Clinica Chimica Acta 438 (2015) 7–11
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Effects of the ABCG2 and ABCB1 drug transporter polymorphisms on the pharmacokinetics of bicalutamide in humans Kyoung-Ah Kim, Yu-Jung Cha, Hae-Mi Lee, Hyun-Jin Joo, Ji-Young Park ⁎ Department of Clinical Pharmacology and Toxicology, Anam Hospital, Korea University College of Medicine, Seoul, Korea
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Article history: Received 3 July 2014 Received in revised form 4 August 2014 Accepted 4 August 2014 Available online 11 August 2014 Keywords: Bicalutamide Prostate cancer ABCB1 P-glycoprotein BCRP ABCG2
a b s t r a c t Backgrounds: Bicalutamide is an oral non-steroidal anti-androgen used in the treatment of prostate cancer. Drug transporters P-glycoprotein encoded by ABCB1 and breast cancer resistance protein (BCRP) encoded by ABCG2 are involved in the transportation of bicalutamide and its treatment failure. We evaluated the roles of ABCB1 and ABCG2 genetic polymorphisms in the pharmacokinetics of bicalutamide in humans. Methods: After a single oral dose of 150 mg bicalutamide was administered, plasma concentrations of bicalutamide were measured, and pharmacokinetic analyses were performed in 27 healthy subjects according to ABCB1 (c.1236C N T, c.2677G N T/A, and c.3435C N T) and ABCG2 (c.34G N A and c.421C N A). Results: ABCB1 polymorphisms did not affect the plasma levels of bicalutamide and the pharmacokinetic parameters did not differ among ABCB1 genotype groups. However, the ABCG2 c.421C N A polymorphism significantly influenced the plasma levels and pharmacokinetics of bicalutamide gene dose-dependently. Conclusions: The ABCB1 genetic polymorphisms did not influence the pharmacokinetics of bicalutamide. However, ABCG2 c.421C N A significantly and gene dose-dependently influenced its pharmacokinetics, but c.34G N A did not. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Prostate cancer is one of the most common forms of cancer in men and has an incidence second only to lung cancer in Europe and has the highest incidence of non-skin cancers in the US [1–3]. In the US population, the estimated numbers of new cases and deaths from prostate cancer are 234,460 (33% of new cases in men) and 27,350 (9% of cancer deaths in men), respectively [2,3]. Bicalutamide is a non-steroidal pure anti-androgen (NSAA) that acts competitively to block the growth-stimulating effects of androgens on prostate tumors [4]. It is used once daily at a dosage of 150 mg as monotherapy or at a dosage of 50 mg in combination with chemical or surgical castration. It is known that bicalutamide competes with the active hormone, 5α-dihydrotestosterone, for androgen receptor binding and activation and thus blocks the prostate tumor growth-stimulating effects of androgens [5]. In humans, the drug is excreted at similar rates in the urine (36%) and feces (42%) [4,6]. It has been reported that bicalutamide is mainly metabolized by the UGT1A9 enzyme through the process of glucuronidation [7]. In addition to drug metabolism, it has been reported that drug transporters, P-gp encoded by ABCB1 and BCRP (breast cancer resistance ⁎ Corresponding author at: Department of Clinical Pharmacology and Toxicology, Anam Hospital, Korea University College of Medicine, 126-1, 5-Ga, Anam-dong, Sungbuk-Gu, Seoul, 136-705, Korea. Tel.: +82 2 920 6288; fax: +82 2 929 3279. E-mail address: [email protected] (J.-Y. Park).
http://dx.doi.org/10.1016/j.cca.2014.08.006 0009-8981/© 2014 Elsevier B.V. All rights reserved.
