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Journal of Pharmaceutical Analysis
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Short communication
VLDL: The key factors influencing the distribution of mitotane in patients with adrenocortical carcinoma
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Xiangjie Di a, b, c, 1, Yixian Liu a, b, 1, Jia You a, b, Yuchun Men a, b, Zhenlei Wang a, b, Chao Zhou ª, Ying Jin a, b, Yating Ge a, b, e, Yongji He a, b, Li Zheng a, b,*
a Cancer Center, Clinical Trial Center, West China Hospital, Sichuan University, Chengdu, 610041, China
b NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug West China Hospital, Sichuan University, Chengdu, 610041, China
” Development and Related Diseases of Women and Children Key Laboratory of Sichuan Province, Sichuan University, Chengdu, 610041, China
d SCIEX China, Shanghai, 200335, China
e Department of Clinical Pharmacy and Pharmacy Administration, West China School of Pharmacy, Sichuan University, Chengdu, 610041, China
ARTICLE INFO
Article history: Received 2 October 2024 Received in revised form 5 February 2025 Accepted 27 February 2025 Available online 1 March 2025
Mitotane, an orphan drug with narrow therapeutic window and significant interindividual variability for treating adrenocor- tical carcinoma, requires therapeutic drug monitoring [1]. Current detection methods fail to accurately measure plasma drug con- centrations after a high-fat meal, and the reasons behind the significant pharmacokinetic variability among individuals remain unclear, complicating individualized treatment [2,3]. During our therapeutic drug monitoring process, we found that hyper- lipidemic patients are more likely to reach the target drug con- centration and experience concurrent neurotoxicity. We also observed that mitotane bound to lipoproteins is crucial for its delivery to target organs and its therapeutic effect, which contrasts with previous research findings. Therefore, the aim of this study is to explore a better therapeutic drug monitoring method, while identifying key factors that influence drug absorption and distribution, providing evidence for rational drug use in patients.
For this purpose, three parts were designed and conducted. Firstly, a new pretreatment method involving freezing and centrifugation was developed and validated to eliminate the impact of high-fat meals on blood drug concentration monitoring. Secondly,
a hyperlipidemic mice model was established to differentiate the effects of chronic hyperlipidemia and transient high-fat diet on drug absorption and distribution. Third, we used metabolomics and the random forest algorithm to identify key factors influencing steady- state and distribution to target organs of mitotane concentration. The materials and methods are shown in the Supplementary data. Animal care and experimental protocols were approved by the An- imal Ethics Committee of West China Hospital of Sichuan University (Approval number: 20240306117). The clinical study was approved by the Ethics Committee of West China Hospital, Sichuan University (Approval number: ChiCTR2300073328) and was registered at https://www.chictr.org.cn.
In the first part, we observed abnormal fluctuations in drug concentrations in lipemic blood following a high-fat diet through clinical observation (Table S1, and Figs. S1 and 1A). Subsequently, we compared 68 samples from 16 subjects using both the new and original methods. Compared with the traditional method, the new method (Supporting Information: 1.3.4.3 Different Mitotane plasma concentration monitoring) incorporates in the pretreatment step. The hyperlipidemic samples return to normal after pretreatments (Fig. S2), which allowed accurate measurement of true blood drug concentrations. The comparison results indicate that the new method can avoid the impact of high-fat diet on drug concentration monitoring (Table S2).
In second part, we established hyperlipidemic mice model and compared it with normal mice to study the effects of short-term high fat diet and hyperlipidemia on the absorption and distribu- tion of mitotane, while applying the new pretreatment procedure to process mouse plasma samples. The experimental design is shown in Table S3. In the mouse adrenal glands, the comparison between group 3 and group 1 showed P = 0.0282, and the com- bined comparison of group 2 with groups 4 and 5 showed P = 2.17 × 10-5 (Fig. 1B). This suggests that hyperlipidemia facilitates mitotane distribution in the adrenal glands, and that long-term high-fat diet combined with hyperlipidemia further enhances mitotane distribution in the adrenal glands. In contrast, long-term
Peer review under responsibility of Xi’an Jiaotong University.
