functions, biological process (green), molecular function (orange), and cellular component (purple). The <span class="html-italic">X</span>-axis represents the positive values of the estimated <span class="html-italic">p</span>-values, calculated as −log10(<span class="html-italic">p</span>-value) via GO term analysis.</p>
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<p>Gene Ontology (GO) and KEGG enrichment of DEGs in KS23-6. Column (<b>A</b>) shows the GO terms and KEGG of DEGs in KS23-6 after comparing the control vs. treatment groups, and column (<b>B</b>) shows GO terms and KEGG pathways after comparing KS23-6 DEGs to CML543 and CML536. In both, a Fisher’s exact test and Bonferroni correction were used to identify the significantly (<span class="html-italic">p</span>-value &lt; 0.05) enriched GO terms and KEGG pathways. In the GO term bar charts, the <span class="html-italic">Y</span>-axis represents the DEGs’ biological process (green), molecular function (orange), and cellular component (purple), while the <span class="html-italic">X</span>-axis represents the positive values of the estimated <span class="html-italic">p</span>-values, calculated as −log10(<span class="html-italic">p</span>-value) via Go term analysis.</p>
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<p>Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A Fisher’s exact test and Bonferroni correction were used to identify the significantly (<span class="html-italic">p</span>-value &lt; 0.05) enriched KEGG terms from the total DEGs. The first group represents enriched GO terms in each genotype, while the second group represents GO enrichment after contrasting expressions between the lines. The <span class="html-italic">Y</span>-axis represents the KEGG terms. The <span class="html-italic">X</span>-axis represents the positive values of the estimated <span class="html-italic">p</span>-values, calculated as −log10(<span class="html-italic">p</span>-value).</p>
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<p>Differential expression of eukaryotic translation initiation factors (eIF4) across the genotypes based on the log2foldchange. The <span class="html-italic">x</span>-axis represents the genotypes. The <span class="html-italic">Y</span>-axis represents the expression value of each gene within a genotype based on the log2foldchange. (The numbers after the underscores indicate the chromosome locations).</p>
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15 pages, 4078 KiB  
Article
NLRC3 Attenuates Antiviral Innate Immune Response by Targeting IRF7 in Grass Carp (Ctenopharyngodon idelus)
by Lei Zhang, Haitai Chen, Xiang Zhao, Youcheng Chen, Shenpeng Li, Tiaoyi Xiao and Shuting Xiong
Int. J. Mol. Sci. 2025, 26(2), 840; https://doi.org/10.3390/ijms26020840 - 20 Jan 2025
Viewed by 273
Abstract
NLRC3 belongs to the NOD-like receptor family and is recognized as a modulator of innate immune mechanisms. In this study, we firstly report that Ctenopharyngodon idelus NLRC3 (CiNLRC3) acts as a negative regulator in the antiviral immune response. Cinlrc3 is ubiquitously [...] Read more.
NLRC3 belongs to the NOD-like receptor family and is recognized as a modulator of innate immune mechanisms. In this study, we firstly report that Ctenopharyngodon idelus NLRC3 (CiNLRC3) acts as a negative regulator in the antiviral immune response. Cinlrc3 is ubiquitously expressed across tested tissues, displaying particularly high expression in the intestine, spleen, gill and kidney. Notably, Cinlrc3 expression is markedly upregulated following grass carp reovirus (GCRV) infection both in vivo and in vitro. Functional assays reveal that the overexpression of CiNLRC3 hampers cellular antiviral responses, thereby facilitating viral replication. Conversely, the silencing of CiNLRC3 through siRNA transfection enhances these antiviral activities. Additionally, CiNLRC3 substantially diminishes the retinoic acid-inducible gene I (RIG-I)-like receptor (RLR)-mediated interferon (IFN) response in fish. Subsequent molecular investigations indicates that CiNLRC3 interacts with the RLR molecule node, IRF7 but not IRF3, by degrading the IRF7 protein in a proteasome-dependent manner. Furthermore, CiNLRC3 co-localizes with CiIRF7 in the cytoplasm and impedes the IRF7-induced IFN response, resulting in impairing IRF7-mediated antiviral immunity. Summarily, these findings underscore the critical inhibitory role of teleost NLRC3 in innate immunity, offering new perspectives on its regulatory functions and potential as a target for resistant breeding in fish. Full article
(This article belongs to the Section Molecular Immunology)
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<p>CiNLRC3 sequence analysis. (<b>A</b>) Structure illustration of CiNLRC3 protein. Structure domains were indicated in a dark frame. (<b>B</b>) Multiple alignment of NLRC3 protein sequences from grass carp (OR282536.1), blunt snout bream (XM_048174542.1), zebrafish (XM_009297629.4), common carp (XM_042752008.1), human (FJ889357.1) and mouse (XM_011245902.3). The NACHT domain is marked by red underline and the LRR domains are indicated by blue underlines.</p>
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<p>Phylogenetic tree of NLRC3 protein homologs. The phylogenetic tree was constructed using the neighbor-joining method implemented in the MEGA 6.0 software. Bootstrap confidence values, displayed at the nodes of the tree, were calculated based on 1,000 bootstrap replications. NLRC3 homologs are listed below. Mammalian: <span class="html-italic">Homo sapiens</span> (NP_849172.2), <span class="html-italic">Pan troglodytes</span> (XP_016784787.3), <span class="html-italic">Oryctolagus cuniculus</span> (XP_051692203.1), <span class="html-italic">Mus musculus</span> (NP_001074749.1), <span class="html-italic">Castor canadensis</span> (XP_020012107.1), <span class="html-italic">Heterocephalus glaber</span> (XP_004864808.1), <span class="html-italic">Acinonyx jubatus</span> (XP_053069323.1), <span class="html-italic">Panthera tigris</span> (XM_042971676.1), <span class="html-italic">Bos taurus</span> (XP_059737649.1), <span class="html-italic">Equus caballus</span> (XP_001499317.2), <span class="html-italic">Panthera leo</span> (XM_042921978.1); Reptilian: <span class="html-italic">Varanus komodoensis</span> (XP_044289647.1), <span class="html-italic">Bodarcis raffonei</span> (XP_053220626.1), <span class="html-italic">Zootoca vivipara</span> (XP_034987245.1); Avian: <span class="html-italic">Phalacrocorax carbo</span> (XP_064318183.1), <span class="html-italic">Gallus gallus</span> (XP_015150161.3), <span class="html-italic">Haemorhous mexicanus</span> (XP_059718048.1), <span class="html-italic">Passer domesticus</span> (XP_064246427.1), <span class="html-italic">Corvus cornix cornix</span> (XP_019136980.2), <span class="html-italic">Taeniopygia guttata</span> (XP_030140601.3; Amphibians: <span class="html-italic">Xenopus tropicalis</span> (XP_017952746.1), <span class="html-italic">Bufo gargarizans</span> (XP_044160788.1), <span class="html-italic">Rana temporaria</span> (XP_040214376.1); Cartilaginous fish: <span class="html-italic">Scyliorhinus_canicula</span> (XP_038676696.1), <span class="html-italic">Heterocephalus_glaber</span> (XP_004864808.1), <span class="html-italic">Callorhinchus_milii</span> (XP_007891876.1), <span class="html-italic">Castor_canadensis</span> (XP_020012107.1), <span class="html-italic">Rhinatrema_bivittatum</span> (XP_029432650.1), <span class="html-italic">Carcharodon_carcharias</span> (XP_041062594.1), <span class="html-italic">Mobula_hypostoma</span> (XP_062915561.1), <span class="html-italic">Hypanus_sabinus</span> (XP_059834825.1), <span class="html-italic">Pristis_pectinata</span> (XP_051877340.1), <span class="html-italic">Rhincodon_typus</span> (XP_048465466.1), <span class="html-italic">Chiloscyllium_plagiosum</span> (XP_043567467.1); and Teleost: <span class="html-italic">Danio_rerio</span> (XM_009297629.4), <span class="html-italic">Ctenopharyngodon idella</span> (XP_051737605.1), <span class="html-italic">Megalobrama_amblycephala</span> (XP_048030497.1), <span class="html-italic">Carassius_gibelio</span> (XP_052451976.1), <span class="html-italic">Cyprinus_carpio</span> (XP_042607942.1), <span class="html-italic">Oryzias_latipes</span> (XP_004080575.1), <span class="html-italic">Oreochromis_niloticus</span> (XP_003438651.1), <span class="html-italic">Lates_calcarifer</span> (XP_018537323.1), <span class="html-italic">Larimichthys_crocea</span> (XP_010730059.1), <span class="html-italic">Siniperca chuatsi</span> (XM_044177955.1), <span class="html-italic">Anguilla rostrata</span> (XP_064178397.1).</p>
