Population Pharmacokinetic and Pharmacogenetic Analysis of Mitotane in Patients with Adrenocortical Carcinoma: Towards Individualized Dosing

A review of mitotane in the management of adrenocortical cancer

IMPORTANCE

Mitotane (Lysodren, o,p'-DDD [1-(o-chlorophenyl)-1-(p-chlorophenyl)-2,2-dichloroethane)] is currently the only United States Food and Drug Administration and European Medicines Agency-approved product for the treatment of adrenocortical carcinoma.

OBSERVATIONS

Mitotane is challenging to administer; however, its toxicities (specifically adrenal insufficiency) are well known, and the management of adverse consequences has established approaches. While often viewed through the prism of a cytotoxic agent, it can also interfere with hormone production making it a valuable asset in managing functional ACC. A recently completed prospective trial has shed some light on its use in the adjuvant setting, but further clarity is needed. Many think mitotane has a role in the advanced or metastatic setting, although prospective data are lacking and retrospective analyses are often difficult to interpret.

CONCLUSIONS AND RELEVANCE

When used carefully and thoughtfully, especially in patients with hormonal excess, mitotane is an important component of the treatment armamentarium for ACC.

Association between SLCO1B1 genetic polymorphisms and bleeding risk in patients treated with edoxaban

Since SLCO1B1 encodes the uptake transporter OATP1B1, which can influence the pharmacokinetic and pharmacodynamic profiles of edoxaban, polymorphisms in SLCO1B1 may affect the edoxaban response. This study aimed to investigate the association between SLCO1B1 gene polymorphisms and the bleeding risk in patients receiving edoxaban. We genotyped 10 single-nucleotide polymorphisms (SNPs) from the SLCO1B1 gene in patients receiving edoxaban. We also analyzed rs3842 of ABCB1 as a confounder. The odds ratio (OR) and adjusted OR (AOR) were calculated from univariate and multivariable analysis, respectively. The area under the receiver operating characteristic curve (AUROC) was constructed for the discrimination of the model. A total of 159 patients receiving edoxaban were analyzed. Overdose and rs4149056 showed significant association with bleeding complications by around 11- and 5.5-fold, respectively. Additionally, patients with the rs4149057 variant allele (C) had a 3.9-fold increased bleeding risk compared with wild-type homozygote carriers (TT), whereas rs2306283 variant homozygote (GG) carriers had a 0.27-fold reduced bleeding risk compared with wild-type allele (A) carriers. Patients with the variant-type homozygote (CC) of ABCB1 rs3842 had a higher bleeding risk than T allele carriers (AOR = 5.3 and 5.9). The final models for multivariable analyses were acceptable based on the AUROC values (> 0.70). These findings may help predict bleeding risk in patients taking edoxaban and help personalize treatment.

Pharmacogenetics of Drugs Used in the Treatment of Cancers

Pharmacogenomics is based on the understanding of the individual differences in drug use, the response to drug therapy (efficacy and toxicity), and the mechanisms underlying variable drug responses. The identification of DNA variants which markedly contribute to inter-individual variations in drug responses would improve the efficacy of treatments and decrease the rate of the adverse side effects of drugs. This review focuses only on the impact of polymorphisms within drug-metabolizing enzymes on drug responses. Anticancer drugs usually have a very narrow therapeutic index; therefore, it is very important to use appropriate doses in order to achieve the maximum benefits without putting the patient at risk of life-threatening toxicities. However, the adjustment of the appropriate dose is not so easy, due to the inheritance of specific polymorphisms in the genes encoding the target proteins and drug-metabolizing enzymes. This review presents just a few examples of such polymorphisms and their impact on the response to therapy.

Mitotane treatment in adrenocortical carcinoma: mechanisms of action and predictive markers of response to therapy

INTRODUCTION

Adrenocortical carcinoma (ACC) is a rare malignancy with a high risk of recurrence even in cases with complete surgical tumor resection. Mitotane represents the cornerstone of the adjuvant therapy as well as the first line of medical treatment in advanced cases. However, evidence on mitotane efficacy is mostly based on retrospective studies and the use of mitotane continues to represent a clinical challenge.

EVIDENCE ACQUISITION

Mitotane causes selective damage to adrenocortical cells, causing an increase of cell apoptosis through a disruption of mitochondria and the induction of the endoplasmic reticulum stress. Different clinical and molecular markers predicting response to mitotane have been proposed with uncertain results. Attainment of mitotane plasma levels within the target range of 14 to 20 mg/L represent the strongest predictor of mitotane effectiveness both in adjuvant and advanced tumor setting. The occurrence of late recurrence after primary ACC diagnosis and changes in metabolic activity on FDG-PET are only weakly associated with mitotane response. Among the proposed molecular markers associated with mitotane efficacy, the investigation of the CYP2W1*6 and CYP2B6*6 single nucleotide polymorphisms appears to be currently the most promising predictive molecular markers of mitotane therapy. However, none of the evaluated markers has been validated for clinical use.

CONCLUSIONS

In the era of precision medicine, a better insight into mitotane molecular mechanisms as well as the potential use in the daily clinical practice of clinical parameters and molecular markers predicting the individual response to mitotane are urgently needed.

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.