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20 pages, 14588 KiB  
Article
Biomineralized MnO2 Nanoparticle-Constituted Hydrogels Promote Spinal Cord Injury Repair by Modulating Redox Microenvironment and Inhibiting Ferroptosis
by Yuyu Sun, Jinlong Zhang, Yong Gu, Tianqing Liu and Liang Chen
Pharmaceutics 2024, 16(8), 1057; https://doi.org/10.3390/pharmaceutics16081057 (registering DOI) - 12 Aug 2024
Abstract
Spinal cord injury (SCI) is one of the most severe injuries, characterized by multiple positive feedback regulatory signaling networks formed by oxidative stress and inflammation in the injury microenvironment, leading to neuronal cell damage and even death. Here, astragaloside IV (AS), known for [...] Read more.
Spinal cord injury (SCI) is one of the most severe injuries, characterized by multiple positive feedback regulatory signaling networks formed by oxidative stress and inflammation in the injury microenvironment, leading to neuronal cell damage and even death. Here, astragaloside IV (AS), known for its regulatory role in ferroptosis, was encapsulated in the cavity of apoferritin (HFn) after an in situ biomineralization process involving MnO2, resulting in the synthesis of HFn@MnO2/AS nanoparticles. These nanoparticles were then dispersed in chitosan/polyvinyl alcohol/glutaraldehyde/sodium β-glycerophosphate (CGPG) hydrogels to form CGPG-HFn@MnO2/AS injectable thermosensitive hydrogels that can scavenge reactive oxygen species (ROS) in the microenvironment. Our findings indicated that the prepared CGPG-HFn@MnO2/AS hydrogel exhibited remarkable efficacy in scavenging ROS in vitro, effectively ameliorating the oxidative stress microenvironment post-SCI. Furthermore, it inhibited oxidative stress-induced ferroptosis in vitro and in vivo by regulating SIRT1 signaling, thereby promoting neuronal cell migration and repair. Hence, the developed hydrogel combining MnO2 and AS exhibited multifaceted abilities to modulate the pathological microenvironment, providing a promising therapeutic strategy for central nervous system (CNS) diseases. Full article
(This article belongs to the Section Nanomedicine and Nanotechnology)
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Figure 1

Figure 1
<p>(<b>A</b>) Hydrodynamic particle size distribution of HFn detected by DLS. (<b>B</b>) The morphology image of the prepared HFn observed by TEM with negative staining by using 2% phosphotungstic acid (Scale bar: 50 nm). (<b>C</b>) Hydrodynamic particle size distribution of HFn@MnO<sub>2</sub>/AS nanoparticles detected by DLS. (<b>D</b>) The morphology image of HFn@MnO<sub>2</sub>/AS nanoparticles observed by TEM without negative staining (Scale bar: 100 nm). (<b>E</b>) Native page image of HFn and HFn@MnO<sub>2</sub>/AS nanoparticles. (<b>F</b>) CD spectra of HFn and HFn@MnO<sub>2</sub>/AS nanoparticles. (<b>G</b>) XPS analysis of HFn@MnO<sub>2</sub>/AS nanoparticles with full scan. (<b>H</b>) Mn 2p core-level spectra of HFn@MnO<sub>2</sub>/AS nanoparticles detected by XPS. (<b>I</b>) The hydrodynamic diameters of HFn@MnO<sub>2</sub>/AS NPs stored in PBS and PBS contained 10% FBS solutions at 4 °C for 7 days.</p>
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<p>(<b>A</b>) The mechanical properties of CS, CGP, CGG, CGPG, and CGPG-HFn@MnO<sub>2</sub>/AS hydrogels. n = 3, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p &lt;</span> 0.001. Rheological G′ and G″ against temperatures of GC (<b>B</b>), GCPC (<b>C</b>), and GCPC-HFn@MnO<sub>2</sub>/AS (<b>D</b>) hydrogels. (<b>E</b>) The gel formation image of blank hydrogels at 37 °C and the SEM micrograph of blank CGPG hydrogels (Scale bar: 50 μm). (<b>F</b>) The gel formation image of CGPG-HFn@MnO<sub>2</sub>/AS hydrogels at 37 °C and the SEM micrograph of CGPG-HFn@MnO<sub>2</sub>/AS hydrogels (Scale bar: 200 μm). (<b>G</b>) The in vitro degradation analysis of GC hydrogels. (<b>H</b>) The in vitro degradation analysis of CGP, CGG, and CGPG hydrogels. (<b>I</b>) The in vitro cumulative release of AS from HFn@MnO<sub>2</sub>/AS nanoparticles. (<b>J</b>) The in vitro cumulative release of AS from CGPG-HFn@MnO<sub>2</sub>/AS hydrogels.</p>
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<p>(<b>A</b>) The degradation behavior of HFn@MnO<sub>2</sub> incubated in different pH solutions (pH 7.4 and 6.5) with or without H<sub>2</sub>O<sub>2</sub>. (<b>B</b>) O<sub>2</sub>-bubbles image observed after incubation with H<sub>2</sub>O<sub>2</sub> in an acidic condition to confirm the formation of MnO<sub>2</sub>. (<b>C</b>) Evaluation of in vitro antioxidant effects of blank CGPG hydrogels and CGPG-HFn@MnO<sub>2</sub>/AS hydrogels in the absence of cells; ** <span class="html-italic">p &lt;</span> 0.01. (<b>D</b>) Evaluation of antioxidant effects of HFn@MnO<sub>2</sub>/AS in PC12 cells after being stimulated by H<sub>2</sub>O<sub>2</sub> (Scale bar: 500 μm) (<b>E</b>) Analysis of the ROS fluorescence intensity according to section D by Image J (version v1.53t). (<b>F</b>) Cellular uptake of FITC-HFn@MnO<sub>2</sub>/AS in CGPG hydrogels by PC12 cells detected by CLSM after incubation for 8, 12, and 24 h. (Scale bar: 75 μm).</p>
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<p>Effects of CGPG-HFn@MnO<sub>2</sub>/AS on H<sub>2</sub>O<sub>2</sub>-treated PC12 cells. (<b>A</b>) Cell viability was detected using the CCK-8 assay kit. (<b>B</b>) Cellular iron levels were detected using a kit. (<b>C</b>) Cellular GSH levels were detected using a kit. (<b>D</b>) Cellular MDA levels were detected using a kit. (<b>E</b>) Cellular SOD activity was detected using a kit. (<b>F</b>,<b>G</b>) Cellular ROS levels were detected using the fluorescent probe DCFH-DA. (Scale bar of <b>G</b>: 500 μm) (<b>H</b>–<b>M</b>) The protein levels of SIRT1, XCT, GPX4, 4-HNE, and TFR1 were detected by western blot assay. G1: control group. G2: H<sub>2</sub>O<sub>2</sub> group. G3: HFn@MnO<sub>2</sub>/AS group. G4:CGPG group. G5: CGPG-HFn@MnO<sub>2</sub>/AS. (<b>N</b>,<b>O</b>) Cell migration was evaluated using the wound healing assay. (Scale bar of <b>N</b>: 400 μm)Statistical analyses were performed using a one-way analysis of variance (ANOVA), followed by Tukey’s post-hoc test (n ≥ 3). # <span class="html-italic">p</span> &lt; 0.05 and ## <span class="html-italic">p</span> &lt; 0.01 vs. the control group; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 vs. the H<sub>2</sub>O<sub>2</sub> group.</p>
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<p>Effects of CGPG-HFn@MnO<sub>2</sub>/AS on rats undergoing SCI. (<b>A</b>,<b>B</b>) The hind-limb motor function recovery of SCI rats was evaluated using footprint analysis. ## <span class="html-italic">p</span> &lt; 0.01 vs. the control group; ** <span class="html-italic">p</span> &lt; 0.01 vs. the SCI group. (<b>C</b>) The degree of hind-limb recovery was evaluated by the BBB score. ## <span class="html-italic">p</span> &lt; 0.01 vs. the sham group; ** <span class="html-italic">p</span> &lt; 0.01 vs. the SCI group. (<b>D</b>) The histological lesion was evaluated using H&amp;E staining. (<b>E</b>–<b>J</b>) The protein levels of SIRT1, XCT, GPX4, 4-HNE, and TFR1 were detected using a western blot assay. G1: sham group. G2: SCI group. G3: CGPG-HFn@MnO<sub>2</sub>/AS group. G4:CGPG group. G5: CGPG-HFn@MnO<sub>2</sub>/AS. (<b>K</b>) The level of iron in the spinal cord was detected using a kit. (<b>L</b>) The level of GSH in the spinal cord was detected using a kit. (<b>M</b>) The level of MDA in the spinal cord was detected using a kit. (<b>N</b>) The activity of SOD in the spinal cord was detected using a kit. Statistical analyses were performed using a one-way analysis of variance (ANOVA), followed by Tukey’s post-hoc test (n ≥ 3). ## <span class="html-italic">p</span> &lt; 0.01 vs. the sham group; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 vs. the SCI group.</p>
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<p>Safety analysis of CGPG-HFn@MnO<sub>2</sub>/AS hydrogels. (<b>A</b>) H&amp;E staining images of different organs (heart, liver, spleen, lung, and kidney) in healthy SD rats after administration (n = 3) (Scale bar: 200 μm). (<b>B</b>) Hematology analysis of RBCs, HGBs, PLTs, and WBCs in different groups (n = 3). (<b>C</b>) Serum biochemical analysis of BUN, ALT, AST, and ALP in different groups (n = 3).</p>
Full article ">
28 pages, 6893 KiB  
Review
Mechanism of Reactive Oxygen Species-Guided Immune Responses in Gouty Arthritis and Potential Therapeutic Targets
by Sai Zhang, Daocheng Li, Mingyuan Fan, Jiushu Yuan, Chunguang Xie, Haipo Yuan, Hongyan Xie and Hong Gao
Biomolecules 2024, 14(8), 978; https://doi.org/10.3390/biom14080978 - 9 Aug 2024
Viewed by 356
Abstract
Gouty arthritis (GA) is an inflammatory disease caused by monosodium urate (MSU) crystals deposited in the joint tissues causing severe pain. The disease can recur frequently and tends to form tophus in the joints. Current therapeutic drugs for the acute phase of GA [...] Read more.
Gouty arthritis (GA) is an inflammatory disease caused by monosodium urate (MSU) crystals deposited in the joint tissues causing severe pain. The disease can recur frequently and tends to form tophus in the joints. Current therapeutic drugs for the acute phase of GA have many side effects and limitations, are unable to prevent recurrent GA attacks and tophus formation, and overall efficacy is unsatisfactory. Therefore, we need to advance research on the microscopic mechanism of GA and seek safer and more effective drugs through relevant targets to block the GA disease process. Current research shows that the pathogenesis of GA is closely related to NLRP3 inflammation, oxidative stress, MAPK, NET, autophagy, and Ferroptosis. However, after synthesizing and sorting out the above mechanisms, it is found that the presence of ROS is throughout almost the entire spectrum of micro-mechanisms of the gout disease process, which combines multiple immune responses to form a large network diagram of complex and tight connections involved in the GA disease process. Current studies have shown that inflammation, oxidative stress, cell necrosis, and pathological signs of GA in GA joint tissues can be effectively suppressed by modulating ROS network-related targets. In this article, on the one hand, we investigated the generative mechanism of ROS network generation and its association with GA. On the other hand, we explored the potential of related targets for the treatment of gout and the prevention of tophus formation, which can provide effective reference ideas for the development of highly effective drugs for the treatment of GA. Full article
(This article belongs to the Special Issue New Insights into Reactive Oxygen Species in Cell Death and Immunity)
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<p>ROS generation mechanism in GA: The pathway of ROS production in the organism is broadly categorized into exogenous stimulation and endogenous activation, in which endogenous activation of ROS production scenarios mainly include the mitochondria, endoplasmic reticulum, and the nucleus, and a variety of metabolic disorders can contribute to the abnormal accumulation of ROS, in which uric acid is one of the triggers of ROS production, and the production of excess ROS is an important prerequisite for the disease process of GA. ADP: Adenosine Diphosphate; ATP: Adenosine Triphosphate; AQP11: Aquaporin11; BckaDH: branched-chain ketoacid dehydrogenase; CAT: catalase; Cyp: cytochrome P450; Cyt c: Cytochrome c; ETFQO: electron transfer flavoprotein oxidoreductase; FAD: flavin adenine dinucleotide; FADH2: flavin adenine dinucleotide; G3PDH: dehydrogenase; GPX: glutathione peroxidase; GR: glutathione reductase; GRP75: glucose-regulated chaperone protein 75; GSH: glutathione; GSSG: oxidized glutathione; H<sub>2</sub>O<sub>2</sub>: hydrogen peroxide; IP3R: inositol 1,4,5-trisphosphate receptors; MCU: Mitochondrial Calcium Uniporter; MPO: Myeloperoxidase; mPTP: mitochondrial permeability transition pore; MSU: monosodium urate; NAD<sup>+</sup>: Nicotinamide adenine dinucleotide; NADH: ubiquinone oxidoreductase; NADPH: nicotinamide adenine dinucleotide phosphate oxidase; •NO: nitric oxide; •NO<sub>2</sub>: nitrogen dioxide; NOS: nitric oxide synthase; NOX: NADPH oxidase; O<sub>2</sub><sup>•−</sup>: superoxide anion; PDH: pyruvate dehydrogenase; ProDH: proline dehydrogenase; PRX: peroxiredoxin; ROS: reactive oxygen species; RyR2: ryanodine receptors type 2; SOD: superoxide-dismutase; SQR: succinate: quinone reductase; TRX: Thioredoxin; TrxR (TR): Thioredoxin reductase; UA: Uric acid; VDAC1: voltage-dependent anion channel 1; XO: xanthine oxidase.</p>