protein) encoded by ABCG2, are involved in the disposition of bicalutamide [8]. It was suggested that these two drug transporters are involved in bicalutamide failure in prostate cancer treatment. Both of these drug transporters play important roles in the disposition of various drugs and genetic polymorphisms of these two genes influence the pharmacokinetics of their substrates [9,10]. However, there has been no available information on whether genetic polymorphisms of the ABCB1 and ABCG2 are associated with the disposition of bicalutamide. The objective of the present study was to assess the influence of ABCB1 and ABCG2 polymorphisms on the pharmacokinetic characteristics of bicalutamide and provide evidence that polymorphisms in these two genes influence inter-individual variability of bicalutamide pharmacokinetics in humans. 2. Materials and methods 2.1. Subjects and study design A total of 27 unrelated healthy Korean male subjects were enrolled in this study. The mean (±SD) age was 25 ± 2 years (range, 22–31 years), mean weight was 71.2 ± 7.5 kg (range, 55–89 kg), and mean height was 177 ± 5 cm (range, 165–186 cm). All subjects were confirmed to be healthy on the basis of a detailed physical examination, 12-lead electrocardiography, and laboratory tests. Subjects were excluded if they had a history of or evidence of a hepatic, renal, gastrointestinal, or hematologic abnormality, hepatitis B or C or HIV infection, any other acute or chronic
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disease, or an allergy to any drug. No subjects were taking any medication two weeks before study initiation or during the study period and all gave written informed consent. The study protocol was approved by the institutional review board of Anam Hospital, Korea University College of Medicine, Seoul, Korea. All subjects were admitted to the clinical trial center of Anam Hospital during the evening prior to the day of drug administration. After an overnight fast, subjects were given a single oral dose of 150 mg of bicalutamide (Casodex®; AstraZeneca Korea, Seoul, Korea) with 240 ml of water in the morning. Blood samples were collected in heparinized tubes (Vacutainer®; Becton Dickinson, Franklin Lakes, NJ, USA) immediately before drug administration (baseline) and then at 2, 4, 6, 8, 10, 12, 24, 36, 48, 60, 72, 96, 120, 264, 432, 600, and 768 hours after drug administration. The plasma was separated by centrifugation at 3000 ×g for 15 min and stored at −70 °C until analysis. 2.2. ABCB1 and ABCG2 genotyping DNA was extracted using standard methods according to the manufacturer's instructions (QIAamp DNA Blood Mini Kit; QIAGEN, Hilden, Germany). All subjects were genotyped for the ABCB1 c.1236C N T (rs1128503), ABCB1 c.2677G N T/A (rs2032582), ABCB1 c.3435C N T (rs1045642), ABCG2 c.421C N A (rs2231142), and ABCG2 c.34G N A (rs2231137) alleles by pyrosequencing methods as described previously [11,12]. 2.3. Drug analysis Plasma levels of bicalutamide were analyzed using a validated highperformance liquid chromatographic-mass spectrometric method (HPLC/MS/MS). Briefly, plasma samples (50 μl) were diluted with distilled water (950 μl) and then 50 μl of the solution was spiked with an internal standard (1 ml of 20 ng/ml nilutamide in acetonitrile). The samples were filtered using a square well filter plate and a 5 μl aliquot of the solution was injected into a Waters Quattro Micromass Premier XE (Waters, Milford, MA, USA) equipped with a Waters 2795 Alliance HT HPLC system (Waters, Milford, MA, USA). Chromatographic separation of the compounds was accomplished using a Luna C18 column (5 μm, 2.0 × 150 mm; Phenomenex, Torrance, CA, USA) with a mobile phase consisting of acetonitrile, methanol, and distilled water (60:10:30, vol/vol/vol). The mass spectrometer with an electrospray source was run in the positive mode and m/z 429.0 → 255.0 and 316.1 → 273.0 for bicalutamide and internal standards, respectively. Linearity calibration curves in the ranges of 50–3000 ng/ml for bicalutamide were established (r2 = 0.99923). The intraday and interday coefficients of variation (CV) were less than 7.6%. 2.4. Pharmacokinetic analysis The pharmacokinetic variables of bicalutamide were estimated by non-compartmental methods using WinNonlin version 5.3 (Pharsight, Cary, NC, USA). The peak concentrations (Cmax) and their time to reach Cmax (tmax) were estimated directly from the observed plasma concentration-time data. The AUClast (area under the time versus concentration curve from zero to the last measurable time) was calculated using the linear trapezoidal rule. The AUC from zero to infinity (AUCinf) was calculated as AUCinf = AUClast + Ct/ke (where Ct is the last plasma concentration measured). The elimination rate constant (ke) was determined by linear regression analysis of the log-linear part of the plasma concentration-time curve. The half-life (t1/2) of bicalutamide was calculated using the equation, half-life = ln2/ke. The apparent oral clearance (CL/ F) of bicalutamide was calculated as follows: CL/F = dose/AUCinf. 2.5. Statistical analysis Data are expressed as mean values ± SD in the text and tables and as mean values ± SEM in the figures. Statistical comparisons of all