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<p><span class="html-italic">Cinlrc3</span> is induced after GCRV infection. (<b>A</b>) The distribution of <span class="html-italic">Cinlrc3</span> in the intestine, spleen, gill, kidney, heart, liver, head kidney, brain, and skin of grass carp. (<b>B</b>) The CiNLRC3 protein is in the cytoplasm. Immunofluorescence cellular localization is performed using constructed HA-CiNLRC3. The plasmid of CiNLRC3-HA is transfected in CIK cells, and the HA antibody is utilized to detect the CiNLRC3-HA fusion protein which is indicated in red fluorescence. DAPI is used for the nuclear staining. Scale bar: 20 μm. (<b>C</b>,<b>D</b>) CIK cells are challenged with GCRV-JX0901, and cell samples are collected at 0 h, 12 h, 24 h, 36 h, and 48 h. Then, the transcriptional levels of <span class="html-italic">ifn1</span> (<b>C</b>) and <span class="html-italic">Cinlrc3</span> (<b>D</b>) are detected by qPCR. (<b>E</b>–<b>P</b>) Grass carps are immersed in GCRV-Huan1307 for 30 min and the liver, spleen, kidney and gill are sampled at 0, 1, 3 and 7 dpi. <span class="html-italic">Cinlrc3</span>, <span class="html-italic">vp7</span> and <span class="html-italic">isg15</span> mRNA in the liver (<b>E</b>,<b>I</b>,<b>M</b>), spleen (<b>F</b>,<b>J</b>,<b>N</b>), kidney (<b>G</b>,<b>K</b>,<b>O</b>) and gill (<b>H</b>,<b>L</b>,<b>P</b>) are detected using qPCR. Letters with the same superscript indicate no significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>CiNLRC3 dampens the cellular antiviral response. (<b>A</b>) CIK cells were seeded into 6-well plates and transfected with an EV or CiNLRC3 (2 μg), respectively. After transfection for 24 h, GCRV was added into the transfected wells. After 36 hpi, the cells were fixed with 4% paraformaldehyde, washed three times with PBS, and then stained with 1% crystal lavender. (<b>B</b>–<b>E</b>) Under the same transfected experiments above, samples were collected at 36 hpi. qPCR was performed to detect mRNA levels of <span class="html-italic">Cinlrc3</span> (<b>B</b>), <span class="html-italic">vp4</span> (<b>C</b>), <span class="html-italic">vp5</span> (<b>D</b>) and <span class="html-italic">ifn1</span> (<b>E</b>). (<b>F</b>,<b>J</b>) CIK cells were seeded into 6-well plates and transfected with siRNA-NC or siRNA-1/2, respectively. After transfection for 12 h, GCRV was added into the transfected wells. After 36 hpi, the cells samples were collected and qPCR was applied to detect the expression of <span class="html-italic">Cinlrc3</span> (<b>F</b>), <span class="html-italic">vp4</span> (<b>G</b>), <span class="html-italic">vp5</span> (<b>H</b>), <span class="html-italic">mx</span> (<b>I</b>) and <span class="html-italic">viperin</span> (<b>J</b>). Asterisks indicate significant differences (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>CiNLRC3 blocks the RLR-mediated IFN response. (<b>A</b>) The GCO cells are seeded in a 24-well plate overnight and then co-transfected with an EV or CiNLRC3 (500 ng), CiIFN1pro-Luc (100 ng), and pRL-TK (10 ng). Moreover, 12 h later, poly (I; C), GCRV, SVCV is added into cells, respectively. Another 24 h later, the samples are collected after 24 h following a dual-luciferase activity assay. (<b>B</b>) The GCO cells are seeded in a 24-well plate overnight and then an EV or the CiNLRC3 (200 ng) plasmid and CiIFN1pro-Luc (100ng), PRL—TK (10 ng), are transfected into the cells. At the same time, the expressing plasmids including RIG-I, MAD5, MAVS, MITA, TBK1, IRF3, and IRF7 (200 ng) are transfected into the cells, respectively. In addition, 24 h later, the samples are collected for the dual-luciferase activity assay. Asterisks indicate significant differences (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>NLRC3 interacts with IRF7 and degrades IRF7 in a proteasome-dependent manner (<b>A</b>) MITA, TBK1, IRF3 and IRF7 are NLRC3-interacting proteins. GCO cells are seeded in 10 cm<sup>2</sup> plates overnight, and then CiNLRC3 is co-transfected with EGFP-HA, MITA-HA, TBK1-HA, IRF3-HA, and IRF7-HA (5 μg each). After 36 h, the cells are collected for the Co-IP experiment. (<b>B</b>–<b>C</b>) NLRC3 degrades IRF7 but not IRF3. GCO cells are seeded in 6-well plates overnight, and then IRF3 (<b>B</b>) or IRF7-HA (<b>C</b>) (1 μg) and NLRC3-Flag (0.3, 0.5, 0.8, 1.0 μg) are co-transfected, respectively. After 36 h, cells are collected, and their bands are detected by Western blotting. (<b>D</b>) NLRC3 degrades IRF7 in a proteasome-dependent manner. GCO cells are seeded in three 6-well plates overnight, one plate co-transfected with IRF7-HA and an EV and the other two plates co-transfected with a repeat of IRF7-HA (1 μg) and NLRC3-HA (1.0 μg). Moreover, 24 h later, the indicated cells are treated with MG132 (20 μM) for 6 h. After 36 h, cells are collected, and their bands are detected by Western blotting. (<b>E</b>,<b>F</b>) IRF7 is co-located with NLRC3. 293T cells are seeded in 12-well plates overnight and transfected with Cherry-IRF7 (<b>E</b>), CiNLRC3-EGFP or EGFP and Cherry-IRF7 (1 μg each) (<b>F</b>) and fixed with 4% paraformaldehyde for 15 min after 24 h. Then, PBS is used for washing three times, DAPI is used for staining for 5 min, and photographs are taken under the microscope.</p>
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<p>CiNLRC3 impairs IRF7-mediated cellular antiviral response. (<b>A</b>–<b>E</b>) CIK cells are seeded in six-well plates overnight, and then EV (1 μg) or EV (0.5 μg) + CiIRF7 (0.5 μg) or CiNLRC3 (0.5 μg) + CiIRF7 (0.5 μg), respectively, and GCRV are added 24 h later. The mRNA levels of isg15, isg20 (<b>A</b>,<b>B</b>), vp5, vp6 and vp7 (<b>C</b>–<b>E</b>) are detected by qPCR after another 24 h. Letters with the same superscript indicate no significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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29 pages, 3188 KiB  
Review
Unlocking the Therapeutic Potential of Algae-Derived Compounds in Hematological Malignancies
by Tamara Vujović, Tina Paradžik, Sanja Babić Brčić and Roberto Piva
Cancers 2025, 17(2), 318; https://doi.org/10.3390/cancers17020318 - 20 Jan 2025
Viewed by 488
Abstract
Algae are a rich source of bioactive compounds that have a wide range of beneficial effects on human health and can show significant potential in the treatment of hematological malignancies such as leukemia, lymphoma, and multiple myeloma. These diseases often pose a therapeutic [...] Read more.
Algae are a rich source of bioactive compounds that have a wide range of beneficial effects on human health and can show significant potential in the treatment of hematological malignancies such as leukemia, lymphoma, and multiple myeloma. These diseases often pose a therapeutic challenge despite recent advances in treatment (e.g., the use of immunomodulatory drugs, proteasome inhibitors, CD38 monoclonal antibodies, stem cell transplant, and targeted therapy). A considerable number of patients experience relapses or resistance to the applied therapies. Algal compounds, alone or in combination with chemotherapy or other more advanced therapies, have exhibited antitumor and immunomodulatory effects in preclinical studies that may improve disease outcomes. These include the ability to induce apoptosis, inhibit tumor growth, and improve immune responses. However, most of these studies are conducted in vitro, often without in vivo validation or clinical trials. This paper summarizes the current evidence on the in vitro effects of algae extracts and isolated compounds on leukemia, lymphoma, and myeloma cell lines. In addition, we address the current advances in the application of algae-derived compounds as targeted drug carriers and their synergistic potential against hematologic malignancies. Full article
(This article belongs to the Special Issue Natural Compounds in Cancers)
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<p>An overview of general steps to be taken before determining the bioactive properties of compounds present in collected algal biomass.</p>
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<p>Algal compounds with the most promising anticancer activities and their effects on tumor cells.</p>
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<p>Green synthesis of algal nanoparticles.</p>
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17 pages, 3385 KiB  
Review
The Role of E3 Ubiquitin Ligase Gene FBK in Ubiquitination Modification of Protein and Its Potential Function in Plant Growth, Development, Secondary Metabolism, and Stress Response
by Yuting Wu, Yankang Zhang, Wanlin Ni, Qinghuang Li, Min Zhou and Zhou Li
Int. J. Mol. Sci. 2025, 26(2), 821; https://doi.org/10.3390/ijms26020821 - 19 Jan 2025
Viewed by 281
Abstract
As a crucial post-translational modification (PTM), protein ubiquitination mediates the breakdown of particular proteins, which plays a pivotal role in a large number of biological processes including plant growth, development, and stress response. The ubiquitin-proteasome system (UPS) consists of ubiquitin (Ub), ubiquitinase, deubiquitinating [...] Read more.