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<p>ROS network formation mechanism in GA: ROS not only contribute to tissue cell damage through the oxidative stress process in the gout disease process, but also act as signaling molecules to activate inflammation, autophagy, NET, and Ferroptosis to cause tissue cell damage in multiple ways, and each pathway interacts with each other, ultimately forming a large network diagram involved in the disease process of GA. AKT: protein kinase B; AMPK: Adenosine 5′-monophosphate (AMP)-activated protein kinase; Atg4: Autophagy protein 4; ARE: Antioxidant Response Element; ASK/Raf/MLK/MEKK/TAK: A member of the MAPKKK family; BNIP3: BCL2/adenovirus E1B 19 kDa interacting protein 3; CAT: catalase; DAMP: damage-associated molecular pattern; ERK/JNK/p38: A member of the MAPK family; FOXO3: Forkhead Box Protein O3; GPX: glutathione peroxidase; GSDMD: gasdermin D; GSH: glutathione; IL-1β/18: interleukin-1β/18; Keap1: Kelch-like ECH-associated protein 1; LC-3: microtubule-associated protein light chain 3; MAPK: mitogen-activated protein kinase; MAPKK: MAP kinase kinase; MAPKKK: MAP kinase kinase kinase; MEK/MKK: A member of the MAPKK family; MPO: Myeloperoxidase; MSU: monosodium urate; mTOR: mammalian target of rapamycin; NADPH: nicotinamide adenine dinucleotide phosphate oxidase; NCX: Sodium Calcium Exchanger; NE: neutrophil elastase; NEK7: NIMA-related kinase 7; NET: neutrophil extracellular traps; NF-κB: nuclear factor kappa-B; NOX: NADPH oxidase; NLRP3: NOD-like receptor thermal protein domain-associated protein 3; Nrf2: Nuclear factor erythroid2-related factor 2; P62: Sequestosome 1; PAD4: peptidylarginine deiminase 4; PAMP: pathogen-associated molecular pattern; PI3K: phosphoinositide 3-kinase; PRX: peroxiredoxin; ROS: reactive oxygen species; sMaf: small musculoaponeurotic fibrosarcoma; SOD: superoxide-dismutase; TLR4: Toll-like receptor 4; TRX: Thioredoxin; TXNIP: thioredoxin interacting protein; UA: Uric acid; XO: xanthine oxidase.</p>
Full article ">Figure 3
<p>Mechanism of ROS-NLRP3 inflammation in GA environment: GSDMD: gasdermin D; IKK: Inhibitor of kappa B kinase; IL-1β/18: interleukin-1β/18; MSU: monosodium urate; MyD88: Myeloid differentiation primary response 88; NF-κB: nuclear factor kappa-B; NOX: NADPH oxidase; NLRP3: NOD-like receptor thermal protein domain-associated protein 3; ROS: reactive oxygen species; TLR4: Toll-like receptor 4; UA: Uric acid; XO: xanthine oxidase.</p>
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<p>Mechanism of ROS-MAPK in GA environment: ASK/Raf/MLK/MEKK/TAK: A member of the MAPKKK family; ERK/JNK/p38: A member of the MAPK family; MAPK: mitogen-activated protein kinase; MAPKK: MAP kinase kinase; MAPKKK: MAP kinase kinase kinase; MEK/MKK: A member of the MAPKK family; MSU: monosodium urate; NF-κB: nuclear factor kappa-B; NOX: NADPH oxidase; Nrf2: Nuclear factor erythroid2-related factor 2; UA: Uric acid; XO: xanthine oxidase.</p>
Full article ">Figure 5
<p>Mechanism of ROS-NET in GA environment: IL-1β/18: interleukin-1β/18; MPO: Myeloperoxidase; MSU: monosodium urate; NE: neutrophil elastase; NOX: NADPH oxidase; PAD4: peptidylarginine deiminase 4; ROS: reactive oxygen species; UA: Uric acid; XO: xanthine oxidase.</p>
Full article ">Figure 6
<p>Mechanism of ROS-autophagy in GA environment: AKT: protein kinase B; AMPK: Adenosine 5′-monophosphate (AMP)-activated protein kinase; Atg4: Autophagy protein 4; BNIP3: BCL2/adenovirus E1B 19kDa interacting protein 3; FOXO3: Forkhead Box Protein O3; IL-1β: interleukin-1β; LC-3: microtubule-associated protein light chain 3; MSU: monosodium urate; mTOR: mammalian target of rapamycin; Nrf2: Nuclear factor erythroid2-related factor 2; P62: Sequestosome 1; PI3K: phosphoinositide 3-kinase; ROS: reactive oxygen species; UA: Uric acid; XO: xanthine oxidase.</p>
Full article ">Figure 7
<p>Mechanism of ROS-Ferroptosis in GA environment: MSU: monosodium urate; NOX: NADPH oxidase; PUFA: polyunsaturated fatty acid; ROS: reactive oxygen species; TRP: transient receptor potential; UA: Uric acid; XO: xanthine oxidase.</p>
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<p>Mechanism of ROS-Nrf2 antioxidant response in GA environment: Cul3: Cullin 3; Keap1: Kelch-like ECH-associated protein 1; MSU: monosodium urate; NOX: NADPH oxidase; Nrf2: Nuclear factor erythroid2-related factor 2; ROS: reactive oxygen species; UA: Uric acid; XO: xanthine oxidase.</p>
Full article ">Figure 9
<p>Diagram of ROS network crosstalk mechanism: NRF2: Nuclear factor erythroid2-related factor 2; ROS: reactive oxygen species; MAPK: mitogen-activated protein kinase; NLRP3: NOD-like receptor thermal protein domain-associated protein 3; NET: neutrophil extracellular traps.</p>
Full article ">
17 pages, 4331 KiB  
Article
Mechanisms of Cell Death Induced by Erastin in Human Ovarian Tumor Cells
by Birandra K. Sinha, Carri Murphy, Shalyn M. Brown, Brian B. Silver, Erik J. Tokar and Carl D. Bortner
Int. J. Mol. Sci. 2024, 25(16), 8666; https://doi.org/10.3390/ijms25168666 - 8 Aug 2024
Viewed by 216
Abstract
Erastin (ER) induces cell death through the formation of reactive oxygen species (ROS), resulting in ferroptosis. Ferroptosis is characterized by an accumulation of ROS within the cell, leading to an iron-dependent oxidative damage-mediated cell death. ER-induced ferroptosis may have potential as an alternative [...] Read more.
Erastin (ER) induces cell death through the formation of reactive oxygen species (ROS), resulting in ferroptosis. Ferroptosis is characterized by an accumulation of ROS within the cell, leading to an iron-dependent oxidative damage-mediated cell death. ER-induced ferroptosis may have potential as an alternative for ovarian cancers that have become resistant due to the presence of Ras mutation or multi-drug resistance1 (MDR1) gene expression. We used K-Ras mutant human ovarian tumor OVCAR-8 and NCI/ADR-RES, P-glycoprotein-expressing cells, to study the mechanisms of ER-induced cell death. We used these cell lines as NCI/ADR-RES cells also overexpresses superoxide dismutase, catalase, glutathione peroxidase, and transferase compared to OVCAR-8 cells, leading to the detoxification of reactive oxygen species. We found that ER was similarly cytotoxic to both cells. Ferrostatin, an inhibitor of ferroptosis, reduced ER cytotoxicity. In contrast, RSL3 (RAS-Selective Ligand3), an inducer of ferroptosis, markedly enhanced ER cytotoxicity in both cells. More ROS was detected in OVCAR-8 cells than NCI/ADR-RES cells, causing more malondialdehyde (MDA) formation in OVCAR-8 cells than in NCI/ADR-RES cells. RSL3, which was more cytotoxic to NCI/ADR-RES cells, significantly enhanced MDA formation in both cells, suggesting that glutathione peroxidase 4 (GPX4) was involved in ER-mediated ferroptosis. ER treatment modulated several ferroptosis-related genes (e.g., CHAC1, GSR, and HMOX1/OX1) in both cells. Our study indicates that ER-induced ferroptotic cell death may be mediated similarly in both NCI/ADR-RES and OVCAR-8 cells. Additionally, our results indicate that ER is not a substrate of P-gp and that combinations of ER and RSL3 may hold promise as more effective treatment routes for ovarian cancers, including those that are resistant to other current therapeutic agents. Full article
(This article belongs to the Section Molecular Oncology)
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<p>Cytotoxicity of erastin in OVCAR-8 and NCI/ADR-RES cells following 72 h of treatment using TiterGlo (<b>A</b>) and Trypan Blue (<b>B</b>) cytotoxicity assays.</p>
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<p>Effects of Ferrostatin-1 (<b>A</b>,<b>B</b>) on the cytotoxicity of erastin in ovarian cells following 48 h incubations. (<b>A</b>) OVCAR-8 and (<b>B</b>) NCI/ADR-RES cells, respectively. Effects of RSL3 (0.5 µM) on cytotoxicity of ER following 24 h of incubations (<b>C</b>) OVCAR-8 and (<b>D</b>) NCI/ADR-RES cells. *, **, and *** <span class="html-italic">p</span> values &gt; 0.05, 0.005, and 0.001, respectively, compared to untreated control. ## and ### <span class="html-italic">p</span> values &gt; 0.005 and 0.001, respectively, compared to treated FES or RSL3 alone to treated ER + FES or ER + RSL3. <span>$</span><span>$</span><span>$</span> <span class="html-italic">p</span> values &lt; 0.001, compared to treated ER alone.</p>
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<p>Dose dependence of RSL3 cytotoxicity in OVCAR-8 (<b>A</b>) and NCI/ADR-RES cells (<b>B</b>). The cells were incubated with different concentrations of RSL3 for 24 h. ## and ### &lt;0.005 and 0.001, respectively, and *** <span class="html-italic">p</span> values &lt; 0.001, compared to untreated control.</p>
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<p>Effects of ER on the Xc-transporter in OVCAR-8 (<b>A</b>) and NCI/ADR-RES (<b>B</b>) cells. *** <span class="html-italic">p</span> values &lt; 0.001, compared to untreated controls; ### and <span>$</span><span>$</span><span>$</span> <span class="html-italic">p</span> values &lt; 0.001 compared to Se-Cysteine treated cells.</p>
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<p>Formation of Mitosox+ cells in OVCAR-8 and NCI/ADR-RES cells following 4 h incubations with ER (<b>B</b>). A representative scatter plot (<b>A</b>) for OVCAR-8 and NCI/ADR-RES cells is shown here. *** <span class="html-italic">p</span> values &lt; 0.001, respectively, compared to untreated control.</p>
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<p>Dose dependence of ER-induced lipid peroxidation in OVCAR-8 and NCI/ADR-RES cells at 4 h (<b>A</b>) and effects of RSL3 on MDA formation (<b>B</b>). The MDA formation was measured at 532 mM. ** and *** <span class="html-italic">p</span> values &lt; 0.005 and &lt;0.001, respectively, compared to untreated control.</p>
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<p>Effects of N-acetyl Cysteine (NAC) on ER cytotoxicity in OVCAR-8 (<b>A</b>) and NCI/ADR-RES cells (<b>B</b>). The cells were incubated with 100 µM NAC for 30 min before adding ER for 24 h. ** and *** <span class="html-italic">p</span> values &lt; 0.005 and 0.001, compared to untreated control. <span>$</span><span>$</span> and ###, <span class="html-italic">p</span> values &lt; 0.005 and 0.001, respectively, compared to ER values alone.</p>
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<p>Effects of erastin (2.5 µM) on various oxidative and ferroptosis-related genes in OVCAR-8 (<b>A</b>) and NCI/ADR-RES cells (<b>B</b>) cells following treatment with erastin for 4 h and 24 h. Protein levels for GPX4, NrF2, and NOX4 following treatment with 2.5 µM for 4 and 24 h in OVCAR-8 and NCI/ADR-RES cells (<b>C</b>). * <span class="html-italic">p</span> &lt; 0.05, ** and *** <span class="html-italic">p</span> values &lt; 0.005 and 0.001, respectively, compared to control (β-Actin at 4 h and 24 h, respectively).</p>
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<p>Effects of erastin on Xc- transporter, VDAC, <span class="html-italic">CHAC1</span>, <span class="html-italic">HMOX1</span>, iNOS, and their implications in erastin-induced lipid peroxidation and ferroptosis in OVCAR-8 and NCI/ADR-RES cells.</p>
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16 pages, 13502 KiB  
Article
Identification of Penexanthone A as a Novel Chemosensitizer to Induce Ferroptosis by Targeting Nrf2 in Human Colorectal Cancer Cells
by Genshi Zhao, Yanying Liu, Xia Wei, Chunxia Yang, Junfei Lu, Shihuan Yan, Xiaolin Ma, Xue Cheng, Zhengliang You, Yue Ding, Hongwei Guo, Zhiheng Su, Shangping Xing and Dan Zhu
Mar. Drugs 2024, 22(8), 357; https://doi.org/10.3390/md22080357 - 6 Aug 2024
Viewed by 396
Abstract
Ferroptosis has emerged as a potential mechanism for enhancing the efficacy of chemotherapy in cancer treatment. By suppressing nuclear factor erythroid 2-related factor 2 (Nrf2), cancer cells may lose their ability to counteract the oxidative stress induced by chemotherapy, thereby becoming more susceptible [...] Read more.