pharmacokinetic variables between ABCB1 or ABCG2 genotype groups were carried out using analysis of variance, followed by a posteriori testing with the Student–Newman–Keuls (SNK) test. All statistical analyses were performed with SAS version 9.2 (SAS Institute, Inc., Cary, NC, USA). Linkage disequilibrium was tested according to the Hardy–Weinberg formula using SNPalyzer ver 7.0 software (Dynacom Co., Ltd., Yokohama, Japan). 3. Results 3.1. Effect of ABCB1 polymorphisms We first assessed whether ABCB1 genetic polymorphisms, including c.1236C N T, c.2677G N T/A, and c.3435C N T affected the pharmacokinetics of bicalutamide. When we assessed their roles in the bicalutamide plasma concentration profile changes, similar plasma concentration profiles of bicalutamide were observed irrespective of ABCB1 genotypes (Fig. 1). Additionally, the pharmacokinetic parameters of bicalutamide did not show any significant differences between ABCB1 genotype groups (Table 1). 3.2. Effect of ABCG2 polymorphisms We also evaluated the effects of ABCG2 genetic polymorphisms including c.34G N A and c.421C N A on the pharmacokinetics of bicalutamide. The ABCG2 c.34G N A genotype did not influence plasma levels of bicalutamide. However, ABCG2 c.421C N A influenced the plasma levels of bicalutamide such that subjects with c.421AA exhibited higher plasma levels than those with c.421CC or c.421CA (Fig. 2). The pharmacokinetics of bicalutamide did not differ between c.34G N A genotype groups whereas c.421C N A genotype substantially influenced its pharmacokinetics. The ABCG2 c.421C N A genotype increased the Cmax values of bicalutamide: 1.7 μg/ml for c.421, 1.8 μg/ml for c.421CA, and 2.2 μg/ml for c.421AA (P = 0.0155; Table 2). Furthermore, the average AUCinf value was 337 ng · hr/ml for c.421CC, 442 ng · hr/ml for c.421CA, and 552 ng · hr/ml for c.421AA (P b 0.001) and their average CL/F values were 0.44 L/hr, 0.33 L/hr, and 0.27 L/hr, respectively (P b 0.001; Fig. 3). When we assessed the linkage disequilibrium between the ABCG2 c.421C N A and c.34G N A polymorphisms, a weak linkage disequilibrium was found (D = −0.0528 and r2 = 0.0895). 4. Discussion Here we provide evidence that the ABCG2 c.421C N A genetic polymorphism influences the inter-individual variability of bicalutamide pharmacokinetics in humans. Furthermore, we also revealed that both ABCG2 c.34G N A and ABCB1 polymorphisms including c.1236C N T, c.2677G N T/A, and c.3435C N T play a minor role in the modulation of bicalutamide pharmacokinetics in humans. It was suggested that treatment failure of bicalutamide is related to multidrug resistance proteins, such as P-gp and BCRP, using an in vitro model, and that these transporters are involved in the transportation of bicalutamide [8]. Due to the polymorphic nature of these genes, which plays a crucial role in the modulation of pharmacokinetics of various substrates [9,10,13]. We observed that ABCG2 c.421C N A influenced plasma concentration profiles of bicalutamide and its pharmacokinetics in a gene dose-dependent manner in this study. Imai et al. showed that the c.421C N A polymorphism is associated with lower expression levels in vitro compared with wild-type ABCG2 [14]. Additionally, another study confirmed this finding by showing evidence that c.421C N A results in approximately 30%–40% lower expression levels compared to wild-type [15]. In this study, subjects with c.421AA and c.421CA exhibited approximately 61% and 30% higher systemic exposure of bicalutamide as compared with those with c.421CC, respectively. This finding indicates that bicalutamide pharmacokinetics were affected by the activity of the BCRP transporter and provides evidence that the
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Fig. 1. Mean (±SEM) plasma concentration profiles of bicalutamide after administration of 150 mg of bicalutamide according to ABCB1 c.1236C N T (A), c.2677G N T/A (B), and c.3435C N T (C) polymorphisms.
c.421C N A polymorphism plays a crucial role in the determination of the pharmacokinetics and plasma concentrations of bicalutamide. Similar to bicalutamide, the c.421C N A polymorphism is associated with variable pharmacokinetics and responses in certain ABCG2 substrates, such as leflunomide [16], diflomotecan [17], gefitinib [18], and topotecan [19]. In contrast to c.421C N A, the c.34G N A polymorphism did not influence the pharmacokinetics of bicalutamide in this study. Although it was reported that a c.34G N A variant decreased the transport activity of BCRP [20], it was also noted that the c.34G N A exhibited similar expression levels and drug resistance profiles to those of wild-type [14,20]. Intriguingly, bicalutamide shows ethnic differences in its pharmacokinetics: the average plasma concentrations of bicalutamide at the daily dose of 100 mg for 12 weeks were 23.7 μg/ml in Japanese patients (n = 34) and 16.6 μg/ml in Caucasian patients (n = 40) [4,21]. Although we do not fully understand the reasons why bicalutamide plasma levels
vary by ethnicity, it seems likely that difference in the frequency of the c.421C N A polymorphism might be at least partially attributable to this finding. Because the allele frequency of c.421C N A is approximately three-fold higher in Japanese populations (26.6%–35.0%) than in Caucasian populations (8.7%–11.3%), the overall plasma levels in Japanese populations might be higher and thus average plasma levels in this population might exhibit such differences [14,20,22–24]. On the other hand, ABCB1 polymorphisms including c.1236C N T, c.2677G N T/A, and c.3435C N T did not affect the plasma concentration profiles of bicalutamide or pharmacokinetics in this study. Despite evidence that P-gp is involved in the efflux of bicalutamide, our data confirmed that ABCB1 genotypes contribute little to the inter-individual variability in bicalutamide pharmacokinetics [8]. It was reported that bicalutamide showed an approximately 2-fold stronger affinity toward BCRP than P-gp in vitro (EC50 [the concentration of a drug that gives half-maximal response]; 73.5 μM for P-gp versus 31.0 μM for BCRP) suggesting that BCRP rather than P-gp might be the dominant efflux
