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Search Results (242)

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15 pages, 2267 KiB  
Article
Unveiling the Anti-Angiogenic Potential of Small-Molecule (Kinase) Inhibitors for Application in Rheumatoid Arthritis
by Fatemeh Khodadust, Eva M. L. Philippon, Maarten M. Steinz, Jan Piet van Hamburg, Johan van Meerloo, Judy R. van Beijnum, Gerrit Jansen, Sander W. Tas and Conny J. van der Laken
Cells 2025, 14(2), 102; https://doi.org/10.3390/cells14020102 (registering DOI) - 11 Jan 2025
Viewed by 334
Abstract
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation leading to joint damage and systemic complications. Angiogenesis promotes inflammation and contributes to RA progression. This study evaluated potential anti-angiogenic effects of several compounds including small-molecule kinase inhibitors, such as sunitinib (pan-kinase [...] Read more.
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation leading to joint damage and systemic complications. Angiogenesis promotes inflammation and contributes to RA progression. This study evaluated potential anti-angiogenic effects of several compounds including small-molecule kinase inhibitors, such as sunitinib (pan-kinase inhibitor), tofacitinib (JAK-inhibitor), NIKi (NF-κB-inducing kinase inhibitor), and the integrin-targeting peptide fluciclatide, using a scratch assay and 3D spheroid-based models of angiogenesis. For all drugs tested in the low micromolar range (1–25 μM), sunitinib (as positive anti-angiogenetic control) showed marked inhibition of endothelial cell (EC) migration and sprouting, effectively reducing both scratch closure and sprout formation. Tofacitinib exhibited marginal effectiveness in the scratch assay, but performed better in the 3D models (55% inhibition), whereas NIKi showed around 50% anti-angiogenic effects in both models. Fluciclatide changed EC morphology rather than migration, and only when stimulated with synovial fluid in spheroid model did it show inhibitory effects (at ≥2.5 µM), with none below this dosage. These results highlight the potential of NIKi and tofacitinib for angiogenesis inhibition and of fluciclatide for safe diagnostic targeting of microdose in RA, as well as the need for advanced screening models that mimic RA’s complex inflammatory pro-angiogenic environment. Full article
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<p>Effects of sunitinib, tofacitinib, and NIKi on HMEC-1 cell migration in scratch assay. HMEC-1 scratch wound analysis in the presence of (<b>A</b>) sunitinib (pan tyrosine kinase receptor inhibitor) at concentrations ranging from 0.33–10 µM. Analysis conducted after 8, 16, and 24 h drug incubations. (<b>B</b>) Tofacitinib (selective JAK1/3 inhibitor), concentration range: 0.33–10 µM, analysis performed after 4, 8, and 16 h drug incubations (with no stimulator added). (<b>C</b>) NIKi (NF-κB inducing kinase inhibitor) at concentrations ranging from 0.33–10 µM (in the presence of LIGHT (TNFSF14) to stimulate non-canonical NF-κB pathway. The % of migrating cells was calculated as the area covered by cells and is represented as an average of 3 independent experiments. Data represent mean ± SEM. <span class="html-italic">p</span>-values represent two-tailed distribution according to Student’s <span class="html-italic">t</span>-test (***: <span class="html-italic">p</span> ≤ 0.001, **: <span class="html-italic">p</span> ≤ 0.01, *: <span class="html-italic">p</span> ≤ 0.05 and ns: not significant).</p>
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<p>Scratch assay images of HMEC-1 cells treated with sunitinib and fluciclatide after 24 h of incubation. Representative images from scratch assay of HMEC-1 cells treated with (<b>A</b>) sunitinib and (<b>B</b>) fluciclatide following 24 h of drug incubation. The images were captured on an automated platform using a Leica DMI3000B microscope (Leica, Rijswijk, The Netherlands) and a Pulnix RMC1327GE camera (Takex Europe, Hampshire, UK) under control of Universal Grab 6.3 software (DCILabs, Keerbergen, Belgium).</p>
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<p>Inhibition of endothelial cell sprouting in 3D spheroid-based angiogenesis model treated with sunitinib, tofacitinib, NIKi, and fluciclatide. Representative confocal images (10× magnification) of 3D spheroid-based angiogenesis model composed of HUVEC depicted (in cyan) and NHDF cells (in magenta) upon stimulation with the growth factors VEGF/bFGF. Inhibition of EC sprouting was monitored after 40 h of incubation with: (<b>A</b>) sunitinib, (<b>B</b>) tofacitinib, (<b>C</b>) NIKi, and (<b>D</b>) fluciclatide. Sprout formation of HUVEC was quantified by measuring the total sprout area of each spheroid, defined by training pixel classifiers in QuPath. Data represent the means of 3 independent experiments. Statistical analysis was conducted using one-way ANOVA, a non-parametric test, followed by the original FDR method of Benjamini and Hochberg with <span class="html-italic">p</span>-values: ****: <span class="html-italic">p</span> ≤ 0.0001, ***: 0.0001 &lt; <span class="html-italic">p</span> ≤ 0.001, **: 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, ns: not significant.</p>
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<p>Effects of inhibitors on HUVEC sprouting in a 3D spheroid-based model of RA synovial angiogenesis. Drug incubations: 40 h. Statistical significance was determined using one-way ANOVA, a non-parametric test, followed by the original FDR method of Benjamini and Hochberg with <span class="html-italic">p</span>-values: ****: <span class="html-italic">p</span> ≤ 0.0001, ***: 0.0001 &lt; <span class="html-italic">p</span> ≤ 0.001, and ns: not significant.</p>
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9 pages, 1748 KiB  
Case Report
Case Report: Successful Treatment of Solitary Fibrous Tumor with Selective Internal Radiation Therapy (SIRT)
by Omar Badran, Sergey Dereza, Labib Mireb, Ziv Neeman and Gil Bar-Sela
Diseases 2024, 12(11), 290; https://doi.org/10.3390/diseases12110290 - 12 Nov 2024
Viewed by 1149
Abstract
Background: This case report details the innovative use of selective internal radiation therapy (SIRT) with Yttrium-90 resin microspheres to treat a 73-year-old woman with a solitary fibrous tumor (SFT), a rare and challenging tumor type. SFTs often present significant treatment difficulties, especially [...] Read more.
Background: This case report details the innovative use of selective internal radiation therapy (SIRT) with Yttrium-90 resin microspheres to treat a 73-year-old woman with a solitary fibrous tumor (SFT), a rare and challenging tumor type. SFTs often present significant treatment difficulties, especially in cases of recurrence or metastasis, as systemic therapies typically show limited effectiveness. This report explores SIRT as an alternative therapeutic approach for SFTs with liver metastasis. Methods: The patient initially presented with a pelvic mass, which was surgically resected. However, metastatic disease later developed in the liver. After experiencing severe side effects from targeted therapy with sunitinib, the patient was selected for treatment with SIRT as an alternative. Results: Following the SIRT intervention, the patient demonstrated a substantial reduction in tumor size and significant relief from symptoms. This outcome suggests SIRT’s effectiveness as a targeted treatment for metastatic SFT. Conclusions: To our knowledge, and based on an extensive literature review, this is the first reported instance of treating SFT with SIRT. This case provides new insights into SIRT’s potential as a therapeutic strategy, particularly for patients for whom conventional treatments are either ineffective or intolerable. The success observed here underscores SIRT’s potential as a less invasive, locally targeted treatment option, offering hope for similar cases. Full article
(This article belongs to the Section Oncology)
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<p>This abdominal and pelvic CT with contrast, performed on 25 December 2023, was compared to the previous abdominal CT from 15 August 2023 and the chest CT from 9 December 2021. The liver demonstrated two hypervascular lesions consistent with SFT: one lesion in segment 8 measuring 0.9 cm, previously 0.6 cm, and another lesion in segment 6 measuring 1.5 cm, previously 1.3 cm.</p>
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<p>This CT angiography, performed on 8 February 2024, simulates contrast injection, highlighting the blood supply to the tumors during the arterial phase.</p>
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<p>In this CT scan, dated 30 July 2024, of the chest, abdomen, and pelvis, performed after intravenous contrast injection with additional oral contrast administration, pre- and post-contrast imaging was conducted using a triphasic protocol focused on the liver. Comparison was made with the previous CT examination from 15 May 2024. The smaller lesions disappeared following SIRT treatment, and the dominant lesion has become hypodense, indicating an inactive metastasis.</p>
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19 pages, 11956 KiB  
Article
Synthesis of New Pyrazolo[3,4-d]pyrimidine Derivatives: NMR Spectroscopic Characterization, X-Ray, Hirshfeld Surface Analysis, DFT, Molecular Docking, and Antiproliferative Activity Investigations
by Mohamed El Hafi, El Hassane Anouar, Sanae Lahmidi, Mohammed Boulhaoua, Mohammed Loubidi, Ashwag S. Alanazi, Insaf Filali, Mohamed Hefnawy, Lhoussaine El Ghayati, Joel T. Mague and El Mokhtar Essassi
Molecules 2024, 29(21), 5020; https://doi.org/10.3390/molecules29215020 - 24 Oct 2024
Viewed by 3008
Abstract
Four new pyrazolo[3,4-d]pyrimidines (P1P4) were successfully synthesized in good relative yields by reacting 3-methyl-1-phenyl-1H-pyrazolo[3,4-d]pyrimidin-4-ol with various alkylating agents (methyl iodide, propargyl bromide, and phenacyl bromide) at room temperature in DMF solvent, employing liquid–solid phase transfer [...] Read more.
