METHODS: Prostate cancer cases diagnosed between 2003 and 2008 which met with the inclusion criteria were included in the study. One hundred and twelfth (112) pairs of cases and controls matched by age and ethnicity were analysed. McNemar Odds Ratios (OR(M)) were calculated using McNemar Calculator software for univariate analysis while conditional logistic regression was used for multivariate analysis, both using SPSS version 12.0.
RESULTS: Most of the prostate cancer patients (68.8%) that came for treatment in UKMMC were above 70 years old. The majority were Chinese (50.0%) followed by Malay (46.4%) and Indian (3.6%). Multivariate analysis showed cases were more likely to have a first-degree relative with a history of cancer (OR= 3.77, 95% CI= 1.19-11.85), to have been exposed to pesticides (OR= 5.57, 95% CI= 1.75-17.78) and consumed more meat (OR= 12.23, 95% CI= 3.89-39.01). Significantly reduced risks of prostate cancer were noted among those consuming more vegetables (OR= 0.12, 95% CI= 0.02-0.84), more tomatoes (OR= 0.35, 95% CI= 0.13-0.93) and those who had frequent sexual intercourse (OR= 0.44, 95% CI= 0.19-0.96).
CONCLUSION: Some lifestyle and occupation factors are strong predictors of the occurrence of prostate cancer among patients in UKMMC. More importantly, with the identification of the potentially modifiable risk factors, proper public health intervention can be improved.
METHODS: The involved approaches build molecules from fragments that are either isosteric to GSH sub-moieties (ligand-based) or successfully docked to GSH binding sub-pockets (structure-based). Compared to reference GST inhibitor of S-hexyl GSH, ligands with improved rigidity, synthetic accessibility, and affinity to receptor were successfully designed. The method involves joining fragments to create ligands. The ligands were then explored using molecular docking, Cartesian coordinate's optimization, and simplified free energy determination as well as MD simulation and MMPBSA calculations. Several tools were used which include OPENEYE toolkit, Open Babel, Autodock Vina, Gromacs, and SwissParam server, and molecular mechanics force field of MMFF94 for optimization and CHARMM27 for MD simulation. In addition, in-house scripts written in Matlab were used to control fragments connection and automation of the tools.