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Search Results (1,209)

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16 pages, 1308 KiB  
Review
Correlating Ultrastructural Changes in the Invasion Area of Colorectal Cancer with CT and MRI Imaging
by Joanna Urbaniec-Stompór, Maciej Michalak and Janusz Godlewski
Int. J. Mol. Sci. 2024, 25(18), 9905; https://doi.org/10.3390/ijms25189905 - 13 Sep 2024
Viewed by 199
Abstract
The cancer invasion of the large intestine, a destructive process that begins within the mucous membrane, causes cancer cells to gradually erode specific layers of the intestinal wall. The normal tissues of the intestine are progressively replaced by a tumour mass, leading to [...] Read more.
The cancer invasion of the large intestine, a destructive process that begins within the mucous membrane, causes cancer cells to gradually erode specific layers of the intestinal wall. The normal tissues of the intestine are progressively replaced by a tumour mass, leading to the impairment of the large intestine’s proper morphology and function. At the ultrastructural level, the disintegration of the extracellular matrix (ECM) by cancer cells triggers the activation of inflammatory cells (macrophages) and connective tissue cells (myofibroblasts) in this area. This accumulation and the functional interactions between these cells form the tumour microenvironment (TM). The constant modulation of cancer cells and cancer-associated fibroblasts (CAFs) creates a specific milieu akin to non-healing wounds, which induces colon cancer cell proliferation and promotes their survival. This review focuses on the processes occurring at the “front of cancer invasion”, with a particular focus on the role of the desmoplastic reaction in neoplasm development. It then correlates the findings from the microscopic observation of the cancer’s ultrastructure with the potential of modern radiological imaging, such as computer tomography (CT) and magnetic resonance imaging (MRI), which visualizes the tumour, its boundaries, and the tissue reactions in the large intestine. Full article
(This article belongs to the Special Issue Molecular Mechanisms and Therapies of Colorectal Cancer 3.0)
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<p>The role of enzymes and signalling molecules involved in promotion and progression of CRC.</p>
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<p>Comparison of two different growth patterns of large intestine cancer. The first one is expansive, with a well-demarcated tumour mass boundary, which pushes away the healthy tissue. The second one is infiltrative, without a demarcated mass boundary, with cords of cancer cells invading the healthy tissue.</p>
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<p>Illustration of different T-stages of CRC and their relation to layers of rectum.</p>
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12 pages, 1072 KiB  
Article
Connecting Gene Variation to Treatment Outcomes in Metastatic Castration-Resistant Prostate Adenocarcinoma: Insights into Second-Generation Androgen Receptor Axis-Targeted Therapies
by Ana Vaz-Ferreira, Valéria Tavares, Inês Guerra de Melo, Patrícia Rafaela Rodrigues, Ana Afonso, Maria Joaquina Maurício and Rui Medeiros
Int. J. Mol. Sci. 2024, 25(18), 9874; https://doi.org/10.3390/ijms25189874 - 12 Sep 2024
Viewed by 252
Abstract
Prostate cancer (PC) is one of the most commonly diagnosed tumours among men. Second-generation androgen receptor axis-targeted (ARAT) agents, namely abiraterone acetate (AbA) and enzalutamide (ENZ), are currently used in the management of metastatic castration-resistant PC (mCRPC). However, the treatment is challenging due [...] Read more.
Prostate cancer (PC) is one of the most commonly diagnosed tumours among men. Second-generation androgen receptor axis-targeted (ARAT) agents, namely abiraterone acetate (AbA) and enzalutamide (ENZ), are currently used in the management of metastatic castration-resistant PC (mCRPC). However, the treatment is challenging due to the lack of prognostic biomarkers. Meanwhile, single-nucleotide polymorphisms (SNPs) have emerged as potential prognostic indicators of mCRPC. Thus, this study evaluated the impact of relevant SNPs on the treatment outcomes of 123 mCRPC patients enrolled in a hospital-based cohort study. The CYP17A1 rs2486758 C allele was associated with a 50% reduction in the risk of developing castration resistance (hazard ratio (HR) = 0.55; p = 0.003). Among patients without metastasis at tumour diagnosis and under AbA, a marginal association between YBX1 rs10493112 and progression-free survival was detected (log-rank test, p = 0.056). In the same subgroup, significant associations of HSD3B1 rs1047303 (CC/CA vs. AA; HR = 3.41; p = 0.025), YBX1 rs12030724 (AT vs. AA; HR = 3.54; p = 0.039) and YBX1 rs10493112 (log-rank test, p = 0.041; CC vs. AA/AC; HR = 3.22; p = 0.053) with overall survival were also observed, which were confirmed by multivariate Cox analyses. Although validation with larger cohorts is required, these findings suggest that SNPs could enhance the prognosis assessment of mCRPC patients, leading to a more personalised treatment. Full article
(This article belongs to the Special Issue Recent Molecular Research in Virology and Oncology)
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<p>Time to castration resistance (TCR) by Kaplan–Meier and Log-rank test for mCRPC patients (N = 116), according to <span class="html-italic">CYP17A1</span> rs2486758 genotypes. Patients with the C allele had a prolonged TCR compared to those carrying the TT genotype (<span class="html-italic">p</span> = 0.003).</p>
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<p>Overall survival (OS) by Kaplan–Meier and Log-rank test for mCRPC patients with localised tumour at diagnosis and under AbA-based treatment (N = 24), according to <span class="html-italic">HSD3B1</span> rs1047303 (<b>a</b>), <span class="html-italic">YBX1</span> rs12030724 (<b>b</b>) and <span class="html-italic">YBX1</span> rs10493112 (<b>c</b>) genotypes. Patients with the <span class="html-italic">HSD3B1</span> rs1047303 C allele genotypes had a lower OS compared to those carrying the AA genotype (<span class="html-italic">p</span> = 0.014). Patients with the <span class="html-italic">YBX1</span> rs12030724 AT genotype had a lower OS than AA genotype carriers (<span class="html-italic">p</span> = 0.027). Patients with the <span class="html-italic">YBX1</span> rs10493112 CC genotype had a lower OS than their counterparts (<span class="html-italic">p</span> = 0.041).</p>
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17 pages, 2274 KiB  
Review
Conjunctival Melanoma: A Clinical Review and Update
by Karam Butt, Rumana Hussain, Sarah E. Coupland and Yamini Krishna
Cancers 2024, 16(18), 3121; https://doi.org/10.3390/cancers16183121 - 10 Sep 2024
Viewed by 300
Abstract
Conjunctival melanoma (Co-M) is an aggressive, invasive eye and eyelid cancer. Its global incidence of ~1 in a million is increasing at a rate ratio of ~1.4, but this rises sharply in over 65-year-olds. Although rare, Co-M has a devastating impact on the [...] Read more.
Conjunctival melanoma (Co-M) is an aggressive, invasive eye and eyelid cancer. Its global incidence of ~1 in a million is increasing at a rate ratio of ~1.4, but this rises sharply in over 65-year-olds. Although rare, Co-M has a devastating impact on the lives of those who develop it. Co-M is often misdiagnosed or overlooked, leading to vision loss either from the destructive effects of the tumour or side effects of therapy, facial disfigurement from radical surgery, and death from metastases. Due to its rarity, there is limited evidence for diagnosis and management; hence, there is no standardised treatment and not all cases are referred to a specialised ocular oncology centre. Recent progress in cancer immunology and genetics have revolutionised the treatment of cutaneous melanomas, which share some similarities to Co-M. Importantly, a better understanding of Co-M and its precursor lesions is urgently needed to lead to the development of novel targeted and immunotherapies both for local tumour control and disseminated disease. This review aims to provide a comprehensive clinical overview of the current knowledge regarding Co-M, its epidemiology, pathogenesis, presentation, diagnosis and recent changes in the classification of its precursor lesions, management, and recent advances in novel biological therapies for personalised treatment of this disease. Full article
(This article belongs to the Special Issue Current Progress and Research Trends in Ocular Oncology)
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<p>Anterior segment photographs of low- and high-grade C-MIL (preinvasive disease) and Co-M (invasive disease). The actual grading was confirmed on histomorphological assessment.</p>
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<p>Co-M histological micrographs. Haematoxylin and eosin staining photomicrographs showing an orbital exenteration specimen with Co-M at low magnification (<b>top left</b>), medium (<b>top right</b>) and higher magnification (<b>bottom left</b>).</p>
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<p>Photomicrographs representing the C-MIL grading system. Haematoxylin and eosin section with corresponding immunohistochemistry for each of the C-MIL scoring grades [<a href="#B88-cancers-16-03121" class="html-bibr">88</a>].</p>
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15 pages, 2577 KiB  
Article
In Silico Exploration of AHR-HIF Pathway Interplay: Implications for Therapeutic Targeting in ccRCC
by Francesco Gregoris, Giovanni Minervini and Silvio C. E. Tosatto
Genes 2024, 15(9), 1167; https://doi.org/10.3390/genes15091167 - 5 Sep 2024
Viewed by 337
Abstract
The oxygen-sensing pathway is a crucial regulatory circuit that defines cellular conditions and is extensively exploited in cancer development. Pathogenic mutations in the von Hippel–Lindau (VHL) tumour suppressor impair its role as a master regulator of hypoxia-inducible factors (HIFs), leading to constitutive HIF [...] Read more.
