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13 pages, 1651 KiB  
Article
Impact of Dupilumab on Skin Surface Lipid-RNA Profile in Severe Asthmatic Patients
by Yoshihiko Sato, Hitoshi Sasano, Sumiko Abe, Yuuki Sandhu, Shoko Ueda, Sonoko Harada, Yuki Tanabe, Kyoko Shima, Tetsuya Kuwano, Yuya Uehara, Takayoshi Inoue, Ko Okumura, Kazuhisa Takahashi and Norihiro Harada
Curr. Issues Mol. Biol. 2024, 46(10), 11425-11437; https://doi.org/10.3390/cimb46100680 - 15 Oct 2024
Viewed by 172
Abstract
The analysis of skin surface lipid-RNAs (SSL-RNAs) provides a non-invasive method for understanding the molecular pathology of atopic dermatitis (AD), but its relevance to asthma remains uncertain. Although dupilumab, a biologic drug approved for both asthma and AD, has shown efficacy in improving [...] Read more.
The analysis of skin surface lipid-RNAs (SSL-RNAs) provides a non-invasive method for understanding the molecular pathology of atopic dermatitis (AD), but its relevance to asthma remains uncertain. Although dupilumab, a biologic drug approved for both asthma and AD, has shown efficacy in improving symptoms for both conditions, its impact on SSL-RNAs is unclear. This study aimed to investigate the impact of dupilumab treatment on SSL-RNA profiles in patients with severe asthma. An SSL-RNA analysis was performed before and after administering dupilumab to asthma patients requiring this intervention. Skin samples were collected non-invasively from patients before and after one year of dupilumab treatment. Although 26 patients were enrolled, an SSL-RNA analysis was feasible in only 7 due to collection challenges. After dupilumab treatment, improvements were observed in asthma symptoms, exacerbation rates, and lung function parameters. Serum levels of total IgE and periostin decreased. The SSL-RNA analysis revealed the differential expression of 218 genes, indicating significant down-regulation of immune responses, particularly those associated with type 2 inflammation, suggesting potential improvement in epithelial barrier function. Dupilumab treatment may not only impact type 2 inflammation but also facilitate the normalization of the skin. Further studies are necessary to fully explore the potential of SSL-RNA analysis as a non-invasive biomarker for evaluating treatment response in asthma. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) Volcano plot of differentially expressed genes between 12 months of dupilumab treatment and 0 months (pre-treatment). The red dots indicate genes up-regulated 12 months after dupilumab treatment and the blue dots indicate those down-regulated at 12 months (Benjamini and Hochberg’s false discovery rate (FDR)  &lt;  0.05). Change in expression level of inflammation (<b>b</b>) and skin barrier-related genes (<b>c</b>) between 0 months and 12 months after dupilumab treatment. (** FDR &lt; 0.01, * FDR &lt; 0.05; Benjamini and Hochberg’s false discovery rate (FDR)  &lt;  0.05).</p>
Full article ">Figure 2
<p>Results of enrichment analysis for the Reactome database in down-regulated genes (<b>a</b>) and up-regulated genes (<b>b</b>) 12 months after dupilumab treatment (Benjamini and Hochberg’s false discovery rate (FDR) &lt; 0.05).</p>
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<p>Results of GSVA. Change in score of the three eosinophil-related (#1, #2, #3; (<b>a</b>), (<b>b</b>), (<b>c</b>), respectively), Th2-related (<b>d</b>), and skin barrier-related (<b>e</b>) gene signatures between 0 months and 12 months after dupilumab treatment. GSVA: gene set variation analysis. #1, #2, #3; GSVA signature scores of the three eosinophil-related gene set. ** <span class="html-italic">p</span> &lt; 0.01; paired <span class="html-italic">t</span>-test.</p>
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48 pages, 7080 KiB  
Article
Proteomic Evidence for Amyloidogenic Cross-Seeding in Fibrinaloid Microclots
by Douglas B. Kell and Etheresia Pretorius
Int. J. Mol. Sci. 2024, 25(19), 10809; https://doi.org/10.3390/ijms251910809 - 8 Oct 2024
Viewed by 2073
Abstract
In classical amyloidoses, amyloid fibres form through the nucleation and accretion of protein monomers, with protofibrils and fibrils exhibiting a cross-β motif of parallel or antiparallel β-sheets oriented perpendicular to the fibre direction. These protofibrils and fibrils can intertwine to form mature amyloid [...] Read more.
In classical amyloidoses, amyloid fibres form through the nucleation and accretion of protein monomers, with protofibrils and fibrils exhibiting a cross-β motif of parallel or antiparallel β-sheets oriented perpendicular to the fibre direction. These protofibrils and fibrils can intertwine to form mature amyloid fibres. Similar phenomena can occur in blood from individuals with circulating inflammatory molecules (and also some originating from viruses and bacteria). Such pathological clotting can result in an anomalous amyloid form termed fibrinaloid microclots. Previous proteomic analyses of these microclots have shown the presence of non-fibrin(ogen) proteins, suggesting a more complex mechanism than simple entrapment. We thus provide evidence against such a simple entrapment model, noting that clot pores are too large and centrifugation would have removed weakly bound proteins. Instead, we explore whether co-aggregation into amyloid fibres may involve axial (multiple proteins within the same fibril), lateral (single-protein fibrils contributing to a fibre), or both types of integration. Our analysis of proteomic data from fibrinaloid microclots in different diseases shows no significant quantitative overlap with the normal plasma proteome and no correlation between plasma protein abundance and their presence in fibrinaloid microclots. Notably, abundant plasma proteins like α-2-macroglobulin, fibronectin, and transthyretin are absent from microclots, while less abundant proteins such as adiponectin, periostin, and von Willebrand factor are well represented. Using bioinformatic tools, including AmyloGram and AnuPP, we found that proteins entrapped in fibrinaloid microclots exhibit high amyloidogenic tendencies, suggesting their integration as cross-β elements into amyloid structures. This integration likely contributes to the microclots’ resistance to proteolysis. Our findings underscore the role of cross-seeding in fibrinaloid microclot formation and highlight the need for further investigation into their structural properties and implications in thrombotic and amyloid diseases. These insights provide a foundation for developing novel diagnostic and therapeutic strategies targeting amyloidogenic cross-seeding in blood clotting disorders. Full article
(This article belongs to the Section Biochemistry)
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Graphical abstract

Graphical abstract
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<p>(<b>A</b>): The clotting cascade and (<b>B</b>) fibrinogen conversion to fibrin. The clotting cascade involves the intrinsic, extrinsic, and common pathways, each comprising various clotting factors. The intrinsic pathway includes factors I (fibrinogen), II (prothrombin), IX (Christmas factor), X (Stuart-Prower factor), XI (plasma thromboplastin), and XII (Hageman factor). The extrinsic pathway consists of factors I, II, VII (stable factor), and X. The common pathway involves factors I, II, V, VIII, and X. These factors circulate in the bloodstream as zymogens and are activated into serine proteases, which catalyse the cleavage of subsequent zymogens into more serine proteases, ultimately activating fibrinogen. The serine proteases include factors II, VII, IX, X, XI, and XII, while factors V, VIII, and XIII are not serine proteases. The intrinsic pathway is activated by exposed endothelial collagen, whereas the extrinsic pathway is triggered by tissue factor released by endothelial cells after external damage. Drawn using Biorender.com.</p>
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<p>Prediction of amyloidogenic regions of (<b>A</b>) human prion protein and (<b>B</b>) fibrinogen α chain on AmyloGram [<a href="#B74-ijms-25-10809" class="html-bibr">74</a>,<a href="#B99-ijms-25-10809" class="html-bibr">99</a>], and (<b>C</b>) fibrinogen α chain on AnuPP [<a href="#B104-ijms-25-10809" class="html-bibr">104</a>]. In the latter case, amyloidogenic regions are shown in green. Blue columns indicate residue numbers.</p>
Full article ">Figure 2 Cont.
<p>Prediction of amyloidogenic regions of (<b>A</b>) human prion protein and (<b>B</b>) fibrinogen α chain on AmyloGram [<a href="#B74-ijms-25-10809" class="html-bibr">74</a>,<a href="#B99-ijms-25-10809" class="html-bibr">99</a>], and (<b>C</b>) fibrinogen α chain on AnuPP [<a href="#B104-ijms-25-10809" class="html-bibr">104</a>]. In the latter case, amyloidogenic regions are shown in green. Blue columns indicate residue numbers.</p>
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<p>Structures of amyloid fibres: Fibril formation by cross-ß elements. Reproduced from an open-access paper [<a href="#B157-ijms-25-10809" class="html-bibr">157</a>].</p>
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<p>Thioflavin T (ThT) binds to amyloid fibrils by recognizing a structural feature common among them. Amyloid fibrils share a cross-β architecture, where the β-sheets are oriented perpendicular to the fibril axis. The surfaces of these cross-β structures form the binding sites for ThT, which results in a characteristic increase in fluorescence upon binding. This property makes ThT a widely used fluorescent stain for detecting and studying amyloid fibrils. ThT binding sites illustrated are of Aβ40 (<b>A</b>,<b>B</b>) and Aβ42 (<b>C</b>,<b>D</b>) fibrils [<a href="#B172-ijms-25-10809" class="html-bibr">172</a>].</p>
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<p>Confocal micrographs where thioflavin T (T) and Amytrackers were used to stain plasma from healthy participants (upper two rows) and those with type 2 diabetes (lower three rows) [<a href="#B196-ijms-25-10809" class="html-bibr">196</a>]. Stains used are as indicated.</p>
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<p>Different classes or types of protein co-aggregation: (<b>A</b>) Titration; (<b>B</b>) Sequestration; (<b>C</b>) Axial and (<b>D</b>) Lateral. Adapted from [<a href="#B365-ijms-25-10809" class="html-bibr">365</a>]. Different colours indicate different protein types.</p>
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<p>Prevalence of proteins (y-axis) in fibrinaloid microclots in the Schofield ‘top 20’ (green) and the one example also seen in the Kruger study (blue) versus average plasma concentrations that are taken from [<a href="#B378-ijms-25-10809" class="html-bibr">378</a>] except for TGFB1 [<a href="#B380-ijms-25-10809" class="html-bibr">380</a>] and periostin [<a href="#B381-ijms-25-10809" class="html-bibr">381</a>]. Abbreviations as in the list of abbreviations. The line of ‘best fit’ is not shown as it has a correlation coefficient r<sup>2</sup> of only 0.1.</p>
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<p>Good correlation between the plasma proteome concentration data in [<a href="#B391-ijms-25-10809" class="html-bibr">391</a>] by Heck and colleagues compared with other measurements of the proteome cited in the text and in <a href="#app1-ijms-25-10809" class="html-app">Supplementary Information</a>. The slope of the line is 0.95 and the correlation coefficient 0.83. Colours encode the datasets in which fibrinaloid proteins were or were not observed, as in <a href="#ijms-25-10809-f007" class="html-fig">Figure 7</a> and <a href="#ijms-25-10809-f009" class="html-fig">Figure 9</a>, viz. blue both, green Schofield, red Kruger, and yellow neither. Abbreviations as in the list of abbreviations.</p>
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<p>Relationship between the standard plasma proteome concentrations (taken from [<a href="#B391-ijms-25-10809" class="html-bibr">391</a>]) and their detection in the Kruger (K), Schofield (S), both (B) studies, or neither (N). Size of symbol encodes protein length in residues. Abbreviations as in list of abbreviations. (<b>A</b>) protein concentrations from other studies delineated in the text and the <a href="#app1-ijms-25-10809" class="html-app">supplementary spreadsheet</a>. (<b>B</b>) Proteins from the study of Heck and colleagues [<a href="#B391-ijms-25-10809" class="html-bibr">391</a>].</p>
Full article ">Figure 9 Cont.