* Corresponding author. Cancer Center, Clinical Trial Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
E-mail address: zhengli@wchscu.cn (L. Zheng).
1 Both authors contributed equally to this work.
A
B
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Adrenal gland
Left brain
Mitontane concentration (mg/L)
Mitontane concentration (mg/L)
2000
30
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Mitotane concentration (mg/L)
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20
64.656
1000
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Plasma
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Cerebellum
Therapeutic ceiling 20 mg Therapeutic threshold 14 mg
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Mitontane concentration (mg/L)
Mitontane concentration (mg/L)
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Random forest classification
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high-fat diet without hyperlipidemia does not increase mitotane distribution in the adrenal glands. In the mouse left brain, we observed that long-term high-fat diet promotes mitotane distri- bution within the cranium (Fig. 1C). From the distribution of mitotane in different organs in group 5 compared to group 4, it is evident that the high plasma concentrations detected by the old method in transient lipemia induced by a high-fat meal do not affect drug distribution (Figs. 1B-E). The new detection method can avoid interference from transient lipemia. We also observed that on the fifth day of the experiment, the fourth and fifth groups were the first to exhibit symptoms of neurotoxicity (Videos S1-S5). Although there was no statistical difference between the group 4 and group 2, the Kolmogorov-Smirnov test with a P value of 0.0159 indicated a difference in data dispersion. These data show a close relationship between lipoproteins and mitotane distribution, as well as the drug’s efficacy and adverse reactions.
Supplementary video related to this article can be found at https://doi.org/10.1016/j.jpha.2025.101252
In third part, untargeted metabolomics was used to validate the relationship between mitotane absorption and distribution with lipoproteins, and to identify which lipoprotein has the greatest impact on the absorption and distribution. Subjects who reached the therapeutic window and received a daily dose >1,500 mg were placed in the normal group(NOR group), while those with a dose ≤1,500 mg were placed in the fast achieved thera- peutic windw group(FAST group). The results and quality control of metabolomics are shown in Table S4 and Fig. S3, integrated with clinical assay data from subjects (Figs. 1F-1I) which indicate that levels of triglycerides (TG) and low-density lipoprotein (LDL) in the FAST group was significantly higher than that in the NOR group. Very low density lipoprotein(VLDL) is a component of LDL and TG. At the same time, In the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (Figs. 1J and K), about FAST group, we observed that downregulation of glycerol-3P, which is located at the end of lipid metabolism, and also downregulation of phospho-ethanolamine and phosphatidyl-ethanolamine, both of which are key components of VLDL secreted by the liver. These data provide multifaceted evidence that VLDL is a key factor influencing the absorption and distribution of mitotane. Mitotane bound to VLDL may be a key factor influencing drug efficacy. This is consistent with our clinical observations and animal experi- ment results, but differs from the conclusion of previous studies which suggested that the free drug is the active form [4,5]. We also identified a series of key metabolites that affect dosing regimens by using volcano plot (Figs.1L and Table S5), orthogonal pro- jections to latent structures discriminant analysis (OPLS-DA) and random forest models (Figs. 1M, 1N and S4). The TG with specific molecular structures, such as TG (15:0/22:4 (7Z,10Z,13Z,16Z)/22:5 (4Z,7Z,10Z,13Z,16Z)) and TG (24:0/15:0/O-18:0), along with
dihydrotestosterone and other metabolites, is key metabolites that differentiate the FAST group from the NOR group. This aligns with our clinical observations of hormonal imbalances and lipid metabolism disorders, thereby reinforcing the physiological relevance of these metabolic changes.
In conclusion, this study suggests that it is important to adopt our new preprocessing method to avoid the impact of transient high-fat meals on drug concentration and dosing guidance. Addi- tionally, it is recommended to measure LDL and TG levels in pa- tients while monitoring drug concentrations. Furthermore, for patients with adrenal cortical carcinoma and elevated LDL and TG levels, a dose escalation regimen may be considered to achieve the target drug concentration, while avoiding high-fat meals to reduce neurotoxicity. For patients with normal LDL and TG levels, a high- dose bolus regimen may be considered based on clinical circum- stances. Of course, due to the limited sample size in our study, specific dosing recommendations need to be validated through rigorously designed clinical trials.