Table 1 Pharmacokinetic parameters of bicalutamide after a single dose of 150 mg of bicalutamide according to ABCB1 genetic polymorphisms. ABCB1 c.1236C N T ke (hr−1) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr) ABCB1 c.2677G N T/A
c.1236CC (n = 2) 0.005 157 18 1.7 403 422 0.37
± ± ± ± ± ± ±
0.001 20 9 0.3 119 121 0.11
c.1236CT (n = 14)
c.1236TT (n = 11)
P-value
0.005 134 37 1.9 407 421 0.38
0.006 129 37 1.7 372 389 0.41
0.423 0.297 0.144 0.431 0.689 0.723 0.679
± ± ± ± ± ± ±
0.001 21 9 0.4 96 95 0.09
± ± ± ± ± ± ±
0.001 25 17 0.3 105 102 0.09
c.2677GG (n = 9)
c.2677GT (n = 5)
c.2677GA (n = 3)
c.2677TT (n = 8)
c.2766TA (n = 2)
P-value
ke (hr ) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
0.006 129.2 29 1.8 389 403.82 0.39
0.005 143.4 38 1.6 369 387 0.41
0.005 154.7 40 1.8 423 437 0.34
0.006 124 36 1.7 358 375 0.42
0.005 137.8 48 2.4 554 566.06 0.27
0.290 0.266 0.368 0.082 0.126 0.137 0.157
ABCB1 c.3435C N T
c.3435CC (n = 11)
−1
ke (hr−1) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
0.005 132 34 1.8 390 404 0.38
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 22.3634 11 0.3 76 77 0.08
0.001 21 9 0.3 64 64 0.07
± ± ± ± ± ± ±
0.001 18.8 13 0.3 122 120 0.11
± ± ± ± ± ± ±
0.000 8.97501 7 0.2 25 26 0.02
± ± ± ± ± ± ±
0.002 27.3 17 0.2 96 93 0.09
± ± ± ± ± ± ±
0.000 0.24084 0 0.6 105 107 0.05
c.3435CT (n = 9)
c.3435TT (n = 7)
P-value
0.005 138 36 1.8 410 428 0.38
0.006 131 38 1.7 372 389 0.40
0.947 0.801 0.832 0.575 0.757 0.718 0.880
± ± ± ± ± ± ±
0.002 28 15 0.5 137 134 0.12
± ± ± ± ± ± ±
0.001 22 18 0.2 94 92 0.09
Data are given as mean ± SD. ke, elimination rate constant; Cmax, peak plasma concentration; tmax, time to peak plasma concentration; AUClast, area under plasma concentration-time curve from time 0 to 768 hours (last available measurement); AUCinf, area under plasma concentration-time curve from time 0 to infinity; CL/F, oral clearance.
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Fig. 2. Mean (± SEM) plasma concentration profiles of bicalutamide after oral administration of 150 mg of bicalutamide according to ABCG2 c.34G N A (A) and c.421C NA (B) polymorphisms.
transporter of bicalutamide [8]. Therefore, because of the relatively lower affinity for bicalutamide, it appears that ABCB1 genetic polymorphisms have a minor impact on the disposition of this drug. ABCG2 physiologically mediates renal uric acid excretion as well as extra-renal (intestinal) uric acid excretion, and its dysfunctional mutations are risk factors for hyperuricemia [25,26]. Genome-wide association studies have revealed that ABCG2 polymorphism, especially c.421C N A, is associated with serum uric acid levels and the prevalence of gout [27,28]. When we compared the uric acid levels measured just before bicalutamide treatment according to ABCB1 and ABCG2 polymorphisms in this study, ABCG2 c.421C N A polymorphism but not c.34G N A significantly influenced serum uric acid levels (Supplementary Table 1). These findings are consistent with the previous data [16,27,28] and support that ABCG2 polymorphisms, especially c.421C N A, influence serum uric acid levels and that serum uric acid is a substrate of ABCG2 transporter. Additionally, a significant correlation between serum uric acid levels and bicalutamide pharmacokinetics is shown (Supplementary Fig. 1). These findings strongly suggest that both uric acid and bicalutamide are substrates of the same transporter, i.e., ABCG2. However, none of ABCB1 polymorphisms influenced serum uric acid levels in this study (Supplementary Table 1).
The study has some limitations that should be acknowledged. First, this is a single-dose study in which we evaluated the variance in the pharmacokinetics of bicalutamide associated with different ABCB1 and ABCG2 genotypes. Second, to exclude confounding factors affecting its pharmacokinetics, the present study was conducted in healthy subjects rather than in patients [4]. However, considering the comparable pharmacokinetics between healthy subjects and patient groups [4], we believe the effects of these polymorphisms on the bicalutamide pharmacokinetics in patients are similar to healthy subjects. Additionally, owing to a relatively small number of participants (n = 27) in this study, we could not perform haplotype analysis for both ABCB1 and ABCG2 polymorphisms on the pharmacokinetic characteristics of bicalutamide. In conclusion, the ABCG2 c.421C N A genetic polymorphism is a main factor to influence plasma levels and pharmacokinetics of bicalutamide. However, ABCB1 genetic polymorphisms including c.1236C N T, c.2677G/T/A, c.3435C N T, and ABCG2 c.34G N A played minor roles in the bicalutamide pharmacokinetics in this study. These findings suggest that the ABCG2 c.421C N A genetic polymorphism affects the disposition of bicalutamide and provides a plausible explanation for inter-individual variation in the disposition of this drug.