<p>Relationship between the standard plasma proteome concentrations (taken from [<a href="#B391-ijms-25-10809" class="html-bibr">391</a>]) and their detection in the Kruger (K), Schofield (S), both (B) studies, or neither (N). Size of symbol encodes protein length in residues. Abbreviations as in list of abbreviations. (<b>A</b>) protein concentrations from other studies delineated in the text and the <a href="#app1-ijms-25-10809" class="html-app">supplementary spreadsheet</a>. (<b>B</b>) Proteins from the study of Heck and colleagues [<a href="#B391-ijms-25-10809" class="html-bibr">391</a>].</p>
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<p>High amyloidogenicity of proteins in the Kruger (red) and Schofield ‘top 20’ (green) studies and in both (blue) plus amyloidogenicity of proteins seen in neither (yellow), and its broad independence from protein length. The line of best fit indicated has an r<sup>2</sup> of just 0.23.</p>
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<p>High amyloidogenicity of proteins in the Kruger (red) and Schofield (green) studies and in both (blue) plus amyloidogenicity of proteins seen in neither (yellow), and its independence from plasma protein concentrations slope =0.01, (r<sup>2</sup> = 0.05) as recorded in the Heck study [<a href="#B391-ijms-25-10809" class="html-bibr">391</a>] (means of first three time points averaged over two controls).</p>
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<p>Amyloidogenicity of α-2-antiplasmin. The FASTA sequence was obtained from the Uniprot site given in <a href="#app1-ijms-25-10809" class="html-app">Supplementary Table S1</a> and run on the Amylogram website <a href="http://biongram.biotech.uni.wroc.pl/AmyloGram/" target="_blank">http://biongram.biotech.uni.wroc.pl/AmyloGram/</a> (accessed on 1 October 2024) with the results as indicated.</p>
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<p>Amyloidogenicity of SERPINA1 (α1-antitrypsin). The FASTA sequence was obtained from the Uniprot site given in <a href="#app1-ijms-25-10809" class="html-app">Supplementary Table S1</a> and run on the Amylogram website <a href="http://biongram.biotech.uni.wroc.pl/AmyloGram/" target="_blank">http://biongram.biotech.uni.wroc.pl/AmyloGram/</a> (accessed on 1 October 2024) with the results as indicated.</p>
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<p>Amyloidogenicity of POSTN (periostin). The FASTA sequence was obtained from the Uniprot site given in <a href="#app1-ijms-25-10809" class="html-app">Supplementary Table S1</a> and run on the Amylogram website <a href="http://biongram.biotech.uni.wroc.pl/AmyloGram/" target="_blank">http://biongram.biotech.uni.wroc.pl/AmyloGram/</a> (accessed on 1 October 2024) with the results as indicated.</p>
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<p>Amyloidogenicity of LPLC1/BPIB1. The FASTA sequence was obtained from the Uniprot site given in <a href="#app1-ijms-25-10809" class="html-app">Supplementary Table S1</a> and run on the Amylogram website <a href="http://biongram.biotech.uni.wroc.pl/AmyloGram/" target="_blank">http://biongram.biotech.uni.wroc.pl/AmyloGram/</a> (accessed on 1 October 2024) with the results as indicated.</p>
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<p>Comparison of the proteome content of normal (non-amyloid) clots vs the standard plasma proteome in controls in the Heck study (average of two controls over first three time points). Colour encoding is as in <a href="#ijms-25-10809-f011" class="html-fig">Figure 11</a>.</p>
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<p>The proteome in normal clots. Data are taken from [<a href="#B438-ijms-25-10809" class="html-bibr">438</a>] and also coded as to whether the proteins were observed in the fibrinaloid microclots observed by Schofield (green), Kruger (red), both (blue), or neither (yellow).</p>
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<p>Healthy versus pathological (amyloid) clotting. Taken from [<a href="#B22-ijms-25-10809" class="html-bibr">22</a>]. Created with Biorender.com. Microclots fluoresce green in the presence of thioflavin T.</p>
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<p>Individual fibrinogen molecules upon polymerisation either polymerise into a normal clot form, which is relatively easily removed by fibrinolysis, or into an anomalous amyloid form or forms, which are not (Taken from [<a href="#B465-ijms-25-10809" class="html-bibr">465</a>]). Created with Biorender.com.</p>
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13 pages, 4413 KiB  
Article
Periostin in Bronchiolitis Obliterans Syndrome after Lung Transplant
by Hye Ju Yeo, Junho Kang, Yun Hak Kim and Woo Hyun Cho
Int. J. Mol. Sci. 2024, 25(19), 10423; https://doi.org/10.3390/ijms251910423 - 27 Sep 2024
Viewed by 296
Abstract
The utility of measuring serum periostin levels for predicting the occurrence of bronchiolitis obliterans syndrome (BOS) after lung transplantation remains underexplored. We analyzed differentially expressed genes (DEGs) between initially transplanted lung tissue and lung tissue with BOS from four patients. Periostin levels were [...] Read more.
The utility of measuring serum periostin levels for predicting the occurrence of bronchiolitis obliterans syndrome (BOS) after lung transplantation remains underexplored. We analyzed differentially expressed genes (DEGs) between initially transplanted lung tissue and lung tissue with BOS from four patients. Periostin levels were assessed in 97 patients who had undergone lung transplantation 1 year post-transplantation and at the onset of BOS. The association between periostin levels and BOS, as well as their correlation with the decline in forced expiratory volume in one second (FEV1), was evaluated. Periostin levels in the BOS group were significantly higher than those in the control group (p < 0.001) and the stable group (p < 0.001). Periostin levels at the onset of BOS were significantly higher than those 1 year post-transplantation in the BOS group (p < 0.001). The serum periostin levels at the time of BOS diagnosis showed a positive correlation with the reduction in FEV1 (%) (r = 0.745, p < 0.001). The increase in the serum periostin levels at the time of BOS diagnosis compared with those 1 year post-transplantation was positively correlated with reduction in FEV1 (%) (r = 0.753, p < 0.001). Thus, serum periostin levels may serve as biomarkers for predicting a decline in lung function in patients with BOS after lung transplantation. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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Figure 1

Figure 1
<p>Comprehensive analysis of differential gene expression. (<b>A</b>): Volcano plot illustrating the differential expression analysis of 25,724 genes. The x-axis represents the log2 fold change, reflecting the magnitude of expression differences. The y-axis represents the negative logarithm (base 10) of the <span class="html-italic">p</span>-value, reflecting the statistical significance of the differential expression of each gene. The genes surpassing the log2 fold change threshold of 2 and <span class="html-italic">p</span>-value threshold of 0.05 are indicated in red (significantly differentially expressed), those only surpassing the <span class="html-italic">p</span>-value threshold are indicated in blue, those only surpassing the fold change threshold are indicated in green, and non-significant genes are indicated in black. (<b>B</b>): Heatmap of the expression patterns of the 332 differentially expressed genes across multiple samples. The x-axis categorizes individual samples, whereas the y-axis lists genes. The expression levels are color-coded, with upregulated genes indicated in varying shades of green and downregulated genes indicated in shades of red, facilitating a clear visual distinction between gene expression trends across different conditions. The color legend on the right side clarifies the gradation of the expression levels. (<b>C</b>): Pathway enrichment analysis of the upregulated genes in the KEGG database. The x-axis quantifies the number of genes involved in each pathway, whereas the y-axis identifies the pathways involved. The circle sizes represent the gene count in each pathway, and the color gradient indicates the significance of pathway enrichment, with darker shades denoting lower <span class="html-italic">p</span>-values. (<b>D</b>): Similar to Panel C, this plot shows the results of the pathway enrichment analysis for the downregulated genes using the same visual and analytical metrics.</p>
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<p>Network analysis of differentially expressed genes between lung tissue at the time of transplantation and BOS lung tissue. (<b>A</b>): Visualization of the protein–protein interaction (PPI) network constructed using the STRING database for 332 differentially expressed genes (DEGs). The network comprises 141 genes that exhibit known interactions, depicted as nodes connected by 359 linkages, reflecting the strength of the interactions and biological relationships among these genes. (<b>B</b>): Detailed representation of a highly connected module within the PPI network, featuring genes with the highest confidence interaction score of ≥9. This module was identified as central to BOS pathogenesis, with nodes corresponding to the genes shown in <a href="#ijms-25-10423-f001" class="html-fig">Figure 1</a>B, underscoring their significant roles. (<b>C</b>): Analysis of hub genes within the PPI network comprising 20 genes that exhibit a high degree of connectivity, reflecting their pivotal role in gene interactions. Connectivity strength is represented by a color gradient from yellow to red, with red indicating the highest connection strength. These genes were selected based on their degree of connectivity, which ranges from 10 to 20, highlighting their critical influence within the network.</p>
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<p>TGF-beta and periostin levels in the three groups. TGF-beta (<b>A</b>) and periostin (<b>B</b>) levels were measured in serum samples from healthy controls (n = 22) and an independent lung transplant cohort (n = 97). The lung transplant cohort was further divided into patients with bronchiolitis obliterans syndrome (BOS) (n = 25) and stable patients (n = 72). In the stable group, the serum levels of periostin and TGF-beta were measured one year after transplantation. In the BOS group, measurements were taken at the time of BOS diagnosis.</p>
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<p>Periostin and TGF-beta between 1 year after lung transplantation and the time of BOS diagnosis in the BOS group. Periostin (<b>A</b>) and TGF-beta (<b>B</b>) were measured in the BOS group at both one year after transplantation and at the time of BOS diagnosis. Paired <span class="html-italic">t</span>-test results show that the periostin levels were significantly higher after the onset of BOS compared with that 1 year post-transplantation (3.7 vs. 153.0, <span class="html-italic">p</span> &lt; 0.001). The TGF-β levels were also significantly higher after the onset of BOS compared with that 1 year post-transplantation (79.8 vs. 267.2, <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Correlation between lung function decline and periostin in the BOS group. (<b>A</b>). Correlation between the reduction rates of FEV1 (%) and periostin level at the time of BOS diagnosis. (<b>B</b>). Correlation between the reduction rates of FEV1 (%) and ΔPOSTN. Δ FEV1 (%) = (FEV1 at 1 year−FEV1 at BOS)/FEV1 at 1 year, BOS: bronchiolis obliterans syndrome. ΔPOSTN: ΔPOSTN = periostin at BOS−periostin at 1 year.</p>
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<p>Serum periostin levels are a useful biomarker for predicting BOS after lung transplantation.</p>
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17 pages, 22610 KiB  
Article
Bleomycin-Induced Pulmonary Fibrosis in Transgenic Mice Carrying the Human MUC5B rs35705950 Variant
by Suphachai Tharavecharak, Hajime Fujimoto, Taro Yasuma, Corina N. D’Alessandro-Gabazza, Masaaki Toda, Atsushi Tomaru, Haruko Saiki, Mei Uemura, Yurie Kogue, Toshiyuki Ito, Kazuki Furuhashi, Tomohito Okano, Atsuro Takeshita, Kota Nishihama, Ryoichi Ono, Osamu Hataji, Tetsuya Nosaka, Tetsu Kobayashi and Esteban C. Gabazza
Cells 2024, 13(18), 1523; https://doi.org/10.3390/cells13181523 - 11 Sep 2024
Viewed by 619
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive, often fatal lung disease characterized by tissue scarring and declining lung function. The MUC5B promoter polymorphism rs35705950, a significant genetic predisposition for IPF, paradoxically associates with better survival and slower disease progression than other IPF genotypes. [...] Read more.
