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16 pages, 4153 KiB  
Article
Metabolic Activity in Human Intermuscular Adipose Tissue Directs the Response of Resident PPARγ+ Macrophages to Fatty Acids
by Xiaoying Chen, Sebastian Ludger Schubert, Aline Müller, Miguel Pishnamaz, Frank Hildebrand and Mahtab Nourbakhsh
Biomedicines 2025, 13(1), 10; https://doi.org/10.3390/biomedicines13010010 (registering DOI) - 25 Dec 2024
Abstract
Background/Objectives: Peroxisome proliferator-activated receptor gamma (PPARγ) is a fatty acid-binding transcription activator of the adipokine chemerin. The key role of PPARγ in adipogenesis was established by reports on adipose tissue-resident macrophages that express PPARγ. The present study examined PPARγ+ macrophages in [...] Read more.
Background/Objectives: Peroxisome proliferator-activated receptor gamma (PPARγ) is a fatty acid-binding transcription activator of the adipokine chemerin. The key role of PPARγ in adipogenesis was established by reports on adipose tissue-resident macrophages that express PPARγ. The present study examined PPARγ+ macrophages in human skeletal muscle tissues, their response to fatty acid (FA) species, and their correlations with age, obesity, adipokine expression, and an abundance of other macrophage phenotypes. Methods: An ex vivo human skeletal muscle model with surgical specimens that were maintained without or with FAs for up to 11 days was utilized. Immunofluorescence analysis was used to detect macrophage phenotypes and mitochondrial activity. Preconfigured arrays were used to detect the expression of 34 different adipokines and chemokines. Results: Data from 14 adults revealed that PPARγ+ macrophages exclusively reside in intermuscular adipose tissue (IMAT), and their abundance correlates with the metabolic status of surrounding adipocytes during tissue maintenance in vitro for 9–11 days. Elevated fatty acid levels lead to significant increases in PPARγ+ populations, which are correlated with the donor’s body mass index (BMI). Conclusions: PPARγ+ macrophages represent a distinctly specialized population of regulatory cells that reside within human IMATs in accordance with their metabolic status. Thus, future in-depth studies on IMAT-resident PPARγ+ macrophage action mechanisms will elucidate the role of skeletal muscle in the pathogenesis of human metabolic dysfunction. Full article
(This article belongs to the Special Issue The Role of Chemerin in Human Disease2nd Edition)
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Figure 1

Figure 1
<p>Representative images of skeletal muscle tissue (HE) and IMATs (IF). All images were obtained from Participant P6. (<b>a</b>) HE image showing the human skeletal muscle tissue comprising the areas of SMFs (red arrowhead) and IMATs (green arrowhead). The scale bar (lower right) indicates 1000 µm. (<b>b</b>) IF images were obtained after costaining with DAPI and secondary antibodies as negative controls (negative-488 or 594). The scale bars (upper left) indicate 50 µm. (<b>c</b>–<b>i</b>) IF images of IMATs after costaining with primary antibodies against designated human markers (white, lower left) and the corresponding secondary antibodies and DAPI. The small panels on the left side represent magnified single-cell images labeled with dashed line circles in larger images using IgG488 (green), IgG594 (red), and DAPI (blue) filters. DAPI and IgG594 or DAPI and IgG488 were merged (Merge) to determine the specificity of the detected signals. The white arrowheads indicate verified positive macrophages. The scale bars (upper left) indicate 50 µm.</p>
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<p>PPARγ<sup>+</sup> macrophages exclusively reside in IMATs. (<b>a</b>) Representative images from a skeletal muscle tissue slice from P2 after IF staining using a primary antibody against PPARγ, IgG488-labeled secondary antibody, and DAPI. The image of brightfield microscopy (middle panel) comprises skeletal muscle fibers (left) and intermuscular adipose tissue with adipocytes (right). Magnified IF images show the labeled areas of skeletal muscle fibers (upper left panel) and intermuscular adipose tissue (lower right panel) exposing a PPARγ<sup>+</sup> macrophage (white arrowhead), respectively. (<b>b</b>) The diagram shows the mean number of PPARγ<sup>+</sup> macrophages (<span class="html-italic">y</span>-axis) in the IMAT and SMF fields of 0.24 mm<sup>2</sup> (<span class="html-italic">x</span>-axis) in donor tissue samples (n = 14). (<b>c</b>) The diagram shows the mean number of PPARγ<sup>+</sup> macrophages (<span class="html-italic">y</span>-axis) relative to 1 mm<sup>2</sup> of IMATs (left <span class="html-italic">y</span>-axis) or relative to the number of adipocytes in 1 mm<sup>2</sup> of IMATs in donor tissue samples (n = 14). The Mann–Whitney test was used to assess the significance of differences in the number of PPARγ<sup>+</sup> macrophages between SMFs and IMATs. <span class="html-italic">p</span> ≤ 0.0001 (****).</p>
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<p>The numbers of CD80<sup>+</sup> and CD11c<sup>+</sup> macrophages correlate with adipocyte VDAC1 expression in the IMATs of donor samples. Pearson correlation analyses were employed to determine the relationships between the mean VDAC1 expression levels and the mean numbers of CD80<sup>+</sup> (<b>a</b>) and CD11c<sup>+</sup> (<b>b</b>) macrophages in 0.24 mm<sup>2</sup> of IMATs from the donors (n = 14). The correlation coefficients (r) and significance levels (<span class="html-italic">p</span>) for the relationships are presented at the top right of each diagram.</p>
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<p>The expression levels of IL-23 and IL-31 correlate with adipocyte VDAC1 expression in the IMATs of donor samples. Spearman’s rank correlation analyses were employed to determine the relationships between mean VDAC1 and IL-23 (<b>a</b>) or IL-31 (<b>b</b>) expression levels (n = 12). The correlation coefficients (r) and significance levels (<span class="html-italic">p</span>) for the relationships are presented at the top right of each diagram.</p>
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<p>Dynamics of the PPARγ<sup>+</sup> macrophage population in IMATs during maintenance in vitro. (<b>a</b>) The diagram shows the mean number of PPARγ<sup>+</sup> macrophages (<span class="html-italic">y</span>-axis) in 0.24 mm<sup>2</sup> of IMAT from all participants (n = 14) before (pre, white bar) and after (post, gray bars) tissue maintenance in vitro. (<b>b</b>) The diagram shows the mean expression of VDAC1 and COXIV (<span class="html-italic">y</span>-axis) in 0.24 mm<sup>2</sup> of IMAT from all participants (n = 14) before (pre, white bars) and after (post, gray bars) tissue maintenance in vitro. A paired t-test or Wilcoxon signed-rank test was applied to evaluate the significance of differences before and after cultivation. <span class="html-italic">p</span> ≤ 0.01 (**). (<b>c</b>,<b>d</b>) Spearman’s rank correlation analyses were applied to determine the relationships between the mean number of PPARγ<sup>+</sup> macrophages and the mean number of CD163<sup>+</sup> (<b>c</b>) or the expression level of COXIV (<b>d</b>) in 0.24 mm<sup>2</sup> of IMAT from all donors (n = 14). The correlation coefficients (r) and significance levels (<span class="html-italic">p</span>) for the relationships are presented at the top right of each diagram.</p>
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<p>Dynamics of the PPARγ<sup>+</sup> macrophage population in IMATs in response to S-FAs and U-FAs during maintenance in vitro. (<b>a</b>) The diagram shows the relative fold change in PPARγ<sup>+</sup> macrophage numbers (<span class="html-italic">y</span>-axis) in 0.24 mm<sup>2</sup> of IMAT from all participants (n = 14) in response to U-FA or S-FAs before (<span class="html-italic">x</span>-axis) in vitro culture. (<b>b</b>) The diagram shows the relative fold change in the expression of VDAC1 (<span class="html-italic">y</span>-axis) in 0.24 mm<sup>2</sup> of IMAT from all participants (n = 14) in response to U-FA or S-FAs before (<span class="html-italic">x</span>-axis) in vitro culture. One-sample <span class="html-italic">t</span>-tests or Wilcoxon signed-rank tests were used to assess the significance of differences before and after cultivation. <span class="html-italic">p</span> ≤ 0.05 (*). (<b>c</b>,<b>d</b>) Pearson correlation and Spearman’s rank correlation analyses were employed to determine the relationships between the S-FA-mediated relative fold change in the number of PPARγ<sup>+</sup> macrophages ((<b>c</b>), <span class="html-italic">y</span>-axis) or the relative fold change in the expression of VDAC1 ((<b>d</b>), <span class="html-italic">y</span>-axis) and donor BMI (n = 14). The correlation coefficients (r) and significance levels (<span class="html-italic">p</span>) for the relationships are presented at the top right of each diagram.</p>
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18 pages, 4207 KiB  
Review
The Therapeutic Potential of Physical Exercise in Cancer: The Role of Chemokines
by Glenda B. B. Buzaglo, Guilherme D. Telles, Rafaela B. Araújo, Gilmar D. S. Junior, Olivia M. Ruberti, Marina L. V. Ferreira, Sophie F. M. Derchain, Felipe C. Vechin and Miguel S. Conceição
Int. J. Mol. Sci. 2024, 25(24), 13740; https://doi.org/10.3390/ijms252413740 - 23 Dec 2024
Abstract
The global increase in cancer cases and mortality has been associated with inflammatory processes, in which chemokines play crucial roles. These molecules, a subfamily of cytokines, are essential for the migration, adhesion, interaction, and positioning of immune cells throughout the body. Chemokines primarily [...] Read more.
The global increase in cancer cases and mortality has been associated with inflammatory processes, in which chemokines play crucial roles. These molecules, a subfamily of cytokines, are essential for the migration, adhesion, interaction, and positioning of immune cells throughout the body. Chemokines primarily originate in response to pathogenic stimuli and inflammatory cytokines. They are expressed by lymphocytes in the bloodstream and are divided into four classes (CC, CXC, XC, and CX3C), playing multifaceted roles in the tumor environment (TME). In the TME, chemokines regulate immune behavior by recruiting cells such as tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), which promote tumor survival. Additionally, they directly influence tumor behavior, promoting pathological angiogenesis, invasion, and metastasis. On the other hand, chemokines can also induce antitumor responses by mobilizing CD8+ T cells and natural killer (NK) cells to the tumor, reducing pro-inflammatory chemokines and enhancing essential antitumor responses. Given the complex interaction between chemokines, the immune system, angiogenic factors, and metastasis, it becomes evident how important it is to target these pathways in therapeutic interventions to counteract cancer progression. In this context, physical exercise emerges as a promising strategy due to its role modulating the expression of anti-inflammatory chemokines and enhancing the antitumor response. Aerobic and resistance exercises have been associated with a beneficial inflammatory profile in cancer, increased infiltration of CD8+ T cells in the TME, and improvement of intratumoral vasculature. This creates an environment less favorable to tumor growth and supports the circulation of antitumor immune cells and chemokines. Therefore, understanding the impact of exercise on the expression of chemokines can provide valuable insights for therapeutic interventions in cancer treatment and prevention. Full article
(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil, 3rd Edition)
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Figure 1

Figure 1
<p>Mechanisms connecting chemokines and their receptors to tumor microenvironment. Solid tumors contain numerous types of stromal cells, such as endothelial cells and fibroblasts, which are major producers of chemokines. These chemokines play a crucial role in the regulation and migration of leukocytes in both tumor bed and TME. The circulation of leukocytes is a highly coordinated process, in which they roll along the endothelium. Chemokines bind to leukocytes through their protein-coupled receptors, resulting in a strong adhesion of leukocytes to the endothelial layer. Eventually, leukocytes overtake the endothelium and migrate towards chemokine-producing tissue or cells. Consequently, the tumor is infiltrated by inflammatory cells, including neutrophils, M2 macrophages, T lymphocytes and dendritic cells. CXC ELR+ chemokines attract tumor-associated neutrophils (N2) expressing CXCR2 and CXCR1. Similarly, chemokines of the CC subfamily attract tumor-associated macrophages (M2) expressing CCR1/2/3/5/8. In contrast, some ELR-CXC chemokines, such as CXCL9/10/11 ligands, attract CXCR3-activated T lymphocytes and NK and CD8+ T cells, which may exert antitumor (cytotoxic) activity. Regarding the production of chemokines by leukocytes, tumor cells and tumor-associated cells (Tam’s subtype M2, Tan’s subtype N2, MDCs, T<sub>reg</sub>) have effects on pathological angiogenesis through their angiogenic ligands (CXCL1/2/3/5/6/7/8-CXCR2; and agonist CXCR4 CXCL2; CCL2/7/8/13/16-CCR2; CCL20-CCR6; CCL1/18-CCR8; CCL27/28-CCR30; CCR3). This triggers the formation of more immature and hypoxic intratumor vessels. The formation of new blood vessels is determinant in tumorigenesis, because it maintains tumor survival and enhances its proliferation, boosting the process of metastasis. In addition, the receptor-ligand axis CXCL13–CXCR5 and CXCR4–CXCL12 is involved in the targeted migration of tumor cells to metastatic sites, through the activation of oncogenic pathways (STAT3, ERK1/2 and MMPs 2/9) that deteriorate the extracellular matrix, facilitating the escape of cancer cells. TME: tumor microenvironment; STAT3: signal transducers and activators of transcription; ERK1/2: extracellular signal regulated kinase; MMPs2/9: matrix metalloproteinases. Created with Biorender.</p>
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<p>Systemic and Molecular Mechanisms Associated with the Modulation of Chemokines by the Immune System and Changes in the Tumor Microenvironment (TME). (<b>A</b>) Physical inactivity is one of the mediators of the inflammatory process. When this inflammation worsens and becomes chronic, there is an excessive production of pro-inflammatory factors, such as the chemokines CC2, CCL3-CCR1, and CXCL13-CXCR5, among others mentioned in this article. These substances aid in the production and excessive migration of pro-tumor cells such as TAMS, TANS, MDSCs, and T-reg into the bloodstream, directing them to an organ of the human body and triggering the formation of a primary tumor. As the signaling axis of chemokines CC2, CCL3-CCR1 facilitates the migration of Tams from the subtype M2 to the TME, this potentiates the inflammatory process. This same axis contributes to increased pathological angiogenesis and intratumor hypoxia, presenting an immature vasculature and low oxygen circulation. When the production and infiltration of CXCL13-CXCR5 chemokines, as well as of TAM pro-tumor cells, TANs of M2 and N2 subtypes, and especially of T reg, becomes uncontrolled, there is an enhanced immunological suppression and tumor proliferation. Additionally, the uncontrolled production of the CXCL13-CXCR5 chemokine axis activates oncogenic pathways, such as STAT3, ERK1/2, and MMPs 2/9, which induce the deterioration of the extracellular matrix. This favors the escape of tumor cells induced by chemokine receptors, such as CXCR5, into the blood circulation, determining the process of metastasis. (<b>B</b>) Single sessions of exercise promote immune regulation, such as increased circulation of immune cells due to the lymphocytosis process, which mainly affects NK cells and CD8+ T cells. This lymphocytosis is driven by physical changes in the body, such as increased blood flow, shear stress, and increased body temperature, resulting in a higher concentration of immune cells in the blood circulation. Subsequently, a transient lymphopenia occurs, in which the mobilized cells are redistributed to the infection sites, improving immunovigilance and increasing the cytotoxic activity of immune cells. This increase in the circulation of NK and T CD8+ cells stimulates the production of antitumor chemokines, such as CXCL9, CXCL11, and CXCR3 (among others already mentioned in the article), which promote the targeted migration of these cells to TME. Additionally, physical changes induced by exercise sessions (increased blood flow, shear stress in the vascular bed, and elevation of body temperature) act directly in the TME, tumor perfusion, and intratumor oxygen supply. This facilitates infiltration of anti-tumor chemokines CXCL9/11-CXCR3 and NK and T CD8+ cells, increasing their cytotoxic activity against tumor cells and reprogramming intratumor immunity. Consequently, there is a reduction in the expression of CXCL13-CXCR5 chemokines and pro-tumor cells associated with the activation of oncogenic signaling pathways linked to metastasis. (<b>C</b>) Repeated bouts of exercise lead to chronic adaptations that include systemic changes, such as improved immune function, with increased circulation of NK immune cells, CD8+ T, and anti-tumor factors. In addition, there is a reduction in chronic inflammation and changes in the tumor microenvironment triggered by physiological angiogenesis, which improves blood perfusion and maturation of tumor vasculature, reducing intratumor hypoxia. These adaptations facilitate greater infiltration of NK and T CD8+ cells and their cytotoxic action, as well as high concentrations of CXCL9/11-CXCR3 chemokines in TME, as a result of immunological reprogramming. Thus, all adaptations corroborate a reduction in tumor proliferation and a low concentration of pro-tumor chemokines. TME: tumor microenvironment; STAT3: signal transducers and activators of transcription; ERK1/2: extracellular signal regulated kinase; MMPs2/9: matrix metalloproteinases. Created with Biorender.</p>
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11 pages, 2557 KiB  
Article
Effects of Hispidulin on the Osteo/Odontogenic and Endothelial Differentiation of Dental Pulp Stem Cells
by Yeon Kim, Hyun-Joo Park, Mi-Kyoung Kim, Hyung Joon Kim, Yong-Il Kim, Soo-Kyung Bae and Moon-Kyoung Bae
Pharmaceuticals 2024, 17(12), 1740; https://doi.org/10.3390/ph17121740 - 23 Dec 2024
Abstract
Background: Human dental pulp stem cells (HDPSCs) with multi-lineage differentiation potential and migration ability are required for HDPSC-based bone and dental regeneration. Hispidulin is a naturally occurring flavonoid with diverse pharmacological activities, but its effects on biological properties of HDPSCs remain unknown. Therefore, [...] Read more.
