Role of cytochrome P450 activity in the fate of anticancer agents and in drug resistance - Focus on tamoxifen, paclitaxel and imatinib metabolism

Although activity of cytochrome P450 iscienzymes (CYPs) plays a major role in the fate of anticancer agents in patients, there are relatively few clinical studies that evaluate drug metabolism with therapeutic outcome. Nevertheless, many clinical reports in various non-oncology fields have shown the dramatic importance of CYP activity in therapeutic efficacy, safety and interindividual variability of drug pharmacokinetics. Moreover, variability of drug metabolism in the liver as well as in cancer cells must also be considered as a potential factor mediating cancer resistance. This review underlines the role of drug metabolism mediated by CYPs in pharmacokinetic variability, drug resistance and safety. As examples, biotransformation pathways of tamoxifen, paclitaxel and imatinib are reviewed. This review emphasises the key role of therapeutic drug monitoring as a complementary tool of investigation to in vitro data. For instance, pharmacokinetic data of anticancer agents have not often been published within subpopulations of patients who show ultra-rapid, extensive or poor metabolism (e.g. due to CYP2D6 and CYP2C19 genotypes). Besides kinetic variability in the systemic circulation, induction of CYP activity may participate in creating drug resistance by speeding up the cancer agent degradation specifically in the target cells. For one cancer agent, various mechanisms of resistance are usually identified within different cell clones. This review also tries to emphasise that drug resistance mediated by CYP activity in cancer cells should be taken into consideration to a greater degree. The unequivocal identification of the metabolising enzymes involved in clinical conditions will eventually allow improvement and individualisation of anticancer agent therapy, i.e. drug dosage and selection. In addition, a more complete understanding of the metabolism of anticancer agents will assist in the prediction of drug-drug interactions, as anticancer agent combinations are becoming more prevalent.