The oxygen-sensing pathway is a crucial regulatory circuit that defines cellular conditions and is extensively exploited in cancer development. Pathogenic mutations in the von Hippel–Lindau (VHL) tumour suppressor impair its role as a master regulator of hypoxia-inducible factors (HIFs), leading to constitutive HIF activation and uncontrolled angiogenesis, increasing the risk of developing clear cell renal cell carcinoma (ccRCC). HIF hyperactivation can sequester HIF-1β, preventing the aryl hydrocarbon receptor (AHR) from correctly activating gene expression in response to endogenous and exogenous ligands such as TCDD (dioxins). In this study, we used protein–protein interaction networks and gene expression profiling to characterize the impact of VHL loss on AHR activity. Our findings reveal specific expression patterns of AHR interactors following exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and in ccRCC. We identified several AHR interactors significantly associated with poor survival rates in ccRCC patients. Notably, the upregulation of the androgen receptor (AR) and retinoblastoma-associated protein (RB1) by TCDD, coupled with their respective downregulation in ccRCC and association with poor survival rates, suggests novel therapeutic targets. The strategic activation of the AHR via selective AHR modulators (SAhRMs) could stimulate its anticancer activity, specifically targeting RB1 and AR to reduce cell cycle progression and metastasis formation in ccRCC. Our study provides comprehensive insights into the complex interplay between the AHR and HIF pathways in ccRCC pathogenesis, offering novel strategies for targeted therapeutic interventions. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
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<p>Pie chart showing the distribution of AHR interactors across databases.</p>
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<p>Merged AHR protein–protein interaction network. The colour code represents interactors following 6 h exposure to 100 nM of TCDD. Red is for upregulated proteins and blue is for downregulated, while nodes with an undefined expression level are represented in grey. Edges are coloured according to their node derivation: green is for interactions found in BIOGRID, violet represents data from HIPPIE, and orange for those from IntAct, while yellow and blue are for KEGG and STRING, respectively. The thickness of the lines represents the confidence score of the interactions as defined by each database, while the colours denote the different sources of the interactions, with each database assigned a distinct colour.</p>
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<p>Networks of interactors clustered by functional relationship with the AHR. Panel (<b>A</b>) groups proteins upregulated after exposition to TCDD, while downregulated nodes after exposition to TCDD are reported in panel (<b>B</b>). Red borders mark upregulated nodes, while blue is for those that are downregulated. Fulfilled red or blue nodes are used to highlight up- or downregulated nodes in both TCDD and ccRCC samples. The thickness of the lines represents the number of sources reporting the interaction.</p>
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<p>Networks of AHR interactors that have significantly worse survival from the Kaplan–Meier analysis. Panel (<b>A</b>) groups proteins upregulated after exposition to TCDD, while downregulated nodes after exposition to TCDD are reported in panel (<b>B</b>). Red borders mark upregulated nodes, while blue is for those that were downregulated. Fulfilled red or blue nodes are used to highlight up- or downregulated nodes in both TCDD and ccRCC samples. The thickness of the lines represents the number of sources reporting the interaction.</p>
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15 pages, 958 KiB  
Review
The Role of circHIPK3 in Tumorigenesis and Its Potential as a Biomarker in Lung Cancer
by Eryk Siedlecki, Piotr Remiszewski and Rafał Stec
Cells 2024, 13(17), 1483; https://doi.org/10.3390/cells13171483 - 4 Sep 2024
Viewed by 391
Abstract
Lung cancer treatment and detection can be improved by the identification of new biomarkers. Novel approaches in investigating circular RNAs (circRNAs) as biomarkers have yielded promising results. A circRNA molecule circHIPK3 was found to be widely expressed in non-small-cell lung cancer (NSCLC) cells, [...] Read more.
Lung cancer treatment and detection can be improved by the identification of new biomarkers. Novel approaches in investigating circular RNAs (circRNAs) as biomarkers have yielded promising results. A circRNA molecule circHIPK3 was found to be widely expressed in non-small-cell lung cancer (NSCLC) cells, where it plays a crucial role in lung cancer tumorigenesis. CircHIPK3 promotes lung cancer progression by sponging oncosuppressive miRNAs such as miR-124, miR-381-3p, miR-149, and miR-107, which results in increased cell proliferation, migration, and resistance to therapies. Inhibiting circHIPK3 has been demonstrated to suppress tumour growth and induce apoptosis, which suggests its potential use in the development of new lung cancer treatment strategies targeting circHIPK3-related pathways. As a biomarker, circHIPK3 shows promise for early detection and monitoring of lung cancer. CircHIPK3 increased expression levels in lung cancer cells, and its potential link to metastasis risk highlights its clinical relevance. Given the promising preliminary findings, more clinical trials are needed to validate circHIPK3 efficacy as a biomarker. Moreover, future research should determine if the mechanisms discovered in NSCLC apply to small cell lung cancer (SCLC) to investigate circHIPK3-targeted therapies for SCLC. Full article
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<p>Biogenesis of circHIPK3 involving intron-pairing-driven circularization model and subsequent sponging of miRNAs in the cytoplasm. CircHIPK3 functions as a miRNA sponge, influencing mRNA expression at the post-transcriptional level and thereby promoting or inhibiting progression in various cancers. This circRNA is formed in the nucleus and exported via the nuclear pore to the cytoplasm, where it binds with the miRNAs. The miRNAs are present in the cytoplasm and formed out of pre-miRNAs in the nucleus.</p>
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<p>Location on 11p13 chromosome and the formation of circHIPK3 out of exon 2 surrounded by Alu repeats. CircHIPK3 is formed primarily in an intron-pairing-driven circularization model, which is also known as the direct back-splicing mechanism. Reverse complementary sequences flanking introns facilitate the process of back-splicing. These flanking complementary sequences, particularly Alu elements, are essential for exon circularization. Perfectly matched complementary sequences enhance the expression of circRNAs.</p>
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37 pages, 2485 KiB  
Review
The Antitumour Mechanisms of Carotenoids: A Comprehensive Review
by Andrés Baeza-Morales, Miguel Medina-García, Pascual Martínez-Peinado, Sandra Pascual-García, Carolina Pujalte-Satorre, Ana Belén López-Jaén, Rosa María Martínez-Espinosa and José Miguel Sempere-Ortells
Antioxidants 2024, 13(9), 1060; https://doi.org/10.3390/antiox13091060 - 30 Aug 2024
Viewed by 639
Abstract
Carotenoids, known for their antioxidant properties, have garnered significant attention for their potential antitumour activities. This comprehensive review aims to elucidate the diverse mechanisms by which carotenoids exert antitumour effects, focusing on both well-established and novel findings. We explore their role in inducing [...] Read more.
Carotenoids, known for their antioxidant properties, have garnered significant attention for their potential antitumour activities. This comprehensive review aims to elucidate the diverse mechanisms by which carotenoids exert antitumour effects, focusing on both well-established and novel findings. We explore their role in inducing apoptosis, inhibiting cell cycle progression and preventing metastasis by affecting oncogenic and tumour suppressor proteins. The review also explores the pro-oxidant function of carotenoids within cancer cells. In fact, although their overall contribution to cellular antioxidant defences is well known and significant, some carotenoids can exhibit pro-oxidant effects under certain conditions and are able to elevate reactive oxygen species (ROS) levels in tumoural cells, triggering mitochondrial pathways that would lead to cell death. The final balance between their antioxidant and pro-oxidant activities depends on several factors, including the specific carotenoid, its concentration and the redox environment of the cell. Clinical trials are discussed, highlighting the conflicting results of carotenoids in cancer treatment and the importance of personalized approaches. Emerging research on rare carotenoids like bacterioruberin showcases their superior antioxidant capacity and selective cytotoxicity against aggressive cancer subtypes, such as triple-negative breast cancer. Future directions include innovative delivery systems, novel combinations and personalized treatments, aiming to enhance the therapeutic potential of carotenoids. This review highlights the promising yet complex landscape of carotenoid-based cancer therapies, calling for continued research and clinical exploration. Full article
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<p>Structure and classification of the most studied carotenoids in cancer. Carotenoids are divided into two main groups, xanthophylls and carotenes. These can also undergo modifications and generate new carotenoids called apocarotenoids. Hydroxyl groups are represented in red. Chemical structures obtained from ChemSpider (Royal Society of Chemistry).</p>
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<p>Scheme of the pro-oxidant carotenoid therapy against cancer. Carotenoids exert pro-oxidant effects to selectively target cancer cells, promoting oxidative stress-induced cell death while potentially protecting normal cells. CAR, carotenoid; ROS, reactive oxygen species. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Scheme of direct antitumoural effects of carotenoids on cancer cells. Carotenoids can induce apoptosis, necroptosis, autophagy or cell differentiation; enhance gap junctional communication; and also exhibit antiangiogenic, antimetastatic, multidrug resistance and antiproliferative effects. CAR, carotenoids. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Mechanism of action of the anticancer properties of carotenoids. Graphical representation of the most common mechanisms of action of carotenoids in tumour cells based on the reviewed literature. Arrows with pointed ends indicate activation, while T-bar arrows indicate inhibition. ΔΨm, membrane potential; Akt, protein kinase B; Bax, Bcl-2-associated X-protein; Bcl-2, B-cell lymphoma 2 protein; CAR, carotenoid; CDK, cyclin-dependent kinases; GADD45α, growth arrest and DNA-damage-inducible protein 45 α; MMP, matrix metalloproteinase; NF-κB, nuclear factor-kappa B; PARP, poly ADP-ribose polymerase; ROS, reactive oxygen species; SKP2, S-phase kinase-associated protein 2. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Chemical structure and formulation of bacterioruberin and its derivatives. Bacterioruberin can be modified and converted into bisanhydrobacterioruberin, monoanhydrobacterioruberin or 2-isopentenyl-3,4-dehydrorhodopin. Hydroxyl groups are represented in red. Chemical structures obtained from ChemSpider (Royal Society of Chemistry).</p>
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19 pages, 2957 KiB  
Article
Prostate Cancer’s Silent Partners: Fibroblasts and Their Influence on Glutamine Metabolism Manipulation
by Pia V. Hönscheid, Gustavo B. Baretton, Martin Puhr, Tiziana Siciliano, Justus S. Israel, Matthias B. Stope, Celina Ebersbach, Alicia-Marie K. Beier, Christian Thomas and Holger H. H. Erb
Int. J. Mol. Sci. 2024, 25(17), 9275; https://doi.org/10.3390/ijms25179275 - 27 Aug 2024
Viewed by 405
Abstract
Cancer-associated fibroblast (CAF)s in the tumour microenvironment (TME) modulate the extracellular matrix, interact with cancer cells, and facilitate communication with infiltrating leukocytes, significantly contributing to cancer progression and therapeutic response. In prostate cancer (PCa), CAFs promote malignancy through metabolic rewiring, cancer stem cell [...] Read more.