Background: Human dental pulp stem cells (HDPSCs) with multi-lineage differentiation potential and migration ability are required for HDPSC-based bone and dental regeneration. Hispidulin is a naturally occurring flavonoid with diverse pharmacological activities, but its effects on biological properties of HDPSCs remain unknown. Therefore, we investigated the effects of hispidulin on the differentiation potential and migration ability of HDPSCs and elucidated their underlying mechanisms. Methods: The osteo/odontogenic capacity of HDPSCs was assessed using the alkaline phosphatase (ALP) and Alizarin Red S (ARS) staining. The migration ability of HDPSCs was evaluated using a scratch wound assay. Furthermore, the endothelial differentiation of HDPSCs was examined by using a capillary sprouting assay and by assessing CD31 expression. Results: Hispidulin significantly enhanced the osteo/odontogenic differentiation of HDPSCs with increased expression of osteo/odontogenic differentiation markers. Hispidulin increased the migration of HDPSCs, which was mediated by the upregulation of C-X-C chemokine receptor type 4 (CXCR4). The treatment of HDPSCs with hispidulin enhanced the differentiation of HDPSCs into endothelial cells, as evidenced by increased capillary sprouting and endothelial marker expression. In addition, we demonstrated that hispidulin activated the ERK1/2 signaling, and its inhibition by U0126 significantly suppressed the hispidulin-induced endothelial differentiation of HDPSCs. Conclusions: These findings demonstrate that hispidulin effectively promotes the osteo/odontogenic and endothelial differentiation, and migration of HDPSCs. These results suggest that hispidulin may have potential therapeutic applications in dental pulp regeneration and tissue engineering. Full article
(This article belongs to the Special Issue Pharmacological Activities of Flavonoids and Their Analogues 2024)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Effect of hispidulin on osteo/odontogenic differentiation and expression of osteo/odontogenic-related markers in HDPSCs. (<b>A</b>) HDPSCs were either cultured in the basic growth medium or osteogenic differentiation medium (ODM) with or without hispidulin (5 μM). ALP staining was performed on days 7 and 14. Stained cells were photographed using a phase contrast microscope at 100× magnification. ALP-positive areas were quantified by densitometry in triplicates. * <span class="html-italic">p</span> &lt; 0.01 compared to control. # <span class="html-italic">p</span> &lt; 0.05 compared to ODM. (<b>B</b>) The formation of mineralized nodules was evaluated by ARS staining and quantified through densitometric analysis in triplicate at days 14 and 21. The stained cells were imaged under 100× magnification. * <span class="html-italic">p</span> &lt; 0.01 compared to control. # <span class="html-italic">p</span> &lt; 0.01 compared to ODM. (<b>C</b>) HDPSCs were cultured with or without ODM in the presence of hispidulin for 14 days. The mRNA expression of <span class="html-italic">ALP</span>, <span class="html-italic">osteocalcin</span>, <span class="html-italic">DMP-1</span>, <span class="html-italic">and Runx-2</span> were assessed through real-time PCR analysis. All values were normalized to β-actin mRNA levels, and the expression level of the control group was designated as 1.0. * <span class="html-italic">p</span> &lt; 0.01 compared to control. ** <span class="html-italic">p</span> &lt; 0.05 compared to control. # <span class="html-italic">p</span> &lt; 0.01 compared to ODM. ## <span class="html-italic">p</span> &lt; 0.05 compared to ODM.</p>
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<p>Effect of hispidulin on the migration of HDPSCs. (<b>A</b>) Scratch wound migration assays were performed on HDPSCs cultured without or with hispidulin (1 or 5 μM) for 24 h. Cell migration into the scratch wound area was photographed at 100× magnification and quantified. Results are expressed as the mean values from three independent experiments per group. * <span class="html-italic">p</span> &lt; 0.05 compared with control. # <span class="html-italic">p</span> &lt; 0.01 compared with control. (<b>B</b>) HDPSCs were treated with hispidulin (1 or 5 μM) for 24 h, and the expression of CXCR4 was analyzed with real-time qPCR. All values were normalized to β-actin mRNA levels, with the control group expression set as 1.0. * <span class="html-italic">p</span> &lt; 0.05 compared with control. (<b>C</b>) Protein expression of CXCR4 was observed by western blotting using an anti-CXCR4 antibody (upper) and densitometric analysis (lower). β-actin was used as the loading control. (<b>D</b>) HDPSCs were incubated with 1 μM hispidulin alone or in combination with AMD3100 (50 μg/mL) for 24 h. Migrated cells beyond the reference line were photographed at 100× magnification and quantified. * <span class="html-italic">p &lt;</span> 0.01 compared with control. # <span class="html-italic">p</span> &lt; 0.01 compared to hispidulin.</p>
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<p>Effect of hispidulin on endothelial differentiation of HDPSCs. (<b>A</b>) HDPSCs implanted on a Matrigel-coated plate were treated with 1 μM hispidulin for 3, 5, and 7 days in the EGM-2MV. The numbers of sprouts were counted and imaged under 100× magnification. Each result represents the mean value of triplicate experiments in each group. * <span class="html-italic">p</span> &lt; 0.01 compared with the 3-days control. # <span class="html-italic">p</span> &lt; 0.05 compared with 5-dayscontrol. ** <span class="html-italic">p</span> &lt; 0.01 compared with the 7-days control. (<b>B</b>) The protein expression of CD31 was analyzed by western blotting. β-actin was used as a loading control. (<b>C</b>) HDPSCs were treated with 1 μM hispidulin for 3, 5, and 7 days. CD31 was measured by flow cytometry.</p>
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<p>Effect of hispidulin on the ERK signaling pathway in endothelial differentiation of HDPSCs. (<b>A</b>) HDPSCs were treated with hispidulin (1 μM) for the indicated times in EGM-2MV. Cell lysates were immunoblotted with antibodies against phospho-ERK and total ERK. β-actin was used as a loading control. (<b>B</b>) HDPSCs were treated with hispidulin (1 μM) alone or in combination with U0126 (10 μM). After 7 days, CD31 protein expression was analyzed by western blotting. β-actin was used as a loading control. (<b>C</b>) HDPSCs were seeded on Matrigel-coated plates and treated with hispidulin (1 μM) alone or in combination with U0126 (10 μM) in EGM-2MV. Capillary sprouting was observed after 7 days (200× magnification). Images are representative of three independent experiments. * <span class="html-italic">p</span> &lt; 0.01 compared to control. # <span class="html-italic">p</span> &lt; 0.01 compared to hispidulin.</p>
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<p>Schematic diagram illustrating the regulatory mechanisms of hispidulin in promoting osteo/odontogenic and endothelial differentiation, and migration of HDPSCs.</p>
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16 pages, 5839 KiB  
Article
PS-MPs Induced Inflammation and Phosphorylation of Inflammatory Signalling Pathways in Liver
by Mengchao Ying, Naimin Shao, Cheng Dong, Yijie Sha, Chen Li, Xinyu Hong, Yu Ding, Jing Xu, Kelei Qian, Gonghua Tao and Ping Xiao
Toxics 2024, 12(12), 932; https://doi.org/10.3390/toxics12120932 - 22 Dec 2024
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Abstract
As new pollutants, microplastics (MPs) have attracted much attention worldwide because they cause serious environmental pollution and pose potential health risks to humans. However, the toxic effects of MPs are still unclear. In this study, we analysed the inflammatory effects of 0.1 μm [...] Read more.
As new pollutants, microplastics (MPs) have attracted much attention worldwide because they cause serious environmental pollution and pose potential health risks to humans. However, the toxic effects of MPs are still unclear. In this study, we analysed the inflammatory effects of 0.1 μm polystyrene microplastics (PS-MPs) on mouse and human liver cell lines. After 28 days of exposure to PS-MPs, the mice presented decreased liver index values and increased AST/ALT values. HL7702 and HepG2 were treated with PS-MPs for 24 h, and the cytotoxicity, the expression levels of inflammatory factors, and the phosphorylation of proteins in inflammation related pathways were confirmed. Compared with the control, the cell viability of these two cells significantly decreased after exposure to the PS-MPs at 1000 μm/cm2, and the BMD model also exhibited a similar dose. LDH leakage and AST also increased in a dose-dependent increase after PS-MPs exposure. The relative levels of chemokines such as GM-CSF, IL-6, IL-8, and IL-12p70 were significantly greater than those in the control. Furthermore, the PS-MPs can increase the expression levels of TLR4, MyD88, and NF-κB and activate the phosphorylation of NF-κB and STATs. Based on these results, exposure to PS-MPs can stimulate liver inflammation and activate the TLR4/MyD88/NF-κB and JAK-STAT pathways. Full article
(This article belongs to the Section Reproductive and Developmental Toxicity)
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Figure 1
<p>Effects of PS-MPs on mice. The (<b>A</b>) body weight; (<b>B</b>) liver weights; and (<b>C</b>) organ index after 28 days of PS-MPs exposure; (<b>D</b>) blood biochemical examination of the serum; (<b>E</b>) ratio of AST/ALT; (<b>F</b>) H&amp;E staining of the liver tissue. Yellow arrow: perivascular infiltration of liver tissue; *: <span class="html-italic">p</span> ≤ 0.05; scale bar: 200 μm.</p>
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<p>PS-MPs enter and cause changes in liver cell morphology. (<b>A</b>) Cell morphology after treatment with different PS-MP doses. Scale bar: 100 μm. (<b>B</b>) The location of green, fluorescent PS-MPs in liver cells. Scale bar: 50 μm.</p>
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<p>Cell viability of PS-MPs in liver cells. (<b>A</b>) Cell viability of two liver cell lines after PS-MP treatment; (<b>B</b>) BMD model of cell viability for HL7702 and HepG2 cells; (<b>C</b>) LDH leakage for HL7702 and HepG2 cells; (<b>D</b>) AST and ALT levels in HL7702 and HepG2 cells. *: <span class="html-italic">p</span> ≤ 0.05; blue line: estimated probability line between cell viability and treatment dose; light green line: the response value of cell viability at BMD; red circle: The cell viability and treatment dose data; green line: the BMD value; yellow line: the BMDL value.</p>
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<p>Effects of PS-MPs on the levels of chemokines in liver cells. (<b>A</b>) Relative levels in the cell culture medium of HL7702 cells. (<b>B</b>) The relative levels in the cell culture medium of HepG2 cells. (<b>C</b>) The relative levels in the lysates of HepG2 cells. *: <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Heatmap of the inflammatory response and autoimmunity gene expression levels. The heatmap shows the relative expression levels of the genes. The red colour indicates upregulated genes, and the blue colour indicates downregulated genes.</p>
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<p>Effects of PS-MPs on the phosphorylation levels of proteins in 5 signalling pathways. The results of the antibody microarray (<b>A</b>) and relative phosphorylation levels (<b>C</b>) in HL7702 cells. The results of the antibody microarray (<b>B</b>) and relative phosphorylation levels (<b>D</b>) in HepG2 cells. *: <span class="html-italic">p</span> ≤ 0.05.</p>
Full article ">Figure 6 Cont.
