We report herein, the design and synthesis of benzimidazole-oxadiazole derivatives as new inhibitors for vascular endothelial growth factor receptor-2 (VEGFR-2). The designed members were assessed for their in vitro anticancer activity against three cancer cell lines and two normal cell lines; A549, MCF-7, PANC-1, hTERT-HPNE and CCD-19Lu. Compounds 4c and 4d were found to be the most effective compounds against three cancer cell lines. Compounds 4c and 4d were then tested for their in vitro VEGFR-2 inhibitory activity, safety profiles, and selectivity indices using the normal hTERT-HPNE and CCD-19Lu cell lines. It was determined that compound 4c was the most effective and safe member of the produced chemical family. Vascular endothelial growth factor A (VEGFA) immunolocalizations of compounds 4c and 4d were evaluated relative to control by VEGFA immunofluorescence staining. Compounds 4c and 4d inhibited VEGFR-2 enzyme with half-maximal inhibitory concentration values of 0.475 ± 0.021 and 0.618 ± 0.028 µM, respectively. Molecular docking of the target compounds was carried out in the active site of VEGFR-2 (Protein Data Bank: 4ASD).
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Eur J Epidemiol
January 2025
Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden.
The Stockholm Early Detection of Cancer Study (STEADY-CAN) cohort was established to investigate strategies for early cancer detection in a population-based context within Stockholm County, the capital region of Sweden. Utilising real-world data to explore cancer-related healthcare patterns and outcomes, the cohort links extensive clinical and laboratory data from both inpatient and outpatient care in the region. The dataset includes demographic information, detailed diagnostic codes, laboratory results, prescribed medications, and healthcare utilisation data.
View Article and Find Full Text PDFNPJ Precis Oncol
January 2025
Zentalis Pharmaceuticals, Inc., San Diego, CA, USA.
Upregulation of Cyclin E1 and subsequent activation of CDK2 accelerates cell cycle progression from G1 to S phase and is a common oncogenic driver in gynecological malignancies. WEE1 kinase counteracts the effects of Cyclin E1/CDK2 activation by regulating multiple cell cycle checkpoints. Here we characterized the relationship between Cyclin E1/CDK2 activation and sensitivity to the selective WEE1 inhibitor azenosertib.
View Article and Find Full Text PDFSci Rep
January 2025
School of Medicine, Nankai University, Tianjin, 300071, China.
Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear.
View Article and Find Full Text PDFAnn Hematol
January 2025
Department of Hematology, Navy Medical Center of PLA, Naval Medical University, No. 338 West Huaihai Road, Changning District, Shanghai, 200052, China.
Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established.
View Article and Find Full Text PDFSci Rep
January 2025
School of Physics, Engineering and Technology, University of York, Heslington, York, YO10 5DD, UK.
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.
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