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  • 1
    Keywords: CANCER ; EXPRESSION ; tumor ; COMBINATION ; Germany ; TYROSINE KINASE ; imaging ; screening ; CLONING ; TUMORS ; NUCLEAR-MEDICINE ; LIGAND ; FAMILY ; BASE ; DISCOVERY ; score ; TRIAL ; IDENTIFICATION ; EFFICIENT ; DATABASE ; LIGANDS ; PHARMACOKINETICS ; nuclear medicine ; TRACER ; INHIBITORS ; radiology ; RE ; SOFTWARE ; methods ; NUCLEAR ; 3D ; CRITERIA ; GA-68-DOTATOC ; docking ; SET ; MEDICINE ; modeling ; SOMATOSTATIN RECEPTOR ; IN-SILICO ; SSTR2 ; virtuals screening ; Y-90-DOTATOC THERAPY
    Abstract: New ligands are needed to improve diagnostics and treatment of SSTR2 expressing tumors. We implemented a procedure to identify ligands based on computer processing methods. A multistep procedure was used. Search entries were taken from National Cancer Institute database. Application of criteria defined by the Lipinski rules reduced the initial data set. Then a pharmacophore criterion including Lys and Trp residues was the next step of the hierarchical filtering, and the ligands considered were transformed from 2D to 3D. Finally, dedicated software was applied for docking ligand studies. Our results have shown that by virtual screening and trial docking, we identified novel ligands with better scores of docked poses compared with previously reported ligands. In conclusion, the use of a focused library that incorporates an initial probe, improved the possibility of a successful virtual screening as compared with random screening and is cost efficient by further combination of trial docking
    Type of Publication: Journal article published
    PubMed ID: 18815664
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  • 2
    Abstract: F-18-FDG kinetics are primarily dependent on the expression of genes associated with glucose transporters and hexokinases but may be modulated by other genes. The dependency of F-18-FDG kinetics on angiogenesis-related gene expression was evaluated in this study. Methods: Patients with primary colorectal tumors (n = 25) were examined with PET and F-18-FDG within 2 days before surgery. Tissue specimens were obtained from the tumor and the normal colon during surgery, and gene expression was assessed using gene arrays. Results: Overall, 23 angiogenesis-related genes were identified with a tumor-to-normal ratio exceeding 1.50. Analysis revealed a significant correlation between k1 and vascular endothelial growth factor (VEGF-A, r = 0.51) and between fractal dimension and angiopoietin-2 (r = 0.48). Q was negatively correlated with VEGF-B (r = -0.46), and a positive correlation was noted for angiopoietin-like 4 gene (r = 0.42). A multiple linear regression analysis was used for the PET parameters to predict the gene expression, and a correlation coefficient of r 0.75 was obtained for VEGF-A and of r = 0.76 for the angiopoietin-2 expression. Thus, on the basis of these multiple correlation coefficients, angiogenesis-related gene expression contributes to about 50% of the variance of the F-18-FDG kinetic data. The global F-18-FDG uptake, as measured by the standardized uptake value and influx, was not significantly correlated with angiogenesis-associated genes. Conclusion: F-18-FDG kinetics are modulated by angiogenesis-related genes. The transport rate for F-18-FDG (k1) is higher in tumors with a higher expression of VEGF-A and angiopoietin-2. The regression functions for the PET parameters provide the possibility to predict the gene expression of VEGF-A and angiopoietin-2
    Type of Publication: Journal article published
    PubMed ID: 18632818
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