As a crucial post-translational modification (PTM), protein ubiquitination mediates the breakdown of particular proteins, which plays a pivotal role in a large number of biological processes including plant growth, development, and stress response. The ubiquitin-proteasome system (UPS) consists of ubiquitin (Ub), ubiquitinase, deubiquitinating enzyme (DUB), and 26S proteasome mediates more than 80% of protein degradation for protein turnover in plants. For the ubiquitinases, including ubiquitin-activating enzyme (E1), ubiquitin-conjugating enzyme (E2), and ubiquitin ligase (E3), the FBK (F-box Kelch repeat protein) is an essential component of multi-subunit E3 ligase SCF (Skp1-Cullin 1-F-box) involved in the specific recognition of target proteins in the UPS. Many FBK genes have been identified in different plant species, which regulates plant growth and development through affecting endogenous phytohormones as well as plant tolerance to various biotic and abiotic stresses associated with changes in secondary metabolites such as phenylpropanoid, phenolic acid, flavonoid, lignin, wax, etc. The review summarizes the significance of the ubiquitination modification of protein, the role of UPS in protein degradation, and the possible function of FBK genes involved in plant growth, development, secondary metabolism, and stress response, which provides a systematic and comprehensive understanding of the mechanism of ubiquitination and potential function of FBKs in plant species. Full article
(This article belongs to the Special Issue New Insights into Environmental Stresses and Plants)
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<p>Classification of different types of ubiquitination processes: (<b>a</b>) mono-ubiquitination, (<b>b</b>) multimono-ubiquitination, (<b>c</b>) linear polyubiquitination, and (<b>d</b>) branching polyubiquitination.</p>
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<p>Post-translational modifications (PTMs), ubiquitination, and ubiquitin–26S proteasome system (UPS) in plants. Ub, ubiquitin; DUB, deubiquitinating enzyme; RING, Really Interesting New Gene; HECT, Homology to E6-associated Carboxy-Terminus; RBR, Ring Between Ring; CRLs, Cullin-RING Ligases; APC/C, Anaphase Promoting Complex/Cyclosome; CBC VHL, Cullin-Elongin-BC-VHL; SCF, SKP1-Cullin1-F-box; BTB, Bric-a-brac-Tram track-Broad; DDB, DNA damage-binding domain-containing; APC, an-aphase-promoting complex; CUL1, Cullin1; RBX1, RING Box-1; SKP1, S-phase Kinase-associated Protein 1; FBK, Kelch structure; FBL, LRR repeat-rich structural domain; FBW, WD40 repeat structure; FBT, Tub structure; FBP, Phloem Protein 2 domain; FBA-D, F-box structure-associated domain. A rectangular box represents a component which cooperates with other components to perform a function in the system, and an oval box represents a subfamily member which exhibits an independent function in the system. Text highlighted in red is the F-Box gene which is discussed in details in this review.</p>
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<p>A working model of protein degradation depending on the ubiquitin–26S proteasome system (UPS) in plants. ADP, adenosine diphosphate; ATP, adenosine triphosphate; CUL1, Cullin1; DUB, deubiquitinating enzyme; E1, ubiquitin-activating enzyme; E2, ubiquitin-conjugating enzyme; E3, ubiquitin-ligating enzyme; RBX1, RING Box-1; SKP1, S-phase Kinase-associated Protein 1; SCF, Skp1-Cullin 1-F-box; Ub, ubiquitin.</p>
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<p>The function of <span class="html-italic">FBK</span> genes related to secondary metabolism in different plant species. The red or green background indicates that the gene positively or negatively regulates the biosynthesis of secondary metabolites, respectively: red=positive and green=negative. Different blue backgrounds indicate different secondary metabolites. All genes in the figure encode F-box protein with Kelch structures. The numbers in parentheses indicate references related to relevant findings. Genes and their correlative references: <span class="html-italic">AtSnRK1</span> [<a href="#B83-ijms-26-00821" class="html-bibr">83</a>]; <span class="html-italic">AtKFB01</span> [<a href="#B24-ijms-26-00821" class="html-bibr">24</a>,<a href="#B80-ijms-26-00821" class="html-bibr">80</a>,<a href="#B85-ijms-26-00821" class="html-bibr">85</a>]; <span class="html-italic">AtKFB20</span> [<a href="#B24-ijms-26-00821" class="html-bibr">24</a>,<a href="#B80-ijms-26-00821" class="html-bibr">80</a>,<a href="#B81-ijms-26-00821" class="html-bibr">81</a>,<a href="#B85-ijms-26-00821" class="html-bibr">85</a>]; <span class="html-italic">AtKFB50</span> [<a href="#B24-ijms-26-00821" class="html-bibr">24</a>,<a href="#B80-ijms-26-00821" class="html-bibr">80</a>,<a href="#B85-ijms-26-00821" class="html-bibr">85</a>]; <span class="html-italic">KFB39</span> [<a href="#B80-ijms-26-00821" class="html-bibr">80</a>,<a href="#B85-ijms-26-00821" class="html-bibr">85</a>]; <span class="html-italic">KFB<sup>CHS</sup> </span> [<a href="#B87-ijms-26-00821" class="html-bibr">87</a>]; <span class="html-italic">CmKFB</span> [<a href="#B86-ijms-26-00821" class="html-bibr">86</a>]; <span class="html-italic">OsFBK1</span> [<a href="#B77-ijms-26-00821" class="html-bibr">77</a>]; <span class="html-italic">PeKFB9</span> [<a href="#B61-ijms-26-00821" class="html-bibr">61</a>]; <span class="html-italic">SAGL1</span> [<a href="#B82-ijms-26-00821" class="html-bibr">82</a>,<a href="#B89-ijms-26-00821" class="html-bibr">89</a>]; <span class="html-italic">SKIP11</span> [<a href="#B90-ijms-26-00821" class="html-bibr">90</a>]; <span class="html-italic">SmKFB5</span> [<a href="#B84-ijms-26-00821" class="html-bibr">84</a>]; <span class="html-italic">StFBK</span> [<a href="#B60-ijms-26-00821" class="html-bibr">60</a>]; <span class="html-italic">VviKFB07</span> [<a href="#B88-ijms-26-00821" class="html-bibr">88</a>].</p>
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14 pages, 3034 KiB  
Article
HERC1 E3 Ubiquitin Ligase Is Necessary for Autophagy Processes and for the Maintenance and Homeostasis of Vesicles in Motor Nerve Terminals, but Not for Proteasomal Activity
by Miguel Ángel Pérez-Castro, Francisco Hernández-Rasco, Isabel María Alonso-Bellido, María S. Letrán-Sánchez, Eva María Pérez-Villegas, Joana Vitallé, Luis Miguel Real, Ezequiel Ruiz-Mateos, José Luis Venero, Lucía Tabares, Ángel Manuel Carrión, José Ángel Armengol, Sara Bachiller and Rocío Ruiz
Int. J. Mol. Sci. 2025, 26(2), 793; https://doi.org/10.3390/ijms26020793 - 18 Jan 2025
Viewed by 307
Abstract
The ubiquitin proteasome system (UPS) is implicated in protein homeostasis. One of the proteins involved in this system is HERC1 E3 ubiquitin ligase, which was associated with several processes including the normal development and neurotransmission at the neuromuscular junction (NMJ), autophagy in projection [...] Read more.
The ubiquitin proteasome system (UPS) is implicated in protein homeostasis. One of the proteins involved in this system is HERC1 E3 ubiquitin ligase, which was associated with several processes including the normal development and neurotransmission at the neuromuscular junction (NMJ), autophagy in projection neurons, myelination of the peripheral nervous system, among others. The tambaleante (tbl) mouse model carries the spontaneous mutation Gly483Glu substitution in the HERC1 E3 protein. Using this model, we analyzed the implication of HERC1 E3 ubiquitin ligase in the activity of UPS, autophagy, and synaptic homeostasis in brain and muscle tissues. Regarding UPS, no differences were found in its activity nor in the specific gene expression in both brain and muscle tissues from tbl compared with the control littermates. Furthermore, the use of the specific UPS inhibitor (MG-132), did not alter the evoked neurotransmitter release in the levator auris longus (LAL) muscle. Interestingly, the expression of the autophagy-related gene p62 was significantly increased in the muscle of tbl compared to the control littermates. Indeed, impaired evoked neurotransmitter release was observed with the autophagy inhibitor Wortmannin. Finally, altered levels of Clathrin and Synaptophysin were detected in muscle tissues. Altogether, our findings show that HERC1 E3 ubiquitin ligase mutation found in tbl mice alters autophagy and vesicular recycling without affecting proteasomal function. Full article
(This article belongs to the Special Issue Molecular and Neuromuscular Mechanisms in Skeletal Muscle Aging)
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<p>Proteasome activity in Ctrl and tbl mutant mice. Chymotrypsin proteasome activity in (<b>A</b>,<b>E</b>) gastrocnemius and (<b>B</b>,<b>F</b>) TVA muscles, and (<b>C</b>,<b>G</b>) brain and (<b>D</b>,<b>H</b>) cerebellum of control (Ctrl) and tambaleante (tbl) mutant mice at two (upper graphs) and four (lower graphs) months of age. n = 5–6 animals/group; technical duplicates. White bars represent Ctrl mice; gray bars represent tbl mice, and individual dots represent individual mice. Data are represented as mean ± SEM; <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>No changes in evoked neurotransmitter release following MG-132 application in Ctrl LAL muscle. (<b>A</b>) Representative EPP traces, (<b>B</b>) mean EPP amplitudes, (<b>C</b>) mean quantum content (QC), and (<b>D</b>) mean of mEPP in vehicle (W/O drug) and MG-132-treated LAL muscles. (<b>E</b>) <span class="html-italic">n</span> (number of occupied sites) and <span class="html-italic">p</span> (probability of release) estimated in W/O drug and MG-132-treated LAL muscles. [(n, N) n, number of fibers; N, number of mice]; <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>RT-qPCR expression of genes related to UPS in TVA muscle from Ctrl and tbl mutant mice. mRNA levels (% to Ctrl) of (<b>A</b>) Psmc2, (<b>B</b>) Hspb8, (<b>C</b>) Bag1, (<b>D</b>) Bag3, and (<b>E</b>) Herc1. n = 7 animals/group; average of technical and experimental triplicates. White bars represent Ctrl mice; gray bars represent tbl mice; individual dots represent individual mouse values. Data are represented as mean ± SEM; <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>RT-qPCR expression analysis of genes related to autophagy pathway in TVA muscle from Ctrl and tbl mutant mice. mRNA levels (% to Ctrl) of (<b>A</b>) Atg10, (<b>B</b>) Lc3b, (<b>C</b>) p62, (<b>D</b>) CathepsinB, (<b>E</b>) CathepsinD, and (<b>F</b>) Rab7. n = 7 animals/group; technical triplicates. White bars represent Ctrl mice; gray bars represent tbl mice; individual dots represent one mouse. Data are represented as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Impaired evoked neurotransmitter release after Wortmannin application in Ctrl LAL muscle. (<b>A</b>) Representative EPP traces, (<b>B</b>) mean EPP amplitudes, (<b>C</b>) mean quantum content (QC), and (<b>D</b>) mean of mEPPs in vehicle (W/O Drug) and Wortmannin-treated LAL muscles. (<b>E</b>) <span class="html-italic">n</span> (number of occupied sites) and <span class="html-italic">p</span> (probability of release) estimated in vehicle (W/O Drug) and Wortmannin-treated LAL muscles. [(n, N) n, number of fibers; N, number of mice]. Data are represented as mean ± SEM. *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>BTX, Syp, and Clathrin immunolabeling at NMJ of tbl and Ctrl mice at 2 months old. (<b>A</b>) Representative z-stack projections of confocal images of NMJs from LAL muscles stained with BTX-Rho (red), anti-Syp (magenta), and anti-Clathrin (green). Area measurement (µm<sup>2</sup>) of (<b>B</b>) Clathrin, (<b>C</b>) Syp, and (<b>D</b>) BTX. (<b>E</b>) Fluorescence intensity (A.U.) of BTX. (<b>F</b>) Ratio of Clathrin/BTX area. Scale bar: 10 μm. 55–57 NMJ were analyzed; n = 3 animals/group. Each dot represents one NMJ. White bars represent Ctrl mice; gray bars represent tbl mice. Data are represented 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>RT-qPCR gene expression analysis of synaptic components in TVA muscle. mRNA levels (% to Ctrl) of (<b>A</b>) S100β, (<b>B</b>) Syp, (<b>C</b>) Mun13, (<b>D</b>) Bche, and (<b>E</b>) Bassoon. n = 6–7 animals/group; technical triplicates. White bars represent Ctrl mice; gray bars represent tbl mice; individual dots represent one mouse. Data are represented as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05.</p>
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17 pages, 3346 KiB  
Article
Dysregulation of Metabolic Peptides Precedes Hyperinsulinemia and Inflammation Following Exposure to Rotenone in Rats
by Vandana Zaman, Denise Matzelle, Naren L. Banik and Azizul Haque
Cells 2025, 14(2), 124; https://doi.org/10.3390/cells14020124 - 16 Jan 2025
Viewed by 422
Abstract
Rotenone, a naturally occurring compound derived from the roots of tropical plants, is used as a broad-spectrum insecticide, piscicide, and pesticide. It is a classical, high-affinity mitochondrial complex I inhibitor that causes not only oxidative stress, α-synuclein phosphorylation, DJ-1 (Parkinson’s disease protein 7) [...] Read more.