Idiopathic pulmonary fibrosis (IPF) is a progressive, often fatal lung disease characterized by tissue scarring and declining lung function. The MUC5B promoter polymorphism rs35705950, a significant genetic predisposition for IPF, paradoxically associates with better survival and slower disease progression than other IPF genotypes. This study investigates the potential paradoxical protective effects of this MUC5B variant in lung fibrosis. For this purpose, we developed a transgenic mouse model overexpressing the human MUC5B rs35705950 variant in the proximal large airways. Lung fibrosis was induced through subcutaneous injection of bleomycin. Results demonstrated significantly reduced lung fibrosis severity in transgenic mice compared to wild-type mice, assessed by trichrome staining, Ashcroft scoring, and hydroxyproline levels. Additionally, transgenic mice showed significantly lower levels of inflammatory cells and cytokines (TNFα, IL-6, IFNγ) and growth factors (PDGF, CTGF, IL-13) in the bronchoalveolar lavage fluid and lung tissues. There was also a significant decrease in mRNA expressions of fibrosis-related markers (periostin, fibronectin, Col1a1). In summary, this study reveals that mucin overexpression related to the MUC5B rs35705950 variant in the large airways significantly attenuates lung fibrosis and inflammatory responses in transgenic mice. These findings suggest that the rs35705950 variant modulates inflammatory and fibrotic responses in the proximal airways, which may contribute to the slower disease progression observed in IPF patients carrying this variant. Our study offers a possible explanation for the paradoxical beneficial effects of the MUC5B variant despite its role as a significant predisposing factor for IPF. Full article
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Figure 1
<p>Generation of human MUC5B [rs35705950] transgenic mice. Preparation of a construct of human MUC5B [rs35705950] recombinant bacterial artificial chromosome (BAC) using the Red/ET recombination strategy (<b>A</b>). Sequence analysis of the junction DNA of the recombinant BAC clone (<b>B</b>). The expression construct linearized with PI-SceI (Proteinase Intein-Scel Endonuclease I) was separated by pulsed-field gel electrophoresis (<b>C</b>). The gel containing the expression construct within the agarose gel was cut out without UV irradiation (upper figure of panel <b>C</b>). The DNA fragments purified by electrophoretic elution and dialysis were applied to pulsed-field gel electrophoresis to confirm that the long-chain DNA fragments were purified without fragmentation (middle figure of panel <b>C</b>). The DNA concentration was determined using a NanoDrop spectrophotometer (Shimazu biotech, Kyoto, Japan) lower figure of panel <b>C</b>). The linearized recombinant BAC clone was microinjected into fertilized eggs of the C57BL/6J strain and the fertilized eggs were transplanted into the oviducts of pseudo-pregnant mice to get the founders (<b>D</b>–<b>F</b>). The marker used was M: NEB Low Range PFG marker. Red/ET, Red recombinase system (RedαRedβ proteins)/Electroporation-Transformation-cloning. Arrows indicate the bands.</p>
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<p>Expression of the human <span class="html-italic">MUC5B</span> [rs35705950] transgene. Southern blot screening for the transgene in the offspring, identifying three transgenic mouse founders (red arrows in (<b>A</b>)). Analysis of relative gene expression of the human <span class="html-italic">MUC5B</span> [rs35705950] transgene in various tissues and organs by PCR (<b>B</b>).</p>
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<p>Sequential body weight changes and significant expression of the human <span class="html-italic">MUC5B</span> transgene rs35705950 in the proximal airways in the bleomycin-induced lung fibrosis model. Lung fibrosis was induced in wild-type (WT/BLM) and human MUC5B rs35705950 transgenic (h-rs35705950-Tg/BLM) mice through continuous subcutaneous administration of BLM. Control groups, consisting of WT (WT/SAL) and human MUC5B rs35705950 transgenic (h-rs35705950-Tg/SAL) mice, similarly received sterile physiological saline. Sequential body weight changes in the four groups of mice (<b>A</b>). Relative mRNA expression of the transgene in the experimental mouse groups (<b>B</b>). Immunostaining for MUC5B protein was performed using an anti-MUC5B polyclonal antibody, which cross-reacts with both human and mouse MUC5B (<b>C</b>,<b>D</b>). Additionally, MUC5B protein staining was conducted using an anti-human MUC5B monoclonal antibody (<b>E</b>,<b>F</b>). Scale bars indicate 100 µm. Data are expressed as the mean ± SD. Statistical analysis was performed using ANOVA with the Neuman-Keuls test. * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001. WT, wild-type; TG, transgenic; BLM, bleomycin; SAL, saline.</p>
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<p>Reduced infiltration of inflammatory cells in human MUC5B rs35705950 transgenic mice with lung fibrosis. (<b>A</b>,<b>B</b>) Lung fibrosis was induced in wild-type (WT/BLM) and human MUC5B rs35705950 transgenic (h-rs35705950-Tg/BLM) mice through continuous subcutaneous administration of BLM. Control groups, consisting of WT (WT/SAL) and human MUC5B rs35705950 transgenic (h-rs35705950-Tg/SAL) mice, similarly received sterile physiological saline. On the 22nd day following BLM administration, bronchoalveolar lavage fluid was collected under profound anesthesia. The total cell count and differential cell count were then assessed. Scale bars indicate 200 μm. Data are expressed as the mean ± SD. Statistical analysis was performed by ANOVA with Neuman-Keuls test. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. WT, wild-type; TG, transgenic; BLM, bleomycin; SAL, saline.</p>
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<p>Reduced expression of inflammatory cytokines in human MUC5B rs35705950 transgenic mice with lung fibrosis. Inflammatory cytokines were measured in bronchoalveolar lavage fluid (<b>A</b>) and lung tissue homogenate (<b>B</b>) by immunoassays using commercially available kits and following the protocols of the manufacturers. Data are expressed as the mean ± SD. Statistical analysis was performed by ANOVA with Neuman-Keuls 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. WT, wild-type; TG, transgenic; BLM, bleomycin; SAL, saline; ns, not significant; OPN, osteopontin.</p>
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<p>Decreased expression of growth factors in human MUC5B rs35705950 transgenic mice with lung fibrosis. Growth factors were measured in bronchoalveolar lavage fluid (<b>A</b>) and lung tissue homogenate (<b>B</b>) by immunoassays using commercially available kits and following the protocols of the manufacturers. Data are expressed as the mean ± SD. Statistical analysis was performed by ANOVA with Neuman-Keuls 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. WT, wild-type; TG, transgenic; BLM, bleomycin; SAL, saline; ns, not significant.</p>
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<p>Reduced expression of extracellular matrix markers in human MUC5B rs35705950 transgenic mice with lung fibrosis. The relative mRNA expression of extracellular matrix markers was assessed by polymerase-chain reaction and the levels of collagen I was assessed by enzyme immunoassays using commercially available kits following the protocol of the manufacturers. Data are expressed as the mean ± SD. Statistical analysis was performed by ANOVA with Neuman-Keuls 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. WT, wild-type; TG, transgenic; BLM, bleomycin; SAL, saline; ns, not significant.</p>
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<p>Reduced lung fibrosis in human MUC5B rs35705950 transgenic mice. Ashcroft scoring was performed in lung tissue stained with hematoxylin &amp; eosin by blinded experts for the treatment groups. The number of mice in: WT/SAL, n = 8, WT/BLM, n = 18, h-rs35705950-TG/SAL, n = 10, h-rs35705950-TG/BLM, n = 16 (<b>A</b>,<b>B</b>). Collagen deposition was evaluated after trichrome staining, and the total lung collagen volume fraction was calculated. The number of mice: WT/SAL, n = 3, WT/BLM, n = 5, h-rs35705950-TG/SAL, n = 3, h-rs35705950-TG/BLM, n = 5 (<b>C</b>,<b>D</b>). The lung tissue hydroxyproline content was measured by a colorimetric assay. The number of mice: WT/SAL, n = 8, WT/BLM, n = 18, h-rs35705950-TG/SAL, n = 10, h-rs35705950-TG/BLM, n = 16 (<b>E</b>). Scale bars indicate 200 µm. Data are the mean ± S.D. Statistical analysis by ANOVA with Newman-Keuls test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.001. WT, wild-type; SAL, saline; BLM, bleomycin.</p>
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17 pages, 13134 KiB  
Article
Expression of Periostin Alternative Splicing Variants in Normal Tissue and Breast Cancer
by Yuko Kanemoto, Fumihiro Sanada, Kana Shibata, Yasuo Tsunetoshi, Naruto Katsuragi, Nobutaka Koibuchi, Tetsuhiro Yoshinami, Koichi Yamamoto, Ryuichi Morishita, Yoshiaki Taniyama and Kenzo Shimazu
Biomolecules 2024, 14(9), 1093; https://doi.org/10.3390/biom14091093 - 31 Aug 2024
Viewed by 859
Abstract
(1) Background: Periostin (Pn) is a secreted protein found in the extracellular matrix, and it plays a variety of roles in the human body. Physiologically, Pn has a variety of functions, including bone formation and wound healing. However, it has been implicated in [...] Read more.
(1) Background: Periostin (Pn) is a secreted protein found in the extracellular matrix, and it plays a variety of roles in the human body. Physiologically, Pn has a variety of functions, including bone formation and wound healing. However, it has been implicated in the pathogenesis of various malignant tumors and chronic inflammatory diseases. Pn has alternative splicing variants (ASVs), and our previous research revealed that aberrant ASVs contribute to the pathogenesis of breast cancer and heart failure. However, the difference in expression pattern between physiologically expressed Pn-ASVs and those expressed during pathogenesis is not clear. (2) Methods and results: We examined normal and breast cancer tissues, focusing on the Pn-ASVs expression pattern to assess the significance of pathologically expressed Pn-ASVs as potential diagnostic and therapeutic targets. We found that most physiologically expressed Pn isoforms lacked exon 17 and 21. Next, we used human breast cancer and normal adjacent tissue (NAT) to investigate the expression pattern of Pn-ASVs under pathological conditions. Pn-ASVs with exon 21 were significantly increased in tumor tissues compared with NAT. In situ hybridization identified the synthesis of Pn-ASVs with exon 21 in peri-tumoral stromal cells. Additionally, the in vivo bio-distribution of 89Zr-labeled Pn antibody against exon 21 (Pn-21Ab) in mice bearing breast cancer demonstrated selective and specific accumulation in tumors, while Pn-21Ab significantly suppressed tumor growth in the mouse breast cancer model. (3) Conclusions: Together, these data indicate that Pn-ASVs might have potential for use as diagnostic and therapeutic targets for breast cancer. Full article
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Figure 1
<p>Physiological distribution of Pn-ASV mRNA and total protein in adult mice. (<b>A</b>) The mPn-ASV mRNA copy number in several organs from C57BL6J mice aged at 8 weeks. Data are shown as mean ± SE, <span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> &lt; 0.05 vs. Pn 1–3. An amount of 1 μg total RNA was subjected to cDNA synthesis. The copy number of each Pn-ASV was calculated using specific primer sets and standard mouse Pn-ASV plasmid. (<b>B</b>) Total mPn protein expression in several organs from adult mice aged 8 weeks old. A total of 10 μg tissue proteins were loaded and detected with Pn exon 12 Ab, which detected all Pn-ASVs. A membrane with Coomassie brilliant blue (CBB) staining was shown as loading control. (<b>C</b>) Quantification data of total mPn protein expression in organs of adult mice.</p>
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<p>Physiological distribution of mPn-ASV protein in adult mice. (<b>A</b>) Confirmation of total mPn protein expression in adult mouse organs. Total mPn protein expression was measured separately in each organ through immunoblotting with Pn exon 12 Ab. Supernatant from human Pn-1-Halotag over-expressed HEK293T cells (10 and 20 μg) and mouse 4T1 breast cancer cells (20 and 40 μg) were simultaneously blotted as a positive control. Proteins from Pn KO mice were used as a negative control. N = 3 for each organ. (<b>B</b>) IP and Western blotting results for mPn-ASVs. A total of 75 μg tissue proteins was immunoprecipitated with exon 14 (lane 2), 17 (lane 3), 21 (lane 4), and control IgG (lane 5). Immune complexes were collected on protein G-Agarose beads under agitation, according to the manufacturer’s instructions. Proteins were solubilized in Laemmli buffer, separated via SDS-PAGE, transferred to PVDF membranes, and detected with Pn exon 12 Ab. A total of 10 μg of un-precipitated sample was also loaded in order to determine the molecular level of physiologically expressed mPn-ASVs (lane 1). Lane 6 shows protein precipitated with beads only. The circle indicates the band of mPn-ASVs with exon 21. Coomassie brilliant blue (CBB) staining was performed, according to the manufacturer’s instructions. (<b>C</b>) Dosage-dependent increase in IP proteins of mPn-ASVs with exon 21. Amounts of 300, 150, and 75 μg of proteins were immunoprecipitated with Pn exon 21 Ab.</p>
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<p>mPn-positive cells in lineage tracing mice. Representative histological sections from several organs of Pn-lineage tracing mice, which show tdTomato-positive labeling cells in the stomach, small intestine, colon, skin, heart, and lung but rarely in the liver, kidney, and cerebrum. In the stomach, interstitial cells in the lamina propria mucosae were positive for tdTomato (arrows in low magnitude and arrowheads in high magnitude), and mucosa (arrows) and submucosa (arrowheads) of the small intestine were observed as positive. In the colon, Pn-positive cells were observed in linear peri-cryptal pattern in normal colonic mucosa (arrows) and submucosa (arrowheads). In the skin, Pn-positive cells were localized in the bulge region of the hair follicle (arrows) and at the basement membrane in the epidermis (arrowheads). In the lung, especially peribronchus area was positive for tdTomato. In the heart, only a small number of cells between myocytes were positive for tdTomato. In the liver, kidney and cerebrum cells expressing tdTomato were rare.</p>
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<p>Physiological distribution of hPn-ASV proteins in humans. (<b>A</b>) Total hPn expression in normal human organs. Tissue microarrays for normal human tissue were stained with Ab against n-terminal of hPn (Atlas Antibodies, Sigma-Aldrich, HPA012306). (<b>B</b>) IP and Western blotting for hPn-ASVs in normal stomach, colon, lung, and breast. A total of 75 μg of tissue proteins were immunoprecipitated with exon 14 (lane 2), 17 (lane 3), 21 (lane 4), and control IgG (lane 5). Immune complexes were collected on protein G-Agarose beads under agitation. Proteins were solubilized in Laemmli buffer, separated via SDS-PAGE, and transferred to PVDF membranes and detected with Pn exon 12 Ab. An amount of 10 μg of un-precipitated sample was also loaded to determine the molecular level of physiologically expressed Pn-ASVs (lane 1). Lane 6 shows beads only. The circle indicates the bands of hPn-ASVs with exon 21.</p>