Table 2 Pharmacokinetic parameters of bicalutamide after a single dose of 150 mg of bicalutamide according to ABCG2 genetic polymorphisms. ABCG2 c.421C N A
c.421CC (n = 17)
c.421CA (n = 6)
c.421AA (n = 4)
P-value
ke (hr−1) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
0.006 125 31 1.7 337 353 0.44
0.005 151 40 1.8 442 458 0.33
0.005 148 48 2.2 552 567 0.27
0.041 0.015 0.036# 0.016#,§ b0.001⁎,#,§ b0.001⁎,#,§
ABCG2 c.34G N A
c.34GG (n = 19)
c.34GA (n = 5)
c.34AA (n = 3)
0.005 135 35 1.8 390 406 0.39
0.005 133 41 1.8 428 443 0.34
0.005 129 32 1.7 350 365 0.42
−1
ke (hr ) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 22 9 0.3 61 59 0.07
0.001 24 14 0.4 109 107 0.10
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 15 6 0.1 47 43 0.03
0.001 24 7 0.1 62 60 0.05
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 16 26 0.4 61 59 0.03
0.001 16 18 0.2 73 69 0.08
b0.001#,§ P-value 0.997 0.926 0.596 0.879 0.561 0.556 0.465
Data are given as mean ± SD. ke, elimination rate constant; Cmax, peak plasma concentration; tmax, time to peak plasma concentration; AUClast, area under plasma concentration-time curve from time 0 to 768 hours (last available measurement); AUCinf, area under plasma concentration-time curve from time 0 to infinity; CL/F, oral clearance. ⁎ P b 0.05 by ANOVA with post hoc comparisons between ABCG2 c.421CC and c.421CA genotype groups. # P b 0.05 by ANOVA with post hoc comparisons between ABCG2 c.421CC and c.421AA genotype groups. § P b 0.05 by ANOVA with post hoc comparisons between ABCG2 c.421CA and c.421AA genotype groups.
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Fig. 3. Box plots for the comparisons of Cmax (A), AUCinf (B), and CL/F (C) of bicalutamide according to the ABCG2 c.421C NA polymorphism.
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Effects of the ABCG2 and ABCB1 drug transporter polymorphisms on the pharmacokinetics of bicalutamide in humans Kyoung-Ah Kim, Yu-Jung Cha, Hae-Mi Lee, Hyun-Jin Joo, Ji-Young Park ⁎ Department of Clinical Pharmacology and Toxicology, Anam Hospital, Korea University College of Medicine, Seoul, Korea
a r t i c l e
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Article history: Received 3 July 2014 Received in revised form 4 August 2014 Accepted 4 August 2014 Available online 11 August 2014 Keywords: Bicalutamide Prostate cancer ABCB1 P-glycoprotein BCRP ABCG2
a b s t r a c t Backgrounds: Bicalutamide is an oral non-steroidal anti-androgen used in the treatment of prostate cancer. Drug transporters P-glycoprotein encoded by ABCB1 and breast cancer resistance protein (BCRP) encoded by ABCG2 are involved in the transportation of bicalutamide and its treatment failure. We evaluated the roles of ABCB1 and ABCG2 genetic polymorphisms in the pharmacokinetics of bicalutamide in humans. Methods: After a single oral dose of 150 mg bicalutamide was administered, plasma concentrations of bicalutamide were measured, and pharmacokinetic analyses were performed in 27 healthy subjects according to ABCB1 (c.1236C N T, c.2677G N T/A, and c.3435C N T) and ABCG2 (c.34G N A and c.421C N A). Results: ABCB1 polymorphisms did not affect the plasma levels of bicalutamide and the pharmacokinetic parameters did not differ among ABCB1 genotype groups. However, the ABCG2 c.421C N A polymorphism significantly influenced the plasma levels and pharmacokinetics of bicalutamide gene dose-dependently. Conclusions: The ABCB1 genetic polymorphisms did not influence the pharmacokinetics of bicalutamide. However, ABCG2 c.421C N A significantly and gene dose-dependently influenced its pharmacokinetics, but c.34G N A did not. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Prostate cancer is one of the most common forms of cancer in men and has an incidence second only to lung cancer in Europe and has the highest incidence of non-skin cancers in the US [1–3]. In the US population, the estimated numbers of new cases and deaths from prostate cancer are 234,460 (33% of new cases in men) and 27,350 (9% of cancer deaths in men), respectively [2,3]. Bicalutamide is a non-steroidal pure anti-androgen (NSAA) that acts competitively to block the growth-stimulating effects of androgens on prostate tumors [4]. It is used once daily at a dosage of 150 mg as monotherapy or at a dosage of 50 mg in combination with chemical or surgical castration. It is known that bicalutamide competes with the active hormone, 5α-dihydrotestosterone, for androgen receptor binding and activation and thus blocks the prostate tumor growth-stimulating effects of androgens [5]. In humans, the drug is excreted at similar rates in the urine (36%) and feces (42%) [4,6]. It has been reported that bicalutamide is mainly metabolized by the UGT1A9 enzyme through the process of glucuronidation [7]. In addition to drug metabolism, it has been reported that drug transporters, P-gp encoded by ABCB1 and BCRP (breast cancer resistance ⁎ Corresponding author at: Department of Clinical Pharmacology and Toxicology, Anam Hospital, Korea University College of Medicine, 126-1, 5-Ga, Anam-dong, Sungbuk-Gu, Seoul, 136-705, Korea. Tel.: +82 2 920 6288; fax: +82 2 929 3279. E-mail address: [email protected] (J.-Y. Park).