Cancer-associated fibroblast (CAF)s in the tumour microenvironment (TME) modulate the extracellular matrix, interact with cancer cells, and facilitate communication with infiltrating leukocytes, significantly contributing to cancer progression and therapeutic response. In prostate cancer (PCa), CAFs promote malignancy through metabolic rewiring, cancer stem cell regulation, and therapy resistance. Pre-clinical studies indicate that targeting amino acid metabolism, particularly glutamine (Gln) metabolism, reduces cancer proliferation and stemness. However, most studies lack the context of CAF–cancer interaction, focusing on monocultures. This study assesses the influence of CAFs on PCa growth by manipulating Gln metabolism using colour-labelled PCa cell lines (red) and fibroblast (green) in a co-culture system to evaluate CAFs’ effects on PCa cell proliferation and clonogenic potential. CAFs increased the proliferation of hormone-sensitive LNCaP cells, whereas the castration-resistant C4-2 cells were unaffected. However, clonogenic growth increased in both cell lines. Gln deprivation and GLS1 inhibition experiments revealed that the increased growth rate of LNCAP cells was associated with increased dependence on Gln, which was confirmed by proteomic analyses. Tissue analysis of PCa patients revealed elevated GLS1 levels in both the PCa epithelium and stroma, suggesting that GLS1 is a therapeutic target. Moreover, the median overall survival analysis of GLS1 expression in the PCa epithelium and stroma identified a “high-risk” patient group that may benefit from GLS1-targeted therapies. Therefore, GLS1 targeting appears promising in castration-resistant PCa patients with high GLS1 epithelium and low GLS1 stromal expression. Full article
(This article belongs to the Special Issue Molecular Advances in Cancer and Cell Metabolism)
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<p>Establishment of prostate cancer (PCa) cell lines expressing mKATE2-NLS. (<b>A</b>) LNCaP and C4-2 cells were transduced with a MOI of 2.5, 5, and 10. Positive cells were detected using the Keyence microscope and analysed with the BZ-X800 Analyzer software. The graphical illustration of the mKATE2-NLS positive cells for each cell line was plotted as a box and whisker plot (min to max) of the six technical replicates. (<b>B</b>) Representative pictures of each cell line before blasticidin selection are shown of the chosen MOI compared with the untransduced cells (negative CTRL). The scalebar represents 100 μm. (<b>C</b>) Analysis of positive cells before and after blasticidin selection. mKATE2-NLS positive cells were detected using the BZ-X800 microscope (Keyence GmBH, Neu-Isenburg, Germany) and analysed with the BZ-X800 Analyzer software (Keyence GmbH). The graphical illustration of the mKATE2-NLS positive cells for each cell line was plotted as the mean ± SD of six technical replicates. An unpaired student’s T-test was used to detect significant differences. <span class="html-italic">p</span>-values ≤ 0.05 were considered significant. ***: <span class="html-italic">p</span> ≤ 0.001. (<b>D</b>) Correlation analysis of cell number determined by mKATE2 counting and cell confluence using the S3 Incucyte Live-Cell Analysis System (Sartorius AG, Göttingen, Germany). Cell lines were seeded in triplicates into 96-well plates, and confluence and mKATE2-NLS numbers were determined for 5 days. Pearson correlation (r) was calculated using Prism software (Boston, MA, USA).</p>
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<p>Influence of glutamine (Gln) deprivation on selected prostate cancer (PCa) cell growth co-cultured with cancer-associated fibroblast (CAF) cells. (<b>A</b>) Influence of Gln deprivation on the LNCaP cell proliferation in the presence or absence of CAF cells. Red object count assessed proliferation for 96 h. Relative changes in AUC values were calculated from the growth curve experiments. Data were plotted as mean ± SEM of three biological replicates. Significant differences were identified using two-way ANOVA. <span class="html-italic">p</span>-values ≤ 0.05 were considered significant. **: <span class="html-italic">p</span> ≤ 0.01. (<b>B</b>) Influence of Gln deprivation on the C4-2 cell proliferation in the presence or absence of CAF cells. Red object count assessed proliferation for 96 h. Relative changes in AUC values were calculated from the growth curve experiments. Data were plotted as mean ± SEM of three biological replicates. Significant differences were identified using two-way ANOVA. <span class="html-italic">p</span>-values ≤ 0.05 were considered significant. **: <span class="html-italic">p</span> ≤ 0.01, ***: <span class="html-italic">p</span> ≤ 0.001 (<b>C</b>) Representative images of the clonogenic assays of the cell lines LNCaP and colony-forming efficiency (CFE) calculated from the clonogenic assays of LNCaP cells co-cultured with CAF cells after Gln deprivation. Colony number (≥50 cells/colony) was scored 10 days after plating. The results are expressed as box and whisker plots (min to max) of 4 biological replicates and are compared with monocultured cells. (<b>D</b>) Representative images of the clonogenic assays of the cell lines C4-2 cells and colony-forming efficiency (CFE) calculated from the clonogenic assays of C4-2 cells co-cultured with CAF cells after Gln deprivation. Colony number (≥50 cells/colony) was scored 10 days after plating. The results are expressed as box and whisker plots (min to max) of 4 biological replicates and are compared with monocultured cells.</p>
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<p>PathfindR and GSEA analysis results for differentially expressed genes after co-culturing LNCaP and CAF cells. (<b>A</b>) Graphical representation of the experimental procedure. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 26 August 2023). LNCaP mKATE2-nls cells (1 × 10<sup>6</sup>) and CAF eGFP-nls cells (5 × 10<sup>5</sup>) were seeded into a 10 cm<sup>2</sup> dish and cultured for 96 h. The different cells were then sorted and monocultured and the sorted cells were lysed for mass spectrometry. (<b>B</b>) Volcano plot of differentially expressed proteins in LNCaP cells after co-culturing the cells for 96 h with CAFs. Colour coding: gray = no statistically significant difference and not differentially expressed; blue = statistically significantly downregulated proteins, red = statistically significantly upregulated proteins. (<b>C</b>) The top 20 enriched pathways were identified by “pathfindR” pathway analysis using Reactome pathways, ordered by −log10(Padj) in LNCaP cells after co-culturing the cells for 96 h with CAF cells. (<b>D</b>) Selected metabolic gene sets enriched in co-cultured LNCaP cells using the REACTOME database. (<b>E</b>) Selected GSEA plots of metabolism of amino acids and derivates for LNCaP cells co-cultured with CAF.</p>
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<p>Influence of CB839 on selected prostate cancer (PCa) cell proliferation co-growth with cancer-associated fibroblast (CAF) cells. (<b>A</b>) qPCR analysis of relative GLS mRNA levels in LNCaP and C4-2 cells (<span class="html-italic">n</span> = 4). mRNA levels were normalised to HPRT1. The results are expressed as box and whisker plots (min to max) of the 4 biological replicates. (<b>B</b>) Representative Western blots of GLS1 (55–65 kDa) and the housekeeper GAPDH (37 kDa). Chameleon duo pre-stained protein ladder (Ladder) was used as protein size standard. (<b>C</b>) Densiometric Western blot analysis of GLS1 protein levels in LNCaP and C4-2 cells (<span class="html-italic">n</span> = 4). Protein levels were normalised to GAPDH. The results are expressed as box and whisker plots (min to max) of 4 biological replicates. (<b>D</b>) Influence of CB-839 on the LNCaP cell proliferation in the presence or absence of CAF cells. Red object count assessed proliferation for 96 h. Relative changes in AUC values were calculated from the growth curve experiments. Data were plotted as mean ± SEM of three biological replicates. Significant differences were identified using two-way ANOVA. <span class="html-italic">p</span>-values ≤ 0.05 were considered significant. **: <span class="html-italic">p</span> ≤ 0.01. (<b>E</b>) Influence of CB-839 on the C4-2 cell proliferation in the presence or absence of CAF cells. Red object count assessed proliferation for 96 h. Relative changes in AUC values were calculated from the growth curve experiments. Data were plotted as mean ± SEM of three biological replicates. Significant differences were identified using two-way ANOVA. <span class="html-italic">p</span>-values ≤ 0.05 were considered significant. ***: <span class="html-italic">p</span> ≤ 0.001. (F + G) Representative images of the clonogenic assays of the cell lines LNCaP (<b>F</b>) and C4-2 (<b>G</b>). (H + I) Colony-forming efficiency (CFE) calculated from the clonogenic assays of LNCaP (<b>H</b>) and C4-2. (<b>I</b>) cells co-cultured CAF cells after CB-839 treatment. Colony number (≥50 cells/colony) was scored 10 days after plating. The results are expressed as box and whisker plots (min to max) of 4 biological replicates and are compared with monocultured cells *: <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>GLS1 expression is elevated in malignant epithelial and stroma prostate areas. (<b>A</b>) Immunohistochemical staining for GLS1 of representative benign and malignant prostate tissue. Scale bar = 100 μm. (<b>B</b>) Quantification of GLS1 after immunohistochemistry (IHC) staining of benign and malignant prostate tissue. Staining was evaluated using the immunoreactivity score (IRS), ranging from 0 to 12 for GLS1. The results are expressed as box and whisker plots (min to max). Significant differences were identified using one-way ANOVA. <span class="html-italic">p</span>-values ≤ 0.05 were considered significant. ***: <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>) Pearson correlation of GLS1 expression in benign and malignant PCa areas. The r-values are displayed in a heat map.</p>
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<p>Kaplan–Meier analysis of the prostate cancer (PCa) cohort according to the GLS1 expression reveals a high-risk group with bad clinical outcomes. Median overall survival (MS) analysis was performed based on GLS1 expression in the epithelium (<b>A</b>), stroma (<b>B</b>), and combined expression in the epithelium and stroma (<b>C</b>). For combination analysis, data were grouped into the following expression patterns (epithelium/stroma): high/high, high/low, low/high, and low/low. The median GLS1-IRS score was selected as the threshold. (<b>D</b>) Kaplan–Meier analysis of the identified high-risk group (high/low) compared with the rest of the PCa cohort. Abbreviations: HR—hazard ratio (log-rank). MS—median overall survival.</p>
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22 pages, 4650 KiB  
Article
The Impact of Liquid Biopsy in Advanced Ovarian Cancer Care
by Antoni Llueca, Sarai Canete-Mota, Anna Jaureguí, Manuela Barneo, Maria Victoria Ibañez, Alexander Neef, Enrique Ochoa, Sarai Tomas-Perez, Josep Mari-Alexandre, Juan Gilabert-Estelles, Anna Serra, Maria Teresa Climent, Carla Bellido, Nuria Ruiz, Blanca Segarra-Vidal and Maria Llueca
Diagnostics 2024, 14(17), 1868; https://doi.org/10.3390/diagnostics14171868 - 26 Aug 2024
Viewed by 415
Abstract
Introduction: Ovarian cancer is the third most common gynaecological cancer and has a very high mortality rate. The cornerstone of treatment is complete debulking surgery plus chemotherapy. Even with treatment, 80% of patients have a recurrence. Circulating tumour DNA (ctDNA) has been shown [...] Read more.
