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Search Results (19,744)

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17 pages, 249 KiB  
Review
Prognostication of Follicular Lymphoma: A Review of Prognostic Scores and Factors
by Ádám Jóna, Evelin Kiss and Árpád Illés
Diagnostics 2025, 15(5), 647; https://doi.org/10.3390/diagnostics15050647 - 6 Mar 2025
Abstract
Follicular lymphoma (FL) is an indolent, rarely curable B-cell malignancy with a heterogeneous clinical course. While generally treatable, FL is characterized by remissions and relapses, and its clinical presentation varies widely. Rituximab has revolutionized FL treatment, significantly improving overall survival over the past [...] Read more.
Follicular lymphoma (FL) is an indolent, rarely curable B-cell malignancy with a heterogeneous clinical course. While generally treatable, FL is characterized by remissions and relapses, and its clinical presentation varies widely. Rituximab has revolutionized FL treatment, significantly improving overall survival over the past two decades. Risk assessment typically relies on histological grade, tumor burden, and the Follicular Lymphoma International Prognostic Index, which incorporates factors like age, hemoglobin level, and Ann Arbor stage. However, these indices have limitations in fully capturing the clinical variability of FL. Some patients experience indolent disease for extended periods without requiring treatment, while others present with aggressive forms resistant to standard therapies. This review examines various prognostic factors in FL, including the FLIPI, FLIPI2, PRIMA-PI, and m7-FLIPI. The FLIPI, based on five risk factors, stratifies patients into low-, intermediate-, and high-risk groups. The FLIPI2 incorporates beta2-microglobulin and the longest diameter of the largest involved node, offering improved prognostication. The PRIMA-PI, designed for patients receiving rituximab-containing regimens, uses beta2-microglobulin, bone marrow involvement, and the longest diameter of the largest involved node. The m7-FLIPI integrates mutational status with FLIPI2 parameters, further refining risk stratification. The review also discusses clinical parameters like maximum standardized uptake value on PET/CT and lymphocyte/monocyte ratio as prognostic factors. A high SUVmax and low lymphocyte/monocyte ratio identify high-risk patients. While FL remains incurable, advances in immunochemotherapy and targeted therapies have improved outcomes. This review provides a comprehensive overview of prognostic tools in FL, emphasizing the importance of risk stratification for personalized treatment strategies. Full article
(This article belongs to the Section Clinical Diagnosis and Prognosis)
22 pages, 369 KiB  
Review
The Role of Epithelial–Mesenchymal Transition in Osteosarcoma Progression: From Biology to Therapy
by Andrei-Valentin Patrașcu, Elena Țarcă, Ludmila Lozneanu, Carmen Ungureanu, Eugenia Moroșan, Diana-Elena Parteni, Alina Jehac, Jana Bernic and Elena Cojocaru
Diagnostics 2025, 15(5), 644; https://doi.org/10.3390/diagnostics15050644 - 6 Mar 2025
Abstract
Osteosarcoma (OS) is the most common primary malignant bone tumor, predominantly affecting children, adolescents, and young adults. Epithelial–mesenchymal transition (EMT), a process in which epithelial cells lose their cell–cell adhesion and gain migratory and invasive properties, has been extensively studied in various carcinomas. [...] Read more.
Osteosarcoma (OS) is the most common primary malignant bone tumor, predominantly affecting children, adolescents, and young adults. Epithelial–mesenchymal transition (EMT), a process in which epithelial cells lose their cell–cell adhesion and gain migratory and invasive properties, has been extensively studied in various carcinomas. However, its role in mesenchymal tumors like osteosarcoma remains less explored. EMT is increasingly recognized as a key factor in the progression of osteosarcoma, contributing to tumor invasion, metastasis, and resistance to chemotherapy. This narrative review aims to provide a comprehensive overview of the molecular mechanisms driving EMT in osteosarcoma, highlighting the involvement of signaling pathways such as TGF-β, transcription factors like Snail, Twist, and Zeb, and the role of microRNAs in modulating EMT. Furthermore, we discuss how EMT correlates with poor prognosis and therapy resistance in osteosarcoma patients, emphasizing the potential of targeting EMT for therapeutic intervention. Recent advancements in understanding EMT in osteosarcoma have opened new avenues for treatment, including EMT inhibitors and combination therapies aimed at overcoming drug resistance. By integrating biological insights with clinical implications, this review underscores the importance of EMT as a critical process in osteosarcoma progression and its potential as a therapeutic target. Full article
(This article belongs to the Special Issue Bone Tumours: From Molecular Pathology to Clinical Practice)
12 pages, 1367 KiB  
Article
Investigation of MicroRNA-17 Expression, Tumor Necrosis Factor-α, and Interleukin-6 Levels in Lumbar Degenerative Disc Disease: Case–Control Study
by Luay Şerifoğlu, Müge Kopuz Álvarez Noval, Selvi Duman Bakırezer, Seda Güleç Yılmaz, Eyüp Varol, Muhittin Emre Altunrende, Ali Haluk Düzkalır and Selçuk Özdoğan
J. Clin. Med. 2025, 14(5), 1772; https://doi.org/10.3390/jcm14051772 - 6 Mar 2025
Abstract
Background/Objectives: The aim of the study is to investigate the role of microRNA-17 (miRNA-17), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) in the pathogenesis of lumbar degenerative disc disease (LDDD). The goal is to explore how miRNA-17 regulates inflammation and apoptosis within the [...] Read more.
Background/Objectives: The aim of the study is to investigate the role of microRNA-17 (miRNA-17), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) in the pathogenesis of lumbar degenerative disc disease (LDDD). The goal is to explore how miRNA-17 regulates inflammation and apoptosis within the intervertebral discs, with a particular focus on its involvement in inflammatory pathways via NF-κB signaling. This research seeks to uncover the molecular mechanisms that contribute to LDDD and its associated chronic lower back pain and disability. Methods: A case–control study was conducted, involving 110 patients diagnosed with LDDD and 17 healthy control individuals. Serum levels of miRNA-17, TNF-α, and IL-6 were measured using quantitative real-time PCR and enzyme-linked immunosorbent assays (ELISAs). The patients were further categorized based on the severity of their condition using the Oswestry Disability Index (ODI), which classified them into five subgroups. The correlation between miRNA-17 expression, pro-inflammatory cytokines, and disease severity was analyzed statistically. Results: The results demonstrated a significant downregulation of microRNA-17 in patients with LDDD compared to healthy controls. Inflammatory markers TNF-α and IL-6 were found to be significantly elevated in the patient group. A peak in inflammation and miRNA-17 expression was observed in patients with moderate to severe disability (ODI Grade 3), while inflammation levels decreased in more advanced stages of the disease (ODI Grades 4 and 5), suggesting a possible shift in disease dynamics. Conclusions: This study demonstrates that miRNA-17 plays a regulatory role in inflammation during the progression of LDDD, particularly through the modulation of TNF-α and IL-6 levels. The findings indicate that inflammation is most pronounced in the mid-stages of LDDD, while the later stages are characterized by structural damage rather than ongoing inflammation. These insights could help guide future therapeutic strategies aimed at targeting the molecular mechanisms underlying LDDD, potentially improving patient outcomes. Full article
(This article belongs to the Section Clinical Neurology)
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<p>(<b>a</b>) Relative expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Relative expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>a</b>) Relative expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Relative expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>a</b>) Comparison of serum TNF-a levels in LDDD patient and control groups (* <span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Comparison of serum TNF-a levels in LDDD patient and control groups (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>a</b>) Association between TNF-α and <b>relative</b> expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Association between TNF-α and relative expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3 Cont.
<p>(<b>a</b>) Association between TNF-α and <b>relative</b> expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Association between TNF-α and relative expression of circulating miRNA-17 in LDDD patient subgroups and control group (* <span class="html-italic">p</span> &lt; 0.05).</p>
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14 pages, 599 KiB  
Article
Cardiometabolic Markers in Algerian Obese Subjects with and Without Type 2 Diabetes: Adipocytokine Imbalance as a Risk Factor
by Hassiba Benbaibeche, Abdenour Bounihi, Hamza Saidi, Elhadj Ahmed Koceir and Naim Akhtar Khan
J. Clin. Med. 2025, 14(5), 1770; https://doi.org/10.3390/jcm14051770 - 6 Mar 2025
Abstract
Background/Objectives: An increase in body fat is linked to abnormalities in energy metabolism. We aimed at determining cardiometabolic risk in Algerian participants with obesity alone and with or without type 2 diabetes. The study measured the concentrations of circulating adipocytokines (leptin, adiponectin, [...] Read more.
Background/Objectives: An increase in body fat is linked to abnormalities in energy metabolism. We aimed at determining cardiometabolic risk in Algerian participants with obesity alone and with or without type 2 diabetes. The study measured the concentrations of circulating adipocytokines (leptin, adiponectin, resistin), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) to identify and examine how imbalances in adipocytokines may affect the parameters of cardiometabolic health. Methods: Algerian participants (n = 300) were recruited and divided into three groups: control, obese, and type 2 diabetics (with two sub-groups: with and without obesity). Insulin resistance was evaluated using HOMA-IR, while ELISA was used to measure adipocytokines. Atherogenic index in plasma (AIP), adiponectin-leptin ratio (ALR), and visceral adiposity index (VAI) were also assessed. One-way ANOVA was used to compare obesity and diabetes groups to the control one (p < 0.05). Logistic regression analysis was conducted to strengthen the robustness of statistical correlations. Results: Participants with reduced adiponectin-leptin ratio (ALR) and elevated levels of resistin, TNF-α, and IL-6 are found to be at higher risk of cardiovascular diseases. An imbalance in adipocytokine levels is caused by a decrease in adiponectin concentrations, and an increase in pro-inflammatory adipocytokines that maintain and exacerbate energy imbalance and induces hyperinsulinemia, exposing individuals to a high risk of cardiovascular diseases. Conclusions: Given that ALR is a functional biomarker of inflammation, insulin resistance, and adipose tissue dysfunction, targeting ALR could potentially be a therapeutic approach to coping with obesity-related cardiometabolic risks. Mediterranean diet, weight loss, and increased physical activity can be key components to promote healthy adipose tissue through the increase in ALR. Full article
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<p>Correlation between HDL and VAI, AIP and VAI and between VAI and ALR.</p>
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17 pages, 8973 KiB  
Article
Gambogenic Acid Suppresses Malignant Progression of Non-Small Cell Lung Cancer via GCH1-Mediated Ferroptosis
by Menghan Wang, Jiao Liu, Wenxi Yu, Jiancang Shao, Yang Bao, Mingming Jin, Qingqing Huang and Gang Huang
Pharmaceuticals 2025, 18(3), 374; https://doi.org/10.3390/ph18030374 - 6 Mar 2025
Abstract
Introduction: Non-small cell lung cancer (NSCLC) is a lethal type of lung cancer (LC) with a 5-year survival rate of 19%. Because drug resistance typically develops following chemotherapy, radiotherapy, and immunotherapy, a novel NSCLC therapeutic strategy is urgently demanded. Gambogenic acid (GNA), a [...] Read more.