Rotenone, a naturally occurring compound derived from the roots of tropical plants, is used as a broad-spectrum insecticide, piscicide, and pesticide. It is a classical, high-affinity mitochondrial complex I inhibitor that causes not only oxidative stress, α-synuclein phosphorylation, DJ-1 (Parkinson’s disease protein 7) modifications, and inhibition of the ubiquitin-proteasome system but it is also widely considered an environmental contributor to Parkinson’s disease (PD). While prodromal symptoms, such as loss of smell, constipation, sleep disorder, anxiety/depression, and the loss of dopaminergic neurons in the substantia nigra of rotenone-treated animals, have been reported, alterations of metabolic hormones and hyperinsulinemia remain largely unknown and need to be investigated. Whether rotenone and its effect on metabolic peptides could be utilized as a biomarker for its toxic metabolic effects, which can cause long-term detrimental effects and ultimately lead to obesity, hyperinsulinemia, inflammation, and possibly gut–brain axis dysfunction, remains unclear. Here, we show that rotenone disrupts metabolic homeostasis, altering hormonal peptides and promoting infiltration of inflammatory T cells. Specifically, our results indicate a significant decrease in glucagon-like peptide-1 (GLP-1), C-peptide, and amylin. Interestingly, levels of several hormonal peptides related to hyperinsulinemia, such as insulin, leptin, pancreatic peptide (PP), peptide YY (PYY), and gastric inhibitory polypeptide (GIP), were significantly upregulated. Administration of rotenone to rats also increased body weight and activated macrophages and inflammatory T cells. These data strongly suggest that rotenone disrupts metabolic homeostasis, leading to obesity and hyperinsulinemia. The potential implications of these findings are vast, given that monitoring these markers in the blood could not only provide a crucial tool for assessing the extent of exposure and its relevance to obesity and inflammation but could also open new avenues for future research and potential therapeutic strategies. Full article
(This article belongs to the Special Issue Neuroinflammation in Brain Health and Diseases)
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<p>Schematic representation of the experimental design. Young adult Lewis rats received vehicle or rotenone (2 mg/kg body weight) in respective treatment groups. Rotenone treatment groups received 10 sub-cutaneous injections of rotenone (total 20 mg/kg body weight). The change in body weight was measured before the treatment (C-pre-treatment, and R-pre-treatment) and one month post-treatment (C-post-treatment and R-post-treatment). Rats were sacrificed one month post-treatment, and samples were collected.</p>
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<p>Alterations of hormonal peptides GIP and GLP-1 in rats following rotenone administration. Plasma samples from control and rotenone-treated rats were analyzed by Metabolic Hormone 10-Plex Discovery Assay. (<b>A</b>) GIP level shows a highly significant increase (<span class="html-italic">p</span> = 0.0003) in the plasma of rotenone-treated rats compared to the control rats. (<b>B</b>) Analysis of GLP-1 showed a significant reduction of this metabolic peptide in the plasma of rotenone-treated rats (<span class="html-italic">p</span> = 0.0045) compared to the control group. N = 5–8.</p>
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<p>Rotenone administration elevated anorectic gut hormones, pancreatic polypeptide and peptide YY, in rats. Both pancreatic polypeptide (<b>A</b>) and peptide YY (<b>B</b>) hormonal peptides were significantly increased (<span class="html-italic">p</span> &lt; 0.0001) in the plasma of the rotenone-treated group compared to the control group. N = 6–9.</p>
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<p>Effects of rotenone on incretin levels in rat plasma one month post-treatment. (<b>A</b>) Metabolic profile in the plasma demonstrates a highly significant increase (<span class="html-italic">p</span> &lt; 0.0001) in the insulin level following rotenone treatment compared to the control group. (<b>B</b>) Meanwhile, the C-peptide level in rotenone-treated rats was significantly decreased (<span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) Amylin levels were also decreased significantly (<span class="html-italic">p</span> &lt; 0.0008) in the rotenone group compared to the control group. (<b>D</b>) However, the plasma level of leptin hormone was increased significantly (<span class="html-italic">p</span> &lt; 0.001) in rotenone-treated rats compared to the control group. These data suggest that rotenone disrupts incretin levels, promoting inflammation and insulinemia. N = 6–9.</p>
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<p>Rotenone treatment increased rat body weight. The change in body weight was measured before the treatment (C-pre-treatment and R-pre-treatment) and one month post-treatment (C-post-treatment and R-post-treatment). The data showed that the rats in the rotenone post-treatment (R-post-treatment) group gained substantial body weight, and it was significantly increased (<span class="html-italic">p</span> &lt; 0.0001) compared to before starting the rotenone treatment (R-pre-treatment) and to the post-vehicle control (C-post-treatment) group (<span class="html-italic">p</span> &lt; 0.005). Body weights of the control pre-treatment and the rotenone pre-treatment group are not significantly different (<span class="html-italic">p</span> &lt; 0.05) at the beginning of the experiment. Moreover, no significant difference (ns) in body weights was detected in the control groups, C-pre-treatment and C-post-treatment. N = 3–7.</p>
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<p>Administration of rotenone promoted activation of macrophages in rats. (<b>A</b>) Immunostaining of CD68 in cryosections of spleens from control and rotenone treatment groups. There was a distinct upregulation of CD68-positive cells in the rat spleen’s red pulp (RP) area following rotenone treatment compared to the vehicle treatment control group. (<b>B</b>) Counting of CD68-stained cells by ImageJ software showed a significant increase (<span class="html-italic">p</span> &lt; 0.05) in CD68-positive cells in the rotenone treatment group compared to the control. N = 4.</p>
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<p>Rotenone treatment promoted activation of inflammatory CD4<sup>+</sup> T cells in rats. (<b>A</b>) Immunostaining for the presence of CD4 and TNF-α in spleens from control and rotenone treatment groups counterstained with DAPI. Expansion of CD4<sup>+</sup> T cells in the spleen following rotenone treatment was noticeable compared to control. These CD4<sup>+</sup> T cells also expressed TNF-α, indicating inflammatory changes in the rotenone-treated animals. (<b>B</b>,<b>C</b>) Counting of cells expressing CD4 (<b>B</b>) and CD4/TNF-α markers (<b>C</b>). The rotenone treatment group showed a significant increase (<span class="html-italic">p</span> &lt; 0.01) in the CD4<sup>+</sup> T cell population in the spleen compared to the spleens from the control group. Moreover, these CD4<sup>+</sup> T cells also co-expressed increased TNF-α in rotenone-treated rats compared to the control group (<span class="html-italic">p</span> &lt; 0.005). N = 4.</p>
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<p>Administration of rotenone disrupts metabolic hormones and influences gut–brain axis and hyperinsulinemia. The observed low levels of GLP-1 and amylin indicate a potential dysregulation of appetite and blood sugar levels. This dysregulation may be associated with increased body weight and hyperinsulinemia. Furthermore, the hyperinsulinemia observed in the rotenone-treated rats indicates that the peripheral toxicity caused by rotenone may have disrupted regulation of insulin secretion mediated by dopamine. Red arrows indicate levels and pathways affected by rotenone treatment. Black arrows indicate the cell types and the metabolic hormones they secret.</p>
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22 pages, 4057 KiB  
Article
CCL5 Induces a Sarcopenic-like Phenotype via the CCR5 Receptor
by Francisco Aguirre, Franco Tacchi, Mayalen Valero-Breton, Josué Orozco-Aguilar, Sabrina Conejeros-Lillo, Josefa Bonicioli, Renata Iturriaga-Jofré, Daniel Cabrera, Jorge A. Soto, Mauricio Castro-Sepúlveda, Marianny Portal-Rodríguez, Álvaro A. Elorza, Andrea Matamoros, Felipe Simon and Claudio Cabello-Verrugio
Antioxidants 2025, 14(1), 84; https://doi.org/10.3390/antiox14010084 - 13 Jan 2025
Viewed by 493
Abstract
Sarcopenia corresponds to a decrease in muscle mass and strength. CCL5 is a new myokine whose expression, along with the CCR5 receptor, is increased in sarcopenic muscle. Therefore, we evaluated whether CCL5 and CCR5 induce a sarcopenic-like effect on skeletal muscle tissue and [...] Read more.