Ferroptosis has emerged as a potential mechanism for enhancing the efficacy of chemotherapy in cancer treatment. By suppressing nuclear factor erythroid 2-related factor 2 (Nrf2), cancer cells may lose their ability to counteract the oxidative stress induced by chemotherapy, thereby becoming more susceptible to ferroptosis. In this study, we investigate the potential of penexanthone A (PXA), a xanthone dimer component derived from the endophytic fungus Diaporthe goulteri, obtained from mangrove plant Acanthus ilicifolius, to enhance the therapeutic effect of cisplatin (CDDP) on colorectal cancer (CRC) by inhibiting Nrf2. The present study reported that PXA significantly improved the ability of CDDP to inhibit the activity of and induce apoptosis in CRC cells. Moreover, PXA was found to increase the level of oxidative stress and DNA damage caused by CDDP. In addition, the overexpression of Nrf2 reversed the DNA damage and ferroptosis induced by the combination of PXA and CDDP. In vivo experiments using zebrafish xenograft models demonstrated that PXA enhanced the therapeutic effect of CDDP on CRC. These studies suggest that PXA enhanced the sensitivity of CRC to CDDP and induce ferroptosis by targeting Nrf2 inhibition, indicating that PXA might serve as a novel anticancer drug in combination chemotherapy. Full article
(This article belongs to the Special Issue Pharmacological Potential of Marine Natural Products, 2nd Edition)
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<p>PXA sensitizes CRC cells to CDDP-induced cytotoxicity and apoptosis. (<b>A</b>) Chemical structural of PXA. (<b>B</b>) CRC cells were co-treated with PXA and CDDP for 48 h, and the percentage of cell viability was determined by CCK-8 assay. (<b>C</b>) 3D visualization of synergy scores between PXA and CDDP obtained using the SynergyFinder tool; these calculated average synergy scores are 20.7 and 11.3 for these two panels of drug combinations (Synergy scores &gt; 10 are considered synergistic). (<b>D</b>) The percentage of apoptotic cells was analyzed and quantified using flow cytometry after Annexin V-FITC/PI staining. (<b>E</b>) The protein levels of Cleaved-PARP, Cleaved-caspase-3, BAX, and Bcl-2 in HCT116 and HT29 cells were detected by Western blot after 24 h treatment; β-acting was used as a loading control. Results are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 versus the control group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 versus the CDDP-treatment group.</p>
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<p>PXA increased CDDP-induced ROS production. (<b>A</b>,<b>B</b>) HCT116 and HT29 cells treated with PXA and CDDP were incubated with the DCFH-DA probe for 20 min, and the ROS levels (DCF fluorescence) were observed and analyzed by fluorescence microscopy (<b>A</b>) and flow cytometry (<b>B</b>). Scale bars: 100 μm. Results are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 versus the control group, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 versus the CDDP-treatment group.</p>
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<p>PXA increased CDDP-induced DNA damage and oxidative stress. (<b>A</b>) DNA damage levels in HCT116 and HT29 cells treated with PXA and CDDP for 24 h were assessed using the comet assay. Scale bars: 100 μm. (<b>B</b>) After 24 h of treating HCT116 and HT29 cells with PXA and CDDP, the content of GSH, SOD, and HO-1 was measured using ELISA. Results are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 versus the control group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 versus the CDDP-treatment group.</p>
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<p>PXA inhibits Nrf2 protein expression. (<b>A</b>,<b>B</b>) Western blotting analyses of Nrf2 expression in HCT116 and HT29 cells treated with PXA for indicated concentrations (<b>A</b>) and time points (<b>B</b>). (<b>C</b>) CETSA was performed to confirm that PXA targets Nrf2 proteins. Results are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 versus the control group.</p>
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<p>Nrf2 overexpression reverses the chemosensitizing activity of PXA. (<b>A</b>) Protein levels of Nrf2 in stably overexpressing empty vector (EV) and Nrf2 HCT116 and HT29 cells were examined by Western blotting. (<b>B</b>) Western blot assay to detect the effect of PXA in combination with CDDP on Nrf2 protein in EV and Nrf2 stable overexpressing HCT116 and HT29 cells. (<b>C</b>) CCK-8 assay was performed on EV and Nrf2 stable overexpressing HCT116 and HT29 cells treated with PXA and CDDP for 48 h. (<b>D</b>) The DNA damage levels of EV and Nrf2 stable overexpressing HCT116 and HT29 cells treated with PXA and CDDP for 24 h were evaluated using the comet assay. Scale bars: 100 μm. Results are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 versus the EV group.</p>
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<p>PXA enhances CDDP-induced ferroptosis by inhibiting Nrf2 pathway. (<b>A</b>) HCT116 and HT29 cells were treated with PXA and CDDP with or without ferroptosis inhibitor (Fer-1) for 24h, and cell viability was measured using the CCK-8 assay. (<b>B</b>) Detection of lipid hydroperoxides by fluorescence imaging of Liperfluo in HCT116 and HT29 cells treated with PXA and CDDP with or without Fer-1. Scale bars: 100 μm. (<b>C</b>) EV and Nrf2 stable overexpressing HCT116 and HT29 cells were treated with PXA and CDDP for 24 h and the expression of SLC7A11 and GPX4 were examined by Western blotting. Results are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 versus the control group, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 versus the Fer-1 group, <sup>%</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>%%</sup> <span class="html-italic">p</span> &lt; 0.01 versus the EV group.</p>
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<p>PXA enhances the therapeutic efficacy of CDDP in CRC xenograft zebrafish model. (<b>A</b>) HCT116-CM-Dil cells were injected into zebrafish embryo. At the end of the experiments, phenotypic map of fluorescence of HCT116-CM-Dil cells in zebrafish were photographed. Scale bars: 250 μm (<b>B</b>) The fluorescence area and intensity of HCT116-CM-Dil cells in zebrafish were analyzed by Image J software (Version 1.54j). Results are expressed as means ± SD. ** <span class="html-italic">p</span> &lt; 0.01 versus the control group, <span class="html-italic"><sup>##</sup> p</span> &lt; 0.01 versus the CDDP-treatment group.</p>
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<p>Schematic representation of PXA enhancing the sensitivity of CRC cells to CDDP by inducing ferroptosis through the inhibition of Nrf2. “↓” indicates promotion; “⊥” indicates inhibition.</p>
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30 pages, 9550 KiB  
Article
Abnormal Histopathological Expression of Klotho, Ferroptosis, and Circadian Clock Regulators in Pancreatic Ductal Adenocarcinoma: Prognostic Implications and Correlation Analyses
by Cielo García-Montero, Oscar Fraile-Martinez, David Cobo-Prieto, Diego De Leon-Oliva, Diego Liviu Boaru, Patricia De Castro-Martinez, Leonel Pekarek, Raquel Gragera, Mauricio Hernández-Fernández, Luis G. Guijarro, María Del Val Toledo-Lobo, Laura López-González, Raul Díaz-Pedrero, Jorge Monserrat, Melchor Álvarez-Mon, Miguel A. Saez and Miguel A. Ortega
Biomolecules 2024, 14(8), 947; https://doi.org/10.3390/biom14080947 - 5 Aug 2024
Viewed by 386
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal tumor with increasing incidence, presenting numerous clinical challenges. The histopathological examination of novel, unexplored biomarkers offers a promising avenue for research, with significant translational potential for improving patient outcomes. In this study, we evaluated the [...] Read more.
Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal tumor with increasing incidence, presenting numerous clinical challenges. The histopathological examination of novel, unexplored biomarkers offers a promising avenue for research, with significant translational potential for improving patient outcomes. In this study, we evaluated the prognostic significance of ferroptosis markers (TFRC, ALOX-5, ACSL-4, and GPX-4), circadian clock regulators (CLOCK, BMAL1, PER1, PER2), and KLOTHO in a retrospective cohort of 41 patients deceased by PDAC. Immunohistochemical techniques (IHC) and multiple statistical analyses (Kaplan–Meier curves, correlograms, and multinomial linear regression models) were performed. Our findings reveal that ferroptosis markers are directly associated with PDAC mortality, while circadian regulators and KLOTHO are inversely associated. Notably, TFRC emerged as the strongest risk marker associated with mortality (HR = 35.905), whereas CLOCK was identified as the most significant protective marker (HR = 0.01832). Correlation analyses indicate that ferroptosis markers are positively correlated with each other, as are circadian regulators, which also positively correlate with KLOTHO expression. In contrast, KLOTHO and circadian regulators exhibit inverse correlations with ferroptosis markers. Among the clinical variables examined, only the presence of chronic pathologies showed an association with the expression patterns of several proteins studied. These findings underscore the complexity of PDAC pathogenesis and highlight the need for further research into the specific molecular mechanisms driving disease progression. Full article
(This article belongs to the Special Issue Genetic and Genomic Biomarkers of Cancer)
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<p>(<b>A</b>) Kaplan–Meier curves for survival time (months) according to tumor expression of TFRC. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>) Histopathological images for high (intense brown staining) versus low/medium expression of TFRC.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of ACSL-4. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of ACSL-4.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of ALOX-5. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of ALOX-5.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of GPX4. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of GPX4.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of Bmal 1. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of Bmal1.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of CLOCK. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of CLOCK.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of PER1. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of PER1.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of PER2. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of PER2.</p>
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<p>(<b>A</b>). Kaplan–Meier curves for survival time (months) according to tumor expression of KLOTHO. Blue curve: negative tissue expression; red curve: low/medium expression; green curve: high expression. (<b>B</b>,<b>C</b>). Histopathological images for high (intense brown staining) versus low/medium expression of KLOTHO.</p>
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<p>Pairwise Heatmap Matrix with Spearman correlation coefficients. <span class="html-italic">p</span> values associated to each Spearman correlation coefficient appear with asterisks and are adjusted by False Discovery Rate correction (FDR): adjusted alpha. We represent in cyan the variables with a protective role and in pink those that are risk markers. *** = <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>A graphical summary of our results and proposed biological networks that may be acting. Red arrows represent inhibitory effects, black arrows defines established bidirectional or unidirectional associations.</p>
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19 pages, 8754 KiB  
Article
Unraveling Novel Strategies in Mesothelioma Treatments Using a Newly Synthetized Platinum(IV) Compound
by Cristina Favaron, Ludovica Gaiaschi, Claudio Casali, Fabrizio De Luca, Federica Gola, Margherita Cavallo, Valeria Ramundo, Elisabetta Aldieri, Gloria Milanesi, Silvia Damiana Visonà, Mauro Ravera and Maria Grazia Bottone
Pharmaceutics 2024, 16(8), 1015; https://doi.org/10.3390/pharmaceutics16081015 - 31 Jul 2024
Viewed by 505
Abstract
Malignant mesothelioma is a rare tumor associated with asbestos exposure. Mesothelioma carcinogenesis is related to enhanced reactive oxygen species (ROS) production and iron overload. Despite the recent advances in biomedical sciences, to date the only available treatments include surgery in a small fraction [...] Read more.
Malignant mesothelioma is a rare tumor associated with asbestos exposure. Mesothelioma carcinogenesis is related to enhanced reactive oxygen species (ROS) production and iron overload. Despite the recent advances in biomedical sciences, to date the only available treatments include surgery in a small fraction of patients and platinum-based chemotherapy in combination with pemetrexed. In this view, the purpose of this study was to evaluate the therapeutic potential of the newly synthetized platinum prodrug Pt(IV)Ac-POA compared to cisplatin (CDDP) on human biphasic mesothelioma cell line MSTO-211H using different complementary techniques, such as flow-cytometry, transmission electron microscopy (TEM), and immunocytochemistry. Healthy mesothelial cell lines Met-5A were also employed to assess the cytotoxicity of the above-mentioned compounds. Our in vitro results showed that Pt(IV)Ac-POA significantly interfere with iron metabolisms and more importantly is able to trigger cell death, through different pathways, including ferroptosis, necroptosis, and apoptosis, in neoplastic cells. On the other hand, CDDP triggers mainly apoptotic and necrotic cell death. In conclusion, Pt(IV)Ac-POA may represent a new promising pharmacological agent in the treatment of malignant mesothelioma. Full article
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<p>Structures of cisplatin and Pt(IV)Ac-POA. Sketch of cisplatin (CDDP), 2-(2-propynyl)octanoic acid, POA, and its Pt(IV) derivative (OC-6-44)-acetatodiamminedichlorido(2-(2-propynyl)octanoato)platinum(IV), Pt(IV)Ac-POA. The asterisk denotes a chiral center.</p>
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<p>CDDP and Pt(IV)Ac-POA affect cell cycle and histone acetylation. (<b>A</b>) Cytofluorimetric analysis. Graphs showing DNA content after PI staining human MSTO-211H cells in control condition and after 12 h and 48 h of CT with CDDP and Pt(IV)Ac-POA treatments (10μM). (<b>B</b>) Stacked histograms displaying the percentage of events recorded across the different cell cycle phases after treatments. (<b>C</b>) Control samples vs. treated cells after 12 h and 48 h of CT to CDDP and Pt(IV)Ac-POA (10 μM). Double immunofluorescence reaction, with the relative quantification, for Ki-67 (red) and acetyl-H3 (green), nuclei were counterstained with Hoechst 33258 (blue) Bar = 40 μm; magnification: 60×. (<b>D</b>,<b>E</b>) Histograms illustrating the results of imaging and statistical analysis for (<b>D</b>) Ki-67 positive cells and (<b>E</b>) Acetyl-H3 fluorescence quantification. One-way ANOVA test: <span class="html-italic">p</span> &lt; 0.0001. * statistical significance respect to control condition is marked by an asterisk; <span class="html-italic">p</span>-values: (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Ultrastructural analysis reveals the activation of different pathways of cell death. (<b>A</b>) MSTO-211H cells in control conditions. (<b>B</b>,<b>C</b>) Cells treated for 12 and 48 h with CDDP 10 μM. Examples of necrosis (<b>B</b>) and apoptosis (<b>C</b>). (<b>D</b>–<b>G</b>) Cells after 12 and 48 h of CT with 10 μM -Pt(IV)Ac-POA prodrug. Examples of (<b>D</b>–<b>F</b>) necroptosis, (<b>E</b>) apoptosis with some vesicles enclosing cell debris (insert), and (<b>G</b>) ferroptosis. Legend: nucleus (n), Golgi apparatus (g), mitochondria (m), citoplasmic vesicles (v), perinuclear space (p).</p>
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<p>BAP1 and NF2 expression are altered by the pharmacological insults. Double immunocytochemical reaction for BAP1 (red fluorescence)<span class="html-italic">—</span>α-tubulin (red) and NF2 (green fluorescence)<span class="html-italic">—</span>β actin (green); DNA counterstaining with Hoechst 33258 (blue fluorescence) in control condition and CDDP- and Pt(IV)Ac-POA (10 μM)-treated samples (both MSTO-211H and Met-5A cells). Bar = 40 μm; magnification: 60×. Histogram represents the relative expression of BAP1 and NF2 for MSTO-211H (pink) and Met-5A (blue) cell lines. Statistical analysis: Two-way ANOVA test: <span class="html-italic">p</span> &lt; 0.0001. * statistical significance with respect to control condition is marked by an asterisk; <span class="html-italic">p</span>-values: (*) <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; 0.005, (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Pt(IV)Ac-POA enhances ROS production. Double immunocytochemical reaction for COX2 (green fluorescence), NRF2 (green fluorescence), Aconitase-2 (green fluorescence), and mitochondria (red fluorescence); DNA counterstaining with Hoechst 33258 (blue fluorescence) in control condition and CDDP and Pt(IV)Ac-POA (10 μM) in MSTO-211H and Met-5A cell lines Bar = 40 μm; magnification: 60×.</p>
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<p>Fluorescent quantification of the investigated markers. Histogram represents the relative expression of COX2, NRF2, Aco2, GPX4, FTH1, and SLC7A11 in the control condition, CDDP, and Pt(IV)Ac-POA (10 μM). Statistical analysis: Two-way ANOVA test. * statistical significance with respect to control condition is marked by an asterisk; <span class="html-italic">p</span>-values: (*) <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; 0.005, (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Pt(IV)Ac-POA triggers the ferroptotic pathway. Double immunocytochemical reaction for GPX4 (green fluorescence)—mitochondria (red fluorescence), FTH1 (green fluorescence)<span class="html-italic">—</span>α-tubulin (red fluorescence), and SLC7A11 (green fluorescence)<span class="html-italic">—</span>α-tubulin (red fluorescence); DNA counterstaining with Hoechst 33258 (blue fluorescence) in control condition and CDDP and Pt(IV)Ac-POA (10 μM). Bar = 40 μm; magnification: 60×.</p>
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<p>Cleaved caspase-3 is detected after treatments in MSTO-211H cell line. Double immunocytochemical reaction for cleaved caspase-3 (green fluorescence) and α-tubulin (red fluorescence); DNA counterstaining with Hoechst 33258 (blue fluorescence) in control condition, CDDP-, and Pt(IV)Ac-POA-treated samples (10 μM). Bar = 40 μm; magnification: 60×. Histogram showing the percentage (%) of positive cleaved caspase-3 cells. Statistical analysis: Two-way ANOVA test. * statistical significance with respect to control condition is marked by an asterisk; <span class="html-italic">p</span>-values: (**) <span class="html-italic">p</span> &lt; 0.01, (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Pt(IV)Ac-POA causes the blockage of the autophagic flux in MSTO-211H cells. Double immunocytochemical reaction for LC3B (red fluorescence), p62/SQSTM1 (red fluorescence), and lysosomes (green fluorescence); DNA counterstaining with Hoechst 33258 (blue fluorescence) in control condition, CDDP-, and Pt(IV)Ac-POA0-treated samples (10 μM). Bar = 40 μm; magnification: 60×. Histogram showing the fluorescence quantification for LC3B and p62/SQSTM1. Statistical analysis: Two-way ANOVA test. * statistical significance with respect to control condition is marked by an asterisk; <span class="html-italic">p</span>-values: (*) <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; 0.005, (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Pt(IV)Ac-POA and CDDP trigger necroptotic cell death only in mesothelioma cell lines. Double immunocytochemical reaction for RIP1 (green fluorescence)—α-tubulin (red fluorescence) and MLKL (red fluorescence)—actin (green fluorescence); DNA counterstaining with Hoechst 33258 (blue fluorescence) in control condition, CDDP-, and Pt(IV)Ac-POA-treated samples (10 μM). Bar = 40 μm; magnification: 60×. Histogram showing the fluorescence quantification for RIP1 and MLKL. Statistical analysis: Two-way ANOVA test. * statistical significance with respect to control condition is marked by an asterisk; <span class="html-italic">p</span>-values: (***) <span class="html-italic">p</span> &lt; 0.005, (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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15 pages, 346 KiB  
Review
Nebulized Glutathione as a Key Antioxidant for the Treatment of Oxidative Stress in Neurodegenerative Conditions
by João Vitor Lana, Alexandre Rios, Renata Takeyama, Napoliane Santos, Luyddy Pires, Gabriel Silva Santos, Izair Jefthé Rodrigues, Madhan Jeyaraman, Joseph Purita and Jose Fábio Lana
Nutrients 2024, 16(15), 2476; https://doi.org/10.3390/nu16152476 - 31 Jul 2024
Viewed by 1037
Abstract
Glutathione (GSH), a tripeptide synthesized intracellularly, serves as a pivotal antioxidant, neutralizing reactive oxygen species (ROS) and reactive nitrogen species (RNS) while maintaining redox homeostasis and detoxifying xenobiotics. Its potent antioxidant properties, particularly attributed to the sulfhydryl group (-SH) in cysteine, are crucial [...] Read more.