Introduction: Non-small cell lung cancer (NSCLC) is a lethal type of lung cancer (LC) with a 5-year survival rate of 19%. Because drug resistance typically develops following chemotherapy, radiotherapy, and immunotherapy, a novel NSCLC therapeutic strategy is urgently demanded. Gambogenic acid (GNA), a major bioactive ingredient isolated from gamboge, has multipotent antitumor effects, although activity against NSCLC is unknown. Methods: CCK8, ethynyl deoxyuridine (EdU), the plate colony formation assay, and the transwell and wound healing (WH) assay were used to study the effect of GNA on the proliferation and migration ability of NSCLC. Flow cytometry was used to detect apoptosis and the cell cycle. Proteomic analysis and LiP-SMap were used to detect the downstream target of GNA. Ferroptosis inhibitor ferrostatin-1 was used to detect the effect of GNA on NSCLC ferroptosis. Overexpressing GCH1 was used for a rescue experiment. Subcutaneous tumor and pulmonary metastasis in a mouse model were used to study the effect of GNA on NSCLC growth and metastasis. Results: The results of the present study showed that GNA inhibited the proliferation and migration of NSCLC cells in a dose- and time-dependent manner, which arrested the cell cycle in the G0/G1 phase. In vivo data revealed that GNA inhibited tumor growth and lung metastasis. Proteomic analysis found that GNA significantly inhibited the expression of GTP cyclohydrolase 1 (GCH1). LiP-SMap analysis showed that GNA interacted with ILE248 and ARG249 of GCH1. GCH1 overexpression had a similar role to the ferroptosis inhibitor ferrostatin-1 and restored cell proliferation and migration after GNA treatment. Also, GNA promoted reactive oxygen species (ROS) accumulation, which reduced mitochondrial membrane potential. GCH1 overexpression or ferrostatin-1 treatment reversed GNA regulation of ROS accumulation and mitochondrial membrane potential inhibition. Conclusions: Taken together, these findings confirmed that GNA suppressed the malignant progression of NSCLC by inducing GCH1-mediated ferroptosis. Full article
(This article belongs to the Section Pharmacology)
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<p>GNA treatment inhibits proliferation ability of NSCLC cells. (<b>A</b>–<b>E</b>) CCK-8 results for proliferation ability of A549, HCC1833, H1650, and BEAS-2B cells after treatment with different GNA doses for 24 h. (<b>F</b>) CCK-8 results for proliferation ability of A549 and HCC1833 cells after treatment with IC50 dose of GNA lasting for 24, 48, and 72 h. Data are expressed as mean ± SD. (<b>G</b>–<b>J</b>) EdU results for proliferation ability of A549 and HCC1833 cells (20×). Data are expressed as mean ± SD. (<b>K</b>–<b>N</b>) Colony formation results for proliferation ability of A549 and HCC1833 cells. Data are expressed as mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control.</p>
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<p>GNA treatment inhibits migration ability of NSCLC cells. (<b>A</b>–<b>D</b>) WH results for migration ability of A549 and HCC1833 cells after treatment with different GNA doses for 0, 24, and 48 h (10×). (<b>E</b>–<b>H</b>) Transwell assay results for migration ability of A549 and HCC1833 cells (20×). Data are expressed as mean ± 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 vs. control.</p>
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<p>Effect of GNA on cell cycle and apoptosis regulation. (<b>A</b>–<b>D</b>) Cell cycle and (<b>E</b>–<b>H</b>) apoptosis were detected using flow cytometry in A549 and HCC1833 cells. Data are expressed as mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001 vs. control.</p>
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<p>Effect of GNA on tumor growth and lung metastasis in vivo. (<b>A</b>) Schematic diagram illustrating nude mouse xenografts. (<b>B</b>,<b>C</b>) Representative HCC1833 tumor formation images in nude mouse xenografts. (<b>D</b>) Tumor weight was determined 14 days after injection. (<b>E</b>) Mouse body weight was determined every two days for 14 days. (<b>F</b>) Tumor volumes were recorded every two days. (<b>G</b>) Immunohistochemical analysis showing percentage of Ki67-positive cells. (<b>H</b>) Fluorescence density was determined using in vivo imaging. (<b>I</b>) HE staining results for tumor lesion numbers. Data are expressed as mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001 vs. control.</p>
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<p>GNA treatment inhibits GCH1 expression. (<b>A</b>) KEGG analysis showing proteomic results after treatment with or without GNA in HCC1833 cells. (<b>B</b>,<b>C</b>) Western blot results for GCH1, DHFR, and GPX4 expression in HCC1833 with or without GNA treatment. Data are expressed as mean ± SD. ns: no significance, *** <span class="html-italic">p</span> &lt; 0.001 vs. NC.</p>
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<p>GCH1 is the downstream target of GNA. (<b>A</b>) GNA is linked to GCH1 active site via hydrogen bonds to form a complex. (<b>B</b>,<b>C</b>) Flow chart depicting LiP-SMap assay. Freshly prepared whole-cell lysates were treated with or without GNA followed by proteinase K (PK) digestion and MS analysis. GCH1 binding prevents PK digestion, leading to differential MS peptide profiling.</p>
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<p>GNA treatment inhibits malignant progression of NSCLC by promoting ferroptosis. (<b>A</b>,<b>B</b>) Colony formation assay results for clone numbers in HCC1833 cells. (<b>C</b>) CCK-8 results for HCC1833 proliferation. (<b>D</b>,<b>E</b>) Immunofluorescence results for mitochondrial membrane potential (20×). (<b>F</b>,<b>G</b>) Immunofluorescence results for ROS deposition (20×). (<b>H</b>,<b>I</b>) BODIPY 581/591 results for lipid peroxidation. Data are expressed as mean ± SD. ns: no 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 vs. control.</p>
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<p>GCH1 overexpression reverses inhibitory effect of GNA on malignant progression in NSCLC by regulation ferroptosis. (<b>A</b>) RT-qPCR results for GCH1 expression in HCC1833 cells after transfection with GCH1 overexpression vector. (<b>B</b>) Western blot results for GCH1 expression. (<b>C</b>) RT-qPCR results for ferroptosis-related gene expression. (<b>D</b>) Western blot results for ferroptosis-related protein expression. (<b>E</b>) CCK-8 results for proliferation ability of HCC1833 cells. (<b>F</b>,<b>G</b>) Colony formation assay results for clone numbers in HCC1833 cells. (<b>H</b>,<b>I</b>) Flow detection of oxidative stress in HCC1833 cells after different treatments. (<b>J</b>,<b>K</b>) Immunofluorescence results for tetramethylrhodamine ethyl ester perchlorate staining show mitochondrial membrane potential (20×). (<b>L</b>,<b>M</b>) BODIPY 665/676 results for lipid peroxidation. Data are expressed as mean ± SD. ns: no 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 vs. control.</p>
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<p>GCH1 overexpression reverses inhibitory effect of GNA on tumor growth in NSCLC. (<b>A</b>) Representative HCC1833 tumor formation images in nude mouse xenografts. (<b>B</b>) Tumor weight was determined 14 days after injection. (<b>C</b>) Mouse body weight was determined every two days for 14 days. (<b>D</b>) Tumor volumes were recorded every two days. Data are expressed as means ± SD. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. NC. (<b>E</b>,<b>F</b>) Immunohistochemical analysis showing percentage of Ki67-positive cells. Data are expressed as mean ± SD. ns: no significance, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001 vs. control.</p>
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20 pages, 1062 KiB  
Review
The Emerging Role of Nanoparticles Combined with Either Radiotherapy or Hyperthermia in Head and Neck Cancer: A Current Review
by Elena Vlastou, Andromachi Kougioumtzopoulou, Kalliopi Platoni, Ioannis Georgakopoulos, Nefeli Lagopati, Vasileios Kouloulias and Anna Zygogianni
Cancers 2025, 17(5), 899; https://doi.org/10.3390/cancers17050899 - 6 Mar 2025
Viewed by 119
Abstract
Head and neck cancer (HNC) includes various malignancies and represents the seventh most common cancer worldwide. The early diagnosis of HNC results in a 70–90% five-year survival rate, which declines with locally advanced stages of disease. Current care employs a multimodal strategy encompassing [...] Read more.
Head and neck cancer (HNC) includes various malignancies and represents the seventh most common cancer worldwide. The early diagnosis of HNC results in a 70–90% five-year survival rate, which declines with locally advanced stages of disease. Current care employs a multimodal strategy encompassing surgery, radiation therapy (RT), chemotherapy, and immunotherapy, while treatment options vary according to the stage, tumor features, and patient characteristics. About 75% of patients with HNC will benefit from RT, either as a primary treatment or as adjuvant therapy following surgical resection. Technological improvements in RT, such as intensity-modulated RT (IMRT) and image-guided RT (IGRT), have enhanced tumor targeting and minimized adjacent healthy tissue irradiation while also expanding RT to the recurrent or metastatic setting. Innovative therapeutic strategies for HNC integrate RT with immunotherapy, gene therapy, molecular targeted therapy, photodynamic therapy, photothermal therapy, and nanoparticles (NPs), with the objective of optimizing tumor control while reducing damage to normal tissues. NPs are emerging as possible radiosensitizers in HNC treatment, enhancing the efficacy of RT, chemotherapy, and immunotherapy. In vivo and in vitro studies on the irradiation of tumors containing gold (Au), gadolinium (Gd), and hafnium oxide (HfO2) NPs show promising results in enhancing tumor destruction and survival rates, indicating their potential for clinical application. Hyperthermia, investigated as an adjunct treatment, potentially improves outcomes when combined with RT or chemotherapy, with advancements in nanotechnology renewing interest in this approach in HNC. At present, NBTXR3 is the sole NP that is being investigated in clinical trials for the enhancement of HNC RT. Full article
(This article belongs to the Special Issue Advances in Radiation Therapy for Head and Neck Cancer)
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<p>The predominant physical mechanisms of photon (energy ≤ 10 MV)–soft tissue atom interactions and their biological effects.</p>
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<p>A brief representation of NPs’ radiosensitization mechanism in an animal model.</p>
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58 pages, 5256 KiB  
Review
The Histomorphology to Molecular Transition: Exploring the Genomic Landscape of Poorly Differentiated Epithelial Endometrial Cancers
by Thulo Molefi, Lloyd Mabonga, Rodney Hull, Absalom Mwazha, Motshedisi Sebitloane and Zodwa Dlamini
Cells 2025, 14(5), 382; https://doi.org/10.3390/cells14050382 - 5 Mar 2025
Viewed by 153
Abstract
The peremptory need to circumvent challenges associated with poorly differentiated epithelial endometrial cancers (PDEECs), also known as Type II endometrial cancers (ECs), has prompted therapeutic interrogation of the prototypically intractable and most prevalent gynecological malignancy. PDEECs account for most endometrial cancer-related mortalities due [...] Read more.