Four new pyrazolo[3,4-d]pyrimidines (P1P4) were successfully synthesized in good relative yields by reacting 3-methyl-1-phenyl-1H-pyrazolo[3,4-d]pyrimidin-4-ol with various alkylating agents (methyl iodide, propargyl bromide, and phenacyl bromide) at room temperature in DMF solvent, employing liquid–solid phase transfer catalysis. The P1P4 structures were elucidated using NMR spectroscopy and X-ray diffraction. Intermolecular interactions in P1P4 were analyzed via Hirshfeld surface analysis and 2D fingerprint plots. Geometrical parameters were accurately modeled by DFT calculations using the B3LYP hybrid functional combined with a 6–311++G(d,p) basis set. The antiproliferative activity of P1P4 towards colorectal carcinoma (HCT 116), human hepatocellular carcinoma (HepG2), and human breast cancer (MCF-7) cell lines, along with one normal cell line (WI38) was investigated using the MTT assay and sunitinib as a reference. Compounds P1 and P2 exhibited antiproliferative activities comparable to the reference drug towards all tested cells, with an IC50 range of 22.7–40.75 µM. Both compounds also showed high selectivity indices and minimal cytotoxic effects on the normal cell line. Molecular docking revealed that the significant antiproliferative activity may attributed to the number and type of intermolecular hydrogen bonding established between pyrazolo[3,4-d]pyrimidines and DNA topoisomerase, a common target for various anticancer agents. Full article
(This article belongs to the Section Organic Chemistry)
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<p>Chemical structures of reported pyrazolo[3,4-<span class="html-italic">d</span>]pyrimidine derivatives.</p>
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<p>2D structures (<b>left</b>) and perspective views of <b>P1</b>–<b>P4</b> (<b>right</b>). The dashed line in <b>P3</b> represents the intramolecular hydrogen bond.</p>
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<p>A portion of one layer in <b>P1</b> projected onto <math display="inline"><semantics> <mrow> <mfenced separators="|"> <mrow> <mn>10</mn> <mover accent="true"> <mrow> <mn>3</mn> </mrow> <mo>¯</mo> </mover> </mrow> </mfenced> <mo>,</mo> </mrow> </semantics></math> with the b-axis horizontal and running from left to right. N—H···O hydrogen bonds and C—H···π(ring) interactions are depicted, respectively, by violet and green dashed lines. Non-interacting hydrogen atoms are omitted for clarity.</p>
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<p>Elevation view of the packing in <b>P2</b> seen parallel to (<math display="inline"><semantics> <mrow> <mn>10</mn> <mover accent="true"> <mrow> <mn>1</mn> </mrow> <mo>¯</mo> </mover> </mrow> </semantics></math>) with C—H···N hydrogen bonds and C—H···π(ring) interactions depicted, respectively, by light blue and green dashed lines.</p>
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<p>A portion of two chains in <b>P3</b> viewed along the <span class="html-italic">a</span>-axis direction with C—H···O and C—H···N hydrogen bonds depicted, respectively, by black and light blue dashed lines. The π-stacking interactions are depicted by orange dashed lines.</p>
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<p>A portion of one chain of <b>P4</b> view along the <span class="html-italic">b</span>-axis. Dashed lines C—H···O represent hydrogen intermolecular bonding.</p>
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<p>The optimized geometries of <b>P1</b>–<b>P4</b> (<b>left</b>) and their superposition with X-ray-generated ones (<b>right</b>, the green color corresponds to the optimized geometry, and the red color corresponds to the X-ray-generated structure).</p>
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<p>The d<sub>norm</sub> surfaces for viewing hydrogen bonding interactions in <b>P1</b>–<b>P4</b> crystals.</p>
Full article ">Figure 8 Cont.
<p>The d<sub>norm</sub> surfaces for viewing hydrogen bonding interactions in <b>P1</b>–<b>P4</b> crystals.</p>
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<p>2D fingerprints of the highest intercontacts in <b>P1</b>–<b>P4</b>.</p>
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<p>2D fingerprints of the highest intercontacts in <b>P1</b>–<b>P4</b>.</p>
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<p>Bar representation of the in vitro antiproliferative activity of <b>P1</b>–<b>P4</b> and sunitinib against HCT 116, HepG2, and MCF-7 cancer cell lines, and one normal cell line WI38.</p>
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<p>2D binding affinities of <b>P1</b>–<b>P4</b> into the DNA topoisomerase binding site.</p>
Full article ">Figure 11 Cont.
<p>2D binding affinities of <b>P1</b>–<b>P4</b> into the DNA topoisomerase binding site.</p>
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<p>3D binding affinities of <b>P1</b>–<b>P4</b> into the DNA topoisomerase binding site.</p>
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<p>Synthesis path of <b>P1</b>–<b>P4</b>.</p>
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<p>Tautomerism of compound <b>P1</b>.</p>
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11 pages, 574 KiB  
Review
Gastroenteropancreatic Neuroendocrine Tumor with Peritoneal Metastasis: A Review of Current Management
by Corey A. Hounschell, Simon Higginbotham, Mazin Al-Kasspooles and Luke V. Selby
Cancers 2024, 16(20), 3472; https://doi.org/10.3390/cancers16203472 - 14 Oct 2024
Viewed by 951
Abstract
Peritoneal metastasis in gastroenteropancreatic neuroendocrine tumors poses a significant clinical challenge, with limited data guiding management strategies. We review the existing literature on surgical and systemic treatment modalities for peritoneal metastasis from gastroenteropancreatic neuroendocrine tumors. Surgical interventions, including cytoreductive surgery, have shown promise [...] Read more.
Peritoneal metastasis in gastroenteropancreatic neuroendocrine tumors poses a significant clinical challenge, with limited data guiding management strategies. We review the existing literature on surgical and systemic treatment modalities for peritoneal metastasis from gastroenteropancreatic neuroendocrine tumors. Surgical interventions, including cytoreductive surgery, have shown promise in improving symptom control and overall survival—particularly in cases in which 70% cytoreduction can be achieved. Hyperthermic intraperitoneal chemotherapy remains controversial due to a paucity of high-level evidence and a lack of consensus for routine use. The use of systemic therapy in the setting of peritoneal metastasis from gastroenteropancreatic neuroendocrine tumors is extrapolated from high-quality evidence for its use in the setting of the solid organ metastasis of this disease. The use of somatostatin analogs for symptom control and some antiproliferative effects is supported by large clinical trials. Additional strong evidence exists for the use of interferon-alpha, everolimus, and sunitinib, particularly in pancreatic neuroendocrine tumors. Cytotoxic chemotherapy and peptide receptor radionuclide therapy may be used in select cases, though as an emerging treatment modality, the optimal sequence of peptide receptor radionuclide therapy within the existing algorithms is unknown. Significant gaps in understanding and standardized management exist, particularly for those patients presenting with peritoneal metastasis, and targeted research to optimize outcomes in this population is needed. Full article
(This article belongs to the Special Issue Neuroendocrine Tumors: From Diagnosis to Therapy)
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<p>Treatment algorithm for gastroenteropancreatic neuroendocrine tumors with peritoneal metastasis proposed by the Chicago Consensus Working Group for Peritoneal Surface Malignancies [<a href="#B22-cancers-16-03472" class="html-bibr">22</a>].</p>
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7 pages, 2099 KiB  
Case Report
Synchronous Seminoma of Testis and Renal Cell Carcinoma: A Rare Case Report
by Stasys Auskalnis, Rasa Janciauskiene, Urte Rimsaite, Aurelija Alksnyte and Rasa Ugenskiene
Medicina 2024, 60(9), 1553; https://doi.org/10.3390/medicina60091553 - 23 Sep 2024
Cited by 1 | Viewed by 1133 | Correction
Abstract
Background and Objectives: Seminoma is the most common solid malignant tumour in young men. Clear-cell kidney carcinoma is the most common malignancy of the genitourinary tract. However, the synchronous occurrence of both of these tumours is rare. Case presentation: We present the [...] Read more.
Background and Objectives: Seminoma is the most common solid malignant tumour in young men. Clear-cell kidney carcinoma is the most common malignancy of the genitourinary tract. However, the synchronous occurrence of both of these tumours is rare. Case presentation: We present the case of a 36-year-old patient who presented to a medical facility at the end of 2019 with an enlarged right testicle. A unilateral orchofuniculectomy was performed, and a mass measuring 30 cm was removed. During histological examination, testicular seminoma pT2, R0, was diagnosed. An abdominal computed tomography (CT) scan showed a 6.4 cm × 6.8 cm × 6.7 cm tumour in the right kidney and a metastatic-like lesion in the right adrenal gland. A right nephrectomy and an adrenalectomy and paraaortic and paracaval lymphadenectomies were performed. A histological evaluation confirmed the presence of clear-cell renal carcinoma pT2aR0 G2, adrenal hyperplasia, and seminoma metastases in the removed lymph node. Chemotherapy with a Bleomycin, Etoposide, and Cisplatin (BEP) regimen was carried out. Three years after the last cycle of chemotherapy, a follow-up CT scan showed metastases in the left kidney, the right ischium, and the right lung. A well-differentiated clear-cell carcinoma G1 of the left kidney and metastasis of clear-cell carcinoma G2 in the right ischium were confirmed after the biopsy, and no tumour lesions were found in the lung tissue specimen. Treatment with targeted therapy with Sunitinib was started because the risk was favourable according to the Heng criteria. Genetic testing was performed, and the following genes were analysed: VHL, BAP1, CHEK2, FH, MET, MUTYH, APC, and STK11. The testing did not reveal any pathogenic or potentially pathogenic mutations or sequence changes of unknown clinical significance in the genes analysed. Conclusions: According to the authors, the occurrence of synchronous primary tumours is linked to one’s genetic predisposition. DNA sequencing of tumour tissue could provide more information on the corresponding aetiopathogenesis. Full article
(This article belongs to the Section Oncology)
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<p>CT image. Pathological paraaortic and paracaval lymph nodes.</p>
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<p>CT image. Tumour mass in the inferior part of the right kidney.</p>
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<p>CT image. Post-right-nephrectomy view. Cyst in the left kidney is shown.</p>
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<p>CT image. Metastatic lesions in the left kidney.</p>
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<p>CT image. Osteoclastic-type metastatic tumour in the pelvic bones.</p>
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<p>CT image. Pathological lymph node with central necrosis in the hilum of the right lung.</p>
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4 pages, 182 KiB  
Commentary
Sunitinib in Patients with Metastatic Renal Cell Carcinoma with Favorable Risk: Be Aware of PD-L1 Expression
by Ilya Tsimafeyeu
Med. Sci. 2024, 12(3), 48; https://doi.org/10.3390/medsci12030048 - 13 Sep 2024
Cited by 1 | Viewed by 8681
Abstract
The treatment landscape for metastatic renal cell carcinoma (RCC) has advanced significantly with first-line immunotargeted therapy combinations. However, no statistically significant differences were observed in the cohort of patients with favorable risk and some oncologists continue to use sunitinib in these patients. PD-L1 [...] Read more.