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<p>hPn-ASVs expression in human breast cancer and adjacent normal tissue. (<b>A</b>) hPn-ASV mRNA expression in breast cancer (tumor) and normal adjacent tissue (NAT). Breast cancer specimens collected from patients undergoing total mastectomy for localized breast cancer were subjected to mRNA analysis. NAT was collected from the contralateral side of tumor across the nipple. Total hPn and hPn-ASVs with exon 17 or 21 were analyzed using specific primer sets and quantitative RT-PCR. Actual values for each patient (<b>A</b>,<b>B</b>) and average of hPn mRNA expression in tumor and NAT are also shown. (<b>C</b>) Data shown as mean ± SE, <span class="html-italic">n</span> = 11, * <span class="html-italic">p</span> &lt; 0.05 vs. NAT. (<b>D</b>) hPn-ASV protein expression in tumor (T) and NAT (N) detected with Ab against exon 12 (all hPn-ASVs, left image) or 21 (right image). Immunoblot with exon 12 or 21 Ab was performed using 10 μg of proteins from 6 patients with breast cancer. (<b>E</b>) Quantitative analysis of change in expression in tumor with reference to NAT.</p>
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<p>ISH against total hPn and hPn-ASVs with exon 21 in breast cancer. (<b>A</b>) ISH with probe for total hPn. Peri-tumoral stroma cells (black triangle) show strong positive signals. Scale bar indicates 500 μm. (<b>B</b>) Quantification data of average number of dots per cell. Data shown as mean ± SE, <span class="html-italic">n</span> = 22, * <span class="html-italic">p</span> &lt; 0.05 vs. stroma (Mann–Whitney U-test). (<b>C</b>) ISH with probe for hPn-ASVs with exon 21. Peri-tumoral stroma cells (red triangle) with spindle-shaped nuclei showed strong positive signals. (<b>D</b>) Quantification data of average number of dots per cell. Data are shown as mean ± SE, <span class="html-italic">n</span> = 22, * <span class="html-italic">p</span> &lt; 0.05 vs. stroma (Mann–Whitney U-test).</p>
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<p>Bio-distribution study of <sup>89</sup>Zn Pn-21Ab and <sup>89</sup>Zn Pn-7/8 Ab. <sup>89</sup>Zr Pn-Ab distribution in BALB/c mice bearing 4T07 mouse TNBC tumor allografts. (<b>A</b>) Coronal (upper panel) and axial (lower panel) micro-PET images of BALB/c mice bearing 4T07 allografts (white arrow) 72 h post-<sup>89</sup>Zr Pn-Ab injection. (<b>B</b>) Quantification of <sup>89</sup>Zr Pn-Ab distribution in blood and tumor pool, and tumor-to-blood ratio (<span class="html-italic">n</span> = 3). Data shown as median SUVmean ± SE and tumor-to-blood ratio based on SUVmean. * <span class="html-italic">p</span> ≤ 0.05 vs. <sup>89</sup>Zr Pn-21Ab (Mann–Whitney U-test). (<b>C</b>) Ex vivo bio-distribution of <sup>89</sup>Zr Pn-Ab 72 h post-tracer administration (<span class="html-italic">n</span> = 5). Data are expressed as %ID/g ± SE. * <span class="html-italic">p</span> ≤ 0.05 vs. <sup>89</sup>Zr Pn-7/8Ab (Mann–Whitney U-test). (<b>D</b>) Ex vivo bio-distribution of <sup>89</sup>Zr Pn-21Ab 72 h post-tracer administration with or without tumor (<span class="html-italic">n</span> = 5). Data are expressed as %ID/g ± SE. * <span class="html-italic">p</span> ≤ 0.05 vs. <sup>89</sup>Zr Pn-21Ab in without tumor (Mann–Whitney U-test). (<b>E</b>) Pn-ASV-specific Ab (Pn-21Ab and Pn-7/8Ab) inhibited the growth of 4T07 syngeneic mouse model. Mice bearing 4T07 cell tumors were treated with Pn-7/8Ab, Pn-21Ab, or vehicle (<span class="html-italic">n</span> = 5 each). The vehicle group received saline, and the other groups were treated with Pn-7/8Ab (10 mg/kg) or Pn-21Ab (10 mg/kg) 2 times per week throughout the experiments starting at day 6. Tumor volumes were recorded as mean ± SE. * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL and ** <span class="html-italic">p</span> &lt; 0.05 vs. Pn-7/8Ab (Mann–Whitney U test). (<b>F</b>) A dose-dependent trend toward tumor shrinkage in Pn-21Ab treated mice with 4T07 breast cancer. Mice bearing 4T07 cell tumors were treated with Pn-21Ab or vehicle (<span class="html-italic">n</span> = 5 each). The vehicle group received saline, and the other groups were treated with Pn-21Ab (10 or 30mg/kg), 2 times per week throughout the experiments starting at day 6. Tumor volumes were recorded as mean ± SE. * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL (Mann–Whitney U test).</p>
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14 pages, 6435 KiB  
Article
The Importance of Suppressing Pathological Periostin Splicing Variants with Exon 17 in Both Stroma and Cancer
by Kana Shibata, Nobutaka Koibuchi, Fumihiro Sanada, Naruto Katsuragi, Yuko Kanemoto, Yasuo Tsunetoshi, Shoji Ikebe, Koichi Yamamoto, Ryuichi Morishita, Kenzo Shimazu and Yoshiaki Taniyama
Cells 2024, 13(17), 1410; https://doi.org/10.3390/cells13171410 - 23 Aug 2024
Viewed by 694
Abstract
Background: Periostin (POSTN) is a type of matrix protein that functions by binding to other matrix proteins, cell surface receptors, or other molecules, such as cytokines and proteases. POSTN has four major splicing variants (PN1–4), which are primarily expressed in fibroblasts and cancer. [...] Read more.
Background: Periostin (POSTN) is a type of matrix protein that functions by binding to other matrix proteins, cell surface receptors, or other molecules, such as cytokines and proteases. POSTN has four major splicing variants (PN1–4), which are primarily expressed in fibroblasts and cancer. We have reported that we should inhibit pathological POSTN (PN1–3), but not physiological POSTN (PN4). In particular, pathological POSTN with exon 17 is present in both stroma and cancer, but it is unclear whether the stroma or cancer pathological POSTN should be suppressed. Methods and Results: We transplanted 4T1 cells (breast cancer) secreting POSTN with exon 17 into 17KO mice lacking POSTN exon 17 to suppress stromal POSTN with exon 17. The results show that 17KO mice had smaller primary tumors and fewer metastases. Furthermore, to suppress cancer POSTN with exon 17, 4T1 cells transfected with POSTN exon 17 skipping oligo or control oligo were transplanted from the tail vein into the lungs. The results show that POSTN exon 17 skipping oligo significantly suppressed lung metastasis. Conclusions: These findings suggest that it is important to suppress POSTN exon 17 in both stroma and cancer. Antibody targeting POSTN exon 17 may be a therapeutic candidate for breast cancer. Full article
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Figure 1
<p>The N-terminus of POSTN has EMI domain and 4 repeat domains (FAS1). The C-terminal region (exons 15–23) centered on PN1–4 undergoes alternative splicing. Pathological POSTN splicing variants include exons 17 and 21 (PN1–3), while physiological POSTN lacks POSTN exon 17 and 21 (PN4).</p>
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<p>(<b>A</b>): Expression patterns of various <span class="html-italic">POSTN</span> splicing variants (PN1–4), which were analyzed in 4T1; a cultured cell line of TNBC model RNA was isolated from the 4T1 cell line and absolute quantification of each <span class="html-italic">POSTN</span> splicing variants was performed using PCR method. PN3 was significantly expressed from 4T1, **; <span class="html-italic">p</span> &lt; 0.05 vs. PN1, 2, and 4. Results are shown as absolute values and expressed as mean ± standard error. (<b>B</b>): A sample from a study performed 21 days after transplantation of 4T1 cells into BALB/c mice. The primary tumor was excised and fixed with 4% paraformaldehyde. Yellow dot line separates cancer and stroma area. The pathology specialists from external agencies, Applied Medical Research Laboratory (Osaka, Japan) distinguished as cancer and stroma, and drew the yellow dot line. Breast cancer cells with large round shapes; strong dysplastic nuclei and alveolar formation can be distinguished. Red color shows the <span class="html-italic">POSTN</span> exon 17 expression in cancer cells and fibroblast cells in stroma. The black scale bar in the figure represents 1000 μm and serves as a size reference.</p>
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<p>(<b>A</b>–<b>D</b>): The 1 10<sup>5</sup> 4T1 cells suspended in PBS were injected into the mammary glands of wild-type mice (7-week-old female BALB/c) and POSTN exon 17KO mice (7-week-old female). (<b>A</b>–<b>C</b>): 17KO mice had significantly suppressed a-SMA positive cells or vimentin positive cells (CAFs), and CD163 positive cells (TAMs) compared to wild-type mice, **; <span class="html-italic">p</span> &lt; 0.01 vs. wild-type mice. (<b>D</b>–<b>E</b>): Tumors were predominantly suppressed in 17KO mice compared to wild-type mice. Lung metastasis was also significantly suppressed in 17KO mice compared to wild-type mice. (<b>F</b>): Tumors were increased in POSTN (1–4) KO mice compared to wild-type mice. On the contrary, lung metastasis was significantly suppressed in POSTN (1–4) KO mice compared to wild-type mice. Lung metastasis was evaluated by staining with Bouin fixation and counting the number of lung colonies. Tumor size was measured on days 14, 21, and 28, with results shown for day 28. Relative values are shown as mean ± standard error (<span class="html-italic">n</span> = 4~7, ** <span class="html-italic">p</span> &lt; 0.01 or * <span class="html-italic">p</span> &lt; 0.05 vs. wild mice). **; <span class="html-italic">p</span> &lt; 0.01 vs. wild-type mice. Primary tumors in mice were evaluated by calculating tumor volume (mm<sup>3</sup>) as 1/2 × length (mm) × width (mm). Results are shown as absolute values and expressed as mean ± standard error. In the representative images, the yellow scale bar is shown at 100 μm.</p>
Full article ">Figure 3 Cont.
<p>(<b>A</b>–<b>D</b>): The 1 10<sup>5</sup> 4T1 cells suspended in PBS were injected into the mammary glands of wild-type mice (7-week-old female BALB/c) and POSTN exon 17KO mice (7-week-old female). (<b>A</b>–<b>C</b>): 17KO mice had significantly suppressed a-SMA positive cells or vimentin positive cells (CAFs), and CD163 positive cells (TAMs) compared to wild-type mice, **; <span class="html-italic">p</span> &lt; 0.01 vs. wild-type mice. (<b>D</b>–<b>E</b>): Tumors were predominantly suppressed in 17KO mice compared to wild-type mice. Lung metastasis was also significantly suppressed in 17KO mice compared to wild-type mice. (<b>F</b>): Tumors were increased in POSTN (1–4) KO mice compared to wild-type mice. On the contrary, lung metastasis was significantly suppressed in POSTN (1–4) KO mice compared to wild-type mice. Lung metastasis was evaluated by staining with Bouin fixation and counting the number of lung colonies. Tumor size was measured on days 14, 21, and 28, with results shown for day 28. Relative values are shown as mean ± standard error (<span class="html-italic">n</span> = 4~7, ** <span class="html-italic">p</span> &lt; 0.01 or * <span class="html-italic">p</span> &lt; 0.05 vs. wild mice). **; <span class="html-italic">p</span> &lt; 0.01 vs. wild-type mice. Primary tumors in mice were evaluated by calculating tumor volume (mm<sup>3</sup>) as 1/2 × length (mm) × width (mm). Results are shown as absolute values and expressed as mean ± standard error. In the representative images, the yellow scale bar is shown at 100 μm.</p>
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<p>(<b>A</b>) Using 3T3 fibroblasts, we checked PN 1–4. PN1 and 3 were prominently decreased after exon 17 skipping. compared to 3T3 Ctrl and 3T3 Ctrl antisense. It can be confirmed that PN 1 and 3 have been erased by exon 17 skipping. 3T3 Ctrl: no-treatment 3T3 fibroblasts, 3T3 Pn delete: <span class="html-italic">POSTN</span> (1–4) all knock out 3T3 cells by CRISPR-Cas9, 3T3 Ctrl AS: control antisense transfected 3T3 cells, 3T3 exon 17 skip: exon 17 skipping antisense transfected 3T3 cells. (<b>B</b>) We transfected control oligo or <span class="html-italic">POSTN</span> exon 17 skipping oligo to 4T1-Luc cells. In mice treated with control oligo-transfected 4T1-Luc cells, high luciferase activity was measured, indicating that 4T1-Luc cells metastasize to the lungs. On the other hand, in mice treated with <span class="html-italic">POSTN</span> exon 17 skipping oligo transfected 4T1-Luc cells, luciferase activity was very low, indicating that 4T1-Luc cells rarely metastasize to the lungs. These results suggest that skipping oligo that selectively skip <span class="html-italic">POSTN</span> exon 17 inhibit metastasis of breast cancer cells to the lung (each <span class="html-italic">n</span> = 3~6, **; <span class="html-italic">p</span> &lt; 0.01 vs. control). For comparison between the two groups, the Mann–Whitney test (MWU) was used.</p>
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<p>(<b>A</b>–<b>D</b>): When we add 4T1 mice TNBC cells supernatant into NH3T3 cells, <span class="html-italic">IL-6</span> and <span class="html-italic">IL-8</span> are significantly increased, and the POSTN exon 17 antibody treatment reduces them significantly. **; <span class="html-italic">p</span> &lt; 0.05 vs. POSTN exon 17 antibody non-treatment. Results are shown as absolute values and expressed as mean ± standard error.</p>
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<p>(<b>A</b>–<b>D</b>) We show the result of PN17-Ab on xenograft model. A total of 1 × 10<sup>6</sup> MDA-MB-231 cells were suspended in PBS and injected into the chest of 7-week-old female NOD/Si-scid,IL-2RγKO mice. Once the tumor volume reached 100 mm<sup>3</sup>, the POSTN exon 17 antibody (PN17-Ab, 40–600 μg/mice) or mouse IgG antibody (Control IgG, 600 μg/mice) was administered once weekly. (<b>A</b>,<b>B</b>): After dissection up to 9 weeks after transplantation, the POSTN exon 17 antibody suppressed primary tumor growth in a dose-dependent manner (<span class="html-italic">n</span> = 6, *; <span class="html-italic">p</span> &lt; 0.05, **; <span class="html-italic">p</span> &lt; 0.01 vs. control IgG). Tumor size (mm<sup>3</sup>) was calculated as 1/2 × width (mm) × length (mm). We evaluated lung metastasis after H and E staining. (<b>C</b>,<b>D</b>): Area of lung colonies were significantly reduced by the treatment of the POSTN exon 17 antibody (<span class="html-italic">n</span> = 6, *; <span class="html-italic">p</span> &lt; 0.05, **; <span class="html-italic">p</span> &lt; 0.01 vs. control IgG). Three site-specific analyses were performed from one lung section. Results are shown as absolute values and expressed as mean ± standard error.</p>
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<p>The pathological POSTN with exon 17 was secreted from both fibroblasts in stroma and cancer. Once secreted, it increased IL-6 and IL-8, which induces the inflammation of the TME with TAMs and may promote malignancy of cancer.</p>
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25 pages, 12993 KiB  
Article
Correlation between Periostin Expression and Pro-Angiogenic Factors in Non-Small-Cell Lung Carcinoma
by Adrian Wasik, Marzenna Podhorska-Okolow, Piotr Dziegiel, Aleksandra Piotrowska, Michal Jerzy Kulus, Alicja Kmiecik and Katarzyna Ratajczak-Wielgomas
Cells 2024, 13(17), 1406; https://doi.org/10.3390/cells13171406 - 23 Aug 2024
Viewed by 724
Abstract
The role of periostin (POSTN) in remodeling the microenvironment surrounding solid tumors and its effect on the tumor cells in non-small-cell lung carcinoma (NSCLC) have not yet been fully understood. The aim of this study was to determine the relationship between POSTN expression [...] Read more.