The peremptory need to circumvent challenges associated with poorly differentiated epithelial endometrial cancers (PDEECs), also known as Type II endometrial cancers (ECs), has prompted therapeutic interrogation of the prototypically intractable and most prevalent gynecological malignancy. PDEECs account for most endometrial cancer-related mortalities due to their aggressive nature, late-stage detection, and poor response to standard therapies. PDEECs are characterized by heterogeneous histopathological features and distinct molecular profiles, and they pose significant clinical challenges due to their propensity for rapid progression. Regardless of the complexities around PDEECs, they are still being administered inefficiently in the same manner as clinically indolent and readily curable type-I ECs. Currently, there are no targeted therapies for the treatment of PDEECs. The realization of the need for new treatment options has transformed our understanding of PDEECs by enabling more precise classification based on genomic profiling. The transition from a histopathological to a molecular classification has provided critical insights into the underlying genetic and epigenetic alterations in these malignancies. This review explores the genomic landscape of PDEECs, with a focus on identifying key molecular subtypes and associated genetic mutations that are prevalent in aggressive variants. Here, we discuss how molecular classification correlates with clinical outcomes and can refine diagnostic accuracy, predict patient prognosis, and inform therapeutic strategies. Deciphering the molecular underpinnings of PDEECs has led to advances in precision oncology and protracted therapeutic remissions for patients with these untamable malignancies. Full article
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<p>Global incidence and mortality rates of endometrial cancer. (<b>A</b>) The graph depicts the global trends in ASIR for endometrial cancer over the last 30 years, from 1990 to 2019, in countries grouped by economic status. The figure shows an increase in the incidence of the disease, regardless of income. However, a trend is visible in that the higher the income of a country, the greater the incidence of endometrial cancer. The study of the global burden of disease classifies different regions of the world. (<b>B</b>) Map depicting high-, middle-, and low-income countries. (<b>C</b>) This figure shows the age-standardized incidence rate per 100,000 in 2019 for each of the adjacent GBD regions. High-income North America, Western Europe, and East Asia are the GBD regions with the highest incidence. GBD values can be used to calculate changes in the incidence of disease over time, represented as a percentage. (<b>D</b>) Shows the global increase in endometrial cancer incidence 1990–2019. This was calculated by dividing the ASIR in 2019 by the ASIR from 1990 and multiplying by 100. The map and heatmap indicate that regions associated with lower income have faster-growing rates of endometrial cancer incidence. The increase in the incidence in low-to middle-income regions is thought to be linked to changes in lifestyle and a higher prevalence of risk factors such as obesity and inactivity levels. ASIR: age-standardized incidence rate. SDI: socio-demographic index. GBD: Global Burden of Disease (Figure adapted from [<a href="#B3-cells-14-00382" class="html-bibr">3</a>]).</p>
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<p>The histologic subtypes of poorly differentiated epithelial endometrial cancers (PDEECs). The histological subtypes of PDEECs are a heterogeneous group of aggressive endometrial malignancies characterized by high-grade cellular atypia, increased mitotic activity, and poor glandular differentiation. The subtypes depicted include serous carcinoma, high-grade endometrioid carcinoma, clear cell endometrial carcinoma, dedifferentiated endometrial carcinoma, differentiated endometrial carcinoma, and undifferentiated endometrial carcinoma. Each histological subtype is associated with distinct molecular alterations, prognostic implications, and treatment responses. Representative histological images stained with hematoxylin and eosin (H&amp;E) highlight the morphological diversity among PDEECs. The immunohistochemical markers used for differential diagnosis include p53, Napsin A, and E-cadherin.</p>
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<p>Molecular classification of poorly differentiated epithelial endometrial cancers (PDEECs). This classification provides insights into the biological diversity and clinical behavior of these aggressive tumors. Primarily defined through genomic and transcriptomic analyses, this classification has helped refine the diagnostic criteria, predict prognosis, and identify potential therapeutic targets. It divides PDEECs into four main subtypes, namely, POLE-ultramutated, microsatellite instability-high (MSI-H), copy number low (CNL), and copy number high (CNH), based on specific molecular markers.</p>
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<p>POLE mutations within the exonuclease domain. POLE exonuclease domain mutations significantly influence PDEEC biology. They drive a hypermutated phenotype that promotes immune recognition, often leading to better patient outcomes despite high tumor grades. This unique profile positions POLE as a valuable prognostic and predictive marker in PDEECs, guiding therapeutic approaches that prioritize immune-based treatments (figure adapted from [<a href="#B105-cells-14-00382" class="html-bibr">105</a>]).</p>
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<p>Overview of the PI3K/AKT/mTOR pathway. In healthy cells, this pathway is tightly regulated, with phosphatase and tensin homolog (PTEN) acting as a critical suppressor by dephosphorylating PIP3 back to PIP2, thereby reducing PI3K/AKT activity. Mutations or dysregulation of genes such as PIK3CA, PTEN, and AKT are common in PDEECs, where the PI3K/AKT/mTOR pathway contributes to uncontrolled cell growth, resistance to apoptosis, and enhanced survival. Consequently, this pathway is a significant focus for PDEEC research, with inhibitors targeting PI3K, AKT, and mTOR showing potential in treating various tumors, especially those that exhibit high pathway activation owing to genetic alterations (figure adapted from [<a href="#B142-cells-14-00382" class="html-bibr">142</a>]).</p>
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<p>Overview of p53 pathway dysfunction. Dysfunction of the p53 pathway in PDEECs is a driving factor in tumor progression and therapy resistance. Understanding and targeting this dysfunction is central to improving treatment strategies for high-grade aggressive cancers. As research advances, the development of p53-targeted therapies, synthetic lethal approaches, and combination regimens holds promise for addressing the challenges associated with p53-mutant PDEECs (figure adapted from [<a href="#B159-cells-14-00382" class="html-bibr">159</a>]).</p>
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<p>Mismatch repair (MMR) pathway and mechanism. MMR deficiency is a critical factor in the pathology and treatment of PDEECs. By contributing to genomic instability and high MSI, it not only promotes tumor progression but also presents an opportunity for targeted immunotherapy, which could enhance survival in affected patients. Identifying and understanding MMR deficiency allows clinicians to personalize treatment and may pave the way for novel therapeutic strategies for endometrial cancer (figure adapted from [<a href="#B163-cells-14-00382" class="html-bibr">163</a>]).</p>
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<p>PARP inhibitors in homologous recombination deficiency (HRD) in PDEECs. PARP inhibitors have emerged as a promising therapeutic strategy for treating PDEECs with homologous recombination deficiency (HRD). HRD is a condition in which cells lose the ability to accurately repair double-strand DNA breaks via the homologous recombination (HR) pathway, often due to mutations or deficiencies in key genes, such as BRCA1, BRCA2, and PTEN. HRD makes cancer cells more reliant on alternative DNA repair mechanisms, such as those mediated by PARP. By inhibiting PARP, these drugs trap cancer cells through a cycle of DNA damage, ultimately leading to cell death. In PDEECs, PARP inhibitors show promise as a targeted treatment, particularly for subtypes that are resistant to conventional therapies (figure adapted from [<a href="#B60-cells-14-00382" class="html-bibr">60</a>]).</p>
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26 pages, 4847 KiB  
Article
Investigation on Human Carbonic Anhydrase IX and XII Inhibitory Activity and A549 Antiproliferative Activity of a New Class of Coumarinamides
by Davide Moi, Simone Carradori, Marialucia Gallorini, Noemi Mencarelli, Alberto Deplano, Andrea Angeli, Serena Vittorio, Claudiu T. Supuran and Valentina Onnis
Pharmaceuticals 2025, 18(3), 372; https://doi.org/10.3390/ph18030372 - 5 Mar 2025
Viewed by 203
Abstract
Background—Aggressive solid tumors are commonly characterized by both basic intracellular pH and acidic extracellular pH, which increase cell survival and proliferation. As carbonic anhydrases IX/XII are involved in this pH regulation, their inhibition is an appealing approach in cancer therapy, avoiding cancer [...] Read more.