Sarcopenia corresponds to a decrease in muscle mass and strength. CCL5 is a new myokine whose expression, along with the CCR5 receptor, is increased in sarcopenic muscle. Therefore, we evaluated whether CCL5 and CCR5 induce a sarcopenic-like effect on skeletal muscle tissue and cultured muscle cells. Electroporation in the tibialis anterior (TA) muscle of mice was used to overexpress CCL5. The TA muscles were analyzed by measuring the fiber diameter, the content of sarcomeric proteins, and the gene expression of E3-ligases. C2C12 myotubes and single-isolated flexor digitorum brevis (FDB) fibers were also treated with recombinant CCL5 (rCCL5). The participation of CCR5 was evaluated using the antagonist maraviroc (MVC). Protein and structural analyses were performed. The results showed that TA overexpression of CCL5 led to sarcopenia by reducing muscle strength and mass, muscle-fiber diameter, and sarcomeric protein content, and by upregulating E3-ligases. The same sarcopenic phenotype was observed in myotubes and FDB fibers. We showed increased reactive oxygen species (ROS) production and carbonylated proteins, denoting oxidative stress induced by CCL5. When the CCR5 was antagonized, the effects produced by rCCL5 were prevented. In conclusion, we report for the first time that CCL5 is a novel myokine that exerts a sarcopenic-like effect through the CCR5 receptor. Full article
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<p><b>Overexpression of CCL5 produces sarcopenia in TA.</b> Male C57BL6 mice were electroporated with control plasmid (Mock) and CCL5 overexpression plasmid (oeCCL5) in the tibialis anterior (TA) muscle for 21 days. (<b>A</b>) Immunofluorescence anti-laminin in TA sections of 10 µm thickness, the left image corresponds to 10X magnification, and the right image corresponds to digital magnification; the scale bar is 100 µm. (<b>B</b>) A cumulative frequency graph of fiber diameters is expressed in % corresponding to a range of diameters. (<b>C</b>) Protein levels of Troponin I and tropomyosin, using β-actin as a loading control. (<b>D</b>,<b>E</b>) densitometric analysis of Troponin I and Tropomyosin protein levels, respectively. (<b>F</b>,<b>G</b>) mRNA levels of murf-1 and atrogin-1, respectively, using β-actin as housekeeping. (<b>H</b>) Measurement of isometric force in TA, using 1–150 Hz frequencies and normalized for tibia length. (<b>I</b>) Determination of the weight of TA: the weights were normalized using the corresponding tibia of each animal. The results are expressed as the mean ± SD (<span class="html-italic">n</span> = 4, ANOVA two-way post hoc Bonferroni; <span class="html-italic">t</span>-test * <span class="html-italic">p</span> &lt; 0.05 vs. Vehicle).</p>
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<p><b>CCL5 via the CCR5 receptor decreases the diameter of muscle cells.</b> C<sub>2</sub>C<sub>12</sub> myoblast cell lines, differentiated for 5 days into myotubes and muscle fibers isolated from FDB, were pretreated with 10 µM of the CCR5 inhibitor (Maraviroc, MVC) for 1 h and subsequently treated with 200 ng/mL of rCCL5 for 72 h. (<b>A</b>) Surface delineation of C<sub>2</sub>C<sub>12</sub> myotubes by immunofluorescence against Cav-3, magnification corresponding to 20X, and the scale bar corresponds to 100 µm. (<b>B</b>) Quantification of the diameter of C<sub>2</sub>C<sub>12</sub> myotubes, using an abundance graph expressed in % vs. range of myotube diameters. (<b>C</b>) Graph of cumulative frequency expressed in % of C<sub>2</sub>C<sub>12</sub> myotubes vs. diameter. (<b>D</b>) Delineation of muscle fibers isolated from FDB by immunofluorescence anti-Cav-3, magnification corresponding to 20X, and scale bar corresponding to 100 µm. (<b>E</b>) Quantification of the diameter of FDB muscle fibers by abundance plot expressed in % relative to muscle-fiber size ranges (µm). (<b>F</b>) FDB muscle-fiber diameter quantification plotted as cumulative frequency (%) versus diameter. The results are expressed as the mean ± SD (<span class="html-italic">n</span> = 3). Eighty myotubes and 50 fibers were analyzed per condition for each “<span class="html-italic">n</span>” (a total of 240 myotubes and 150 fibers for each condition). ANOVA two-way post hoc Bonferroni * <span class="html-italic">p</span> &lt; 0.05 vs. Vehicle).</p>
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<p><b>CCL5, through the CCR5 receptor, decreases the protein levels of sarcomere components in muscle cells.</b> C<sub>2</sub>C<sub>12</sub> myoblast cell lines differentiated for 5 days into myotubes were preincubated with 10 µM of the CCR5 antagonist (Maraviroc, MVC) for 1 h and subsequently incubated with 200 ng/mL of rCCL5 for 72 h. (<b>A</b>,<b>C</b>) Protein levels of sarcomere component proteins, MHC, and troponin I, respectively, using β-actin as a loading control. (<b>B</b>,<b>D</b>) Densitometric analysis of the protein levels of MHC and troponin I, respectively. The results are expressed as the mean ± SD (<span class="html-italic">n</span> = 3, one-way ANOVA post hoc Bonferroni * <span class="html-italic">p</span> &lt; 0.05 vs. vehicle).</p>
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<p><b>CCL5, via the CCR5 receptor, deregulates protein synthesis and degradation processes in muscle cells.</b> C<sub>2</sub>C<sub>12</sub> myoblasts were differentiated for 5 days into myotubes, and muscle fibers isolated from FDB were pretreated with 10 µM of the CCR5 inhibitor (Maraviroc, MVC) for 1 h and subsequently treated with 200 ng/mL of rCCL5 for 24 h. (<b>A</b>,<b>B</b>) mRNA levels of the E3s ligases <span class="html-italic">murf-1</span> and <span class="html-italic">atrogin-1</span> respectively, using <span class="html-italic">β-actin</span> as housekeeping. (<b>C</b>) Puromycin incorporation assay in C<sub>2</sub>C<sub>12</sub> myotubes, determined through protein levels using β-actin as a loading control. (<b>D</b>) Densitometric analysis of puromycin levels in C<sub>2</sub>C<sub>12</sub> myotubes. (<b>E</b>) Puromycin assay in FDB muscle fibers, determined through immunofluorescence with anti-puromycin antibody, magnification of the images corresponding to 40X, scale bar corresponding to 100 µm. (<b>F</b>) Quantification of puromycin incorporation through fluorescence intensity of FDB fibers. The results are expressed as the mean ± SD (<span class="html-italic">n</span> = 3). Fifty fibers were analyzed per condition for each “<span class="html-italic">n</span>” (a total of 150 fibers for each condition). One-way ANOVA post hoc Bonferroni * <span class="html-italic">p</span> &lt; 0.05 vs. Vehicle).</p>
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<p><b>CCL5, through the CCR5 receptor, produces oxidative stress, increasing the production of ROS in muscle cells.</b> C<sub>2</sub>C<sub>12</sub> myoblast cell lines were differentiated for 5 days into myotubes, and muscle fibers isolated from FDB were pretreated with 10 µM of the CCR5 inhibitor (Maraviroc, MVC) for 1 h and subsequently treated with 200 ng/mL of rCCL5 for 48 h. (<b>A</b>) Reactive oxygen species (ROS) are detected through DCF in FDB muscle fibers. Magnification of 40X and the corresponding scale bar at 100 µm. (<b>B</b>) Quantification of ROS production through fluorescence intensity of the DCF probe. (<b>C</b>) Determination of protein levels of carbonylated proteins in C<sub>2</sub>C<sub>12</sub> myotubes using Oxyblot, using β-actin as a loading control. (<b>D</b>) Densitometric analysis of protein carbonylation. The results are expressed as the mean ± SD (<span class="html-italic">n</span> = 3). Fifty fibers were analyzed per condition for each “<span class="html-italic">n</span>” (a total of 150 fibers for each condition). One-way ANOVA post hoc Bonferroni * <span class="html-italic">p</span> &lt; 0.05 vs. Vehicle).</p>
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38 pages, 1123 KiB  
Review
Proteostasis Decline and Redox Imbalance in Age-Related Diseases: The Therapeutic Potential of NRF2
by Brigitta Buttari, Antonella Tramutola, Ana I. Rojo, Niki Chondrogianni, Sarmistha Saha, Alessandra Berry, Letizia Giona, Joana P. Miranda, Elisabetta Profumo, Sergio Davinelli, Andreas Daiber, Antonio Cuadrado and Fabio Di Domenico
Biomolecules 2025, 15(1), 113; https://doi.org/10.3390/biom15010113 - 13 Jan 2025
Viewed by 670
Abstract
Nuclear factor erythroid 2-related factor 2 (NRF2) is a master regulator of cellular homeostasis, overseeing the expression of a wide array of genes involved in cytoprotective processes such as antioxidant and proteostasis control, mitochondrial function, inflammation, and the metabolism of lipids and glucose. [...] Read more.
Nuclear factor erythroid 2-related factor 2 (NRF2) is a master regulator of cellular homeostasis, overseeing the expression of a wide array of genes involved in cytoprotective processes such as antioxidant and proteostasis control, mitochondrial function, inflammation, and the metabolism of lipids and glucose. The accumulation of misfolded proteins triggers the release, stabilization, and nuclear translocation of NRF2, which in turn enhances the expression of critical components of both the proteasomal and lysosomal degradation pathways. This process facilitates the clearance of toxic protein aggregates, thereby actively maintaining cellular proteostasis. As we age, the efficiency of the NRF2 pathway declines due to several factors including increased activity of its repressors, impaired NRF2-mediated antioxidant and cytoprotective gene expression, and potential epigenetic changes, though the precise mechanisms remain unclear. This leads to diminished antioxidant defenses, increased oxidative damage, and exacerbated metabolic dysregulation and inflammation—key contributors to age-related diseases. Given NRF2’s role in mitigating proteotoxic stress, the pharmacological modulation of NRF2 has emerged as a promising therapeutic strategy, even in aged preclinical models. By inducing NRF2, it is possible to mitigate the damaging effects of oxidative stress, metabolic dysfunction, and inflammation, thus reducing protein misfolding. The review highlights NRF2’s therapeutic implications for neurodegenerative diseases and cardiovascular conditions, emphasizing its role in improving proteostasis and redox homeostasis Additionally, it summarizes current research into NRF2 as a therapeutic target, offering hope for innovative treatments to counteract the effects of aging and associated diseases. Full article
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<p>Schematic overview of the NRF2 interaction mechanisms with the unfold protein response (UPR), the mTOR/autophagy pathways and the ubiquitin-proteasome system (UPS). See details in the text (created with BioRender, Toronto, ON, Canada).</p>
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<p>Schematic overview of the central role of NRF2 in regulating protein homeostasis and redox balance. Green lines describe the interventions of NRF2 in homeostatic mechanisms (created with BioRender, Toronto, ON, Canada).</p>
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16 pages, 4230 KiB  
Article
PROTAC-Mediated GSPT1 Degradation Impairs the Expression of Fusion Genes in Acute Myeloid Leukemia
by Alicia Perzolli, Christian Steinebach, Jan Krönke, Michael Gütschow, C. Michel Zwaan, Farnaz Barneh and Olaf Heidenreich
Cancers 2025, 17(2), 211; https://doi.org/10.3390/cancers17020211 - 10 Jan 2025
Viewed by 543
Abstract
Background: Proteolysis targeting chimeras (PROTACs) are heterobifunctional small molecules that utilize the ubiquitin–proteasome system to selectively degrade target proteins. This innovative technology has shown remarkable efficacy and specificity in degrading oncogenic proteins and has progressed through various stages of preclinical and clinical development [...] Read more.
