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21 pages, 4995 KiB  
Article
Ontogeny of Fetal Cardiometabolic Pathways: The Potential Role of Cortisol and Thyroid Hormones in Driving the Transition from Preterm to Near-Term Heart Development in Sheep
by Reza Amanollahi, Stacey L. Holman, Melanie R. Bertossa, Ashley S. Meakin, Kent L. Thornburg, I. Caroline McMillen, Michael D. Wiese, Mitchell C. Lock and Janna L. Morrison
J. Cardiovasc. Dev. Dis. 2025, 12(2), 36; https://doi.org/10.3390/jcdd12020036 - 21 Jan 2025
Viewed by 375
Abstract
Understanding hormonal and molecular changes during the transition from preterm to near-term gestation is essential for investigating how pregnancy complications impact fetal heart development and contribute to long-term cardiovascular risks for offspring. This study examines these cardiac changes in fetal sheep, focusing on [...] Read more.
Understanding hormonal and molecular changes during the transition from preterm to near-term gestation is essential for investigating how pregnancy complications impact fetal heart development and contribute to long-term cardiovascular risks for offspring. This study examines these cardiac changes in fetal sheep, focusing on the changes between 116 days (preterm) and 140 days (near term) of gestation (dG, term = 150) using Western blotting, LC-MS/MS, and histological techniques. We observed a strong correlation between cortisol and T3 (Triiodothyronine) in heart tissue in near-term fetuses, highlighting the role of glucocorticoid signalling in fetal heart maturation. Protein expression patterns in the heart revealed a decrease in multiple glucocorticoid receptor isoforms (GRα-A, GR-P, GR-A, GRα-D2, and GRα-D3), alongside a decrease in IGF-1R (a marker of cardiac proliferative capacity) and p-FOXO1(Thr24) but an increase in PCNA (a marker of DNA replication), indicating a shift towards cardiomyocyte maturation from preterm to near term. The increased expression of proteins regulating mitochondrial biogenesis and OXPHOS complex 4 reflects the known transition from glycolysis to oxidative phosphorylation, essential for meeting the energy demands of the postnatal heart. We also found altered glucose transporter expression, with increased pIRS-1(ser789) and GLUT-4 but decreased GLUT-1 expression, suggesting improved insulin responsiveness as the heart approaches term. Notably, the reduced protein abundance of SIRT-1 and SERCA2, along with increased phosphorylation of cardiac Troponin I(Ser23/24), indicates adaptations for more energy-efficient contraction in the near-term heart. In conclusion, these findings show the complex interplay of hormonal, metabolic, and growth changes that regulate fetal heart development, providing new insights into heart development that are crucial for understanding pathological conditions at birth and throughout life. Full article
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Graphical abstract
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<p>Hormone concentrations of fetal cardiac tissue. The fetal cardiac concentration of cortisol (<b>A</b>) and cortisone (<b>B</b>) were not different between preterm and near-term fetuses. The cortisol: cortisone ratio (<b>C</b>) was higher, while 11-deoxycortisol (<b>D</b>) and corticosterone (<b>E</b>) were lower with no change in progesterone (<b>F</b>) in the near-term compared to preterm fetuses. T<sub>4</sub> (<b>G</b>) was lower with no change in T<sub>3</sub> (<b>H</b>) concentrations in the near-term compared to preterm fetuses. In the near-term fetuses only, there were positive linear relationships of T<sub>3</sub> with cortisol (<b>I</b>). Males (M) = circles, females (F) = triangles. preterm, left ventricle (LV) tissue from fetuses at 116 days of gestation (dG) (open symbols; hormone = 2M, 5F). Near-term, LV tissue from fetuses at 140 dG (closed symbols; hormone = 3M, 4F). One sample per animal was analysed via LC-MS/MS. Data were excluded due to a technical error in hormone concentration. Up to one outlier was excluded per group using the Grubbs method (Alpha = 0.05), when applicable. Data are expressed as mean ± SD and were analysed using either an unpaired <span class="html-italic">t</span>-test or simple linear regression. Data for progesterone, T<sub>3</sub>, and T<sub>4</sub> failed the normality test and were consequently analysed using the Mann–Whitney test. (*) indicates a statistically significant difference between the groups. <span class="html-italic">p</span> &lt; 0.05 was considered significant. AU: arbitrary unit.</p>
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<p>Abundance of glucocorticoid receptor isoforms in the fetal heart. The cardiac protein abundance of glucocorticoid receptors (GR) including GRα-A (<b>A</b>), GR-P (<b>B</b>), GR-A (<b>C</b>), GRα-D2 (<b>D</b>), and GRα-D3 (<b>E</b>) was lower in the near-term compared to preterm fetuses. In the near-term fetuses only, there was a positive linear relationship between cortisol and GRα-D2 (<b>F</b>). Males (M) = circles, females (F) = triangles. Preterm, left ventricle (LV) tissue from fetuses at 116 days of gestation (dG) (open symbols; protein = 3M, 5F; hormone = 2M, 5F). Near-term, LV tissue from fetuses at 140 dG (closed symbols; protein = 3M, 4F; hormone = 3M, 4F). One sample per animal was run per Western blot and LC-MS/MS. Data were excluded due to a technical error in hormone concentration. Up to one outlier was excluded per group using the Grubbs method (Alpha = 0.05) when applicable. Data were expressed as mean ± SD and were analysed using either an unpaired <span class="html-italic">t</span>-test or simple linear regression. (*) indicates a statistically significant difference between the groups. <span class="html-italic">p</span> &lt; 0.05 was considered significant. AU: arbitrary unit. (X) indicates data excluded from analysis (due to a defect on the band/s).</p>
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<p>Molecular markers of fetal cardiac growth. The cardiac protein expression of IGF-1R (<b>A</b>) and p-FOXO1:FOXO1 ratio (<b>B</b>) was lower, while PCNA (<b>C</b>) was higher in the near term compared to preterm fetuses. There was no difference in the p-mTOR:mTOR ratio (<b>D</b>), p-Akt:Akt ratio (<b>E</b>), and p-P70 S6K:P70 S6K ratio (<b>F</b>) between the groups. Males (M) = circles, females (F) = triangles. Preterm, left ventricle (LV) tissue from fetuses at 116 days of gestation (dG) (open symbols; protein = 3M, 5F). Near-term, LV tissue from fetuses at 140 dG (closed symbols; protein = 3M, 4F). One sample per animal was run per Western blot. Up to one outlier was excluded per group using the Grubbs method (Alpha = 0.05), when applicable. Data are expressed as mean ± SD and were analysed either using an unpaired <span class="html-italic">t</span>-test or simple linear regression. (*) indicates a statistically significant difference between the groups. <span class="html-italic">p</span> &lt; 0.05 was considered significant. AU: arbitrary unit. (X) indicates data excluded from analysis (due to a defect on the band/s).</p>
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<p>Molecular markers of fetal cardiac OXPHOS and mitochondrial content. The cardiac protein abundance of complex 4 (<b>D</b>) was higher in the near-term compared to preterm fetuses, while there was no difference in complex 1 (<b>A</b>), 2 (<b>B</b>), 3 (<b>C</b>), and 5 (<b>E</b>). The MT-COXI: SDHA ratio (<b>F</b>), a marker of mitochondrial content) was higher in the near-term compared to preterm fetuses. CS activity (<b>G</b>) did not differ between the groups, while CS activity: mitochondrial content ratio (<b>H</b>) was lower in the near-term compared to preterm fetuses. Males (M) = circles, females (F) = triangles. Preterm, left ventricle (LV) tissue from fetuses at 116 days of gestation (dG) (open symbols; protein/CS activity = 3M, 5F). Near-term, LV tissue from fetuses at 140 dG (closed symbols; protein/CS activity = 3M, 4F). One sample per animal was run per Western blot and CS activity. Up to one outlier was excluded per group using the Grubbs method (Alpha = 0.05), when applicable. Data are expressed as mean ± SD and were analysed using either an unpaired <span class="html-italic">t</span>-test or simple linear regression. (*) indicates a statistically significant difference between the groups. <span class="html-italic">p</span> &lt; 0.05 was considered significant. AU: arbitrary unit. (X) indicates data excluded from analysis (due to a defect on the band/s).</p>
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<p>Molecular markers of fetal cardiac glucose metabolism. The ratio of p-IRS-1:IRS-1 ratio (<b>A</b>) and GLUT-4 (<b>C</b>) were higher, while the ratio of p-AS160:AS160 (<b>B</b>) was not different, and GLUT-1 (<b>D</b>) was lower in the near-term compared to preterm fetuses. The abundance of PDK-4 protein (<b>E</b>), and activity of LDH (<b>F</b>) were not different in preterm and near-term fetuses. In the preterm fetuses only, there were positive linear relationships between GRα-D2 and GLUT-1 (<b>G</b>), as well as GRα-D3 and GLUT-1 (<b>H</b>). Males (M) = circles, females (F) = triangles. Preterm, left ventricle (LV) tissue from fetuses at 116 days of gestation (dG) (open symbols; protein/LDH activity = 3M, 5F). Near-term, LV tissue from fetuses at 140 dG (closed symbols; protein/LDH activity = 3M, 4F). One sample per animal was run per Western blot and LDH activity. Up to one outlier was excluded per group using the Grubbs method (Alpha = 0.05), when applicable. Data are expressed as mean ± SD and were analysed using either an unpaired <span class="html-italic">t</span>-test or simple linear regression. Data for p-AS160:AS160 ratio failed the normality test and were consequently analysed using the Mann–Whitney test. (*) indicates a statistically significant difference between the groups. <span class="html-italic">p</span> &lt; 0.05 was considered significant. AU: arbitrary unit. (X) indicates data excluded from analysis (due to a defect on the band/s).</p>
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<p>Molecular markers of fetal cardiac contractility. The expression of SIRT-1 (<b>A</b>) and SERCA2 (<b>B</b>) in cardiac tissue was lower, while there was no difference in the ratio of p-PLN:PLN (<b>C</b>) in the near-term compared to preterm fetuses. The ratio of p-TroponinI:TroponinI (<b>D</b>) was higher, while NOX-2 (<b>E</b>) was lower in near-term compared to preterm fetuses. Males (M) = circles, females (F) = triangles. Preterm, left ventricle (LV) tissue from fetuses at 116 days of gestation (dG) (open symbols; protein = 3M, 5F). Near-term, LV tissue from fetuses at 140 dG (closed symbols; protein = 3M, 4F). One sample per animal was run per Western blot. Up to one outlier was excluded per group using the Grubbs method (Alpha = 0.05), when applicable. Data are expressed as mean ± SD and were analysed using either an unpaired <span class="html-italic">t</span>-test or simple linear regression. (*) indicates a statistically significant difference between the groups. <span class="html-italic">p</span> &lt; 0.05 was considered significant. AU: arbitrary unit.</p>
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<p>Fetal cardiac glycogen, collagen, and Ki67 staining: 20× magnification representative micrograph of glycogen staining using PAS (black arrow indicates glycogen stained in magenta) in preterm (<b>A</b>) and near term (<b>B</b>). 20× magnification representative micrograph of collagen staining using Masson’s trichrome (black arrow indicates collagen stained in blue) in preterm (<b>D</b>) and near term (<b>E</b>). 40× magnification representative micrograph of Ki67 staining using IHC (black arrow) in preterm (<b>G</b>) and near term (<b>H</b>). The fetal cardiac glycogen (<b>C</b>), collagen (<b>F</b>), and Ki67 (<b>I</b>) staining were not different between preterm and near-term fetuses. Males (M) = circles, females (F) = triangles. Preterm, left ventricle (LV) tissue from fetuses at 116 days of gestation (dG) (open symbols; histology/IHC = 3M, 2F). Near-term, LV tissue from fetuses at 140 dG (closed symbols; histology/IHC = 2M, 3F). One sample per animal was run per histology and IHC. A smaller subset of animals was included in this analysis due to missing fixed tissue samples. Scale bars = 100 μm. Data are expressed as mean ± SD and were analysed using an unpaired <span class="html-italic">t</span>-test. <span class="html-italic">p</span> &lt; 0.05 was considered significant.</p>
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15 pages, 1576 KiB  
Case Report
Kenny–Caffey Syndrome Type 2 (KCS2): A New Case Report and Patient Follow-Up Optimization
by Kyriaki Hatziagapiou, Amalia Sertedaki, Vasiliki Dermentzoglou, Nataša Čurović Popović, George I. Lambrou, Louis Papageorgiou, Trias Thireou, Christina Kanaka-Gantenbein and Sophia D. Sakka
J. Clin. Med. 2025, 14(1), 118; https://doi.org/10.3390/jcm14010118 - 28 Dec 2024
Viewed by 544
Abstract
Background/Objectives: Kenny–Caffey syndrome 2 (KCS2) is a rare cause of hypoparathyroidism, inherited in an autosomal dominant mode, resulting from pathogenic variants of the FAM111A gene, which is implicated in intracellular pathways regulating parathormone (PTH) synthesis and skeletal and parathyroid gland development. Methods: [...] Read more.