<p>Effects of PS-MPs on the phosphorylation levels of proteins in 5 signalling pathways. The results of the antibody microarray (<b>A</b>) and relative phosphorylation levels (<b>C</b>) in HL7702 cells. The results of the antibody microarray (<b>B</b>) and relative phosphorylation levels (<b>D</b>) in HepG2 cells. *: <span class="html-italic">p</span> ≤ 0.05.</p>
Full article ">Figure 6 Cont.
<p>Effects of PS-MPs on the phosphorylation levels of proteins in 5 signalling pathways. The results of the antibody microarray (<b>A</b>) and relative phosphorylation levels (<b>C</b>) in HL7702 cells. The results of the antibody microarray (<b>B</b>) and relative phosphorylation levels (<b>D</b>) in HepG2 cells. *: <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>The protein expression levels of NF-κB, Erk1/2, JAK1, STAT1, STAT2, STAT3, and GAPDH after exposure to PS-MPs. (<b>A</b>) Western blot at 24 h after exposure to PS-MPs and (<b>B</b>) the area under the curve of protein expression. *: <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>The ratios of p-NF-κB, NF-κB, p-Erk1/2, Erk1/2, p-JAK1, JAK1, p-STAT1, STAT1, p-STAT2, STAT2, p-STAT3, and STAT3. The protein expression was quantified via densitometry and normalized to that of GAPDH. *: <span class="html-italic">p</span> ≤ 0.05.</p>
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12 pages, 1491 KiB  
Article
Overlapping Systemic Proteins in COVID-19 and Lung Fibrosis Associated with Tissue Remodeling and Inflammation
by Barbora Svobodová, Anna Löfdahl, Annika Nybom, Jenny Wigén, Gabriel Hirdman, Franziska Olm, Hans Brunnström, Sandra Lindstedt, Gunilla Westergren-Thorsson and Linda Elowsson
Biomedicines 2024, 12(12), 2893; https://doi.org/10.3390/biomedicines12122893 - 19 Dec 2024
Viewed by 372
Abstract
Background/Objectives: A novel patient group with chronic pulmonary fibrosis is emerging post COVID-19. To identify patients at risk of developing post-COVID-19 lung fibrosis, we here aimed to identify systemic proteins that overlap with fibrotic markers identified in patients with idiopathic pulmonary fibrosis (IPF) [...] Read more.
Background/Objectives: A novel patient group with chronic pulmonary fibrosis is emerging post COVID-19. To identify patients at risk of developing post-COVID-19 lung fibrosis, we here aimed to identify systemic proteins that overlap with fibrotic markers identified in patients with idiopathic pulmonary fibrosis (IPF) and may predict COVID-19-induced lung fibrosis. Methods: Ninety-two proteins were measured in plasma samples from hospitalized patients with moderate and severe COVID-19 in Sweden, before the introduction of the vaccination program, as well as from healthy individuals. These measurements were conducted using proximity extension assay (PEA) technology with a panel including inflammatory and remodeling proteins. Histopathological alterations were evaluated in explanted lung tissue. Results: Connecting to IPF pathology, several proteins including decorin (DCN), tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) and chemokine (C-X-C motif) ligand 13 (CXCL13) were elevated in COVID-19 patients compared to healthy subjects. Moreover, we found incrementing expression of monocyte chemotactic protein-3 (MCP-3) and hepatocyte growth factor (HGF) when comparing moderate to severe COVID-19. Conclusions: Both extracellular matrix- and inflammation-associated proteins were identified as overlapping with pulmonary fibrosis, where we found DCN, TNFRSF12A, CXCL13, CXCL9, MCP-3 and HGF to be of particular interest to follow up on for the prediction of disease severity. Full article
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<p>Elevated protein amount of DCN, TNFRSF12A, MCP-3, HGF, CXCL13 and CXCL9 in plasma from patients with moderate and severe COVID-19 in comparison to healthy subjects. NPX = normalized protein expression. Patients with moderate (n = 8) and severe (n = 8) COVID-19; healthy individuals (n = 7). One-way ANOVA with Tukey’s multiple comparison test. * <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.</p>
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<p>The overlapping protein patterns of DCN and POSTN in post-COVID-19 and IPF. In distal lung tissue, the expression of POSTN was mainly localized to the subepithelial regions of bronchioles in healthy (<b>A</b>,<b>D</b>), post-COVID-19 (<b>B</b>,<b>E</b>) and IPF (<b>C</b>,<b>F</b>) patients, enclosed upon magnification in the basement membrane zone (arrow). POSTN was highly expressed in fibroblastic foci in IPF (<b>G</b>,<b>H</b>, encircled area) and in similar structures in post-COVID-19 patients (<b>I</b>,<b>J</b>). Similarly, DCN was found to be intensely expressed in the subepithelial regions of bronchioles (arrowhead) and in vascular adventitia (arrow) (healthy, <b>K</b>–<b>M</b>). Increased DCN expression was also seen in pleura (arrows) and subpleural regions in healthy (<b>N</b>, including HE staining), post-COVID-19 (<b>O</b>, including HE staining) and IPF (<b>P</b>, including HE staining) patients. Scale bar: 500 µm (<b>N</b>–<b>P</b>); 100 µm (<b>A</b>–<b>F</b>, <b>K</b>–<b>M</b>; enlargements <b>N</b>–<b>P</b>); 20 µm (enlargement (<b>D</b>–<b>F</b>), <b>G</b>–<b>J</b>). * = bronchiole; v = vessel.</p>
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15 pages, 3611 KiB  
Article
Chemokine CXCL12 Activates CXC Receptor 4 Metastasis Signaling Through the Upregulation of a CXCL12/CXCR4/MDMX (MDM4) Axis
by Rusia Lee, Viola Ellison, Dominique Forbes, Chong Gao, Diana Katanov, Alexandra Kern, Fayola Levine, Pam Leybengrub, Olorunseun Ogunwobi, Gu Xiao, Zhaohui Feng and Jill Bargonetti
Cancers 2024, 16(24), 4194; https://doi.org/10.3390/cancers16244194 - 16 Dec 2024
Viewed by 441
Abstract
Background: The metastasis-promoting G-protein-coupled receptor CXC Receptor 4 (CXCR4) is activated by the chemokine CXCL12, also known as stromal cell-derived factor 1 (SDF-1). The CXCL12/CXCR4 pathway in cancer promotes metastasis but the molecular details of how this pathway cross-talks with oncogenes are understudied. [...] Read more.
Background: The metastasis-promoting G-protein-coupled receptor CXC Receptor 4 (CXCR4) is activated by the chemokine CXCL12, also known as stromal cell-derived factor 1 (SDF-1). The CXCL12/CXCR4 pathway in cancer promotes metastasis but the molecular details of how this pathway cross-talks with oncogenes are understudied. An oncogene pathway known to promote breast cancer metastasis in MDA-MB-231 xenografts is that of Mouse Double Minute 2 and 4 (MDM2 and MDM4, also known as MDMX). MDM2 and MDMX promote circulating tumor cell (CTC) formation and metastasis, and positively correlate with a high expression of CXCR4. Interestingly, this MDMX-associated upregulation of CXCR4 is only observed in cells grown in the tumor microenvironment (TME), but not in MDA-MB-231 cells grown in a tissue culture dish. This suggested a cross-talk signaling factor from the TME which was predicted to be CXCL12 and, as such, we asked if the exogenous addition of the cell non-autonomous CXCL12 ligand would recapitulate the MDMX-dependent upregulation of CXCR4. Methods: We used MDA-MB-231 cells and isolated CTCs, with and without MDMX knockdown, plus the exogenous addition of CXCL12 to determine if MDMX-dependent upregulation of CXCR4 could be recapitulated outside of the TME context. We added exogenous CXCL12 to the culture medium used for growth of MDA-MB-231 cells and isogenic cell lines engineered for MDM2 or MDMX depletion. We carried out immunoblotting, and quantitative RT-PCR to compare the expression of CXCR4, MDM2, MDMX, and AKT activation. We carried out Boyden chamber and wound healing assays to assess the influence of MDMX and CXCL12 on the cells’ migration capacity. Results: The addition of the CXCL12 chemokine to the medium increased the CXCR4 cellular protein level and activated the PI3K/AKT signaling pathway. Surprisingly, we observed that the addition of CXCL12 mediated the upregulation of MDM2 and MDMX at the protein, but not at the mRNA, level. A reduction in MDMX, but not MDM2, diminished both the CXCL12-mediated CXCR4 and MDM2 upregulation. Moreover, a reduction in both MDM2 and MDMX hindered the ability of the added CXCL12 to promote Boyden chamber-assessed cell migration. The upregulation of MDMX by CXCL12 was mediated, at least in part, by a step upstream of the proteasome pathway because CXCL12 did not increase protein stability after cycloheximide treatment, or when the proteasome pathway was blocked. Conclusions: These data demonstrate a positive feed-forward activation loop between the CXCL12/CXCR4 pathway and the MDM2/MDMX pathway. As such, MDMX expression in tumor cells may be upregulated in the primary tumor microenvironment by CXCL12 expression. Furthermore, CXCL12/CXCR4 metastatic signaling may be upregulated by the MDM2/MDMX axis. Our findings highlight a novel positive regulatory loop between CXCL12/CXCR4 signaling and MDMX to promote metastasis. Full article
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<p>Chemokine CXCL12 addition to cell culture increases CXCR4, activates PI3K/AKT, and MDMX and MDM2 protein levels. (<b>A</b>) Panels show immunoblot analysis for MDMX, MDM2, CXCR4, and phospho-AKT S473, total AKT, and actin in MDA-MB-231.mlp cells after treatment for up to 60 min with CXCL12 at 50 ng/mL for 0, 1, 5, 10, 20, and 60 min, lanes 1–6. Total AKT and actin were used as loading controls. The proteins were derived from the same samples run on different gels/membranes at the same time and their molecular weights are shown. (<b>B</b>) Untreated cells and those following the 20 min treatments were compared for the MDMX and MDM2 protein levels evaluated (using actin as a normalizer control for loading) using ImageJ and graphs were created with Prism 10 software, with the untreated value set as 1 and the ratio reported for CXCL12-treated samples (20 min) used to report the fold change. (<b>C</b>) Untreated and 20 min treatments were compared for CXCR4 and phospho-AKT S473 protein levels quantified via ImageJ relative to total AKT as a loading control with the untreated value set as 1 and the ratio reported for CXCL12-treated samples (20 min) used to report the fold change. Images were analyzed using ImageJ and graphs were created with Prism software. Error bars represent SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, NS = non-significant (N = 4 biological replicates).</p>
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<p>Knockdown of MDMX in MDA-MB-231 cells disrupts CXCL12 signaling to upregulate CXCR4, MDM2, and AKT activation. MDA-MB-231.mlp, MDA-MB-231.mlp.sh<span class="html-italic">mdm2</span>, and MDA-MB-231.mlp.sh<span class="html-italic">mdmx</span> cells treated in cell culture with the addition of CXCL12 at a final concentration of 50 ng/mL in cell culture for up to 60 min. (<b>A</b>) CXCR4 and phospho-AKT S473 protein levels were semi-quantified at 20 min via ImageJ relative to actin as a loading control. Protein level analysis was carried out using Western blot results using Image J and Prism software and densitometries were measured as a ratio relative to the actin band density. Fold change was calculated relative to protein levels in the untreated 231.mlp vector control cells. Error bars represent SD. * <span class="html-italic">p</span> &lt; 0.05, NS = non-significant (N = 3 biological replicates). (<b>B</b>) Immunoblot analysis for CXCR4, phospho-AKT, MDMX, and MDM2 protein levels in MDA-MB-231 or knockdown cells after the addition of CXCL12. (<b>C</b>) MDMX and MDM2 protein levels were semi-quantified at 20 min post addition of CXCL12 to the cell culture. Protein levels were normalized to actin and fold change was calculated relative to untreated 231.mlp vector control cells. MDM2 or MDMX knockdown were confirmed for each respective cell line. Protein level analysis was carried out from Western blot results using Image J and Prism software and expression scores were normalized to actin. Error bars represent SD. * <span class="html-italic">p</span> &lt; 0.05, NS = non-significant (N = 3 biological replicates).</p>
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<p>CXCL12 does not enhance chemotaxis in MDM2- or MDMX-knockdown MDA-MB-231 cells. (<b>A</b>) Representative images of crystal violet-stained cells of chemotaxis assay membrane inserts. A total of 50,000 MDA-MB-231 cells were loaded into the upper chamber in media (final vol: 200 µL). Migration was initiated by adding 500 µL of medium to the lower chamber with or without CXCL12 at a final concentration of 50 ng/mL for 24 h. Cells were incubated for 24 h at 37 degree Celsius in a 5% CO<sub>2</sub> incubator. Insert was stained with crystal violet and washed with Millipore water. Representative images of stained cells on insert shown by imaging via microscopy. (<b>B</b>) Graph of % wound closure at the 24 h time point. Error bars represent SD. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, NS = nonsignificant. The <span class="html-italic">p</span> values were calculated using two-tailed unpaired <span class="html-italic">t</span> tests on Prism software.</p>
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<p>MDA-MB-231.mlp.CTC lines compared to MDA-MB-231.<span class="html-italic">shmdm2</span>.CTC and MDA-MB-231.<span class="html-italic">shmdmx</span>.CTC maintain increased migratory compacity but have reduced response to CXCL12. (<b>A</b>) Immunoblot of whole cell lysates from MDA-MB-231.mlp, MDA-MB-231.<span class="html-italic">shmdm2,</span> and MDA-MB-231.<span class="html-italic">shmdmx</span> (lanes 1–3) and MDA-MB-231.mlp.CTC A and B (lanes 4 and 5), MDA-MB-231.<span class="html-italic">shmdm2</span>.CTC (lane 6), and MDA-MB-231.<span class="html-italic">shmdmx</span>.CTC (lane 7) cell lines probed for MDMX (top) and MDM2 (middle). The loading control was actin (bottom) (<b>B</b>) Representative images of MDA-MB-231-derived CTC lines in wound healing assay. Black lines denote the borders of the scratch made. (<b>C</b>) Graph of % wound closure at 12 h time point. Error bars represent SD. *** <span class="html-italic">p</span> &lt; 0.001, NS = nonsignificant. The <span class="html-italic">p</span> value was calculated using two-tailed unpaired <span class="html-italic">t</span> tests on Prism software (<b>D</b>) Immunoblot of whole cell lysates from MDA-MB-231.mlp.CTC lines treated with CXCL12 at a final concentration of 50 ng/mL for 30 and 60 min. (<b>E</b>) MDMX and MDM2 protein expression was compared using ImageJ quantitation relative to actin, respectively, as a loading control.</p>
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<p>CXCL12 addition does not increase MDMX protein half-life following cycloheximide or MG132 treatment. (<b>A</b>) Immunoblot analysis of lysates from MDA-MB-231 cells treated with CXCL12 (50 ng/mL) for 30 min followed by cycloheximide (CHX) or DMSO for 40 or 80 min. Cells were harvested and lysed in CHAPS lysis buffer and subjected to immunoblotting to probe for MDM2 and MDMX. Actin was probed as a loading control. (<b>B</b>,<b>C</b>) Evaluation of Western blot band density was carried out using ImageJ and Prism software. Error bars represent SD. * <span class="html-italic">p</span> &lt; 0.05, NS = non-significant. (<b>D</b>) HCT116 p53-/- cells were transfected with pcDNA3-MDMX for 24 h and then treated with CXCL12 (50 ng/mL) for 30 min followed by MG132 or DMSO for 40 or 80 min. Cells were harvested and lysed in CHAPS lysis buffer and subjected to immunoblotting to probe for MDM2, MDMX, and Ubiquitin. Actin was probed as a loading control. (<b>E</b>,<b>F</b>) Evaluation of Western blot band density was carried out using ImageJ and Prism 10 software. Error bars represent SD. * <span class="html-italic">p</span> &lt; 0.05, NS = non-significant.</p>
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<p>A model of CXCL12/CXCR4/AKT signaling to the MDMX/MDM2 axis. CXCL12/CXCR4/AKT signaling works to upregulate MDMX in the primary tumor in cooperation with the TME and results in a feed forward activation loop. This promotes intravasation of the cancer cells into the blood stream and the promotion of CTCs. The CTCs are then able to survive but have a reduced CXCL12 feed-forward loop with MDMX and MDM2 which we posit is re-established when cells extravasate into CXCL12-rich environments to form metastasis.</p>
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13 pages, 2748 KiB  
Article
The Differential Complement, Fc and Chemokine Receptor Expression of B Cells in IgG4-Related Pancreatobiliary Disease and Primary Sclerosing Cholangitis and Its Relevance for Targeting B Cell Pathways in Disease
by Tamsin Cargill, Eleanor Barnes, Theo Rispens and Emma L. Culver
Biomedicines 2024, 12(12), 2839; https://doi.org/10.3390/biomedicines12122839 - 13 Dec 2024
Viewed by 478
Abstract
Background: Immune-mediated liver and biliary conditions, such as IgG4-related pancreatobiliary disease (IgG4-PB) and a subset of primary sclerosing cholangitis (PSC- high(h)IgG4), exhibit increased IgG4 levels in the blood. The relative expression of IgG4+ and IgG1+ B cells in the blood and the expression [...] Read more.