Background: Proteolysis targeting chimeras (PROTACs) are heterobifunctional small molecules that utilize the ubiquitin–proteasome system to selectively degrade target proteins. This innovative technology has shown remarkable efficacy and specificity in degrading oncogenic proteins and has progressed through various stages of preclinical and clinical development for hematologic malignancies, including adult acute myeloid leukemia (AML). However, the application of PROTACs in pediatric AML remains largely unexplored. Methods: In this study, we show the potent effect of GSPT1 degradation against AML cells induced by either a GSPT1-selective cereblon modulator CC-90009 or by an off-target effect caused by a CDK6-PROTAC named GU3341. Results: Both in vitro and ex vivo experiments revealed that GSPT1 degradation significantly inhibited tumor growth, induced cell cycle arrest, and triggered apoptosis in two pediatric AML subtypes characterized by RUNX1::RUNX1T1 and FUS::ERG fusion genes. Furthermore, the degradation of GSPT1 impaired the expression of RUNX1::RUNX1T1 and its cooperating transcription factors RUNX1 and ERG. Similarly, GSPT1 degradation also reduced FUS::ERG fusion transcript levels in AML cells harboring the translocation t(16;24)(p11:q22). Conclusions: These findings suggest a new role of GSPT1 in regulating leukemic transcriptional networks and open a new therapeutic strategy to target leukemic fusion genes in pediatric AML patients. Full article
(This article belongs to the Special Issue Oncology: State-of-the-Art Research in The Netherlands)
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Figure 1
<p>GU3341 PROTAC induces stronger anti-AML activity in RUNX1::RUNX1T1 cell lines compared to palbociclib. (<b>A</b>) The chemical structure of CDK6-PROTACs: BSJ-03-123, CST651, and GU3341. (<b>B</b>) Quantitative PCR analysis of the expression levels of CRBN and VHL in Kasumi-1 and SKNO-1 cell lines (<span class="html-italic">n</span> = 1 biologically independent sample). (<b>C</b>) Proliferation curve of Kasumi-1 cell line treated with palbociclib, BSJ-03-123, CST651, and GU3341 for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>D</b>) Viability of Kasumi-1 and SKNO-1 cell lines treated with palbociclib, BSJ-03-123, CST651, GU3341, and DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). Significant <span class="html-italic">p</span>-values were plotted to compare differences between drug-treatment groups at the same dose. (<b>E</b>) Number of colonies of Kasumi-1 cell line treated with palbociclib, BSJ-03-123, CST651, GU3341, and DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>F</b>) Images of colony formation assay of Kasumi-1 cell line treated with 1000 nM palbociclib, BSJ-03-123, CST651, GU3341, and DMSO for 72 h. * (<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) indicate differences between treatment groups.</p>
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<p>CDK6-PROTACs preferentially reduce CDK6 protein levels. (<b>A</b>) Western blotting of CDK6, CDK4, and GAPDH in Kasumi-1 cell line treated with BSJ-03-123 or DMSO for 24, 48, and 72 h. (<b>B</b>) Western blotting of CDK6, CDK4, and vinculin in Kasumi-1 cells treated with CST651 or DMSO for 24, 48, and 72 h. (<b>C</b>) Western blotting of CDK6, CDK4, and vinculin in Kasumi-1 cells treated with GU3341 or DMSO for 24, 48, and 72 h. (<b>D</b>) Western blotting of P-Rb (Ser780) and vinculin in Kasumi-1 cells treated with CST651 or DMSO for 6 and 24 h. (<b>E</b>) Western blotting of P-Rb (Ser780) and vinculin in Kasumi-1 cells treated with GU3341 or DMSO for 6 and 24 h.</p>
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<p>GU3341 reduces GSPT1 and Ikaros protein levels in RUNX1::RUNX1T1 AML cells. (<b>A</b>) Percentage of cells in subG1 phase of the cell cycle in Kasumi-1 cells after treatment with palbociclib or GU3341 or DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). Significant <span class="html-italic">p</span>-values were plotted to compare differences between drug-treatment groups at the same dose. (<b>B</b>) Percentage of cells in G1/S/G2M phases of cell cycle in Kasumi-1 cells after treatment with palbociclib or GU3341 or DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>C</b>) Apoptosis assay Sytox Red in Kasumi-1 cells after treatment with palbociclib or GU3341 or DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). Significant <span class="html-italic">p</span>-values were plotted to compare differences between drug-treatment groups at the same dose. (<b>D</b>) Western blotting of GSPT1, Ikaros, β-tubulin, vinculin in Kasumi-1 cells treated with BSJ-03-123, CST651, GU3341, or DMSO for 24 h. * (<span class="html-italic">p</span> &lt; 0.05) and ** (<span class="html-italic">p</span> &lt; 0.01) indicate differences between treatment groups.</p>
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<p>CC-90009 induces anti-AML activity in a RUNX1::RUNX1T1 cell line. (<b>A</b>) The chemical structure of CC-90009. (<b>B</b>) Proliferation curve of Kasumi-1 cell line treated with CC-90009 or DMSO for 24, 48, and 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>C</b>) Western blotting of GSPT1, Ikaros, and β-tubulin in Kasumi-1 cells treated with CC-90009 or DMSO for 72 h. (<b>D</b>) Western blotting of RUNX1::RUNX1T1, RUNX1 and β-tubulin in Kasumi-1 cells treated with CC-90009 or DMSO for 24 and 48 h. (<b>E</b>) Quantitative PCR analysis of the expression levels of RUNX1::RUNX1T1 transcripts in Kasumi-1 cells treated with CC-90009 or DMSO for 24 and 48 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>F</b>) Quantitative PCR analysis of the expression levels of RUNX1 transcripts in Kasumi-1 cells treated with CC-90009 or DMSO for 24 and 48 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>G</b>) Quantitative PCR analysis of the expression levels of ERG transcripts in Kasumi-1 cells treated with CC-90009 or DMSO for 24 and 48 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>H</b>) Western blotting of ERG and GAPDH in Kasumi-1 cells treated with CC-90009 or DMSO for 24 and 48 h. * (<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) indicate differences between controls and treatment groups.</p>
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<p>CC-90009 treatment reduces RUNX1::RUNX1T1 expression in PDX and primary AML cells. (<b>A</b>) Proliferation curve of RUNX1::RUNX1T1 PDX cells treated with CC-90009 or DMSO. Cells were counted and treatment was refreshed every 3 days (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>B</b>) Proliferation curve of primary RUNX1::RUNX1T1 AML cells treated with CC-90009 or DMSO. Cells were counted and treatment was refreshed every 3 days (<span class="html-italic">n</span> = 2 biologically independent samples). (<b>C</b>) Cell cycle analysis after treatment with CC-90009 or DMSO for 3 days (<span class="html-italic">n</span> = 1 biologically independent samples). (<b>D</b>) Proliferation curve of RUNX1::RUNX1T1 PDX cells treated with CC-90009 or DMSO for 24 and 48 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>E</b>) Western blotting of RUNX1::RUNX1T1, RUNX1, and vinculin in RUNX1::RUNX1T1 PDX cells treated with CC-900009 or DMSO for 24 and 48 h. (<b>F</b>) Quantitative PCR analysis of the expression level of RUNX1::RUNX1T1 transcripts in RUNX1::RUNX1T1 PDX cells treated with CC-90009 or DMSO for 24 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>G</b>) Quantitative PCR analysis of the expression of RUNX1 transcript in RUNX1::RUNX1T1 PDX cells treated with CC-900009 or DMSO for 24 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>H</b>) Quantitative PCR analysis of the expression of ERG transcript in RUNX1::RUNX1T1 PDX cells treated with CC-900009 or DMSO for 24 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). * (<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) indicate differences between controls and treatment groups.</p>
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<p>CC-90009 and GU3341 PROTACs induce anti-AML activity in FUS::ERG cell lines. (<b>A</b>) Quantitative PCR analysis of the expression levels of CRBN in TSU-1621-MT and YNH-1 cell lines (<span class="html-italic">n</span> = 1 independent experiment). (<b>B</b>) Proliferation curve of TSU-1621-MT cell line treated with CC-90009 and DMSO for 24 and 48 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>C</b>) Viability of TSU-1621-MT cells treated with CC-90009 and DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>D</b>) Quantitative PCR analysis of the expression level of FUS::ERG transcripts in TSU-1621-MT cells treated with CC-90009 or DMSO for 24 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>E</b>) Western blotting of GSPT1, Ikaros, β-tubulin, vinculin in TSU-1621-MT and YNH-1 cells treated with BSJ-03-123, CST651, GU3341, or DMSO for 24 h. (<b>F</b>) Proliferation curve of TSU-1621-MT and YNH-1 cell lines treated with GU3341 and DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>G</b>) Viability of TSU-1621-MT cells treated with GU3341 and DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). (<b>H</b>) Viability of YNH-1 cells treated with GU3341 and DMSO for 72 h (mean ± SD, <span class="html-italic">n</span> = 3 biologically independent samples). * (<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) indicate differences between controls and treatment groups.</p>
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18 pages, 2480 KiB  
Article
Differential Activity and Expression of Proteasome in Seminiferous Epithelium During Mouse Spermatogenesis
by Héctor Zapata-Carmona, Emilce Silvina Díaz, Patricio Morales and Marco Jara
Int. J. Mol. Sci. 2025, 26(2), 494; https://doi.org/10.3390/ijms26020494 - 9 Jan 2025
Viewed by 300
Abstract
Proteasome-mediated protein degradation is essential for maintaining cellular homeostasis, particularly during spermatogenesis, where extensive cellular transformations, such as spermatid differentiation, require precise protein turnover. A key player in this process is the ubiquitin–proteasome system (UPS). This study aimed to investigate proteasome enzymatic activity [...] Read more.