Background/Objectives: Kenny–Caffey syndrome 2 (KCS2) is a rare cause of hypoparathyroidism, inherited in an autosomal dominant mode, resulting from pathogenic variants of the FAM111A gene, which is implicated in intracellular pathways regulating parathormone (PTH) synthesis and skeletal and parathyroid gland development. Methods: The case of a boy is reported, presenting with the characteristic and newly identified clinical, biochemical, radiological, and genetic abnormalities of KCS2. Results: The proband had noticeable dysmorphic features, and the closure of the anterior fontanel was delayed until the age of 4 years. Biochemical evaluation at several ages revealed persistent hypocalcemia, high normal phosphorous, and inappropriately low normal PTH. To exclude other causes of short stature, the diagnostic approach revealed low levels of IGF-1, and on CNS MRI, small pituitary gland and empty sella. Nocturnal levels of growth hormone were normal. MRI also revealed bilateral symmetrical microphthalmia and torturous optic nerves. Skeletal survey was compatible with cortical thickening and medullary stenosis of the long bones. Genomic data analysis revealed a well-known pathogenic variant of the FAM111A gene (c.1706G>A, p. R569H), which is linked with KCS2 or nanophthalmos. Conclusions: KCS2, although a rare disease, should be included in the differential diagnosis of hypoparathyroidism and short stature. Understanding the association of pathogenic variants with KCS2 phenotypic variability will allow the advancement of clinical genetics and personalized long-term follow-up and will offer insights into the role of the FAM111A gene in the disease pathogenesis and normal embryogenesis of implicated tissues and organs. Full article
(This article belongs to the Special Issue Endocrine Disorders in Children)
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<p>Anthropometric measurements: height (cm), weight (kg), head circumference (cm), and BMI (kg/m<sup>2</sup>) of the proband (WHO Child Growth Standards) [<a href="#B23-jcm-14-00118" class="html-bibr">23</a>].</p>
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<p>(<b>A</b>) T1-w midsagittal image shows hypoplasia of the anterior pituitary with a concave surface and almost empty sella appearance (arrow). The stalk is normal, and the posterior pituitary is orthotopic. (<b>B</b>) T2-w sagittal image demonstrates tortuosity of the optic nerve (arrow) and dilatation of the subarachnoid space surrounding its anterior portion (arrowhead). (<b>C</b>) T1-w axial image depicts bilateral symmetrical microphthalmia. X-rays of the (<b>D</b>) femur, (<b>E</b>) tibia, and (<b>F</b>) humerus show increased cortical thickness of the diaphysis, with mild narrowing of the medullary cavities. Relative flaring of the proximal tibial metaphysis.</p>
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<p>The <span class="html-italic">FAM111A</span> gene variants associated with KCS2 and other related diseases. Pathogenic variants that have been directly associated with KCS2 (red) and likely pathogenic variants (yellow).</p>
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23 pages, 3021 KiB  
Article
Increased Levels of hsa-miR-199a-3p and hsa-miR-382-5p in Maternal and Neonatal Blood Plasma in the Case of Placenta Accreta Spectrum
by Angelika V. Timofeeva, Ivan S. Fedorov, Anastasia D. Nikonets, Alla M. Tarasova, Ekaterina N. Balashova, Dmitry N. Degtyarev and Gennady T. Sukhikh
Int. J. Mol. Sci. 2024, 25(24), 13309; https://doi.org/10.3390/ijms252413309 - 11 Dec 2024
Viewed by 680
Abstract
Despite the increasing number of placenta accreta spectrum (PAS) cases in recent years, its impact on neonatal outcomes and respiratory morbidity, as well as the underlying pathogenetic mechanism, has not yet been extensively studied. Moreover, no study has yet demonstrated the effectiveness of [...] Read more.
Despite the increasing number of placenta accreta spectrum (PAS) cases in recent years, its impact on neonatal outcomes and respiratory morbidity, as well as the underlying pathogenetic mechanism, has not yet been extensively studied. Moreover, no study has yet demonstrated the effectiveness of antenatal corticosteroid therapy (CT) for the prevention of respiratory distress syndrome (RDS) in newborns of mothers with PAS at the molecular level. In this regard, microRNA (miRNA) profiling by small RNA deep sequencing and quantitative real-time PCR was performed on 160 blood plasma samples from preterm infants (gestational age: 33–36 weeks) and their mothers who had been diagnosed with or without PAS depending on the timing of the antenatal RDS prophylaxis. A significant increase in hsa-miR-199a-3p and hsa-miR-382-5p levels was observed in the blood plasma of the newborns from mothers with PAS compared to the control group. A clear trend toward the normalization of hsa-miR-199a-3p and hsa-miR-382-5p levels in the neonatal blood plasma of the PAS groups was observed when CT was administered within 14 days before delivery, but not beyond 14 days. Direct correlations were found among the hsa-miR-382-5p level in neonatal blood plasma and the hsa-miR-199a-3p level in the same sample (r = 0.49; p < 0.001), the oxygen requirements in the NICU (r = 0.41; p = 0.001), the duration of the NICU stay (r = 0.31; p = 0.019), and the severity of the newborn’s condition based on the NEOMOD scale (r = 0.36; p = 0.005). Logistic regression models based on the maternal plasma levels of hsa-miR-199a-3p and hsa-miR-382-5p predicted the need for cardiotonic therapy, invasive mechanical ventilation, or high-frequency oscillatory ventilation in newborns during the early neonatal period, with a sensitivity of 95–100%. According to the literary data, these miRNAs regulate fetal organogenesis via IGF-1, the formation of proper lung tissue architecture, surfactant synthesis in alveolar cells, and vascular tone. Full article
(This article belongs to the Special Issue The Role of miRNA in Human Diseases)
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<p>PLS-A analysis of deep sequencing data of miRNA in the peripheral blood plasma of day-old newborns from mothers with PAS and without PAS (control).</p>
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<p>The dependence of hsa-miR-382-5p and hsa-miR-199a-3p content in the blood plasma of newborns and their mothers on the severity of placenta accreta spectrum (PAS) and the timing of antenatal corticosteroid therapy (CT). Levels of miR-382-5p (−∆Ct, PCR data) in the blood plasma of newborns from mothers with placenta accreta or placenta increta or placenta percreta without CT or with CT 2–14 days before delivery in comparison with control group—without PAS and without CT (<b>A</b>). Levels of miR-382-5p (−∆Ct, PCR data) in the blood plasma of pregnant women with placenta accreta or placenta increta or placenta percreta without CT or with CT 2–14 days before delivery in comparison with control group—without PAS and without CT (<b>B</b>). Levels of miR-199a-3p (−∆Ct, PCR data) in the blood plasma of newborns from mothers with placenta accreta or placenta increta or placenta percreta without CT or with CT 2–14 days before delivery in comparison with control group—without PAS and without CT (<b>C</b>). Levels of miR-199a-3p (−∆Ct, PCR data) in the blood plasma of pregnant women with placenta accreta or placenta increta or placenta percreta without CT or with CT 2–14 days before delivery in comparison with control group—without PAS and without CT (<b>D</b>). “Wo” means “without”.</p>
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<p>Dynamics of changes in hsa-miR-199a-3p levels in the blood plasma of newborns relative to their mothers’ blood plasma, with and without PAS, depending on the antenatal corticosteroid therapy (CT). “Wo” means “without”.</p>
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<p>Levels of hsa-miR-199a-3p and hsa-miR-382-5p in the blood plasma of newborns with PAS, categorized by their severity score according to the Neomod scale.</p>
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<p>Levels of miR-181a-5p, miR-199a-3p and miR-382-5p in blood plasma of pregnant women with/without PAS and with/without antenatal corticosteroid therapy. “Wo” means “without”.</p>
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<p>Logistic regression models for predicting neonatal complications by plasma miR-199a-3p and/or miR-382-5p levels in pregnant women with PAS using miR-181a-5p as a reference endogenous RNA. (<b>A</b>) Respiratory complications probability models. (<b>B</b>) Cardiovascular complications probability models. Se—sensitivity, Sp—specificity.</p>
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<p>Enrichment analysis of gene targets of hsa-miR-382-5p and hsa-miR-199a-3p using FunRich software tool.</p>
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19 pages, 3494 KiB  
Article
Leveraging Tumor Mutation Profiles to Forecast Immune Checkpoint Blockade Resistance in Melanoma, Lung, Head and Neck, Bladder and Renal Cancers
by Guillaume Mestrallet
Onco 2024, 4(4), 439-457; https://doi.org/10.3390/onco4040031 - 10 Dec 2024
Viewed by 731
Abstract
Immune checkpoint blockade (ICB), radiotherapy, chemotherapy and surgery are currently used as therapeutic strategies against melanoma, lung, bladder and renal cancers, but their efficacy is limited. Thus, I need to predict treatment response and resistance to address this challenge. In this study, I [...] Read more.