Background: Immune-mediated liver and biliary conditions, such as IgG4-related pancreatobiliary disease (IgG4-PB) and a subset of primary sclerosing cholangitis (PSC- high(h)IgG4), exhibit increased IgG4 levels in the blood. The relative expression of IgG4+ and IgG1+ B cells in the blood and the expression of complement and Fc receptors on these IgG1+ and IgG4+ B cells in IgG4-PB and PSC have not been previously described. We hypothesised that the patterns of expression of these cells and their receptors would differ, are relevant to disease pathogenesis and may represent therapeutic targets. Methods: CD19+ B cells were sorted from blood collected from patients with IgG4-PB, PSC-high(h)IgG4 and healthy volunteers. Cells were stained with fluorescent labelled antibodies specific to IgG1, IgG4, complement receptors (CR1 and CR2), Fc receptors (FcεRII and FcγRIIb) and chemokine receptors (CXCR3, CXCR4, CXCR5) and were analysed by flow cytometry. Findings: IgG4-PB, compared to healthy volunteers, showed decreased CR2 expression on IgG1+ B cells (MFI 416 (275–552) vs. 865 (515–3631), p = 0.04) and IgG4+ B cells (MFI 337 (231–353) vs. 571 (398–2521), p = 0.03). IgG4-PB, compared to healthy volunteers, showed increased FcεRII expression on IgG4+ B cells (MFI 296 (225–617) vs. 100 (92–138), p = 0.0145) and decreased FcγRIIb expression on IgG1+ B cells (134 (72–161) vs. 234 (175–291), p = 0.0262). FcγRIIb expression was also decreased in IgG1+ B cells in patients with PSC-hIgG4 compared to healthy volunteers. Conclusions: This exploratory study indicates that in IgG4-PB, B cells have decreased CR2 and FcγRIIb expression and increased FcεRII expression, suggesting altered sensitivity to complement, IgG-mediated inhibition and sensitisation by IgE, which may promote the relative expansion of IgG4+ B cells in this disease. Full article
(This article belongs to the Special Issue Cholestatic Liver Diseases: From the Bench to Bedside)
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<p>Expression of complement receptors 1 and 2 on ex vivo Total B cells from healthy volunteers compared with patients with PSC-high IgG4 (PSC-hIgG4) and patients with IgG4-pancreatobiliary disease (IgG4-PB) measured by flow cytometry. Median fluorescence intensity (MFI) of (<b>A</b>) complement receptor 1 (CR1, CD35) (<b>B</b>) and complement receptor 2 (CR2, CD21) on total B cells and total number of B cells positive for (<b>C</b>) CR1 and (<b>D</b>) CR2. A Kruskal–Wallis test with Dunn’s multiple comparisons is used to compare two or more unpaired groups. Median and interquartile ranges are shown. ns = not significant.</p>
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<p>Expression of complement receptors 1 and 2 on ex vivo IgG1+ and IgG4+ B cells from healthy volunteers compared with patients with PSC-high IgG4 (PSC-hIgG4) and patients with IgG4-related pancreatobiliary disease (IgG4-PB) measured by flow cytometry. (<b>A</b>) Gating strategy to identify IgG1+ and IgG4+ B cells with each dot representing a single cell (colored blue to red, indicating increasing intensity). Populations gated from left to right; lymphocyte population by forward scatter area (FSC-A) and side scatter area (SSC-A), singlet cells population by FSC-A and forward scatter-height (FSC-H), live CD20 B cell population by DAPI negative CD20 positive, IgG1+ and IgG4+ B cell population by IgG1 (upper box) or IgG4 (lower box) positivity. Median fluorescence intensity (MFI) of complement receptor 1 (CR1, CD35) on (<b>B</b>) IgG1+ compared to IgG4+ B cells (<b>C</b>) IgG1+ B cells and (<b>D</b>) IgG4+ B cells and complement receptor 2 (CR2, CD21) on (<b>E</b>) IgG1+ compared to IgG4+ B cells, (<b>F</b>) IgG1+ B cells and (<b>G</b>) IgG4+ B cells. A Kruskal–Wallis test with Dunn’s multiple comparisons is used to compare two or more unpaired groups. Median and interquartile ranges are shown. * <span class="html-italic">p</span> &lt; 0.05, ns = not significant.</p>
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<p>Expression of complement receptors 1 and 2 on ex vivo IgG1+ and IgG4+ B cells from healthy volunteers compared with patients with PSC-high IgG4 (PSC-hIgG4) and patients with IgG4-related pancreatobiliary disease (IgG4-PB) measured by flow cytometry. (<b>A</b>) Gating strategy to identify IgG1+ and IgG4+ B cells with each dot representing a single cell (colored blue to red, indicating increasing intensity). Populations gated from left to right; lymphocyte population by forward scatter area (FSC-A) and side scatter area (SSC-A), singlet cells population by FSC-A and forward scatter-height (FSC-H), live CD20 B cell population by DAPI negative CD20 positive, IgG1+ and IgG4+ B cell population by IgG1 (upper box) or IgG4 (lower box) positivity. Median fluorescence intensity (MFI) of complement receptor 1 (CR1, CD35) on (<b>B</b>) IgG1+ compared to IgG4+ B cells (<b>C</b>) IgG1+ B cells and (<b>D</b>) IgG4+ B cells and complement receptor 2 (CR2, CD21) on (<b>E</b>) IgG1+ compared to IgG4+ B cells, (<b>F</b>) IgG1+ B cells and (<b>G</b>) IgG4+ B cells. A Kruskal–Wallis test with Dunn’s multiple comparisons is used to compare two or more unpaired groups. Median and interquartile ranges are shown. * <span class="html-italic">p</span> &lt; 0.05, ns = not significant.</p>
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<p>Expression of Fc receptors on ex vivo Total B cells from healthy volunteers compared with patients with PSC-high IgG4 (PSC-hIgG4) and patients with IgG4-related pancreatobiliary disease (IgG4-PB) measured by flow cytometry. Median fluorescence intensity (MFI) of (<b>A</b>) Fc epsilon receptor 2 (FcεRII, CD23) (<b>B</b>) and Fc gamma receptor 2b (FcγRIIb, CD32) on total B cells and the total number of B cells positive for (<b>C</b>) FcεRII and (<b>D</b>) FcγRIIb. The Kruskal–Wallis test with Dunn’s multiple comparisons is used to compare two or more unpaired groups. Median and interquartile ranges are shown. ** <span class="html-italic">p</span> &lt; 0.01, ns = not significant.</p>
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<p>Expression of Fc receptors on ex vivo IgG1+ and IgG4+ B cells from healthy volunteers compared with patients with PSC-high IgG4 (PSC-hIgG4) and patients with IgG4-related pancreatobiliary disease (IgG4-PB) measured by flow cytometry. Median fluorescence intensity (MFI) of Fc epsilon receptor 2 (FcεRII, CD23) on (<b>A</b>) IgG1+ compared to IgG4+ B cells, (<b>B</b>) IgG1+ B cells and (<b>C</b>) IgG4+ B cells and Fc gamma receptor 2b (FcγRIIb, CD32) on (<b>D</b>) IgG1+ compared to IgG4+ B cells, (<b>E</b>) IgG1+ B cells and (<b>F</b>) IgG4+ B cells. A Kruskal–Wallis test with Dunn’s multiple comparisons is used to compare two or more unpaired groups. Median and interquartile ranges are shown. * <span class="html-italic">p</span> &lt; 0.05, ns = not significant.</p>
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<p>Expression of Chemokine receptors on ex vivo B cells from healthy volunteers compared with patients with IgG4-related pancreatobiliary disease (IgG4-PB) pre or post-steroid. Median fluorescence intensity (MFI) of (<b>A</b>) CXCR4, (<b>B</b>) CXCR3, (<b>C</b>) CXCR5, (<b>D</b>) CCR5, (<b>E</b>) CCR6 and (<b>F</b>) CCR7. A Kruskal–Wallis test with Dunn’s multiple comparisons is used to compare two or more unpaired groups. Median and interquartile ranges are shown. * <span class="html-italic">p</span> &lt; 0.05, ns = not significant.</p>
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49 pages, 2915 KiB  
Review
The Chemokine System as a Key Regulator of Pulmonary Fibrosis: Converging Pathways in Human Idiopathic Pulmonary Fibrosis (IPF) and the Bleomycin-Induced Lung Fibrosis Model in Mice
by Remo Castro Russo and Bernhard Ryffel
Cells 2024, 13(24), 2058; https://doi.org/10.3390/cells13242058 - 12 Dec 2024
Viewed by 729
Abstract
Idiopathic pulmonary fibrosis (IPF) is a chronic and lethal interstitial lung disease (ILD) of unknown origin, characterized by limited treatment efficacy and a fibroproliferative nature. It is marked by excessive extracellular matrix deposition in the pulmonary parenchyma, leading to progressive lung volume decline [...] Read more.