http://dx.doi.org/10.1016/j.cca.2014.08.006 0009-8981/© 2014 Elsevier B.V. All rights reserved.
protein) encoded by ABCG2, are involved in the disposition of bicalutamide [8]. It was suggested that these two drug transporters are involved in bicalutamide failure in prostate cancer treatment. Both of these drug transporters play important roles in the disposition of various drugs and genetic polymorphisms of these two genes influence the pharmacokinetics of their substrates [9,10]. However, there has been no available information on whether genetic polymorphisms of the ABCB1 and ABCG2 are associated with the disposition of bicalutamide. The objective of the present study was to assess the influence of ABCB1 and ABCG2 polymorphisms on the pharmacokinetic characteristics of bicalutamide and provide evidence that polymorphisms in these two genes influence inter-individual variability of bicalutamide pharmacokinetics in humans. 2. Materials and methods 2.1. Subjects and study design A total of 27 unrelated healthy Korean male subjects were enrolled in this study. The mean (±SD) age was 25 ± 2 years (range, 22–31 years), mean weight was 71.2 ± 7.5 kg (range, 55–89 kg), and mean height was 177 ± 5 cm (range, 165–186 cm). All subjects were confirmed to be healthy on the basis of a detailed physical examination, 12-lead electrocardiography, and laboratory tests. Subjects were excluded if they had a history of or evidence of a hepatic, renal, gastrointestinal, or hematologic abnormality, hepatitis B or C or HIV infection, any other acute or chronic
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disease, or an allergy to any drug. No subjects were taking any medication two weeks before study initiation or during the study period and all gave written informed consent. The study protocol was approved by the institutional review board of Anam Hospital, Korea University College of Medicine, Seoul, Korea. All subjects were admitted to the clinical trial center of Anam Hospital during the evening prior to the day of drug administration. After an overnight fast, subjects were given a single oral dose of 150 mg of bicalutamide (Casodex®; AstraZeneca Korea, Seoul, Korea) with 240 ml of water in the morning. Blood samples were collected in heparinized tubes (Vacutainer®; Becton Dickinson, Franklin Lakes, NJ, USA) immediately before drug administration (baseline) and then at 2, 4, 6, 8, 10, 12, 24, 36, 48, 60, 72, 96, 120, 264, 432, 600, and 768 hours after drug administration. The plasma was separated by centrifugation at 3000 ×g for 15 min and stored at −70 °C until analysis. 2.2. ABCB1 and ABCG2 genotyping DNA was extracted using standard methods according to the manufacturer's instructions (QIAamp DNA Blood Mini Kit; QIAGEN, Hilden, Germany). All subjects were genotyped for the ABCB1 c.1236C N T (rs1128503), ABCB1 c.2677G N T/A (rs2032582), ABCB1 c.3435C N T (rs1045642), ABCG2 c.421C N A (rs2231142), and ABCG2 c.34G N A (rs2231137) alleles by pyrosequencing methods as described previously [11,12]. 2.3. Drug analysis Plasma levels of bicalutamide were analyzed using a validated highperformance liquid chromatographic-mass spectrometric method (HPLC/MS/MS). Briefly, plasma samples (50 μl) were diluted with distilled water (950 μl) and then 50 μl of the solution was spiked with an internal standard (1 ml of 20 ng/ml nilutamide in acetonitrile). The samples were filtered using a square well filter plate and a 5 μl aliquot of the solution was injected into a Waters Quattro Micromass Premier XE (Waters, Milford, MA, USA) equipped with a Waters 2795 Alliance HT HPLC system (Waters, Milford, MA, USA). Chromatographic separation of the compounds was accomplished using a Luna C18 column (5 μm, 2.0 × 150 mm; Phenomenex, Torrance, CA, USA) with a mobile phase consisting of acetonitrile, methanol, and distilled water (60:10:30, vol/vol/vol). The mass spectrometer with an electrospray source was run in the positive mode and m/z 429.0 → 255.0 and 316.1 → 273.0 for bicalutamide and internal standards, respectively. Linearity calibration curves in the ranges of 50–3000 ng/ml for bicalutamide were established (r2 = 0.99923). The intraday and interday coefficients of variation (CV) were less than 7.6%. 2.4. Pharmacokinetic analysis The pharmacokinetic variables of bicalutamide were estimated by non-compartmental methods using WinNonlin version 5.3 (Pharsight, Cary, NC, USA). The peak concentrations (Cmax) and their time to reach Cmax (tmax) were estimated directly from the observed plasma concentration-time data. The AUClast (area under the time versus concentration curve from zero to the last measurable time) was calculated using the linear trapezoidal rule. The AUC from zero to infinity (AUCinf) was calculated as AUCinf = AUClast + Ct/ke (where Ct is the last plasma concentration measured). The elimination rate constant (ke) was determined by linear regression analysis of the log-linear part of the plasma concentration-time curve. The half-life (t1/2) of bicalutamide was calculated using the equation, half-life = ln2/ke. The apparent oral clearance (CL/ F) of bicalutamide was calculated as follows: CL/F = dose/AUCinf. 2.5. Statistical analysis Data are expressed as mean values ± SD in the text and tables and as mean values ± SEM in the figures. Statistical comparisons of all