Immune checkpoint blockade (ICB), radiotherapy, chemotherapy and surgery are currently used as therapeutic strategies against melanoma, lung, bladder and renal cancers, but their efficacy is limited. Thus, I need to predict treatment response and resistance to address this challenge. In this study, I analyzed 350 lung cancer, 320 melanoma, 215 bladder cancer, 139 head and neck cancer and 151 renal carcinoma patients treated with ICB to identify tumor mutations associated with response and resistance to treatment. I identified several tumor mutations linked with a difference in survival outcomes following ICB. In lung cancer, missense mutations in ABL1, ASXL1, EPHA3, EPHA5, ERBB4, MET, MRE11A, MSH2, NOTCH1, PAK7, PAX5, PGR, ZFHX3, PIK3C3 and REL genes were indicative of favorable responses to ICB. Conversely, mutations in TGFBR2, ARID5B, CDKN2C, HIST1H3I, RICTOR, SMAD2, SMAD4 and TP53 genes were associated with shorter overall survival post-ICB treatment. In melanoma, mutations in FBXW7, CDK12, CREBBP, CTNNB1, NOTCH1 and RB1 genes predict resistance to ICB, whereas missense mutations in FAM46C and RHOA genes are associated with extended overall survival. In bladder cancer, mutations in HRAS genes predict resistance to ICB, whereas missense mutations in ERBB2, GNAS, ATM, CDKN2A and LATS1 genes, as well as nonsense mutations in NCOR1 and TP53 genes, are associated with extended overall survival. In head and neck cancer, mutations in genes like PIK3CA and KRAS correlated with longer survival, while mutations in genes like TERT and TP53 were linked to shorter survival. In renal carcinoma, mutations such as EPHA5, MGA, PIK3R1, PMS1, TSC1 and VHL were linked to prolonged overall survival, while others, including total splice mutations and mutations in B2M, BCOR, JUN, FH, IGF1R and MYCN genes were associated with shorter overall survival following ICB. Then, I developed predictive survival models by machine learning that correctly forecasted cancer patient survival following ICB within an error between 5 and 8 months based on their distinct tumor mutational attributes. In conclusion, this study advocates for personalized immunotherapy approaches in cancer patients. Full article
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<p>Mutations associated with a difference in overall survival for patients with lung cancer following immunotherapy. N = 350 lung cancer patients. I investigated patient response or resistance to immune checkpoint blockade (ICB) based on mutation profiles. Only mutations included in the MSK IMPACT panel that showed statistically significant differences in survival were shown. I employed Cox regression and hazard ratios, with significance set at <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Mutations associated with a difference in overall survival for patients with melanoma following immunotherapy. N = 320 melanoma patients. I investigated patient response or resistance to immune checkpoint blockade (ICB) based on mutation profiles. Only mutations included in the MSK IMPACT panel that showed statistically significant differences in survival were shown. I employed Cox regression and hazard ratios, with significance set at <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Mutations associated with a difference in overall survival for patients with bladder cancer following immunotherapy. N = 215 bladder cancer patients. I investigated patient response or resistance to immune checkpoint blockade (ICB) based on mutation profiles. Only mutations included in the MSK IMPACT panel that showed statistically significant differences in survival were shown. I employed Cox regression and hazard ratios, with significance set at <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Mutations associated with a difference in overall survival for patients with renal carcinoma following immunotherapy. N = 151 renal carcinoma patients. I investigated patient response or resistance to immune checkpoint blockade (ICB) based on mutation profiles. Only mutations included in the MSK IMPACT panel that showed statistically significant differences in survival were shown. I employed Cox regression and hazard ratios, with significance set at <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Mutations associated with a difference in overall survival for patients with head and neck cancer following immunotherapy. N = 139 head and neck cancer patients. I investigated patient response or resistance to immune checkpoint blockade (ICB) based on mutation profiles. Only mutations included in the MSK IMPACT panel that showed statistically significant differences in survival were shown. I employed Cox regression and hazard ratios, with significance set at <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Profiling of cancer patient mutations enables the prediction of their overall survival following ICB. (<b>A</b>) N = 350 lung cancer patients. (<b>B</b>) N = 320 melanoma patients. (<b>C</b>) N = 215 bladder cancer patients. (<b>D</b>) N = 151 renal carcinoma patients. (<b>E</b>) N = 139 head and neck cancer patients. Machine learning models were employed to predict patient overall survival in months after immune checkpoint blockade using previously identified mutational features. The dataset was partitioned into five different subsets and further split into training (80% of the patients) and testing (20% of the patients) subsets. Various algorithms, including Gradient Boosting, Random Forest, Decision Tree, Logistic Regression, Support Vector Classifier (SVC) and Multi-layer Perceptron (MLP), were trained on the mutational features using five-fold cross-validation. Additionally, a Mean Ensemble model combining the best-performing Random Forest and Gradient Boosting models was utilized to improve the accuracy of survival predictions. Hyperparameters of the models were optimized and their performance was evaluated using standard metrics on the test sets.</p>
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<p>Shapley values for each model predicting overall survival following ICB. (<b>A</b>) N = 350 lung cancer patients. (<b>B</b>) N = 320 melanoma patients. (<b>C</b>) N = 215 bladder cancer patients. (<b>D</b>) N = 151 renal carcinoma patients. (<b>E</b>) N = 139 head and neck cancer patients.</p>
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19 pages, 8400 KiB  
Article
Investigating the Potential Effects of 6PPDQ on Prostate Cancer Through Network Toxicology and Molecular Docking
by Yuanzhi Song, Wuhong Weng and Shengde Wu
Toxics 2024, 12(12), 891; https://doi.org/10.3390/toxics12120891 - 8 Dec 2024
Viewed by 1175
Abstract
(1) Background: N-(1,3-Dimethylbutyl)-N′-phenyl-p-phenylenediamine-quinone (6PPDQ), as a newly discovered environmental toxin, has been found more frequently in our living conditions. The literature reports that damage to the reproductive and cardiovascular system is associated with exposure to 6PPDQ. However, the relationship between 6PPDQ and cancer [...] Read more.
(1) Background: N-(1,3-Dimethylbutyl)-N′-phenyl-p-phenylenediamine-quinone (6PPDQ), as a newly discovered environmental toxin, has been found more frequently in our living conditions. The literature reports that damage to the reproductive and cardiovascular system is associated with exposure to 6PPDQ. However, the relationship between 6PPDQ and cancer still requires more investigation. This research aims to investigate the association between 6PPDQ and prostate cancer. (2) Methods and Results: Based on the data retrieved from the Pharmmapper, CTD, SEA, SwissTargetPrediction, GeneCard, and OMIM databases, we summarized 239 potential targets utilizing the Venn tool. Through the STRING network database and Cytoscape software, we constructed a PPI network and confirmed ten core targets, including IGF1R, PIK3R1, PTPN11, EGFR, SRC, GRB2, JAK2, SOS1, KDR, and IRS1. We identified the potential pathways through which 6PPDQ acts on these core targets using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Ultimately, through molecular docking methods, 6PPDQ binds closely with these ten core targets. These findings indicate that 6PPDQ may influence the proteins related to prostate cancer and may be linked to prostate cancer via several known signaling pathways. (3) Conclusions: This article employs innovative network toxicology to elucidate the prostate carcinogenic effects of 6PPDQ through its modulation of specific vital genes and signaling pathways, thereby establishing a foundational platform for future investigations into the impact of 6PPDQ on prostate cancer and potentially other tumors. Full article
(This article belongs to the Section Reproductive and Developmental Toxicity)
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<p>The flow chart of this research.</p>
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<p>Venn diagram of the overlapping targets of 6PPDQ and prostate cancer. The number of 239 represents the overlapping targets.</p>
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<p>PPI network of common targets generated by STRING.</p>
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<p>The network of potential targets Each node represents a gene, while the edges indicate their interactions. The size of the node is directly related to its degree, and the intensity of the color reflects the betweenness centrality of the nodes.</p>
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<p>The PPI network of the core targets. Each node represents a gene, while the edges indicate their interactions.</p>
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<p>The top 10 GO terms (<b>a</b>) and enriched pathways (<b>b</b>) of core genes ranked by <span class="html-italic">p</span>-value.</p>
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<p>The top 10 GO terms (<b>a</b>) and enriched pathways (<b>b</b>) of core genes ranked by <span class="html-italic">p</span>-value.</p>
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<p>(<b>a</b>,<b>b</b>) Molecular docking structures with each core target in the lowest Vina score.</p>
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<p>(<b>a</b>,<b>b</b>) Molecular docking structures with each core target in the lowest Vina score.</p>
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18 pages, 2149 KiB  
Article
Lactic Acid and Glutamine Have Positive Synergistic Effects on Growth Performance, Intestinal Function, and Microflora of Weaning Piglets
by Junjie Jiang, Daiwen Chen, Bing Yu, Jun He, Jie Yu, Xiangbing Mao, Zhiqing Huang, Yuheng Luo, Junqiu Luo and Ping Zheng
Animals 2024, 14(23), 3532; https://doi.org/10.3390/ani14233532 - 6 Dec 2024
Viewed by 748
Abstract
The objective of this study was to evaluate the effects of dietary addition of lactic acid and glutamine, and their interactions, on growth performance, nutrient digestibility, digestive enzyme activity, intestinal barrier functions, microflora, and expressions of intestinal development-related genes of weaning piglets. Ninety-six [...] Read more.