The role of periostin (POSTN) in remodeling the microenvironment surrounding solid tumors and its effect on the tumor cells in non-small-cell lung carcinoma (NSCLC) have not yet been fully understood. The aim of this study was to determine the relationship between POSTN expression (in tumor cells [NSCLC cells] and the tumor stroma) and pro-angiogenic factors (CD31, CD34, CD105, and VEGF-A) and microvascular density (MVD) in NSCLC. In addition, these associations were analyzed in individual histological subtypes of NSCLC (SCC, AC, and LCC) and their correlations with clinicopathological factors and prognosis were examined. Immunohistochemistry using tissue microarrays (TMAs) was used to assess the expression of POSTN (in tumor cells and cancer-associated fibroblasts [CAFs]) and the pro-angiogenic factors. A significant positive correlation was found between the expression of POSTN (in cancer cells/CAFs) and the expression of the analyzed pro-angiogenic factors (CD31, CD34, CD105, and VEGF-A) and MVD in the entire population of patients with NSCLC and individual histological subtypes (AC, SCC). In addition, this study found that POSTN expression (in tumor cells/CAFs) increased with tumor size (pT), histopathological grade (G), and lymph-node involvement (pN). In addition, a high expression of POSTN (in tumor cells and CAFs) was associated with shorter survival among patients with NSCLC. In conclusion, a high expression of POSTN (in cancer cells and CAFs) may be crucial for angiogenesis and NSCLC progression and can constitute an independent prognostic factor for NSCLC. Full article
(This article belongs to the Special Issue Advances in the Research of a Key Molecule in Periostin)
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<p>Comparison of the expression of POSTN (in cells (<b>A</b>) and in stroma (<b>B</b>)) and the expression of pro-angiogenic markers (VEGF-A (<b>C</b>); CD31 (<b>D</b>); CD34 (<b>E</b>); CD105 (<b>F</b>)) between non-malignant lung tissue and cancer cells. The significance of the differences was determined using the Mann–Whitney U test. The images in (<b>G</b>–<b>K</b>) show punches from tissue microarrays illustrating an example of the immunohistochemical (IHC) reaction for each individual protein, as described above. Error bars represent the standard deviation (SD). *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Bar charts showing the expression of POSTN in cells (<b>A</b>–<b>C</b>) and in stroma (<b>D</b>–<b>F</b>) across all cancer types with regard to the T-stage (<b>A</b>,<b>D</b>) and N-stage (<b>B</b>,<b>E</b>) of the TNM classification as well as the tumor stage (<b>C</b>–<b>F</b>). The significance of the differences was determined using the Kruskal–Wallis ANOVA test and the differences between individual groups were evaluated using the appropriate post hoc test. Error bars represent the standard deviation (SD). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Bar charts showing the expression of POSTN in cells (<b>A</b>–<b>D</b>) and in stroma (<b>E</b>–<b>H</b>), across all cancer types (<b>A</b>,<b>E</b>), in adenocarcinoma (<b>B</b>,<b>F</b>), and in squamous-cell carcinoma (<b>C</b>,<b>G</b>), with regard to the tumor grade. The significance of the differences was determined using the Kruskal–Wallis ANOVA test (<span class="html-italic">p</span> &lt; 0.001 in bar plots (<b>A</b>–<b>C</b>,<b>E</b>–<b>G</b>)), and differences between individual groups were evaluated with the appropriate post hoc test. The results obtained for large-cell carcinoma were statistically insignificant (<b>D</b>,<b>H</b>). The images in (<b>I</b>–<b>Q</b>) show representative punches demonstrating the IHC reaction for POSTN in adenocarcinoma (<b>I</b>–<b>K</b>), squamous-cell carcinoma (<b>L</b>–<b>N</b>), and large-cell carcinoma (<b>O</b>–<b>Q</b>) with respect to the tumor grade. Error bars represent the standard deviation (SD). *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Bar plot showing the only statistically significant difference between males and females (Mann–Whitney U test). Error bars represent the standard deviation (SD). * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Correlation plots comparing POSTN expression in cells to POSTN expression in stroma, across all cancer types (<b>A</b>), in adenocarcinoma (<b>B</b>), in squamous-cell carcinoma (<b>C</b>), and in large-cell carcinoma (<b>D</b>). The plots include <span class="html-italic">p</span>-values and R-values (calculated with Spearman’s correlation test) and the number of cases, which can be seen in the lower right corner of each plot.</p>
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<p>Correlation plots comparing the quantities of CD31-positive (<b>A</b>), CD34-positive (<b>B</b>), and CD105-positive (<b>C</b>) vessels quantified via the Chalkley and Weidner methods. The plots include <span class="html-italic">p</span>-values and R-values (calculated with Spearman’s correlation test) and the number of cases, which can be seen in the lower right corner of each plot.</p>
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<p>Correlation plots comparing the expression of POSTN in stroma with the expression of pro-angiogenic markers, as quantified via the Weidner (<b>A</b>–<b>C</b>) or Chalkley (<b>D</b>–<b>F</b>) method. The pro-angiogenic factors are CD31 (<b>A</b>,<b>D</b>), CD34 (<b>B</b>,<b>E</b>), and CD105 (<b>C</b>,<b>F</b>). The plots include <span class="html-italic">p</span>-values and R-values (calculated with Spearman’s correlation test) and the number of cases, which can be seen in the lower right corner of each plot.</p>
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<p>Correlation plots comparing the expression of POSTN in cells (<b>A</b>–<b>C</b>) and in stroma (<b>D</b>–<b>F</b>) with the expression of pro-angiogenic markers, as quantified via the Chalkley method, assessed in adenocarcinoma. The pro-angiogenic factors are CD31 (<b>A</b>,<b>D</b>), CD34 (<b>B</b>,<b>E</b>), and CD105 (<b>C</b>,<b>F</b>). The plots include <span class="html-italic">p</span>-values and R-values (calculated with Spearman’s correlation test) and the number of cases, which can be seen in the lower right corner of each plot. The images in (<b>G</b>–<b>I</b>) show punches from tissue microarrays demonstrating an example of the immunohistochemical (IHC) reaction for each individual protein, as previously described. The images in (<b>J</b>–<b>L</b>) show representative magnified regions of the microarray punches.</p>
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<p>Correlation plots comparing the expression of POSTN in cells (<b>A</b>–<b>C</b>) and in stroma (<b>D</b>–<b>F</b>) with the expression of pro-angiogenic markers, as quantified via the Chalkley method, assessed in squamous-cell carcinoma. The pro-angiogenic factors are CD31 (<b>A</b>,<b>D</b>), CD34 (<b>B</b>,<b>E</b>), and CD105 (<b>C</b>,<b>F</b>). The plots include <span class="html-italic">p</span>-values and R-values (calculated with Spearman’s correlation test) and the number of cases, which can be seen in the lower right corner of each plot. The images in (<b>G</b>–<b>I</b>) show punches from tissue microarrays demonstrating an example of the immunohistochemical (IHC) staining for each individual protein, as previously described. The images in (<b>J</b>–<b>L</b>) show representative magnified regions of the microarray punches.</p>
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<p>Correlation plots comparing the expression of POSTN in stroma (<b>A</b>–<b>D</b>) with the expression of VEGF-A, as assessed with the semi-quantitative IRS method, across all cancer types (<b>A</b>), in adenocarcinoma (<b>B</b>), in squamous-cell carcinoma (<b>C</b>), and in large-cell carcinoma (<b>D</b>). The images in (<b>E</b>–<b>G</b>) show punches from tissue microarrays demonstrating an example of the immunohistochemical (IHC) staining for each individual protein, as previously described. The images in (<b>H</b>–<b>J</b>) show representative magnified regions of the microarray punches.</p>
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<p>Kaplan–Meier plots of survival for patients expressing POSTN in their cells (<b>A</b>), POSTN in their stroma (<b>B</b>), and VEGF-A (<b>C</b>) at levels below or above the median. The graphs in (<b>D</b>,<b>E</b>) show the plots of survival for patients with regard to the quartile classifications of the levels of POSTN expression in their cells (<b>D</b>) or stroma (<b>E</b>). Quartiles are shown in ascending order, with I representing the first 25% of results, II representing 26–50%, III representing 51–75%, and IV representing 76% and above. The significance of the differences was determined with the log-rank test. The <span class="html-italic">p</span>-value and the number of cases are given in the lower right corner of each plot.</p>
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<p>Kaplan–Meier plots of survival for patients with POSTN in their cells (<b>A</b>,<b>B</b>) or stroma (<b>C</b>,<b>D</b>) with regard to the tumor type (adenocarcinoma (<b>A</b>,<b>C</b>) or squamous-cell carcinoma (<b>B</b>,<b>D</b>)). The significance of the differences was determined using the log-rank test. The <span class="html-italic">p</span>-value and the number of cases are given in the lower right corner of each plot.</p>
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<p>Receiver operating characteristic (ROC) curve demonstrating the sensitivity and specificity of the logistic regression model for predicting patient survival over a five-year period, as detailed in <a href="#cells-13-01406-t005" class="html-table">Table 5</a>. This curve illustrates the impact of various cut-off values on the model’s sensitivity and specificity. The area under the curve (AUC) can be regarded as a comprehensive indicator of the model’s overall performance. The values in the lower right quadrant represent the model’s performance when the cut-off is set to 50% of the survival probability.</p>
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13 pages, 840 KiB  
Article
Differences in Bone Metabolism between Children with Prader–Willi Syndrome during Growth Hormone Treatment and Healthy Subjects: A Pilot Study
by Joanna Gajewska, Magdalena Chełchowska, Katarzyna Szamotulska, Witold Klemarczyk, Małgorzata Strucińska and Jadwiga Ambroszkiewicz
Int. J. Mol. Sci. 2024, 25(17), 9159; https://doi.org/10.3390/ijms25179159 - 23 Aug 2024
Viewed by 1038
Abstract
Despite therapy with growth hormone (GH) in children with Prader–Willi syndrome (PWS), low bone mineral density and various orthopedic deformities have been observed often. Therefore, this study aimed to analyze bone markers, with an emphasis on vitamin K-dependent proteins (VKDPs), in normal-weight children [...] Read more.
Despite therapy with growth hormone (GH) in children with Prader–Willi syndrome (PWS), low bone mineral density and various orthopedic deformities have been observed often. Therefore, this study aimed to analyze bone markers, with an emphasis on vitamin K-dependent proteins (VKDPs), in normal-weight children with PWS undergoing GH therapy and a low-energy dietary intervention. Twenty-four children with PWS and 30 healthy children of the same age were included. Serum concentrations of bone alkaline phosphatase (BALP), osteocalcin (OC), carboxylated-OC (Gla-OC), undercarboxylated-OC (Glu-OC), periostin, osteopontin, osteoprotegerin (OPG), sclerostin, C-terminal telopeptide of type I collagen (CTX-I), and insulin-like growth factor-I (IGF-I) were determined using immunoenzymatic methods. OC levels and the OC/CTX-I ratios were lower in children with PWS than in healthy children (p = 0.011, p = 0.006, respectively). Glu-OC concentrations were lower (p = 0.002), but Gla-OC and periostin concentrations were higher in patients with PWS compared with the controls (p = 0.005, p < 0.001, respectively). The relationships between IGF-I and OC (p = 0.013), Gla-OC (p = 0.042), and the OC/CTX-I ratio (p = 0.017) were significant after adjusting for age in children with PWS. Bone turnover disorders in children with PWS may result from impaired bone formation due to the lower concentrations of OC and the OC/CTX-I ratio. The altered profile of OC forms with elevated periostin concentrations may indicate more intensive carboxylation processes of VKDPs in these patients. The detailed relationships between the GH/IGF-I axis and bone metabolism markers, particularly VKDPs, in children with PWS requires further research. Full article
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<p>Concentrations of vitamin K-dependent proteins (VKDPs) in children with Prader–Willi syndrome (PWS) and in healthy children (dark grey—children with PWS, light grey—healthy children. Data are presented as mean values ± SD. OC—osteocalcin; Gla-OC—carboxylated osteocalcin; Glu-OC—undercarboxylated osteocalcin.</p>
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<p>Flowchart of the study. BMI—body mass index; GH—growth hormone.</p>
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37 pages, 3523 KiB  
Review
A Comprehensive Review of Protein Biomarkers for Invasive Lung Cancer
by Alexandre Mezentsev, Mikhail Durymanov and Vladimir A. Makarov
Curr. Oncol. 2024, 31(9), 4818-4854; https://doi.org/10.3390/curroncol31090360 - 23 Aug 2024
Viewed by 1534
Abstract
Invasion and metastasis are important hallmarks of lung cancer, and affect patients’ survival. Early diagnostics of metastatic potential are important for treatment management. Recent findings suggest that the transition to an invasive phenotype causes changes in the expression of 700–800 genes. In this [...] Read more.