Idiopathic pulmonary fibrosis (IPF) is a chronic and lethal interstitial lung disease (ILD) of unknown origin, characterized by limited treatment efficacy and a fibroproliferative nature. It is marked by excessive extracellular matrix deposition in the pulmonary parenchyma, leading to progressive lung volume decline and impaired gas exchange. The chemokine system, a network of proteins involved in cellular communication with diverse biological functions, plays a crucial role in various respiratory diseases. Chemokine receptors trigger the activation, proliferation, and migration of lung-resident cells, including pneumocytes, endothelial cells, alveolar macrophages, and fibroblasts. Around 50 chemokines can potentially interact with 20 receptors, expressed by both leukocytes and non-leukocytes such as tissue parenchyma cells, contributing to processes such as leukocyte mobilization from the bone marrow, recirculation through lymphoid organs, and tissue influx during inflammation or immune response. This narrative review explores the complexity of the chemokine system in the context of IPF and the bleomycin-induced lung fibrosis mouse model. The goal is to identify specific chemokines and receptors as potential therapeutic targets. Recent progress in understanding the role of the chemokine system during IPF, using experimental models and molecular diagnosis, underscores the complex nature of this system in the context of the disease. Despite advances in experimental models and molecular diagnostics, discovering an effective therapy for IPF remains a significant challenge in both medicine and pharmacology. This work delves into microarray results from lung samples of IPF patients and murine samples at different stages of bleomycin-induced pulmonary fibrosis. By discussing common pathways identified in both IPF and the experimental model, we aim to shed light on potential targets for therapeutic intervention. Dysregulation caused by abnormal chemokine levels observed in IPF lungs may activate multiple targets, suggesting that chemokine signaling plays a central role in maintaining or perpetuating lung fibrogenesis. The highlighted chemokine axes (CCL8-CCR2, CCL19/CCL21-CCR7, CXCL9-CXCR3, CCL3/CCL4/CCL5-CCR5, and CCL20-CCR6) present promising opportunities for advancing IPF treatment research and uncovering new pharmacological targets within the chemokine system. Full article
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<p>Chemokine receptor and atypical chemokine receptor (ACKR) activation and signaling. Chemokines bind to classical chemokine receptors, which are G protein-coupled receptors (GPCRs) expressed on cell surfaces, sensing the presence of chemokines, and initiating critical intracellular signaling cascades during inflammation. Upon activation, GPCRs dissociate G protein subunits Gα and Gβγ, triggering key pathways of Phospholipase C (PLC) and Phosphoinositide 3-Kinase (PI3K). PLC cleaves phosphatidylinositol 4,5-bisphosphate (PIP2) into Inositol triphosphate (IP3), which promotes calcium release from intracellular stores; and Diacylglycerol (DAG) activates protein kinase C (PKC), influencing migration and gene expression. PI3K activation by chemokine receptor signaling, converts PIP2 to phosphatidylinositol 3,4,5-trisphosphate (PIP3), activating the PI3K/AKT pathway, crucial for survival and motility. Additionally, GPCRs engage the JAK/STAT and Ras/Raf/ERK pathways, driving proliferation, differentiation, and adhesion. Phosphorylation by GPCR kinases (GRKs) recruits β-arrestin, leading to receptor internalization and activation of ERK and MAPK pathways. These cascades activate transcription factors such as STAT, FOXO, AP-1, and NF-κB, promoting the expression of inflammatory genes. This orchestrates cellular activation, adhesion, and migration, central to inflammation and immune responses. Atypical chemokine receptors (ACKRs) modulate chemokine activity by binding chemokines and functioning as scavengers. Upon ligand binding, ACKRs undergo phosphorylation by GPCR kinases (GRKs), leading to β-arrestin recruitment. This process facilitates the internalization of chemokines and their subsequent lysosomal degradation, effectively reducing extracellular chemokine levels. Following ligand degradation, ACKRs are recycled back to the cell surface through intracellular trafficking mechanisms, enabling them to continue their regulatory functions. Additionally, β-arrestin recruitment activates MAPK-related-signaling pathways, particularly ERK1/2 and AKT, which are critical for promoting cell survival and proliferation. By scavenging chemokines and preventing their interaction with classical chemokine receptors, ACKRs play a key role in fine-tuning extracellular chemokine concentrations. This mechanism diminishes chemokine signaling through traditional receptors, thereby regulating immune responses and preventing excessive inflammation. Red arrows illustrate the cellular processes initiated by signaling pathways activated via chemokine receptors. Black arrows denote the signaling pathways induced by the G protein subunits Gα and Gβγ. Orange arrows indicate the signaling pathways activated through β-arrestin in chemokine receptors.</p>
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<p>Cell types, chemokine and chemokine receptor expression, chemokine-receptor axis, and activities in idiopathic pulmonary fibrosis. The complexity of the chemokine system and its functions are illustrated based on the reviewed literature.</p>
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<p>The chemokine system pathways in the context of pulmonary fibrosis: Chemokine and receptors up-regulated in IPF lung tissues by microarray analysis GEO database: (GSE32537 and GSE53845) and up-regulated in RNAseq analysis of IPF lung tissue (GEO database: GSE99621) are converging chemokine pathways in human IPF samples (<b>A</b>). Chemokine and receptors were grouped by function in IPF—Inflammation, Angiogenesis, and Fibrosis (<b>B</b>), note that some chemokines have more than one function that contributes to fibrogenesis. Chemokine and receptors up-regulated in lung tissues from bleomycin-induced pulmonary fibrosis by microarray analysis (GEO database: GSE37635) and expressed according to the developmental stages (week 1, 2, 3, 4, and 5) of pathology progression during the experimental pulmonary fibrosis in mice (<b>C</b>). Common chemokine signatures up-regulated in IPF lung tissues by microarray GEO database: GSE32537, GEO database: GSE53845, and confirmed by RNAseq analysis of IPF lung tissue (GEO database: GSE99621) and bleomycin-induced pulmonary fibrosis in mice microarray (GEO database: GSE37635) analyzed by Phantasus (<b>D</b>). There are converging chemokine pathways up-regulated in both human IPF and bleomycin-induced pulmonary fibrosis in mice by lung tissue microarray analysis and RNAseq.</p>
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15 pages, 2833 KiB  
Article
Anti-Inflammatory Potential of 3-Hydroxy-β-Ionone from Moringa oleifera: Decreased Transendothelial Migration of Monocytes Through an Inflamed Human Endothelial Cell Monolayer by Inhibiting the IκB-α/NF-κB Signaling Pathway
by Thitiya Luetragoon, Krai Daowtak, Yordhathai Thongsri, Pachuen Potup, Philip C. Calder and Kanchana Usuwanthim
Molecules 2024, 29(24), 5873; https://doi.org/10.3390/molecules29245873 - 12 Dec 2024
Viewed by 627
Abstract
Moringa leaves provide numerous health benefits due to their anti-inflammatory properties. This study presents the first evidence that endothelial cell inflammation can potentially be ameliorated by moringa leaf extract. Here, we established an experimental human blood vessel cell model of inflammation using EA.hy926 [...] Read more.
Moringa leaves provide numerous health benefits due to their anti-inflammatory properties. This study presents the first evidence that endothelial cell inflammation can potentially be ameliorated by moringa leaf extract. Here, we established an experimental human blood vessel cell model of inflammation using EA.hy926 cells. TNF-α was added after pre-treating the cells with crude leaf extract from Moringa oleifera Lam., a constituent fraction of the extract, and the bioactive component 3-hydroxy-β-ionone. The extract and the active ingredient significantly decreased the levels of pro-inflammatory mediators such as IL-6, IL-8, and MCP-1; decreased IκB-α and NF-κB p65 phosphorylation; and decreased the expression of VCAM-1, PECAM-1, and ICAM-1, three significant adhesion molecules. Furthermore, they attenuated THP-1 monocyte adhesion to the EA.hy926 monolayer and decreased monocyte transmigration across the monolayer. These findings suggest that 3-hydroxy-β-ionone and moringa leaf extract have anti-inflammatory properties and can be used as therapeutic agents to reduce the progression of diseases involving the inflamed endothelium by decreasing the production of inflammatory cytokines, chemokines, and adhesion molecules. This is promising for conditions such as atherosclerosis and neuroinflammation. Full article
(This article belongs to the Special Issue Bioactivity of Natural Compounds: From Plants to Humans)
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Graphical abstract

Graphical abstract
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<p>Effect of MO leaf extract, fraction 6, and 3-HBI on the viability of EA.hy926 cells determined using an MTT assay. (<b>a</b>) Sigmoidal curve fitting analysis of EA.hy926 cells after treatment for 24 h with MO extract, fraction 6, and 3-HBI. Black dots represent the percentage of cell viability at different doses of MO extract, Fr.6, and 3-HBI, displayed on a logarithmic scale. (<b>b</b>) followed by incubation with TNF-α (1 ng/mL) for 24 h. (<b>c</b>) Viability of EA.hy926 cells after incubation for 24 h with DMEM (control) or crude MO leaf extract (75, 100 µg/mL), fraction 6 (75, 100 µg/mL), and 3-HBI (50, 75 µg/mL), followed by incubation with or without TNF-α (1 ng/mL) for 24 h. The data are presented as the means ±SEM (<span class="html-italic">n</span> = 3).</p>
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<p>Effects of MO leaf extract, fraction 6, and 3-HBI on the levels of pro-inflammatory mediators in the supernatants of TNF-α-stimulated EA.hy926 endothelial cells. Concentrations of (<b>a</b>) IL-6, (<b>b</b>) IL-8, and (<b>c</b>) MCP-1 were measured in supernatants of EA.hy926 cells incubated for 24 h with DMEM (control; white bar), DMEM followed by 24 h of TNF-α stimulation (red bar), or with MO leaf extract, fraction 6, or 3-HBI followed by 24 h of TNF-α stimulation (gray bars). The data are presented as the means ±SEM (<span class="html-italic">n</span> = 3). # <span class="html-italic">p</span> &lt; 0.001 compared to the control (no TNF-α). *** Statistically significant (<span class="html-italic">p</span> &lt; 0.001) compared to TNF-α stimulation alone.</p>
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<p>Flow cytometry analysis of adhesion molecules on the surface of EA.hy926 cells. (<b>a</b>) Histogram surface marker analysis, where the brown histograms represent the isotope control, while the light gray histogram indicates ICAM-1 (CD54) expression on untreated cells and cells treated with MO extract (green), Fr.6 (blue), and 3-HBI (pink). Bar graphs showing the percentages of (<b>b</b>) ICAM-1- and (<b>d</b>) PECAM-1-positive cells. (<b>c</b>) Dot plots representing endothelial cells gates within PECAM-1 (CD31)-positive cells. Bar graphs of the mean fluorescence intensity (MFI) of (<b>e</b>) PECAM-1 and (<b>f</b>) ICAM-1 expression. The data are presented as the means ±SEM (<span class="html-italic">n</span> = 3). # <span class="html-italic">p</span> &lt; 0.001 compared to the isotype control. * Statistically significant (<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 compared to TNF-α stimulation alone.</p>
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<p>Adhesion of THP-1 monocytes to EA.hy926 cells incubated for 24 h with DMEM (control) or treatment with MO extract, fraction 6, and 3-HBI followed by stimulation with TNF-α (1 ng/mL) for 6 h and 1 h co-culture with calcein-labeled THP-1 cells. (<b>a</b>) Attached THP-1 cells were visualized by a Nikon H600l fluorescence microscope. (<b>b</b>) Cell adhesion was detected using a fluorescence plate reader at 480 nm/520 nm. THP-1 monocyte adhesion was measured as a percentage of TNF-α stimulated cells (TNF-α). The data are presented as the means ±SEM (<span class="html-italic">n</span> = 3). # Statistically significant (<span class="html-italic">p</span> &lt; 0.001) compared to the control. *** Statistically significant (<span class="html-italic">p</span> &lt; 0.001) compared to TNF-α.</p>
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<p>Analysis of THP-1 cell transmigration through an endothelial cell monolayer. EA.hy926 cells were cultured in an insert well for 72 h until the endothelial cells formed a monolayer. (<b>a</b>,<b>b</b>) Cells were incubated with DMEM (control) or with MO leaf extract, fraction 6, or 3-HBI for 24 h followed by stimulation with TNF-α (1 ng/mL) for 6 h and co-culture with calcein-AM-labeled THP-1 cells for 12 h at 37 °C. FMLP: N-Formylmethionyl-leucyl-phenylalanine. (<b>c</b>) The relative fluorescence unit (RFU) of the medium under the insert was measured using a fluorescence plate reader at Ex/Em = 480/520 nm in the end-point mode. The data are presented as the means ±SEM (<span class="html-italic">n</span> = 3). # <span class="html-italic">p</span> &lt; 0.001 compared to the control. *** Statistically significant (<span class="html-italic">p</span> &lt; 0.001) compared to TNF-α stimulation.</p>
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<p>Effects of crude MO leaf extract, fraction 6, and 3-HBI on protein expression in EA.hy926 cells. (<b>a</b>) Band intensity of total protein levels of ICAM-1, VCAM-1, NF-κB P65, p-NF-κB P65, IkB-α, and p-IκB-α. β-actin was used as loading control. (<b>b</b>) Bar graphs represent the relative intensity of protein expression in control and treatment groups. (<b>c</b>) The ratio of phosphorylated NF-κB P65 and IκB-α to total protein levels of NF-κB P65 and IκB-α. Endothelial cells were exposed to crude MO extract (75 µg/mL), fraction 6 (75 µg/mL), and 3-HBI (50 µg/mL) for 24 h followed by stimulation with TNF-α (1 ng/mL) for 6 h. The cell extracts were subjected to 10–12% SDS-PAGE prior to Western blot analysis. β-actin was used as an internal control. The data are presented as the means ± SEM (<span class="html-italic">n</span> = 3). # <span class="html-italic">p</span>&lt; 0.001 compared to the control. Statistically significant compared to TNF-α stimulation alone: *<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. All original blots are presented in <a href="#app1-molecules-29-05873" class="html-app">Supplementary Figures S4–S11</a>.</p>
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17 pages, 3548 KiB  
Article
CXCR1 Expression in MDA-PCa-2b Cell Upregulates ITM2A to Inhibit Tumor Growth
by Timothy O. Adekoya, Nikia Smith, Parag Kothari, Monique A. Dacanay, Yahui Li and Ricardo M. Richardson
Cancers 2024, 16(24), 4138; https://doi.org/10.3390/cancers16244138 - 11 Dec 2024
Viewed by 443
Abstract
Background: Chemokines, along with their receptors, exert critical roles in tumor development and progression. In prostate cancer (PCa), interleukin-8 (IL-8/CXCL8) was shown to enhance angiogenesis, proliferation, and metastasis. CXCL8 activates two receptors, CXCR1 and CXCR2. While CXCR2 expression was shown to promote PCa [...] Read more.
