RESULTS: The mRNA expression of PPARα was significantly induced in HCT116 cells following treatment with chrysin for 36 h, but the mRNA expression of PPARα was inhibited, when the cells were treated with a combination of chrysin and MK886 (PPARα inhibitor). This phenomenon proved that the incorporation of MK886 lowers the expression levels of PPARα, thus enabling us to study the function of PPARα. The cell population of the G0/G1 phase significantly increased in chrysin-treated cells, which was accompanied by a decrease in the percentage of S phase cell population after 12 h of treatment. However, treatments of HCT116 cells with chrysin only or a combination of chrysin and MK886 did not show the opposite situation in the G0/G1 and S phase cell populations, indicating that the expression of PPARα may not be associated with the cell cycle in the treated cells. The migration rate in chrysin-treated HCT116 cells was reduced significantly after 24 and 36 h of treatments. However, the activity was revived, when the expression of PPARα was inhibited, indicating that the migration activity of chrysin-treated cells is likely correlated with the expression of PPARα. Comparison of the CYP2S1 and CYP1B1 mRNA expression in chrysin only treated, and a combination of chrysin and MK886-treated HCT116 cells for 24 and 36 h showed a significant difference in the expression levels, indicating that PPARα inhibitor could also modify the expression of CYP2S1 and CYP1B1.
CONCLUSION: The study indicates that PPARα may play an essential role in regulating the migration activity, and the expression of CYP2S1 and CYP1B1 in chrysin-treated colorectal cancer cells.
METHODS: We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow.
RESULTS: We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population.
CONCLUSION: Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.
METHODS: Articles that report genetic polymorphisms, genotype frequencies and allele frequencies in CYP2C9, CYP2C19, CYP2D6 and CYP3A5 were retrieved from the PubMed database.
RESULTS AND DISCUSSIONS: A total of 86 studies that fulfilled the eligibility criteria representing different ethnic populations of SEEA, ie, Burmese, Chinese, Japanese, Karen ethnic minority, Korean, Malaysian, Philippino, Singaporean, Taiwanese, Thai, Indonesian, and Vietnamese, were included in the analysis. In general, the genotype frequencies across SEEA populations are comparable. The CYP2C9*1/*1 (69.3%-99.1%), *1/*3 (2.3%-20.1%) and *3/*3 (0%-2.2%) genotypes are reported in most SEEA populations. Six major CYP2C19 genotypes, ie, *1/*1 (6.25%-88.07%), *1/*2 (21.5%-86.46%), *1/*3 (0.8%-15.8%), *2/*2 (3.4%-14.5%), *2/*3 (0%-7.3%) and *3/*3 (0%-10.2%), are reported in most SEEA populations. Major CYP2D6 genotypes include *10/*10 (0%-69.6%), *1/*1 (0%-61.21%) and *1/*10 (0%-62.0%). Major CYP3A5 genotypes are *3/*3 (2.0%-71.4%), *1/*3 (16.0%-57.1%) and *1/*1 (0%-82.0%). Genotyping of abnormal genotypes of CYP2C9 (*1/*3), CYP2C19 (*1/*2, *1/*3), CYP3A5 (*1/*3) and CYP2D6 (*5/*10) associated with IM (Intermediate metabolizer) status, may be clinically beneficial in SEEA populations. Similarly, with CYP2C19 (*2/*2, *2/*3), CYP2D6 (*5/*5 ) linked to PM (Poor metabolizer), CYP2D6 (*10/*10, *1/*5 and to lesser extent *1/*4, *2/*5, *10/*41, *10/*49, *10/*14) and CYP3A5 (*1/*1) associated with EM (extensive metabolizer).
WHAT IS NEW AND CONCLUSION: Sufficient number of studies has provided comparable results in general. This review suggests that comparable genotype frequencies of CYP2C9, CYP2C19, CYP2D6 and CYP3A5 exist among the SEEA populations. It is noted that more research data are reported from East Asians compared with South-East Asians. Concerned efforts are required to establish partnerships among SEEA countries that will ensure sufficient data from South-East Asian countries which will assist in establishing the databases for SEEA populations.
PURPOSE: The concomitant use of therapeutic drugs may cause potential drug-drug interactions by decreasing or increasing plasma levels of the administered drugs, leading to a suboptimal clinical efficacy or a higher risk of toxicity. Thus, evaluating the inhibitory potential of a new chemical entity, and to clarify the mechanism of inhibition and kinetics in the various CYP enzymes is an important step to predict drug-drug interactions.
STUDY DESIGN: This study was designed to assess the potential inhibitory effects of Alpinia conchigera Griff. rhizomes extract and its active constituent, ACA, on nine c-DNA expressed human cytochrome P450s (CYPs) enzymes using fluorescent CYP inhibition assay.
METHODS/RESULTS: The half maximal inhibitory concentration (IC50) of Alpinia conchigera Griff. rhizomes extract and ACA was determined for CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C19, CYP2D6, CYP2E1, CYP3A4 and CYP3A5. A. conchigera extract only moderately inhibits on CYP3A4 (IC50 = 6.76 ± 1.88µg/ml) whereas ACA moderately inhibits the activities of CYP1A2 (IC50 = 4.50 ± 0.10µM), CYP2D6 (IC50 = 7.50 ± 0.17µM) and CYP3A4 (IC50 = 9.50 ± 0.57µM) while other isoenzymes are weakly inhibited. In addition, mechanism-based inhibition studies reveal that CYP1A2 and CYP3A4 exhibited non-mechanism based inhibition whereas CYP2D6 showed mechanism-based inhibition. Lineweaver-Burk plots depict that ACA competitively inhibited both CYP1A2 and CYP3A4, with a Ki values of 2.36 ± 0.03 µM and 5.55 ± 0.06µM, respectively, and mixed inhibition towards CYP2D6 with a Ki value of 4.50 ± 0.08µM. Further, molecular docking studies show that ACA is bound to a few key amino acid residues in the active sites of CYP1A2 and CYP3A4, while one amino residue of CYP2D6 through predominantly Pi-Pi interactions.
CONCLUSION: Overall, ACA may demonstrate drug-drug interactions when co-administered with other therapeutic drugs that are metabolized by CYP1A2, CYP2D6 or CYP3A4 enzymes. Further in vivo studies, however, are needed to evaluate the clinical significance of these interactions.
METHODS: CYP proteins expressed in Escherichia coli were studied using the substrate 3-cyano-7- ethoxycoumarin (CEC) and inhibitor probes (quinidine, fluoxetine, paroxetine, terbinafine) in the enzyme assay. Computer modelling was additionally used to create three-dimensional structures of the CYP2D6*14 variants.
RESULTS: Kinetics data indicated significantly reduced intrinsic clearance in CYP2D6*14 variants, suggesting that P34S, G169R, R296C, and S486T substitutions worked cooperatively to alter the conformation of the active site that negatively impacted the deethylase activity of CYP2D6. For the inhibition studies, IC50 values decreased in quinidine, paroxetine, and terbinafine but increased in fluoxetine, suggesting a varied ligand-specific susceptibility to inhibition. Molecular docking further demonstrated the role of P34S and R296C in altering access channel dimensions, thereby affecting ligand access and binding and subsequently resulting in varied inhibition potencies.
CONCLUSION: In summary, the differential selectivity of CYP2D6*14 variants for the ligands (substrate and inhibitor) was governed by the alteration of the active site and access channel architecture induced by the natural mutations found in the alleles.