The treatment landscape for metastatic renal cell carcinoma (RCC) has advanced significantly with first-line immunotargeted therapy combinations. However, no statistically significant differences were observed in the cohort of patients with favorable risk and some oncologists continue to use sunitinib in these patients. PD-L1 expression has emerged as a negative prognostic factor in RCC, particularly in sunitinib-treated patients, where higher PD-L1 levels are linked to worse outcomes. This article discusses the potential risks associated with the use of sunitinib in PD-L1-positive patients. Full article
(This article belongs to the Special Issue Molecular and Clinical Advances in Kidney Cancer)
23 pages, 5206 KiB  
Article
Fibroblast Growth Factor 2 (FGF2) Activates Vascular Endothelial Growth Factor (VEGF) Signaling in Gastrointestinal Stromal Tumors (GIST): An Autocrine Mechanism Contributing to Imatinib Mesylate (IM) Resistance
by Sergei Boichuk, Pavel Dunaev, Aigul Galembikova and Elena Valeeva
Cancers 2024, 16(17), 3103; https://doi.org/10.3390/cancers16173103 - 7 Sep 2024
Cited by 2 | Viewed by 1279
Abstract
We showed previously that the autocrine activation of the FGFR-mediated pathway in GIST lacking secondary KIT mutations was a result of the inhibition of KIT signaling. We show here that the FGF2/FGFR pathway regulates VEGF-A/VEGFR signaling in IM-resistant GIST cells. Indeed, recombinant FGF2 [...] Read more.
We showed previously that the autocrine activation of the FGFR-mediated pathway in GIST lacking secondary KIT mutations was a result of the inhibition of KIT signaling. We show here that the FGF2/FGFR pathway regulates VEGF-A/VEGFR signaling in IM-resistant GIST cells. Indeed, recombinant FGF2 increased the production of VEGF-A by IM-naive and resistant GIST cells. VEGF-A production was also increased in KIT-inhibited GIST, whereas the neutralization of FGF2 by anti-FGF2 mAb attenuated VEGFR signaling. Of note, BGJ 398, pan FGFR inhibitor, effectively and time-dependently inhibited VEGFR signaling in IM-resistant GIST T-1R cells, thereby revealing the regulatory role of the FGFR pathway in VEGFR signaling for this particular GIST cell line. This also resulted in significant synergy between BGJ 398 and VEGFR inhibitors (i.e., sunitinib and regorafenib) by enhancing their pro-apoptotic and anti-proliferative activities. The high potency of the combined use of VEGFR and FGFR inhibitors in IM-resistant GISTs was revealed by the impressive synergy scores observed for regorafenib or sunitinib and BGJ 398. Moreover, FGFR1/2 and VEGFR1/2 were co-localized in IM-resistant GIST T-1R cells, and the direct interaction between the aforementioned RTKs was confirmed by co-immunoprecipitation. In contrast, IM-resistant GIST 430 cells expressed lower basal levels of FGF2 and VEGF-A. Despite the increased expression VEGFR1 and FGFR1/2 in GIST 430 cells, these RTKs were not co-localized and co-immunoprecipitated. Moreover, no synergy between FGFR and VEGFR inhibitors was observed for the IM-resistant GIST 430 cell line. Collectively, the dual targeting of FGFR and VEGFR pathways in IM-resistant GISTs is not limited to the synergistic anti-angiogenic treatment effects. The dual inhibition of FGFR and VEGFR pathways in IM-resistant GISTs potentiates the proapoptotic and anti-proliferative activities of the corresponding RTKi. Mechanistically, the FGF2-induced activation of the FGFR pathway turns on VEGFR signaling via the overproduction of VEGF-A, induces the interaction between FGFR1/2 and VEGFR1, and thereby renders cancer cells highly sensitive to the dual inhibition of the aforementioned RTKs. Thus, our data uncovers the novel mechanism of the cross-talk between the aforementioned RTKs in IM-resistant GISTs lacking secondary KIT mutations and suggests that the dual blockade of FGFR and VEGFR signaling might be an effective treatment strategy for patients with GIST-acquired IM resistance via KIT-independent mechanisms. Full article
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<p>FGFR, VEGFR, and KIT signaling pathways in IM-naive (GIST T-1) and IM-resistant (GIST T-1R, GIST 430) cells. (<b>A</b>) Expression of FGF/FGFR signaling proteins in GIST cells; (<b>B</b>) expression of the VEGF/FGFR signaling proteins in GIST cells; (<b>C</b>) changes in the relative expression level of VEGF-A and VEGFR1, 2, and 3 in GIST T-1 vs. T-1R and GIST 430 cells, as determined by quantitative RT-PCR. For internal control, the amplification of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used; data are presented as median ± SD. Significant differences with <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**) from <span class="html-italic">n</span> ≥ 3 using unpaired Student’s <span class="html-italic">t</span>-test. (<b>D</b>) Expression of the KIT signaling proteins in GIST cells. Actin stain was used as a loading control for all experiments shown in (<b>A</b>,<b>B</b>,<b>D</b>). (<b>E</b>) Concentration of VEGF-A (pg/mL) in supernatants of IM-naive (GIST T-1) and resistant (GIST T-1R and 430) cells measured by ELISA, as described in <a href="#sec4-cancers-16-03103" class="html-sec">Section 4</a>. Data are presented as median ± SD. Significant differences with <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**) from <span class="html-italic">n</span> ≥ 3 using unpaired Student’s <span class="html-italic">t</span>-test. The original Western blot figures can be found in <a href="#app1-cancers-16-03103" class="html-app">Supplementary File S1</a>.</p>
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<p>(<b>A</b>,<b>B</b>) The exogenous FGF2 activates VEGFR signaling in GIST T-1 cells via up-regulation of VEGF-A. (<b>A</b>) FGF-2 stimulates, whereas anti-FGF2 neutralizing Abs abrogates VEGFR signaling GIST T-1 cells. Cells were treated with FGF2 (100 ng/mL), IM (0.02 µM) alone or in the presence of anti-FGF2 neutralizing Abs (20 µg/mL) for 72 h. Expression of VEGF-A, total and phosphorylated forms of VEGFR, KIT, MAPK, AKT, and STAT1 was assessed by immunoblot analysis. Actin stain was used as a loading control for each sample. (<b>B</b>) Concentration of VEGF-A (pg/mL, measured by ELISA) in supernatants of IM-naive (GIST T-1) cells treated with DMSO (control), FGF-2 (100 ng/mL), IM (0.02 µM) alone or in the presence of anti-FGF-2 Abs (20 µg/mL) for 72 h. Data are presented as median ± SD. Significant differences with <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**) from <span class="html-italic">n</span> ≥ 3 using unpaired Student’s <span class="html-italic">t</span>-test. (<b>C</b>) Changes in the relative expression level of mRNA VEGF-A and VEGFR1, 2, and 3 in GIST T-1 after treatment with FGF-2 (100 ng/mL), as determined by quantitative RT-PCR. The amplification of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used for internal control. Data are presented as median ± SD. Significant differences with <span class="html-italic">p</span> &lt; 0.05 (*) from <span class="html-italic">n</span> ≥ 3 using unpaired Student’s <span class="html-italic">t</span>-test. The original Western blot figures can be found in <a href="#app1-cancers-16-03103" class="html-app">Supplementary File S1</a>.</p>
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<p>Inhibition of FGFR signaling attenuates activation of FGFR and VEGFR pathways in GIST T-1R cells. GIST T-1R cells were treated with BGJ 398 (2 µM) or regorafenib (REGO) (1 µM) for 24 h and subjected for WB analysis to examine expression of total and phosphorylated forms of VEGFR, FGFR, and FRS-2. Actin staining was used to show the comparable amounts of protein loaded into each sample. The original Western blot figures can be found in <a href="#app1-cancers-16-03103" class="html-app">Supplementary File S1</a>.</p>
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<p>(<b>A</b>–<b>D</b>). Crosstalk between FGFR1/2 and VEGFR1/2 in IM-resistant GISTs. GIST T-1 R (<b>A</b>) and GIST 430 (<b>B</b>) were subjected to the double immunofluorescence staining for FGFR1 or 2 and VEGFR1 or 2. To outline the nucleus, the images were also merged with DAPI staining. (<b>C</b>) Percentages of cells with co-localized RTKs from three independent experiments. * <span class="html-italic">p</span> &lt; 0.05; (<b>D</b>) co-immunoprecipitation of FGFR1 or 2 with VEGFR1 in IM-resistant GISTs. FGFR1 or -2 expression in GIST cell lysates immunoprecipitated by anti-VGFR1 Abs to demonstrate endogenous complex formation. The original Western blot figures can be found in <a href="#app1-cancers-16-03103" class="html-app">Supplementary File S1</a>.</p>
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<p>(<b>A</b>,<b>B</b>) Pro-apoptotic and anti-proliferative activities of sunitinib (SU) (<b>A</b>) or regorafenib (REGO) (<b>B</b>) used alone or in combination with BGJ 398 in GIST T-1R cells. Cells were treated for 72 h and subjected to WB analysis to examine expression of apoptotic markers—cleaved forms of PARP and caspase-3 and downstream signaling molecules of FGFR and VEGFR pathways: total and phosphorylated forms of AKT, MAPK, and STAT-1. Actin staining was used to show the comparable amounts of protein loaded into each sample. The original Western blot figures can be found in <a href="#app1-cancers-16-03103" class="html-app">Supplementary File S1</a>.</p>
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<p>(<b>A</b>–<b>D</b>) Anti-proliferative activity BGJ 398 used in combination with sunitinib (SU) or regorafenib (REGO) in GIST-T1R cells. Cells were treated with RTKis (BGJ398 1 µM, SU 0.5µM, REGO 0.5µM) for 72 h (<b>A</b>) Changes in growth kinetics of GIST-T1R cells treated with DMSO (control), SU or BGJ 398 alone and in combination; (<b>B</b>) changes in growth kinetics of GIST-T1R cells treated with DMSO (control), REGO, or BGJ 398 alone and in combination; (<b>C</b>) (<b>Upper</b>) panel—representative images of crystal violet staining of GIST-T1R cells treated with SU or BGJ 398 alone or in combination. (<b>Lower</b>) panel—quantification of crystal violet staining of GIST cells, as shown in the upper panel. *: <span class="html-italic">p</span> ≤ 0.001; (<b>D</b>) (<b>Upper</b>) panel—representative images of crystal violet staining of GIST-T1R cells treated with REGO or BGJ 398 alone or in combination. (<b>Lower</b>) panel—quantification of crystal violet staining of GIST cells, as shown in the upper panel. *: <span class="html-italic">p</span> ≤ 0.001. The culture dishes for (<b>C</b>) and (<b>D</b>) were stained with crystal violet and photographed. The cells treated with DMSO were used as a control. Quantification of crystal violet staining of GIST cells is described in <a href="#sec4-cancers-16-03103" class="html-sec">Section 4</a>.</p>
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<p>Assessment of the synergy between BGJ 398 and sunitinib (SU) (<b>A</b>) or regorafenib (REGO) (<b>B</b>) observed for IM-resistant GIST T-1R cells (ZIP model).</p>
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<p>Inhibition of KIT signaling activates FGFR and VEGFR signaling via overproduction of FGF-2 and VEGF-A in IM-resistant GIST-T1 cells.</p>
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11 pages, 2765 KiB  
Article
Development of Simultaneous Drug Concentration Measurement Method Using an Automated Pretreatment Liquid Chromatography/Tandem Mass Spectrometry System for Therapeutic Drug Monitoring
by Yu Sato, Hiroki Kondo, Yuji Sato, Ai Abe, Masafumi Kikuchi, Toshihiro Sato, Masaki Kumondai, Kohei Yoshikawa, Yoshihiro Hayakawa, Masamitsu Maekawa and Nariyasu Mano
Pharmaceutics 2024, 16(9), 1138; https://doi.org/10.3390/pharmaceutics16091138 - 28 Aug 2024
Viewed by 1455
Abstract
Therapeutic drug monitoring (TDM) is a personalized treatment approach that involves optimizing drug dosages based on patient-specific factors, such as drug plasma concentrations, therapeutic efficacy, or adverse reactions. The plasma concentration of drugs is determined using liquid chromatography/tandem mass spectrometry (LC-MS/MS) or various [...] Read more.