Introduction: Ovarian cancer is the third most common gynaecological cancer and has a very high mortality rate. The cornerstone of treatment is complete debulking surgery plus chemotherapy. Even with treatment, 80% of patients have a recurrence. Circulating tumour DNA (ctDNA) has been shown to be useful in the control and follow-up of some tumours. It could be an option to define complete cytoreduction and for the early diagnosis of recurrence. Objective: We aimed to demonstrate the usefulness of ctDNA and cell-free DNA (cfDNA) as a marker of complete cytoreduction and during follow-up in patients with advanced ovarian cancer. Material and Methods: We selected 22 women diagnosed with advanced high-grade serous ovarian cancer, of which only 4 had complete records. We detected cfDNA by polymerase chain reaction (PCR), presented as ng/mL, and detected ctDNA with droplet digital PCR (ddPCR). We calculated Pearson correlation coefficients to evaluate correlations among cfDNA, ctDNA, and cancer antigen 125 (CA125), a biomarker. Results: The results obtained in the evaluation of cfDNA and ctDNA and their correlation with tumour markers and the radiology of patients with complete follow-up show disease progression during the disease, stable disease, or signs of recurrence. cfDNA and ctDNA correlated significantly with CA125. Following cfDNA and ctDNA over time indicated a recurrence several months earlier than computed tomography and CA125 changes. Conclusion: An analysis of cfDNA and ctDNA offers a non-invasive clinical tool for monitoring the primary tumour to establish a complete cytoreduction and to diagnose recurrence early. Full article
(This article belongs to the Special Issue Pathology and Diagnosis of Ovarian Cancer)
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<p>(<b>A</b>) Summary of patient 5’s clinical information, including the treatment type and dates (treatment dates indicated by the coloured vertical stripes; the date of the cytoreduction surgery is indicated by a red vertical line, and the date of the diagnosed recurrence is indicated by a red cross) as well as computed tomography images and summarised results. (<b>B</b>) Cell-free DNA (cfDNA) plasma levels are presented as ng/mL. (<b>C</b>) Circulating tumour DNA (ctDNA) plasma levels are expressed as the number of mutated copies/mL of plasma. Replicates were used to quantify the average <span class="html-italic">TP53</span> R175H copies for each time point, and the error bars represent the standard deviation across replicates; no bar indicates that the standard deviation was too low to be visualised on the scale used. The volume-adjusted limit of detection was 21.2 GEs (genome equivalent)/mL for all time points. A two-tailed <span class="html-italic">t</span>-test was used to compare the ctDNA levels between sequential time points. (<b>D</b>) Cancer antigen 125 (CA125) serum levels (U/mL); data from multiple replicates were not provided. * <span class="html-italic">p</span> = 0.05.</p>
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<p>The number of <span class="html-italic">TP53</span> (R175H) copies quantified by digital droplet polymerase chain reaction.</p>
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<p>(<b>A</b>) Summary of patient 11’s clinical information, including the treatment type and dates (treatment dates indicated by the coloured vertical stripes; the date of the cytoreduction surgery is indicated by a red vertical line, and the date of a diagnosed relapse is indicated by a red cross) as well as computed tomography images and summarised results. (<b>B</b>) Cell-free DNA (cfDNA) plasma levels are presented as ng/mL. (<b>C</b>) Circulating tumour DNA (ctDNA) plasma levels are expressed as the number of mutated copies/mL. Replicates were used to quantify the average <span class="html-italic">BRCA1</span> E272* (c.814 G&gt;T) levels for each time point, and the error bars represent the standard deviation across replicates; no bars indicate that the standard deviation was too low to be visualised on the scale used. The volume-adjusted limit of detection was 21.2 GE/mL for all time points. A two-tailed <span class="html-italic">t</span>-test was used to compare the ctDNA quantities between sequential time points. (<b>D</b>) Cancer antigen 125 (CA125) serum levels (U/mL); data from multiple replicates were not provided. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>The number of <span class="html-italic">BCRA1</span> E272* (c.814 G&gt;T) copies quantified by digital droplet polymerase chain reaction.</p>
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<p>(<b>A</b>) Summary of patient 10’s clinical information, including the treatment type and dates (treatment dates indicated by the coloured vertical stripes, and date of the cytoreduction surgery indicated by a red vertical line) as well as a computed tomography scan and summarised results. (<b>B</b>) Cell-free DNA (cfDNA) plasma levels are presented as ng/mL. (<b>C</b>) Circulating tumour DNA (ctDNA) plasma levels are expressed as the number of mutated copies/mL. Replicates were used to quantify the average TP53 G245 levels for each time point, and the error bars represent the standard deviation across replicates (<span class="html-italic">n</span> = 3); no bars indicate that the standard deviation was too low to be visualised on the scale used. The volume-adjusted limit of detection was 21.2 GE/mL for all time points. A two-tailed <span class="html-italic">t</span>-test was used to compare the ctDNA quantities between sequential time points. (<b>D</b>) Cancer antigen 125 (CA125) serum levels (U/mL); data from multiple replicates were not provided. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>(<b>A</b>) Summary of patient 8’s clinical information, including the treatment type and dates (treatment dates indicated by the coloured vertical stripes; the date of the cytoreduction surgery is indicated by a red vertical line, and the date of a diagnosed relapse is indicated by a red cross) as well as computed tomographic images and summarised results. (<b>B</b>) Cell-free DNA (cfDNA) plasma levels are presented as ng/mL. (<b>C</b>) Circulating tumour DNA (ctDNA) plasma levels are expressed as the number of mutated copies/mL. Replicates were used to quantify the average <span class="html-italic">TP53</span> (c.994C-1G) levels for each time point, and the error bars represent the standard deviation across replicates (n = 3); no bars indicate that the standard deviation was too low to be visualised on the scale used. The volume-adjusted limit of detection was 21.2 GE/mL for all time points. A two-tailed <span class="html-italic">t</span>-test was used to compare the ctDNA quantities between sequential time points. (<b>D</b>) Cancer antigen 125 (CA125) serum levels (U/mL); data from multiple replicates were not provided. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Aggregated correlation between (<b>A</b>) cell-free DNA (cfDNA) and CA125 and (<b>B</b>) <span class="html-italic">TP53-</span>ctDNA and CA125 for the four patients with complete records.</p>
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<p>Aggregated correlation between (<b>A</b>) cfDNA and CA125 and (<b>B</b>) <span class="html-italic">TP53</span>-ctDNA and CA125 for eleven different patients of the dataset.</p>
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<p>Aggregated correlation between (<b>A</b>) cfDNA and CA125 and (<b>B</b>) <span class="html-italic">TP53</span> ctDNA and CA125 for two patients with the same disease progression on treatment.</p>
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<p>Monitoring cell-free DNA (cfDNA) and cancer antigen 125 (CA125) over time in patient 5.</p>
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<p>Monitoring cell-free DNA (cfDNA) and cancer antigen 125 (CA125) over time in patient 11.</p>
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<p>Monitoring cell-free DNA (cfDNA) and cancer antigen 125 (CA125) over time in patient 8.</p>
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20 pages, 1155 KiB  
Review
The Role of Inflammatory Mediators in the Pathogenesis of Obesity
by Estera Bakinowska, Mariusz Krompiewski, Dominika Boboryko, Kajetan Kiełbowski and Andrzej Pawlik
Nutrients 2024, 16(17), 2822; https://doi.org/10.3390/nu16172822 - 23 Aug 2024
Viewed by 399
Abstract
Obesity is a pandemic of the 21st century, and the prevalence of this metabolic condition has enormously increased over the past few decades. Obesity is associated with a number of comorbidities and complications, such as diabetes and cardiovascular disorders, which can be associated [...] Read more.