Invasion and metastasis are important hallmarks of lung cancer, and affect patients’ survival. Early diagnostics of metastatic potential are important for treatment management. Recent findings suggest that the transition to an invasive phenotype causes changes in the expression of 700–800 genes. In this context, the biomarkers restricted to the specific type of cancer, like lung cancer, are often overlooked. Some well-known protein biomarkers correlate with the progression of the disease and the immunogenicity of the tumor. Most of these biomarkers are not exclusive to lung cancer because of their significant role in tumorigenesis. The dysregulation of others does not necessarily indicate cell invasiveness, as they play an active role in cell division. Clinical studies of lung cancer use protein biomarkers to assess the invasiveness of cancer cells for therapeutic purposes. However, there is still a need to discover new biomarkers for lung cancer. In the future, minimally invasive techniques, such as blood or saliva analyses, may be sufficient for this purpose. Many researchers suggest unconventional biomarkers, like circulating nucleic acids, exosomal proteins, and autoantibodies. This review paper aims to discuss the advantages and limitations of protein biomarkers of invasiveness in lung cancer, to assess their prognostic value, and propose novel biomarker candidates. Full article
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<p>Oxidative deamination catalyzed by lysyl oxidases. In the beginning (left), the enzyme catalyzes the oxidative deamination of a lysyl residue in a targeted protein substrate. The product of the enzyme reaction (allysine/peptidyl-α-aminoadipic-δ-semialdehyde) participates in subsequent nonenzymatic condensation reactions. The interactions with lysine and allysine yield the formation of bifunctional crosslink intermediates, Shiff base, and aldol (upper and lower intermediates in the middle). The further spontaneous rearrangements lead to formation of tri-, tetra-, and even penta-functional crosslinks in the affected proteins.</p>
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<p>Activation of the PI3K/PKB and RHO/ROCK pathways by integrins. Activated integrin receptor initiates signal transduction by binding to the tyrosine-protein kinase, FAK. The binding of FAK follows clustering the integrins and the recruitment of adaptor proteins. In response to the interaction with the ligand–receptor complex, FAK autophosphorylates. The autophosphorylation of FAK causes conformational changes and creates a binding site for SRC kinase. After engaging FAK, SRC becomes activated and phosphorylates few additional amino acids. The activated SRC kinase recruits phosphoinositide 3-Kinase (PI3K) to the complex and phosphorylates it. PI3K phosphorylates the 3-position hydroxyl group of the inositol ring of PIP<sub>2</sub>, a small lipid anchored in the cellular membrane, and converts it to PIP<sub>3</sub>. Traveling in the inner layer of the membrane, PIP<sub>3</sub> interacts with PDPK1. Binding PIP<sub>3</sub> anchors PDK1 in the cellular membrane. Then, PDK1 recruits PKB and activates it by phosphorylation. One of the PKB target proteins, DLC1 (Deleted in Liver Cancer 1), is a GTPase-activating protein that inactivates RHOA by stimulating the hydrolysis of GTP bound to the enzyme. Phosphorylating DLC1, PKB suppresses this biological effect and shifts the balance toward RHOA-GTP, which activates ROCK by causing conformational changes in its molecule.</p>
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<p>The biological effects of LOXL2 that promote the invasive behavior of tumor cells. LOXL2 exerts its effects through multiple mechanisms: (<b>A</b>)—In the extracellular matrix, LOXL2 crosslinks proteins such as collagens, elastins, and fibronectins, leading to the formation of a dense and rigid matrix that facilitates tumor cell invasion (small black arrows indicate the crosslinking sites). (<b>B</b>)—In the nucleus, LOXL2 deaminates histones H3 and other DNA- and RNA-binding proteins (including SNAI2, TCF3, and KLF4), resulting in chromatin condensation and altered gene expression. (<b>C</b>)—In the cytoplasm and the nucleus, LOXL2 generates reactive oxygen species (ROS) that cause protein and DNA damage, contributing to genomic instability. (<b>D</b>)—LOXL2 modulates intracellular signaling by oxidizing lysine residues on cellular receptors, such as PDGFRβ, thereby activating the downstream signaling pathways. (<b>E</b>)—In the cytosol, LOXL2 prevents apoptosis by inactivating MARCKSL1 and promotes the Warburg effect by deacetylating fructose-bisphosphate aldolase A. (<b>F</b>)—In the endoplasmic reticulum, LOXL2 interferes with protein glycosylation and induces a stress response by interacting with the heat shock protein HSAP5.</p>
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<p>The role of MAPK15 in regulation of gene expression. On the top: two ways to phosphorylate/activate MAPK15—autophosphorylation and phosphorylation by a fusion protein exhibiting a kinase activity; (<b>A</b>)—MAPK15 activates the transcription factor NFκB. The enzyme destabilizes the inhibitory subunit IκBα and directly interacts with p50. The complex of p50 and MAPK15 is transcriptionally active; (<b>B</b>)—MAPK activates/phosphorylates the AP1 transcription factor c-JUN inducing AP1 target genes; (<b>C</b>)—MAPK15 represses the transcription of nuclear receptors (AR, GR, and PR), competing with them for their binding partner, TGFB1I1. (<b>D</b>)—MAPK15 represses ERRα target genes by escorting ERRα to the cytoplasm for degradation.</p>
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<p>The enzymatic reaction catalyzed by prolyl 4-hydroxylase. (<b>A</b>). The hydroxylation of proline to 4-hydroxyproline by α subunits of P4H. For catalysis, the enzyme requires three different cofactors: molecular oxygen (O<sub>2</sub>), iron (Fe<sup>2+</sup>), and ascorbic acid (vitamin C). The essential proline residue of a substrate protein (e.g., “collagen”) shall be a part of the specific amino acid motif, typically -X-Pro-Gly-, where X can be any amino acid. During the catalytic process, α-ketoglutaric acid binds to the enzyme-Fe(II) complex, followed by a protocollagen strand and O<sub>2</sub>. After forming the ferryl ion and hydroxylation of the proline residue, the enzyme releases the nascent 4-hydroxyproline-containing polypeptide, CO<sub>2</sub>, and succinate. (<b>B</b>). The isomerization of disulfide bonds catalyzed by the β subunit of P4H. The catalytic process includes the formation of disulfide intermediates between the SH-groups of the substrate protein(s) and the enzyme (P4HB), their structural rearrangements to achieve the desired connectivity, and a recovery of the enzyme.</p>
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13 pages, 5495 KiB  
Article
Experimental Study: The Development of a Novel Treatment for Chemotherapy-Resistant Tongue Cancer with the Inhibition of the Pathological Periostin Splicing Variant 1-2 with Exon 21
by Shoji Ikebe, Nobutaka Koibuchi, Kana Shibata, Fumihiro Sanada, Hideo Shimizu, Toshihiko Takenobu and Yoshiaki Taniyama
Cells 2024, 13(16), 1341; https://doi.org/10.3390/cells13161341 - 13 Aug 2024
Viewed by 761
Abstract
Tongue squamous cell carcinoma (TSCC) occurs frequently in the oral cavity, and because of its high proliferative and metastatic potential, it is necessary to develop a novel treatment for it. We have reported the importance of the inhibition of the periostin (POSTN) pathological [...] Read more.
Tongue squamous cell carcinoma (TSCC) occurs frequently in the oral cavity, and because of its high proliferative and metastatic potential, it is necessary to develop a novel treatment for it. We have reported the importance of the inhibition of the periostin (POSTN) pathological splicing variant, including exon 21 (PN1-2), in various malignancies, but its influence is unclear in tongue cancer. In this study, we investigated the potential of POSTN exon 21-specific neutralizing antibody (PN21-Ab) as a novel treatment for TSCC. Human PN2 was transfected into the human TSCC (HSC-3) and cultured under stress, and PN2 was found to increase cell viability. PN2 induced chemotherapy resistance in HSC-3 via the phosphorylation of the cell survival signal Akt. In tissues from human TSCC and primary tumors of an HSC-3 xenograft model, PN1-2 was expressed in the tumor stroma, mainly from fibroblasts. The intensity of PN1-2 mRNA expression was positively correlated with malignancy. In the HSC-3 xenograft model, CDDP and PN21-Ab promoted CDPP’s inhibition of tumor growth. These results suggest that POSTN exon 21 may be a biomarker for tongue cancer and that PN21-Ab may be a novel treatment for chemotherapy-resistant tongue cancer. The treatment points towards important innovations for TSCC, but many more studies are needed to extrapolate the results. Full article
(This article belongs to the Special Issue Advances in the Research of a Key Molecule in Periostin)
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<p>The N-terminus of POSTN has four repeat domains (FAS1). The C-terminal region (exons 15–23) centered on PN1-4 undergoes alternative splicing. Pathological POSTN splicing variants include exons 17 and 21 (PN1-3).</p>
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<p>Hematoxylin–eosin (HE)-stained images and expression patterns of <span class="html-italic">PN1-4</span> and <span class="html-italic">PN1-2</span> mRNA using ISH (RNAscope<sup>TM</sup>, BaseScope<sup>TM</sup>) in each tissue. (<b>A</b>) Normal <span class="html-italic">human</span> tongue tissue. (<b>B</b>) <span class="html-italic">Human</span> TSCC (grade-1) tissue. (<b>C</b>) <span class="html-italic">Human</span> TSCC (grade-2) tissue. In (<b>B</b>,<b>C</b>), the lower images (RNAscope<sup>TM</sup>, BaseScope<sup>TM</sup>) are magnified views of the yellow box in the upper image (HE). The tumor parenchyma is surrounded by yellow dashed lines. <span class="html-italic">PN</span>1-4 and <span class="html-italic">PN</span>1-2 mRNA are stained red (as indicated by the yellow arrows).</p>
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<p>Hematoxylin–eosin (HE)-stained images and expression patterns of <span class="html-italic">PN1-4</span> and <span class="html-italic">PN1-2</span> mRNA using ISH (RNAscope<sup>TM</sup>, BaseScope<sup>TM</sup>) in each tissue. (<b>A</b>) Normal <span class="html-italic">human</span> tongue tissue. (<b>B</b>) <span class="html-italic">Human</span> TSCC (grade-1) tissue. (<b>C</b>) <span class="html-italic">Human</span> TSCC (grade-2) tissue. In (<b>B</b>,<b>C</b>), the lower images (RNAscope<sup>TM</sup>, BaseScope<sup>TM</sup>) are magnified views of the yellow box in the upper image (HE). The tumor parenchyma is surrounded by yellow dashed lines. <span class="html-italic">PN</span>1-4 and <span class="html-italic">PN</span>1-2 mRNA are stained red (as indicated by the yellow arrows).</p>
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<p>Impact of PN2 on cell death in HSC-3. (<b>A</b>) Number of HSC-3 cells transfected with <span class="html-italic">PN2</span> in serum-free culture (<span class="html-italic">n</span> = 8, **; <span class="html-italic">p</span> &lt; 0.01 vs. control). (<b>B</b>) Number of <span class="html-italic">PN2</span>-transfected HSC-3 cells in serum-free culture with cisplatin treatment (<span class="html-italic">n</span> = 8, *; <span class="html-italic">p</span> &lt; 0.05 vs. control).</p>
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<p>Protein expression of phospho-Akt in <span class="html-italic">PN2</span> transgenic HSC-3 (serum-free culture). (<b>A</b>) Expression levels of phospho-Akt and total Akt, as measured by Western blotting. (<b>B</b>) Histograms indicating the relative expression levels of phospho-Akt/total Akt (*; <span class="html-italic">p</span> &lt; 0.05 vs. Venus).</p>
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<p>Protein expression of phospho-Akt in <span class="html-italic">PN2</span>-transfected HSC-3 (with CDDP administration). (<b>A</b>) Expression level of phospho-Akt and total Akt, as detected by Western blotting. (<b>B</b>) Histograms indicating the relative expression levels of phospho-Akt/total Akt. CDDP alone significantly decreased phospho-Akt/total Akt compared to Venus (*; <span class="html-italic">p</span> &lt; 0.05 vs. control), and CDDP with <span class="html-italic">PN2</span> transfection significantly increased phospho-Akt/total Akt compared to CDDP alone (*; <span class="html-italic">p</span> &lt; 0.05 vs. Venus).</p>
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<p>Expression patterns of <span class="html-italic">PN1-4</span> and <span class="html-italic">PN1-2</span> mRNA using ISH (RNAscope<sup>TM</sup>, BaseScope<sup>TM</sup>) in tissues of HSC-3 xenograft model primary tumors. The lower images are magnified views of the yellow box in the upper images. <span class="html-italic">PN1-4</span> and <span class="html-italic">PN1-2</span> are stained red. Cancer cells (cancer foci) are indicated by yellow arrows. The yellow scale bar indicates 50 µm.</p>
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<p>(<b>A</b>) Tumor size of primary tumors in an HSC-3 xenograft model treated with PN21-Ab; PN21-Ab significantly decreased tumor size at 14 days (<span class="html-italic">n</span> = 5, **; <span class="html-italic">p</span> &lt; 0.01 vs. control). (<b>B</b>) Tumor size of primary tumor in HSC-3 xenograft model treated with CDDP and PN21-Ab; CDDP significantly decreased tumor size compared to the control, and CDDP with PN21-Ab significantly decreased it compared to CDDP alone (<span class="html-italic">n</span> = 4, **; <span class="html-italic">p</span> &lt; 0.01 vs. control or CDDP with PN21-Ab). Tumor size (mm<sup>3</sup>) was calculated as 1/2 × width (mm) × length (mm).</p>
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<p>Possible mechanism of PN1-2 expression. PN1-2 is expressed primarily in stromal fibroblasts. Of course, the anticancer effect of CDDP decreases phospho-Akt in tongue cancer cells. However, it is thought that PN1-2 expressed from host stromal fibroblasts actually increases phospho-Akt.</p>
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7 pages, 1864 KiB  
Brief Report
Unbiased Proteomic Exploration Suggests Overexpression of Complement Cascade Proteins in Plasma from Patients with Psoriasis Compared with Healthy Individuals
by Bjørn Kromann, Lili Niu, Line B. P. Møller, Julie Sølberg, Karolina Sulek, Mette Gyldenløve, Beatrice Dyring-Andersen, Lone Skov and Marianne B. Løvendorf
Int. J. Mol. Sci. 2024, 25(16), 8791; https://doi.org/10.3390/ijms25168791 - 13 Aug 2024
Viewed by 695
Abstract
Knowledge about the molecular mechanisms underlying the systemic inflammation observed in psoriasis remains incomplete. In this study, we applied mass spectrometry-based proteomics to compare the plasma protein levels between patients with psoriasis and healthy individuals, aiming to unveil potential systemically dysregulated proteins and [...] Read more.