The objective of this study was to evaluate the effects of dietary addition of lactic acid and glutamine, and their interactions, on growth performance, nutrient digestibility, digestive enzyme activity, intestinal barrier functions, microflora, and expressions of intestinal development-related genes of weaning piglets. Ninety-six 24-day-old weaning piglets (Duroc × Landrace × Yorkshire, weaned at 21 ± 1 d and fed the basal diet for a 3 d adaptation period) with initial body weight of 7.24 ± 0.09 kg were randomly assigned to one of four dietary treatments with six replicates per treatment and four pigs per replicate in a 2 × 2 factorial treatment arrangements: (1) CON (a 2-period basal diet; control), (2) LS (supplemented with 2% lactic acid), (3) GS (supplemented with 1% glutamine), and (4) LGS (supplemented with 2% lactic acid and 1% glutamine). The study lasted for 28 d. On days 25–28, fresh fecal samples were collected to evaluate apparent total tract digestibility (ATTD) of nutrients. After 28 d, one weaning pig per pen was euthanized, and physiological samples obtained. Results showed that the supplementation of lactic acid improved the ADFI of the pigs (p < 0.05), while the pigs fed the glutamine diet had a greater ADFI and higher G/F (p < 0.05), and there were significant interactive effects between lactic acid and glutamine on the ADFI and G/F of the pigs (p < 0.05). The ATTD of CP and ash for pigs fed with lactic acid was significantly enhanced, and pigs fed the glutamine diet had greater ATTD of CP and ash (p < 0.05), while there were significant interactive effects between lactic acid and glutamine on the ATTD of CP and ash of the pigs (p < 0.05). Pigs fed with lactic acid exhibited greater activity of α-amylase and lipase (p < 0.05); moreover, the activity of lipase in the pigs showed a significant interactive effect between lactic acid and glutamine (p < 0.05). There was a greater villus height and villus height to crypt depth ratio in pigs fed with lactic acid (p < 0.05), and the villus height to crypt depth ratio of pigs fed with glutamine was greater (p < 0.05). There were greater GLUT2, IGF-1, TGF-β2, OCLN, and ZO-1 mRNA levels in pigs fed with lactic acid (p < 0.05), and the supplementation of glutamine increased SGLT1, GLUT2, PepT1, IGF-1, IGF-1R, TGFβ-2, GLP-2, and OCLN mRNA levels (p < 0.05), Additionally, expressions of SGLT1, GLUT2, PepT1, IGF-1, IGF-1R, TGFβ-2, GLP-2, CLDN-2, OCLN, and ZO-1 mRNA levels of pigs showed a positive interactive effect between lactic acid and glutamine (p < 0.05). Supplementation of lactic acid significantly increased the populations of Bifidobacterium in cecal digesta, Lactobacillus in colonic digesta, and the content of butyric acid in colonic digesta (p < 0.05). In addition, there were significant interactive effects between lactic acid and glutamine on populations of Bifidobacterium in cecal digesta, Lactobacillus in colonic digesta, and the content of acetic acid, butyric acid, and total VFAs in cecal digesta of the pigs (p < 0.05). Collectively, the current results indicate that dietary supplementation with lactic acid and glutamine had a positive synergistic effect on weaning pigs, which could improve growth performance through promoting the development of the small intestine, increasing digestive and barrier function, and regulating the balance of microflora in pigs, and which might be a potential feeding additive ensemble to enhance the health and growth of weaning piglets in the post-antibiotic era. Full article
(This article belongs to the Special Issue Feed Ingredients and Additives for Swine and Poultry)
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<p>Comparison of jejunal microscopic photographs with histological staining of weaning piglets. 1. CON, the basal diet; 2. LS, supplemented with 2% lactic acid; 3. GS, supplemented with 1% glutamine; 4. LGS, supplemented with 2% lactic acid and 1% glutamine.</p>
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<p>Effects of lactic acid, glutamine, and their interactions on the mRNA levels of jejunal nutrient transporter-related genes in weaning piglets. Each column represents the mean expression level of six independent replications. Letters above the bars (a, b) indicate statistical significance (<span class="html-italic">p</span> &lt; 0.05) of gene expression among the four treatments. CON, the basal diet; LS, supplemented with 2% lactic acid; GS, supplemented with 1% glutamine; LGS, supplemented with 2% lactic acid and 1% glutamine; <span class="html-italic">SGLT1</span>, sodium–glucose cotransporter 1; <span class="html-italic">GLUT2</span>, glucose transporter 2; <span class="html-italic">PePT1</span>, peptide transporter 1.</p>
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<p>Effects of lactic acid, glutamine, and their interactions on the mRNA levels of jejunal development-related genes in weaning piglets. Each column represents the mean expression level of six independent replications. Letters above the bars (a, b) indicate statistical significance (<span class="html-italic">p</span> &lt; 0.05) of gene expression among the four treatments. CON, a basal diet; LS, supplemented with 2% lactic acid; GS, supplemented with 1% glutamine; LGS, supplemented with 2% lactic acid and 1% glutamine; <span class="html-italic">IGF-1</span>, Insulin- like growth factor 1; <span class="html-italic">IGF-1R</span>, Insulin- like growth factor 1 receptor; <span class="html-italic">TGF-β2</span>, Transforming growth factor β2; <span class="html-italic">GLP-2</span>, Glucagon-like peptide 2.</p>
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<p>Effects of lactic acid, glutamine and their interactions on the mRNA levels of jejunal barrier-related genes in weaning piglets. Each column represents the mean expression level of six independent replications. Letters above the bars (a, b) indicate statistical significance (<span class="html-italic">p</span> &lt; 0.05) of gene expression among the four treatments. CON, a basal diet; LS, supplemented with 2% lactic acid; GS, supplemented with 1% glutamine; LGS, supplemented with 2% lactic acid and 1% glutamine; <span class="html-italic">CLDN-1</span>, claudin 1; <span class="html-italic">CLDN-2</span>, claudin 2; <span class="html-italic">OCLN</span>, occludin; <span class="html-italic">ZO-1</span>, zonula occludens 1; <span class="html-italic">ZO-2</span>, zonula occludens 2.</p>
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16 pages, 1047 KiB  
Article
Serum CS/DS, IGF-1, and IGFBP-3 as Biomarkers of Cartilage Remodeling in Juvenile Idiopathic Arthritis: Diagnostic and Therapeutic Implications
by Katarzyna Winsz-Szczotka, Kornelia Kuźnik-Trocha, Ewa M. Koźma, Bogusław Żegleń, Anna Gruenpeter, Grzegorz Wisowski, Katarzyna Komosińska-Vassev and Krystyna Olczyk
Biomolecules 2024, 14(12), 1526; https://doi.org/10.3390/biom14121526 - 28 Nov 2024
Viewed by 602
Abstract
Cartilage destruction in juvenile idiopathic arthritis (JIA) is diagnosed, often too late, on basis of clinical evaluation and radiographic imaging. This case–control study investigated serum chondroitin/dermatan sulfate (CS/DS) as a potential biochemical marker of cartilage metabolism, aiming to improve early diagnosis and precision [...] Read more.
Cartilage destruction in juvenile idiopathic arthritis (JIA) is diagnosed, often too late, on basis of clinical evaluation and radiographic imaging. This case–control study investigated serum chondroitin/dermatan sulfate (CS/DS) as a potential biochemical marker of cartilage metabolism, aiming to improve early diagnosis and precision treatment for JIA. We also measured the levels of insulin-like growth factor-1 (IGF-1) and insulin-like growth factor-binding protein-3 (IGFBP-3) (using ELISA methods) in JIA patients (n = 55) both before and after treatment (prednisone, sulfasalazine, methotrexate, administered together), and analyzed their relationships with CS/DS levels. Untreated JIA patients [8.26 µg/mL (6.25–9.66)], especially untreated girls [8.57 µg/mL (8.13–9.78)] and patients with a polyarticular form of the disease [7.09 µg/mL (5.63–8.41)], had significantly reduced levels of serum CS/DS compared with the control [14.48 µg/mL (10.23–15.77)]. Therapy resulted in a significant increase in this parameter, but without normalization. We also found significantly lower levels of IGF-1 [66.04 ng/mL (49.45–96.80)] and IGFBP-3 [3.37 ng/mL (2.65–4.88)] in untreated patients compared with the control [96.92 ng/mL (76.04–128.59), 4.84 ng/mL (4.21–7.750), respectively]. Based on receiver operating characteristic (ROC) curve analysis, the blood concentration of CS/DS demonstrated the highest diagnostic power (AUC = 0.947) for JIA among all the tested markers. Untreated patients showed significant correlations between CS/DS and IGF-1 (r = −0.579, p = 0.0000), IGFBP-3 (r = −0.506, p = 0.0001), and C-reactive protein (r = 0.601, p = 0.0005). The observed changes in CS/DS during the course of JIA, influenced by both impairment of the IGF/IGFBP axis and inflammation, indicate the need for continued therapy to protect patients from potential disability. We suggest that CS/DS may be a useful biomarker of disease activity and could be employed to assess treatment efficacy and progress toward remission. Full article
(This article belongs to the Special Issue Hyaluronic Acid and Proteoglycans: Basic and Biomedical Applications)
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<p>ROC curves for circulating CS/DS, IGF-1, and IGFBP-3 in JIA patients.</p>
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<p>Graphical analysis of the linear relationship between serum concentrations of CS/DS and IGF-1 (<b>a</b>) as well as IGFBP-3 (<b>b</b>) in healthy children (A, control subjects), untreated JIA patients (B), and the same patients after treatment (C).</p>
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15 pages, 2350 KiB  
Article
Transcranial Magnetic Stimulation Enhances the Therapeutic Effect of IGF-Trap in Intracerebral Glioma Models
by Stephanie Perrino, Udi Vazana, Ofer Prager, Lior Schori, Gal Ben-Arie, Anna Minarik, Yinhsuan Michely Chen, Orçun Haçariz, Masakazu Hashimoto, Yiftach Roth, Gabriel S. Pell, Alon Friedman and Pnina Brodt
Pharmaceuticals 2024, 17(12), 1607; https://doi.org/10.3390/ph17121607 - 28 Nov 2024
Viewed by 759
Abstract
Background: Glioblastoma multiforme is an aggressive malignancy with a dismal 5-year survival rate of 5–10%. Current therapeutic options are limited, due in part to drug exclusion by the blood–brain barrier (BBB). We have previously shown that high-amplitude repetitive transcranial magnetic stimulation (rTMS) in [...] Read more.
Background: Glioblastoma multiforme is an aggressive malignancy with a dismal 5-year survival rate of 5–10%. Current therapeutic options are limited, due in part to drug exclusion by the blood–brain barrier (BBB). We have previously shown that high-amplitude repetitive transcranial magnetic stimulation (rTMS) in rats allowed the delivery across the BBB of an IGF signaling inhibitor—IGF-Trap. The objective of this study was to assess the therapeutic effect of IGF-Trap when delivered in conjunction with rTMS on the intracerebral growth of glioma. Results: We found that systemic administration of IGF-Trap without rTMS had a minimal effect on the growth of orthotopically injected glioma cells in rats and mice, compared to control animals injected with vehicle only or treated with sham rTMS. In rats treated with a combination of rTMS and IGF-Trap, we observed a growth retardation of C6 tumors for up to 14 days post-tumor cell injection, although tumors eventually progressed. In mice, tumors were detectable in all control groups by 14–17 days post-injection of glioma GL261 cells and progressed rapidly thereafter. In mice treated with rTMS prior to IGF-Trap administration, tumor growth was inhibited or delayed, although the tumors also eventually progressed. Conclusion: The results showed that rTMS could increase the anti-tumor effect of IGF-Trap during the early phases of tumor growth. Further optimization of the rTMS protocol is required to improve survival outcomes. Full article
(This article belongs to the Special Issue Therapeutic Agents for the Treatment of Tumors in the CNS)