Background—Aggressive solid tumors are commonly characterized by both basic intracellular pH and acidic extracellular pH, which increase cell survival and proliferation. As carbonic anhydrases IX/XII are involved in this pH regulation, their inhibition is an appealing approach in cancer therapy, avoiding cancer cell survival and proliferation. Substituted coumarins are selective non-classical CA IX and CA XII inhibitors. Methods—In this study, new 7-hydroxycoumarinamides were synthesized and assayed for CA inhibition and antiproliferative activity. Results—All of the coumarinamides showed human CA IX and CA XII selective inhibition over the off-target CA I and CA II isoforms. Coumarin acts as a suicide inhibitor because its heterocyclic ring can be hydrolyzed by CA esterase activity to give the corresponding 2-hydroxycinnamic acid derivative which blocks the entrance of the active site. The 2-hydroxycinnamic acid derivatives deriving from the most potent and selective coumarinamides were docked into CA IX and XII to better understand the activity and selectivity against the two CA isoforms. The most active coumarinamides also produced a decrease of A549 cell proliferation and were able to arrest cells at the G1/S checkpoint. Conclusions—These results may open new perspectives for developing coumarin-based CA IX/XII inhibitors. Full article
(This article belongs to the Section Medicinal Chemistry)
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Figure 1

Figure 1
<p>Hydrolysis of coumarin (<b>A</b>) to 2-hydroxycinnamic acid (<b>B</b>).</p>
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<p>Docking poses of the <span class="html-italic">E/Z</span> isomers of hydrolyzed coumarins <b>7A</b>, <b>9A</b>, <b>23A</b> and <b>38A</b> into <span class="html-italic">h</span>CA IX. (<b>A</b>) (<span class="html-italic">E</span>)-<b>7A</b>, (<b>B</b>) (<span class="html-italic">Z</span>)-<b>7A</b>, (<b>C</b>) (<span class="html-italic">E</span>)-<b>9A</b>, (<b>D</b>) (<span class="html-italic">Z</span>)-<b>9A</b>, (<b>E</b>) (<span class="html-italic">E</span>)-<b>23A</b>, (<b>F</b>) (<span class="html-italic">Z</span>)-<b>23A</b>, (<b>G</b>) (<span class="html-italic">E</span>)-<b>38A</b>, (<b>H</b>) (Z)-<b>38A</b>.</p>
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<p>Docking poses of the <span class="html-italic">E/Z</span> isomers of hydrolyzed coumarins <b>7A</b>, <b>9A</b>, <b>23A</b> and <b>38A</b> into <span class="html-italic">h</span>-CA XII. (<b>A</b>) (<span class="html-italic">E</span>)-<b>7A</b>, (<b>B</b>) (<span class="html-italic">Z</span>)-<b>7A</b>, (<b>C</b>) (<span class="html-italic">E</span>)-<b>9A</b>, (<b>D</b>) (<span class="html-italic">Z</span>)-<b>9A</b>, (<b>E</b>) (<span class="html-italic">E</span>)-<b>23A</b>, (<b>F</b>) (<span class="html-italic">Z</span>)-<b>23A</b>, (<b>G</b>) (<span class="html-italic">E</span>)-<b>38A</b>, (<b>H</b>) (<span class="html-italic">Z</span>)-<b>38A</b>.</p>
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<p>Cell viability of BEAS (<b>a</b>) and (<b>b</b>) A549 cells exposed to increasing concentrations (0–150 µM) of selected compounds (<b>4</b>-<b>7</b>, <b>9</b>, <b>19</b>, <b>22</b>, <b>23</b>, <b>25</b>, <b>29</b>, <b>30</b>, <b>32</b>, <b>38</b>, <b>44</b> and <b>45</b>) for 48 h. (<b>c</b>) Cell viability of BEAS and A549 cells exposed to doxorubicin (0-10 µM) after 48 h of exposure. Bar graphs represent cell viability percentages. The untreated control (CTRL = 0 µM) is set as the 100%. Data are presented as means ± standard deviations obtained from one experiment in triplicates (n = 3). * = <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, **** = <span class="html-italic">p</span> &lt; 0.00001 comparing treated to the untreated control.</p>
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<p>(<b>a</b>) Cytotoxicity occurrence in A549 cells exposed to increasing concentrations (0–150 µM) of compounds <b>7</b>, <b>9</b>, <b>23</b> and <b>38</b> after 24 h. The bar graphs show the amount of lactate dehydrogenase (LDH) released from treated A549 cells as a fold increase respective to that secreted by untreated cells (CTRL = 0 µM) after 24 h of exposure. (<b>b</b>) Light phase-contrast images of A549 cells 48 h after treatment. Magnification 10×. Yellow arrows highlight morphological changes in the cell population. Data are presented as means ± standard deviations obtained from one experiment in triplicates (n = 3). ** = <span class="html-italic">p</span> &lt; 0.001, **** = <span class="html-italic">p</span> &lt; 0.00001 comparing treated to the untreated control.</p>
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<p>(<b>a</b>) Cell cycle analysis in A549 cells exposed to increasing concentrations (0–150 µM) of compounds <b>7</b>, <b>9</b>, <b>23</b> and <b>38</b> after 48 h. Data are presented as means ± standard deviations from three independent experiments (n = 3). Bars highlight cell percentages in the various phases of the cell cycle (G1, S, and G2) of A549. * = <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, **** = <span class="html-italic">p</span> &lt; 0.00001 comparing treated with the untreated control (G1 phase). § = <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, §§§§ = <span class="html-italic">p</span> &lt; 0.00001 comparing treated with the untreated control (S phase). # = <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, #### = <span class="html-italic">p</span> &lt; 0.00001 comparing treated with the untreated control (G2 phase). (<b>b</b>) The top panel displays the DNA profile of cells 48 h after treatment. Peaks are generated by the emission of PI in the FL3 fluorescence channel. The bottom panel is a dot plot representing the gating strategy.</p>
Full article ">Scheme 1
<p>General synthetic procedure for 7-hydroxycoumarin amides <b>4</b>–<b>45</b>. Reagents and conditions are as follows: (i) CH<sub>3</sub>COONH<sub>4</sub>, water, reflux 15 h, 87% yield; (ii) substituted benzylamines, EDCI, HOBt, dry MeCN, r.t. 6 h, 44–92% yield; (iii) substituted phenylethylamines, EDCI, HOBt, dry MeCN, r.t. 6 h, 70–90% yield; (iv) substituted piperazines, EDCI, HOBt, dry MeCN, r.t. 6 h, 47–82% yield.</p>
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<p>Hydrolysis of coumarins <b>7</b>, <b>9</b>, <b>23</b> and <b>38</b> to 2,4-dihydroxycinnamic acid amides <b>7A</b>, <b>9A</b>, <b>23A</b> and <b>38A</b>.</p>
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20 pages, 20795 KiB  
Article
Effects of Pharmacological Dose of Vitamin C on MDA-MB-231 Cells
by Lunawati Lo Bennett
Biomedicines 2025, 13(3), 640; https://doi.org/10.3390/biomedicines13030640 - 5 Mar 2025
Viewed by 104
Abstract
Background/Objectives: In 2022, approximately 2.3 million women were diagnosed with breast cancer worldwide, resulting in 670,000 deaths, which accounted for 6.9% of all cancer-related deaths. In the United States, 1 in 8 women will be diagnosed with breast cancer during their lifetime. It [...] Read more.
Background/Objectives: In 2022, approximately 2.3 million women were diagnosed with breast cancer worldwide, resulting in 670,000 deaths, which accounted for 6.9% of all cancer-related deaths. In the United States, 1 in 8 women will be diagnosed with breast cancer during their lifetime. It was estimated that 2024 would identify about 310,720 women and 2800 men diagnosed with invasive breast cancer. The future global burden of breast cancer is projected to rise to over 3 million new cases and 1 million deaths by 2040. Approximately 20% of breast cancer diagnoses are triple-negative breast cancer (TNBC), a type of cancer that lacks receptors for estrogen (ER-negative), progesterone (PR-negative), and human epidermal growth factor receptor 2 (HER2/neu-negative). Consequently, TNBC does not respond to hormonal or targeted therapies, making it challenging to treat due to its rapid growth, metastasis, and high recurrence rate within the first three years of therapy. Alternative chemotherapies are needed to address this problem. A pharmacological dose of vitamin C (high-dose VC) has been identified as a potential treatment for some cancer cells. The present study aimed to evaluate whether VC has a therapeutic effect on TNBC, using MDA-MB-231 cells as the model. Additionally, VC’s effects were trialed on other cancer cells such as MCF7 and on non-cancerous kidney HEK 293 and lung CCL205 cells. Methods: The MTT assay, Hoechst 33342 staining, nuclear-ID red/green staining, Rhodamine 123 staining, and Western blot analysis were employed to test the hypothesis that a pharmacological dose of VC can kill TNBC cells. Results: The upregulation of Apaf-1 and caspases -7, -8, and -9, the inhibition of matrix metalloproteinases (MMP-2 and MMP-9), a reduction in cell cycle protein expression, and the enhancement of tumor suppressor proteins such as p53 and p21 indicate that a pharmacological dose of VC has promising anti-cancer properties in the treatment of breast cancers. Conclusions: Pharmacological dose of VC exerts significant anti-cancer effects in MDA-MB-231 cells by promoting apoptosis, inhibiting metastasis, disrupting cell cycle progression, and enhancing tumor suppressor activity. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) MTT result of cell viability MDA-MB-231 cells treated with VC from 0 to 125 mM. (<b>b</b>) shows MCF7 cells treated with VC from 0 to 125 mM. (<b>c</b>) shows that rat spleen had higher % cell viability with treatment of VC at 2.5 mM and 8 mM showing non-cytotoxic effect of VC on normal cells.</p>
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<p>Inverted microscopic images of MDA-MB-231 and MCF7 cancer cells after 24 h of treatment with VC at concentrations of 8 mM and 16 mM for MDA-MB-231, and with VC at concentrations of 4 mM and 7 mM for MCF7. Higher concentrations of VC led to increased cell death in both MDA-MB-231 and MCF7 compared to their respective controls (<b>a,b</b>). In contrast, VC at 5 mM and 15 mM promoted cell growth in non-cancerous HEK-293 kidney cells (<b>c</b>). The scale bar represents 40×.</p>
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<p>Image (<b>a</b>) displays inverted microscope images of cell migration following the 24 h treatment of MDA-MB-231 cells with VC 8 mM or 16 mM VC, while MCF7 cells received 4 mM and 7 mM of VC. In the control groups, a narrow scratch area indicated maximal cancer cell migration, whereas VC-treated cells exhibited a wider scratch area, reflecting reduced migration (<b>a</b>,<b>c</b>). Conversely, VC at 5 mM and 15 mM enhanced cell growth in non-cancerous HEK 293 kidney cells, as evidenced by a decreased scratch width (<b>e</b>). Figures (<b>b</b>,<b>d</b>,<b>f</b>) presents the corresponding histograms, with ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 (post hoc Newman–Keuls test) compared to the 0 h measurements of the corresponding control cells.</p>
Full article ">Figure 3 Cont.
