Band 32, Heft 4

Background: The gene COQ2 , encoding 4-hydroxybenzoate-polyprenyltransferase (coenzyme Q2), belongs to the candidates potentially influencing statin treatment tolerability. This enzyme is involved in the biosynthesis of coenzyme Q10 (CoQ10), in which depletion induced by statin treatment is implicated in the development of statin-associated muscle symptoms (SAMS). Thus, polymorphisms in the COQ2 gene might explain susceptibility to SAMS. Methods: Adult patients with SAMS (on low doses of atorvastatin and simvastatin)-induced myalgia/myopathy (n=278), patients on statins but without SAMS (n=293) and population (part of the post-MONICA [Multinational MONItoring of trends and determinants in CArdiovascular disease] study) controls (n=561) were genotyped (polymerase chain reaction-restriction fragment length polymorphism [PCR-RFLP] assay) for rs6535454 and rs4693075 polymorphisms within the COQ2 gene loci. Results: Distribution of rs6535454 in patients with SAMS (GG=51.1%, GA=40.0%, AA=8.9%) did not significantly differ (p=0.33; respectively 0.32 for codominant models of the analysis) from that in the population controls (GG=48.1%, GA=45.0%, AA=6.9%) or the SAMS-unaffected patients (GG=49.8%, GA=40.3%, AA=9.7%). Similarly, neither rs4693075 was associated with SAMS (CC=36.8%, CG=48.2%, GG=15.0% in patients suffering SAMS vs. CC=36.6%, CG=47.5%, GG=15.9 in controls and CC=35.8%, CG=48.2%, GG=15.9% in symptom-free patients, p=0.94 and 0.95 for codominant models of the analysis). Also, the haplotype distributions were not significantly different between the groups analyzed. Conclusions: The polymorphisms of the COQ2 gene do not associate with SAMS in the Czech patients treated with low doses of statins. This is another clue that the coenzyme Q10 pathway is not the most important for the development of SAMS.

Background: We have earlier developed a pharmacogenomic algorithm for acenocoumarol dose prediction in Greek patients that included CYP2C9 / VKORC1 genetic information. This study aims at analyzing the potential effect of CYP4F2 , CYP2C19 , and CYP1A2 gene polymorphisms on acenocoumarol dose requirements and at further improving the Greek-specific pharmacogenomic algorithm. Methods: A total of 205 Greek patients taking acenocoumarol (140 who reached and 65 who did not reach stable dose), participants of acenocoumarol EU-PACT trial, were included in the study. CYP4F2 , CYP2C19 , and CYP1A2 polymorphisms were genotyped by use of the PCR-RFLP method. All patients were previously genotyped for CYP2C9 / VKORC1 polymorphisms. Results: In the pooled sample, CYP4F2 , CYP2C19 , and CYP1A2 polymorphisms do not affect independently acenocoumarol dose requirements. For CYP4F2 , significant effects were found on patients’ ability to reach stable dose and on acenocoumarol dose requirements when CYP2C9/VKORC1 sub-phenotypes were analyzed. Specifically, when the patients were stratified according to their CYP2C9/VKORC1 functional bins, in sensitive responders, CYP4F2 *3 allele carriers ( CYP4F2 *1/*3 and *3/*3 genotypes) were more frequent in the patient group who reached stable dose (p=0.049). Additionally, in CYP2C9 intermediate metabolizers (IMs), after adjusting for age, weight, and VKORC1 genotypes, CYP4F2 genotypes were significantly associated with acenocoumarol stable dose (β: 0.07; 95% CI: 0.006–0.134; p=0.033). Conclusions: CYP4F2 gene shows a prominent weak association with acenocoumarol dose requirements. Sub-phenotype analysis is potentially important in determining additional gene polymorphisms that are associated with acenocoumarol dose requirements.