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<p>Repeated low-frequency rTMS is safe. (<b>A</b>) shows a diagrammatic depiction of the experimental protocol. ((<b>B</b>)-<b>top</b>) shows T2-weighted (T2w) coronal rat brain MRI acquired after five consecutive days of repeated low-frequency rTMS (day 5, <b>left</b>) and three days later (day 8, <b>right</b>), overlaid with detection of hyper-intensified voxels; and ((<b>B</b>)-<b>bottom</b>) shows T1-weighted (T1w) coronal rat brain MRI at days 5 (<b>left</b>) and 8 (<b>right</b>), overlaid with detection of BBB dysfunction voxels (BBBD, blue). (<b>C</b>) shows the results of the analysis of MRI T2w and T1w scans (reflecting edema and BBBD, respectively) conducted in animals exposed to five consecutive days of repeated low-frequency rTMS or treated with sham rTMS. No significant differences were found between the two groups on either day 5 (<b>left</b>) or 8 (<b>right</b>), confirming the safety of rTMS. (<b>D</b>) shows the results of repeated neurological assessments performed on days 9–12 (red line indicates the integer level of 18, indicating proper function). No difference was detected in NSS between rTMS-exposed and sham-treated rats (<span class="html-italic">n</span> = 7) at any of the time points. Data in (<b>C</b>) are expressed as median and IQR, and in D as means ± standard error of the mean.</p>
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<p>Intracerebral C6 tumor growth in rats is partially inhibited by the combination of rTMS and systemically administered IGF-Trap. (<b>A</b>) shows a diagrammatic representation of the experimental protocol. (<b>B</b>) shows representative contrast-enhanced T1-weighted coronal rat brain MRI images acquired 7 days following intracranial injection of C6 cells to animals subjected to rTMS alone (c6-rTMS, <b>top</b>), sham animals stimulated and injected intravenously with IGF-Trap (c6-sham—IGFT, <b>middle</b>), and animals subjected to rTMS and intravenously injected with IGF-Trap (c6-rTMS-IGFT, <b>bottom</b>). On the left are raw images and on the right are images overlaid with detection of voxels with BBB dysfunction. (<b>C</b>) shows relative volumes of T2w hyper-intensity (<b>top</b>) and BBBD (<b>bottom</b>) on days 7 and 14 post-C6 injection, calculated for c6-rTMS (dark gray), c6-sham-IGFT (light gray) and c6-rTMS-IGFT (black) rats compared to naïve animals. While c6-rTMS and c6-sham-IGFT rats exhibited increased relative BBBD volumes on day 7 compared to naïve animals, BBBD was significantly lower in the c6-rTMS-IGFT group. (<b>E</b>) shows median tumor sizes as evaluated by a radiologist based on T1w-MRI scans acquired on day 7. The difference in tumor size in the different treatment groups was not significant at that time point. (<b>D</b>) shows survival plots. Due to mortality, parameter extraction for c6-sham-IGFT was not feasible on day 14. Data in (<b>C</b>,<b>E</b>) are expressed as median and IQR, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Lack of effect of rTMS on intracerebral tumor growth. Shown in (<b>A</b>) is a diagrammatic representation of the experimental protocol. Shown in ((<b>B</b>)—<b>left</b>) are optical images acquired following intracranial injection of 10<sup>5</sup> GL261 cell, followed by bi-weekly rTMS administration from day 3 onward and (in (<b>B</b>)—<b>right</b>) the radiance per group (<span class="html-italic">n</span> = 5) expressed as median and IQR per treatment group.</p>
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<p>Systemic administration of IGF-Trap in conjunction with rTMS has a partial inhibitory effect on tumor growth and survival. GL261 (10<sup>5</sup> cells/mouse) were injected orthotopically into NSG male mice (<span class="html-italic">n</span> = 5–6). The mice were randomized on day 3, at which time treatment began and continued twice weekly up to 57 days post tumor cell injection. The mice were injected intravenously with 10 mg/kg IGF-Trap, preceded (or not) by 5 rounds of TMS (1min pulses at 1Hz). Control mice received intravenous injections of vehicle (PBS) only. (<b>A</b>) shows a diagrammatic representation of the experimental protocol. (<b>B</b>) shows optical images of mice brains where the intensity of the signal, as represented in the color scales on the right, corresponds to tumor size and (<b>C</b>) shows the radiance expressed as median and IQR per group. (<b>D</b>) shows a Kaplan–Meier survival curve. Arrows in (<b>B</b>) denote mice that did not develop detectable tumors until 63 and 140 days post injection, and survived for 81 and 168 days, respectively.</p>
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<p>Tumor growth is delayed in mice treated with TMS prior to systemic IGF-Trap administration. Mice (<span class="html-italic">n</span> = 5) were injected intra-cerebrally with 3 × 10<sup>4</sup> GL261v cells and randomized for treatment 3 days later. They received intravenous injections of 10 mg/kg IGF-Trap or vehicle (PBS) that were preceded (or not) with TMS administration 5 min earlier on day 3 and twice weekly thereafter until humane endpoint (morbidity). Tumor growth was monitored by optical imaging, performed once weekly following injection of luciferin. One mouse from the TMS/IGF-Trap treatment group was removed from the study due to a technical issue. For a diagrammatic depiction of the experimental protocol, see <a href="#pharmaceuticals-17-01607-f004" class="html-fig">Figure 4</a>. (<b>A</b>) shows representative mice from each treatment group, (<b>B</b>) shows the median and IQR for each group and (<b>C</b>) shows a Kaplan–Meier survival curve. * <span class="html-italic">p</span> &lt; 0.05. as determined by the Mann–Whitney test (radiance) and the log-rank Mantel–Cox test (survival).</p>
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17 pages, 6313 KiB  
Article
Could CH3-M6P Be a Potential Dual-Functioning Candidate for Bone Regeneration?
by Fidan Huseynova, Cătălina Ionescu, Frederic Cuisinier, Irada Huseynova, Alamdar Mammadov and Véronique Barragan-Montero
Biomedicines 2024, 12(12), 2697; https://doi.org/10.3390/biomedicines12122697 - 26 Nov 2024
Viewed by 722
Abstract
Background: CI-RM6P has different binding sites with affinities for both M6P and IGF2, plays a role in the regulation of the TGF-β and IGF pathways that is important for controlling cell growth and differentiation. We hypothesize that previously synthesised derivative of M6P [...] Read more.
Background: CI-RM6P has different binding sites with affinities for both M6P and IGF2, plays a role in the regulation of the TGF-β and IGF pathways that is important for controlling cell growth and differentiation. We hypothesize that previously synthesised derivative of M6P could be an alternative candidate for bone tissue regeneration in terms of higher binding affinity, stability in human serum, low cost and temporal delivery. Methods: CH3-M6P is synthesised based on previously described protocol; mesenchymal origin of isolated DPSCs was assessed by flow cytometry and AR staining prior to alkaline phosphatase (ALP) activity test, qPCR to evaluate differentiation specific marker expression, immunofluoresence, and SEM/EDS to evaluate organic and inorganic matrix formation; and rat aortic ring model to evaluate angiogenic effect of molecule. Results: CH3-M6P upregulated ALP activity, the expression of the ALP, Col1, RunX2, Mef2C, TGFβ1, TGFβ1R, TGFβ2, and Smad3 genes under osteogenic conditions. The results of immunofluorescence and SEM/EDS studies did not show enhancing effect on matrix formation. As we observed, the induction effect of CH3-M6P on the expression of angiogenic genes such as SMAD3 and TGFβ1R, even under osteogenic conditions, within the scope of research, we checked the angiogenic effect of the molecule and compared it to VEGF, showing that the CH3-M6P is really angiogenic. Conclusions: Our findings provide an important clue for the further exploration of the molecule, which can be necessary to enhance the capability of the commonly used osteomedium, possibly leading to the development of bone-forming drugs and has the potential to be a dual-functioning molecule for bone tissue engineering. Full article
(This article belongs to the Special Issue Angiogenesis)
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<p>Identification of MSC markers by flow cytometry expressed on dental pulp cells. (<b>a</b>) CD90 is positive at 92.4%, (<b>b</b>) CD73 is positive at 99.8%, (<b>c</b>) CD105 is positive at 96.5%, (<b>d</b>) Stro1 is positive at 64.5% (<b>e</b>) CD34 is positive at 85.4%, (<b>f</b>) CD117 is negative. Blue spectra shows autoimmunofluoresence, while red spectra shows immunfluoresence of labeled antibody against marker.</p>
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<p>AR staining and assesment of Ca deposition. (<b>a</b>) Pictures obtained by optical microscopy at 14 and 21 days. The cells cultured with OM stained with red due to high amount of calcium deposition. (<b>b</b>) Graphs showing calcium deposition at 14 (*** <span class="html-italic">p</span> = 0.0007) and 21 days (**** <span class="html-italic">p</span> &lt; 0.0001), assessed by spectrophotometric measurement (OM—osteomedium, BM—basal medium).</p>
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<p>The effect of 200, 100, and 10 µM of methyl M6P on cell viability 16 h and 65 h after (<span class="html-italic">n</span> = 1, pentaplicat, ns—shows non-significant). (Vehicle is the mix of DMSO and water that was used to solve molecule).</p>
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<p>The effect of 100 µM of methyl M6P on alkaline phosphatase activity (ALP) at day 7 (<span class="html-italic">p</span> = 0.13, ns—shows non-significant) and day 14 (** <span class="html-italic">p</span> = 0.007) as compared to the control group (OM(v)—osteomedium with the vehicle) (<span class="html-italic">n</span> = 2, triplicate).</p>
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<p>Picture obtained by SEM at 3 weeks of osteodifferentiation after treatment with methyl M6P and OM(v). The result in the graph was obtained by EDS and shows the Ca/P ratio for the same groups.</p>
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<p>Top: (<b>a</b>) pictures obtained by immunofluorescence microscopy after immunostaining against collagen (scale bar is correspond to 83 μm). Bottom: (<b>b</b>) graph showing organic matrix formation at day 21 (tetraplicate). ns shows non-significant.</p>
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<p>CH<sub>3</sub>-M6P effect on osteodifferentiation. The graphs show Col1, ALP, RunX2, Smad3, TSP1, VEGFA, TGFb1, TGFb1R, TGFb2, and Mef2C mRNA expression during 1 or 2 weeks of osteodifferentiation (<span class="html-italic">n</span> = 3, triplicate, ns = not significant, * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, **** <span class="html-italic">p</span> ≤ 0.0001).</p>
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<p>(<b>a</b>) Comparison of the angiogenic effect of 100 µM methyl M6P and 30 ng/mL VEGF on rat aortic ring model. *** <span class="html-italic">p</span> ≤ 0.001 and **** <span class="html-italic">p</span> ≤ 0.0001 were considered significant; * always shows the comparison against control at the same time point. (<b>b</b>) Assessing the existence of microvessels by immunostaining against lectin at the end of experiment (scale bar 100 µm). (<b>c</b>) Left picture, after treatment with 100 µM Methyl-M6P, and right picture, after treatment with 30 ng/mL VEGF, were obtained by light microscope on day 8 of living culture. (<span class="html-italic">n</span> = 3, pentaplicate).</p>
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<p>Synthesis of CH3-M6P. Reaction conditions and yield: pyridine, DMAP, POCl<sub>3</sub>, CH<sub>2</sub>Cl<sub>2</sub>, 0 °C to r.t., 1 h, 75%.</p>
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19 pages, 3653 KiB  
Article
Metformin Impairs Linsitinib Anti-Tumor Effect on Ovarian Cancer Cell Lines
by Diana Luísa Almeida-Nunes, João P. N. Silva, Mariana Nunes, Patrícia M. A. Silva, Ricardo Silvestre, Ricardo Jorge Dinis-Oliveira, Hassan Bousbaa and Sara Ricardo
Int. J. Mol. Sci. 2024, 25(22), 11935; https://doi.org/10.3390/ijms252211935 - 6 Nov 2024
Viewed by 1185
Abstract
Ovarian cancer (OC) remains one of the leading causes of cancer-related mortality among women. Targeting the insulin-like growth factor 1 (IGF-1) signaling pathway has emerged as a promising therapeutic strategy. Linsitinib, an IGF-1 receptor (IGF-1R) inhibitor, has shown potential in disrupting this pathway. [...] Read more.