Glutathione (GSH), a tripeptide synthesized intracellularly, serves as a pivotal antioxidant, neutralizing reactive oxygen species (ROS) and reactive nitrogen species (RNS) while maintaining redox homeostasis and detoxifying xenobiotics. Its potent antioxidant properties, particularly attributed to the sulfhydryl group (-SH) in cysteine, are crucial for cellular health across various organelles. The glutathione-glutathione disulfide (GSH-GSSG) cycle is facilitated by enzymes like glutathione peroxidase (GPx) and glutathione reductase (GR), thus aiding in detoxification processes and mitigating oxidative damage and inflammation. Mitochondria, being primary sources of reactive oxygen species, benefit significantly from GSH, which regulates metal homeostasis and supports autophagy, apoptosis, and ferroptosis, playing a fundamental role in neuroprotection. The vulnerability of the brain to oxidative stress underscores the importance of GSH in neurological disorders and regenerative medicine. Nebulization of glutathione presents a novel and promising approach to delivering this antioxidant directly to the central nervous system (CNS), potentially enhancing its bioavailability and therapeutic efficacy. This method may offer significant advantages in mitigating neurodegeneration by enhancing nuclear factor erythroid 2-related factor 2 (NRF2) pathway signaling and mitochondrial function, thereby providing direct neuroprotection. By addressing oxidative stress and its detrimental effects on neuronal health, nebulized GSH could play a crucial role in managing and potentially ameliorating conditions such as Parkinson’s Disease (PD) and Alzheimer’s Disease (AD). Further clinical research is warranted to elucidate the therapeutic potential of nebulized GSH in preserving mitochondrial health, enhancing CNS function, and combating neurodegenerative conditions, aiming to improve outcomes for individuals affected by brain diseases characterized by oxidative stress and neuroinflammation. Full article
(This article belongs to the Special Issue Glutathione and Its Related Enzymes in Health and Diseases)
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13 pages, 4624 KiB  
Article
Paeoniflorin Promotes Ovarian Development in Mice by Activating Mitophagy and Preventing Oxidative Stress
by Huaming Xi, Ziqian Wang, Minghui Li, Xing Duan and Yuan Li
Int. J. Mol. Sci. 2024, 25(15), 8355; https://doi.org/10.3390/ijms25158355 - 30 Jul 2024
Viewed by 467
Abstract
During the development of animal organs, various adverse stimuli or toxic environments can induce oxidative stress and delay ovarian development. Paeoniflorin (PF), the main active ingredient of the traditional Chinese herb Paeonia lactiflora Pall., has protective effects on various diseases by preventing oxidative [...] Read more.
During the development of animal organs, various adverse stimuli or toxic environments can induce oxidative stress and delay ovarian development. Paeoniflorin (PF), the main active ingredient of the traditional Chinese herb Paeonia lactiflora Pall., has protective effects on various diseases by preventing oxidative stress. However, the mechanism by which PF attenuates oxidative damage in mouse ovaries remains unclear. We evaluated the protective effects of PF on ovaries in an H2O2-induced mouse oxidative stress model. The H2O2-induced mouse ovarian oxidative stress model was used to explore the protective effect of PF on ovarian development. Histology and follicular development were observed. We then detected related indicators of cell apoptosis, oxidative stress, and autophagy in mouse ovaries. We found that PF inhibited H2O2-induced ovarian cell apoptosis and ferroptosis and promoted granulosa cell proliferation. PF prevented oxidative stress by increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) expression levels. In addition, the autophagic flux of ovarian cells was activated and was accompanied by increased lysosomal biogenesis. Moreover, PF-mediated autophagy was involved in clearing mitochondria damaged by H2O2. Importantly, PF administration significantly increased the number of primordial follicles, primary follicles, secondary follicles, and antral follicles. PF administration improved ovarian sizes compared with the H2O2 group. The present study suggested that PF administration reversed H2O2-induced ovarian developmental delay and promoted follicle development. PF-activated mitophagy is crucial for preventing oxidative stress and improving mitochondrial quality. Full article
(This article belongs to the Section Bioactives and Nutraceuticals)
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<p><b>Effects of PF on H<sub>2</sub>O<sub>2</sub>-induced ovarian developmental delay in mice</b>. (<b>A</b>) Mice were treated with normal saline, H<sub>2</sub>O<sub>2</sub>, or PF. (<b>B</b>) Quantification analysis of body weight (n = 10). (<b>C</b>) Quantification analysis of ovary weight (n = 10). (<b>D</b>) Quantification analysis of ovary weight/body weight (n = 10). (<b>E</b>) Histological changes in ovaries were examined by hematoxylin and eosin staining. PMF, primordial follicle. PFs, primary follicles. SF, secondary follicle. ANF, antral follicle. ATF, atretic follicle. (<b>F</b>–<b>J</b>) Quantification of the number of primordial follicles, primary follicles, secondary follicles, antral follicles, and atretic follicles (n = 5). Data represent mean ± SEM. Ctrl, control group. PF + H<sub>2</sub>O<sub>2</sub>, Paeoniflorin + H<sub>2</sub>O<sub>2</sub> group. ns, no significance. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p><b>PF promotes granulosa cell proliferation and inhibits H<sub>2</sub>O<sub>2</sub>-induced ovarian cell apoptosis</b>. (<b>A</b>,<b>B</b>) Representative immunofluorescence images and analysis of PCNA in ovary sections (Bar = 100 μm). (<b>C</b>–<b>E</b>) Western blot and quantification of BAX and BCL2 in ovarian tissues (n = 6). ACTB served as an internal control. (<b>F</b>,<b>G</b>) Quantification of TUNEL-positive cell numbers (Bar = 50 μm). (<b>H</b>,<b>I</b>) Representative immunofluorescence images and analysis of γH2A in ovary sections (Bar = 50 μm). Data represent mean ± SEM. Ctrl, control group. PF + H<sub>2</sub>O<sub>2</sub>, Paeoniflorin + H<sub>2</sub>O<sub>2</sub> group. * <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><b>PF prevents oxidative stress and inhibits ferroptosis in mouse ovaries</b>. (<b>A</b>–<b>C</b>) Representative immunofluorescence images and analysis of HO-1 and Nrf2 in ovary sections (Bar = 100 μm). (<b>D</b>,<b>E</b>) Western blot and quantification of GPX4 in ovarian tissues (n = 6). ACTB served as an internal control. Data represent mean ± SEM. Ctrl, control group. PF + H<sub>2</sub>O<sub>2</sub>, Paeoniflorin + H<sub>2</sub>O<sub>2</sub> group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p><b>PF activates autophagy activity and lysosomal biogenesis in the mouse ovaries</b>. (<b>A</b>–<b>C</b>) Western blot and quantification of LC3-II and p62 in ovarian tissues (n = 6). ACTB served as an internal control. (<b>D</b>–<b>F</b>) Representative immunofluorescence images and analysis of Beclin-1 and p62 in ovary sections (Bar = 100 μm). (<b>G</b>,<b>H</b>) Western blot and quantification of TFEB in ovarian tissues (n = 6). ACTB served as an internal control. (<b>I</b>,<b>J</b>) Representative immunofluorescence images and analysis of LAMP2 in ovary sections (Bar = 100 μm). Data represent mean ± SEM. Ctrl, control group. PF + H<sub>2</sub>O<sub>2</sub>, Paeoniflorin + H<sub>2</sub>O<sub>2</sub> group. * <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><b>PF promotes mitophagy to improve mitochondrial quality</b>. (<b>A</b>–<b>D</b>) Western blot and quantification of DRP1, MFN1, and TOM20 in ovarian tissues (n = 6). ACTB served as an internal control. (<b>E</b>–<b>G</b>) Representative immunofluorescence images and analysis of PINK1 and Parkin in ovary sections (Bar = 100 μm). (<b>H</b>–<b>J</b>) Representative immunofluorescence images and analysis of LC3 and COX IV in ovary sections (Bar = 100 μm). Data represent mean ± SEM. Ctrl, control group. PF + H<sub>2</sub>O<sub>2</sub>, Paeoniflorin + H<sub>2</sub>O<sub>2</sub> group. * <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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22 pages, 9753 KiB  
Article
Discovery of the Inhibitor Targeting the SLC7A11/xCT Axis through In Silico and In Vitro Experiments
by Jianda Yue, Yekui Yin, Xujun Feng, Jiawei Xu, Yaqi Li, Tingting Li, Songping Liang, Xiao He, Zhonghua Liu and Ying Wang
Int. J. Mol. Sci. 2024, 25(15), 8284; https://doi.org/10.3390/ijms25158284 - 29 Jul 2024
Viewed by 373
Abstract
In the development and progression of cervical cancer, oxidative stress plays an important role within the cells. Among them, Solute Carrier Family 7 Member 11 (SLC7A11/xCT) is crucial for maintaining the synthesis of glutathione and the antioxidant system in cervical cancer cells. In [...] Read more.
In the development and progression of cervical cancer, oxidative stress plays an important role within the cells. Among them, Solute Carrier Family 7 Member 11 (SLC7A11/xCT) is crucial for maintaining the synthesis of glutathione and the antioxidant system in cervical cancer cells. In various tumor cells, studies have shown that SLC7A11 inhibits ferroptosis, a form of cell death, by mediating cystine uptake and maintaining glutathione synthesis. Additionally, SLC7A11 is also involved in promoting tumor metastasis and immune evasion. Therefore, inhibiting the SLC7A11/xCT axis has become a potential therapeutic strategy for cervical cancer. In this study, through structure-based high-throughput virtual screening, a compound targeting the SLC7A11/xCT axis named compound 1 (PubChem CID: 3492258) was discovered. In vitro experiments using HeLa cervical cancer cells as the experimental cell model showed that compound 1 could reduce intracellular glutathione levels, increase glutamate and reactive oxygen species (ROS) levels, disrupt the oxidative balance within HeLa cells, and induce cell death. Furthermore, molecular dynamics simulation results showed that compound 1 has a stronger binding affinity with SLC7A11 compared to the positive control erastin. Overall, all the results mentioned above indicate the potential of compound 1 in targeting the SLC7A11/xCT axis and treating cervical cancer both in vitro and in silico. Full article
(This article belongs to the Section Biochemistry)
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<p>SLC7A11/xCT maintains intracellular GSH/GSSG balance mechanism.</p>
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<p>Process of discovering the potential inhibitors targeting the SLC7A11/xCT axis through molecular docking. Eint represents the interaction energy.</p>
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<p>Oxidative/antioxidant balance within the HeLa cells influenced by compound 1. (<b>A</b>) After 24 h of drug treatment, the effect of 25 μM compound 1 and erastin on intracellular GSH levels in HeLa cells (n = 6). (<b>B</b>) After 24 h of drug treatment, the effect of 25 μM compound 1 and erastin on intracellular relative glutamate levels in HeLa cells (n = 6). (<b>C</b>) Cytotoxicity assay results of compound 1 incubated with HeLa cells for 12 h, 24 h, 36 h, and 48 h, respectively (n = 6). (<b>D</b>) Cytotoxicity assay results of compound 1 incubated with HeLa cells for 36 h in the presence or absence of 2.5 mM L-cysteine (n = 6). (<b>E</b>) Cytotoxicity assay results of compound 1 and erastin at concentrations of 50, 25, 12.5, 6.25, and 3.13 μM, respectively, after 36 h of incubation (n = 5). (<b>F</b>) The effect of 25 μM compound 1 and erastin on intracellular ROS levels in HeLa cells (n = 4). (<b>G</b>) Cytotoxicity assay results of 5 or 10 mM NAC combined with compound 1 treatment or compound 1 treatment alone after 36 h of incubation (n = 6). (<b>H</b>) Calcein-AM staining results of 5 or 10 mM NAC combined with compound 1 treatment or compound 1 treatment alone after 36 h of incubation. (<b>I</b>) The 2D structure of compound 1. The magnification is 40×. (<b>J</b>) The 2D structure of erastin. The data are presented as mean ± S.D. *, <span class="html-italic">p</span> &lt; 0.05; ***, <span class="html-italic">p</span> &lt; 0.001, “ns” indicates “non-significant.”</p>
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<p>Inhibition of HeLa cell migration by compound 1 at low concentrations. (<b>A</b>) Wound healing images. (<b>B</b>) Quantitative analysis of scratch wounds treated with different concentrations of compound 1 (0.5, 1, 2, 4 μM) and erastin (0.5, 1, 2, 4 μM) for 24 h (n = 4). (<b>C</b>) Transwell migration images. (<b>D</b>) Quantitative analysis of Transwell migration after treatment with compound 1 (4 μM) and erastin (4 μM) for 24 h (n = 4). The data are presented as mean ± S.D. *, <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, “ns” usually indicates “non-significant.”</p>
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<p>Toxic effects of compound 1 on HeLa three-dimensional spheroids. (<b>A</b>) HeLa spheroids were treated with 10 μM erastin or 5 μM and 10 μM compound 1 in a 96-well round-bottom ultra-low-attachment plate. The treatment started on day 0, and images were captured and HeLa spheroid volumes were measured daily from day 0, with six consecutive recordings. (<b>B</b>) Changes in HeLa spheroid volumes over 6 days (n = 5). (<b>C</b>) Proliferation rates of HeLa spheroid volumes over 6 days (n = 5). The data are presented as mean ± S.D. *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01 and ***, <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Structural analyses of APO, SLC7A11-c1, and SLC7A11-erastin. (<b>A</b>) RMSD of APO, SLC7A11-c1, and SLC7A11-erastin. (<b>B</b>) RMSD of compound 1 and erastin. (<b>C</b>) Radius of gyration of APO, SLC7A11-c1, and SLC7A11-erastin. (<b>D</b>) RMSF of APO, SLC7A11-c1, and SLC7A11-erastin. (<b>E</b>) The 2D structure of SLC7A11. APO, SLC7A11-c1, and SLC7A11-erastin (<b>A</b>–<b>D</b>) are outlined in green, red, and blue lines, respectively.</p>
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<p>Principal component analysis (PCA) of APO, SLC7A11-c1, and SLC7A11-erastin. (<b>A</b>) Essential subspace projection of PC1 vs. PC2 of APO, SLC7A11-c1, and SLC7A11-erastin. The continuous color scale (from blue to white to red) indicates that there are periodic jumps between these conformers throughout the trajectory. (<b>B</b>) Porcupine plots represent the motions captured in PC1 of APO, SLC7A11-c1, and SLC7A11-erastin, color scale from blue to red depict low to high atomic displacements. (<b>C</b>) Line plots represent the degree of motions captured in PC1 for APO, SLC7A11-c1, and SLC7A11-erastin. The solid box in (<b>B</b>) highlights the ligand-binding pocket within the structure.</p>
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<p>The dynamics cross-correlation matrix (DCCM) plots for APO (<b>A</b>,<b>D</b>), SLC7A11-c1 (<b>B</b>,<b>E</b>), and SLC7A11-erastin (<b>C</b>,<b>F</b>). Red (−1) and blue (+1) correspond to correlated and anti-correlated motions, respectively.</p>
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<p>H-bond analysis results. (<b>A</b>) Analysis of hydrogen bond interactions between erastin and SLC7A11. (<b>B</b>) Analysis of hydrogen bond interactions between compound 1 and SLC7A11. (<b>C</b>) H-bond occupancy of each interacting residue in their relevant systems, including SLC7A11-c1, and SLC7A11-erastin.</p>
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<p>Representative conformation of compound 1(orange) and erastin(yellow) bound to SLC7A11. The key residues of SLC7A11 are in green.</p>
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<p>Residue binding energy contribution of SLC7A11-c1 and SLC7A11-erastin. (<b>A</b>) Overall binding free energies of compounds with SLC7A11. (<b>B</b>) Binding energies of compounds to SLC7A11 residues. (<b>C</b>) The positions of residues with high energy contribution bound to erastin. (<b>D</b>) The positions of residues with high energy contribution bound to compound 1. The deeper the color, the higher the energy contribution.</p>
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20 pages, 8349 KiB  
Article
Single-Cell RNA-seq Analysis Reveals a Positive Correlation between Ferroptosis and Beta-Cell Dedifferentiation in Type 2 Diabetes
by Jiajing Ma, Xuhui Li, Xuesi Wan, Jinmei Deng, Yanglei Cheng, Boyuan Liu, Liehua Liu, Lijuan Xu, Haipeng Xiao and Yanbing Li
Biomedicines 2024, 12(8), 1687; https://doi.org/10.3390/biomedicines12081687 - 29 Jul 2024
Viewed by 404
Abstract
Insulin deficiency in patients with type 2 diabetes mellitus (T2D) is associated with beta-cell dysfunction, a condition increasingly recognized to involve processes such as dedifferentiation and apoptosis. Moreover, emerging research points to a potential role for ferroptosis in the pathogenesis of T2D. In [...] Read more.