Background: Chemokines, along with their receptors, exert critical roles in tumor development and progression. In prostate cancer (PCa), interleukin-8 (IL-8/CXCL8) was shown to enhance angiogenesis, proliferation, and metastasis. CXCL8 activates two receptors, CXCR1 and CXCR2. While CXCR2 expression was shown to promote PCa growth and metastasis, the role of CXCR1 remains unclear. Methods: In this study, we stably expressed CXCR1 and, as control, CXCR2 in the androgen-dependent PCa cell line MDA-PCa-2b to evaluate the effect of CXCR1 in tumor development. Results: MDA-PCa-2b-CXCR1 cells showed decreased cell migration, protein kinase-B (AKT) activation, prostate-specific antigen (PSA) expression, cell proliferation, and tumor development in nude mice, relative to MDA-PCa-2b-Vec and MDA-PCa-2b-CXCR2 cells. MDA-PCa-2b-CXCR1 cells also displayed a significant transition to mesenchymal phenotypes as characterized by decreased E-cadherin expression and a corresponding increased level of N-cadherin and vimentin expression. RNA-seq and Western blot analysis revealed a significant increase in the tumor suppressor integral membrane protein 2A (ITM2A) expression in MDA-PCa-2b-CXCR1 compared to control cells. In prostate adenocarcinoma tissue, ITM2A expression was also shown to be downregulated relative to a normal prostate. Interestingly, the overexpression of ITM2A in MDA-PCa-2b cells (MDA-PCa-2b-ITM2A-GFP) inhibited tumor growth similar to that of MDA-PCa-2b-CXCR1. Conclusions: Taken together, the data suggest that CXCR1 expression in MDA-PCa-2b cells may upregulate ITM2A to abrogate tumor development. Full article
(This article belongs to the Section Molecular Cancer Biology)
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Figure 1
<p>Expression and characterization of MDA-PCa-2b cells stably expressing CXCR1 and CXCR2. (<b>A</b>) MDA-PCa-2b cells were transfected with pcDNA3.1-C-(k)DYK plasmid containing CXCR1 (MDA-PCa-2b-CXCR1) or CXCR2 (MDA-PCa-2b-CXCR2) constructs or vector alone (MDA-PCa-2b-Vec). G418-resistant cells were sorted using receptor-specific antibodies. Depicted are representative FACS analyses of at least 5 experiments. (<b>B</b>) Western blot analysis of MDA-PCa-2b cells expressing empty vector (lane 1), vector containing CXCR1 (lane 2), or CXCR2 (lane 3). (<b>C</b>) Representative image of a single clone morphology following clonogenic assay and transfection of cells with GFP protein. (<b>D</b>) For the chemotaxis assay, the dose response of IL-8-induced cell migration was assessed using the NeuroProbe chemotaxis plate. Graphical quantification of the chemotaxis index at 0, 10, 100, and 200 nM of IL-8 are shown. Results are representative of two independent experiments performed in quadruplets. (<b>E</b>) Representative Western blotting image and graphical quantification of average band density for phospho-AKT and total AKT following IL-8 induced AKT phosphorylation. * <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>Effects of CXCR1 and CXCR2 overexpression on AR, PSA, and EMT marker expression in MDA-PCa-2b cells. (<b>A</b>) MDA-PCa-2b-Vec, MDA-PCa-2b-CXCR1, and MDA-PCa-2b-CXCR2 cell lysates were assayed by Western blotting for AR, PSA, and GAPDH using specific antibodies. (<b>B</b>,<b>C</b>) The graphical quantification of band density analysis for AR (<b>B</b>) and PSA (<b>C</b>), relative to GAPDH. (<b>D</b>) Cell lysates were assayed by Western blotting for E-cadherin, N-cadherin, and vimentin and GAPDH expression using specific antibodies. Graphical quantification for E-cadherin (<b>E</b>), N-cadherin (<b>F</b>), and vimentin (<b>G</b>) expression, relative to GAPDH. Data were obtained from at least three independent experiments. * <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>Effect of CXCR1 and CXCR2 overexpression on in-vitro and in-vivo growth of MDA-PCa-2b cells. (<b>A</b>) In vitro cell proliferation rates for MDA-PCa-2b-CXCR1, MDA-PCa-2b-CXCR2, or MDA-PCa-2b-Vec cells were determined using the MTT assay, as described in <a href="#sec2-cancers-16-04138" class="html-sec">Section 2</a>. Results are expressed as absorbance at 570 nm. The data are representative of one of three independent experiments. (<b>B</b>–<b>D</b>) For tumor xenografts, cells (5 × 10<sup>6</sup> cells) were injected subcutaneously into 6–8-week-old nude mice. Tumor growth was monitored weekly until the mice were euthanized, and the tumor weight was determined as described in <a href="#sec2-cancers-16-04138" class="html-sec">Section 2</a>. Shown are the representative images of harvested tumors (<b>B</b>), tumor volume measured over time (<b>C</b>), and the tumor weight of mice [n = at least 7 mice per group] (<b>D</b>). Results shown are representative of three independent experiments. * <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>Effect of CXCR1 and CXCR2 overexpression in LNCaP cells. LNCaP cells were transfected with pcDNA3.1-C-(k)DYK plasmid containing CXCR1 (LNCaP-CXCR1), CXCR2 (LNCaP-CXCR2), or vector alone (LNCaP-Vec). G418-resistant cells were sorted using receptor-specific antibodies. (<b>A</b>) Representative FACS analysis of 3 experiments. (<b>B</b>) Western blot analysis of LNCaP-Vec (lane 1), LNCaP-CXCR1 (lane 2), and LNCaP-CXCR2 (lane 3). (<b>C</b>) Representative Western blotting image and graphical quantification of average band density for phospho-AKT and total AKT following IL-8-induced AKT phosphorylation. (<b>D</b>) In vitro cell proliferation rates for LNCaP-CXCR1, LNCaP-CXCR2, and control LNCaP-Vec cells were determined using the MTT assay. The data shown are representative of two independent experiments. (<b>E</b>,<b>F</b>) For tumor xenografts, cells (5 × 10<sup>6</sup> cells) were injected subcutaneously into 6–8-week-old nude mice [n = 8 mice per group], and animals were monitored weekly. Animals were euthanized, and the tumor weight normalized by the weight of the mice was determined. Shown are representative tumors (<b>E</b>) and the average tumor weight (<b>F</b>) of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Analysis of chemokines and VEGF expression and immune cell infiltration in MDA-PCa-2b-CXCR1 and MDA-PCa-2b-CXCR2 tumor microenvironments. (<b>A</b>,<b>B</b>) Tumor lysates from MDA-PCa-2b-Vec, MDA-PCa-2b-CXCR1, and MDA-PCa-2b-CXCR2 xenografts were assayed for a variety of chemokines using the mouse chemokine array as described in <a href="#sec2-cancers-16-04138" class="html-sec">Section 2</a>. (<b>A</b>) Representative images and (<b>B</b>) the graphical quantification of chemokine band densities. The experiment was repeated twice. * <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>C</b>–<b>E</b>) Single-cell isolates from MDA-PCa-2b-Vec, MDA-PCa-2b-CXCR1, and MDA-PCa-2b-CXCR2 tumor xenografts were stained for different leukocyte subpopulations (CD45, LY6G, and NKp46) and were analyzed by a FACScan flow cytometer using CellQuest software. Graphical plots for CD45 (<b>C</b>), LY6G (<b>D</b>), and NKp46 (<b>E</b>) are shown. * <span class="html-italic">p</span> &lt; 0.05. (<b>F</b>) Lysates from different tumors were assayed by Western blot for VEGF expression. Representative Western blot image and graphical representation of band densities for VEGF relative to GAPDH are shown. (<b>G</b>–<b>I</b>) For tumor xenografts, cells (5 × 10<sup>6</sup> cells) were injected subcutaneously into 6–8-week-old NSG mice [n = 5 mice per group]. Tumor growth was monitored weekly until mice were euthanized, and the tumor weight was determined as described in <a href="#sec2-cancers-16-04138" class="html-sec">Section 2</a>. Shown are the representative images of harvested tumors (<b>G</b>), tumor volume measured over time (<b>H</b>), and the tumor weight (g) of mice (<b>I</b>). * <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>Analysis of chemokines and VEGF expression and immune cell infiltration in MDA-PCa-2b-CXCR1 and MDA-PCa-2b-CXCR2 tumor microenvironments. (<b>A</b>,<b>B</b>) Tumor lysates from MDA-PCa-2b-Vec, MDA-PCa-2b-CXCR1, and MDA-PCa-2b-CXCR2 xenografts were assayed for a variety of chemokines using the mouse chemokine array as described in <a href="#sec2-cancers-16-04138" class="html-sec">Section 2</a>. (<b>A</b>) Representative images and (<b>B</b>) the graphical quantification of chemokine band densities. The experiment was repeated twice. * <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>C</b>–<b>E</b>) Single-cell isolates from MDA-PCa-2b-Vec, MDA-PCa-2b-CXCR1, and MDA-PCa-2b-CXCR2 tumor xenografts were stained for different leukocyte subpopulations (CD45, LY6G, and NKp46) and were analyzed by a FACScan flow cytometer using CellQuest software. Graphical plots for CD45 (<b>C</b>), LY6G (<b>D</b>), and NKp46 (<b>E</b>) are shown. * <span class="html-italic">p</span> &lt; 0.05. (<b>F</b>) Lysates from different tumors were assayed by Western blot for VEGF expression. Representative Western blot image and graphical representation of band densities for VEGF relative to GAPDH are shown. (<b>G</b>–<b>I</b>) For tumor xenografts, cells (5 × 10<sup>6</sup> cells) were injected subcutaneously into 6–8-week-old NSG mice [n = 5 mice per group]. Tumor growth was monitored weekly until mice were euthanized, and the tumor weight was determined as described in <a href="#sec2-cancers-16-04138" class="html-sec">Section 2</a>. Shown are the representative images of harvested tumors (<b>G</b>), tumor volume measured over time (<b>H</b>), and the tumor weight (g) of mice (<b>I</b>). * <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>Overexpression of CXCR1 upregulates ITM2A expression. (<b>A</b>) Heat map showing the differential expression of genes in MDA-PCa-2b-Vec, MDA-PCa-2b-CXCR1, and MDA-PCa-2b-CXCR2. (<b>B</b>) Volcano plot showing the significantly expressed genes in MDA-PCa-2b-CXCR2 versus MDA-PCa-2b-Vec cells. (<b>C</b>) Volcano plot showing the significantly expressed genes in MDA-PCa-2b-CXCR1 versus MDA-PCa-2b-Vec cells. (<b>D</b>) GSEA analysis showing the downregulation of genes associated with cancer pathways in MDA-PCa-2b-CXCR1, when compared to MDA-PCa-2b-Vec cells. (<b>E</b>) Cell lysates were assayed by Western blot for ITM2A expression. Representative Western blot image and the graphical representation of band densities for ITM2A relative to GAPDH are shown. (<b>F</b>) ITM2A gene expression analysis of TCGA data between human prostate cancer and normal prostate tissues, extracted from UALCAN. Data are depicted as ITM2A transcript number per million. * <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>Effect of ITM2A overexpression on growth of MDA-PCa-2b cells. (<b>A</b>) Cells were transfected with pcDNA3.1-C-eGFP plasmid containing either human ITM2A or control vector, and G418-resistant clones (MDA-PCa-2b-ITM2A-GFP or MDA-PCa-2b-eGFP) were obtained. (<b>A</b>) Western blot analysis validating the overexpression of ITM2A in MDA-PCa-2b cells. (<b>B</b>) Representative tumors were harvested from nude mice, following the subcutaneous injection of MDA-PCa-2b-eGFP and MDA-PCa-2b-ITM2A-GFP cells [n = 5 mice per group] (<b>C</b>) The tumor volume was monitored and measured over the course of 8 weeks. (<b>D</b>) Graphical quantification of the average weight (g) of harvested tumors for MDA-PCa-2b-eGFP and MDA-PCa-2b-ITM2A-GFP cells. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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12 pages, 1866 KiB  
Article
Potential Serum HMGB1, HSP90, and S100A9 as Metastasis Predictive Biomarkers for Cancer Patients and Relevant Cytokines: A Pilot Study
by Worawat Songjang, Chatchai Nensat, Wittawat Jitpewngarm and Arunya Jiraviriyakul
Int. J. Mol. Sci. 2024, 25(24), 13232; https://doi.org/10.3390/ijms252413232 - 10 Dec 2024
Viewed by 602
Abstract
Metastatic cancer is still one of the leading causes of death worldwide despite significant advancements in diagnosis and treatment. Biomarkers are one of the most promising diagnostic tools that are used alongside traditional diagnostic tools in cancer patients. DAMPs are intracellular molecules released [...] Read more.
Metastatic cancer is still one of the leading causes of death worldwide despite significant advancements in diagnosis and treatment. Biomarkers are one of the most promising diagnostic tools that are used alongside traditional diagnostic tools in cancer patients. DAMPs are intracellular molecules released in response to cellular stress, tissue injury, and cell death. There have been shown to be associated with worsening prognosis among such patients, and some DAMPs could potentially be used as predictive biomarkers of metastatic status. The goal of this study is to investigate DAMP expression and the probability that certain DAMPs could be predictive biomarkers of the metastatic stage in various cancer types. Forty cancer patients at Naresuan University Hospital, Thailand, were enrolled. Then, an investigation of HSP90, HMGB1, S100A9, and ATP expression and cytokine/chemokine profiling in serum was performed using an immunological-based assay. We assessed the predictive biomarker candidates and the association between DAMP expression and cytokines/chemokines using an ROC curve analysis and a correlation regression analysis. The results showed that HSP90 has strong potential as a metastatic predictive biomarker, with a cutoff value of 25.46 ng/mL (AUC 0.8207, sensitivity 82.61%, specificity 75.00%, 95% CI 0.6860–0.9553). This was followed by HMGB1 and S100A9, which exhibited sensitivity of 82.61 and 65.22%, and specificity of 68.75 and 56.25%, respectively. Interestingly, the candidate DAMPs negatively correlate with various serum cytokines, for example, HMGB1 vs. IL-15 (slope 88.05, R 0.3297, p-value 0.005), HMGB1 vs. IFN-γ (slope 2.235, R 0.3052, p-value 0.0013) and HSP90 vs. IFN-γ (slope 0.0614, R 0.2187, p-value 0.008), suggesting that they are highly elevated in advanced metastatic tumors, which is possibly associated with the immunomodulation effect. We postulated that HSP90, HMGB1, and S100A9 have the potential to be predictive biomarkers for supporting tumor metastasis categorization using histopathology. Full article
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Figure 1
<p>Serum candidate DAMP profiling according to TNM staging. Candidate DAMPs’ concentration levels in serum were determined with ELISA kit. All data are shown as individual mean values, M (mean values) ± SEM (standard error deviation). A significance threshold of <span class="html-italic">p</span>-value &lt; 0.05 was considered as statistical significance. * <span class="html-italic">p</span>-value &lt; 0.05; ** <span class="html-italic">p</span>-value &lt; 0.01; *** <span class="html-italic">p</span>-value &lt; 0.001; ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>ROC analysis of candidate DAMPs for biomarkers of tumor metastatic status. ROC curve analysis of candidate DAMPs in predictive discrimination of M0 and M1 patients.</p>
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<p>Cytokine and chemokine profiling of cancer patients’ serum according to tumor metastatic status. (<b>A</b>) Cytokines and chemokines were clustered according to their main deduced functions, including Th1/2 cytokines. (<b>B</b>) Analysis of selected cytokines, including IL-15 and IFN-γ in different stages of tumor metastasis. A significance threshold of <span class="html-italic">p</span>-value &lt; 0.05 was considered as statistical significance. * <span class="html-italic">p</span>-value &lt; 0.05; ** <span class="html-italic">p</span>-value &lt; 0.01.</p>
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17 pages, 14804 KiB  
Article
A Role for Periostin Pathological Variants and Their Interaction with HSP70-1a in Promoting Pancreatic Cancer Progression and Chemoresistance
by Yasuo Tsunetoshi, Fumihiro Sanada, Yuko Kanemoto, Kana Shibata, Atsushi Masamune, Yoshiaki Taniyama, Koichi Yamamoto and Ryuichi Morishita
Int. J. Mol. Sci. 2024, 25(23), 13205; https://doi.org/10.3390/ijms252313205 - 8 Dec 2024
Viewed by 693
Abstract
Pancreatic ductal adenocarcinoma (PDAC) characterized by an abundant cancer stroma is an aggressive malignancy with a poor prognosis. Periostin (Pn) is a key extracellular matrix (ECM) protein in various tumor progression. Previously, we described the role of Pn alternative splicing variants (ASVs) with [...] Read more.