Ovarian cancer (OC) remains one of the leading causes of cancer-related mortality among women. Targeting the insulin-like growth factor 1 (IGF-1) signaling pathway has emerged as a promising therapeutic strategy. Linsitinib, an IGF-1 receptor (IGF-1R) inhibitor, has shown potential in disrupting this pathway. Additionally, metformin, commonly used in the treatment of type 2 diabetes, has been studied for its anti-cancer properties due to its ability to inhibit metabolic pathways that intersect with IGF-1 signaling, making it a candidate for combination therapy in cancer treatments. This study explores the anti-cancer effects of linsitinib and metformin on OVCAR3 cells by the suppression of the IGF-1 signaling pathway by siRNA-mediated IGF-1 gene silencing. The goal is to evaluate their efficacy as therapeutic agents and to emphasize the critical role of this pathway in OC cell proliferation. Cellular viability was evaluated by resazurin-based assay, and apoptosis was assessed by flux cytometry. The results of this study indicate that the combination of linsitinib and metformin exhibits an antagonistic effect (obtained by SynergyFinder 2.0 Software), reducing their anti-neoplastic efficacy in OC cell lines. Statistical analyses were performed using ordinary one-way or two-way ANOVA, followed by Tukey’s or Šídák’s multiple comparison tests. While linsitinib shows promise as a therapeutic option for OC, further research is needed to identify agents that could synergize with it to enhance its therapeutic efficacy, like the combination with standard chemotherapy in OC (carboplatin and paclitaxel). Full article
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<p>The insulin-like growth factor 1 signaling pathway. Insulin-like growth factor 1 (IGF-1) activates both phosphatidylinositol 3-kinase/Akt and Ras/mitogen-activated protein kinase pathways, resulting in cell proliferation, increased protein synthesis, and cell growth. Phosphatidylinositol 3-kinase/Akt activates nuclear factor-κB and MDM2 for cell survival and inhibits apoptosis through inhibition of BAD and FKHR. Akt—Ak strain transforming; BAD—BCL2-associated agonist of cell death; Erk—extracellular-signal-regulated kinase; FKHR—Forkhead transcription factor FOXO1; IGF-I—insulin-like growth factor 1; IGF-IR—insulin-like growth factor 1 receptor; IGFBP—insulin-like growth factor binding protein; IRSs—insulin receptor substrate proteins; MDM2—mouse double minute 2; MEK—mitogen-activated protein kinase; mTOR—mammalian target of rapamycin; NFκB—nuclear factor immunoglobulin κ chain enhancer-B cell; P—phosphate; PI3K—phosphatidylinositol 3-kinase; PIP2—phosphatidylinositol 3, 4 phosphates; PIP3—phosphatidylinositol 3, 4, 5 phosphates; Raf—rapidly accelerated fibrosarcoma; Ras—rat sarcoma; SHC—Src homology/collagen. Figure created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p><span class="html-italic">IGF-1</span> gene expression in ovarian cell lines. Bar chart showing relative IGF-1 mRNA expression levels in HOSE6.3, OVCAR3, OVCAR8, and OVCAR8 PTX R P cell lines determined by qRT-PCR with β-Actin and GAPDH used as housekeeping genes. The assays were carried out in triplicate in at least three independent experiments. Data are expressed as mean ± standard error of mean deviation (SEM) and plotted using GraphPad Prism Software Inc., San Diego, CA, USA v9. Statistical analysis was performed using ordinary one-way ANOVA followed by Šídák’s multiple comparison test, and values of **** &lt; 0.0001 were considered statistically significant.</p>
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<p>Silencing of <span class="html-italic">IGF-1</span> gene in OVCAR3 cell line. (<b>a</b>) Bar chart showing relative IGF-1 mRNA expression levels in OVCAR3, OVCAR3 transfected with siRNA control (OVCAR3 siNEG), and OVCAR3 transfected with siRNA of IGF-1 (OVCAR3 siIGF-1) determined by qRT-PCR. β-Actin and GAPDH were used as housekeeping genes. (<b>b</b>) Representative Western blot showing IGF-1 protein expression in HOSE6.3, OVCAR3, OVCAR3 siNEG, and OVCAR3 siIGF-1 cell lines. α-tubulin was used as a loading control. (<b>c</b>) Bar chart showing relative IGF-1 protein expression levels in HOSE6.3, OVCAR3, OVCAR3 siNEG, and OVCAR3 siIGF-1 determined by ImageJ 1.4v software. α-tubulin intensity levels were used as a control. The assays were carried out in triplicate in at least three independent experiments. Data are expressed as mean ± standard error of mean deviation (SEM) and plotted using GraphPad Prism Software Inc. v9. Statistical analysis was performed using ordinary one-way ANOVA followed by Šídák’s multiple comparison test and values of * &lt; 0.05 and ** &lt; 0.001 were considered statistically significant.</p>
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<p>Dose–response curves for HOSE6.3 and OVCAR3 of drugs linsitinib and metformin. (<b>a</b>) Dose–response curves for HOSE6.3 and OVCAR3 cells were obtained by Presto Blue assay after exposure to increasing concentrations of linsitinib (780 to 100,000 nM) for 48 h. (<b>b</b>) Dose–response curves for HOSE6.3 and OVCAR3 cells were obtained by Presto Blue assay after exposure to increasing concentrations of metformin (80 to 10,000 μM) for 48 h. IC<sub>50</sub> values are represented by a dotted line in each dose–response curve and are mentioned below. The assays were carried out in triplicate in at least three independent experiments. Data are expressed as mean ± standard error of mean deviation (SEM) and plotted using GraphPad Prism Software Inc. v9.</p>
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<p>Linsitinib demonstrates high efficacy in reducing the cellular viability of OVCAR3 and OVCAR3 siIGF-1. (<b>a</b>) Bar charts showing cell viability of OVCAR3 cells obtained by Presto Blue assay after exposure to a fixed-dose ratio of linsitinib combined with metformin. (<b>b</b>) Bar charts showing cell viability of OVCAR3 siIGF-1 cells obtained by Presto Blue assay after exposure to a fixed-dose ratio of linsitinib combined with metformin. All assays were performed in triplicate in at least three independent experiments. Data are expressed as mean ± standard deviation and plotted using GraphPad Prism Software Inc. v9. Statistical analysis was performed using ordinary two-way ANOVA followed by Šidák’s multiple comparison test, and values of * &lt; 0.05, ** &lt; 0.001, *** &lt; 0.005, and **** &lt; 0.0001 were considered statistically significant.</p>
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<p>Stain with Annexin V/PI and analyzed by flow cytometry to confirm the cellular viability using the drugs linsitinib and metformin in the OVCAR3 and OVCAR3 siIGF-1 cells. (<b>a</b>) Representative flow cytometry histogram of propidium iodide (PI) versus annexin V (FITC-A) intensity in OVCAR3 and OVCAR3 siIGF-1 before (control–DMSO) and after exposure to metformin (500 µM), linsitinib (35 µM), and the combination of both drugs, during 48 h. DMSO was used as a control. The quadrants Q were defined as Q1 = live cells (Annexin V-negative/PI-negative), Q1-LR = early stage of apoptosis (Annexin V-positive/PI-negative), Q1-UL = late stage of apoptosis (Annexin V-positive/PI-positive), and Q1-UL = necrosis (Annexin V-negative/PI-positive). (<b>b</b>) Bar charts showing the percentage of Annexin V-positive cells (early and late stage of apoptosis) to the different conditions of OVCAR3 and OVCAR3 siIGF-1. The assays were carried out in triplicate in at least three independent experiments. Data are expressed as mean ± standard error of mean deviation (SEM) and plotted using GraphPad Prism Software Inc. v9. Statistical analysis was performed using ordinary one-way ANOVA followed by Šídák’s multiple comparison test and values of ** &lt; 0.001, *** &lt; 0.005, and **** &lt; 0.0001 were considered statistically significant.</p>
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<p>Stain with Annexin V/PI and analyzed by flow cytometry to confirm the cellular viability using the drugs linsitinib and metformin in the OVCAR3 and OVCAR3 siIGF-1 cells. (<b>a</b>) Representative flow cytometry histogram of propidium iodide (PI) versus annexin V (FITC-A) intensity in OVCAR3 and OVCAR3 siIGF-1 before (control–DMSO) and after exposure to metformin (500 µM), linsitinib (35 µM), and the combination of both drugs, during 48 h. DMSO was used as a control. The quadrants Q were defined as Q1 = live cells (Annexin V-negative/PI-negative), Q1-LR = early stage of apoptosis (Annexin V-positive/PI-negative), Q1-UL = late stage of apoptosis (Annexin V-positive/PI-positive), and Q1-UL = necrosis (Annexin V-negative/PI-positive). (<b>b</b>) Bar charts showing the percentage of Annexin V-positive cells (early and late stage of apoptosis) to the different conditions of OVCAR3 and OVCAR3 siIGF-1. The assays were carried out in triplicate in at least three independent experiments. Data are expressed as mean ± standard error of mean deviation (SEM) and plotted using GraphPad Prism Software Inc. v9. Statistical analysis was performed using ordinary one-way ANOVA followed by Šídák’s multiple comparison test and values of ** &lt; 0.001, *** &lt; 0.005, and **** &lt; 0.0001 were considered statistically significant.</p>
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<p>Combining linsitinib with metformin has an antagonist effect on OVCAR3 and OVCAR3 siIGF-1 cells. (<b>a</b>) ZIP, Bliss Independence, Loewe, and High Single Agent (HSA) synergy 2D and 3D plots showing drug antagonism of OVCAR3 cells after exposure to a fixed-dose ratio of linsitinib and metformin for 48 h. (<b>b</b>) ZIP, Bliss Independence, Loewe, and HSA synergy 2D and 3D plots showing drug antagonism of OVCAR3 siIGF-1 cells after exposure to a fixed-dose ratio of linsitinib and metformin for 48 h. The combined treatment was co-administered at the same time. All assays were performed in triplicate in at least three independent experiments. Synergy score: &lt;10 (antagonism, green), =1 (additivity, white), and &gt;10 (synergism, red).</p>
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<p>Schematic representation of metformin’s possible interaction with linsitinib. The most common pathway involves the activation of AMPK, which regulates energy metabolism by modulating complex 1 of the respiratory chain in mitochondria by changes in the AMP/ATP ratio, which inhibits Akt and mTOR. Metformin binds with IGF-1 and modulates pathways involved in tumor progression. Upon binding, metformin inhibits the PI3K/Akt/mTOR and Ras/Raf/ERK pathways, leading to reductions in cell proliferation, thereby causing tumor cell death. Metformin, through AMPK activation and mTOR inhibition, could increase glucose uptake and glycolysis and have better efficiency in low-glucose media. The arrows ↑ ↓ indicate upregulation and downregulation, respectively. The drug linsitinib blocks IGF-1R (represented by the red *), which helps to block the IGF-1 signaling pathway. ADP—adenosine diphosphate; Akt—Ak strain transforming; AMP—adenosine monophosphate; AMPK—adenosine monophosphate-activated protein kinase; ATP—adenosine triphosphate; Erk—extracellular-signal-regulated kinase; IGF-I—insulin-like growth factor 1; IGF-IR—insulin-like growth factor 1 receptor; MEK—mitogen-activated protein kinase; mTOR—mammalian target of rapamycin; PI3K—phosphatidylinositol 3-kinase; Raf—rapidly accelerated fibrosarcoma; Ras—rat sarcoma. Figure created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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22 pages, 7373 KiB  
Article
Insights into the Therapeutic Potential of Active Ingredients of Citri Reticulatae Pericarpium in Combatting Sarcopenia: An In Silico Approach
by Amin Ullah, Yacong Bo, Jiangtao Li, Jinjie Li, Pipasha Khatun, Quanjun Lyu and Guangning Kou
Int. J. Mol. Sci. 2024, 25(21), 11451; https://doi.org/10.3390/ijms252111451 - 25 Oct 2024
Viewed by 1139
Abstract
Sarcopenia is a systemic medical disorder characterized by a gradual decline in muscular strength, function, and skeletal muscle mass. Currently, there is no medication specifically approved for the treatment of this condition. Therefore, the identification of new pharmacological targets may offer opportunities for [...] Read more.