<p>Image (<b>a</b>) displays inverted microscope images of cell migration following the 24 h treatment of MDA-MB-231 cells with VC 8 mM or 16 mM VC, while MCF7 cells received 4 mM and 7 mM of VC. In the control groups, a narrow scratch area indicated maximal cancer cell migration, whereas VC-treated cells exhibited a wider scratch area, reflecting reduced migration (<b>a</b>,<b>c</b>). Conversely, VC at 5 mM and 15 mM enhanced cell growth in non-cancerous HEK 293 kidney cells, as evidenced by a decreased scratch width (<b>e</b>). Figures (<b>b</b>,<b>d</b>,<b>f</b>) presents the corresponding histograms, with ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 (post hoc Newman–Keuls test) compared to the 0 h measurements of the corresponding control cells.</p>
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<p>(<b>a</b>) displays fluorescence microscopy images of MDA-MB-231 control cells alongside cells treated with 8 mM and 16 mM VC for 24 h, followed by Hoechst 33342 staining. (<b>b</b>) illustrates a histogram comparing the percentage of apoptotic and live cells relative to the control. (<b>c</b>) presents Western blot analysis showing the expression levels of Bax, Bcl-2, and cytochrome C, while (<b>d</b>) provides a histogram comparing these expression levels to the control group. In MCF7 cells, fluorescence analysis revealed significant changes in the live-to-apoptotic cell ratio (<b>e</b>,<b>f</b>). In contrast, VC treatment at 5 mM and 15 mM in non-cancerous HEK 293 kidney cells or CCL 205 lung cells did not significantly affect this ratio, indicating no cytotoxic effect on non-cancerous cells (<b>g</b>–<b>j</b>). The scale bar represents 100 µm. Statistical significance was determined using the post hoc Newman–Keuls test ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001) compared to the respective controls.</p>
Full article ">Figure 4 Cont.
<p>(<b>a</b>) displays fluorescence microscopy images of MDA-MB-231 control cells alongside cells treated with 8 mM and 16 mM VC for 24 h, followed by Hoechst 33342 staining. (<b>b</b>) illustrates a histogram comparing the percentage of apoptotic and live cells relative to the control. (<b>c</b>) presents Western blot analysis showing the expression levels of Bax, Bcl-2, and cytochrome C, while (<b>d</b>) provides a histogram comparing these expression levels to the control group. In MCF7 cells, fluorescence analysis revealed significant changes in the live-to-apoptotic cell ratio (<b>e</b>,<b>f</b>). In contrast, VC treatment at 5 mM and 15 mM in non-cancerous HEK 293 kidney cells or CCL 205 lung cells did not significantly affect this ratio, indicating no cytotoxic effect on non-cancerous cells (<b>g</b>–<b>j</b>). The scale bar represents 100 µm. Statistical significance was determined using the post hoc Newman–Keuls test ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001) compared to the respective controls.</p>
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<p>(<b>a</b>) Fluorescence microscopic images of MDA-MB-231cells after 24 h treatment with VC 8 mM or VC 16 mM and staining with Rhodamine 123. (<b>b</b>) Histogram represents percentage of cells changing in mitochondrial membrane potential, with higher VC showing pronounced decrease in membrane potential and darker cells compared to control. (<b>c</b>) Shows Western blot analysis of different signaling activity proteins involved in caspase cascade and Apaf-1. (<b>d</b>) Histogram represents upregulation of Apaf-1 and cas-3 and -9 in cells treated with VC 8 mM or 16 mM in MD-MBA-231 cells. Fluorescence analysis of MCF7 also showed pronounced decrease in cells treated with VC 4 mM and 7 mM, with the histogram representing the change in fluorescence (<b>e</b>,<b>f</b>). In contrast, VC treatment at 5 mM and 15 mM in non-cancerous HEK 293 and CCL 205 cells showed significant increase in membrane potential assuring favorable effect of VC in non-cancerous cells (<b>g</b>,<b>i</b>). The histograms show the effect of VC on HEK 293 and CCL 205 (<b>h</b>,<b>j</b>). Scale bar represents 100 µm. Significant change in mitochondrial membrane potential for treatment vs. control group, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001, post hoc Newman–Keuls test.</p>
Full article ">Figure 5 Cont.
<p>(<b>a</b>) Fluorescence microscopic images of MDA-MB-231cells after 24 h treatment with VC 8 mM or VC 16 mM and staining with Rhodamine 123. (<b>b</b>) Histogram represents percentage of cells changing in mitochondrial membrane potential, with higher VC showing pronounced decrease in membrane potential and darker cells compared to control. (<b>c</b>) Shows Western blot analysis of different signaling activity proteins involved in caspase cascade and Apaf-1. (<b>d</b>) Histogram represents upregulation of Apaf-1 and cas-3 and -9 in cells treated with VC 8 mM or 16 mM in MD-MBA-231 cells. Fluorescence analysis of MCF7 also showed pronounced decrease in cells treated with VC 4 mM and 7 mM, with the histogram representing the change in fluorescence (<b>e</b>,<b>f</b>). In contrast, VC treatment at 5 mM and 15 mM in non-cancerous HEK 293 and CCL 205 cells showed significant increase in membrane potential assuring favorable effect of VC in non-cancerous cells (<b>g</b>,<b>i</b>). The histograms show the effect of VC on HEK 293 and CCL 205 (<b>h</b>,<b>j</b>). Scale bar represents 100 µm. Significant change in mitochondrial membrane potential for treatment vs. control group, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001, post hoc Newman–Keuls test.</p>
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<p>(<b>a</b>) shows the results of intracellular ROS generation in MDA-MB-231 cells using the H2DCFDA staining method. Control cells displayed minimal ROS formation, as indicated by darker green fluorescence. In contrast, cells treated with VC at 8 mM and 16 mM exhibited increased ROS levels, as characterized by progressively brighter green fluorescence. The intensity of ROS generation was directly proportional to the concentration of VC, with 16 mM showing the highest level of ROS. (<b>b</b>) presents a histogram comparing ROS levels in treated cells versus control. To further evaluate the effect of VC on different cell lines, ROS generation was also assessed in MCF7 cells and non-cancerous HEK 293 kidney and CCL 205 lung cells. MCF cells demonstrated a similar increase in ROS as MDA-MB-231 cells (<b>c</b>) with histogram presented (<b>d</b>). Non-cancerous HEK 293 and CCL 205 cells exhibited significantly lower levels of ROS in response to VC treatment, suggesting a minimal or non-cytotoxic effect of VC on non-cancerous cells (<b>e</b>–<b>h</b>). Scale bar indicated 100 µm. A significant change in intracellular ROS generation versus control, *** <span class="html-italic">p</span> &lt; 0.001, post hoc Newman–Keuls test.</p>
Full article ">Figure 6 Cont.
<p>(<b>a</b>) shows the results of intracellular ROS generation in MDA-MB-231 cells using the H2DCFDA staining method. Control cells displayed minimal ROS formation, as indicated by darker green fluorescence. In contrast, cells treated with VC at 8 mM and 16 mM exhibited increased ROS levels, as characterized by progressively brighter green fluorescence. The intensity of ROS generation was directly proportional to the concentration of VC, with 16 mM showing the highest level of ROS. (<b>b</b>) presents a histogram comparing ROS levels in treated cells versus control. To further evaluate the effect of VC on different cell lines, ROS generation was also assessed in MCF7 cells and non-cancerous HEK 293 kidney and CCL 205 lung cells. MCF cells demonstrated a similar increase in ROS as MDA-MB-231 cells (<b>c</b>) with histogram presented (<b>d</b>). Non-cancerous HEK 293 and CCL 205 cells exhibited significantly lower levels of ROS in response to VC treatment, suggesting a minimal or non-cytotoxic effect of VC on non-cancerous cells (<b>e</b>–<b>h</b>). Scale bar indicated 100 µm. A significant change in intracellular ROS generation versus control, *** <span class="html-italic">p</span> &lt; 0.001, post hoc Newman–Keuls test.</p>
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<p>(<b>a</b>) Fluorescence microscopic images from alive and death nucleic acid staining using nuclear-ID red/green cell viability method. (<b>b</b>) The histogram represents the percentage of alive or death from cells treated with VC 8 mM or VC 18 16 mM vs. control of MDA-MB-231. (<b>c</b>–<b>h</b>) depict the effects of varying VC concentrations on cell viability in MCF7 cancer cells, non-cancerous HEK 293 kidney cells, and CCL 205 lung cells. MCF7 cells exhibited an increase in cell death at higher VC concentrations: 7 mM vs 4 mM (<b>c</b>,<b>d</b>). As the VC dose increased, a higher proportion of cells were stained red, reflecting the cytotoxic effects of VC. Control HEK 293 and CCL 205 cells versus cells treated with 5 mM or 15 mM VC displayed a similar proportion of live and dead cells, indicating that VC had no significant cytotoxic effect on these non-cancerous cell lines. The green fluorescence in both HEK 293 and CCL 205 cells was predominant, signifying high cell viability in both control and VC-treated groups (<b>e</b>–<b>h</b>). These findings highlight VC’s selective cytotoxicity, with higher concentrations inducing cell death in cancerous MDA-MB-231 and MCF7 cells, while non-cancerous HEK 293 and CCL 205 cells remained largely unaffected. Scale bar indicates 100 µm. Significant change in cells death due to VC treatment versus control, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001, post hoc Newman–Keuls test.</p>
Full article ">Figure 7 Cont.