Proteasome-mediated protein degradation is essential for maintaining cellular homeostasis, particularly during spermatogenesis, where extensive cellular transformations, such as spermatid differentiation, require precise protein turnover. A key player in this process is the ubiquitin–proteasome system (UPS). This study aimed to investigate proteasome enzymatic activity at different stages of the spermatogenic cycle within the seminiferous tubules of mice and explore the regulatory mechanisms that influence its proteolytic function. Specifically, we assessed the trypsin-like, chymotrypsin-like, and peptidyl-glutamyl-peptide-hydrolyzing (PGPH) activities of the proteasome. Additionally, we examined the expression of catalytic and structural subunits of the 20S core, the assembly of the 20S core with regulatory complexes, and the phosphorylation status of proteasome subunits in various segments of the seminiferous tubules. Our findings demonstrated distinct patterns of proteasomal enzymatic activity in the analyzed segments. While the expression levels of structural and catalytic subunits of the 20S core remained consistent, significant differences were detected in the assembly of the 20S core, the expression of regulatory complexes, and the phosphorylation of proteasome subunits mediated by protein kinase A. These results indicate that proteasomal activity is finely regulated through multiple mechanisms depending on the specific stage of the seminiferous epithelial cycle, highlighting the complexity of proteostasis during spermatogenesis. Full article
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Figure 1
<p>A schematic of the experimental design. Testes from sexually mature adult mice were obtained via abdominal incision and decapsulated to remove the tunica albuginea. The seminiferous tubules were mechanically separated from the interstitial tissue using fine forceps under a transillumination dissecting microscope. Through transillumination, different segments of interest corresponding to the WS (stages XII–I), SS (stages II–VI), DZ (stages VII and VII), and PZ (stages IX–XI) zones were identified. Sperm released into the lumen were flushed out of the lumen by washing. These segments were sonicated, and the supernatant from the homogenate was collected as the protein extract used for this study. (Created by Zapata-Carmona et al., via BioRender, <a href="https://app.biorender.com/" target="_blank">https://app.biorender.com/</a>, on 29 November 2024).</p>
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<p>Proteasomal activity in mouse seminiferous epithelium. (<b>A</b>) The chymotrypsin-like, (<b>B</b>) trypsin-like, and (<b>C</b>) PGPH activities were evaluated in protein extracts from the PZ (stages IX–XI), WS (stages XII and I), SS (stages II–VI), and DZ (stages VII and VIII) zones, corresponding to the different zones of the mouse seminiferous epithelium. Protein extracts were incubated with the appropriate fluorogenic substrates in the presence (black bars) or absence (white bars) of 10 µM epoxomicin. Data are expressed as mean ± SEM of the replicates indicated in each activity. Different letters indicate statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the groups.</p>
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<p>Protein level of the 20S proteasome subunits in the mouse seminiferous epithelium. The protein levels of the structural subunits PSMA7 (<b>A</b>) and PSMB2 (<b>B</b>), and the catalytic subunits PSMB7 (<b>C</b>) and PSMB5 (<b>D</b>), were determined by Western blot in the PZ (stages IX–XI), WS (stages XII and I), SS (stages II–VI), and DZ (stages VII and VIII) zones. For densitometric analysis, β-tubulin load was used as a control. The bars represent the mean ± S.E.M. from three different experiments.</p>
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<p>Assembly of the 20S proteasome in the mouse seminiferous epithelium. Extracts from the PZ (stages IX–XI), WS (stages XII and II), SS (stages II–VI), and DZ zones (stages VII and VIII) were immunoprecipitated with an anti-proteasome antibody and were detected by Western blot using an antibody against the PSMA7 subunit (<b>A</b>), the PSMB5 subunit (<b>B</b>), and the PSMB2 subunit (<b>C</b>). For densitometric analysis, the PSMA7 subunit was used as a control (<b>D</b>). The bars represent the mean ± S.E.M. from three different experiments. Different letters indicate significant statistical differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Association between the 20S core and the 19S regulatory complex in the mouse seminiferous epithelium. The protein level of the Rpt6 subunit (<b>A</b>) and assembly by immunoprecipitation (<b>B</b>) were determined in the extracts from the PZ (stages IX–XI), WS (stages XII and I), SS (stages II–VI), and DZ (stages VII and VIII) zones. Immunoprecipitation of the proteasome was performed with an anti-PSMA7 proteasome subunit antibody. For densitometric analysis, the protein load of β-tubulin (<b>A</b>) and the PSMA7 subunit (<b>B</b>) was used. The bars represent the mean ± S.E.M. from three different experiments. Different letters indicate significant statistical differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Association between the 20S core and the PA200 regulatory complex in the mouse seminiferous epithelium. The protein levels of PA200 (<b>A</b>) and assembly by immunoprecipitation (<b>B</b>) were determined in the extracts from the PZ (stages IX–XI), WS (stages XII and I), SS (stages II–VI), and DZ (stages VII and VIII) zones. Immunoprecipitation of the proteasome was performed with an anti-PSMA7 proteasome subunit antibody. For densitometric analysis, the protein load of β-tubulin (<b>A</b>) and the PSMA7 subunit (<b>B</b>) was used. The bars represent the mean ± S.E.M. from three different experiments. Different letters indicate significant statistical differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Phosphorylation of proteasome subunits by protein kinase A in mouse seminiferous epithelium. The proteasome was immunoprecipitated with an anti-PSMA7 proteasome subunit antibody in the extracts from the PZ (stages IX–XI), WS (stages XII and I), SS (stages II–VI), and DZ (stages VII and VIII) zones. The phosphorylation of proteasomal subunits by PKA was evaluated by Western blot (<b>A</b>) using an antibody against phosphorylated PKA substrates (pPKAs). For densitometric analysis, the PSMA7 subunit was used as a control (<b>B</b>). The bars represent the mean ± S.E.M. of the total signal from phosphorylated proteasome components from three different experiments. Different letters indicate statistically significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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37 pages, 1133 KiB  
Review
Ubiquitination Enzymes in Cancer, Cancer Immune Evasion, and Potential Therapeutic Opportunities
by Aiman B. Awan, Maryiam Jama Ali Osman and Omar M. Khan
Cells 2025, 14(2), 69; https://doi.org/10.3390/cells14020069 - 7 Jan 2025
Viewed by 581
Abstract
Ubiquitination is cells’ second most abundant posttranslational protein modification after phosphorylation. The ubiquitin–proteasome system (UPS) is critical in maintaining essential life processes such as cell cycle control, DNA damage repair, and apoptosis. Mutations in ubiquitination pathway genes are strongly linked to the development [...] Read more.
Ubiquitination is cells’ second most abundant posttranslational protein modification after phosphorylation. The ubiquitin–proteasome system (UPS) is critical in maintaining essential life processes such as cell cycle control, DNA damage repair, and apoptosis. Mutations in ubiquitination pathway genes are strongly linked to the development and spread of multiple cancers since several of the UPS family members possess oncogenic or tumor suppressor activities. This comprehensive review delves into understanding the ubiquitin code, shedding light on its role in cancer cell biology and immune evasion. Furthermore, we highlighted recent advances in the field for targeting the UPS pathway members for effective therapeutic intervention against human cancers. We also discussed the recent update on small-molecule inhibitors and PROTACs and their progress in preclinical and clinical trials. Full article
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<p>The ubiquitination cascade. A ubiquitin molecule is first charged by the E1 enzyme at the expense of an ATP molecule. The charged ubiquitin is then transferred to the E2 via a transthiolation reaction. E2 collaborates with E3 ubiquitin ligase, which adds ubiquitin to the protein substrate. A polyubiquitinated substrate is recognized by the proteasome machinery, where the substrate is degraded, and ubiquitin is recycled. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Types of ubiquitination. (<b>a</b>) A single ubiquitin is attached to the substrate protein. (<b>b</b>) Several ubiquitin molecules are attached to multiple lysine residues within the same protein. (<b>c</b>) The same type of ubiquitination is used throughout a single polyubiquitin chain. (<b>d</b>) More than two different types of ubiquitin linkages are used in a polyubiquitin chain. (<b>e</b>) A single ubiquitin is used for two or more ubiquitin attachments subsequently. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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22 pages, 2897 KiB  
Article
Pharmacological Modulation of the Unfolded Protein Response as a Therapeutic Approach in Cutaneous T-Cell Lymphoma
by Nadia St. Thomas, Benjamin N. Christopher, Leticia Reyes, Reeder M. Robinson, Lena Golick, Xiaoyi Zhu, Eli Chapman and Nathan G. Dolloff
Biomolecules 2025, 15(1), 76; https://doi.org/10.3390/biom15010076 - 7 Jan 2025
Viewed by 450
Abstract
Cutaneous T-cell lymphoma (CTCL) is a rare T-cell malignancy characterized by inflamed and painful rash-like skin lesions that may affect large portions of the body’s surface. Patients experience recurrent infections due to a compromised skin barrier and generalized immunodeficiency resulting from a dominant [...] Read more.