Sarcopenia is a systemic medical disorder characterized by a gradual decline in muscular strength, function, and skeletal muscle mass. Currently, there is no medication specifically approved for the treatment of this condition. Therefore, the identification of new pharmacological targets may offer opportunities for the development of novel therapeutic strategies. The current in silico study investigated the active ingredients and the mode of action of Citri Reticulatae Pericarpium (CRP) in addressing sarcopenia. The active ingredients of CRP and the potential targets of CRP and sarcopenia were determined using various databases. The STRING platform was utilized to construct a protein–protein interaction network, and the key intersecting targets were enriched through the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. Molecular docking was used to determine the binding interactions of the active ingredients with the hub targets. The binding affinities obtained from molecular docking were subsequently validated through molecular dynamics simulation analyses. Five active ingredients and 45 key intersecting targets between CRP and sarcopenia were identified. AKT1, IL6, TP53, MMP9, ESR1, NFKB1, MTOR, IGF1R, ALB, and NFE2L2 were identified as the hub targets with the highest degree node in the protein–protein interaction network. The results indicated that the targets were mainly enriched in PIK3-AKT, HIF-1, and longevity-regulating pathways. The active ingredients showed a greater interaction affinity with the hub targets, as indicated by the results of molecular docking and molecular dynamics simulations. Our findings suggest that the active ingredients of Citri Reticulatae Pericarpium, particularly Sitosterol and Hesperetin, have the potential to improve sarcopenia by interacting with AKT1 and MTOR proteins through the PI3K-AKT signaling pathway. Full article
(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery)
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<p>Flowchart of the study. TCMP: Traditional Chinese Medicine Systems Pharmacology; BATMAN: Bioinformatics Annotation daTabase for Molecular mechANism; OMIM: Online Mendelian Inheritance in Man; NCBI: National Center for Biotechnology Information; CTD: Comparative Toxicogenomics Database; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; PPI: protein–protein interaction; H-C-T-P: herb-compound-target-pathway.</p>
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<p>Target collection from various drug and disease databases. (<b>A</b>) Active ingredients of <span class="html-italic">Citri Reticulatae Pericarpium</span>-related targets; (<b>B</b>) Sarcopenia-related targets.</p>
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<p>Venn diagram of <span class="html-italic">Citri Reticulatae Pericarpium</span> and sarcopenia: the red part represents <span class="html-italic">Citri Reticulatae Pericarpium</span> with 702 targets, the green part represents sarcopenia with 568 targets, while the brown intersecting part represents the core intersecting targets between <span class="html-italic">Citri Reticulatae Pericarpium</span> and sarcopenia.</p>
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<p>(<b>A</b>) Protein–protein interaction network of key intersecting targets of <span class="html-italic">Citri Reticulatae Pericarpium</span> and sarcopenia; (<b>B</b>) visualized nodes and edges of protein–protein interaction network; (<b>C</b>) top 10 hub genes in the protein–protein interaction network.</p>
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<p>Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment. (<b>A</b>) Biological process (BP); (<b>B</b>) cellular component (CC); (<b>C</b>) molecular function (MF); (<b>D</b>) gene ontology bar chart; (<b>E</b>) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment.</p>
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<p>Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment. (<b>A</b>) Biological process (BP); (<b>B</b>) cellular component (CC); (<b>C</b>) molecular function (MF); (<b>D</b>) gene ontology bar chart; (<b>E</b>) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment.</p>
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<p>The herb-compound-target-pathway network. The <span style="color:#FC4E2A">orange diamond</span> in the center represents the herb <span class="html-italic">Citri Reticulatae Pericarpium</span>, the five <span style="color:#0099FF">blue diamonds</span> represent the active ingredients, the <span style="color:#999900">olive-green octagons</span> and <span style="color:#00CCCC">cyan octagons</span> represent the core intersecting targets, while the outer <span style="color:#FF6633">ellipse shapes</span> represent the pathways in the network.</p>
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<p>Heatmap illustrating the binding energies (kcal/mol) between the active ingredients of <span class="html-italic">Citri Reticulatae Pericarpium</span> and 10 hub targets (<span class="html-italic">n</span> = 50).</p>
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<p>Molecular docking of Sitosterol, Hesperetin, Naringenin, and Nobiletin with AKT1, MTOR, and ALB proteins. (<b>A</b>) Sitosterol–AKT1; (<b>B</b>) Sitosterol–MTOR; (<b>C</b>) Sitosterol–ALB; (<b>D</b>) Hesperetin–AKT1, (<b>E</b>) Hesperetin–MTOR; (<b>F</b>) Naringenin–AKT1; (<b>G</b>) Nobiletin–AKT1.</p>
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<p>Molecular dynamics simulation of AKT1, MTOR, ALB, and active ingredients. (<b>A</b>) AKT1–Hesperetin/Naringenin/Nobiletin/Sitosterol; (<b>B</b>) MTOR–Hesperetin/Sitosterol; (<b>C</b>) ALB–Sitosterol.</p>
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21 pages, 7821 KiB  
Article
Single-Cell Analysis Reveals the Cellular and Molecular Changes of Liver Injury and Fibrosis in Mice During the Progression of Schistosoma japonicum Infection
by Julu Lu, Xinyue Zhang, Panpan Dong, Congjin Mei, Yingying Yang, Chuanxin Yu and Lijun Song
Curr. Issues Mol. Biol. 2024, 46(11), 11906-11926; https://doi.org/10.3390/cimb46110707 - 23 Oct 2024
Viewed by 1776
Abstract
Schistosomiasis is a parasitic disease that poses a serious threat to human health. However, the pathogenic mechanism during the progression of Schistosoma japonicum infection remains unclear. In order to elucidate this mechanism, we used single-cell RNA sequencing (scRNA-seq) to investigate the transcriptome characteristics [...] Read more.
Schistosomiasis is a parasitic disease that poses a serious threat to human health. However, the pathogenic mechanism during the progression of Schistosoma japonicum infection remains unclear. In order to elucidate this mechanism, we used single-cell RNA sequencing (scRNA-seq) to investigate the transcriptome characteristics of the cellular (single-cell) landscape in the livers of mice infected with Schistosoma japonicum, which were divided into three groups: uninfected mice (0 week (w)), infected mice at 6 w post-infection (the acute phase), and infected mice at 10 w post-infection (the chronic phase). A total of 31,847 liver cells were included and clustered into 21 groups. The cells and T-cells had high heterogeneity in the liver during the progression of schistosome infection. The number and intensity of the intercellular interactions significantly increased at 6 w after infection but decreased at 10 w. The inflammatory signaling pathways chemoattractant cytokine ligand (CCL)5-chemokine C-C-motif receptor (CCR)5 between macrophages and T-cells were predominant at 6 w post-infection; the CCL6-CCR2 signaling pathway between macrophages was predominant at 10 w. The CD80 signaling pathway related to T-cell activation was increased at 6 w after infection, and increased expression of its receptor CD28 on the surfaces of CD4+ and CD8+ T-cells was confirmed by flow cytometry, suggesting an increase in their activation. In addition, scRNA-seq and quantitative reverse transcription polymerase chain reaction (qRT-PCR) confirmed that the intercellular communication between secretory phosphoprotein 1 (SPP1)-cluster of differentiation (CD44), insulin-like growth factor (IGF)-1-IGF1r and visfatin-insulin receptor (Insr) associated with bone metabolism and insulin metabolism was increased and enhanced in the liver at 6 w post-infection. Overall, we provide the comprehensive single-cell transcriptome landscape of the liver in mice during the progression of schistosome infection and delineate the key cellular and molecular events involved in schistosome infection-induced liver injury and fibrosis. The elevated CCL5-CCR5 and CCL6-CCR2 signaling pathways in the liver may be a drug target for liver injury and fibrosis caused by schistosome infection, respectively. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Pathological changes and cell clustering annotation in the livers of mice during the progression of <span class="html-italic">S. japonicum</span> infection. (<b>A</b>) Liver pathological changes at 0 w (healthy mice), 6 w and 10 w after schistosome infection. (<b>B</b>) UMAP graph of the dimensionality reduction clustering of single cells (colored by cluster, cell type, and infection time). (<b>C</b>) Changes in the proportion of liver cell populations in different groups before and after schistosome infection. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Changes in the T-cell subtypes in the livers of mice during the progression of <span class="html-italic">S. japonicum infection.</span> (<b>A</b>) The 2322 T-cell dimensionality reduction clustering UMAP plot (stained by cell type and infection time). (<b>B</b>) Violin plot of the gene expression in different T-cell subtypes. (<b>C</b>) Changes in the T-cell subtypes in the livers of mice before and after schistosome infection. (<b>D</b>) Bubble plot of the enriched KEGG pathways in Th1 cells compared with other T-cell subtypes. (<b>E</b>) Bubble plot of the enriched KEGG pathways in Th2 cells compared with other T-cell subtypes. (<b>F</b>) Pseudotemporal analysis of the T-cell subtypes.</p>
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<p>Cell communication in the livers of mice during the progression of <span class="html-italic">S. japonicum</span> infection. (<b>A</b>) The number and intensity of the interactions between cells in the liver before and after <span class="html-italic">S. japonicum</span> infection. (<b>B</b>) The number and intensity of the interactions between liver cells in mice infected with schistosomes at 6 w post-infection compared with those in uninfected mice (0 w). (<b>C</b>) The number and intensity of the interactions between liver cells in mice infected with schistosomes at 10 w post-infection compared with those in uninfected mice (0 w). (<b>D</b>) The number and intensity of the interactions between liver cells in mice infected with schistosomes at 6 w post-infection compared with those in mice at 10 w post-infection. (<b>E</b>) Information flow of various signaling pathways in the livers of mice before and after schistosome infection.</p>
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<p>Promoted CCL and CXCL signaling pathways in the livers of mice during the progression of <span class="html-italic">S. japonicum</span> infection. (<b>A</b>) Cellular communication network diagram of CCL4-CCR5 in the liver at 6 and 10 w after schistosome infection. (<b>B</b>) Cellular communication network diagram of CCL5-CCR5 in the liver at 6 and 10 w after schistosome infection. (<b>C</b>) Cellular communication network diagram of CCL6-CCR2 in the liver of mice at 10 w after schistosome infection. (<b>D</b>) Cellular communication network diagram of CXCL2-CXCR2 in the liver of mice at 6 and 10 w after schistosome infection. (<b>E</b>) Heatmap of the intensity of the CCL signaling pathway between different cell types in the liver at 6 and 10 w after schistosome infection. (<b>F</b>) Heatmap of the intensity of the CXCL signaling pathway between different cell types in the liver at 6 and 10 w after schistosome infection. (<b>G</b>) The relative mRNA expression of CCL4-CCR5, CCL5-CCR5, and CCL6-CCR2 in the liver of mice. (<b>H</b>) The relative mRNA expression of CXCL2-CXCR2 in the liver of mice at 0 w, 6 w, 10 w after schistosome infection (n = 5). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>CD80 signaling pathway related to T-cell activation signaling pathways in the livers of mice during the progression of <span class="html-italic">S</span>. <span class="html-italic">japonicum</span> infection. (<b>A</b>) Distribution of CD80 ligands and receptors in the livers of mice at 6 w after schistosome infection. (<b>B</b>) Heatmap of the communication intensity of the CD80 signaling pathway between different cell types in the livers of mice at 6 w after schistosome infection. (<b>C</b>) Violin plot of the expression distribution of CD80 signaling pathway-related genes. (<b>D</b>) Cellular communication network diagram of CD80-CD28 and CD80-CD274 in the livers of mice at 6 w after schistosome infection. (<b>E</b>) The relative mRNA expression of CD80-CD28 and CD80-CD274 in the livers of the mice at 0 w, 6 w, 10 w after schistosome infection (<span class="html-italic">n</span> = 5). (<b>F</b>) Flow cytometry detection of the expression of CD28 and CD274 on CD4<sup>+</sup> and CD8<sup>+</sup> cells in the liver of the mice at 0 w, 6 w, 10 w after schistosome infection (<span class="html-italic">n</span> = 5). ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Promoted SPP1, IGF1 and visfatin signaling pathways in the livers of mice infected with schistosomes. (<b>A</b>) Violin plot of the expression distribution of SPP1, IGF1 and visfatin signaling pathway-related genes. (<b>B</b>) Cellular communication network diagram of SPP1-CD44, IGF-1-IGF-1r and visfatin-Insr in the liver of mice at 6 w after schistosome infection. (<b>C</b>) Heatmap of the communication intensity of the SPP1, IGF1 and visfatin signaling pathway between different cell types in the liver of mice at 6 w after schistosome infection. (<b>D</b>) The relative mRNA expression of SPP1-CD44, IGF-1-IGF-1r and visfatin-Insr in the liver of mice at 0 w, 6 w, 10 w after schistosome infection (n = 5). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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12 pages, 1631 KiB  
Review
The Impact of Pdcd4, a Translation Inhibitor, on Drug Resistance
by Qing Wang and Hsin-Sheng Yang
Pharmaceuticals 2024, 17(10), 1396; https://doi.org/10.3390/ph17101396 - 19 Oct 2024
Viewed by 1106
Abstract
Programmed cell death 4 (Pdcd4) is a tumor suppressor, which has been demonstrated to efficiently suppress tumorigenesis. Biochemically, Pdcd4 binds with translation initiation factor 4A and represses protein translation. Beyond its role in tumor suppression, growing evidence suggests that Pdcd4 enhances the chemosensitivity [...] Read more.