<p>(<b>a</b>) Fluorescence microscopic images from alive and death nucleic acid staining using nuclear-ID red/green cell viability method. (<b>b</b>) The histogram represents the percentage of alive or death from cells treated with VC 8 mM or VC 18 16 mM vs. control of MDA-MB-231. (<b>c</b>–<b>h</b>) depict the effects of varying VC concentrations on cell viability in MCF7 cancer cells, non-cancerous HEK 293 kidney cells, and CCL 205 lung cells. MCF7 cells exhibited an increase in cell death at higher VC concentrations: 7 mM vs 4 mM (<b>c</b>,<b>d</b>). As the VC dose increased, a higher proportion of cells were stained red, reflecting the cytotoxic effects of VC. Control HEK 293 and CCL 205 cells versus cells treated with 5 mM or 15 mM VC displayed a similar proportion of live and dead cells, indicating that VC had no significant cytotoxic effect on these non-cancerous cell lines. The green fluorescence in both HEK 293 and CCL 205 cells was predominant, signifying high cell viability in both control and VC-treated groups (<b>e</b>–<b>h</b>). These findings highlight VC’s selective cytotoxicity, with higher concentrations inducing cell death in cancerous MDA-MB-231 and MCF7 cells, while non-cancerous HEK 293 and CCL 205 cells remained largely unaffected. Scale bar indicates 100 µm. Significant change in cells death due to VC treatment versus control, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001, post hoc Newman–Keuls test.</p>
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<p>(<b>a</b>) Western blot analysis of proteins involved in cell cycle regulation. The expression of CDK2, cyclin D1, and cyclin B1 significantly decreased in cells treated with VC. (<b>b</b>) shows histogram downregulation of these proteins compared to its control, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span>&lt; 0.001, post hoc Newman–Keuls test.</p>
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<p>(<b>a</b>) Western blot analysis of MMP2 and MMP9 proteins. (<b>b</b>) Histogram represents downregulation of these proteins vs. control group. Significant decrease in protein expressions *** <span class="html-italic">p</span>&lt; 0.001, post hoc Newman–Keuls test.</p>
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<p>(<b>a</b>) Western blot analysis of p21, p53, pTEN, and MDM2 proteins. (<b>b</b>) Histogram represents the upregulation of p21, p53 and pTEN proteins and the downregulation of MDM2 as compared to the control. Significant change in protein expressions vs. control, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span>&lt; 0.001, post hoc Newman–Keuls test.</p>
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<p>(<b>a</b>) Western blot analysis of p13k, Akt, and mTOR proteins. (<b>b</b>) Histogram represents the downregulation of p13k, Akt, and mTOR proteins from cells treated with VC as compared to the control. Significant change in protein expressions *** <span class="html-italic">p</span>&lt; 0.001, post hoc Newman–Keuls test.</p>
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<p>The proposed mechanism of action of a high dose of VC on MDA-MB 231 cells.</p>
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17 pages, 1939 KiB  
Review
Exosomes in Ovarian Cancer: Towards Precision Oncology
by Maria Grazia Perrone, Silvana Filieri, Amalia Azzariti, Domenico Armenise, Olga Maria Baldelli, Anselma Liturri, Anna Maria Sardanelli, Savina Ferorelli, Morena Miciaccia and Antonio Scilimati
Pharmaceuticals 2025, 18(3), 371; https://doi.org/10.3390/ph18030371 - 5 Mar 2025
Viewed by 84
Abstract
Background: Identification of targetable biomarkers to improve early disease detection and overall patient outcomes is becoming an urgent need in clinical oncology. Ovarian cancer (OC) has one of the highest mortality rates among gynecological cancers. It is asymptomatic and almost always diagnosed [...] Read more.
Background: Identification of targetable biomarkers to improve early disease detection and overall patient outcomes is becoming an urgent need in clinical oncology. Ovarian cancer (OC) has one of the highest mortality rates among gynecological cancers. It is asymptomatic and almost always diagnosed at an advanced stage (III or IV), leading to a 5-year survival rate of approximately 35%. Methods: Current therapeutic approaches for OC are very limited and mainly consist of cytoreductive surgery and cisplatin plus taxane-based chemotherapy. No gender and tumor specific biomarkers are known. Exosomes, lipid bilayer vesicles of endocytic origin secreted by most cell types, represent sources of information for their involvement in the onset and progression of many diseases. Hence, research on exosome contents as tools and targets in precise oncology therapy provides knowledge essential to improving diagnosis and prognosis of the disease. Results: This review attempts to give an overview of how exosomes are implicated in ovarian carcinoma pathogenesis to trigger further cancer exosome-based investigations aimed at developing ovarian cancer fine-tuning diagnostic methodologies. Conclusions: It is essential to investigate exosome-based cancer drugs to advance understanding, improve treatment plans, create personalized strategies, ensure safety, and speed up clinical translation to increase patients’ overall survival and quality of life. Papers published in PubMed and Web of Science databases in the last five years (2020–2024) were used as a bibliographic source. Full article
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Graphical abstract

Graphical abstract
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<p>Schematic representation of exosome biogenesis, secretion, and molecular content release. Exosomes protrude from the surface of the membrane and, degraded by lysosomes or secreted as multivesicular bodies, release their cargo in various body fluids, e.g., saliva, blood, breast milk (BM), tears, urine, cerebrospinal fluid (CSF), and ascites. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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<p>Strategies for leveraging exosomes in cancer therapy. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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<p>Exosomal microRNAs released by adipose-derived mesenchymal stem cells (MSCs), macrophages, and fibroblasts in ovarian cancer cells. miRNAs released by adipose MSCs induce apoptosis by decreasing BCL-2 and increasing BAX expression that induce Caspase-3 activation increasing apoptosis. miR-7, miR-29-a, and miR-223 reduce metastasis, induce T-cell balance, and induce drug resistance, respectively. TGFβ1 induces EMT via the SMAD pathway. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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<p>Two main strategies for OC-specific exosome drug delivery: passive and active. Passive loading relies on diffusion-based methods like co-incubation and other physical treatments to enhance exosome permeability, e.g., electroporation, sonication, freeze–thaw cycles, dialysis, extrusion, surfactant treatment, and in situ synthesis. Active loading leverages cellular mechanisms to incorporate proteins or nucleic acids during exosome biogenesis, often through genetic modification of parental cells. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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21 pages, 5495 KiB  
Article
Repurposing ProTAME for Bladder Cancer: A Combined Therapeutic Approach Targeting Cell Migration and MMP Regulation
by Ihsan Nalkiran and Hatice Sevim Nalkiran
Biology 2025, 14(3), 263; https://doi.org/10.3390/biology14030263 - 5 Mar 2025
Viewed by 155
Abstract
Bladder cancer, the fourth most common cancer type among men, remains a therapeutic challenge due to its heterogeneity and frequent development of chemoresistance. Cisplatin-based chemotherapy, often combined with gemcitabine, is the standard treatment, yet resistance and off-target effects in non-cancerous tissues limit its [...] Read more.
Bladder cancer, the fourth most common cancer type among men, remains a therapeutic challenge due to its heterogeneity and frequent development of chemoresistance. Cisplatin-based chemotherapy, often combined with gemcitabine, is the standard treatment, yet resistance and off-target effects in non-cancerous tissues limit its efficacy. This study evaluated the effects of cisplatin, gemcitabine, and the APC/C inhibitor proTAME, both individually and in combination, on cell migration and MMP2/MMP9 expression in RT4 bladder cancer and ARPE-19 normal epithelial cells. Molecular docking analyses were conducted to investigate the interactions of these compounds with MMP2 and MMP9. IC20 values for gemcitabine, cisplatin, and proTAME were applied in scratch-wound healing and quantitative real-time PCR (qRT-PCR) assays. Docking results predicted that proTAME may interact favorably with MMP2 (−9.2 kcal/mol) and MMP9 (−8.7 kcal/mol), showing high computational binding affinities and potential key hydrogen bonds; however, these interactions require further experimental validation. Scratch-wound healing and qRT-PCR assays demonstrated that proTAME-containing combinations were associated with reduced cell migration and decreased MMP2 and MMP9 expression in RT4 cells. Cisplatin combined with proTAME showed the most pronounced reduction in MMP expression and cell migration, with proTAME alone also exhibiting notable inhibitory effects. In ARPE-19 cells, gemcitabine and cisplatin upregulated MMP2 and MMP9 expression, suggesting a potential stress response, whereas proTAME mitigated this effect. These differential effects show the importance of tumor-specific responses in RT4 cells, where proTAME shows promise in enhancing the efficacy of chemotherapy by modulating MMP-related pathways involved in tumor migration and invasion. In conclusion, this study highlights the potential of proTAME as a repurposed agent in bladder cancer treatment due to its association with reduced cell migration and MMP downregulation. While these in vitro and in silico findings suggest a promising role for proTAME in combination therapies, further validation in advanced preclinical models is necessary to assess its therapeutic applicability and safety. Full article
(This article belongs to the Special Issue Cancer and Signalling: Targeting Cellular Pathways)
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<p>The structures of the therapeutic agents and ligands used in the molecular docking study are shown. (<b>a</b>) represents the 2D structure of proTAME. (<b>b</b>) illustrates gemcitabine, while (<b>c</b>) shows cisplatin. (<b>d</b>) presents the small-molecule ligand I52, and (<b>e</b>) depicts the 2D structure of the small-molecule ligand NFH. The chemical structures used in this figure were downloaded and modified from the PubChem database, <a href="https://pubchem.ncbi.nlm.nih.gov" target="_blank">https://pubchem.ncbi.nlm.nih.gov</a> (accessed on 9 October 2024).</p>