Obesity is a pandemic of the 21st century, and the prevalence of this metabolic condition has enormously increased over the past few decades. Obesity is associated with a number of comorbidities and complications, such as diabetes and cardiovascular disorders, which can be associated with severe and fatal outcomes. Adipose tissue is an endocrine organ that secretes numerous molecules and proteins that are capable of modifying immune responses. The progression of obesity is associated with adipose tissue dysfunction, which is characterised by enhanced inflammation and apoptosis. Increased fat-tissue mass is associated with the dysregulated secretion of substances by adipocytes, which leads to metabolic alterations. Importantly, the adipose tissue contains immune cells, the profile of which changes with the progression of obesity. For instance, increasing fat mass enhances the presence of the pro-inflammatory variants of macrophages, major sources of tumour necrosis factor α and other inflammatory mediators that promote insulin resistance. The pathogenesis of obesity is complex, and understanding the pathophysiological mechanisms that are involved may provide novel treatment methods that could prevent the development of serious complications. The aim of this review is to discuss current evidence describing the involvement of various inflammatory mediators in the pathogenesis of obesity. Full article
(This article belongs to the Section Nutrition and Obesity)
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<p>A schematic illustration demonstrating pro-inflammatory and pro-apoptotic pathways present in adipose tissue of patients with obesity.</p>
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<p>A schematic presentation of adipose tissue in obesity. The tissue is infiltrated with pro-inflammatory macrophages which secrete inflammatory mediators, such as TNF-α. M2 macrophages play a protective role by secreting anti-inflammatory cytokines and enhancing insulin sensitivity.</p>
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<p>A schematic presentation of the impact of chemokines on the immune cell infiltration of adipose tissue in patients with obesity.</p>
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13 pages, 1419 KiB  
Article
Exploring the Genetic Landscape of Vitiligo in the Pura Raza Español Horse: A Genomic Perspective
by Nora Laseca, Antonio Molina, Davinia Perdomo-González, Chiraz Ziadi, Pedro J. Azor and Mercedes Valera
Animals 2024, 14(16), 2420; https://doi.org/10.3390/ani14162420 - 21 Aug 2024
Viewed by 617
Abstract
Vitiligo is a depigmentation autoimmune disorder characterized by the progressive loss of melanocytes leading to the appearance of patchy depigmentation of the skin. The presence of vitiligo in horses is greater in those with grey coats. The aim of this study was therefore [...] Read more.
Vitiligo is a depigmentation autoimmune disorder characterized by the progressive loss of melanocytes leading to the appearance of patchy depigmentation of the skin. The presence of vitiligo in horses is greater in those with grey coats. The aim of this study was therefore to perform a genome-wide association study (GWAS) to identify genomic regions and putative candidate loci associated with vitiligo depigmentation and susceptibility in the Pura Raza Español population. For this purpose, we performed a wssGBLUP (weighted single step genomic best linear unbiased prediction) using data from a total of 2359 animals genotyped with Affymetrix Axiom™ Equine 670 K and 1346 with Equine GeneSeek Genomic Profiler™ (GGP) Array V5. A total of 60,136 SNPs (single nucleotide polymorphisms) present on the 32 chromosomes from the consensus dataset after quality control were employed for the analysis. Vitiligo-like depigmentation was phenotyped by visual inspection of the different affected areas (eyes, mouth, nostrils) and was classified into nine categories with three degrees of severity (absent, slight, and severe). We identified one significant genomic region for vitiligo around the eyes, eight significant genomic regions for vitiligo around the mouth, and seven significant genomic regions for vitiligo around the nostrils, which explained the highest percentage of variance. These significant genomic regions contained candidate genes related to melanocytes, skin, immune system, tumour suppression, metastasis, and cutaneous carcinoma. These findings enable us to implement selective breeding strategies to decrease the incidence of vitiligo and to elucidate the genetic architecture underlying vitiligo in horses as well as the molecular mechanisms involved in the disease’s development. However, further studies are needed to better understand this skin disorder in horses. Full article
(This article belongs to the Special Issue Advances in Equine Genetics and Breeding)
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<p>Phenotypic levels of vitiligo depigmentation in Pura Raza Español horses. (<b>a</b>) Slight degree in eyes; (<b>b</b>) slight degree in mouth and nostrils; (<b>c</b>) slight degree in eyes; (<b>d</b>) severe degree in eyes, mouth, and nostrils; and (<b>e</b>) severe degree in eyes, mouth, and nostrils. All the animals have grey coats.</p>
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<p>Manhattan plot of SNP additive genetic variance (y axis) explained at each of the SNPs by 1 Mb window of adjacent SNPs for traits (<b>a</b>) VE: vitiligo around eyes; (<b>b</b>) VM: vitiligo around mouth; (<b>c</b>) VN: vitiligo around nostrils. Red line: percentage of additive genetic variance above 1%.</p>
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23 pages, 3408 KiB  
Article
Implication of Capillary Morphogenesis Gene 2 (CMG2) in the Disease Progression and Peritoneal Metastasis of Pancreatic Cancer
by Ziqian Fang, Carly Bunston, Yali Xu, Fiona Ruge, Laijian Sui, Ming Liu, Bilal Al-Sarireh, Paul Griffiths, Kate Murphy, Matthew R. Pugh, Chunyi Hao, Wen G. Jiang and Lin Ye
Cancers 2024, 16(16), 2893; https://doi.org/10.3390/cancers16162893 - 20 Aug 2024
Viewed by 475
Abstract
Capillary morphogenesis gene 2 (CMG2) mediates cell–matrix interactions to facilitate cell adhesion and migration. CMG2 has been implicated in the disease progression of breast cancer, prostate cancer and gastric cancer. The present study aims to determine the role of CMG2 in the disease [...] Read more.
Capillary morphogenesis gene 2 (CMG2) mediates cell–matrix interactions to facilitate cell adhesion and migration. CMG2 has been implicated in the disease progression of breast cancer, prostate cancer and gastric cancer. The present study aims to determine the role of CMG2 in the disease progression and peritoneal metastasis of pancreatic cancer. Pancreatic tumour samples were collected from Peking University Cancer Hospital. CMG2 expression was determined using quantitative PCR. After the creation of knockdown and overexpression of CMG2 in pancreatic cancer cells, the effect of CMG2 on several cell functions and adhesion to the peritoneum was examined. Potential pathways regulated by CMG2 were found via proteomics analysis and drug tests. CMG2 was upregulated in pancreatic cancer tissues and associated with a poor prognosis. CMG2 was increased in metastatic lesions and those primary tumours with distant metastases. CMG2 promotes cell–cell, cell–matrix and cell–hyaluronic acid adhesion, which may be mediated by epidermal growth factor receptor (EGFR) and focal adhesion kinase (FAK) pathway activation. Full article
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<p>Increased CMG2 expression in pancreatic cancer was associated with disease progression and poor prognosis. (<b>A</b>) Expression of CMG2 in pancreatic tumours was analysed in comparison with adjacent normal pancreatic tissues in the public cohort GSE71729 [<a href="#B16-cancers-16-02893" class="html-bibr">16</a>] (<b>B</b>) Shown are the IHC scores of CMG2 staining in normal pancreas tissues, adjacent normal pancreatic tissues, inflammation tissues, hyperplasia tissues, benign tumour tissues and in primary tumours on the tissue microarray (PA2081). (<b>C</b>) Shown are representative images that were reduced from photos taken at magnifications of 200× and 400×. The negative control was staining performed with the secondary antibody only. CMG2-overexpressing HECV cells were included as a positive control for the staining. (<b>D</b>) The association between CMG2 expression and patients’ survival was analysed using the KMplot online platform (<a href="http://www.KMplot.com" target="_blank">www.KMplot.com</a>, accessed on 40 April 2024) [<a href="#B20-cancers-16-02893" class="html-bibr">20</a>], including overall survival (OS) and relapse-free survival (RFS). (<b>E</b>) Shown are CMG2 transcript levels in primary tumours according to the status of distant metastasis in TCGA cohort. (<b>F</b>) The expression of CMG2 in metastatic tumours (MT) (<span class="html-italic">n</span> = 61) was compared with the primary tumours (<span class="html-italic">n</span> = 162) in the GSE71729 cohort. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>CMG2 regulated pancreatic cancer cell growth and adhesion. (<b>A</b>) CMG2 protein expression in MiaPaCa-2, ASPC-1 and PANC-1 cell lines was determined using Western blotting. The knockdown and overexpression were successfully established, which were verified using Western blotting (<b>B</b>) and quantitative PCR (<b>C</b>), respectively. (<b>D</b>) The influence of CMG2 on the proliferation of MiaPaCa-2, PANC-1 and ASPC-1 was determined using CCK8. Six replicates were examined for each cell line in an experiment. (<b>E</b>) Adhesion to an artificial basement membrane (Matrigel) was determined in the CMG2-overexpressing MiaPaCa-2 and PANC-1 cell lines and CMG2-knockdown cells of PANC-1 and ASPC-1. Three independent experiments were conducted. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effect of CMG2 overexpression or knockdown on the peritoneum metastasis of pancreatic cancer. (<b>A</b>) Adhesion to mesothelial cells was determined in MiaPaCa-2CMG2exp, PANC-1CMG2shRNA and ASPC-1shRNA against corresponding control groups, respectively. The cells were stained with DiI. Shown are representative photos. (<b>B</b>) The PANC-1 cell line with CMG2 overexpression was treated with high-molecular-weight, low-molecular-weight, and ultra-low-molecular-weight hyaluronic acid and a hyaluronic acid inhibitor with different concentrations. Shown are the PANC-1 cell number adhered to the MET5A cell monolayer. * v.s. corresponding untreated controls, ^ v.s. pEF control, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, ^^ <span class="html-italic">p</span> &lt; 0.01 and ^ <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>CMG2 and anoikis. (<b>A</b>) Hoechst staining was used to determine the apoptotic cells in suspended MiaPaCa-2, PANC-1 and ASPC-1 cells with CMG2 overexpression or knockdown. (<b>B</b>) Apoptosis in the suspended MiaPaCa-2 and PANC-1 cells was determined using the flow cytometric apoptosis assay. The apoptotic population included both early apoptotic (Q3) and late apoptotic (Q2) cells. Three independent experiments were conducted. Shown are the representative results from one experiment. (<b>C</b>) CCK8 was also used to determine cell viability in MiaPaCa-2, PANC-1 and ASPC-1 cells with CMG2 overexpression or knockdown. (<b>D</b>) After a suspension culture of 2.5 h, the expression of Bim and BCL-2 and the activation state of caspase 3 and caspase 8 in MiaPaCa-2, PANC-1 and ASPC-1 cells with CMG2 overexpression and knockdown were shown. Bar graphs show the normalised integrated density of bands against the corresponding GAPDH following the semi-quantification of the bands using Image J (Version 8). (<b>E</b>) Cell aggregation was determined in MiaPaCa-2, PANC-1 and ASPC-1 cells. Shown are the numbers of clusters and cells per ml. *** indicates <span class="html-italic">p</span> &lt; 0.001, ** indicates <span class="html-italic">p</span> &lt; 0.01 and * indicates <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>CMG2 regulated cell adhesion molecules. The cell adhesion genes were positively associated with CMG2 at both the transcript level (<b>A</b>) and protein level (<b>B</b>). Horizontal red dashed lines indicate a level of <span class="html-italic">p</span> = 0.05 while vertical dashed lines indicate a change in folds = 0. QPCR results show the transcript changes of ITGB3 (<b>C</b>) and ICAM-1 (<b>D</b>) after CMG2 overexpression or knockdown in MiaPaCa-2, PANC-1 and ASPC-1 cells. ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Protein phosphorylation regulated by CMG2. (<b>A</b>) The phosphorylation status of the key proteins that enhance cell adhesion was analysed. Shown are the phosphorylation statuses of these proteins that are positively associated with CMG2 in proteomics and Kinexus protein array results. Horizontal red dashed lines indicate a level of P = 0.05 while vertical dashed lines indicate a change in folds = 0. (<b>B</b>) The phosphorylation status of candidate proteins was verified in pancreatic cancer cell lines with CMG2 overexpression and knockdown. (<b>C</b>) Shown are the semi-quantification result of the phosphorylation status of PTK2, EGFR, shc and ELK1.</p>
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<p>EGFR, ERK and FAK in CMG2-regulated ICAM-1 and ITGB3. QPCR was performed to check the expression of ICAM-1 (<b>A</b>) and ITGB3 (<b>B</b>) in the MiaPaCa-2 cell line with CMG2 overexpression, which was treated with an EGFR inhibitor (Gefitinib, 400 nM), FAK inhibitor 14 (400 nM) and ERK inhibitor (FR18024, 200 nM). Cell lines were treated with small inhibitors for 4 and 24 h * v.s. untreated control, ^ v.s. pEF corresponding control. (<b>C</b>) Shown are ICAM-1 expression at the protein level in MiaPaCa-2 and PANC-1 cell lines with CMG2 overexpression and in their corresponding pEF control cell lines. Cells were treated with an EGFR inhibitor (Gefitinib, 400 nM), FAK inhibitor 14 (400 nM) and ERK inhibitor (FR18024, 200 nM) for 24 h. Bar graphs show the normalised integrated density of bands against the corresponding GAPDH following semi-quantification of the bands using Image J (Version 8). *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, ^^ <span class="html-italic">p</span> &lt; 0.01, ^ <span class="html-italic">p</span> &lt; 0.05.</p>
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17 pages, 4127 KiB  
Article
Impact of the Immunomodulatory Factor Soluble B7-H4 in the Progress of Preeclampsia by Inhibiting Essential Functions of Extravillous Trophoblast Cells
by Yuyang Ma, Liyan Duan, Beatrix Reisch, Rainer Kimmig, Antonella Iannaccone and Alexandra Gellhaus
Cells 2024, 13(16), 1372; https://doi.org/10.3390/cells13161372 - 17 Aug 2024
Viewed by 617
Abstract
A key aspect of preeclampsia pathophysiology is the reduced invasiveness of trophoblasts and the impairment of spiral artery remodelling. Understanding the causes of altered trophoblast function is critical to understand the development of preeclampsia. B7-H4, a checkpoint molecule, controls a wide range of [...] Read more.
A key aspect of preeclampsia pathophysiology is the reduced invasiveness of trophoblasts and the impairment of spiral artery remodelling. Understanding the causes of altered trophoblast function is critical to understand the development of preeclampsia. B7-H4, a checkpoint molecule, controls a wide range of processes, including T-cell activation, cytokine release, and tumour progression. Our previous findings indicated that B7-H4 levels are elevated in both maternal blood and placental villous tissue during the early stages of preeclampsia. Here, we investigated the function of B7-H4 in trophoblast physiology. Recombinant B7-H4 protein was used to treat human SGHPL-5 extravillous trophoblast cells. Biological functions were investigated using MTT, wound healing, and transwell assays. Signalling pathways were analysed by immunoblotting and immunofluorescence. The functionality of B7-H4 was further confirmed by immunoblotting and immunohistochemical analysis in placental tissues from control and preeclamptic patients following therapeutic plasma exchange (TPE) or standard of care treatment. This study showed that B7-H4 inhibited the proliferation, migration, and invasion capacities of SGHPL-5 extravillous cells while promoting apoptosis by downregulating the PI3K/Akt/STAT3 signalling pathway. These results were consistently confirmed in placental tissues from preterm controls compared to early-onset preeclamptic placental tissues from patients treated with standard of care or TPE treatment. B7-H4 may play a role in the development of preeclampsia by inhibiting essential functions of extravillous trophoblast cells during placental development. One possible mechanism by which TPE improves pregnancy outcomes in preeclampsia is through the elimination of B7-H4 amongst other factors. Full article
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<p>B7-H4 reduces the proliferative and migratory capacities of SGHPL-5 cells. (<b>A</b>) SGHPL-5 cells were treated with rhB7-H4 protein (0, 0.05, 0.1, 0.2 and 0.5 μg/mL) for 24, 48 or 72 h. Cell viability was determined by MTT assay. (<b>B</b>) The effect of B7-H4 on cell horizontal migration was determined by wound healing assay; yellow line: marked scratch. (<b>C</b>) Quantitative analysis of (<b>B</b>). (<b>D</b>) The effect of B7-H4 on cell invasion was determined by transwell assay. SGHPL-5 cells were treated with different concentrations of rhB7-H4 protein (0, 0.1, 0.5 μg/mL) for 24 h. (<b>E</b>) Quantitative analysis of (<b>D</b>). Data represent means ± SD of triplicate 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 vs. control. Scale bar: 1 mm.</p>