Programmed cell death 4 (Pdcd4) is a tumor suppressor, which has been demonstrated to efficiently suppress tumorigenesis. Biochemically, Pdcd4 binds with translation initiation factor 4A and represses protein translation. Beyond its role in tumor suppression, growing evidence suggests that Pdcd4 enhances the chemosensitivity of several anticancer drugs. To date, numerous translational targets of Pdcd4 have been identified. These targets govern important signal transduction pathways, and their attenuation may improve chemosensitivity or overcome drug resistance. This review will discuss the signal transduction pathways regulated by Pdcd4 and the potential mechanisms through which Pdcd4 enhances chemosensitivity or counteracts drug resistance. Full article
(This article belongs to the Section Pharmacology)
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<p>Pdcd4 is a tumor suppressor. Experimental evidence has shown that Pdcd4 suppresses various cancer cell characteristics including inflammation, proliferation, survival, invasion, and metastasis. Additionally, Pdcd4 promotes apoptosis and helps to overcome drug resistance.</p>
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<p>Schematic diagram of the functional motifs of Pdcd4. Two MA-3 domains binding with eIF4A to inhibit protein translation; Ser67 phosphorylated by Akt or p70S6K for proteasome degradation; Ser457 phosphorylated by Akt for nuclear localization; Arg110 methylated by PRMT5 to attenuate the tumor suppression function; the positive amino acid cluster (+++) binding with RNAs.</p>
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<p>Pdcd4 suppresses mTORC2–Akt pathway.</p>
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<p>Pdcd4 suppresses the E-cadherin–β-catenin pathway. The transcription repressor Snail suppresses E-cadherin expression, leading to β-catenin nuclear translocation and binding with Tcf4 to stimulate expression of oncogenes and chemoresistance genes.</p>
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<p>Pdcd4 suppresses JNK–AP-1 pathway. Pdcd4 inhibits MAP4K1 expression or directly binds to c-Jun, resulting in suppression of JNK–AP-1 pathway.</p>
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26 pages, 8774 KiB  
Review
RNA Binding Proteins as Potential Therapeutic Targets in Colorectal Cancer
by Vikash Singh, Amandeep Singh, Alvin John Liu, Serge Y. Fuchs, Arun K. Sharma and Vladimir S. Spiegelman
Cancers 2024, 16(20), 3502; https://doi.org/10.3390/cancers16203502 - 16 Oct 2024
Viewed by 1924
Abstract
RNA-binding proteins (RBPs) play critical roles in regulating post-transcriptional gene expression, managing processes such as mRNA splicing, stability, and translation. In normal intestine, RBPs maintain the tissue homeostasis, but when dysregulated, they can drive colorectal cancer (CRC) development and progression. Understanding the molecular [...] Read more.
RNA-binding proteins (RBPs) play critical roles in regulating post-transcriptional gene expression, managing processes such as mRNA splicing, stability, and translation. In normal intestine, RBPs maintain the tissue homeostasis, but when dysregulated, they can drive colorectal cancer (CRC) development and progression. Understanding the molecular mechanisms behind CRC is vital for developing novel therapeutic strategies, and RBPs are emerging as key players in this area. This review highlights the roles of several RBPs, including LIN28, IGF2BP1–3, Musashi, HuR, and CELF1, in CRC. These RBPs regulate key oncogenes and tumor suppressor genes by influencing mRNA stability and translation. While targeting RBPs poses challenges due to their complex interactions with mRNAs, recent advances in drug discovery have identified small molecule inhibitors that disrupt these interactions. These inhibitors, which target LIN28, IGF2BPs, Musashi, CELF1, and HuR, have shown promising results in preclinical studies. Their ability to modulate RBP activity presents a new therapeutic avenue for treating CRC. In conclusion, RBPs offer significant potential as therapeutic targets in CRC. Although technical challenges remain, ongoing research into the molecular mechanisms of RBPs and the development of selective, potent, and bioavailable inhibitors should lead to more effective treatments and improved outcomes in CRC. Full article
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<p>(<b>A</b>,<b>B</b>) show 3D representations of the binding and surface view of inhibitor Ln7 with RNA binding protein Ln28 (PDBID: 5UDZ). (<b>C</b>) shows 2D representations of binding interactions of Ln7. (<b>D</b>) The binding energy of inhibitors with RNA binding protein Ln28 along with interacting residues. Color code: green = carbon, white = hydrogen, blue = nitrogen, and red = oxygen.</p>
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<p>(<b>A</b>,<b>B</b>) show 3D representations of the binding and surface view of inhibitor R12–8–44–3 with RNA binding protein Musash1 (PDBID: 2RS2). (<b>C</b>) shows 2D representations of binding interactions of Musashi1. (<b>D</b>) The binding energy of inhibitors with RNA binding protein Musashi 1 along with interacting residues. Color code: green = carbon, white = hydrogen, blue = nitrogen, and red = oxygen.</p>
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<p>(<b>A</b>,<b>B</b>) show 3D representations of the binding and surface view of inhibitor R12–8–44–3 with RNA binding protein Musash1 (PDBID: 2RS2). (<b>C</b>) shows 2D representations of binding interactions of Musashi1. (<b>D</b>) The binding energy of inhibitors with RNA binding protein Musashi 1 along with interacting residues. Color code: green = carbon, white = hydrogen, blue = nitrogen, and red = oxygen.</p>
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<p>(<b>A</b>,<b>B</b>) show 3D representations of the binding and surface view of inhibitor palmatine with RNA binding protein Musash2 (PDBID: 6DBP). (<b>C</b>) shows 2D representations of binding interactions of Musashi2. (<b>D</b>) The binding energy of inhibitors with RNA binding protein Musashi 2 along with interacting residues. Color code: green = carbon, white = hydrogen, blue = nitrogen, and red = oxygen.</p>
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<p>(<b>A</b>,<b>B</b>) show 3D representations of the binding and surface view of inhibitor C11 with RNA binding protein HUR (PDBID: 4ED5). (<b>C</b>) shows 2D representations of binding interactions of HUR. (<b>D</b>) The binding energy of inhibitors with RNA binding protein HUR along with interacting residues. Color code: green = carbon, white = hydrogen, blue = nitrogen, and red = oxygen.</p>
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<p>(<b>A</b>,<b>B</b>) show 3D representations of the binding and surface view of inhibitor C11 with RNA binding protein HUR (PDBID: 4ED5). (<b>C</b>) shows 2D representations of binding interactions of HUR. (<b>D</b>) The binding energy of inhibitors with RNA binding protein HUR along with interacting residues. Color code: green = carbon, white = hydrogen, blue = nitrogen, and red = oxygen.</p>
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<p>(<b>A</b>,<b>B</b>) show 3D representations of the binding and surface view of inhibitor compound27 with RNA binding protein CELFI (PDBID: 3NMR). (<b>C</b>) shows 2D representations of binding interactions of CELFI. (<b>D</b>) The binding energy of inhibitors with RNA binding protein CELFI along with interacting residues. Color code: green = carbon, white = hydrogen, blue = nitrogen, and red = oxygen.</p>
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Opinion
Teprotumumab for the Treatment of Thyroid Eye Disease: Why Should We Keep Our Eyes “Wide Open”?—A Clinical and Pharmacovigilance Point of View
by Arnaud Martel, Fanny Rocher and Alexandre Gerard
J. Pers. Med. 2024, 14(10), 1027; https://doi.org/10.3390/jpm14101027 - 26 Sep 2024
Viewed by 1335
Abstract
Objectives: Thyroid eye disease (TED) treatment has been recently revolutionized with the approval of teprotumumab, a targeted insulin growth factor 1 receptor (IGF1R) inhibitor. To date, teprotumumab is the only FDA-approved drug for treating TED. In this article, we would like to temper [...] Read more.
Objectives: Thyroid eye disease (TED) treatment has been recently revolutionized with the approval of teprotumumab, a targeted insulin growth factor 1 receptor (IGF1R) inhibitor. To date, teprotumumab is the only FDA-approved drug for treating TED. In this article, we would like to temper the current enthusiasm around IGF1R inhibitors. Methods: critical review of the literature by independent academic practitioners. Results: several questions should be raised. First, “how an orphan drug has become a blockbuster with annual sales exceeding $1 billion?” Teprotumumab infusions are expensive, costing about USD 45,000 for one infusion and USD 360,000 for eight infusions in a 75 kg patient. Teprotumumab approval was based on two randomized clinical trials investigating active (clinical activity score ≥ 4) TED patients. Despite this, teprotumumab was approved by the FDA for “the treatment of TED” without distinguishing between active and inactive forms. The second question is as follows: “how can a new drug, compared only to a placebo, become the new standard without being compared to historically established gold standard medical or surgical treatments?” Teprotumumab has never been compared to other medical treatments in active TED nor to surgery in chronic TED. Up to 75% of patients may experience proptosis regression after treatment discontinuation. Finally, ototoxicity has emerged as a potentially devastating side effect requiring frequent monitoring. Investigation into the long-term side effects, especially in women of childbearing age, is also warranted. Conclusions: Teprotumumab is undoubtedly a major treatment option in TED. However, before prescribing a drug, practitioners should assess its benefit/risk ratio based on the following: (i) evidence-based medicine; (ii) their empirical experience; (iii) the cost/benefit analysis; (iv) the long-term outcomes and safety profile. Full article
(This article belongs to the Section Evidence Based Medicine)
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