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<p>Molecular docking interactions of proTAME, gemcitabine, cisplatin, and I52 with MMP2. (<b>a</b>,<b>b</b>) ProTAME–MMP2: 3D visualization (<b>a</b>) demonstrates stable positioning of proTAME within the active site of MMP2, supported by interactions with key residues, as detailed in the 2D interaction map (<b>b</b>). (<b>c</b>,<b>d</b>) Gemcitabine–MMP2: 3D visualization (<b>c</b>) shows gemcitabine effectively bound to active site of MMP2, with the 2D interaction map (<b>d</b>) outlining residue-specific interactions. (<b>e</b>,<b>f</b>) Cisplatin–MMP2: 3D visualization (<b>e</b>) illustrates the positioning of cisplatin within the active site of MMP2, with the 2D interaction map (<b>f</b>) displaying key stabilizing interactions. (<b>g</b>,<b>h</b>) I52–MMP2: 3D visualization (<b>g</b>) highlights strong binding of I52 to the active site of MMP2, with the 2D interaction map (<b>h</b>) summarizing its stabilizing interactions. This figure highlights the varying binding affinities and interaction networks of these ligands within the active site of MMP2.</p>
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<p>Molecular docking interactions of proTAME, gemcitabine, cisplatin, and NFH with MMP9. (<b>a</b>,<b>b</b>) ProTAME–MMP9: 3D visualization (<b>a</b>) demonstrates the stable binding of proTAME within the active site of MMP9, supported by interactions with surrounding residues. The 2D interaction map (<b>b</b>) highlights key stabilizing interactions, including hydrogen bonds and other forces. (<b>c</b>,<b>d</b>) Gemcitabine–MMP9: 3D visualization (<b>c</b>) shows the effective positioning of gemcitabine within the active site of MMP9, with the 2D interaction map (<b>d</b>) displaying residue-specific interactions contributing to binding. (<b>e</b>,<b>f</b>) Cisplatin–MMP9: 3D visualization (<b>e</b>) illustrates binding of cisplatin to the active site of MMP9, stabilized by multiple interactions as shown in the 2D interaction map (<b>f</b>). (<b>g</b>,<b>h</b>) NFH–MMP9: 3D visualization (<b>g</b>) highlights the positioning of NFH and interactions within the active site of MMP9, with the 2D interaction map (<b>h</b>) summarizing key hydrogen bonds and stabilizing forces. This figure emphasizes the varying binding affinities and interaction networks of these ligands with MMP9.</p>
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<p>Inhibition of cell migration in ARPE-19 and RT4 cells by cisplatin, gemcitabine, and proTAME treatments in scratch-wound healing assay. (<b>a</b>,<b>d</b>) The images of scratch-wound healing assays performed on ARPE-19 (<b>a</b>) and RT4 (<b>d</b>) cells at 0, 24, and 48 h post-treatment. The cells were treated with DMSO control, cisplatin, gemcitabine, proTAME, or combinations of cisplatin+proTAME, gemcitabine+proTAME, gemcitabine+cisplatin, and gemcitabine+cisplatin+proTAME. Images represent one of three independent replicates (<span class="html-italic">n</span> = 3), with three technical replicates per condition. Images were captured using an inverted microscope at 4× magnification. (<b>b</b>,<b>e</b>) Quantification of the scratch-wound area (µm<sup>2</sup>) over time for ARPE-19 (<b>b</b>) and RT4 (<b>e</b>) cells, with measurements taken at 0, 24, and 48 h. The data show the reduction in scratch area across different treatment groups, indicating varying degrees of cell migration inhibition. (<b>c</b>,<b>f</b>) The percentage of the scratch-wound area remaining at 48 h relative to the initial wound size (0 h) for ARPE-19 (<b>c</b>) and RT4 (<b>f</b>) cells.</p>
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<p>Effects of cisplatin, gemcitabine, and proTAME on MMP2 and MMP9 gene expression in ARPE-19 and RT4 cells. (<b>a</b>) MMP2 gene expression fold change in ARPE-19 and RT4 cells following treatment with cisplatin, gemcitabine, proTAME, and their combinations. (<b>b</b>) MMP2 gene expression heat map visualization. (<b>c</b>) MMP9 gene expression fold change in ARPE-19 and RT4 cells under the same treatment conditions as (<b>a</b>). (<b>d</b>) MMP9 gene expression heat map visualization. Gene expression levels were normalized to GAPDH, and fold changes were calculated using the 2<sup>−ΔΔCt</sup> method. The data are presented as fold change relative to the ARPE-19 untreated control, with statistical comparisons conducted against the untreated control for cisplatin-, gemcitabine-, and cisplatin+gemcitabine-treated groups. Statistical significance is indicated as follows: ns: non-significant, *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001. Statistical analyses were performed for proTAME, cisplatin+proTAME, gemcitabine+proTAME, and gemcitabine+cisplatin+proTAME groups compared to DMSO control. The statistical significance is indicated as follows: ns (bold): non-significant, §: <span class="html-italic">p</span> &lt; 0.05, §§: <span class="html-italic">p</span> &lt; 0.01, §§§: <span class="html-italic">p</span> &lt; 0.001. The statistical significance of RT4 untreated control was compared to ARPE-19 untreated control. All experiments were performed with three independent biological replicates, each consisting of three technical replicates, and data are presented as mean ± standard deviation (SD) from three independent experiments.</p>
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42 pages, 2758 KiB  
Review
Unveiling Gestational Diabetes: An Overview of Pathophysiology and Management
by Rahul Mittal, Karan Prasad, Joana R. N. Lemos, Giuliana Arevalo and Khemraj Hirani
Int. J. Mol. Sci. 2025, 26(5), 2320; https://doi.org/10.3390/ijms26052320 - 5 Mar 2025
Viewed by 147
Abstract
Gestational diabetes mellitus (GDM) is characterized by an inadequate pancreatic β-cell response to pregnancy-induced insulin resistance, resulting in hyperglycemia. The pathophysiology involves reduced incretin hormone secretion and signaling, specifically decreased glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), impairing insulinotropic effects. Pro-inflammatory cytokines, [...] Read more.
Gestational diabetes mellitus (GDM) is characterized by an inadequate pancreatic β-cell response to pregnancy-induced insulin resistance, resulting in hyperglycemia. The pathophysiology involves reduced incretin hormone secretion and signaling, specifically decreased glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), impairing insulinotropic effects. Pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), impair insulin receptor substrate-1 (IRS-1) phosphorylation, disrupting insulin-mediated glucose uptake. β-cell dysfunction in GDM is associated with decreased pancreatic duodenal homeobox 1 (PDX1) expression, increased endoplasmic reticulum stress markers (CHOP, GRP78), and mitochondrial dysfunction leading to impaired ATP production and reduced glucose-stimulated insulin secretion. Excessive gestational weight gain exacerbates insulin resistance through hyperleptinemia, which downregulates insulin receptor expression via JAK/STAT signaling. Additionally, hypoadiponectinemia decreases AMP-activated protein kinase (AMPK) activation in skeletal muscle, impairing GLUT4 translocation. Placental hormones such as human placental lactogen (hPL) induce lipolysis, increasing circulating free fatty acids which activate protein kinase C, inhibiting insulin signaling. Placental 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) overactivity elevates cortisol levels, which activate glucocorticoid receptors to further reduce insulin sensitivity. GDM diagnostic thresholds (≥92 mg/dL fasting, ≥153 mg/dL post-load) are lower than type 2 diabetes to prevent fetal hyperinsulinemia and macrosomia. Management strategies focus on lifestyle modifications, including dietary carbohydrate restriction and exercise. Pharmacological interventions, such as insulin or metformin, aim to restore AMPK signaling and reduce hepatic glucose output. Emerging therapies, such as glucagon-like peptide-1 receptor (GLP-1R) agonists, show potential in improving glycemic control and reducing inflammation. A mechanistic understanding of GDM pathophysiology is essential for developing targeted therapeutic strategies to prevent both adverse pregnancy outcomes and the progression to overt diabetes in affected women. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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<p>Outcomes of gestational diabetes mellitus (GDM) on mothers and offspring: This figure illustrates short-term and long-term outcomes of GDM for both mothers and their offspring. For mothers, short-term outcomes include increased risk of cesarean delivery and hypertensive disorders of pregnancy, while long-term outcomes encompass a heightened risk of developing type 1 diabetes (T1D) or type 2 diabetes (T2D). For offspring, short-term outcomes highlight the risks of macrosomia, neonatal hypoglycemia, and respiratory distress syndrome. Long-term outcomes for offspring demonstrate an increased risk of T1D or T2D and metabolic syndrome into adulthood. Created in BioRender. <a href="https://BioRender.com/n76l932" target="_blank">https://BioRender.com/n76l932</a> (accessed on 2 December 2024).</p>
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<p>A schematic representation of insulin signaling: When insulin binds to its receptor (IR), it triggers activation of IRS-1. Adiponectin enhances activation of IRS-1 via the AMP-activated protein kinase (AMPK) pathway. Activated IRS-1 then stimulates phosphatidylinositol-3-kinase (PI3K), which converts phosphatidylinositol-4, 5-bisphosphate (PIP2) into phosphatidylinositol-3-, 4-, 5-phosphate (PIP3). PIP3 subsequently activates Akt2, leading to the translocation of GLUT4 transporters to the cell surface and facilitating glucose entry into the cell. On the other hand, pro-inflammatory cytokines activate protein kinase C (PKC) through the IκB kinase (IKK), which then inhibits IRS-1 leading to disruption in insulin signaling. Created in BioRender. <a href="https://BioRender.com/a92r994" target="_blank">https://BioRender.com/a92r994</a> (accessed on 2 December 2024).</p>
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<p>A comparison of β-cell function and insulin sensitivity in normal and GDM pregnancies: During normal pregnancy, β-cells undergo expansion through hyperplasia and hypertrophy to accommodate the increased metabolic requirements. Concurrently, there is an increase in blood glucose levels due to reduced insulin sensitivity. After pregnancy, β-cells, blood glucose, and insulin sensitivity generally revert to their original state. However, in GDM, β-cells are unable to adequately adapt to the demands of pregnancy, causing an increase in blood glucose levels due to decreased insulin sensitivity. GDM resolves postpartum as the primary drivers of insulin resistance—placental hormones such as human placental lactogen (hPL) and progesterone—are no longer present. However, residual β-cell dysfunction, persistent low-grade inflammation, and metabolic abnormalities remain in many women, increasing their long-term risk for type 2 diabetes (T2D). Created in BioRender. <a href="https://BioRender.com/o66i148" target="_blank">https://BioRender.com/o66i148</a> (accessed on 2 December 2024).</p>
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15 pages, 3827 KiB  
Article
Antagonizing the S1P-S1P3 Axis as a Promising Anti-Angiogenic Strategy
by Sofia Avnet, Emi Mizushima, Beatrice Severino, Maria Veronica Lipreri, Antonia Scognamiglio, Angela Corvino, Nicola Baldini and Margherita Cortini
Metabolites 2025, 15(3), 178; https://doi.org/10.3390/metabo15030178 - 5 Mar 2025
Viewed by 79
Abstract
Background: Angiogenesis, the process of new blood vessel formation, is critically regulated by a balance of pro- and anti-angiogenic factors. This process plays a central role in tumor progression and is modulated by tumor cells. Sphingosine-1-phosphate (S1P), a bioactive lipid signaling molecule acting [...] Read more.