CRediT authorship contribution statement
Xiangjie Di: Writing - original draft, Visualization, Validation, Project administration, Methodology, Investigation, Funding acquisition, Data curation. Yixian Liu: Writing - review & editing, Visualization, Validation, Supervision, Software, Project adminis- tration, Investigation, Data curation. Jia You: Supervision, Project administration, Investigation, Data curation. Yuchun Men: Re- sources, Project administration, Investigation. Zhenlei Wang: Su- pervision, Data curation. Chao Zhou: Software. Ying Jin: Software, Data curation. Yating Ge: Methodology. Yongji He: Data curation. Li Zheng: Writing - review & editing, Supervision, Funding acquisi- tion, Conceptualization.
Declaration of competing interest
The authors declare that there are no conflicts of interest.
Acknowledgments
This study was supported by 1.3.5 Project for Disciplines of Excellence-Clinical Research Fund, West China Hospital, Sichuan University, China (Grant No .: 23HXFH027), Foundation of Devel- opment and Related Diseases of Women and Children Key Labo- ratory of Sichuan Province, China (Grant No .: FYYFEJB2024002) and The Key Research and Development Program of Sichuan Province, China (Grant No .: 2024YFFK0334).
line at 20 mg/L and the lower dashed line at 14 mg/L. (B) MTT concentration in the adrenal gland; Group4/Group3: P = 0.0282; Group1/Group3: P = 0.0282; Group1/Group4: P = 0; Group2/Group4: P = 0.0124; Group1/Group5: P = 0.0001; Group2/Group5: P = 0.0454. (C) MTT concentration in the left brain; Group4/Group3: P = 0.0011; Group5/Group3: P = 0.0013; Group1/Group4: P = 0; Group 1/Group5: P = 0; Group2/Group1: P = 0.0084. (D) MTT concentration in the plasma; Group4/Group3: P = 0.0009; Group5/Group3: P = 0.0075; Group1/Group4: P = 0.00000304; Group2/Group4: P = 0.042; Group1/Group5: P = 0; Group2/Group1: P = 0.0037. (E) MTT concentration in the cerebellum; Group4/Group3: P = 0.001; Group5/Group3: P = 0.0027; Group1/Group4: P = 0; Group1/Group5: P = 0; Group2/Group1: P = 0.0079. (F) Comparative analysis of triglycerides (TG) levels between two groups of study subjects: P = 0.0004. (G) Comparative analysis of low-density lipoprotein (LDL) levels between two groups of study subjects: P = 0.0344. (H) Comparative analysis of total cholesterol (TC) levels between two groups of study subjects: P = 0.0778. (I) Comparison of high-density lipoprotein (HDL) levels between the two groups of subjects: P = 0.6494. (J) Metabolic pathways undergoing significant changes in fast achieved therapeutic windw (FAST) group compared to normal (NOR) group. (K) Glycerophospholipid metabolism pathway. (L) Volcano plot of differential metabolites. Differential metabolites (red and blue) and nondifferential substances (black) were determined under the con- ditions of fold change (FC) ≥ 1.2 and false discovery rate-adjusted P value threshold <0.05. (M) Orthogonal projections to latent structures discriminant analysis (OPLS-DA) score plots for vein plasma in electrospray ionization positive (ESI+) model. FAST group is shown in green, and NOR group is shown in blue. (N) Random Forest classification error rates over the number of trees for different classes. The overall error rate (red line), the FAST group (green line), and the NOR group (blue line) as a function of the number of trees in the random forest model.
In Figs 1F-I, Group 1: normolipidemic, normal diet, MTT; Group 2: normolipidemic, normal diet, MTT in corn oil; Group 3: hyperlipidemia, high-fat diet, MTT; Group 4: hyper- lipidemia; high-fat diet, MTT in corn oil; Group 5: hyperlipidemia, high-fat diet, MTT in corn oil, extra oil before execution.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jpha.2025.101252.
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