Abstract

Cytochrome P450 3A4 (CYP3A4), one of the most important members of the cytochrome P450 subfamily, is a crucial catalyst in the metabolism of numerous drugs. As it catalyzes numerous processes for drug activation or inactivation, the pharmacological activities and clinical outcomes of anticancer drugs metabolized by CYP3A4 are highly dependent on the enzyme's activity and expression. Due to the complexity of tumor microenvironments and various influencing factors observed in human in vitro models and clinical studies, the pharmacokinetics of most anticancer drugs are influenced by the extent of induction or inhibition of CYP3A4-mediated metabolism, and these details are not fully recognized and highlighted. Therefore, this interindividual variability due to genetic and nongenetic factors, together with the narrow therapeutic index of most anticancer drugs, contributes to their unique set of exposures and responses, which have important implications for achieving the expected efficacy and minimizing adverse events of chemotherapy for cancer in individuals. To elucidate the mechanisms of CYP3A4-mediated activation/inactivation of anticancer drugs associated with personalized therapy, this review focuses on the underlying determinants that contribute to differences in CYP3A4 metabolic activity and provides a comprehensive and valuable overview of the significance of these factors, which differs from current considerations for dosing regimens in cancer therapy. We also discuss knowledge gaps, challenges and opportunities to explore optimal dosing regimens for drug metabolic activation/inactivation in individual patients, with particular emphasis on pooling and analyzing clinical information that affects CYP3A4 activity.

Significance Statement This review focuses on anticancer drugs that are activated/deactivated by CYP3A4 and highlights outstanding factors affecting the interindividual variability of CYP3A4 activity in order to gain a detailed understanding of CYP3A4-mediated drug metabolism mechanisms. A systematic analysis of available information on the underlying genetic and non-genetic determinants leading to variation in CYP3A4 metabolic activity to predict therapeutic response to drug exposure, maximize efficacy and avoid unpredictable adverse events has clinical implications for the identification and development of CYP3A4-targeted cancer therapeutics.