Cutaneous T-cell lymphoma (CTCL) is a rare T-cell malignancy characterized by inflamed and painful rash-like skin lesions that may affect large portions of the body’s surface. Patients experience recurrent infections due to a compromised skin barrier and generalized immunodeficiency resulting from a dominant Th2 immune phenotype of CTCL cells. Given the role of the unfolded protein response (UPR) in normal and malignant T-cell development, we investigated the impact of UPR-inducing drugs on the viability, transcriptional networks, and Th2 phenotype of CTCL. We found that CTCL cells were >5-fold more sensitive to the proteasome inhibitor bortezomib (Btz) and exhibited a distinct signaling and transcriptional response compared to normal CD4+ cells. The CTCL response was dominated by the induction of the HSP70 family member HSPA6 (HSP70B’) and, to a lesser extent, HSPA5 (BiP/GRP78). To understand the significance of these two factors, we used a novel isoform selective small-molecule inhibitor of HSPA5/6 (JG-023). JG-023 induced pro-apoptotic UPR signaling and enhanced the cytotoxic effects of proteasome inhibitors and other UPR-inducing drugs in CTCL but not normal T cells. Interestingly, JG-023 also selectively suppressed the production of Th2 cytokines in CTCL and normal CD4+ T cells. Conditioned media (CM) from CTCL were immunosuppressive to normal T cells through an IL-10-dependent mechanism. This immunosuppression could be reversed by JG-023, other HSP70 inhibitors, Btz, and combinations of these UPR-targeted drugs. Our study points to the importance of the UPR in the pathology of CTCL and demonstrates the potential of proteasome and targeted HSPA5/6 inhibitors for therapy. Full article
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<p>Btz selectively targets CTCL cells over normal CD4+ T cells. (<b>A</b>) (<b>Left</b>) Cell surface CD4 expression was measured by flow cytometry in Hut78 and HH CTCL cells. (<b>Right</b><span class="html-italic">)</span> Non-malignant CD4+ T cells were isolated from PBMCs from normal human donors, which are a mixture of CD4+ and CD8+ T-cell populations. Flow cytometry data are shown for CD8- and CD4-stained cells. (<b>B</b>) Hut78, HH, and normal CD4+ T cells were treated with dose ranges of the indicated ER stress-inducing drugs for 48 h. Cell viability data are shown. (<b>C</b>) Effective concentration 50 (EC<sub>50</sub>) values were extrapolated from dose curves shown in (<b>B</b>). EC50 values are shown in μM. (<b>D</b>) Effective concentration 50 (EC<sub>50</sub>) values were extrapolated from Btz dose curves representing 2–3 experiments for each of the indicated cell lines. CD4+ T cells from 2 different human donors are shown. Statistical significance was determined using Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05, N = 3). (<b>E</b>) Hut78 CTCL cells and normal CD4+ T cells were treated with the indicated concentrations of Btz for 24 h. Flow cytometry data for cleaved caspase-3 positive cells are shown (mean ± SEM, N = 3). (<b>F</b>) HH and normal CD4+ T cells were treated with Btz (20 nM) for 16 h. Western blot analysis of the indicated UPR and apoptotic markers is shown.</p>
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<p>HSPA6 is a biomarker of response to Btz in CTCL cells. (<b>A</b>) Hut78, HH, and normal CD4+ T cells were treated with Btz for 16 h. RT-qPCR using primers for the indicated transcripts was conducted. Data were normalized to <span class="html-italic">GAPDH</span> (internal control) and DMSO-treated (treatment control) groups. (<b>B</b>) HH and normal CD4+ T cells were treated with an EC<sub>50</sub> dose of the indicated ER stress-inducing drugs. RT-qPCR data for the indicated HSP70 isoform gene transcripts are shown. Data are expressed as average fold change ± SEM after normalization to <span class="html-italic">GAPDH</span> (internal control) and DMSO (treatment control). (<b>C</b>) HH cells were treated with Btz (10 nM) and expression levels of the indicated UPR genes were measured over time via RT-qPCR. Data are presented as fold change. (<b>D</b>) HH and normal CD4+ T cells were treated with Btz (20 nM) for 16 h. RT-qPCR data using primers for the indicated HSP70 isoform transcripts are shown. Statistical significance was determined using Student’s <span class="html-italic">t</span>-test (N = 3). (<b>E</b>) HH and normal CD4+ T cells were treated with Btz (20 nM) for 24 h. Western blots for the indicated HSP70 proteins are shown.</p>
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<p>Selective HSPA5/6 inhibition using compound JG-023. (<b>A</b>) The chemical structure of JG-023 is shown. (<b>B</b>) A fluorescently labeled JG-023 (FAM-JG023) analog to be used in fluorescence polarization studies was synthesized using a copper-free click chemistry strategy. Chemical synthesis schema is shown. (<b>C</b>) Full-length (FL) HSPA5 and HSPA6 were titrated against 20 nM FAM-JG023. Fluorescence polarization binding data are shown. (<b>D</b>) Competition experiments were conducted using 1 mM HSPA6 FL, HSPA5 FL, and the HSPA5 substrate-binding domain (SBD) and 20 nM FAM-JG023. A dose range of unlabeled JG-023 was used to compete off FAM-JG023. Binding data from a fluorescence polarization assay are shown.</p>
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<p>HSPA5/6-selective inhibitors induce the UPR and enhance proteasome inhibitor sensitivity in CTCL models. (<b>A</b>) Hut78 cells were treated with the indicated HSPA5/6- (JG-023) or HSPA6- (Zxy-0028 and Zxy-0029) selective inhibitors at 20 μM for 16 h. Western blots are shown. (<b>B</b>) HH cells were treated with a dose range of JG-023 for 16 h. Western blots are shown. (<b>C</b>) HH and Hut78 cells were treated with DMSO (control) or JG-023 (10 μM) for 16 h. RT-qPCR data are shown normalized to GAPDH (internal control) and DMSO (treatment control). Statistical significance was determined using Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05, N = 3). (<b>D</b>) (<b>Left</b>) HH cells were treated with a dose range of Btz in the presence or absence (DMSO) of JG-023 (25 μM). Cell viability data are shown (DMSO: EC50 = 9.5 ± 2.3 μM; JG-023: EC50 = 1.9 ± 0.6 μM). (<b>Right</b>) Isobologram analysis is shown and confirms synergy between Btz and JG-023. The dotted line represents the no-effect isobole. (<b>E</b>) Hut78 cells were treated with a dose range of the second-generation proteasome inhibitor, carfilzomib, in the absence (DMSO) and presence of the pan HSP70 inhibitors, VER155008 (<b>Left</b>, 5 μM) and AP-4-139B (<b>Right</b>, 5 μM). Cell viability data are shown (carfilzomib EC50: DMSO = 8.1 ± 2.5 μM; VER155008 = 2.0 ± 0.6 μM; DMSO = 11.4 ± 3.3 μM; AP-4-139B = 0.42 ± 0.2 μM).</p>
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<p>HSPA5/6 inhibition represses the Th2 phenotype in CTCL cells. (<b>A</b>) RT-qPCR was conducted on untreated HH, Hut78, and normal CD4+ T cells using primers targeting the indicated gene transcripts. Data were normalized to GAPDH to generate a relative fold change (mean ± SEM, N = 3). * <span class="html-italic">p</span> &lt; 0.01 comparing normal CD4+ to both HH and Hut78 using a one-way ANOVA. (<b>B</b>) HH, Hut78, and normal CD4+ T cells were activated using phorbol ester (PMA, 1 μM) and ionomycin (Iono, 200 ng/mL) for 16 h and mRNA levels for the indicated cytokine gene panels were analyzed. RT-qPCR data are shown normalized to GAPDH (internal control) and DMSO (treatment control) and expressed as fold change (mean ± SEM, N = 3). * <span class="html-italic">p</span> &lt; 0.01 comparing normal CD4+ to both HH and Hut78 using a one-way ANOVA. (<b>C</b>) The indicated T cells were activated with PMA + Iono in the presence or absence of JG-023 (20 μM) for 6 h. Cells were washed to remove treatments and incubated in fresh media for an additional 18 h. mRNA transcript levels for the indicated gene targets were then quantified. RT-qPCR data are shown in heat map format. Data were normalized to GAPDH (internal control) and DMSO (treatment control).</p>
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<p>CTCL cells suppress normal T-cell activation. (<b>A</b>) Normal T cells from healthy human PBMCs were activated in the presence of conditioned media (CM) from resting and activated Hut78 and HH cells. IFNγ levels were determined by ELISA (mean ± SEM, N = 3). Normal T cells were activated using a trimeric anti-CD3/28/2 antibody. CM from activated CTCL cells were collected by treating Hut78 and HH cells with a combination of PMA + ionomycin for 6 h, after which, cells were washed to remove drug, and cells were finally incubated in fresh media for an additional 18 h. Statistical significance was determined using Student’s <span class="html-italic">t</span>-test (N = 3). (<b>B</b>) Experiments described in (<b>A</b>) were conducted using normal T cells from 3 healthy human donors and varying dilutions of CM from Hut78 and HH cells. * <span class="html-italic">p</span> &lt; 0.0001 compared to T-cell stimulation alone (“-”) by Student’s <span class="html-italic">t</span>-test (N = 3). (<b>C</b>) Normal T cells from healthy human donors were activated (+) in the absence or presence of Hut78 CM that were collected under the indicated conditions of treatment with JG-023 (10 μM), Btz (5 nM), VER155008 (5 mM), or combinations thereof. Hut78 cells were activated with PMA and ionomycin for 6 h in the presence of drugs followed by a wash-out. IFNg levels in the media from normal T-cell activation cultures were measured by ELISA after 48 h (mean ± SEM, N = 3). Statistical significance was determined by Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, NS = no statistical significance). (<b>D</b>) Hut78 CM from the treatment groups described in (<b>A</b>) were analyzed by cytokine bead array for the indicated cytokines. To account for any effects of the drugs on cell viability and proliferation, cytokine levels were normalized to the number of viable cells counted at the time of CM collection. Data are expressed as pg/mL per 10<sup>6</sup> viable Hut78 cells. (<b>E</b>) Normal T cells from healthy human donors were activated in the presence of Hut78 CM and neutralizing antibodies to the indicated cytokines. IFNg levels in the media from activated normal T-cell cultures were analyzed by ELISA (mean ± SEM, N = 3). Statistical significance was determined using Student’s <span class="html-italic">t</span>-test.</p>
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