Therapeutic drug monitoring (TDM) is a personalized treatment approach that involves optimizing drug dosages based on patient-specific factors, such as drug plasma concentrations, therapeutic efficacy, or adverse reactions. The plasma concentration of drugs is determined using liquid chromatography/tandem mass spectrometry (LC-MS/MS) or various immunoassays. Compared with immunoassays, LC-MS/MS requires more pretreatment time as the number of samples increases. Recently, fully automated pretreatment LC-MS/MS systems have been developed to automatically perform whole-sample pretreatment for LC-MS/MS analysis. In this study, we developed a method for simultaneous concentration determination of five analytes (clozapine, mycophenolic acid, sunitinib, N-desethylsunitinib, and voriconazole) using LC-MS/MS for clinical TDM using a fully automated LC-MS/MS pretreatment system. In the developed method, the intra- and inter-assay relative error (RE) values ranged between −14.8% and 11.3%; the intra- and inter-assay coefficient of variation (CV) values were <8.8% and <10.5%, respectively. The analytes showed good stability, with RE values ranging between −13.6% and 10.9% and CV values <8.9%. Furthermore, the plasma concentrations in clinical samples using this method and the conventional manual pretreatment method showed similar results. Therefore, the method developed in this study could be considered a useful pretreatment method for routine TDM in patients. Full article
(This article belongs to the Section Clinical Pharmaceutics)
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<p>Chemical structures of clozapine, clozapine-d8, mycophenolic acid, mycophenolic acid-d3, sunitinib, sunitinib-d10, <span class="html-italic">N</span>-desethylsunitinib, voriconazole, and voriconazole-d3.</p>
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<p>Sample pretreatment process for the CLAM method (<b>A</b>) and manual pretreatment methods (<b>B</b>). Squares represent the steps automatically processed using CLAM-2030.</p>
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<p>LC-MS/MS chromatograms of the MQC sample for (<b>A</b>) clozapine, (<b>B</b>) clozapine-d8, (<b>C</b>) <span class="html-italic">N</span>-desethylsunitinib, (<b>D</b>) sunitinib, (<b>E</b>) sunitinib-d10, (<b>F</b>) voriconazole, (<b>G</b>) voriconazole-d3, (<b>H</b>) mycophenolic acid, and (<b>I</b>) mycophenolic acid-d3.</p>
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<p>LC-MS/MS chromatograms of LLOQ sample for (<b>A</b>) clozapine, (<b>B</b>) mycophenolic acid, (<b>C</b>) sunitinib, (<b>D</b>) <span class="html-italic">N</span>-desethylsunitinib, and (<b>E</b>) voriconazole.</p>
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<p>Passing–Bablok regression analysis of the CLAM and manual pretreatment methods for (<b>A</b>) clozapine, (<b>B</b>) mycophenolic acid, (<b>C</b>) sunitinib, (<b>D</b>) <span class="html-italic">N</span>-desethylsunitinib, and (<b>E</b>) voriconazole. The thick solid line indicates the estimated regression equation, the dashed lines indicate the upper and lower limits of the 95% confidence interval, and the dotted line indicates the identity line (<span class="html-italic">x</span> = <span class="html-italic">y</span>).</p>
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<p>Bland–Altman plots for (<b>A</b>) clozapine, (<b>B</b>) mycophenolic acid, (<b>C</b>) sunitinib, (<b>D</b>) <span class="html-italic">N</span>-desethylsunitinib, and (<b>E</b>) voriconazole. The relative difference is calculated using the following equation: (CLAM method − manual pretreatment method)/mean of both methods × 100. The solid line indicates the mean relative difference between the two assays, whereas the dashed line indicates the upper and lower limits of agreement calculated as the mean relative difference ± 1.96 standard deviations.</p>
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13 pages, 18480 KiB  
Article
Predicting Survival of Metastatic Clear Cell Renal Cell Cancer Treated with VEGFR-TKI-Based Sequential Therapy
by Javier C. Angulo, Gorka Larrinaga, David Lecumberri, Ane Miren Iturregui, Jon Danel Solano-Iturri, Charles H. Lawrie, María Armesto, Juan F. Dorado, Caroline E. Nunes-Xavier, Rafael Pulido, Claudia Manini and José I. López
Cancers 2024, 16(16), 2786; https://doi.org/10.3390/cancers16162786 - 7 Aug 2024
Viewed by 1018
Abstract
(1) Objective: To develop a clinically useful nomogram that may provide a more individualized and accurate estimation of cancer-specific survival (CSS) for patients with clear-cell (CC) metastatic renal cell carcinoma (mRCC) treated with nephrectomy and vascular endothelial growth factor receptor–tyrosine kinase inhibitor (VEGFR-TKI)-based [...] Read more.
(1) Objective: To develop a clinically useful nomogram that may provide a more individualized and accurate estimation of cancer-specific survival (CSS) for patients with clear-cell (CC) metastatic renal cell carcinoma (mRCC) treated with nephrectomy and vascular endothelial growth factor receptor–tyrosine kinase inhibitor (VEGFR-TKI)-based sequential therapy. (2) Methods: A prospectively maintained database of 145 patients with mRCC treated between 2008 and 2018 was analyzed to predict the CSS of patients receiving sunitinib and second- and third-line therapies according to current standards of practice. A nomogram based on four independent clinical predictors (Eastern Cooperative Oncology Group status, International Metastatic RCC Database Consortium score, the Morphology, Attenuation, Size and Structure criteria and Response Evaluation Criteria in Solid Tumors response criteria) was calculated. The corresponding 1- to 10-year CSS probabilities were then determined from the nomogram. (3) Results: The median age was 60 years (95% CI 57.9–61.4). The disease was metastatic at diagnosis in 59 (40.7%), and 86 (59.3%) developed metastasis during follow-up. Patients were followed for a median 48 (IQR 72; 95% CI 56–75.7) months after first-line VEGFR-TKI initiation. The concordance probability estimator value for the nomogram is 0.778 ± 0.02 (mean ± SE). (4) Conclusions: A nomogram to predict CSS in patients with CC mRCC that incorporates patient status, clinical risk classification and response criteria to first-line VEGFR-TKI at 3 months is presented. This new tool may be useful to clinicians assessing the risk and prognosis of patients with mRCC. Full article
(This article belongs to the Special Issue New Insights into Kidney Disease Development and Therapy Strategies)
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<p>(<b>a</b>) Overall survival and (<b>b</b>) cancer-specific survival with VEGFR-TKI sequential therapy.</p>
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<p>CSS according to variables predictive in univariate analysis: (<b>a</b>) ECOG status; (<b>b</b>) metastases at diagnosis; (<b>c</b>) NCCN stage at diagnosis; (<b>d</b>) IMDC risk score at initiation of treatment; (<b>e</b>) MASS response criteria; (<b>f</b>) RECIST response criteria.</p>
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<p>Nomogram predicting the probability of CSS at different times (1 to 10 years), calculated by obtaining the value for each parameter by drawing a straight line to the point axis, adding the points together, and filling the sum-of-total-points axis (* Response Criteria).</p>
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<p>Area under the curve for the Cox predictive model with 95% CI during follow-up.</p>
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19 pages, 779 KiB  
Review
Axitinib after Treatment Failure with Sunitinib or Cytokines in Advanced Renal Cell Carcinoma—Systematic Literature Review of Clinical and Real-World Evidence
by Anand Sharma, Amit Bahl, Ricky Frazer, Esha Godhania, Nicholas Halfpenny, Kristina Hartl, Dorothea Heldt, John McGrane, Sera Şahbaz Gülser, Balaji Venugopal, Aimi Ritchie and Katherine Crichton
Cancers 2024, 16(15), 2706; https://doi.org/10.3390/cancers16152706 - 30 Jul 2024
Viewed by 1285
Abstract
Background: We conducted a systematic literature review (SLR) to identify clinical evidence on treatments in advanced renal cell carcinoma (aRCC) after the failure of prior therapy with cytokines, tyrosine kinase inhibitors, or immune checkpoint inhibitors. Herein, we summarise the evidence for axitinib in [...] Read more.