Knowledge about the molecular mechanisms underlying the systemic inflammation observed in psoriasis remains incomplete. In this study, we applied mass spectrometry-based proteomics to compare the plasma protein levels between patients with psoriasis and healthy individuals, aiming to unveil potential systemically dysregulated proteins and pathways associated with the disease. Plasma samples from adult patients with moderate-to-severe psoriasis vulgaris (N = 59) and healthy age- and sex-matched individuals (N = 21) were analyzed using liquid chromatography–tandem mass spectrometry. Patients did not receive systemic anti-psoriatic treatment for four weeks before inclusion. A total of 776 protein groups were quantified. Of these, 691 were present in at least 60% of the samples, providing the basis for the downstream analysis. We identified 20 upregulated and 22 downregulated proteins in patients with psoriasis compared to controls (p < 0.05). Multiple proteins from the complement system were upregulated, including C2, C4b, C5, and C9, and pathway analysis revealed enrichment of proteins involved in complement activation and formation of the terminal complement complex. On the other end of the spectrum, periostin was the most downregulated protein in sera from patients with psoriasis. This comprehensive proteomic investigation revealed significantly elevated levels of complement cascade proteins in psoriatic plasma, which might contribute to increased systemic inflammation in patients with psoriasis. Full article
(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Skin Diseases)
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<p>Plasma-derived proteins from patients with psoriasis reveal enrichment of the complement cascade. (<b>A</b>) In this study, we analyzed the proteomic differences between plasma from 59 patients with psoriasis and 21 healthy individuals by DIA LC-MS/MS. (<b>B</b>) Rank plot showing the overall mean label-free quantification (LFQ) intensities of the quantified proteins. As expected, albumin was the most abundant protein in this study of non-depleted plasma. (<b>C</b>) String network analysis of the 20 upregulated proteins (<span class="html-italic">p</span> &lt; 0.05). The red nodes are proteins present in the ‘immune system’. Reactome pathway and blue nodes represent proteins from the ‘Complement activation, classical pathway’ in the Gene Ontology knowledgebase. The string interaction score cut-off was set to 0.4. (<b>D</b>) Enrichment analysis based on the 20 upregulated proteins. The bar chart shows the top five enriched terms from the Reactome database, along with their corresponding <span class="html-italic">p</span>-values. All <span class="html-italic">p</span>-values remained significant after correction for multiple testing (FDR &lt; 0.05). (<b>E</b>) Boxplots of protein intensities of selected proteins in plasma from patients with psoriasis compared with healthy controls (* = <span class="html-italic">p</span> &lt; 0.05; ** = <span class="html-italic">p</span> &lt; 0.01). Abbreviations: DIA = data-independent acquisition; LC-MS/MS = liquid chromatography–tandem mass spectrometry; LFQ = label-free quantification.</p>
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20 pages, 5257 KiB  
Article
The Role of Vimentin in Human Corneal Fibroblast Spreading and Myofibroblast Transformation
by Miguel Miron-Mendoza, Kara Poole, Sophie DiCesare, Emi Nakahara, Meet Paresh Bhatt, John D. Hulleman and Walter Matthew Petroll
Cells 2024, 13(13), 1094; https://doi.org/10.3390/cells13131094 - 25 Jun 2024
Viewed by 988
Abstract
Vimentin has been reported to play diverse roles in cell processes such as spreading, migration, cell–matrix adhesion, and fibrotic transformation. Here, we assess how vimentin impacts cell spreading, morphology, and myofibroblast transformation of human corneal fibroblasts. Overall, although knockout (KO) of vimentin did [...] Read more.
Vimentin has been reported to play diverse roles in cell processes such as spreading, migration, cell–matrix adhesion, and fibrotic transformation. Here, we assess how vimentin impacts cell spreading, morphology, and myofibroblast transformation of human corneal fibroblasts. Overall, although knockout (KO) of vimentin did not dramatically impact corneal fibroblast spreading and mechanical activity (traction force), cell elongation in response to PDGF was reduced in vimentin KO cells as compared to controls. Blocking vimentin polymerization using Withaferin had even more pronounced effects on cell spreading and also inhibited cell-induced matrix contraction. Furthermore, although absence of vimentin did not completely block TGFβ-induced myofibroblast transformation, the degree of transformation and amount of αSMA protein expression was reduced. Proteomics showed that vimentin KO cells cultured in TGFβ had a similar pattern of protein expression as controls. One exception included periostin, an ECM protein associated with wound healing and fibrosis in other cell types, which was highly expressed only in Vim KO cells. We also demonstrate for the first time that LRRC15, a protein previously associated with myofibroblast transformation of cancer-associated fibroblasts, is also expressed by corneal myofibroblasts. Interestingly, proteins associated with LRRC15 in other cell types, such as collagen, fibronectin, β1 integrin and α11 integrin, were also upregulated. Overall, our data show that vimentin impacts both corneal fibroblast spreading and myofibroblast transformation. We also identified novel proteins that may regulate corneal myofibroblast transformation in the presence and/or absence of vimentin. Full article
(This article belongs to the Special Issue Cell Biology of the Cornea and Ocular Surface)
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<p>Western blot showing a lack of vimentin protein expression in vimentin knockout (KO) cells as compared to wild-type (WT) and controls.</p>
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<p>The effect of Vim KO on corneal fibroblasts spreading on 2D substrates following culture for 4 h in the presence of serum-free (SF) media with or without the addition of PDGF. (<b>A</b>) Representative pictures of samples that were fixed and labeled for F-actin (red) and nuclei (blue). Scale bar is 50 μm. (<b>B</b>) Graphs showing morphological data from 3 independent experiments. Error bars show standard deviations. (* <span class="html-italic">p</span> &lt; 0.05, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>The effect of Vim KO on corneal fibroblasts spreading on 2D substrates following culture for 24 h in the presence of serum-free (SF) media with or without the addition of PDGF. (<b>A</b>) Representative pictures of samples that were fixed and labeled for F-actin (red). Scale bar is 50 μm. (<b>B</b>) Graphs showing morphological data from 3 independent experiments. Error bars show standard deviations. (** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Vim KO cell spreading in 3D collagen matrices for 24 h in the presence of PDGF and SF media. (<b>A</b>) Representative pictures of samples that were fixed and labeled for F-actin. Scale bar is 50 μm. (<b>B</b>) Graphs are morphological data from 3 different experiments. (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Collagen matrix contraction induced by wild-type (WT) and Vim KO cells. Graphs are data from 3 different experiments. (** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Vim KD cell spreading in 3D collagen matrices for 24 h in the presence of PDGF and SF media.Representative pictures of cells that were fixed and labeled for F-actin. Scale bar is 50 μm.</p>
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<p>(<b>A</b>) Representative pictures of initial cell spreading of corneal fibroblasts cultured on 2D collagen-coated dishes. Cells were cultured for 4 and 24 h with media containing PDGF BB or PDGF BB + 2 µM WTA to block vimentin polymerization. After incubation, samples were fixed and stained for F-Actin (red), Nuclei (blue). Image width is 465 µm. (<b>B</b>) Graphs are data from 3 different experiments. (* <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; 0.0001).</p>
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<p>Reduction in traction force and global matrix contraction. (<b>A</b>) Confocal reflection microscopy was used to visualize cell–collagen matrix interactions. Cells cultured with WTA showed a reduction in the compaction of matrix, which can be visualized as a reduction in the accumulation of collagen fibers around cell extensions. Image width is 185 µm. (<b>B</b>) Global matrix contraction was also reduced when vimentin polymerization was blocked with WTA (* <span class="html-italic">p</span> &lt; 0.05), indicating a reduction in tractional force generation. Data are the average of 3 different experiments with 3 different samples per experiment.</p>
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<p>Vim KO cells transform into myofibroblasts. (<b>A</b>) Representative pictures of corneal fibroblasts cultured on 2D substrates for 6 days in serum-free media (SF) with or without TGFβ1. After incubation, cells were fixed and labeled for F-actin (red in top panel), αSMA (green in top panel), vimentin (cyan in bottom panel), and nuclei (red in bottom panel). Bar is 100 μm. (<b>B</b>) Western blot shows αSMA protein expression following incubation in TGFβ for all cell types. (<b>C</b>) Quantification of protein expression from Western blots. Data from 3 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>Increase in protein expression induced by TGFβ1 (as compared to SF media). All 3 cell types were incubated for 6 days with media containing TGFβ or SF basal media. Subsequently, protein was extracted and processed for mass spectrometry. (<b>A</b>) Increase in expression of known proteins associated with corneal myofibroblasts. (<b>B</b>) Additional proteins that were found to have at least twofold increases in all 3 cell types.</p>
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23 pages, 412 KiB  
Review
Involvement of Matricellular Proteins in Cellular Senescence: Potential Therapeutic Targets for Age-Related Diseases
by Motomichi Fujita, Manabu Sasada, Takuya Iyoda and Fumio Fukai
Int. J. Mol. Sci. 2024, 25(12), 6591; https://doi.org/10.3390/ijms25126591 - 15 Jun 2024
Cited by 1 | Viewed by 1106
Abstract
Senescence is a physiological and pathological cellular program triggered by various types of cellular stress. Senescent cells exhibit multiple characteristic changes. Among them, the characteristic flattened and enlarged morphology exhibited in senescent cells is observed regardless of the stimuli causing the senescence. Several [...] Read more.
Senescence is a physiological and pathological cellular program triggered by various types of cellular stress. Senescent cells exhibit multiple characteristic changes. Among them, the characteristic flattened and enlarged morphology exhibited in senescent cells is observed regardless of the stimuli causing the senescence. Several studies have provided important insights into pro-adhesive properties of cellular senescence, suggesting that cell adhesion to the extracellular matrix (ECM), which is involved in characteristic morphological changes, may play pivotal roles in cellular senescence. Matricellular proteins, a group of structurally unrelated ECM molecules that are secreted into the extracellular environment, have the unique ability to control cell adhesion to the ECM by binding to cell adhesion receptors, including integrins. Recent reports have certified that matricellular proteins are closely involved in cellular senescence. Through this biological function, matricellular proteins are thought to play important roles in the pathogenesis of age-related diseases, including fibrosis, osteoarthritis, intervertebral disc degeneration, atherosclerosis, and cancer. This review outlines recent studies on the role of matricellular proteins in inducing cellular senescence. We highlight the role of integrin-mediated signaling in inducing cellular senescence and provide new therapeutic options for age-related diseases targeting matricellular proteins and integrins. Full article
(This article belongs to the Section Bioactives and Nutraceuticals)
16 pages, 3425 KiB  
Article
Targeted Antisense Oligonucleotide-Mediated Skipping of Murine Postn Exon 17 Partially Addresses Fibrosis in D2.mdx Mice
by Jessica Trundle, Ngoc Lu-Nguyen, Alberto Malerba and Linda Popplewell
Int. J. Mol. Sci. 2024, 25(11), 6113; https://doi.org/10.3390/ijms25116113 - 1 Jun 2024
Cited by 2 | Viewed by 1052
Abstract
Periostin, a multifunctional 90 kDa protein, plays a pivotal role in the pathogenesis of fibrosis across various tissues, including skeletal muscle. It operates within the transforming growth factor beta 1 (Tgf-β1) signalling pathway and is upregulated in fibrotic tissue. Alternative splicing of Periostin’s [...] Read more.