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<p>Effects of rhB7-H4 on the expression of Cyclin D1, p21, and cleaved caspase 3 proteins in SGHPL-5 cells. SGHPL-5 cells were treated with rhB7-H4 at various concentrations for 24 h (<b>A</b>) or with 0.1 μg/mL rhB7-H4 for 0, 12, 24, 48 h (<b>B</b>), and the levels of Cyclin D1, p21, cleaved caspase 3 and actin proteins were determined by immunoblotting. (<b>C</b>) Quantitative analysis of (<b>A</b>) to represent Cyclin D1/actin, p21/actin, and cleaved caspase 3/actin. (<b>D</b>) Quantitative analysis of (<b>B</b>) to represent Cyclin D1/Actin, p21/actin, and cleaved caspase 3/actin. (<b>E</b>) Effects of rhB7-H4 on the expression of Ki67 and cleaved caspase 3 in SGHPL-5 cells were determined by immunofluorescence (green: Ki67; blue: DAPI nucleus staining; merge: Ki67/DAPI). (<b>F</b>) Quantitative analysis of (<b>E</b>). Data represent means ± SD of triplicate experiments. Significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 versus control. Scale bar: 75 μm.</p>
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<p>B7-H4 downregulates the PI3K/Akt/STAT3 signalling pathway in SGHPL-5 cells. (<b>A</b>) SGHPL-5 cells were incubated with rhB7-H4 at various concentrations for 24 h, then the PI3K/Akt/STAT3 signal pathway-related proteins and actin were determined by immunoblotting. (<b>B</b>) SGHPL-5 cells were incubated with 0.1 μg/mL rhB7-H4 for 0, 12, 24, 48 h, and the PI3K/Akt/STAT3 signal pathway-related proteins and actin were determined by immunoblotting. (<b>C</b>) Quantitative analysis of (<b>A</b>) to represent p-PI3K/PI3K, p-Akt/Akt, p-STAT3/STAT3. (<b>D</b>) Quantitative analysis of (<b>B</b>) to represent p-PI3K/PI3K, p-Akt/Akt, p-STAT3/STAT3. Data represent means ± SD of triplicate experiments. Significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 versus control.</p>
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<p>IL-6, an activator of PI3K/Akt/STAT3, partially attenuated B7-H4-induced inhibitory effects in SGHPL-5 cells. SGHPL-5 cells were incubated with rhB7-H4/IL-6/LY-294002 alone or in combination for 24 h, and the levels of PI3K/Akt/STAT3 pathway-related proteins, (<b>A</b>) as well as Cyclin D1, p21, and cleaved caspase 3 (<b>B</b>), were determined by immunoblotting. (<b>C</b>–<b>E</b>) Quantitative analysis of (<b>A</b>). (<b>F</b>–<b>H</b>) Quantitative analysis of (<b>B</b>). Data represent means ± SD of triplicate experiments. Significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>B7-H4 may suppress trophoblast cell proliferation and induce apoptosis in patients with PE. (<b>A</b>) Representative immunoblot of p21 and Cyclin D1 protein expression in placental chorionic villi of the control (<span class="html-italic">n</span> = 12), PE (<span class="html-italic">n</span> = 13) and PE + TPE (<span class="html-italic">n</span> = 12) groups. (<b>B</b>,<b>C</b>) Quantitative analysis of (<b>A</b>). (<b>D</b>) Representative immunoblot of p21 and Cyclin D1 protein expression in placental decidua basalis of the control (<span class="html-italic">n</span> = 8), PE <span class="html-italic">n</span> = 11) and PE +TPE (<span class="html-italic">n</span> = 11) groups. (<b>E</b>,<b>F</b>) Quantitative analysis of (<b>D</b>). (<b>G</b>) IHC staining images of cleaved caspase 3 in placental sections among control (<span class="html-italic">n</span> = 10), PE (<span class="html-italic">n</span> = 12), and PE + TPE (<span class="html-italic">n</span> = 12) patients. (<b>H</b>) Quantitative analysis of (<b>G</b>) to represent the AOD value of cleaved caspase 3 expression in placental tissue section. Data represent medians (lines inside boxes)/means (crosses inside boxes)  ±  interquartile ranges with minimum/maximum values as whiskers. Scale bar: 300 μm. Significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. ns: not significant.</p>
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<p>B7-H4 may suppress PI3K/Akt/STAT3 pathway in placental chorionic villi and decidua basalis in patients with PE. (<b>A</b>) Representative immunoblot of p-PI3K, PI3K, p-Akt, Akt, p-STAT3 and STAT3 protein expression levels in placental chorionic villi of the control (<span class="html-italic">n</span> = 12), PE (<span class="html-italic">n</span>= 13) and PE + TPE (<span class="html-italic">n</span> = 12) groups. (<b>B</b>) Representative immunoblot of p-PI3K, PI3K, p-Akt, Akt, p-STAT3 and STAT3 protein expression levels in placental decidua basalis of the control (<span class="html-italic">n</span> = 8), PE (<span class="html-italic">n</span> = 11) and PE + TPE (<span class="html-italic">n</span> = 11) groups. (<b>C</b>–<b>E</b>) Quantitative analysis of (<b>A</b>). (<b>F</b>–<b>H</b>) Quantitative analysis of (<b>B</b>). Data represent medians (lines inside boxes)/means (crosses inside boxes)  ±  interquartile ranges with minimum/maximum values as whiskers. Significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. ns: not significant.</p>
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<p>Potential schematic overview of the B7-H4-mediated signalling pathway in trophoblast cells in patients with early-onset PE. sB7-H4 diminishes trophoblast cell proliferation and migration while promoting apoptosis. The introduction of IL-6, an activator of the PI3K/Akt/STAT3 pathway, reverses sB7-H4’s inhibitory effects on trophoblast cells. These findings illuminate sB7-H4’s role in regulating trophoblast cell proliferation, migration, and apoptosis via the PI3K/Akt/STAT3 pathway in PE. <b>Abbreviations:</b> CM: cell membrane; NM, nuclear membrane. The diagram was created with BioRender.com.</p>
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13 pages, 1405 KiB  
Article
A Retrospective Analysis of the Prognostic Factors and Adverse Events in the Treatment of Mucosal Melanoma in a Single Centre
by Lambert Wesener, Victoria Hagelstein, Patrick Terheyden and Ewan A. Langan
J. Clin. Med. 2024, 13(16), 4741; https://doi.org/10.3390/jcm13164741 - 13 Aug 2024
Viewed by 587
Abstract
Background: Despite the dramatic advances in the management of metastatic cutaneous melanoma, there remains no consensus-based, evidence-based strategy for the management of mucosal melanoma. The rare nature of the disease, its late clinical presentation, and distinct tumour biology all complicate efforts to optimise [...] Read more.
Background: Despite the dramatic advances in the management of metastatic cutaneous melanoma, there remains no consensus-based, evidence-based strategy for the management of mucosal melanoma. The rare nature of the disease, its late clinical presentation, and distinct tumour biology all complicate efforts to optimise patient outcomes. Methods: To this end, we carried out a monocentric, retrospective analysis of all patients diagnosed with mucosal melanoma and treated between 2013 and 2021. Both tumour- and patient-specific characteristics were recorded, in addition to immune-related adverse events, in order to provide real-world data on disease progression, treatment efficacy, and the identification of prognostic markers. Results: A total of 20 patients were identified (14 females and 6 males), with a mean age at diagnosis of 65.9 years. The median follow-up was 3.9 years (95% CI 1.4–6.4 years) from the initiation of systemic therapy. The median OS in the entire cohort was 1.9 years (95% CI 0.5–3.3 years). Performance status, sex, body mass index, and the presence of brain metastases were not associated with poorer outcomes. However, serum lactate dehydrogenase levels (LDH) (p = 0.04) and an NRAS mutation were markers of a poor prognosis (p = 0.004). Conclusuion: There is a pressing need for real-world, prospective, and clinical trial data to inform the optimal management of mucosal melanoma, and data supporting the use of adjuvant and neo-adjuvant immunotherapy are currently lacking. However, an elevated LDH is a reliable, independent negative prognostic marker. Inter-disciplinary management remains essential in order to develop optimal treatment strategies. Full article
(This article belongs to the Section Dermatology)
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<p>(<b>A</b>) Distribution of melanoma sites based on and modified from the classification of Heppt et al. [<a href="#B32-jcm-13-04741" class="html-bibr">32</a>]. (<b>B</b>) Lines of treatment and treatment responses. (<b>C</b>) The effect of serum LDH on overall survival.</p>
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<p>(<b>A</b>) Distribution of melanoma sites based on and modified from the classification of Heppt et al. [<a href="#B32-jcm-13-04741" class="html-bibr">32</a>]. (<b>B</b>) Lines of treatment and treatment responses. (<b>C</b>) The effect of serum LDH on overall survival.</p>
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25 pages, 3019 KiB  
Review
Targeting IL-8 and Its Receptors in Prostate Cancer: Inflammation, Stress Response, and Treatment Resistance
by Shauna McClelland, Pamela J. Maxwell, Cristina Branco, Simon T. Barry, Cath Eberlein and Melissa J. LaBonte
Cancers 2024, 16(16), 2797; https://doi.org/10.3390/cancers16162797 - 8 Aug 2024
Viewed by 1072
Abstract
This review delves into the intricate roles of interleukin-8 (IL-8) and its receptors, CXCR1 and CXCR2, in prostate cancer (PCa), particularly in castration-resistant (CRPC) and metastatic CRPC (mCRPC). This review emphasizes the crucial role of the tumour microenvironment (TME) and inflammatory cytokines in [...] Read more.