Background: Angiogenesis, the process of new blood vessel formation, is critically regulated by a balance of pro- and anti-angiogenic factors. This process plays a central role in tumor progression and is modulated by tumor cells. Sphingosine-1-phosphate (S1P), a bioactive lipid signaling molecule acting via G-protein-coupled receptors (S1PR1–5), has emerged as a key mediator of vascular development and pathological angiogenesis in cancer. Consequently, targeting the S1P-S1PRs axis represents a promising strategy for antiangiogenic therapies. This study explores S1PR3 as a potential therapeutic target in osteosarcoma, the most common primary bone malignancy, which we have previously demonstrated to secrete S1P within the acidic tumor microenvironment. Methods: The effects of KRX-725-II and its derivatives, Tic-4-KRX-725-II and [D-Tic]4-KRX-725-II—pepducins acting as S1PR3 antagonists as allosteric modulators of GPCR activity—were tested on metastatic osteosarcoma cells (143B) for proliferation and migration inhibition. Anti-angiogenic activity was assessed using endothelial cells (HUVEC) through proliferation and tubulogenesis assays in 2D, alongside sprouting and migration analyses in a 3D passively perfused microfluidic chip. Results: S1PR3 inhibition did not alter osteosarcoma cell growth or migration. However, it impaired endothelial cell tubulogenesis up to 75% and sprouting up to 30% in respect to controls. Conventional 2D assays revealed reduced tubule nodes and length, while 3D microfluidic models demonstrated diminished sprouting area and maximum migration distance, indicating S1PR3’s role in driving endothelial cell differentiation. Conclusions: These findings highlight S1PR3 as a critical regulator of angiogenesis and posit its targeting as a novel anti-angiogenic strategy, particularly for aggressive, S1P-secreting tumors with pronounced metastatic potential and an acidic microenvironment. Full article
(This article belongs to the Special Issue Cell Death and Cancer Metabolism)
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<p>S1P receptor expression in HUVEC and 143B cells. Real-time PCR analysis of the indicated genes normalized to three housekeeping genes (GAPDH, GUSB, and YWAHZ) in 143B and HUVEC cells cultured as monolayers for 72 h. Data presented as mean ± S.E.M. Unpaired two-tailed Mann–Whitney U test (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 versus HUVEC; <span class="html-italic">n</span> = 3).</p>
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<p>Inhibition of S1P3 does not affect OS cell proliferation or migration. (<b>A</b>–<b>C</b>) 143B OS cells were cultured in monolayer, incubated with the indicated compounds for 24, 48, or 72 h at the indicated concentrations. Total number of cells was assessed by staining of cell nuclei by Hoechst data presented as mean ± S.E.M. (unpaired two-tailed Mann–Whitney U test; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 versus control, <span class="html-italic">n</span> = 6). (<b>D</b>) Viability of OS spheroids (expressed as 580 nm absorbance). 143B were cultured as spheroids, treated with the indicated compounds at a concentration of 100 μM. The Alamar Blue assay was performed 72 h after the treatment (<span class="html-italic">n</span> = 12). (<b>E</b>) Migration of 143B OS spheroids as indicated, representative images. Spheroids formed in ultra-low attachment plates, moved to flat-bottom plates to allow adhesion, treated as indicated and imaged for 24 h (scale bar: 500 μm). (<b>F</b>) Quantification of the representative images shown in E. To measure the migration area, the area of the spheroids was assessed at time point 0 (black circle) and after 24 h (red circle). The graph shows the difference between the two areas (μm<sup>2</sup>) (<span class="html-italic">n</span> = 6).</p>
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<p>Pepducins do not affect endothelial cell proliferation. (<b>A</b>) Schematic representation of cells seeded in monolayer and graphs showing the results of quantification. HUVEC endothelial cells were cultured and incubated with the inhibitors for 24, 48, or 72 h at different concentrations. The total number of cells was assessed by staining of cell nuclei by Hoechst (<span class="html-italic">n</span> = 6). (<b>B</b>) Schematic representation of cells seeded as 3D spheroids in ultra-low attachment plates and graph related to the viability assay of HUVEC spheroid cells (expressed as 580 nm absorbance). HUVEC were treated with the inhibitors at a concentration of 100 μM. The Alamar Blue assay was performed 72 h after the treatment. (<span class="html-italic">n</span> = 12, data presented as mean ± S.E.M).</p>
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<p>Tubulogenesis is impaired by S1PR<sub>3</sub> inhibition. Data presented as mean ± S.E.M. (<b>A</b>) Schematic representation of the tubulogenesis experiment. HUVEC were seeded on top of a layer of 75% Matrigel<sup>®</sup>, and tubulogenesis was followed for 24 h post-seeding. (<b>B</b>) Representative images of the experiment schematized in (<b>A</b>). HUVEC-GFP cells were treated as indicated, and tubules were imaged 12 h post-seeding. Images show an overlay of brightfield and GFP acquisitions (scale bar: 500 μm). (<b>C</b>) Quantification of the number of nodes and total tubule length of the experiment shown in panel B (unpaired two-tailed Mann–Whitney test; * <span class="html-italic">p</span> &lt; 0.05 versus control; ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 versus control, <span class="html-italic">n</span> = 6).</p>
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<p>S1PR<sub>3</sub> modulation decreases endothelial cell sprouting. (<b>A</b>) Schematic representation of vessel formation in a microfluidic platform. Three-lane Mimetas<sup>®</sup> microchambers are used for HUVEC vessel formation; cells are seeded in the top channel, Matrigel<sup>®</sup> is injected in the middle channel, and the lower channel is used for the addition of the angiogenic cocktail (S1P 250 nM and VEGF 37.5 ng/mL). HUVEC-GFP cells were allowed to form vessels for 24 h before the addition of the angiogenic cocktail or pepducins at a concentration of 100 μM (in the upper channel); 24 h after drug treatment, vessels were live imaged with GFP fluorescence. (<b>B</b>) Representative images showing 3D endothelial vessel formation from side and top view. HUVEC-GFP cells were fixed and stained with anti-VE cadherin (red) and Hoechst (nuclei, blue, scale bar: 100 μm). (<b>C</b>) HUVEC-GFP endothelial cells live sprouting from the upper channel to the Matrigel<sup>®</sup> matrix, top view, representative images. The endothelial vessel was acquired on a 180 μm Z-stack, with images every 3 μm. Images show the maximum intensity projection of the whole Z-stack (scale bar: 100 μm). (<b>D</b>,<b>E</b>) Quantification of the sprouting area and maximum migration distance of the images shown in (<b>C</b>). Sprouting was measured and quantified using maximum intensity projection images, excluding cells on top of the phase guide, whereas the maximum migration distance was measured using maximum intensity projection images (unpaired two-tailed Mann–Whitney test; * <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 versus control, <span class="html-italic">n</span> = 10).</p>
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23 pages, 4007 KiB  
Review
Exploring the Impact of Chemotherapy on the Emergence of Antibiotic Resistance in the Gut Microbiota of Colorectal Cancer Patients
by Mutebi John Kenneth, Chin-Chia Wu, Chuan-Yin Fang, Tsui-Kang Hsu, I-Ching Lin, Shih-Wei Huang, Yi-Chou Chiu and Bing-Mu Hsu
Antibiotics 2025, 14(3), 264; https://doi.org/10.3390/antibiotics14030264 - 5 Mar 2025
Viewed by 109
Abstract
With nearly half of colorectal cancer (CRC) patients diagnosed at advanced stages where surgery alone is insufficient, chemotherapy remains a cornerstone for this cancer treatment. To prevent infections and improve outcomes, antibiotics are often co-administered. However, chemotherapeutic interactions with the gut microbiota cause [...] Read more.
With nearly half of colorectal cancer (CRC) patients diagnosed at advanced stages where surgery alone is insufficient, chemotherapy remains a cornerstone for this cancer treatment. To prevent infections and improve outcomes, antibiotics are often co-administered. However, chemotherapeutic interactions with the gut microbiota cause significant non-selective toxicity, affecting not only tumor and normal epithelial cells but also the gut microbiota. This toxicity triggers the bacterial SOS response and loss of microbial diversity, leading to bacterial mutations and dysbiosis. Consequently, pathogenic overgrowth and systemic infections increase, necessitating broad-spectrum antibiotics intervention. This review underscores how prolonged antibiotic use during chemotherapy, combined with chemotherapy-induced bacterial mutations, creates selective pressures that drive de novo antimicrobial resistance (AMR), allowing resistant bacteria to dominate the gut. This compromises the treatment efficacy and elevates the mortality risk. Restoring gut microbial diversity may mitigate chemotherapy-induced toxicity and improve therapeutic outcomes, and emerging strategies, such as fecal microbiota transplantation (FMT), probiotics, and prebiotics, show considerable promise. Given the global threat posed by antibiotic resistance to cancer treatment, prioritizing antimicrobial stewardship is essential for optimizing antibiotic use and preventing resistance in CRC patients undergoing chemotherapy. Future research should aim to minimize chemotherapy’s impact on the gut microbiota and develop targeted interventions to restore microbial diversity affected during chemotherapy. Full article
(This article belongs to the Special Issue Pathogenic and Antibiotic-Resistant Bacteria in Gut Microbiota)
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<p>The impact of gut microbiota to the efficacy and toxicity of CRC chemotherapy.</p>
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26 pages, 3130 KiB  
Review
Advancements in Nanotechnology for Targeted and Controlled Drug Delivery in Hematologic Malignancies: Shaping the Future of Targeted Therapeutics
by Abdurraouf Mokhtar Mahmoud and Clara Deambrogi
Appl. Biosci. 2025, 4(1), 16; https://doi.org/10.3390/applbiosci4010016 - 5 Mar 2025
Viewed by 137
Abstract
Hematologic malignancies, including leukemia, lymphoma, and multiple myeloma, pose significant therapeutic challenges due to their heterogeneity and high relapse rates. Nanotechnology has emerged as a promising avenue for precision drug delivery in these malignancies, allowing for enhanced drug concentration at tumor sites and [...] Read more.
Hematologic malignancies, including leukemia, lymphoma, and multiple myeloma, pose significant therapeutic challenges due to their heterogeneity and high relapse rates. Nanotechnology has emerged as a promising avenue for precision drug delivery in these malignancies, allowing for enhanced drug concentration at tumor sites and reducing systemic toxicity. Recent developments in nanocarriers—such as liposomes, polymeric nanoparticles, and inorganic nanoparticles—have enabled targeted approaches, utilizing molecular markers specific to malignant cells to increase therapeutic efficacy while minimizing adverse effects. Evidence from preclinical and clinical studies underscores the potential of nanotechnology to improve patient outcomes by facilitating controlled release, improved bioavailability, and reduced toxicity. However, translating these advancements into clinical practice requires further research to validate their safety and efficacy. This review provides a comprehensive analysis of the latest innovations in nanotechnology for targeted drug delivery in hematologic malignancies, addressing current achievements and future directions for integrating these approaches into Clinical Hemato-Oncology. Full article
(This article belongs to the Special Issue Feature Papers in Applied Biosciences 2024)
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<p>Nanotherapeutic strategies in hematological malignancies, including categories such as chemonanotherapy and immunotherapy. (Created in BioRender. Mahmoud, A. (2025)).</p>
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<p>Schematic representation of liposome-based nanocarrier functionalization and drug delivery to cancer cells. (Created in BioRender. Mahmoud, A. (2025)).</p>
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<p>Nanotechnology platforms for targeted hemato-oncology treatment. (Created in BioRender. Mahmoud, A. (2025)).</p>
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<p>Nanoparticle-based drug delivery platforms and their drug-loading efficiencies. (Created in BioRender. Mahmoud, A. (2025)).</p>
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<p>Passive targeting of nanoparticles Via the enhanced permeability and retention (EPR) effect. (Created in BioRender. Mahmoud, A. (2025)).</p>
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<p>Active targeting strategies using nanoparticle-based platforms for hematologic malignancies. (Created in BioRender. Mahmoud, A. (2025)).</p>
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