Periostin, a multifunctional 90 kDa protein, plays a pivotal role in the pathogenesis of fibrosis across various tissues, including skeletal muscle. It operates within the transforming growth factor beta 1 (Tgf-β1) signalling pathway and is upregulated in fibrotic tissue. Alternative splicing of Periostin’s C-terminal region leads to six protein-coding isoforms. This study aimed to elucidate the contribution of the isoforms containing the amino acids encoded by exon 17 (e17+ Periostin) to skeletal muscle fibrosis and investigate the therapeutic potential of manipulating exon 17 splicing. We identified distinct structural differences between e17+ Periostin isoforms, affecting their interaction with key fibrotic proteins, including Tgf-β1 and integrin alpha V. In vitro mouse fibroblast experimentation confirmed the TGF-β1-induced upregulation of e17+ Periostin mRNA, mitigated by an antisense approach that induces the skipping of exon 17 of the Postn gene. Subsequent in vivo studies in the D2.mdx mouse model of Duchenne muscular dystrophy (DMD) demonstrated that our antisense treatment effectively reduced e17+ Periostin mRNA expression, which coincided with reduced full-length Periostin protein expression and collagen accumulation. The grip strength of the treated mice was rescued to the wild-type level. These results suggest a pivotal role of e17+ Periostin isoforms in the fibrotic pathology of skeletal muscle and highlight the potential of targeted exon skipping strategies as a promising therapeutic approach for mitigating fibrosis-associated complications. Full article
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<p><b>Bioinformatic analysis of Periostin isoforms.</b> (<b>A</b>) Phyre2 [<a href="#B25-ijms-25-06113" class="html-bibr">25</a>]-predicted tertiary structure highlighting the C-terminal region (red) for each protein-coding isoform. (<b>B</b>) Domain and motif prediction using ScanProsite [<a href="#B27-ijms-25-06113" class="html-bibr">27</a>]. (<b>C</b>) Protein–protein docking prediction of each of the 6 protein-coding Postn isoforms with interactants Tgf-β1, integrin alpha-5 (Itgαv), decorin, procollagen (col1α1), fibronectin (FN1), interleukin 3 (IL3), and interleukin 13 (IL13). For ease of complex orientation visualisation, the N-termini of each Periostin isoform (grey) is labelled in red, with the interactant in blue.</p>
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<p><b>Designed antisense oligonucleotides for m<span class="html-italic">Postn</span> exon 17 skipping.</b> SR protein-binding sites (<b>A</b>) were identified using ESEfinder [<a href="#B29-ijms-25-06113" class="html-bibr">29</a>]. SRSF1 (red), SRSF1 IgM-BRCA1 (pink), SRSF2 (blue), SRSF5 (green), and SRSF6 (yellow) sites were analysed at thresholds of 1.956, 1.867, 2.383, 2.67, and 2.676, respectively. (<b>B</b>) Lead PMO candidates and splice sites (ESEfinder) were mapped onto the mfold secondary structure prediction [<a href="#B30-ijms-25-06113" class="html-bibr">30</a>]. (<b>C</b>) Sequence and characteristics of each designed PMO.</p>
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<p><b>In vitro optimisation of <span class="html-italic">Postn</span> exon 17 skipping antisense PMOs.</b> TGF-β1 dose (<b>A</b>,<b>C</b>) and time response (<b>B</b>,<b>D</b>) PCR products were run on 3% agarose gels, with the longer product containing <span class="html-italic">Postn</span> exon 17 (<span class="html-italic">Ex17+ mPostn</span>) and the shorter one lacking exon 17 (<span class="html-italic">Ex17</span>− <span class="html-italic">mPostn</span>). The <span class="html-italic">Ex17 + mPostn</span> band pixel density was partially quantified on a GelAnalyzer and normalised to total band expression to give a percentage readout. (<b>E</b>) RT-qPCR results of fold change in <span class="html-italic">Postn</span> exon 17 expression in response to PMO1–3 in vitro. All treatment groups, at all doses, were significantly reduced compared to the +ve control. Negative control (−ve) = unstimulated Mh cells; positive control (+ve) = 10 ng/mL TGF-β1-stimulated Mh cells; and treatment groups = 10 ng/mL TGF-β1-stimulated Mh cells plus designated PMO1–3 dose treatment (0.5 µM, 1 µM, 2 µM, and 5 µM). Significance (one-way ANOVA with Tukey post hoc test) recorded as * = <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. Error bars = +/−SD. <span class="html-italic">N</span> = 3; qPCR was performed in triplicate.</p>
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<p><b>e17+ <span class="html-italic">Postn</span> mRNA expression in D2.<span class="html-italic">mdx</span> muscle.</b> RT-qPCR characterisation of e17+ <span class="html-italic">Postn</span> expression in the DIA (diaphragm), QUAD (quadricep), GAS (gastrocnemius), HRT (heart), and TA (tibialis anterior) in D2.<span class="html-italic">mdx</span> mice at 2, 6, and 24 weeks of age (N = 5). Outliers were identified via the ROUT method and omitted from the statistical analysis. The data were analysed by one-way ANOVA with Tukey post hoc tests and significance was recorded as *** = <span class="html-italic">p</span> &lt; 0.001; **** = <span class="html-italic">p</span> &lt; 0.0001. Error bars = +/−SD; qPCR was performed in triplicate.</p>
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<p><b>vivoPMO significantly reduced m<span class="html-italic">Postn</span> exon 17 expression and induced beneficial effect on muscles.</b> RT-qPCR analysis of e17+ (<b>A</b>) and total (<b>B</b>) <span class="html-italic">Postn</span> mRNA expression represented as fold change compared to wild type (N = 4–6). (<b>C</b>) Full-length protein expression assessment using Western blot (<b>D</b>) analysis. (<b>E</b>) DIA hydroxyproline analysis (indicative of collagen level). (<b>F</b>) Forelimb grip strength was measured as the average of 5 discrete measurements of maximum force normalised to body weight. Outliers were identified via the ROUT method and omitted from the statistical analysis. The data were analysed by one-way ANOVA with Tukey post hoc tests and significance was recorded as * = <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; 0.0001. Error bars = +/−SD; qPCR was performed in triplicate. Legend: ‘wt’ = Dba.2J wild type; ‘mdx’ = D2.<span class="html-italic">mdx</span> + Scramble vivoPMO; ‘mdx + pmo’ = D2.<span class="html-italic">mdx</span> + Postn exon 17 skipping vivoPMO.</p>
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16 pages, 2940 KiB  
Article
Characterisation and Expression of Osteogenic and Periodontal Markers of Bone Marrow Mesenchymal Stem Cells (BM-MSCs) from Diabetic Knee Joints
by Nancy Hussein, Josephine Meade, Hemant Pandit, Elena Jones and Reem El-Gendy
Int. J. Mol. Sci. 2024, 25(5), 2851; https://doi.org/10.3390/ijms25052851 - 1 Mar 2024
Viewed by 1412
Abstract
Type 2 diabetes mellitus (T2DM) represents a significant health problem globally and is linked to a number of complications such as cardiovascular disease, bone fragility and periodontitis. Autologous bone marrow mesenchymal stem cells (BM-MSCs) are a promising therapeutic approach for bone and periodontal [...] Read more.
Type 2 diabetes mellitus (T2DM) represents a significant health problem globally and is linked to a number of complications such as cardiovascular disease, bone fragility and periodontitis. Autologous bone marrow mesenchymal stem cells (BM-MSCs) are a promising therapeutic approach for bone and periodontal regeneration; however, the effect of T2DM on the expression of osteogenic and periodontal markers in BM-MSCs is not fully established. Furthermore, the effect of the presence of comorbidities such as diabetes and osteoarthritis on BM-MSCs is also yet to be investigated. In the present study, BM-MSCs were isolated from osteoarthritic knee joints of diabetic and nondiabetic donors. Both cell groups were compared for their clonogenicity, proliferation rates, MSC enumeration and expression of surface markers. Formation of calcified deposits and expression of osteogenic and periodontal markers were assessed after 1, 2 and 3 weeks of basal and osteogenic culture. Diabetic and nondiabetic BM-MSCs showed similar clonogenic and growth potentials along with comparable numbers of MSCs. However, diabetic BM-MSCs displayed lower expression of periostin (POSTN) and cementum protein 1 (CEMP-1) at Wk3 osteogenic and Wk1 basal cultures, respectively. BM-MSCs from T2DM patients might be suitable candidates for stem cell-based therapeutics. However, further investigations into these cells’ behaviours in vitro and in vivo under inflammatory environments and hyperglycaemic conditions are still required. Full article
(This article belongs to the Special Issue Stem Cells in Health and Disease 2.0)
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<p>CFUF-Fs and PDT assays of nondiabetic (ND) and diabetic (D) BM-MSCs. (<b>A</b>) Representative CFU-Fs of early-passage BM-MSCs isolated from an ND and (<b>B</b>) a D donor. (<b>C</b>) CFU-Fs% in ND and D donors. (<b>D</b>) Population doubling, (<b>E</b>) accumulative population doubling and (<b>F</b>) population doubling time in ND and D BM-MSCs. Data are presented as mean ± SD (<span class="html-italic">n</span> = 3) and analysed using unpaired t test.</p>
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<p>Enumeration of MSC population in diabetic (D) BM-MSCs. (<b>A</b>) Gating to exclude dead cells and debris based on their forward and side scatter. (<b>B</b>) Gating to include living cells based on their negative uptake of fixable viability stain. (<b>C</b>) Gating to include CD73<sup>+</sup>CD90<sup>+</sup> cells in quadrant Q1-UR. (<b>D</b>) Gating to include CD73<sup>+</sup>CD90<sup>+</sup>CD105<sup>+</sup>CD14<sup>−</sup> cells in quadrant Q2-LR. (<b>E</b>) Gating to include CD73<sup>+</sup>CD90<sup>+</sup>CD105<sup>+</sup>CD14<sup>−</sup>CD19<sup>−</sup>CD34<sup>−</sup> in quadrant Q3-LL. (<b>F</b>) Gating to include CD73<sup>+</sup>CD90<sup>+</sup>CD105<sup>+</sup>CD14<sup>−</sup>CD19<sup>−</sup>CD34<sup>−</sup>CD45<sup>−</sup>HLA-DR<sup>−</sup> in quadrant Q4-LL. The same approach was employed with BM-MSCs from nondiabetic (ND) and D donors. (<b>G</b>) Expression of MSC markers in ND and D BM-MSCS. (<b>H</b>) Enumeration of MSC population in ND and D MSCs. Data are presented as mean ± SD (<span class="html-italic">n</span> = 3) and analysed using unpaired <span class="html-italic">t</span> test.</p>
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<p>Comparing osteogenic differentiation of diabetic (D) and nondiabetic (ND) BM-MSCs: (<b>a</b>) Alkaline phosphatase stain of D and ND BM-MSCs under basal and osteogenic conditions after 1, 2 and 3 weeks of culture. (<b>b</b>) Alizarin Red (AR) stain of ND and D BM-MSCs under basal and osteogenic conditions after 1, 2 and 3 weeks of culture. (<b>c</b>) Quantification of AR stain of ND and D BM-MSCs. Data are presented as mean ± SD (<span class="html-italic">n</span> = 3), analysed using unpaired <span class="html-italic">t</span> test and showed no significant difference (* <span class="html-italic">p</span> &lt; 0.05)).</p>
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<p>Comparing the relative changes in gene expression of periodontal markers (top panel: COL1A1, POSTN and CEMP-1) and osteogenic markers (lower panel: ALPL, Runx2, OCN) in ND and D BM-MSCs cultured under basal or osteogenic media for 1, 2 and 3 weeks as well as baseline untreated cells (0 time point). Data are presented as mean value ± SEM (<span class="html-italic">n</span> = 3) normalised to housekeeping (HPRT1) and were statistically analysed using unpaired <span class="html-italic">t</span> test for unmatched groups, paired <span class="html-italic">t</span> test for matched groups and repeated measures ANOVA for comparing time points, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Comparing the relative changes in gene expression of bone homeostasis markers: RANKL, OPG, OPG/RANKL ratio) in ND and D BM-MSCs cultured under basal or osteogenic media for 1, 2 and 3 weeks as well as baseline untreated cells (0 time point). Data are presented as mean value ± SEM (<span class="html-italic">n</span> = 3) normalised to housekeeping (HPRT1) and were statistically analysed using unpaired <span class="html-italic">t</span> test for unmatched groups, paired <span class="html-italic">t</span> test for matched groups and repeated measures ANOVA for comparing time points. There was no significant difference between D and ND BMSCS, culture conditions or time points (NS &gt; 0.05).</p>
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