Insulin deficiency in patients with type 2 diabetes mellitus (T2D) is associated with beta-cell dysfunction, a condition increasingly recognized to involve processes such as dedifferentiation and apoptosis. Moreover, emerging research points to a potential role for ferroptosis in the pathogenesis of T2D. In this study, we aimed to investigate the potential involvement of ferroptosis in the dedifferentiation of beta cells in T2D. We performed single-cell RNA sequencing analysis of six public datasets. Differential expression and gene set enrichment analyses were carried out to investigate the role of ferroptosis. Gene set variation and pseudo-time trajectory analyses were subsequently used to verify ferroptosis-related beta clusters. After cells were categorized according to their ferroptosis and dedifferentiation scores, we constructed transcriptional and competitive endogenous RNA networks, and validated the hub genes via machine learning and immunohistochemistry. We found that ferroptosis was enriched in T2D beta cells and that there was a positive correlation between ferroptosis and the process of dedifferentiation. Upon further analysis, we identified two beta clusters that presented pronounced features associated with ferroptosis and dedifferentiation. Several key transcription factors and 2 long noncoding RNAs (MALAT1 and MEG3) were identified. Finally, we confirmed that ferroptosis occurred in the pancreas of high-fat diet-fed mice and identified 4 proteins (NFE2L2, CHMP5, PTEN, and STAT3) that may participate in the effect of ferroptosis on dedifferentiation. This study helps to elucidate the interplay between ferroptosis and beta-cell health and opens new avenues for developing therapeutic strategies to treat diabetes. Full article
(This article belongs to the Section Endocrinology and Metabolism Research)
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<p>Integration, clustering, and cell proportion calculation of single-cell RNA sequencing (scRNA-seq) data. (<b>A</b>) Uniform Manifold Approximation and Projection (UMAP) plot showing elimination of batch effect. (<b>B</b>) Eighteen clusters visualized based on UMAP. (<b>C</b>) Cell populations identified by marker genes. (<b>D</b>) Comparison of cell proportions between type 2 diabetes mellitus (T2D)-affected islets and non-diabetic islets.</p>
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<p>The landscape of ferroptosis in T2D. (<b>A</b>) Volcano plot of differentially expressed genes (DEGs). (<b>B</b>) Venn diagram of DEGs and ferroptosis-related genes (FRGs) based on the FerrDb database. (<b>C</b>) Heatmap of the 24 ferroptosis-related DEGs. (<b>D</b>) Gene set enrichment analysis (GSEA) of the “WP_FERROPTOSIS” pathway. (<b>E</b>) Ferroptosis scores of T2D and non-diabetic samples.</p>
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<p>Dedifferentiation characteristics of beta cells. (<b>A</b>) Dot map of dedifferentiation-related genes. (<b>B</b>) Dedifferentiation scores of T2D and non-diabetic samples. (<b>C</b>) Dedifferentiation scores of “Ferro_high” and “Ferro_low” beta cells. (<b>D</b>) Proportion of 4 groups of beta cells between T2D and non-diabetic samples.</p>
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<p>Identification of ferroptosis-related clusters in beta cells. (<b>A</b>) UMAP plot showing 6 beta-cell clusters. (<b>B</b>) Comparison of beta-cell cluster proportions between T2D and non-diabetic tissues. (<b>C</b>) Expression of 5 markers of each cluster. (<b>D</b>) Ferroptosis scores of different beta-cell clusters.</p>
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<p>Gene set variation analysis (GSVA) of ferroptosis-related pathways in beta-cell clusters. (<b>A</b>) GSVA of oxidative-stress-related pathways. (<b>B</b>) GSVA of lipid-metabolism-related pathways. (<b>C</b>) GSVA of iron-related pathways.</p>
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<p>Cellular trajectory analysis in beta cells. (<b>A</b>) Pseudo-time trajectories of changes in FRGs. (<b>B</b>) Pseudo-time trajectories of changes in beta-identity-related genes.</p>
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<p>Construction of regulatory networks in beta cells. (<b>A</b>) DEGs of double-high cells compared with double-low cells. (<b>B</b>) Differentially activated transcription factors of double-high cells compared with double-low cells. (<b>C</b>) The transcriptional regulatory network (the orange circles represent TFs, and the green circles represent their target genes). (<b>D</b>) Differentially expressed long non-coding RNAs (DELs) of double-high cells compared with double-low cells. (<b>E</b>) The competitive endogenous RNA (ceRNA) network.</p>
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<p>Screening of key genes using machine learning methods. (<b>A</b>) Dispersion of Least Absolute Shrinkage and Selection Operator (LASSO) coefficients. Each curve represents the trajectory of each independent variable coefficient. (<b>B</b>) Tenfold cross-validation for LASSO model parameter selection tuning. (<b>C</b>) Random Forest (RF) algorithm plot illustrating the connection between error rate and tree count. The three lines in the figure represent, from bottom to top, the error rate of the first class, the overall error rate, and the error rate of the second class, respectively. (<b>D</b>) RF algorithm-based gene ranking according to relative importance. (<b>E</b>) Venn diagram demonstrating the key genes shared by the LASSO results, RF algorithm results, and DEGs of T2D. (<b>F</b>) Correlation analysis performed among key genes.</p>
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<p>Expression and receiver operator characteristic (ROC) curves of key genes in beta cells. (<b>A</b>) Box plots displaying the expression of 8 key genes in non-diabetic and T2D samples. (<b>B</b>) ROC curves of the 8 key genes in T2D. (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Ferroptosis markers in control and T2D mouse samples. (<b>A</b>) Body weight of control and high-fat diet(HFD) groups. (<b>B</b>) Fasting blood glucose was measured after a 6 h fast. (<b>C</b>) Glucose tolerance test (GTT) and AUC results of the control and HFD group (i.p. 2.0 g/kg glucose). (<b>D</b>) The serum iron level was measured using an iron assay kit. (<b>E</b>) The serum ferritin level was measured using a ferritin ELISA kit. (<b>F</b>) The iron level in pancreatic tissues was measured using an iron assay kit. (<b>G</b>) The malondialdehyde (MDA) level in pancreatic tissues was measured using an MDA assay kit. (<b>H</b>) The glutathione (GSH) level in pancreatic tissues was measured using a GSH assay kit. (n = 10 in each group; values are shown as means ± standard deviations. * <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, and **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Expression of hub genes in the islets of the control and HFD groups. (<b>A</b>) Immunohistochemical staining of the NFE2L2, CHMP5, PTEN, and STAT3 proteins in the islets of the control and HFD groups. (<b>B</b>) Quantitative analysis of immunohistochemical staining of the NFE2L2, CHMP5, PTEN, and STAT3 proteins. (n = 3 in each group; 4–6 islets per mouse were analyzed; values are shown as means ± standard deviations. *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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35 pages, 20176 KiB  
Review
Skin Aging and the Upcoming Role of Ferroptosis in Geroscience
by Rita Rezzani, Gaia Favero, Giorgia Cominelli, Daniela Pinto and Fabio Rinaldi
Int. J. Mol. Sci. 2024, 25(15), 8238; https://doi.org/10.3390/ijms25158238 - 28 Jul 2024
Viewed by 377
Abstract
The skin is considered the most important organ system in mammals, and as the population ages, it is important to consider skin aging and anti-aging therapeutic strategies. Exposure of the skin to various insults induces significant changes throughout our lives, differentiating the skin [...] Read more.
The skin is considered the most important organ system in mammals, and as the population ages, it is important to consider skin aging and anti-aging therapeutic strategies. Exposure of the skin to various insults induces significant changes throughout our lives, differentiating the skin of a young adult from that of an older adult. These changes are caused by a combination of intrinsic and extrinsic aging. We report the interactions between skin aging and its metabolism, showing that the network is due to several factors. For example, iron is an important nutrient for humans, but its level increases with aging, inducing deleterious effects on cellular functions. Recently, it was discovered that ferroptosis, or iron-dependent cell death, is linked to aging and skin diseases. The pursuit of new molecular targets for ferroptosis has recently attracted attention. Prevention of ferroptosis is an effective therapeutic strategy for the treatment of diseases, especially in old age. However, the pathological and biological mechanisms underlying ferroptosis are still not fully understood, especially in skin diseases such as melanoma and autoimmune diseases. Only a few basic studies on regulated cell death exist, and the challenge is to turn the studies into clinical applications. Full article
(This article belongs to the Special Issue Dermatology: Advances in Pathophysiology and Therapies (2nd Edition))
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<p>Aging and ferroptosis. The illustration represents the aging induction of ferroptosis, which, in turn, disrupts the imbalance between oxidative stress and antioxidant defense, thereby implementing, in a vicious cycle, the aging-related damage. Illustration from Mazhar et al., 2021 [<a href="#B7-ijms-25-08238" class="html-bibr">7</a>]. (This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International license).</p>
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<p>Aging, iron dyshomeostasis, ferroptosis, and hepidicin. The illustration represents a possible interaction among aging, iron dyshomeostasis, ferroptosis, and hepidicin, a hepatic iron-regulatory hormone. Aging increases iron stores in tissues, and the intracellular iron induces redox imbalances and cellular injury, leading to ferroptosis, which, in turn, promotes aging and associated morbidity. The aging-related increment in intracellular iron levels may be linked to the increased production of hepcidin due to underlying chronic inflammation. (GPX4): glutathione peroxidase-4; (GSH): glutathione; (NK): natural killer; (B): B lymphocytes; (CD4 T): CD4 T lymphocyte; (M): microfold cells; (MQ): macrophages; (COX2): cyclooxygenase-2; (TNF-α): tumor necrosis factor alpha; (NF-kB): nuclear factor kappa-light-chain-enhancer of activated B cells; (iNOS): inducible nitric oxide synthase; (IL-1): interleukin-1; (IL-6): interleukin-6; (ROS): reactive oxygen species; (FPN): ferroportin. Illustration from Mazhar et al., 2021 [<a href="#B7-ijms-25-08238" class="html-bibr">7</a>]. (This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International license).</p>
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<p>Adult human skin. Representative photomicrograph of face skin from adult donors (under 65 years old). Haematoxylin-eosin staining. The skin biopsies were obtained from head cadaveric specimens (MedCure, Amsterdam, The Netherlands). Specimens were stored at −20 °C, defrosted before the anatomical dissecting session, and analyzed at the Anatomical Facility “Luigi Fabrizio Rodella” of the University of Brescia (Italy). The human cadaveric studies have been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Bar: 20 µm. (E): epidermis; (D): dermis; (white stars): epidermal network ridges. Illustration adapted from Favero et al., 2024 [<a href="#B18-ijms-25-08238" class="html-bibr">18</a>].</p>
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<p>Human skin functions. The illustration summarizes the main human skin functions. Illustration adapted from Ahmed and Mikail et al,. 2024 [<a href="#B3-ijms-25-08238" class="html-bibr">3</a>].</p>
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<p>Human skin microbiota. The skin microbiota affects the cutaneous physical barrier function. The microbiota enhances the skin’s chemical barrier by producing lipases that digest sebum triglycerides into free fatty acids, which in turn amplify skin acidity and limit colonization by transient and pathogenic species. Moreover, the skin microbiota stimulates innate and adaptive immune defenses. Illustration adapted from Harris-Tryon and Grice, 2022 [<a href="#B28-ijms-25-08238" class="html-bibr">28</a>].</p>
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<p>Human skin aging physiopathological process. Human skin aging is related to biomechanical, structural, and physical change at nano-, micro-, and macro-scales. Illustration adapted from Park, 2022 [<a href="#B32-ijms-25-08238" class="html-bibr">32</a>].</p>
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<p>Elderly human skin. Representative photomicrograph of face skin from elderly donors (over 65 years old). Haematoxylin-eosin staining. The skin biopsies were obtained from head cadaveric specimens (MedCure, Amsterdam, The Netherlands). Specimens were stored at −20 °C, defrosted before the anatomical dissecting session, and analyzed at the Anatomical Facility “Luigi Fabrizio Rodella” of the University of Brescia (Italy). The human cadaveric studies have been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Bar: 20 µm. (E): epidermis; (D): dermis; (white stars): epidermal network ridges; (arrows): melanocytes; (**): fibroblasts; (*): mast cells. Illustration adapted from Favero et al., 2024 [<a href="#B18-ijms-25-08238" class="html-bibr">18</a>].</p>
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<p>Human epidermal thickness evaluation in adult and elderly specimens. The plot shows the epidermal thickness distribution performed on adult (under 65 years old) and elderly (over 65 years old) donor specimens. The face skin sections were stained with hematoxylin-eosin following standard procedures. The thickness of the epidermal layer of each specimen was calculated in micrometers (μm) by a blind examiner using an image analyzer (Image Pro Premier 9.1; Media Cybernetics, Rockville, MD, USA). The epidermal layer was measured from the free margin of skin to the dermal papillae and epidermal network ridge. The analysis was performed on five alternately stained sections for each skin specimen. Illustration adapted from Favero et al., 2024 [<a href="#B18-ijms-25-08238" class="html-bibr">18</a>].</p>
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<p>Human dermal mast cell quantification in adult and elderly specimens. The plot summarizes the total number of mast cells in the dermal layer performed on adult (under 65 years old) and elderly (over 65 years old) donor specimens. The face skin sections were stained with toluidine blue. The numbers of mast cells were evaluated by a blind examiner using an optical BX50 microscope (Olympus, Hamburg, Germany) as the number of cells per field. At least five representative visual fields of five alternate sections for each skin specimen were analyzed. Illustration adapted from Favero et al., 2024 [<a href="#B18-ijms-25-08238" class="html-bibr">18</a>].</p>