This review delves into the intricate roles of interleukin-8 (IL-8) and its receptors, CXCR1 and CXCR2, in prostate cancer (PCa), particularly in castration-resistant (CRPC) and metastatic CRPC (mCRPC). This review emphasizes the crucial role of the tumour microenvironment (TME) and inflammatory cytokines in promoting tumour progression and response to tumour cell targeting agents. IL-8, acting through C-X-C chemokine receptor type 1 (CXCR1) and type 2 (CXCR2), modulates multiple signalling pathways, enhancing the angiogenesis, proliferation, and migration of cancer cells. This review highlights the shift in PCa research focus from solely tumour cells to the non-cancer-cell components, including vascular endothelial cells, the extracellular matrix, immune cells, and the dynamic interactions within the TME. The immunosuppressive nature of the PCa TME significantly influences tumour progression and resistance to emerging therapies. Current treatment modalities, including androgen deprivation therapy and chemotherapeutics, encounter persistent resistance and are complicated by prostate cancer’s notably “immune-cold” nature, which limits immune system response to the tumour. These challenges underscore the critical need for novel approaches that both overcome resistance and enhance immune engagement within the TME. The therapeutic potential of inhibiting IL-8 signalling is explored, with studies showing enhanced sensitivity of PCa cells to treatments, including radiation and androgen receptor inhibitors. Clinical trials, such as the ACE trial, demonstrate the efficacy of combining CXCR2 inhibitors with existing treatments, offering significant benefits, especially for patients with resistant PCa. This review also addresses the challenges in targeting cytokines and chemokines, noting the complexity of the TME and the need for precision in therapeutic targeting to avoid side effects and optimize outcomes. Full article
(This article belongs to the Section Tumor Microenvironment)
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<p>Interleukin-8 (IL-8) and CXCR1/2 signalling in cancer hallmarks. This figure illustrates the central role of IL-8/CXCR1/2 in modulating key hallmarks of cancer. IL-8, a pro-inflammatory chemokine, interacts with its receptors CXCR1/2 to exert its effect on cancer progression [<a href="#B39-cancers-16-02797" class="html-bibr">39</a>,<a href="#B40-cancers-16-02797" class="html-bibr">40</a>]. Abbreviations: CXCR1: C-X-C chemokine receptor type 1; CXCR2: C-X-C chemokine receptor type 2; FAK: focal adhesion kinase; HIF-1α: hypoxia-inducible factor-1-alpha; IL-8: interleukin 8; MAPK: mitogen-activated protein kinase; MDSC: myeloid-derived suppressor cell; NF-kB: nuclear factor kappa-light-chain-enhancer of activated B cells; p53: tumour protein P53; PI3K/AKT: phosphoinositide 3-kinase; Rb: retinoblastoma protein; RNS: reactive nitrogen species.</p>
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<p>IL-8 signalling cascade and activated downstream pathways. The figure illustrates the intricate signalling network initiated by IL-8 binding to its receptors, CXCR1 and CXCR2, leading to a series of intracellular events. The cascade involves the activation of PI3K, PTEN, MAPK, AKT, and PLC, with subsequent interactions of PI3K with JAK/STAT3. The bottom of the figure highlights the linkage of the various signalling cascades to crucial cellular processes, including cell proliferation, invasion, migration, survival, metabolism, and angiogenesis. Abbreviations: AKT: protein kinase B; CXCR1: C-X-C chemokine receptor type 1; CXCR2: C-X-C chemokine receptor type 2; ERK1: extracellular signal-regulated kinase 1;IL-8: interleukin-8; JAK: Janus kinase; MAPK: mitogen-activated protein kinase; MEK: mitogen-activated protein kinase; mTOR: mammalian target of rapamycin; p38MAPK: p38 mitogen-activated protein kinase; PI3K: phosphoinositide 3-kinase; PKC: protein kinase C; PLC: phospholipase C; PTEN: phosphatase and tensin homolog; RAF: Rapidly Accelerated Fibrosarcoma; RasGTP: Ras guanosine triphosphate; STAT3: signal transducer and activator of transcription 3.</p>
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<p>Tumour and immune response to interleukin-8 (IL-8). The figure illustrates the complex interaction of IL-8 within the tumour (TME) and immune (IME) microenvironment components. Tumour cells, CAFs, MDSCs, and TAMs all secrete IL-8, which in turn recruits MDSCs, TAMs, and TANs. IL-8 promotes tumour cell proliferation and EMT directly and indirectly. IL-8 aids in the accumulation of pro-tumourigenic immune cells and promotes immunosuppression within the TME. Abbreviations: CAF: cancer-associated fibroblast; CD8+T: CD8-positive T-cells; DC: dendritic cell; EMT: epithelial–mesenchymal transition; IL-8: interleukin 8; MDSC: myeloid-derived suppressor cell; NK: natural killer cells; TAM: tumour-associated macrophage; TAN: tumour-associated neutrophil; Treg: T regulatory cell.</p>
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21 pages, 13456 KiB  
Article
Tracking Ovine Pulmonary Adenocarcinoma Development Using an Experimental Jaagsiekte Sheep Retrovirus Infection Model
by Chris Cousens, James Meehan, David Collie, Steven Wright, Ziyuan Chang, Helen Todd, Jo Moore, Lynn Grant, Carola R. Daniel, Peter Tennant, Adrian Ritchie, James Nixon, Chris Proudfoot, Stefano Guido, Helen Brown, Calum D. Gray, Tom J. MacGillivray, R. Eddie Clutton, Stephen N. Greenhalgh, Rachael Gregson, David J. Griffiths, James Spivey, Nicole Storer, Chad E. Eckert and Mark Grayadd Show full author list remove Hide full author list
Genes 2024, 15(8), 1019; https://doi.org/10.3390/genes15081019 - 2 Aug 2024
Viewed by 730
Abstract
Ovine pulmonary adenocarcinoma (OPA) is an infectious, neoplastic lung disease of sheep that causes significant animal welfare and economic issues throughout the world. Understanding OPA pathogenesis is key to developing tools to control its impact. Central to this need is the availability of [...] Read more.
Ovine pulmonary adenocarcinoma (OPA) is an infectious, neoplastic lung disease of sheep that causes significant animal welfare and economic issues throughout the world. Understanding OPA pathogenesis is key to developing tools to control its impact. Central to this need is the availability of model systems that can monitor and track events after Jaagsiekte sheep retrovirus (JSRV) infection. Here, we report the development of an experimentally induced OPA model intended for this purpose. Using three different viral dose groups (low, intermediate and high), localised OPA tumour development was induced by bronchoscopic JSRV instillation into the segmental bronchus of the right cardiac lung lobe. Pre-clinical OPA diagnosis and tumour progression were monitored by monthly computed tomography (CT) imaging and trans-thoracic ultrasound scanning. Post mortem examination and immunohistochemistry confirmed OPA development in 89% of the JSRV-instilled animals. All three viral doses produced a range of OPA lesion types, including microscopic disease and gross tumours; however, larger lesions were more frequently identified in the low and intermediate viral groups. Overall, 31% of JSRV-infected sheep developed localised advanced lesions. Of the sheep that developed localised advanced lesions, tumour volume doubling times (calculated using thoracic CT 3D reconstructions) were 14.8 ± 2.1 days. The ability of ultrasound to track tumour development was compared against CT; the results indicated a strong significant association between paired CT and ultrasound measurements at each time point (R2 = 0.799, p < 0.0001). We believe that the range of OPA lesion types induced by this model replicates aspects of naturally occurring disease and will improve OPA research by providing novel insights into JSRV infectivity and OPA disease progression. Full article
(This article belongs to the Special Issue Application of Animal Modeling in Cancer)
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<p>Pictures documenting sheep undergoing general anaesthesia for imaging and virus instillation. (<b>A</b>) Trans-thoracic ultrasound, (<b>B</b>) CT imaging, and (<b>C</b>) Bronchoscopy and virus instillation.</p>
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<p>CT image analysis for the identification of regions of interest and tumour volumes. Each CT slice was segmented to create regions of interest, including the trachea, mainstem bronchi, small airways, left and right normal lungs, and tumour areas. Blue, green and red lines indicate CT slices corresponding to the shown axial (<b>A</b>), coronal (<b>B</b>) and sagittal (<b>C</b>) planes. (<b>D</b>) Final 3D reconstruction, dorsal view. Trachea, mainstem, and segmental and subsegmental bronchi (yellow); left, right, and accessory lung lobes (grey); right lung tumour (red).</p>
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<p>Gross post mortem images and representative IHC results. (<b>A</b>) Control (sheep No. 3). (<b>B</b>) OPA-positive: no gross lesions, JSRV positive cells detected by IHC (sheep No. 28). (<b>C</b>) OPA-positive: small early lesions with a width of &lt;2 cm visible on the pleural surface, JSRV-positive cells detected by IHC (sheep No. 25). (<b>D</b>) OPA-positive: localised advanced lesions affecting greater than half of the affected lobe, JSRV-positive cells detected by IHC (sheep No. 20). IHC was performed using an antibody raised against the JSRV envelope SU protein. Pleural surface mottling apparent in the lungs in panel D represents post-euthanasia artefact.</p>
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<p>Sheep weight gain over the course of the study. (<b>A</b>) Average sheep weight gain with respect to treatment group. Mixed-effects analysis followed by a Tukey’s multiple comparison test, comparing all of the different groups to each other at each time point (mean ± SEM, n = 3–6). (<b>B</b>) Average weight gain with sheep separated into groups by tumour status at the time of euthanasia. Mixed-effects analysis followed by Tukey’s multiple comparison test, comparing each of the different groups to each other at each time point (mean ± SEM, n = 2–13).</p>
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<p>Normal thoracic ultrasound and CT appearance of ovine lungs from a control sheep over 9 months. (<b>A</b>) Transverse ultrasound images taken at the 4–6th intercostal spaces in the region of the cardiac lung lobes. An uninterrupted hyperechoic line consistent with the normal appearance of the visceral pleural surface can be seen at all time points. (<b>B</b>) Axial CT images highlighting the left and right cardiac lung lobes. Normal lung characterised by hypoattenuating lung parenchyma, through which air-filled (black) bronchi and bronchioles run, can be seen at all time points.</p>
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<p>Serial ultrasound, CT and 3D reconstructions documenting OPA tumour development. Transverse ultrasound images were taken at the 4–6th right and left intercostal spaces in the region of the cardiac lung lobes. Blue arrows indicate progression of a right cardiac lobe OPA lesion from an irregular hyperechoic pleural line with B lines at 8 weeks to a large hypoechoic lesion at 16 weeks post-JSRV instillation. Red arrow indicates a left cardiac lobe OPA lesion identified at 16 weeks post-JSRV instillation. Axial CT images highlighting the left and right cardiac lung lobes. Blue and red lines highlight the progression of right and left OPA lesions, respectively. CT 3D reconstructions include the trachea, mainstem, segmental, and subsegmental bronchi (yellow); left, right, and accessory lung lobes (grey); left and right lung tumours (red).</p>
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<p>CT image documenting difficulties in CT-based OPA diagnosis. Axial CT image highlighting the left and right cardiac lung lobes from sheep 17. The region outlined in blue highlights hyperattenuating lung in the instilled right cardiac lung lobe, subsequently confirmed as OPA. The region outlined in yellow highlights hyperattenuating lung in the contralateral left cardiac lung lobe that was grossly normal and demonstrated no evidence of OPA by IHC.</p>
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<p>OPA tumour volumes. (<b>A</b>) Graph showing right cardiac lobe tumour volumes from all 5 sheep that were identified at post mortem examination as having advanced localised gross OPA lesions. The gross lesion that developed in the contralateral left cardiac lung lobe of sheep 14 is also shown (sheep 14 L, dashed line). (<b>B</b>) Graph showing tumour volumes from the 2 sheep that had gross post mortem lesions with &lt;2 cm width visible on the pleural surface.</p>
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<p>Changes in OPA lesion depth over time using CT and ultrasound. Measurements were taken from lesions identified within the right cardiac lung lobe. (<b>A</b>) Corresponding CT and ultrasound measurements were taken at each time point. CT tumour depth (green), ultrasound tumour depth (blue). (<b>B</b>) Pearson correlation scatterplot of paired CT and ultrasound measurements (R<sup>2</sup> = 0.799; <span class="html-italic">p</span> &lt; 0.0001).</p>
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