Background: For estimation of fractions metabolized (fm) by different hepatic recombinant human CYP enzymes (rhCYP), calculation of inter-system extrapolation factors (ISEFs) has been proposed. Methods: ISEF values for CYP1A2, CYP2C19 and CYP3A4/5 were measured. A CYP2C9 ISEF was taken from a previous report. Using a set of compounds, fractions metabolized by CYP enzymes (fm,CYP) values calculated with the ISEFs based on rhCYP data were compared with those from the chemical inhibition data. Oral pharmacokinetics (PK) profiles of midazolam were simulated using the physiologically based pharmacokinetics (PBPK) model with the CYP3A ISEF. For other CYPs, the in vitro fm,CYP values were compared with the reference fm,CYP data back-calculated with, e.g. modeling of test substrates by feeding clinical PK data. Results: In vitro - in vitro fm,CYP3A4 relationship between the results from rhCYP incubation and chemical inhibition was drawn as an exponential correlation with R 2 =0.974. A midazolam PBPK model with the CYP3A4/5 ISEFs simulated the PK profiles within twofold error compared to the clinical observations. In a limited number of cases, the in vitro methods could not show good performance in predicting fm,CYP1A2, fm,CYP2C9 and fm,CYP2C19 values as reference data. Conclusions: The rhCYP data with the measured ISEFs provided reasonable calculation of fm,CYP3A4 values, showing slight over-estimation compared to chemical inhibition.

Background: The aqueous extract of the Allophylus cominia (L) Sw (Sapindaceae) leaves has shown anti-diabetic, anti-obesity and anti-inflammatory properties. In the Caribbean region, it is typically used for the treatment of type-2 diabetes. Methods: Considering the herb–drug interaction, the aim of this study was to evaluate the potential effects of the A. cominia extract on the cytochrome P450 (CYP) (rat hepatocyte model) and P-glycoprotein (P-gp) (4T1 cell line) systems. Results: The extract did not decrease the cell viability after being assayed by the MTT test at up to 1500 μg/mL for 72 h. The exposure of the cultured rat hepatocytes to the product (up to 250 μg/mL) for 48 h increased the activities of CYP-1A2, 2C9, and 2E1 by 1.46-, 1.60-, and 1.51-fold, respectively, compared with the controls. The activities of CYP-2B6, 2D6, and 3A4 were not significantly altered, whereas the activity of P-gp decreased by 2- and 4-fold. In addition, the extracts at 100 and 200 μg/mL significantly increased doxorubicin cytotoxicity in these cells 24 h after treatment. Conclusions: The findings indicate that the A. cominia extract modulates the CYP and P-gp systems increasing sensitivity to doxorubicin. Further studies are necessary to evaluate the potential herb–drug interaction or chemosensitive properties.

Background: Fluoropyrimidines form the chemotherapy backbone of advanced and metastatic colorectal cancer (CRC). These drugs are frequently associated with toxicity events that result in dose adjustments and even suspension of the treatment. The thymidylate synthase ( TYMS ) gene is a potential marker of response and toxicity to fluoropyirimidines as this enzyme is the molecular target of these drugs. Our aim was to assess the association between variants of TYMS with response and toxicity to fluoropyrimidines in patients with CRC in independent retrospective and prospective studies. Methods: Variants namely rs45445694, rs183205964, rs2853542 and rs151264360 of TYMS were genotyped in 105 CRC patients and were evaluated to define their association with clinical response and toxicity to fluoropyrimidines. Additionally, the relationship between genotypes and tumor gene expression was analyzed by quantitative polymerase chain reaction. Results: The 2R/2R (rs45445694) was associated with clinical response (p=0.05, odds ratio (OR)=3.45) and severe toxicity (p=0.0014, OR=5.21, from pooled data). Expression analysis in tumor tissues suggested a correlation between the 2R/2R genotype and low TYMS expression. Conclusions: The allele 2R (rs45445694) predicts severe toxicity and objective response in advanced CRC patients. In addition, the alleles G(rs2853542) and 6bp-(rs151264360) are independent predictors of response failure to chemotherapy. This is the first study made on a Latin American population that points out TYMS gene variants have predictive values for response and toxicity in patients with CRC treated with fluoropyrimidine-based chemotherapy.

Background: The objective of this study was to evaluate the occurrence of drug-drug interactions (DDIs) in patients on cancer chemotherapy, with the identification of risk factors for these DDIs. Methods: This was a cross-sectional, descriptive study carried out at the Department of Onco-Radiation at Guru Gobind Singh Medical College, Faridkot, Punjab. The DDIs were recorded with the help of a drug interaction/interplay information software. Results: In total, 354 interactions were identified from 283 patient records. The mean age of the patients in the study was 49.05±14.35 years. According to the mechanism of interaction, 306 (86.44%) drug interactions were classified as pharmacokinetic and 48 (13.56%) as pharmacodynamic in nature. Conclusions: Sensitization of the treating oncologist and the establishment of alerts, such as electronic alerts or a novel fully digital computerized technology that gives a warning when a health expert enters a patient’s prescription orders into the electronic medical documentation, can be helpful in controlling DDIs.