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<p>Geroscience and age-related diseases. The illustration represents the link between geroscience and aging. Genetics and environmental factors affect various cellular and physiological pathways fundamental to aging and inflammation. These factors, together with disease-specific risk factors, can increase the risk of aging-related chronic disease development. Illustration adapted from Campisi et al., 2019 [<a href="#B37-ijms-25-08238" class="html-bibr">37</a>].</p>
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<p>Human skin dermal collagen. Representative photomicrographs of type I (<b>a</b>) and type III (<b>b</b>) collagen immunohistochemistry at the dermal layer were performed on adult (<b>a</b>) and old (<b>b</b>) skin specimens. Type I collagen immunostaining was widely distributed, whereas type III collagen immunostaining was light and sparse with an uneven distribution. Bars: 200 µm. Illustration from Cheng et al., 2011 [<a href="#B51-ijms-25-08238" class="html-bibr">51</a>]. (This is an open access article distributed under the terms of the Creative Commons CC-BY license).</p>
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<p>Young and adult sun-protected skin. Representative photomicrographs of skin melanocytes and collagen 17 and collagen 17a immunofluorescence were performed on young (22 years old) and adult (years old) sun-protected skin specimens. Aged skin showed a flattened dermal-epidermal junction, a decreased number of melanocytes, and reduced immunostaining for collagen 17 and 17a. Bars: 50 µm. Illustration from Chin et al., 2023 [<a href="#B31-ijms-25-08238" class="html-bibr">31</a>]. (This is an open access article distributed under the terms of the Creative Commons CC-BY license).</p>
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<p>Collagen 17 modulates interfollicular epidermis homeostasis. The illustration represents the possible mechanism of action of collagen 17 in regulating paw interfollicular epidermis homeostasis. Illustration from Watanabe et al., 2017 [<a href="#B54-ijms-25-08238" class="html-bibr">54</a>]. (This is an open access article distributed under the terms of the Creative Commons CC-BY license).</p>
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<p>Schematic representation of human skin barrier immunity. The epidermal layer consists of T-resident memory cells (T<sub>rm</sub>), Langerhans cells, and keratinocytes; the latter form a stratified corneum with interspersed melanocytes. The dermal layer is populated by dermal dendritic cells (DCs), macrophages, Foxp3<sup>+</sup> T regulatory cells (Tregs), CD4+ and CD8+ T<sub>rm</sub>, fibroblasts, and mast cells. The subcutaneous layer is composed of adipocytes. Illustration from Chambers et al., 2020 [<a href="#B23-ijms-25-08238" class="html-bibr">23</a>]. (License number 5835261420374).</p>
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<p>Skin immune functions. The graph summarizes the implications of immune cells for skin immune functions. Illustration adapted from Agrawal et al., 2023 [<a href="#B105-ijms-25-08238" class="html-bibr">105</a>].</p>
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<p>Iron homeostasis. The illustration represents an overview of the iron sources, the systemic processes that balance the iron level, and its cellular uses. The regulation of iron homeostasis involves the absorption, transport, storage, recycling, and utilization of iron. Illustration from Zeidan et al., 2024 [<a href="#B125-ijms-25-08238" class="html-bibr">125</a>]. (This is an open access article distributed under the terms of the Creative Commons CC-BY license).</p>
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<p>Ultraviolet irradiation and ferritin. The illustration represents the ultraviolet irradiation injury at skin level. The skin’s ultraviolet irradiation increases cell-free iron, promoting ferritin degradation, which, in a vicious cycle, implements the free iron release. (NF-kB): nuclear factor kappa-light-chain-enhancer of activated B cells. Illustration adapted from Pouillot et al., 2014 [<a href="#B127-ijms-25-08238" class="html-bibr">127</a>].</p>
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<p>Programmed or non-programmed cell death. The illustration compares the main morphologic features of programmed and non-programmed cell death: ferroptosis, pyroptosis, apoptosis, and necrosis. Illustration from Khorsandi et al., 2023 [<a href="#B130-ijms-25-08238" class="html-bibr">130</a>]. (This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International license).</p>
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<p>The development of the ferroptosis concept. Timeline diagram of last decades’ history observations on regulated cell deaths and the advances that contributed to the emergence of the concept of ferroptosis. Ferroptosis was observed in various contexts before coining of the term in 2012. Illustration adapted from Hirschhorn and Stockwell, 2019 [<a href="#B135-ijms-25-08238" class="html-bibr">135</a>].</p>
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<p>Ferroptosis hallmarks. The illustration summarizes the three main hallmarks that promote ferroptotic death: oxidizable phospholipids acylated with polyunsaturated fatty acids, redox-active iron, and defective lipid peroxide repair. Illustration adapted from Dixon and Stockwell, 2019 [<a href="#B143-ijms-25-08238" class="html-bibr">143</a>].</p>
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<p>Ferroptosis cell pathways. The illustrations summarize the main conditions that can trigger cell ferroptosis. (TFR1): transferrin receptor 1; (FPN): ferroportin; (DMT1): divalent metal transporter 1; (STEAP3): six-transmembrane epithelial antigens of the prostate 3; (NCOA4): Nuclear receptor coactivator 4; (LIP): labile iron pool; (ROS): reactive oxygen species; (SLC3A2): Solute Carrier Family 3 Member 2; (SLC7A11): Solute Carrier Family 7 Member 11; (PUFAs): polyunsaturated fatty acids; (AA/AdA): arachidonic acid/adrenic acid (AdA); (AA/AdA-Pes): AA/AdAphosphatidylethanolamine (PE); (AA/AdA-PEs-OH): AA/AdA-PEs-alcohols; (AA/AdA-PEs-OOH): AA/AdA-PEs-hydroperoxides; (GPX4): glutathione peroxidase-4; (GSH): glutathione; (GSSG): glutathione disulfide; (LOXs): lipoxygenases; (ACSL4/LPCAT3): acyl-CoA synthetase long-chain family member 4/lysophosphatidylcholine acyltransferase 3. Illustration (<b>A</b>) is from Liu et al., 2023 [<a href="#B140-ijms-25-08238" class="html-bibr">140</a>]. (This is an open access article distributed under the term of the Creative Commons CC-BY license). Illustration (<b>B</b>) is from Khorsandi et al., 2023 [<a href="#B130-ijms-25-08238" class="html-bibr">130</a>]. (This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International license).</p>
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<p>Ferroptosis and gut microbiota. The illustration represents the influence of gut microbiota on ferroptosis in various tissues, organs, and diseases. Illustration from Mao et al., 2024 [<a href="#B152-ijms-25-08238" class="html-bibr">152</a>]. (This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International license).</p>
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<p>Dermatological manifestation of vitiligo. The illustration showed the main dermatological features of vitiligo. Cutaneous chronic depigmentation and white lesions of a vitiligo patient (<b>A</b>). Comparison of skin morphology between a healthy subject and a vitiligo patient. Haematoxylin-eosin staining. Black arrows indicate melanocytes (×400) (<b>B</b>). Comparison of skin melanocytes between a healthy subject and a vitiligo patient underling. Melan-A (red staining) immunofluorescence. Nuclei have been counterstained with 4′,6′-diamidino-2-phenylindole (blue staining). Bar = 100 µm. The white arrows indicated melanocytes (<b>C</b>). (<b>B</b>,<b>C</b>) underline the absence of melanocytes in vitiligo skin. Illustration from Chen et al., 2020 [<a href="#B158-ijms-25-08238" class="html-bibr">158</a>]. (This is an open access article distributed under the terms of the Creative Commons CC-BY license).</p>
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<p>Melanocytes in vitiligo. The illustration represents schematically the main hallmarks that promote melanocyte destruction, resulting in the depletion of melanocytes in vitiligo lesional skin. (ROS): reactive oxygen species; (RCD): regulated cell death. Illustration adapted from Chen et al., 2020 [<a href="#B158-ijms-25-08238" class="html-bibr">158</a>].</p>
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<p>Autoimmune diseases and ferroptosis. The illustration summarizes the ferroptosis pathway in vitiligo-affected patients. (IFN-α): interferon-α; (GPX4): glutathione peroxidase-4; (SLE): systemic lupus erythematosus; (circRNA): circular RNAs. Illustration from Liu et al., 2023 [<a href="#B140-ijms-25-08238" class="html-bibr">140</a>]. (This is an open access article distributed under the terms of the Creative Commons CC-BY license).</p>
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<p>Young vs. old human skin. The illustration compares human young skin to human aged skin. Aged skin is characterized by an altered epithelial barrier, a thin and impaired dermal layer, inflammation, and excessive senescent fibroblasts and immune cells. Illustration from Zhang et al., 2024 [<a href="#B219-ijms-25-08238" class="html-bibr">219</a>]. (This is an open access article distributed under the terms of the Creative Commons CC-BY license).</p>
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18 pages, 6874 KiB  
Article
Chromosome Segregation–1–like Gene Participates in Ferroptosis in Human Ovarian Granulosa Cells via Nucleocytoplasmic Transport
by Luanqian Hu, Tongtong Hong, Yuheng He, Huiyuan Wang, Jinxiang Cao, Danhua Pu, Li Gao, Chao Gao, Yugui Cui, Jie Wu and Rongrong Tan
Antioxidants 2024, 13(8), 911; https://doi.org/10.3390/antiox13080911 - 28 Jul 2024
Viewed by 326
Abstract
Premature ovarian insufficiency (POI) is defined as the depletion of ovarian function before the age of 40 years. The global prevalence of POI is 3.5%. To date, genetic factors account for 23.5% of the etiology of POI. Herein, a previously uncharacterized pathogenic homozygous [...] Read more.
Premature ovarian insufficiency (POI) is defined as the depletion of ovarian function before the age of 40 years. The global prevalence of POI is 3.5%. To date, genetic factors account for 23.5% of the etiology of POI. Herein, a previously uncharacterized pathogenic homozygous variant of the chromosome segregation–1–like gene (CSE1L) was identified in POI patients via targeted panel sequencing. It is reported that dysregulated iron metabolism is involved in many reproductive endocrine disorders; however, its precise role in POI remains obscure. In this study, we identified CSE1L as a potential candidate gene that plays an important role in maintaining iron homeostasis. Deficiency of CSE1L led to ferroptosis in human granulosa cells, which was confirmed by transmission electron microscopy. Mechanistically, coimmunoprecipitation identified the direct interaction between CSE1L and FoxO1. Inhibition of CSE1L led to the excessive accumulation of FoxO1 in the nucleus via nucleocytoplasmic transport. Then, FoxO1 bound to the promoter region of NCOA4 and promoted its transcription, which was verified by a chromatin immunoprecipitation assay. Moreover, inhibition of CSE1L in cumulus cell monolayer could impede oocyte maturation, which might be associated with oxidative stress. Consequently, our study first revealed that CSE1L participated in ferroptosis in human ovarian granulosa cells via nucleocytoplasmic transportation, which might be helpful in revealing the molecular mechanism of CSE1L in the development of POI. Importantly, these findings might provide new insights into the application of ferroptosis inhibitors in the treatment of POI. Full article
(This article belongs to the Section Aberrant Oxidation of Biomolecules)
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<p>The sketch of co–culture system of cumulus cell monolayer and denuded oocyte.</p>
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<p>Mutant CSE1L (c. 1261T&gt;C) inhibited the viability of human granulosa cells. (<b>A</b>) Flag–CSE1L protein expression in KGN and SVOG cells transfected with mutant CSE1L (c. 1261T&gt;C) plasmid was detected by Western blotting. (<b>B</b>,<b>C</b>) Quantification of band intensity of Flag–CSE1L/β–actin ratios in KGN and SVOG cells. (<b>D</b>,<b>E</b>) Cell viability in KGN and SVOG cells was detected by CCK8 assay. N = 3 for each group. Data were expressed as mean ± SD. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared to WT, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 compared to WT.</p>
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<p>The expression of CSE1L was downregulated in aged mice ovaries. (<b>A</b>) CSE1L protein expression in ovaries was detected by Western blotting. (<b>B</b>) Quantification of band intensity of CSE1L/β–actin ratios in ovaries. (<b>C</b>) Localization of CSE1L in the 8w ovary. Immunofluorescence staining of CSE1L (red), DDX4 (green) in ovary were analyzed by confocal microscopy. Nuclei were counterstained with Hochest (blue). Scale bar: 100 µm. (<b>D</b>) Cell localization of CSE1L in KGN and SVOG cell. Immunofluorescence staining of CSE1L (green), Nuclei (blue) in cells were analyzed by confocal microscopy. Scale bar: 100 µm. N = 3 for each group. Data were expressed as mean ± SD. * <span class="html-italic">p</span> &lt; 0.05 compared to 3–month–old mice.</p>
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<p>CSE1L silence affected iron metabolism in human granulosa cells. (<b>A</b>) Volcano plot of differentially expressed genes (Q value ≤ 0.05, |log2FC| ≥ 1). (<b>B</b>,<b>C</b>) Ferrous iron level in KGN and SVOG cells transfected with sh–CSE1L or CSE1L overexpression of the lentivirus. (<b>D</b>) FTH1 protein expression in KGN and SVOG cells transfected with sh–CSE1L was detected by Western blotting. (<b>E</b>,<b>F</b>) Quantification of band intensity of FTH1/β–actin ratios in KGN and SVOG cells transfected with sh–CSE1L. (<b>G</b>) FTH1 protein expression in KGN and SVOG cells transfected with CSE1L overexpression of the lentivirus was detected by Western blotting. (<b>H</b>,<b>I</b>) Quantification of band intensity of FTH1/β–actin ratios in KGN and SVOG cells transfected with CSE1L overexpression of the lentivirus. (<b>J</b>) TF, TFR protein expression in KGN and SVOG cells transfected with sh–CSE1L was detected by Western blotting. (<b>K</b>,<b>L</b>) Quantification of band intensity of TF/β–actin, TFR/β–actin ratios in KGN and SVOG cells transfected with sh–CSE1L. (<b>M</b>) TF, TFR protein expression in KGN and SVOG cells transfected with CSE1L overexpression of the lentivirus was detected by Western blotting. (<b>N</b>,<b>O</b>) Quantification of band intensity of TF/β–actin, TFR/β–actin ratios in KGN and SVOG cells transfected with CSE1L overexpression of the lentivirus. N = 3 for each group. Data were expressed as mean ± SD. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared to WT, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 compared to WT. * <span class="html-italic">p</span> &lt; 0.05 compared to ctrl, ** <span class="html-italic">p</span> &lt; 0.01 compared to ctrl.</p>