Pancreatic ductal adenocarcinoma (PDAC) characterized by an abundant cancer stroma is an aggressive malignancy with a poor prognosis. Periostin (Pn) is a key extracellular matrix (ECM) protein in various tumor progression. Previously, we described the role of Pn alternative splicing variants (ASVs) with specific functional features in breast cancer. Pn is known to associate with a chemoresistance of PDAC, but the functions of the Pn-ASVs remain largely unknown. In this study, we focused on physiological and pathological Pn-ASVs, and examined the characteristics of Pn-expressing cells and the difference in function of each ASV. We found that cancer-associated fibroblasts (CAFs) are a main source of Pn synthesis, which selectively secrete pathological Pn-ASVs with exon 21 both in mouse and human samples. RNA sequencing identified a gene signature of Pn-positive CAFs associated with ECM-related genes and chemokines, factors that shape the chemoresistance tumor microenvironment (TME). Additionally, only pathological Pn-ASVs interacted with heat shock protein 70-1a (HSP70-1a), leading to significant rescue of gemcitabine-induced PDAC apoptosis. In silico analysis revealed that the presence or absence of exon 21 changes the tertiary structure of Pn and the binding sites for HSP70-1a. Altogether, Pn-ASVs with exon 21 secreted from CAFs play a key role in supporting tumor growth by interacting with cancer cell-derived HSP70-1a, indicating that Pn-ASVs with exon 21 might be a potential therapeutic and diagnostic target in PDAC patients with rich stroma. Full article
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<p>The expression of total Pn is elevated in PDAC. (<b>A</b>) Representative Pn immunohistochemical staining of normal pancreas and PDAC. S: stroma, C: cancer cells. (<b>B</b>) % of Pn-positive area in PDAC (n = 20) and normal pancreas (n = 4). (<b>C</b>) Average % of Pn-positive area in PDAC and normal pancreas. * <span class="html-italic">p</span> &lt; 0.05 vs. normal pancreas.</p>
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<p>Pn-ASVs expression in PDAC and CAFs. (<b>A</b>) Human Pn-ASV structures. In addition to four major variants, Pn 1, Pn 2-1, Pn 3 and Pn 4-1, four other isoforms have been reported. Red arrows indicate the position of primers for Pn-ASV detection. The EMI domain, the four FAS-1 domains and the N- and C-terminal end of the carboxyl-terminal domain are depicted. (<b>B</b>) Pn-ASVs mRNA expression in PDAC cell lines (Panc 1, AsPC 1 and BxPC 3) and CAFs (hPSC5 and hPSC14). N = 4, * <span class="html-italic">p</span> &lt; 0.05 vs. Panc 1, AsPC 1 and BxPC 3, ** <span class="html-italic">p</span> &lt; 0.05 vs. Panc 1, AsPC 1, BxPC 3 and hPSC5. <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 vs. Pn 1, Pn 3 and Pn 4, <sup>‡</sup> <span class="html-italic">p</span> &lt; 0.05 vs. Pn 1 and Pn 2-1 and Pn 3. (<b>C</b>) Total Pn protein secreted from PDAC cell lines (Panc 1, AsPC 1 and BxPC 3) and CAFs (hPSC5 and hPSC14). (<b>D</b>) Pn-ASVs protein secreted from CAF. Pn-ASV proteins immunoprecipitated from a culture supernatant of CAFs using the specific antibodies against Pn exon 1, 17 and 21 were analyzed by Western blotting with Pn antibody for exon 12.</p>
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<p>Restricted distribution of Pn-ASVs with exon 21 and sequencing analysis of Pn-positive cells. (<b>A</b>) A representative in situ hybridization image of total Pn (RNAscope) and Pn-ASVs with exon 21 (Basescope) in PDAC specimen. The red color indicates a positive signal for Pn mRNA. Both total Pn and Pn-ASVs with exon 21 mRNA was expressed in fibroblasts surrounding cancer. S: stroma, C: cancer cells. Bar indicates 100 μm. (<b>B</b>) Pn expression and prognosis in patients with PDAC. Pn expression and PDAC prognostic analysis was examined using the Kaplan–Meier plotter. It was found that the prognosis was worse in the group with high Pn expression. (<b>C</b>) Single-cell RNA-sequence analysis in different cell types show that the fibroblast and smooth muscle cell clusters are the ones that show high Pn expression. (<b>D</b>) Violin plot for Pn expression in different cell types in PDAC on the data from the Single Cell Portal.</p>
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<p>PDAC tumors activate Pn expression in CAFs. (<b>A</b>) KPC mice-derived YFP+ PDAC cells were subcutaneously implanted in the back of 8-week-old male C57BL6 mice and sacrificed on day 35. (<b>B</b>) YFP-positive and negative cells isolation by fluorescence-activated cell sorting (FACS). (<b>C</b>) Total Pn (amplicon: exon 9–10) and Pn-ASV with exon 21 (amplicon: exon 21–22) expression was higher in YFP-negative cells containing CAFs. N = 4, * <span class="html-italic">p</span> &lt; 0.05 vs. pre-transplantation cancer cell and YFP+ cell. (<b>D</b>) YFP+ PDAC cells were subcutaneously implanted into the back of 8-week-old male Postn-tdTomato mice and sacrificed on day 35. Tamoxifen was administered intraperitoneally 5 days prior to sacrifice. (<b>E</b>) Tdtomato, a Pn-positive signal, was identified in the stroma of the excised tumor. TFP-positive ODAC cells were shown in green. White bar indicates 100 μm. (<b>F</b>) CAFs were isolated from excised tumors by FACS using GFP-negative and CD90-positive sorting. Tdtomato was further used to divide the CAFs to Pn-positive and negative groups. (<b>G</b>) Tdtomato-positive CAFs had higher expression of total Pn (exon 9–10 amplicon) and exon 21-containing ASVs (exon 21–22 amplicon). N = 3, * <span class="html-italic">p</span> &lt; 0.05 vs. CD90+ Tdtomato-CAFs.</p>
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<p>The transcriptome of Pn-positive (CD90+ tdTomato+) and negative (CD90+ tdTomato-) CAFs. RNA sequence analysis was performed using Pn-positive and Pn-negative CAFs isolated from a mouse PDAC syngeneic model. RNA-seq analysis comparing Pn-positive and Pn-negative CAFs. (<b>A</b>) RNA-seq analysis showing a volcano plot and heat map of differentially expressed genes (DEGs) in Pn-positive and Pn-negative CAFs. The data represent three biological replicates. It revealed 7624 differentially expressed genes (DEGs, red dots in MA plot) when comparing Pn-positive CAFs from Pn-negative CAFs (FDR &lt; 0.05). Among 7624 DEGs, 4418 were up-regulated, while 3206 were up-regulated in Pn-positive CAFs. (<b>B</b>) Gene ontology enrichment and KEGG analysis of up-regulated genes in the Pn-positive CAFs from the RNA-seq data. (<b>C</b>) Representative genes whose expression was increased in the Pn-positive CAFs group. Up-regulated genes in Pn-positive CAFs include several genes related to cancer progression and chemoresistance. Data are the log2 of fold change (LogFC). Relative expression pattern analysis of up-regulated genes in Pn-positive CAFs by qRT-PCR analysis to validate the RNA-seq data is shown in <a href="#app1-ijms-25-13205" class="html-app">Supplementary Figure S4</a>.</p>
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<p>Pn-ASVs with exon 21 interacts with HSP70 and promotes gemcitabine resistance in pancreatic cancer. (<b>A</b>) Pull-down solutions were electrophoresed on gels and silver stained. Protein analysis of bands that appeared specifically in the pull-down solution of Pn2-1 was performed (red arrows). (<b>B</b>) Amino acid sequence of HSP70 was detected by LC-MS/MS analysis of gel bands analysis. Western blotting with primary antibody for HSP70 in post-pull-down solution detected a strong band in lane Pn2-1 but not Pn4-1. (<b>C</b>) HSPA1A and HSPA8 expression in PDAC cells and CAFs. HSP70 was higher in PDAC cell lines as compared to CAFs. N = 4, * <span class="html-italic">p</span> &lt; 0.05 vs. hPSC 5, ** <span class="html-italic">p</span> &lt; 0.05 vs. BxPC 3. (<b>D</b>) The 3D predicted steric structures of Pn2-1 and Pn4-1, and predicted binding sites with HSPA1A are shown. Colored blue to red from n-terminus to c-terminus. (<b>E</b>) GEM significantly reducing proliferation of PDAC and CAFs cell lines. N = 6, * <span class="html-italic">p</span> &lt; 0.05 vs. 0 μM. (<b>F</b>) Pn-ASV with exon 21 suppresses GEM-induced PDAC cell line cell death. However, knockdown of HSPA1A prevents the rescue benefit. N = 12, * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL siRNA.</p>
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12 pages, 2819 KiB  
Article
Dictamnus dasycarpus Turcz. Root Bark Improves Skin Barrier Function and Symptoms of Atopic Dermatitis in Mice
by Sangjun Park, Jinkyu Yang, Kyoungmin Sun, Seonah Park, Jimi Lee, Soyeon Kim, Ji Hyo Lyu and Hyungwoo Kim
Int. J. Mol. Sci. 2024, 25(23), 13178; https://doi.org/10.3390/ijms252313178 - 7 Dec 2024
Viewed by 527
Abstract
The root bark of Dictamus dasycarpus Turcz. has been traditionally used for the topical treatment of skin disorders like pruritus. This study was designed to investigate the inflammatory and skin barrier protective effects of D. dasycarpus in mice with calcipotriol (MC903)-induced atopic dermatitis [...] Read more.
The root bark of Dictamus dasycarpus Turcz. has been traditionally used for the topical treatment of skin disorders like pruritus. This study was designed to investigate the inflammatory and skin barrier protective effects of D. dasycarpus in mice with calcipotriol (MC903)-induced atopic dermatitis (AD). Topical skin lesions on male Balb/c mice (8 weeks old) were treated topically with an ethanolic extract of D. dasycarpus (EEDD), and skin water content, water holding capacity (WHC), histopathological abnormalities, and inflammatory cytokine and chemokine levels were investigated. Topical application of EEDD effectively alleviated skin lesion severity, improved skin water content and WHC, and ameliorated histopathological abnormalities, including hyperkeratosis, blood vessel numbers near the epidermis, spongiotic changes, and immune cell infiltration in skin tissues. EEDD also suppressed inflammatory cytokines and chemokines, such as tumor necrosis factor (TNF)-α, thymic stromal lymphopoietin (TSLP), interleukin (IL)-1β, IL-4, IL-8, and monocyte chemotactic protein (MCP)-1. In RAW264.7 cells, EEDD reduced nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) expression and suppressed the phosphorylations of extracellular signal-regulated kinase (ERK) and p38. These results suggest that the root bark of D. dasycarpus has therapeutic potential due to its anti-dermatitis and skin barrier protective effects in AD and that it could be used as an ingredient in skincare products. Full article
(This article belongs to the Section Bioactives and Nutraceuticals)
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<p>Effects of EEDD on skin color and lesions in AD mice (<b>A</b>) a, treatment-naïve mice (NOR); b, AD control (CTL); c, 30 μg/day EEDD; d, 90 μg/day EEDD; e, 300 μg/day EEDD; f, 150 μg/day DEX. (<b>B</b>) Skin lesion scores; (<b>C</b>) Cutaneous thickness; (<b>D</b>) Weight of skin samples; (<b>E</b>) Erythema indices. A.U., arbitrary units; N.D., undetectable; EEDD, ethanol extract of <span class="html-italic">D. dasycarpus</span> root bark; DEX, dexamethasone. Results are presented as means ± SDs. ## <span class="html-italic">p</span> &lt; 0.01 and ### <span class="html-italic">p</span> &lt; 0.001 vs. NOR; * <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 vs. CTL.</p>
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<p>Effects of EEDD on skin water contents and WHCs in AD mice. (<b>A</b>) Water content; (<b>B</b>) WHC. EEDD, ethanol extract of <span class="html-italic">D. dasycarpus</span>, root bark; DEX, dexamethasone. Results are presented as means ± SDs. # <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 vs. NOR; * <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 vs. CTL.</p>
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<p>Effects of EEDD on histopathological abnormalities in inflamed tissues (<b>A</b>) Abbreviations are consistent with those in <a href="#ijms-25-13178-f001" class="html-fig">Figure 1</a>A. The solid arrow shows a blood vessel located near the epidermis, and the solid wedge indicates an indistinct basal layer between the epidermis and dermis (100×); (<b>B</b>) Severity scores; (<b>C</b>) Infiltrating immune cells. EEDD, ethanol extract of <span class="html-italic">D. dasycarpus</span>, root bark; DEX, dexamethasone. Results are presented as means ± SDs. ### <span class="html-italic">p</span> &lt; 0.001 vs. the NOR; * <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 vs. CTL.</p>
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<p>Effects of EEDD on MC903-induced TNF-α, IL-2, IL-4, and IL-6 increases in skin tissues (<b>A</b>), TNF-α; (<b>B</b>), IL-2; (<b>C</b>), IL-4; (<b>D</b>), IL-6. EEDD, ethanol extract of <span class="html-italic">D. dasycarpus</span>, root bark; DEX, dexamethasone. Results are presented as means ± SDs. # <span class="html-italic">p</span> &lt; 0.05 and ### <span class="html-italic">p</span> &lt; 0.001 vs. the NOR; * <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 vs. CTL.</p>
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<p>Effects of EEDD on the mRNA levels of cytokines and chemokines in RAW264.7 cells. Levels of TSLP, S100A8, TNF, IL-1β, IL-6, IL-8, IL-4, and MCP-1 were measured by quantitative PCR. Results are presented as means ± SDs. n.s., not significant; ** <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 vs. CTL.</p>
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<p>Effects of EEDD on NF-κB and MAPK signalling pathways in RAW264.7 cells. The protein levels of IκB-α, NF-κB (<b>A</b>), ERK, p38, and JNK (<b>B</b>) were determined by Western blot.</p>
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15 pages, 2431 KiB  
Review
Non-[18F]FDG PET-Radiopharmaceuticals in Oncology
by Antonia Dimitrakopoulou-Strauss, Leyun Pan and Christos Sachpekidis
Pharmaceuticals 2024, 17(12), 1641; https://doi.org/10.3390/ph17121641 - 6 Dec 2024
Viewed by 502
Abstract
Molecular imaging is a growing field, driven by technological advances, such as the improvement of PET-CT scanners through the introduction of digital detectors and scanners with an extended field of view, resulting in much higher sensitivity and a variety of new specific radiopharmaceuticals [...] Read more.