Background: We conducted a systematic literature review (SLR) to identify clinical evidence on treatments in advanced renal cell carcinoma (aRCC) after the failure of prior therapy with cytokines, tyrosine kinase inhibitors, or immune checkpoint inhibitors. Herein, we summarise the evidence for axitinib in aRCC after the failure of prior therapy with cytokines or sunitinib. Methods: This SLR was registered with PROSPERO (CRD42023492931) and followed the 2020 PRISMA statement and the Cochrane guidelines. Comprehensive searches were conducted in MEDLINE and Embase as well as for conference proceedings. Study eligibility was defined according to population, intervention, comparator, outcome, and study design. Results: Of 1252 titles/abstracts screened, 266 peer-reviewed publications were reviewed, of which 182 were included. In addition, 28 conference abstracts were eligible. Data on axitinib were reported in 55 publications, of which 16 provided efficacy and/or safety outcomes on axitinib after therapy with sunitinib or cytokines. In these patients, median progression-free and overall survival ranged between 5.5 and 8.7 months and 11.0 and 69.5 months, respectively. Conclusions: Axitinib is commonly used in clinical practice and has a well-characterised safety and efficacy profile in the treatment of patients with aRCC after the failure of prior therapy with sunitinib or cytokines. Full article
(This article belongs to the Section Systematic Review or Meta-Analysis in Cancer Research)
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<p>PRISMA flow diagram. <sup>α</sup> Conferences covered in Embase database search (2021–2023): American Society of Clinical Oncology, ASCO Genitourinary, American Urological Association, European Association of Urology, European Society for Medical Oncology, International Kidney Cancer Symposium, European International Kidney Cancer Symposium, Society of Immunotherapy of Cancer.</p>
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22 pages, 7688 KiB  
Article
IDO1 Inhibitor RY103 Suppresses Trp-GCN2-Mediated Angiogenesis and Counters Immunosuppression in Glioblastoma
by Zikang Xing, Xuewen Li, Zhen Ning Tony He, Xin Fang, Heng Liang, Chunxiang Kuang, Aiying Li and Qing Yang
Pharmaceutics 2024, 16(7), 870; https://doi.org/10.3390/pharmaceutics16070870 - 28 Jun 2024
Viewed by 1373
Abstract
Glioma is characterized by strong immunosuppression and excessive angiogenesis. Based on existing reports, it can be speculated that the resistance to anti-angiogenic drug vascular endothelial growth factor A (VEGFA) antibody correlates to the induction of novel immune checkpoint indoleamine 2,3-dioxygenase 1 (IDO1), while [...] Read more.
Glioma is characterized by strong immunosuppression and excessive angiogenesis. Based on existing reports, it can be speculated that the resistance to anti-angiogenic drug vascular endothelial growth factor A (VEGFA) antibody correlates to the induction of novel immune checkpoint indoleamine 2,3-dioxygenase 1 (IDO1), while IDO1 has also been suggested to be related to tumor angiogenesis. Herein, we aim to clarify the potential role of IDO1 in glioma angiogenesis and the mechanism behind it. Bioinformatic analyses showed that the expressions of IDO1 and angiogenesis markers VEGFA and CD34 were positively correlated and increased with pathological grade in glioma. IDO1-overexpression-derived-tryptophan depletion activated the general control nonderepressible 2 (GCN2) pathway and upregulated VEGFA in glioma cells. The tube formation ability of angiogenesis model cells could be inhibited by IDO1 inhibitors and influenced by the activity and expression of IDO1 in condition medium. A significant increase in serum VEGFA concentration and tumor CD34 expression was observed in IDO1-overexpressing GL261 subcutaneous glioma-bearing mice. IDO1 inhibitor RY103 showed positive anti-tumor efficacy, including the anti-angiogenesis effect and upregulation of natural killer cells in GL261 glioma-bearing mice. As expected, the combination of RY103 and anti-angiogenesis agent sunitinib was proved to be a better therapeutic strategy than either monotherapy. Full article
(This article belongs to the Section Gene and Cell Therapy)
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<p>The expression of IDO1, VEGFA, and CD34 in glioma increased with pathological grade, and the expression of IDO1 was positively correlated with the expression of various angiogenic factors and pathological grade, while negatively correlated with the prognosis of glioma patients. Data of B and D are in log<sub>2</sub>(FPKM). (<b>A</b>) Expression of IDO1, VEGFA and CD34 in gliomas of different pathological grades. Positive cells are indicated by the arrow. The magnification of the image is 400×, and the length of the scale bar is 20 μm. Non-glioma n = 5, grade I/II n = 3, grade III/IV n = 10. (<b>B</b>) The mRNA expression of <span class="html-italic">IDO1</span>, <span class="html-italic">VEGFA</span>, <span class="html-italic">MMP2</span>, <span class="html-italic">MMP9</span> and <span class="html-italic">CD34</span> in glioma patients at different pathological grades. Data were obtained from the CGGA database, WHO II n = 188, WHO III n = 255, WHO IV n = 249. (<b>C</b>) Correlation between the expression of <span class="html-italic">IDO1, VEGFA</span>, <span class="html-italic">MMP2</span>, <span class="html-italic">MMP9</span>, <span class="html-italic">CD34</span> and the overall survival of glioma patients. Data were obtained from the CGGA database, Kaplan–Meier curves of overall survival of glioma patients were determined by log-rank test. n = 222 for <span class="html-italic">IDO1</span> and <span class="html-italic">CD34</span>. n = 404 for <span class="html-italic">VEGFA</span>, <span class="html-italic">MMP2</span>, <span class="html-italic">MMP9</span>. “High” represents the data with higher expression than the median of overall data and “low” with lower expression. (<b>D</b>) Correlation between mRNA expressions of IDO1 with <span class="html-italic">VEGFA</span>, <span class="html-italic">CD34</span>, <span class="html-italic">MMP2</span> and <span class="html-italic">MMP9</span> in glioma patients. Data were obtained from the CGGA database, n = 404.</p>
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<p>Trp deficiency caused by overexpression of IDO1-activated GCN2 pathway induced the expression of VEGFA. GL261 cells were transfected with IDO1 expressing plasmids and grown in regular medium for 24 h (<b>A</b>,<b>B</b>) or 72 h (<b>C</b>–<b>E</b>). Wild-type GL261 (<b>F</b>,<b>G</b>), U87 (<b>H</b>), U251 (<b>I</b>), A172 (<b>J</b>) cells were grown in Trp-deficient medium for 24 h. The levels of Trp and Kyn were detected by HPLC, and the Kyn/Trp ratio was calculated. Protein and mRNA expression levels were detected by WB and qPCR, respectively, with corresponding expression levels of β-actin serving as internal controls. n = 3/group. (<b>A</b>,<b>C</b>) Concentration of Trp and Kyn in culture medium. n = 3/group. (<b>B</b>,<b>D</b>) The mRNA expression levels of <span class="html-italic">IDO1</span>, <span class="html-italic">CHOP</span>, and <span class="html-italic">VEGFA</span>. n = 3/group. E. Protein expression levels of ATF4, IDO1, VEGFA and CHOP. n = 3/group. (<b>F</b>,<b>H</b>–<b>J</b>). The proliferation activity of cells detected by CCK-8, and the mRNA expression levels of <span class="html-italic">CHOP</span> and <span class="html-italic">VEGFA</span>. n = 3/group. (<b>G</b>) Protein expression levels of p-GCN2, GCN2, ATF4 and IDO1. n = 3/group.</p>
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<p>RY103 inhibited the tube-forming ability of hCMEC/D3 and HUVEC cells. The designation of the different treatments is described in the <a href="#sec2-pharmaceutics-16-00870" class="html-sec">Section 2</a>. Capillary-like structures were detected using a phase-contrast microscope, and the networks formed by hCMEC/D3 cells (<b>A</b>,<b>B</b>) or HUVEC cells (<b>C</b>) were quantified with ImageJ software (Version 1.53t). Magnification, 40 ×; scale bar, 200 µm. n = 3/group. (<b>A</b>,<b>C</b>) The effect of sunitinib, RY103 and 1-MT on the tube-forming ability of hCMEC/D3 (<b>A</b>) or HUVEC (<b>C</b>) cells. (<b>B</b>) The effect of IDO1 on the tube-forming ability of hCMEC/D3 cells.</p>
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<p>Overexpression of IDO1 promoted expression of angiogenic factors in the tumor of GL261 subcutaneous glioma-bearing mice. The construction of mouse models is described in the <a href="#sec2-pharmaceutics-16-00870" class="html-sec">Section 2</a>. Mice were sacrificed 14 days post-implantation. The tumors were excised, weighed and photographed. The blood was collected and used for the detection for Trp, Kyn and VEGFA levels. (<b>A</b>). Body weight change curve. n = 7/group. (<b>B</b>). Body weight before sacrifice. n = 7/group. (<b>C</b>) Spleen weight. n = 7/group. (<b>D</b>) Splenic index (spleen weight (mg)/body weight (g)). n = 7/group. (<b>E</b>). The tumor weight. n = 7/group. (<b>F</b>) The tumor volumes. n = 7/group. (<b>G</b>) Concentration of Trp and Kyn in serum was detected by HPLC. The Kyn/Trp ratio was also calculated. n = 7/group. (<b>H</b>) The concentration of VEGFA in serum was detected by ELISA. n = 7/group. (<b>I</b>) Protein expression levels of CD34, ATF4, IDO1 and VEGFA in tumors were detected by WB. β-actin was used as an internal control. n = 3/group.</p>
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<p>RY103 downregulated angiogenic factors in tumor of GL261 subcutaneous glioma-bearing mice. The construction of mouse models and the designation of the different treatments are described in the <a href="#sec2-pharmaceutics-16-00870" class="html-sec">Section 2</a>. (<b>A</b>) The tumor weight. n = 9/group. (<b>B</b>) The tumor volumes. n = 7/group. (<b>C</b>) The mRNA expression levels of <span class="html-italic">MMP2</span>, <span class="html-italic">MMP9</span>, <span class="html-italic">VEGFA</span>, <span class="html-italic">VEGFR2</span>, <span class="html-italic">CD105</span>, <span class="html-italic">CD31</span>, <span class="html-italic">CD34</span> and Factor VIII in tumors were detected by qPCR. β-actin was used as an internal control. n = 4/group. (<b>D</b>) Protein expression levels of CD34, ATF4, IDO1, and VEGFA expression in tumors were detected by WB. β-actin was used as an internal control. n = 3/group. (<b>E</b>) Body weight change curve. n = 9/group. (<b>F</b>) The expression of IDO1 and CD34 in paraffin sections of tumors was detected by immunohistochemistry. The cells positive for IDO1 or CD34 were indicated by the arrows. The magnification of the image is 200× and the length of the scale is 50 μm. (<b>G</b>) The expression of IDO1 and CD34 in tumors was detected by immunofluorescence. The magnification of the image is 400× and the length of the scale is 50 μm.</p>