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<p>CSE1L silence induced ferroptosis in human granulosa cells. (<b>A</b>,<b>B</b>) ROS level in KGN and SVOG cells transfected with sh–CSE1L or CSE1L overexpression of the lentivirus. (<b>C</b>,<b>D</b>) MDA level in KGN and SVOG cells transfected with sh–CSE1L or CSE1L overexpression of the lentivirus. (<b>E</b>–<b>H</b>) ROS and MDA level in KGN and SVOG cells treated with DFO. (<b>I</b>–<b>L</b>) ROS and MDA level in KGN and SVOG cells treated with FAC. (<b>M</b>) Images from TEM showing morphology of mitochondria (red arrows) in human granulosa cells transfected with sh–CSE1L. Scale bar: 1 µm (<b>N</b>) GPX4 protein expression in KGN and SVOG cells transfected with sh–CSE1L was detected by Western blotting. (<b>O</b>,<b>P</b>) Quantification of band intensity of GPX4/β–actin ratios in KGN and SVOG cells transfected with sh–CSE1L. N = 3 for each group. Data were expressed as mean ± SD. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared to WT, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 compared to WT. * <span class="html-italic">p</span> &lt; 0.05 compared to ctrl, ** <span class="html-italic">p</span> &lt; 0.01 compared to ctrl. <sup>%</sup> <span class="html-italic">p</span> &lt; 0.05 compared to cells treated with DFO. <sup><span>$</span></sup> <span class="html-italic">p</span> &lt; 0.05 compared to cells treated with FAC, <sup><span>$</span><span>$</span></sup> <span class="html-italic">p</span> &lt; 0.01 compared to cells treated with FAC. <sup>&amp;</sup> <span class="html-italic">p</span> &lt; 0.05 compared to cells transfected with sh–CSE1L#1.</p>
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<p>CSE1L silence promoted ferroptosis via activating NCOA4–mediated ferritinophagy. (<b>A</b>) NCOA4, FTH1 protein expression in KGN and SVOG cells transfected with sh–CSE1L was detected by Western blotting. (<b>B</b>,<b>C</b>) Quantification of band intensity of NCOA4/β–actin, FTH1/β–actin ratios in KGN and SVOG cells transfected with sh–CSE1L. (<b>D</b>) ATG5, ATG7 protein expression in KGN and SVOG cells transfected with sh–CSE1L was detected by Western blotting. (<b>E</b>,<b>F</b>) Quantification of band intensity of ATG5/β–actin, ATG7/β–actin ratios in KGN and SVOG cells transfected with sh–CSE1L. (<b>G</b>) LC3 II protein expression in KGN and SVOG cells transfected with sh–CSE1L was detected by Western blotting. (<b>H</b>,<b>I</b>) Quantification of band intensity of LC3 II/β–actin ratios in KGN and SVOG cells transfected with sh–CSE1L. (<b>J</b>) FTH1 protein expression in KGN and SVOG cells treated with 9a was detected by Western blotting. (<b>K</b>,<b>L</b>) Quantification of band intensity of FTH1/β–actin ratios in KGN and SVOG cells treated with 9a. (<b>M</b>–<b>P</b>) ROS and MDA level in KGN and SVOG cells treated with 9a. N = 3 for each group. Data were expressed as mean ± SD. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared to WT, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 compared to WT, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 compared to WT. * <span class="html-italic">p</span> &lt; 0.05 compared to ctrl, ** <span class="html-italic">p</span> &lt; 0.01 compared to ctrl, *** <span class="html-italic">p</span> &lt; 0.001 compared to ctrl. <sup>◇</sup> <span class="html-italic">p</span> &lt; 0.05 compared to cells treated with 9a, <sup>◇◇</sup> <span class="html-italic">p</span> &lt; 0.01 compared to cells treated with 9a. <sup>&amp;</sup> <span class="html-italic">p</span> &lt; 0.05 compared to cells transfected with sh–CSE1L#1, <sup>&amp;&amp;</sup> <span class="html-italic">p</span> &lt; 0.01 compared to cells transfected with sh–CSE1L#1, <sup>&amp;&amp;&amp;</sup> <span class="html-italic">p</span> &lt; 0.001 compared to cells transfected with sh–CSE1L#1.</p>
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<p>FoxO1 promoted the transcription of NCOA4. (<b>A</b>,<b>B</b>) NCOA4 mRNA expression in KGN and SVOG cells transfected with sh–CSE1L was detected qRT–PCR. (<b>C</b>) FoxO1 protein expression in KGN and SVOG cells transfected with sh–CSE1L was detected by Western blotting. (<b>D</b>,<b>E</b>) Quantification of band intensity of FoxO1/vinculin ratios in KGN and SVOG cells transfected with sh–CSE1L. (<b>F</b>,<b>G</b>) ChIP assay was conducted in KGN and SVOG cells. (<b>H</b>) NCOA4 protein expression in KGN and SVOG cells transfected with si–FOXO1 was detected by Western blotting. (<b>I</b>,<b>J</b>) Quantification of band intensity of NCOA4/vinculin ratios in KGN and SVOG cells transfected with si–FoxO1. N = 3 for each group. Data were expressed as mean ± SD. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared to WT, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 compared to WT, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 compared to WT. * <span class="html-italic">p</span> &lt; 0.05 compared to ctrl, ** <span class="html-italic">p</span> &lt; 0.01 compared to ctrl, *** <span class="html-italic">p</span> &lt; 0.001 compared to ctrl. <sup>☆☆</sup> <span class="html-italic">p</span> &lt; 0.01 compared to cells transfected with si–FoxO1. <sup>&amp;</sup> <span class="html-italic">p</span> &lt; 0.05 compared to cells transfected with sh–CSE1L#1, <sup>&amp;&amp;</sup> <span class="html-italic">p</span> &lt; 0.01 compared to cells transfected with sh–CSE1L#1.</p>
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<p>CSE1L participated in ferritinophagy via regulating the nucleocytoplasmic transport of FoxO1. (<b>A</b>,<b>B</b>) Localization of FoxO1 in KGN and SVOG cells transfected with sh–CSE1L. Immunofluorescence staining of FoxO1 (red) in cells were analyzed by confocal microscopy. Nuclei were counterstained with Hochest (blue). Scale bar: 10 µm. (<b>C</b>,<b>D</b>) Immunoprecipitation of the interaction between Flag–CSE1L and FoxO1 in KGN and SVOG cells. N = 3 for each group.</p>
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<p>Inhibition of CSE1L in cumulus cell monolayer impeded oocyte maturation. (<b>A</b>) CSE1L mRNA expression in mice granulosa cells transfected with si–CSE1L was detected by qRT–PCR. (<b>B</b>) ROS levels of co–cultured oocytes. Scale bar: 10 µm. (<b>C</b>) The first polar body extrusion rate of co–cultured oocytes. Scale bar: 100 µm. N = 3 for each group (Each replication included at least 30 oocytes). Data were expressed as mean ± SD. * <span class="html-italic">p</span> &lt; 0.05 compared to NC, *** <span class="html-italic">p</span> &lt; 0.001 compared to NC.</p>
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29 pages, 6856 KiB  
Review
Ferroptosis in Arthritis: Driver of the Disease or Therapeutic Option?
by Shania Bieri, Burkhard Möller and Jennifer Amsler
Int. J. Mol. Sci. 2024, 25(15), 8212; https://doi.org/10.3390/ijms25158212 - 27 Jul 2024
Viewed by 351
Abstract
Ferroptosis is a form of iron-dependent regulated cell death caused by the accumulation of lipid peroxides. In this review, we summarize research on the impact of ferroptosis on disease models and isolated cells in various types of arthritis. While most studies have focused [...] Read more.
Ferroptosis is a form of iron-dependent regulated cell death caused by the accumulation of lipid peroxides. In this review, we summarize research on the impact of ferroptosis on disease models and isolated cells in various types of arthritis. While most studies have focused on rheumatoid arthritis (RA) and osteoarthritis (OA), there is limited research on spondylarthritis and crystal arthropathies. The effects of inducing or inhibiting ferroptosis on the disease strongly depend on the studied cell type. In the search for new therapeutic targets, inhibiting ferroptosis in chondrocytes might have promising effects for any type of arthritis. On the other hand, ferroptosis induction may also lead to a desired decrease of synovial fibroblasts in RA. Thus, ferroptosis research must consider the cell-type-specific effects on arthritis. Further investigation is needed to clarify these complexities. Full article
(This article belongs to the Section Molecular Endocrinology and Metabolism)
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<p>General overview of the mechanisms of ferroptosis, irrespective of the cell type. System Xc- functions as an amino acid antiporter, widely distributed within phospholipid bilayers. Comprising two subunits, solute carrier family 7 member 11 (SLC7A11) and solute carrier family 3 member 2 (SLC3A2), it forms a crucial part of the cellular antioxidant system. The exchange of cystine and glutamate occurs through System Xc- at a balanced ratio of 1:1, both entering and exiting the cell. Cystine, acquired through cellular uptake, undergoes reduction within cells and participates in glutathione (GSH) synthesis. GSH plays a role as an electron donor in reducing reactive oxygen species (ROS) and reactive nitrogen under the influence of GPXs, thereby forming oxidized GSSG out of two GSH molecules. Hampering the function of system Xc- influences the synthesis of GSH by impeding cystine absorption, leading to diminished GPX activity, reduced cellular antioxidant capacity, lipid ROS accumulation, and oxidative damage, culminating in ferroptosis. Further abbreviations are explained in the abbreviation table at the end of the review.</p>
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<p>Experiments on ferroptosis in rheumatoid arthritis. Animal experiments are marked in blue. Experiments on isolated human fibroblast-like synoviocytes (FLS) are marked in pink. Abbreviations are explained in the glossary.</p>
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<p>Experiments on ferroptosis in osteoarthritis. Animal experiments for inhibition or induction of ferroptosis in vivo or in vitro are marked in purple. Experiments on human chondrocytes in vitro are marked in green. Abbreviations are explained in the glossary.</p>
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44 pages, 8117 KiB  
Review
Advances and Challenges in Immune-Modulatory Biomaterials for Wound Healing Applications
by Yuqi Cao, Jiagui Sun, Shengao Qin, Zhengshu Zhou, Yanan Xu and Chenggang Liu
Pharmaceutics 2024, 16(8), 990; https://doi.org/10.3390/pharmaceutics16080990 - 26 Jul 2024
Viewed by 698
Abstract
Wound healing progresses through three distinct stages: inflammation, proliferation, and remodeling. Immune regulation is a central component throughout, crucial for orchestrating inflammatory responses, facilitating tissue repair, and restraining scar tissue formation. Elements such as mitochondria, reactive oxygen species (ROS), macrophages, autophagy, ferroptosis, and [...] Read more.
Wound healing progresses through three distinct stages: inflammation, proliferation, and remodeling. Immune regulation is a central component throughout, crucial for orchestrating inflammatory responses, facilitating tissue repair, and restraining scar tissue formation. Elements such as mitochondria, reactive oxygen species (ROS), macrophages, autophagy, ferroptosis, and cytokines collaboratively shape immune regulation in this healing process. Skin wound dressings, recognized for their ability to augment biomaterials’ immunomodulatory characteristics via antimicrobial, antioxidative, pro- or anti-inflammatory, and tissue-regenerative capacities, have garnered heightened attention. Notwithstanding, a lack of comprehensive research addressing how these dressings attain immunomodulatory properties and the mechanisms thereof persists. Hence, this paper pioneers a systematic review of biomaterials, emphasizing immune regulation and their underlying immunological mechanisms. It begins by highlighting the importance of immune regulation in wound healing and the peculiarities and obstacles faced in skin injury recovery. This segment explores the impact of wound metabolism, infections, systemic illnesses, and local immobilization on the immune response during healing. Subsequently, the review examines a spectrum of biomaterials utilized in skin wound therapy, including hydrogels, aerogels, electrospun nanofiber membranes, collagen scaffolds, microneedles, sponges, and 3D-printed constructs. It elaborates on the immunomodulatory approaches employed by these materials, focusing on mitochondrial and ROS modulation, autophagic processes, ferroptosis, macrophage modulation, and the influence of cytokines on wound healing. Acknowledging the challenge of antibiotic resistance, the paper also summarizes promising plant-based alternatives for biomaterial integration, including curcumin. In its concluding sections, the review charts recent advancements and prospects in biomaterials that accelerate skin wound healing via immune modulation. This includes exploring mitochondrial transplantation materials, biomaterial morphology optimization, metal ion incorporation, electrostimulation-enabled immune response control, and the benefits of composite materials in immune-regulatory wound dressings. The ultimate objective is to establish a theoretical foundation and guide future investigations in the realm of skin wound healing and related materials science disciplines. Full article
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<p>Skin injuries, repair difficulties, and several types of wound dressings with immunomodulatory functions.</p>
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<p>Immunomodulatory mechanisms of cutaneous wound dressings.</p>
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<p>Studies of wound dressings that modulate mitochondria and ROS. (<b>A</b>) PEPGS promotes ATP and M2 macrophage production (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001). (<b>A</b>(<b>a</b>)) PEPGS was somewhat successful in restoring ATP production (AGEs + PEPGS vs. AGEs, 1.09 ± 0.06 μM vs. 0.66 ± 0.02 μM, <span class="html-italic">p</span> &lt; 0.01). (<b>A</b>(<b>b</b>)) The PEPGS group (13.58 ± 2.13%) induced the conversion of RAW 264.7 cells into M2 macrophages [<a href="#B141-pharmaceutics-16-00990" class="html-bibr">141</a>]. (<b>B</b>) GA/OKGM/MT + NIR + ES reduces inflammatory cells by decreasing ROS (** <span class="html-italic">p</span> &lt; 0.01). (<b>B</b>(<b>a</b>)) A reduction in the amount of ROS. (<b>B</b>(<b>b</b>)) Reduction in the amount of inflammatory cells (black scale bar: 1000 μm; white scale bar: 100 μm) [<a href="#B142-pharmaceutics-16-00990" class="html-bibr">142</a>] (<b>C</b>) TGP@CEC-HA hydrogel has excellent ROS scavenging ability (white scale bar: 100 μm) [<a href="#B147-pharmaceutics-16-00990" class="html-bibr">147</a>]. (<b>D</b>) PF-MN significantly promotes MRSA-infected diabetic wound healing (scale bar, 2 mm) [<a href="#B20-pharmaceutics-16-00990" class="html-bibr">20</a>]. (<b>E</b>) SeC@PA MN promotes M2 macrophage polarization [<a href="#B148-pharmaceutics-16-00990" class="html-bibr">148</a>].</p>