Molecular imaging is a growing field, driven by technological advances, such as the improvement of PET-CT scanners through the introduction of digital detectors and scanners with an extended field of view, resulting in much higher sensitivity and a variety of new specific radiopharmaceuticals that allow the visualization of specific molecular pathways and even theragnostic approaches. In oncology, the development of dedicated tracers is crucial for personalized therapeutic approaches. Novel peptides allow the visualization of many different targets, such as PD-1 and PD-L1 expression, chemokine expression, HER expression, T-cell imaging, microenvironmental imaging, such as FAP imaging, and many more. In this article, we review recent advances in the development of non-[18F]FDG PET radiopharmaceuticals and their current clinical applications in oncology, as well as some future aspects. Full article
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<p>Maximum intensity projection (MIP) images of a patient with multiple myeloma 1 h after i.v. [<sup>18</sup>F]FDG injection (left side) and 1 h after [<sup>18</sup>F]FLT injection (right side). The [<sup>18</sup>F]FLT images show high uptake in the bone marrow of the axial skeleton, the pelvic bones, the spleen, and the liver. The [<sup>18</sup>F]FDG images show no focal or diffuse enhanced uptake in the bone marrow. Normal [<sup>18</sup>F]FDG excretion in the urinary tract.</p>
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<p>Example of a patient with biochemical recurrence of prostate cancer. MIP images 1.5 h after i.v. injection of [<sup>18</sup>F]PSMA-1007 (left side) and 1.5 h after application of [<sup>68</sup>Ga]Ga-PSMA-11 (right side) on the following day due to some non-specific bone uptake of [<sup>18</sup>F]PSMA-1007. Fused transversal images of a prostate cancer recurrence (red arrow) with both tracers. Of note is the different distribution of the two tracers. Enhanced hepatobiliary excretion of the [<sup>18</sup>F]PSMA-1007. Increased urinary excretion of [<sup>68</sup>Ga]Ga-PSMA-11.</p>
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<p>Pie chart showing the percentage of radionuclides used for labeling of different targets for PET immunoimaging.</p>
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18 pages, 3287 KiB  
Article
The C-X-C Motif Chemokine Ligand 5, Which Exerts an Antioxidant Role by Inducing HO-1 Expression, Is C-X-C Motif Chemokine Receptor 2-Dependent in Human Prostate Stroma and Cancer Cells
by Kang-Shuo Chang, Syue-Ting Chen, Shu-Yuan Hsu, Hsin-Ching Sung, Wei-Yin Lin, Ke-Hung Tsui, Yu-Hsiang Lin, Chen-Pang Hou and Horng-Heng Juang
Antioxidants 2024, 13(12), 1489; https://doi.org/10.3390/antiox13121489 - 5 Dec 2024
Viewed by 662
Abstract
While the C-X-C motif chemokine ligand 5 (CXCL5) is recognized as an inflammatory mediator and a potent attractant for immune cells, its functions within the human prostate remain unclear. This study explored the expression, functions, and regulatory mechanisms of CXCL5 in prostate stroma [...] Read more.
While the C-X-C motif chemokine ligand 5 (CXCL5) is recognized as an inflammatory mediator and a potent attractant for immune cells, its functions within the human prostate remain unclear. This study explored the expression, functions, and regulatory mechanisms of CXCL5 in prostate stroma and cancer cells. CXCL5 secreted from prostate cancer cells enhanced neutrophil migration. CXCL5 induced cell proliferation and invasion of prostate cancer cells in vitro and tumorigenesis in a xenograft animal model. C-X-C motif chemokine receptor 2 (CXCR2) has been identified on the surface of prostate fibroblasts and cancer cells. The supernatant of LNCaP cells or CXCL5 overexpression enhanced the migration and contraction of prostate myofibroblast WPMY-1 cells; however, pretreatment with SB225002, a CXCR2 inhibitor, can reverse these effects. CXCL5 evinces antioxidant properties by upregulating heme oxygenase-1 (HO-1) to counteract H2O2-induced reactive oxygen species (ROS) in a CXCR2-dependent manner in WPMY-1 and prostate cancer cells. Our findings illustrate that CXCL5, through HO-1, plays a role in antioxidation, and determine that the CXCL5/CXCR2/HO-1 pathway facilitates antioxidative communication between fibroblasts and cancer cells in the prostate. Therefore, targeting the CXCL5/CXCR2 signaling pathway could provide a new strategy for managing oxidative stress within the prostate. Full article
(This article belongs to the Special Issue Oxidative Stress and Inflammation in Cancer Biology)
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<p>Modulation of CXCL5 in the cell proliferation and invasion of prostate cancer cells. (<b>A</b>) CXCL5 mRNA levels of prostate cells were determined by RT-qPCR. Data are presented as the ΔCT relative to β-actin. The cell immunofluorescent staining of CXCR2 protein in LNCaP (<b>B</b>) and PC-3 (<b>C</b>) cells was determined by flow cytometry. Data from quantitative analysis represented the percentage of CXCR2-positive cells. (<b>D</b>) CXCL5 levels in the supernatant from PC_shCOL and PC_shCXCL5 cells were assessed by ELISA. (<b>E</b>) The mRNA levels (±SE, <span class="html-italic">n</span> = 3) of CXCL5 and HO-1 of PC_shCOL cells relative to PC_shCXCL5 cells. (<b>F</b>) Reporter activity (±SE, <span class="html-italic">n</span> = 6) of HO-1 reporter vector after co-transfected with various dosages of CXCL5 expression vectors. (<b>G</b>) The protein levels of the CXCR2, CXCL5, and HO-1 of mock-transducted PC-3 (PC_shCOL) and CXCL5 knockdown PC-3 (PC_shCXCL5) cells were examined by immunoblot assays. Quantitative analysis (±SE, <span class="html-italic">n</span> = 3) was presented as a relative density of proteins/β-actin. (<b>H</b>) The abilities of cellular proliferation in PC_shCOL and PC_shCXCL5 cells were measured by flow cytometry using a Ki67 flow cytometry kit (±SE, <span class="html-italic">n</span> = 3). (<b>I</b>) The protein levels of EMT markers (E-cadherin, N-cadherin, Snail, Slug, and Vimentin) in PC_shCOL and PC_shCXCL5 cells were determined by immunoblot assays and quantitative analysis (±SE, <span class="html-italic">n</span> = 3). (<b>J</b>) The cellular invasion ability was determined by in vitro Matrigel invasion assays. Data are presented as the mean percentage (±SE; <span class="html-italic">n</span> = 3) in relation to the PC_shCOL cells. (<b>K</b>) The cell numbers for neutrophil trans-membrane migration induced by supernatant from PC_shCOL and PC_shCXCL5 cells (±SE, <span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Knockdown of CXCL5 blocks PC-3 cell tumor growth of cells in xenograft mouse models. Athymic male nude mice were subcutaneously injected with PC_shCOL or PC_shCXCL5 cells for 33 days. (<b>A</b>) Photographs of representative xenografted mice and tumors. (<b>B</b>) The tumor sizes derived from PC_shCOL and PC_shCXCL5 were measured every 3 days. (<b>C</b>) Average body weights (mean ± SE) of mice during the experimental period. (<b>D</b>) Quantitative data (mean ± SE; <span class="html-italic">n</span> = 6) describing tumor weight of the PC_shCOL and PC_shCXCL5 groups when the mice were sacrificed on day 33. (<b>E</b>) Whole-cell lysates of tumor samples from the PC_shCOL and PC_shCXCL5 groups were subjected to immunoblot assays for CXCL5, HO-1, and β-actin. (<b>F</b>) The mRNA levels of CXCL5 and HO-1 in the xenografted tumors were analyzed using RT-qPCR assays (±SE, <span class="html-italic">n</span> = 3). ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Modulation of CXCL5 and SB225002 in endogenous and H<sub>2</sub>O<sub>2</sub>-induced ROS in prostate cancer PC-3 cells. (<b>A</b>) ROS levels and quantitative data from PC_shCOL and PC_shCXCL5 cells after treatment with or without H<sub>2</sub>O<sub>2</sub>, as measured by flow cytometry. (<b>B</b>) The levels of the CXCR2, HO-1, and CXCL5 proteins after treatment with various concentrations of SB225002, as indicated, as examined by immunoblotting assays. Quantitative data are presented as the intensity of the protein bands of the target proteins/β-actin relative to the vehicle-treated group. (<b>C</b>) ROS levels and quantitative data from PC3 cells after treatment with various concentrations of SB225002 and with/without H<sub>2</sub>O<sub>2</sub>, as measured by flow cytometry. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Modulation of CXCL5 in neutrophil migration and cell proliferation in prostate cancer LNCaP cells. (<b>A</b>) Protein levels of CXCL5 and HO-1 from mock-transfected LNCaP (LN-DNA) and LNCaP-overexpressed CXCL5 (LN-CXCL5) cells were examined by immunoblot assays. Quantitative analysis (±SE, <span class="html-italic">n</span> = 3) is presented as the relative density of target proteins/β-actin. (<b>B</b>) The mRNA levels (±SE, <span class="html-italic">n</span> = 3) of CXCL5 and the HO-1 of LN-DNA and LN-CXCL5 cells, as determined by RT-qPCR. (<b>C</b>) CXCL5 levels in the supernatant of LN-DNA and LN-CXCL5 cells, as evaluated by ELISA. (<b>D</b>) The numbers of neutrophil transmembrane migration cells induced by supernatant from LN-DNA and LN-CXCL5 cells (±SE, <span class="html-italic">n</span> = 3). (<b>E</b>) The cellular proliferation abilities of LN-CXCL5 relative to LN-DNA cells were measured by flow cytometry using a Ki67 flow cytometry kit (±SE, <span class="html-italic">n</span> = 3). (<b>F</b>) Cell cycle analysis of LN-DNA and LN-CXCL5 cells. (<b>G</b>) Cell cycle modulators’ protein levels were determined by immunoblot assays and quantitative analysis (±SE, <span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. ND: not detectable.</p>
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<p>Modulation of CXCL5 via CXC2R in endogenous and H<sub>2</sub>O<sub>2</sub>-induced ROS in prostate cancer LNCaP cells. (<b>A</b>) The protein levels of CXCR2, PSA, and HO-1 of LN-DNA, LN-CXCL5, and SB225002-treated LN-CXCL5 cells were examined by immunoblot assays. Quantitative analysis (±SE, <span class="html-italic">n</span> = 3) is presented as the relative density of target proteins/β-actin. (<b>B</b>) Reporter activity (±SE, <span class="html-italic">n</span> = 6) of the PSA reporter vector after co-transfected with various doses of CXCL5 expression vectors. (<b>C</b>) PSA levels (±SE, <span class="html-italic">n</span> = 6) in the supernatant of LN-DNA, LN-CXCL5, and LN-CXC5 treated with CXCL5 antibody or CXCR2 antibody, as assessed by ELISA. Data are presented as PSA secretion in relation to the LN-DNA group. (<b>D</b>) ROS levels and quantitative data (±SE, <span class="html-italic">n</span> = 3) of LN-DNA and LN-CXCL5 cells after treatment with or without H<sub>2</sub>O<sub>2</sub> and SB225002, as measured by flow cytometry. (<b>E</b>) HO-1 protein levels when LN-CXCL5 cells were transiently knocked down as to the HO-1 gene by immunoblot assays and quantitative analysis (±SE, <span class="html-italic">n</span> = 3). (<b>F</b>) ROS levels and quantitative data (±SE, <span class="html-italic">n</span> = 3) from LN-DNA, LN-CXCL5, and HO-1-knockdown LN-CXCL5 cells after treatment with/without H<sub>2</sub>O<sub>2</sub>, as measured by flow cytometry. ** <span class="html-italic">p</span> &lt; 0.01. N.S., no significant difference.</p>
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<p>Modulation of CXCL5 in cell contraction and migration in prostate stroma myofibroblast WPMY-1 cells. (<b>A</b>) Cell immunofluorescent staining of the CXCR2 protein in WPMY-1 cells was determined by flow cytometry. The data from the quantitative analysis represents the percentage of CXCR2-positive cells. (<b>B</b>) Protein levels of Fibronectin, α-SMA, HO-1, CXCL5, and β-actin in WPMY-1-DNA and WPMY-1-CXCL5 cells, as determined by immunoblot assays and quantitative analysis (±SE, <span class="html-italic">n</span> = 3). (<b>C</b>) Cell contraction of mock-transfected WPMY-1 (WPMY-1-DNA) and CXCL5-overexpressed WPMY-1 (WPMY-1-CXCL5) cells, as measured by collagen contraction assays. Data are presented as the mean percentage (±SE; <span class="html-italic">n</span> = 3) of WPMY-1-CXCL5 cells in relation to WPMY-1-DNA cells. (<b>D</b>) Cell contraction of WPMY-1 cells when treated with the supernatant from the LN-DNA, LN-CXCL5, or LN-CXCL5 with SB225002. Data are presented as the mean percentage (±SE; <span class="html-italic">n</span> = 3) in relation to the supernatant from LN-DNA-treated WPMY-1 cells. (<b>E</b>) Migration capabilities in WPMY1 cells treated with conditioned media of LN-DNA, LN-CXCL5, or LN-CXCL5 with SB225002. The white line indicates the average of the leading edges of cells and the size of the wound area. Data are presented as the mean percentage (±SE; <span class="html-italic">n</span> = 3) in relation to the supernatant from LN-DNA-treated WPMY-1 cells. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 7
<p>Modulation of CXCL5 and SB225002 in endogenous and H<sub>2</sub>O<sub>2</sub>-induced ROS in prostate stroma myofibroblast WPMY-1 cells. (<b>A</b>) The protein levels of α-SMA, CXCR2, and HO-1 of WPMY-1 cells after treatment with the conditioned media of the LN-DNA, LN-CXCL5, or LN-CXCL5 with SB225002, as examined by immunoblot assays. Quantitative analysis (±SE, <span class="html-italic">n</span> = 3) is presented as the relative density of target proteins/β-actin. (<b>B</b>) ROS levels and quantitative data for WPMY-1 cells after treatment with the conditioned media of the LN-DNA, LN-CXCL5, or LN-CXCL5 with SB225002, and with/without H2O2, as measured by flow cytometry. (<b>C</b>) ROS levels and quantitative data from WPMY-1-DNA, WPMY-1-CXCL5, and SB225002-treated WPMY-1-CXCL5 cells, after treatment with or without H<sub>2</sub>O<sub>2</sub>, as measured by flow cytometry. (<b>D</b>) ROS levels and quantitative data for WPMY-1 cells after treatment with 2 μM SB225002 and with/without H<sub>2</sub>O<sub>2</sub>, as measured by flow cytometry. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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