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<p>RY103 inhibited tumor growth and decreased Treg proportion in spleens in GL261 orthotopic glioma-bearing mice. The construction of mouse models and the designation of the different treatments are described in the <a href="#sec2-pharmaceutics-16-00870" class="html-sec">Section 2</a>. (<b>A</b>,<b>B</b>). The tumor volumes. One day before the mice were sacrificed, the tumor volumes were assessed by MRI. n = 5/group. (<b>C</b>) Body weight before sacrifice. n = 5/group. (<b>D</b>) Spleen weight. n = 5/group. (<b>E</b>) Splenic index (spleen weight (mg)/body weight (g)). n = 5/group. (<b>F</b>,<b>G</b>). The proportion of Treg cells in the spleens (<b>F</b>) or brains (<b>G</b>) were detected by FCM. n = 5/group. (<b>H</b>) Concentrations of Trp and Kyn in serum were detected by HPLC, and the Kyn/Trp ratio was calculated. n = 5/group.</p>
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<p>The combination of RY103 and sunitinib exhibited stronger antitumor and anti-angiogenesis effects in GL261 subcutaneous glioma-bearing mice. The construction of mouse models and the designation of the different treatments are described in the <a href="#sec2-pharmaceutics-16-00870" class="html-sec">Section 2</a>. (<b>A</b>) The tumor volumes. n = 5/group. (<b>B</b>) The tumor weight. n = 5/group. (<b>C</b>) The concentration of VEGFA in serum was detected by ELISA. n = 5/group. (<b>D</b>) The proportion of NK cells in the spleens and tumors was detected by FCM. n = 5/group. (<b>E</b>) Concentrations of Trp and Kyn in serum were detected by HPLC, and the Kyn/Trp ratio was calculated. n = 5/group. (<b>F</b>) Protein expression levels of CD34, ATF4, IDO1 and VEGFA in tumor were detected by WB, β-actin was used as an internal control. n = 3/group.</p>
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15 pages, 8868 KiB  
Article
177Lu Anti-Angiogenic Radioimmunotherapy Targeting ATP Synthase in Gastric Cancer Model
by Bok-Nam Park, Young-Sil An, Su-Min Kim, Su-Jin Lee, Yong-Jin Park and Joon-Kee Yoon
Antibodies 2024, 13(3), 51; https://doi.org/10.3390/antib13030051 - 27 Jun 2024
Viewed by 1283
Abstract
This study investigated a novel radioimmunotherapy strategy for targeting tumor angiogenesis. We developed a radiopharmaceutical complex by labeling an anti-adenosine triphosphate synthase (ATPS) monoclonal antibody (mAb) with the radioisotope 177Lu using DOTA as a chelating agent. 177Lu-DOTA-ATPS mAb demonstrated high labeling [...] Read more.
This study investigated a novel radioimmunotherapy strategy for targeting tumor angiogenesis. We developed a radiopharmaceutical complex by labeling an anti-adenosine triphosphate synthase (ATPS) monoclonal antibody (mAb) with the radioisotope 177Lu using DOTA as a chelating agent. 177Lu-DOTA-ATPS mAb demonstrated high labeling efficiency (99.0%) and stability in serum. MKN-45 cancer cells exhibited the highest cellular uptake, which could be specifically blocked by unlabeled ATPS mAb. In mice, 177Lu-DOTA-ATPS mAb accumulated significantly in tumors, with a tumor uptake of 16.0 ± 1.5%ID/g on day 7. 177Lu-DOTA-ATPS mAb treatment significantly reduced the viability of MKN-45 cells in a dose-dependent manner. In a xenograft tumor model, this radioimmunotherapy strategy led to substantial tumor growth inhibition (82.8%). Furthermore, combining 177Lu-DOTA-ATPS mAb with sunitinib, an anti-angiogenic drug, enhanced the therapeutic efficacy of sunitinib in the mouse model. Our study successfully developed 177Lu-DOTA-ATPS mAb, a radioimmunotherapy agent targeting tumor blood vessels. This approach demonstrates significant promise for inhibiting tumor growth, both as a single therapy and in combination with other anti-cancer drugs. Full article
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<p>Schematic diagram for radiosynthesis of <sup>177</sup>Lu-DOTA-ATPS mAb.</p>
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<p>Labeling efficiency (<b>A</b>) and in vitro stability (<b>B</b>) of <sup>177</sup>Lu-DOTA-ATPS mAb. The Rf value of <sup>177</sup>Lu-DOTA-ATPS mAb was between 0.01 and 0.05, while that of <sup>177</sup>LuCl<sub>3</sub> was between 0.6 and 1.0. The in vitro stabilities of <sup>177</sup>Lu-DOTA-ATPS mAb in serum remained unchanged up to 7 days. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody; RT, room temperature; PBS, phosphate-buffered saline.</p>
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<p>The cellular uptake (<b>A</b>), specific binding (<b>B</b>), and inhibition study (<b>C</b>) of <sup>177</sup>Lu-DOTA-ATPS mAb. MKN-45 cells showed the highest cellular uptake of <sup>177</sup>Lu-DOTA-ATPS mAb among the tested cancer cell lines. <sup>177</sup>Lu-DOTA-ATPS mAb uptake was specific and inhibited by unlabeled ATPS mAb in MKN-45 cells. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.005 **, ns: not significant.</p>
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<p>Radioimmunotherapy with <sup>177</sup>Lu-DOTA-ATPS mAb alone (<b>A</b>) and <sup>177</sup>Lu-DOTA-ATPS mAb in combination with sunitinib (<b>B</b>) in MKN-45 cells. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.005 **, <span class="html-italic">p</span> &lt; 0.001 ***, <span class="html-italic">p</span> &lt; 0.0005 <sup>+</sup>, <span class="html-italic">p</span> &lt; 0.00005 <sup>++</sup>.</p>
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<p>Biodistribution of <sup>177</sup>Lu-DOTA-ATPS mAb (<b>A</b>), <sup>177</sup>LuCl<sub>3</sub> (<b>B</b>), and <sup>177</sup>Lu-DOTA-IgG (<b>C</b>) in wild-type mice on days 1, 2, 4, and 7. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody.</p>
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<p>Biodistribution of <sup>177</sup>Lu-DOTA-ATPS mAb (<b>A</b>), <sup>177</sup>LuCl<sub>3</sub> (<b>B</b>), and <sup>177</sup>Lu-DOTA-IgG (<b>C</b>) in mice bearing MKN-45 tumors on day 1, 2, 4, and 7. Comparison of bone marrow and tumor uptake among radiopharmaceuticals (<b>D</b>). Inhibition of <sup>177</sup>Lu-DOTA-ATPS mAb uptake in tumors by unlabeled ATPS mAb (<b>E</b>). DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.005 **, ns: not significant.</p>
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<p>Radioimmunotherapy with <sup>177</sup>Lu-DOTA-ATPS mAb. (<b>A</b>) Tumor growth curve during the 4-week treatment with <sup>177</sup>Lu-DOTA-ATPS mAb, unlabeled ATPS mAb, IgG, and vehicle. (<b>B</b>) Immunohistochemical staining with anti-CD31 antibody for MKN-45 tumors after 4 weeks of treatment. (<b>C</b>) <sup>18</sup>F-FDG PET imaging in mice bearing MKN-45 tumors at baseline and at 4th week of treatment. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.01 **, arrows indicate positive staining.</p>
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<p>Radioimmunotherapy with <sup>177</sup>Lu-DOTA-ATPS mAb. (<b>A</b>) Tumor growth curve during the 4-week treatment with <sup>177</sup>Lu-DOTA-ATPS mAb, unlabeled ATPS mAb, IgG, and vehicle. (<b>B</b>) Immunohistochemical staining with anti-CD31 antibody for MKN-45 tumors after 4 weeks of treatment. (<b>C</b>) <sup>18</sup>F-FDG PET imaging in mice bearing MKN-45 tumors at baseline and at 4th week of treatment. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody. <span class="html-italic">p</span> &lt; 0.05 *, <span class="html-italic">p</span> &lt; 0.01 **, arrows indicate positive staining.</p>
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<p>Combination chemo-radioimmunotherapy with sunitinib and <sup>177</sup>Lu-DOTA-ATPS mAb. (<b>A</b>) Tumor growth curve during the 4-week treatment with <sup>177</sup>Lu-DOTA-ATPS mAb, sunitinib, combination, and vehicle. (<b>B</b>) Immunohistochemical staining with anti-CD31 antibody for MKN-45 tumors after 4 weeks of treatment. (<b>C</b>) <sup>18</sup>F-FDG PET imaging in mice bearing MKN-45 tumors at baseline and 4th week of treatment. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody. <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; 0.005 ***, arrows indicate positive staining.</p>
Full article ">Figure 8 Cont.
<p>Combination chemo-radioimmunotherapy with sunitinib and <sup>177</sup>Lu-DOTA-ATPS mAb. (<b>A</b>) Tumor growth curve during the 4-week treatment with <sup>177</sup>Lu-DOTA-ATPS mAb, sunitinib, combination, and vehicle. (<b>B</b>) Immunohistochemical staining with anti-CD31 antibody for MKN-45 tumors after 4 weeks of treatment. (<b>C</b>) <sup>18</sup>F-FDG PET imaging in mice bearing MKN-45 tumors at baseline and 4th week of treatment. DOTA, tetraazacyclododecane-1,4,7,10-tetraacetic acid; ATPS, adenosine triphosphate synthase; mAb, monoclonal antibody. <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; 0.005 ***, arrows indicate positive staining.</p>
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23 pages, 6503 KiB  
Article
Identification of miRNAs and Their Target Genes Associated with Sunitinib Resistance in Clear Cell Renal Cell Carcinoma Patients
by María Armesto, Stéphane Nemours, María Arestín, Iraide Bernal, Jon Danel Solano-Iturri, Manuel Manrique, Laura Basterretxea, Gorka Larrinaga, Javier C. Angulo, David Lecumberri, Ane Miren Iturregui, José I. López and Charles H. Lawrie
Int. J. Mol. Sci. 2024, 25(13), 6881; https://doi.org/10.3390/ijms25136881 - 22 Jun 2024
Cited by 1 | Viewed by 1737
Abstract
Sunitinib has greatly improved the survival of clear cell renal cell carcinoma (ccRCC) patients in recent years. However, 20–30% of treated patients do not respond. To identify miRNAs and genes associated with a response, comparisons were made between biopsies from responder and non-responder [...] Read more.
