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Träfflista för sökning "(WFRF:(Porter Christopher C.)) srt2:(2013-2014)"

Sökning: (WFRF:(Porter Christopher C.)) > (2013-2014)

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1.
  • Fu, Yi-Ping, et al. (författare)
  • The 19q12 Bladder Cancer GWAS Signal : Association with Cyclin E Function and Aggressive Disease
  • 2014
  • Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 74:20, s. 5808-5818
  • Tidskriftsartikel (refereegranskat)abstract
    • A genome-wide association study (GWAS) of bladder cancer identified a genetic marker rs8102137 within the 19q12 region as a novel susceptibility variant. This marker is located upstream of the CCNE1 gene, which encodes cyclin E, a cell-cycle protein. We performed genetic fine-mapping analysis of the CCNE1 region using data from two bladder cancer GWAS (5,942 cases and 10,857 controls). We found that the original GWAS marker rs8102137 represents a group of 47 linked SNPs (with r(2) >= 0.7) associated with increased bladder cancer risk. From this group, we selected a functional promoter variant rs7257330, which showed strong allele-specific binding of nuclear proteins in several cell lines. In both GWASs, rs7257330 was associated only with aggressive bladder cancer, with a combined per-allele OR = 1.18 [95% confidence interval (CI), 1.09-1.27, P = 4.67 x 10(-5)] versus OR = 1.01 (95% CI, 0.93-1.10, P = 0.79) for nonaggressive disease, with P = 0.0015 for case-only analysis. Cyclin E protein expression analyzed in 265 bladder tumors was increased in aggressive tumors (P = 0.013) and, independently, with each rs7257330-A risk allele (P-trend = 0.024). Overexpression of recombinant cyclin E in cell lines caused significant acceleration of cell cycle. In conclusion, we defined the 19q12 signal as the first GWAS signal specific for aggressive bladder cancer. Molecular mechanisms of this genetic association may be related to cyclin E overexpression and alteration of cell cycle in carriers of CCNE1 risk variants. In combination with established bladder cancer risk factors and other somatic and germline genetic markers, the CCNE1 variants could be useful for inclusion into bladder cancer risk prediction models.
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2.
  • Field, Christopher B., et al. (författare)
  • Summary for Policymakers
  • 2014
  • Ingår i: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and SectoralAspects.. - 9781107415379 ; , s. 1-32
  • Bokkapitel (refereegranskat)
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3.
  • Persson, Linda C., et al. (författare)
  • Computational Prediction of Drug Solubility in Lipid Based Formulation Excipients
  • 2013
  • Ingår i: Pharmaceutical research. - : Springer Science and Business Media LLC. - 0724-8741 .- 1573-904X. ; 30:12, s. 3225-3237
  • Tidskriftsartikel (refereegranskat)abstract
    • To investigate if drug solubility in pharmaceutical excipients used in lipid based formulations (LBFs) can be predicted from physicochemical properties. Solubility was measured for 30 structurally diverse drug molecules in soybean oil (SBO, long-chain triglyceride; TG(LC)), Captex355 (medium-chain triglyceride; TG(MC)), polysorbate 80 (PS80; surfactant) and PEG400 co-solvent and used as responses during PLS model development. Melting point and calculated molecular descriptors were used as variables and the PLS models were validated with test sets and permutation tests. Solvation capacity of SBO and Captex355 was equal on a mol per mol scale (R (2) = 0.98). A strong correlation was also found between PS80 and PEG400 (R (2) = 0.85), identifying the significant contribution of the ethoxylation for the solvation capacity of PS80. In silico models based on calculated descriptors were successfully developed for drug solubility in SBO (R (2) = 0.81, Q (2) = 0.76) and Captex355 (R (2) = 0.84, Q (2) = 0.80). However, solubility in PS80 and PEG400 were not possible to quantitatively predict from molecular structure. Solubility measured in one excipient can be used to predict solubility in another, herein exemplified with TG(MC) versus TG(LC), and PS80 versus PEG400. We also show, for the first time, that solubility in TG(MC) and TG(LC) can be predicted from rapidly calculated molecular descriptors.
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