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<p>Studies on wound dressings that modulate autophagy. (<b>A</b>) ZnMet-PF127 attenuates inflammatory responses by promoting autophagy in NIH3T3 cells to inhibit ROS production (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001). (<b>A</b>(<b>a</b>)) ZnMet-PF127 scavenges ROS. (<b>A</b>(<b>b</b>)) Schematic diagram of the mechanism of ROS scavenging by ZnMet-PF127. (<b>A</b>(<b>c</b>)) ZnMet-PF127 promotes the formation of autophagosomes in NIH3T3 cells. (<b>A</b>(<b>d</b>)) ZnMet-PF127 reduces the level of pro-inflammatory factors [<a href="#B159-pharmaceutics-16-00990" class="html-bibr">159</a>]. (<b>B</b>) MGC NPs enhance the immunoreactivity of wound tissue by promoting macrophage autophagy. (<b>B</b>(<b>a</b>)) MGC NPs chitosan hydrogel polarizes M2 macrophages with a large number of autophagic vesicles. (<b>B</b>(<b>b</b>)) MGC NPs chitosan hydrogel promotes wound healing by activating the expression of M2 macrophages in the late wound healing phase. (<b>B</b>(<b>c</b>)) MGC NPs chitosan hydrogel promotes infected wound healing in mice [<a href="#B154-pharmaceutics-16-00990" class="html-bibr">154</a>].</p>
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<p>Studies on wound dressings that modulate bacterial iron death in wounds. (<b>A</b>) FeS/GA acts as an antibacterial agent by promoting iron death in <span class="html-italic">Staphylococcus aureus</span>. (<b>A</b>(<b>a</b>)) FeS/GA hydrogels decreased M1 macrophage activation and led to a shift to an M2 phenotype (white scale bar: 100 μm). (<b>A</b>(<b>b</b>)) Diagram of the mechanism by which FeS/GA hydrogels sterilize bacteria by inducing bacterial iron death. (<b>A</b>(<b>c</b>)) FeS/GA hydrogels reduce levels of pro-inflammatory factors (* <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, and **** <span class="html-italic">p</span> &lt; 0.0001). (<b>A</b>(<b>d</b>)) FeS/GA hydrogels promote the healing of infected wounds in diabetic mice [<a href="#B162-pharmaceutics-16-00990" class="html-bibr">162</a>]. (<b>B</b>) Fe<sup>3+</sup> in FeCl<sub>3</sub>-PB hydrogels successfully enters <span class="html-italic">P. aeruginosa</span> and triggers an elevated level of unstable Fe<sup>2+</sup> in the cell, generating hydroxyl radicals that induce ROS production, lipid peroxidation, DNA damage, and iron death in <span class="html-italic">Pseudomonas aeruginosa</span> cells, which exerts an antimicrobial effect (statistical significance was denoted by different letters (<span class="html-italic">p</span> &lt; 0.05) [<a href="#B163-pharmaceutics-16-00990" class="html-bibr">163</a>].</p>
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<p>Studies on wound dressings that modulate macrophage behavior. (<b>A</b>) TPH@MN promotes the macrophage efferocytosis capacity, and the expression of MerTK, CX3CR1, Gas6, and Rac1, mRNAs associated with the role of efferocytosis, was significantly upregulated in macrophages after TPH@MN intervention (* <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; ns, not significant; white scale bar, 100 μm) [<a href="#B169-pharmaceutics-16-00990" class="html-bibr">169</a>]. (<b>B</b>) The ChMA/PCL nanofibrous membrane reduces pro-inflammatory factor levels (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.005) [<a href="#B172-pharmaceutics-16-00990" class="html-bibr">172</a>]. (<b>C</b>) DNA-FKNa/Ag hydrogels promote M2 macrophage recruitment (red scale bar: 100 μm) [<a href="#B173-pharmaceutics-16-00990" class="html-bibr">173</a>]. (<b>D</b>) C@P attenuates the inflammatory response by reducing M1 macrophage polarization. (<b>D</b>(<b>a</b>)) C@P downregulates macrophage miR-29a/b1 expression (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01). (<b>D</b>(<b>b</b>)) C@P promotes wound healing in diabetic mice [<a href="#B79-pharmaceutics-16-00990" class="html-bibr">79</a>]. (<b>E</b>) Gel-QAS decreased the expression of pro-inflammatory factors secreted by M1 cells and increased the expression of anti-inflammatory factors secreted by M2 cells (* <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; ns, not significant) [<a href="#B76-pharmaceutics-16-00990" class="html-bibr">76</a>]. (<b>F</b>) ICOQF attenuates the inflammatory response by prompting macrophages to polarize from the M1 to the M2 type. (<b>F</b>(<b>a</b>)) ICOQF inhibits the proliferation of activated macrophages and promotes macrophage phenotypic polarization to fight inflammation. (<b>F</b>(<b>b</b>)) ICOQF promotes wound healing in diabetic mice infected with MRSA [<a href="#B181-pharmaceutics-16-00990" class="html-bibr">181</a>].</p>
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<p>Studies on wound dressings that modulate cytokines. (<b>A</b>) CMCS-CEBT reduced levels of pro-inflammatory factors TNF-α, IL-1β, IL-6, and IL-10 (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01; NS, not significant) [<a href="#B189-pharmaceutics-16-00990" class="html-bibr">189</a>]. (<b>B</b>) CQDs/hydrogels reduce levels of pro-inflammatory factors TNF-α and IL-6 and promote collagen deposition and angiogenesis (scale bar: 100 μm) [<a href="#B192-pharmaceutics-16-00990" class="html-bibr">192</a>]. (<b>C</b>) HMP hydrogel promotes macrophage polarization from M1 to M2 (scale bar: 50 μm) [<a href="#B194-pharmaceutics-16-00990" class="html-bibr">194</a>]. (<b>D</b>) Man-PEI-ASO hydrogel promoted M2 macrophage polarization by decreasing the levels of inflammatory factors and increasing the levels of anti-inflammatory factors. (<b>D</b>(<b>a</b>)) Man-PEI-ASO hydrogel reduced the expression of pro-inflammatory factors IL-1β and TNF-α and increased the expression of anti-inflammatory factor IL-4 (** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001; ns, not significant). (<b>D</b>(<b>b</b>)) Man-PEI-ASO hydrogel promotes wound healing in diabetic mice [<a href="#B186-pharmaceutics-16-00990" class="html-bibr">186</a>]. (<b>E</b>) M-NPs/MLN4924 hydrogels promoted M2 macrophage polarization by decreasing levels of inflammatory factors and increasing levels of anti-inflammatory factors (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001). (<b>E</b>(<b>a</b>)) M-NPs/MLN4924 hydrogels inhibited macrophage M1 polarization and promoted their shift to an M2 repair phenotype. (<b>E</b>(<b>b</b>)) M-NPs/MLN4924 reduced TNF-α and IL-6 secretion [<a href="#B193-pharmaceutics-16-00990" class="html-bibr">193</a>].</p>
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<p>Studies on wound dressings that modulate cytokines. (<b>A</b>) CMCS-CEBT reduced levels of pro-inflammatory factors TNF-α, IL-1β, IL-6, and IL-10 (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01; NS, not significant) [<a href="#B189-pharmaceutics-16-00990" class="html-bibr">189</a>]. (<b>B</b>) CQDs/hydrogels reduce levels of pro-inflammatory factors TNF-α and IL-6 and promote collagen deposition and angiogenesis (scale bar: 100 μm) [<a href="#B192-pharmaceutics-16-00990" class="html-bibr">192</a>]. (<b>C</b>) HMP hydrogel promotes macrophage polarization from M1 to M2 (scale bar: 50 μm) [<a href="#B194-pharmaceutics-16-00990" class="html-bibr">194</a>]. (<b>D</b>) Man-PEI-ASO hydrogel promoted M2 macrophage polarization by decreasing the levels of inflammatory factors and increasing the levels of anti-inflammatory factors. (<b>D</b>(<b>a</b>)) Man-PEI-ASO hydrogel reduced the expression of pro-inflammatory factors IL-1β and TNF-α and increased the expression of anti-inflammatory factor IL-4 (** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001; ns, not significant). (<b>D</b>(<b>b</b>)) Man-PEI-ASO hydrogel promotes wound healing in diabetic mice [<a href="#B186-pharmaceutics-16-00990" class="html-bibr">186</a>]. (<b>E</b>) M-NPs/MLN4924 hydrogels promoted M2 macrophage polarization by decreasing levels of inflammatory factors and increasing levels of anti-inflammatory factors (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001). (<b>E</b>(<b>a</b>)) M-NPs/MLN4924 hydrogels inhibited macrophage M1 polarization and promoted their shift to an M2 repair phenotype. (<b>E</b>(<b>b</b>)) M-NPs/MLN4924 reduced TNF-α and IL-6 secretion [<a href="#B193-pharmaceutics-16-00990" class="html-bibr">193</a>].</p>
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21 pages, 1792 KiB  
Review
Different Types of Cell Death in Diabetic Neuropathy: A Focus on Mechanisms and Therapeutic Strategies
by Shang Ye, Zilin Cheng, Dongye Zhuo and Shuangmei Liu
Int. J. Mol. Sci. 2024, 25(15), 8126; https://doi.org/10.3390/ijms25158126 - 25 Jul 2024
Viewed by 317
Abstract
Diabetic neuropathy (DN) is a common complication of diabetes, affecting over 50% of patients, leading to significant pain and a burden. Currently, there are no effective treatments available. Cell death is considered a key factor in promoting the progression of DN. This article [...] Read more.
Diabetic neuropathy (DN) is a common complication of diabetes, affecting over 50% of patients, leading to significant pain and a burden. Currently, there are no effective treatments available. Cell death is considered a key factor in promoting the progression of DN. This article reviews how cell death is initiated in DN, emphasizing the critical roles of oxidative stress, mitochondrial dysfunction, inflammation, endoplasmic reticulum stress, and autophagy. Additionally, we thoroughly summarize the mechanisms of cell death that may be involved in the pathogenesis of DN, including apoptosis, autophagy, pyroptosis, and ferroptosis, among others, as well as potential therapeutic targets offered by these death mechanisms. This provides potential pathways for the prevention and treatment of diabetic neuropathy in the future. Full article
(This article belongs to the Section Molecular Endocrinology and Metabolism)
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Figure 1

Figure 1
<p>Pathways leading to cell death in DN. Hyperglycemia activates several metabolic pathways: the polyol pathway, hexosamine pathway, PKC pathway, and AGE-RAGE pathway. In the polyol pathway, hyperglycemia increases glucose flux, converting glucose to sorbitol via AR, which consumes NADPH and reduces GSH regeneration, leading to oxidative stress. The hexosamine pathway increases UDP-GlcNAc, contributing to advanced glycation end-products (AGEs) and enhancing oxidative stress. The PKC pathway is activated by elevated DAG and GAP, promoting inflammation and oxidative stress. The AGE-RAGE pathway activates signaling pathways (MAPK, JNK, NF-κB), increasing inflammatory cytokines (IL-1β, IL-2, IL-6, IL-8, TNF-α, CXCL1, CCL2). Hyperglycemia also directly leads to glutamate-induced excitotoxicity, contributing to neuronal damage. These pathways converge to produce ROS, causing oxidative stress, DNA damage (via PARP activation), ER stress, mitochondrial dysfunction, and glutamate-induced excitotoxicity, ultimately leading to neuronal cell death. Red arrows indicate a decrease in certain molecules or pathways, green arrows indicate an increase in certain molecules or pathways. GSH, glutathione; NADPH, nicotinamide adenine dinucleotide phosphate (reduced form); AR, aldose reductase; F-6-P, fructose-6-phosphate; UDP-GlcNAc, UDP-N-acetylglucosamine; DAG, diacylglycerol; GAP, glyceraldehyde-3-phosphate; PKC, protein kinase C; AGE, advanced glycation end-product; RAGE, receptor for advanced glycation end-products; MAPK, mitogen-activated protein kinase; JNK, c-Jun N-terminal kinase; NF-κB, nuclear factor kappa-light-chain-enhancer of activated B cells; IL, interleukin; TNF-α, tumor necrosis factor-alpha; CXCL1, C-X-C motif chemokine ligand 1; CCL2, C-C motif chemokine ligand 2; ROS, reactive oxygen species; PARP, poly (ADP-ribose) polymerase.</p>
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<p>Mechanisms of ER stress in the cellular response. In mild ER stress, three primary signaling pathways are activated: the ATF6 pathway, which upregulates genes involved in ER-associated degradation to reduce the load of misfolded proteins; the IRE1 pathway, which splices XBP1 mRNA, leading to the production of UPR target genes that enhance protein folding capacity; and the PERK pathway, which phosphorylates eIF2α, reducing protein synthesis to decrease the protein load entering the ER. Under severe and persistent ER stress, these pathways lead to different outcomes: the ATF6 pathway modulates the expression of CHOP, influencing cell fate; the IRE1 pathway activates ASK1, JNK, and the MAPK pathway, leading to apoptosis; and the PERK pathway’s phosphorylation of eIF2α promotes the translocation of ATF4, upregulating CHOP and contributing to apoptotic signaling. This dual response mechanism shows how cells attempt to restore homeostasis under mild ER stress but may trigger apoptotic pathways if the stress is severe and prolonged, ultimately determining the cell fate. Red arrows indicate a decrease in certain molecules or pathways, green arrows indicate an increase in certain molecules or pathways. ATF6, activating transcription factor 6; IRE1, inositol-requiring enzyme 1; XBP1, X-box binding protein 1; PERK, protein kinase RNA-like ER kinase; eIF2α, eukaryotic initiation factor 2-alpha; UPR, unfolded protein response; ASK1, apoptosis signal-regulating kinase 1; JNK, c-Jun N-terminal kinase; MAPK, mitogen-activated protein kinase; CHOP, C/EBP homologous protein; ATF4, activating transcription factor 4.</p>
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<p>Mechanisms of pyroptosis and approaches for targeting pyroptosis. Activation of inflammasomes by PAMPs and DAMPs leads to the cleavage of pro-caspase-1 into active caspase-1. Caspase-1 then activates GSDMD, which forms membrane pores, resulting in cell swelling, rupture, and inflammation. Alternatively, LPS can activate caspase-4/5/11, which also cleaves GSDMD. Potassium efflux through P2X7 receptors and calcium influx are critical regulators of inflammasome activation. Therapeutic approaches include MCC950 (inflammasome inhibitor), necrosulfonamide (GSDMD inhibitor), melatonin (suppresses caspase-1), and lncRNA-UC.360+ shRNA (modulates upstream signaling). PAMPs, pathogen-associated molecular patterns; DAMPs, danger-associated molecular patterns; GSDMD, gasdermin D; P2X7R, purinergic ligand-gated ion channel seven receptor.</p>
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<p>Mechanisms of ferroptosis and representative approaches for targeting ferroptosis. Ferroptosis is driven by lipid ROS and PUFA-OOH. Fpn transports Fe into the cell, where excess iron participates in the Fenton reaction, producing ROS. These ROS initiate and propagate the peroxidation of PUFAs in cell membranes, leading to the formation of PUFA-OOH. The accumulation of PUFA-OOH increases ROS levels and disrupts membrane integrity, resulting in ferroptosis. Therapeutic approaches aim to mitigate this process. Activation of the Nrf2 pathway enhances antioxidant defenses by upregulating HO-1 and GPX4. HO-1 modulates iron metabolism, reducing free iron levels, while GPX4 reduces PUFA-OOH to PUFA-OH. Erythropoietin decreases cellular iron levels. Liraglutide promotes the expression of the cystine/glutamate antiporter SLC7A11/SLC3A2, facilitating cystine uptake and GSH synthesis, which is crucial for GPX4 activity. Additionally, naringin activates Nrf2 via the P2Y14 receptor, further bolstering antioxidant defenses and inhibiting ferroptosis. PUFAs, polyunsaturated fatty acids; Fpn, ferroportin; Nrf2, nuclear factor erythroid 2-related factor 2; HO-1, heme oxygenase-1; GPX4, glutathione peroxidase 4; P2Y14, P2Y purinoceptor 14.</p>
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