Sunitinib has greatly improved the survival of clear cell renal cell carcinoma (ccRCC) patients in recent years. However, 20–30% of treated patients do not respond. To identify miRNAs and genes associated with a response, comparisons were made between biopsies from responder and non-responder ccRCC patients. Using integrated transcriptomic analyses, we identified 37 miRNAs and 60 respective target genes, which were significantly associated with the NF-kappa B, PI3K-Akt and MAPK pathways. We validated expression of the miRNAs (miR-223, miR-155, miR-200b, miR-130b) and target genes (FLT1, PRDM1 and SAV1) in 35 ccRCC patients. High levels of miR-223 and low levels of FLT1, SAV1 and PRDM1 were associated with worse overall survival (OS), and combined miR-223 + SAV1 levels distinguished responders from non-responders (AUC = 0.92). Using immunohistochemical staining of 170 ccRCC patients, VEGFR1 (FLT1) expression was associated with treatment response, histological grade and RECIST (Response Evaluation Criteria in Solid Tumors) score, whereas SAV1 and BLIMP1 (PRDM1) were associated with metachronous metastatic disease. Using in situ hybridisation (ISH) to detect miR-155 we observed higher tumoural cell expression in non-responders, and non-tumoural cell expression with increased histological grade. In summary, our preliminary analysis using integrated miRNA-target gene analyses identified several novel biomarkers in ccRCC patients that surely warrant further investigation. Full article
(This article belongs to the Special Issue Role of MicroRNAs in Cancer Development and Treatment, 2nd Edition)
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Figure 1

Figure 1
<p>Schematic diagram of the workflow used in this study.</p>
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<p>Heatmap of unsupervised cluster analyses depicting expression of (<b>A</b>) mature miRNAs, (<b>B</b>) pre-miRNAs, (<b>C</b>) snoRNAs and scaRNAs, (<b>D</b>) lncRNA and (<b>E</b>) coding genes in ccRCC cases. The dendrogram at the side shows the distribution of the RNAs, and at the top the relationship between patient samples (blue responder and red non-responder) is shown.</p>
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<p>String visualisation network of miRNA–target gene interactions associated with sunitinib resistance in ccRCC patients.</p>
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<p>Gene ontology and pathway mapping of miRNA targeted genes. Terms are functionally grouped based on shared genes (kappa score) and are shown in different colours. The node size represents the degree of significance.</p>
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<p>Box and whisker plots of levels of differentially expressed miRNAs measured by qRT-PCR in NR and R ccRCC cases. (<b>A</b>) <span class="html-italic">miR-17-3p</span>; (<b>B</b>) <span class="html-italic">miR-99a-5p</span>; (<b>C</b>) <span class="html-italic">miR-223-3p</span>; (<b>D</b>) <span class="html-italic">miR-155</span>; (<b>E</b>) <span class="html-italic">miR-484</span>; (<b>F</b>) <span class="html-italic">miR-200b-3p;</span> (<b>G</b>) <span class="html-italic">miR-200c-3p</span>; (<b>H</b>) <span class="html-italic">miR-150-5p</span>; (<b>I</b>) <span class="html-italic">miR-130b-3p</span>. Significant differences (<span class="html-italic">p</span> &lt; 0.05) are denoted by asterisks (*).</p>
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<p>Box and whisker plots of levels of differentially expressed genes measured by qRT-PCR in NR and R ccRCC cases. (<b>A</b>) <span class="html-italic">CD274</span>; (<b>B</b>) <span class="html-italic">EPAS1</span>; (<b>C</b>) <span class="html-italic">VEGFA</span>; (<b>D</b>) <span class="html-italic">FLT1</span>; (<b>E</b>) <span class="html-italic">ZEB1</span>; (<b>F</b>) <span class="html-italic">LRP6;</span> (<b>G</b>) <span class="html-italic">PTBP2</span>; (<b>H</b>) <span class="html-italic">PRDM1</span>; (<b>I</b>) <span class="html-italic">SAV1</span>. Significant differences (<span class="html-italic">p</span> &lt; 0.05) are denoted by asterisks (*).</p>
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<p>Kaplan–Meier survival curves in univariate analysis of expression levels of (<b>A</b>) <span class="html-italic">miR-223-3p</span>, (<b>B</b>) <span class="html-italic">PRDM1</span>, (<b>C</b>) <span class="html-italic">FLT1</span> and (<b>D</b>) <span class="html-italic">SAV1</span> as a function of overall survival (OS) in months.</p>
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<p>Examples of <span class="html-italic">miR-155</span> expression detection by ISH in ccRCC cases demonstrating (<b>A</b>) positive expression in tumour cells, (<b>B</b>) positive expression in non-tumour cells and (<b>C</b>) negative expression.</p>
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<p>Schematic summary of main findings in this study.</p>
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22 pages, 3085 KiB  
Article
Metabolomics Reveals Tyrosine Kinase Inhibitor Resistance-Associated Metabolic Events in Human Metastatic Renal Cancer Cells
by Filipa Amaro, Márcia Carvalho, Maria de Lourdes Bastos, Paula Guedes de Pinho and Joana Pinto
Int. J. Mol. Sci. 2024, 25(12), 6328; https://doi.org/10.3390/ijms25126328 - 7 Jun 2024
Viewed by 1559
Abstract
The development of resistance to tyrosine kinase inhibitors (TKIs) is a major cause of treatment failure in metastatic renal cell carcinoma (mRCC). A deeper understanding of the metabolic mechanisms associated with TKI resistance is critical for refining therapeutic strategies. In this study, we [...] Read more.
The development of resistance to tyrosine kinase inhibitors (TKIs) is a major cause of treatment failure in metastatic renal cell carcinoma (mRCC). A deeper understanding of the metabolic mechanisms associated with TKI resistance is critical for refining therapeutic strategies. In this study, we established resistance to sunitinib and pazopanib by exposing a parental Caki-1 cell line to increasing concentrations of sunitinib and pazopanib. The intracellular and extracellular metabolome of sunitinib- and pazopanib-resistant mRCC cells were investigated using a nuclear magnetic resonance (NMR)-based metabolomics approach. Data analysis included multivariate and univariate methods, as well as pathway and network analyses. Distinct metabolic signatures in sunitinib- and pazopanib-resistant RCC cells were found for the first time in this study. A common metabolic reprogramming pattern was observed in amino acid, glycerophospholipid, and nicotinate and nicotinamide metabolism. Sunitinib-resistant cells exhibited marked alterations in metabolites involved in antioxidant defence mechanisms, while pazopanib-resistant cells showed alterations in metabolites associated with energy pathways. Sunitinib-resistant RCC cells demonstrated an increased ability to proliferate, whereas pazopanib-resistant cells appeared to restructure their energy metabolism and undergo alterations in pathways associated with cell death. These findings provide potential targets for novel therapeutic strategies to overcome TKI resistance in mRCC through metabolic regulation. Full article
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Graphical abstract

Graphical abstract
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<p>(<b>a</b>,<b>b</b>) Non-linear regression models represented with mean values and 95% confidence intervals obtained for sunitinib- and pazopanib-induced cell death in parental (green line), sunitinib-resistant (red line) and pazopanib-resistant (blue line) Caki-1 cell lines as assessed by the MTT after 48 h exposure. Statistical significance assessed between models using the Extra Sum of Squares F test revealing a <span class="html-italic">p</span> &lt; 0.0001. (<b>c</b>,<b>d</b>) Effects on cell proliferation of parental (green bars), sunitinib-resistant (red bars) and pazopanib-resistant (blue bars) Caki-1 cells exposed to 2 µM sunitinib or 24 µM pazopanib. (<b>e</b>) Representative phase contrast microscopy images of parental and resistant Caki-1 cell lines. Scale bar: 100 µm. Original magnification 10×. Results were obtained from three independent experiments, performed in triplicate, and are presented as mean ± standard error of the mean. **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>(<b>a</b>,<b>b</b>) PLS-DA score scatter and loading plots of intracellular polar metabolic profiles from sunitinib-resistant (green circles, <span class="html-italic">n</span> = 8) vs. parental (red circles, <span class="html-italic">n</span> = 8) Caki-1 cells. (<b>c</b>,<b>d</b>) PLS-DA score scatter and loading plots of intracellular lipid profiles from sunitinib-resistant (green circles, <span class="html-italic">n</span> = 8) vs. parental (red circles, <span class="html-italic">n</span> = 8) Caki-1 cells. (<b>e</b>,<b>f</b>) PLS-DA score scatter and loading plots of extracellular metabolic profiles from sunitinib-resistant (green circles, <span class="html-italic">n</span> = 8) vs. parental (red circles, <span class="html-italic">n</span> = 8) Caki-1 cell lines. Acc, R<sup>2</sup> and Q<sup>2</sup> values were obtained with two components. Abbreviations: Ala: alanine; Asp: aspartate; CEs: cholesteryl esters; ChoP: phosphocholine; ETA: ethanolamine; FC: free cholesterol; Gly: glycine; Gln: glutamine; GSH: glutathione; GPC: glycerophosphocholine; Iso: isoleucine; Leu: leucine; MGs: monoglycerides; NAD<sup>+</sup>: nicotinamide adenine dinucleotide; PEs: phosphatidylethanolamines; PUFAs: polyunsaturated fatty acids; Val: valine.</p>