pharmacokinetic variables between ABCB1 or ABCG2 genotype groups were carried out using analysis of variance, followed by a posteriori testing with the Student–Newman–Keuls (SNK) test. All statistical analyses were performed with SAS version 9.2 (SAS Institute, Inc., Cary, NC, USA). Linkage disequilibrium was tested according to the Hardy–Weinberg formula using SNPalyzer ver 7.0 software (Dynacom Co., Ltd., Yokohama, Japan). 3. Results 3.1. Effect of ABCB1 polymorphisms We first assessed whether ABCB1 genetic polymorphisms, including c.1236C N T, c.2677G N T/A, and c.3435C N T affected the pharmacokinetics of bicalutamide. When we assessed their roles in the bicalutamide plasma concentration profile changes, similar plasma concentration profiles of bicalutamide were observed irrespective of ABCB1 genotypes (Fig. 1). Additionally, the pharmacokinetic parameters of bicalutamide did not show any significant differences between ABCB1 genotype groups (Table 1). 3.2. Effect of ABCG2 polymorphisms We also evaluated the effects of ABCG2 genetic polymorphisms including c.34G N A and c.421C N A on the pharmacokinetics of bicalutamide. The ABCG2 c.34G N A genotype did not influence plasma levels of bicalutamide. However, ABCG2 c.421C N A influenced the plasma levels of bicalutamide such that subjects with c.421AA exhibited higher plasma levels than those with c.421CC or c.421CA (Fig. 2). The pharmacokinetics of bicalutamide did not differ between c.34G N A genotype groups whereas c.421C N A genotype substantially influenced its pharmacokinetics. The ABCG2 c.421C N A genotype increased the Cmax values of bicalutamide: 1.7 μg/ml for c.421, 1.8 μg/ml for c.421CA, and 2.2 μg/ml for c.421AA (P = 0.0155; Table 2). Furthermore, the average AUCinf value was 337 ng · hr/ml for c.421CC, 442 ng · hr/ml for c.421CA, and 552 ng · hr/ml for c.421AA (P b 0.001) and their average CL/F values were 0.44 L/hr, 0.33 L/hr, and 0.27 L/hr, respectively (P b 0.001; Fig. 3). When we assessed the linkage disequilibrium between the ABCG2 c.421C N A and c.34G N A polymorphisms, a weak linkage disequilibrium was found (D = −0.0528 and r2 = 0.0895). 4. Discussion Here we provide evidence that the ABCG2 c.421C N A genetic polymorphism influences the inter-individual variability of bicalutamide pharmacokinetics in humans. Furthermore, we also revealed that both ABCG2 c.34G N A and ABCB1 polymorphisms including c.1236C N T, c.2677G N T/A, and c.3435C N T play a minor role in the modulation of bicalutamide pharmacokinetics in humans. It was suggested that treatment failure of bicalutamide is related to multidrug resistance proteins, such as P-gp and BCRP, using an in vitro model, and that these transporters are involved in the transportation of bicalutamide [8]. Due to the polymorphic nature of these genes, which plays a crucial role in the modulation of pharmacokinetics of various substrates [9,10,13]. We observed that ABCG2 c.421C N A influenced plasma concentration profiles of bicalutamide and its pharmacokinetics in a gene dose-dependent manner in this study. Imai et al. showed that the c.421C N A polymorphism is associated with lower expression levels in vitro compared with wild-type ABCG2 [14]. Additionally, another study confirmed this finding by showing evidence that c.421C N A results in approximately 30%–40% lower expression levels compared to wild-type [15]. In this study, subjects with c.421AA and c.421CA exhibited approximately 61% and 30% higher systemic exposure of bicalutamide as compared with those with c.421CC, respectively. This finding indicates that bicalutamide pharmacokinetics were affected by the activity of the BCRP transporter and provides evidence that the
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Fig. 1. Mean (±SEM) plasma concentration profiles of bicalutamide after administration of 150 mg of bicalutamide according to ABCB1 c.1236C N T (A), c.2677G N T/A (B), and c.3435C N T (C) polymorphisms.