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<p>(<b>a</b>,<b>b</b>) PLS-DA score scatter and loading plots of intracellular polar metabolic profiles from pazopanib-resistant (green circles, <span class="html-italic">n</span> = 8) vs. parental (red circles, <span class="html-italic">n</span> = 8) Caki-1 cell lines. (<b>c</b>,<b>d</b>) PLS-DA scores scatter and loading plots of intracellular lipid profiles from pazopanib-resistant (green circles, <span class="html-italic">n</span> = 8) vs. parental (red circles, <span class="html-italic">n</span> = 8) Caki-1 cell lines. (<b>e</b>,<b>f</b>) PLS-DA scores scatter and loading plots of extracellular metabolic profiles from pazopanib-resistant (green circles, <span class="html-italic">n</span> = 8) vs. parental (red circles, <span class="html-italic">n</span> = 8) Caki-1 cell lines. Acc, R<sup>2</sup> and Q<sup>2</sup> values were obtained with two components. Abbreviations: Ala: alanine; Asn: asparagine; Asp: aspartate; CEs: cholesteryl esters; ChoP: phosphocholine; FAs: fatty acids: Gly: glycine; Gln: glutamine; Glu: glucose; GPC: glycerophosphocholine; Iso: isoleucine; Leu: leucine; MGs: monoglycerides; MNA: 1-methylnicotinamide; NAD<sup>+</sup>: nicotinamide adenine dinucleotide; UFAs: unsaturated fatty acids; Val: valine.</p>
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<p>(<b>a</b>,<b>b</b>) Heatmaps illustrating the mean levels of intracellular and extracellular metabolites altered in sunitinib- and pazopanib-resistant Caki-1 cell lines and the putatively altered metabolic pathways. Columns represent each sample group, and rows correspond to the mean normalised peak area of each metabolite coloured from minimum value (dark blue) to maximum value (dark red). Statistical significance was assessed by comparison with the parental Caki-1 cell line (first column in each heatmap) * <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. (<b>c</b>,<b>d</b>) Pathway analysis was performed on the list of metabolites found to be altered in sunitinib- and pazopanib-resistant Caki-1 cell lines, respectively. The annotated pathways were considered statistically significant (<span class="html-italic">p</span> &lt; 0.05). Abbreviations: ChoP: phosphocholine; FAs: fatty acids; PEs: phosphatidylethanolamine; NAD<sup>+</sup>: nicotinamide adenine dinucleotide; UFAs: unsaturated fatty acids.</p>
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<p>(<b>a</b>,<b>b</b>) Putative metabolic changes in sunitinib- and pazopanib-resistant Caki-1 cells. Red and green squares indicate increased and decreased metabolites, respectively. Blue squares represent extracellular changes. Arrows indicate metabolites consumed (orientation from outside to inside) and excreted (orientation from inside to outside). The consumption and excretion of metabolites can be interpreted from the boxplots shown in <a href="#app1-ijms-25-06328" class="html-app">Figure S4</a>. Dashed lines represent multiple-step reactions. Abbreviations: Ala: alanine; Arg: arginine; Asn: asparagine; Asp: aspartate; C: cholesterol; CEs: cholesteryl esters; ChoP: phosphocholine; ETA: ethanolamine; FAs: fatty acids; Gly: glycine; Gln: glutamine; Glu: glutamate; GSH: glutathione; GPC: glycerophosphocholine; Iso: isoleucine; Leu: leucine; Lys: lysine; Met: methionine; MGs: monoglycerides; NAD<sup>+</sup>: nicotinamide adenine dinucleotide; PEs: phosphatidylethanolamines; TCA: tricarboxylic acid cycle; Tyr: tyrosine; UFAs: unsaturated fatty acids; Val: valine.</p>
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28 pages, 3798 KiB  
Article
Discovery and Anticancer Screening of Novel Oxindole-Based Derivative Bearing Pyridyl Group as Potent and Selective Dual FLT3/CDK2 Kinase Inhibitor
by Aya Soudi, Onur Bender, Ismail Celik, Amer Ali Abd El-Hafeez, Rumeysa Dogan, Arzu Atalay, Eslam B. Elkaeed, Aisha A. Alsfouk, Elshimaa M. N. Abdelhafez, Omar M. Aly, Wolfgang Sippl and Taha F. S. Ali
Pharmaceuticals 2024, 17(5), 659; https://doi.org/10.3390/ph17050659 - 20 May 2024
Cited by 1 | Viewed by 1752
Abstract
Protein kinases regulate cellular activities and make up over 60% of oncoproteins and proto-oncoproteins. Among these kinases, FLT3 is a member of class III receptor tyrosine kinase family which is abundantly expressed in individuals with acute leukemia. Our previous oxindole-based hit has a [...] Read more.
Protein kinases regulate cellular activities and make up over 60% of oncoproteins and proto-oncoproteins. Among these kinases, FLT3 is a member of class III receptor tyrosine kinase family which is abundantly expressed in individuals with acute leukemia. Our previous oxindole-based hit has a particular affinity toward FLT3 (IC50 = 2.49 μM) and has demonstrated selectivity towards FLT3 ITD-mutated MV4-11 AML cells, with an IC50 of 4.3 μM. By utilizing the scaffold of the previous hit, sixteen new compounds were synthesized and screened against NCI-60 human cancer cell lines. This leads to the discovery of a potent antiproliferative compound, namely 5l, with an average GI50 value against leukemia and colon cancer subpanels equalling 3.39 and 5.97 µM, respectively. Screening against a specific set of 10 kinases that are associated with carcinogenesis indicates that compound 5l has a potent FLT3 inhibition (IC50 = 36.21 ± 1.07 nM). Remarkably, compound 5l was three times more effective as a CDK2 inhibitor (IC50 = 8.17 ± 0.32 nM) compared to sunitinib (IC50 = 27.90 ± 1.80 nM). Compound 5l was further analyzed by means of docking and molecular dynamics simulation for CDK2 and FLT3 active sites which provided a rational for the observed strong inhibition of kinases. These results suggest a novel structural scaffold candidate that simultaneously inhibits CDK2 and FLT3 and gives encouragement for further development as a potential therapeutic for leukemia and colon cancer. Full article
(This article belongs to the Special Issue Kinase Inhibitors in Targeted Cancer Therapy)
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Graphical abstract

Graphical abstract
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<p>Structure of sunitinib, FN-1501, III, IV, and targeted compounds (<b>5a–p</b>).</p>
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<p>Dynamics of compound <b>5l</b> on 60 cancer cell lines from 9 different cancer panels. (<b>a</b>) % growth inhibition exerted by compound <b>5l</b> at 10 µM concentration over NCI-60 cancer cell lines. Red squares indicate the highest number of consistent inhibitory activity. (<b>b</b>) Radar representation of the inhibitory activity of compound <b>5l</b> on nine types of cancers. The red line is shaped in relation to increasing activity outward from the radar center. (<b>c</b>) Variations in <b>5l</b> inhibitory effect among cell lines in each panel of cancer in NCI-60. The turquoise line shows 20% as the threshold.</p>
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<p>Five dose (0.01 to 100 μM) assay with compound <b>5l</b> against NCI-60 cell lines. Cells were treated with five different doses of <b>5l</b> for 48 h. Charts represent percentage growth between −100 and 100. Each cell line is indicated with different shapes and colors under the corresponding cancer chart. (<b>a</b>) Leukemia; (<b>b</b>) Non-small cell lung cancer; (<b>c</b>) Colon cancer; (<b>d</b>) CNS (central nervous system) cancer; (<b>e</b>) Melanoma; (<b>f</b>) Ovarian cancer; (<b>g</b>) Renal cancer; (<b>h</b>) Prostate cancer; (<b>i</b>) Breast cancer.</p>
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<p>The percentage of inhibition of the tested compound <b>5l</b> (10 µM) against PTK2B, JAK1, CDK2, FGFR1, IGF1R, VEDFR-2, PDGFRα, PDGFRβ, FLT3, and SRC kinases.</p>
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<p>Dose titrations of <b>5l</b> compared to sunitinib and FN-1501 against (<b>a</b>) FLT3 and (<b>b</b>) CDK2 kinases from 1 to 10,000 nM. (<b>c</b>) The half maximal inhibitory concentration (IC<sub>50</sub>) of compound <b>5l</b> against FLT3 and CDK2 kinase activity compared to sunitinib and FN-1501. <sup>a</sup> IC<sub>50</sub> values are of three separate experiments ± SD. * <span class="html-italic">p</span> ≤ 0.05, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001.</p>
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<p>Docking interactions and dynamics simulations of compound <b>5l</b> with kinase targets related to colorectal cancer and AML. (<b>a</b>) The conformation of compound <b>5l</b> within CDK2 (PDB ID: 3TI1) active site, showing interaction points. (<b>b</b>) FLT3 (PDB ID: 6JQR) in complex with compound <b>5l</b>, presenting the compound’s orientation and contact regions. (<b>c</b>,<b>d</b>) Molecular dynamics simulation of compound <b>5l</b> with kinase targets over 100 ns. RMSD profiles for <b>5l</b> for each target (green), CDK2 (red line) and FLT3 (blue line) complexes, indicating deviations from initial conformations. Conformational space exploration of <b>5l</b> with each kinase, represented using PCA. Hydrogen bond count over the simulation period, reflecting interaction consistency for each kinase–ligand complex. (<b>e</b>) MM/PBSA binding free energy components for compound <b>5l</b> with kinase targets. The bar graph summarizes the van der Waals, electrostatic, and solvation energy contributions to the total binding free energy (ΔTOTAL) of <b>5l</b> with CDK2 and FLT3.</p>
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<p>ADME estimation of active compound <b>5l.</b> (<b>a</b>) The BOILED-Egg plot showcases the predicted GI absorption and BBB permeability for <b>5l</b>, aligning with non-P-glycoprotein substrate characteristics (PGP−), and (<b>b</b>) the bioavailability radar chart, with the pink area depicting the optimal property values and the red lines representing the properties of <b>5l</b>, which largely fall within the desirable range, indicating good oral bioavailability.</p>
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<p>Synthetic approach of compounds <b>5a–p</b>. Reagents and conditions: (<b>a</b>) K<sub>2</sub>CO<sub>3</sub>, ACN, reflux, 2 h; (<b>b</b>) Piperidine, EtOH, reflux, 5 h.</p>
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