c.421C N A polymorphism plays a crucial role in the determination of the pharmacokinetics and plasma concentrations of bicalutamide. Similar to bicalutamide, the c.421C N A polymorphism is associated with variable pharmacokinetics and responses in certain ABCG2 substrates, such as leflunomide [16], diflomotecan [17], gefitinib [18], and topotecan [19]. In contrast to c.421C N A, the c.34G N A polymorphism did not influence the pharmacokinetics of bicalutamide in this study. Although it was reported that a c.34G N A variant decreased the transport activity of BCRP [20], it was also noted that the c.34G N A exhibited similar expression levels and drug resistance profiles to those of wild-type [14,20]. Intriguingly, bicalutamide shows ethnic differences in its pharmacokinetics: the average plasma concentrations of bicalutamide at the daily dose of 100 mg for 12 weeks were 23.7 μg/ml in Japanese patients (n = 34) and 16.6 μg/ml in Caucasian patients (n = 40) [4,21]. Although we do not fully understand the reasons why bicalutamide plasma levels
vary by ethnicity, it seems likely that difference in the frequency of the c.421C N A polymorphism might be at least partially attributable to this finding. Because the allele frequency of c.421C N A is approximately three-fold higher in Japanese populations (26.6%–35.0%) than in Caucasian populations (8.7%–11.3%), the overall plasma levels in Japanese populations might be higher and thus average plasma levels in this population might exhibit such differences [14,20,22–24]. On the other hand, ABCB1 polymorphisms including c.1236C N T, c.2677G N T/A, and c.3435C N T did not affect the plasma concentration profiles of bicalutamide or pharmacokinetics in this study. Despite evidence that P-gp is involved in the efflux of bicalutamide, our data confirmed that ABCB1 genotypes contribute little to the inter-individual variability in bicalutamide pharmacokinetics [8]. It was reported that bicalutamide showed an approximately 2-fold stronger affinity toward BCRP than P-gp in vitro (EC50 [the concentration of a drug that gives half-maximal response]; 73.5 μM for P-gp versus 31.0 μM for BCRP) suggesting that BCRP rather than P-gp might be the dominant efflux
Table 1 Pharmacokinetic parameters of bicalutamide after a single dose of 150 mg of bicalutamide according to ABCB1 genetic polymorphisms. ABCB1 c.1236C N T ke (hr−1) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr) ABCB1 c.2677G N T/A
c.1236CC (n = 2) 0.005 157 18 1.7 403 422 0.37
± ± ± ± ± ± ±
0.001 20 9 0.3 119 121 0.11
c.1236CT (n = 14)
c.1236TT (n = 11)
P-value
0.005 134 37 1.9 407 421 0.38
0.006 129 37 1.7 372 389 0.41
0.423 0.297 0.144 0.431 0.689 0.723 0.679
± ± ± ± ± ± ±
0.001 21 9 0.4 96 95 0.09
± ± ± ± ± ± ±
0.001 25 17 0.3 105 102 0.09
c.2677GG (n = 9)
c.2677GT (n = 5)
c.2677GA (n = 3)
c.2677TT (n = 8)
c.2766TA (n = 2)
P-value
ke (hr ) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
0.006 129.2 29 1.8 389 403.82 0.39
0.005 143.4 38 1.6 369 387 0.41
0.005 154.7 40 1.8 423 437 0.34
0.006 124 36 1.7 358 375 0.42
0.005 137.8 48 2.4 554 566.06 0.27
0.290 0.266 0.368 0.082 0.126 0.137 0.157
ABCB1 c.3435C N T
c.3435CC (n = 11)
−1
ke (hr−1) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
0.005 132 34 1.8 390 404 0.38
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 22.3634 11 0.3 76 77 0.08
0.001 21 9 0.3 64 64 0.07
± ± ± ± ± ± ±
0.001 18.8 13 0.3 122 120 0.11
± ± ± ± ± ± ±
0.000 8.97501 7 0.2 25 26 0.02
± ± ± ± ± ± ±
0.002 27.3 17 0.2 96 93 0.09
± ± ± ± ± ± ±
0.000 0.24084 0 0.6 105 107 0.05
c.3435CT (n = 9)
c.3435TT (n = 7)
P-value
0.005 138 36 1.8 410 428 0.38
0.006 131 38 1.7 372 389 0.40
0.947 0.801 0.832 0.575 0.757 0.718 0.880
± ± ± ± ± ± ±
0.002 28 15 0.5 137 134 0.12
± ± ± ± ± ± ±
0.001 22 18 0.2 94 92 0.09
Data are given as mean ± SD. ke, elimination rate constant; Cmax, peak plasma concentration; tmax, time to peak plasma concentration; AUClast, area under plasma concentration-time curve from time 0 to 768 hours (last available measurement); AUCinf, area under plasma concentration-time curve from time 0 to infinity; CL/F, oral clearance.
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Fig. 2. Mean (± SEM) plasma concentration profiles of bicalutamide after oral administration of 150 mg of bicalutamide according to ABCG2 c.34G N A (A) and c.421C NA (B) polymorphisms.
transporter of bicalutamide [8]. Therefore, because of the relatively lower affinity for bicalutamide, it appears that ABCB1 genetic polymorphisms have a minor impact on the disposition of this drug. ABCG2 physiologically mediates renal uric acid excretion as well as extra-renal (intestinal) uric acid excretion, and its dysfunctional mutations are risk factors for hyperuricemia [25,26]. Genome-wide association studies have revealed that ABCG2 polymorphism, especially c.421C N A, is associated with serum uric acid levels and the prevalence of gout [27,28]. When we compared the uric acid levels measured just before bicalutamide treatment according to ABCB1 and ABCG2 polymorphisms in this study, ABCG2 c.421C N A polymorphism but not c.34G N A significantly influenced serum uric acid levels (Supplementary Table 1). These findings are consistent with the previous data [16,27,28] and support that ABCG2 polymorphisms, especially c.421C N A, influence serum uric acid levels and that serum uric acid is a substrate of ABCG2 transporter. Additionally, a significant correlation between serum uric acid levels and bicalutamide pharmacokinetics is shown (Supplementary Fig. 1). These findings strongly suggest that both uric acid and bicalutamide are substrates of the same transporter, i.e., ABCG2. However, none of ABCB1 polymorphisms influenced serum uric acid levels in this study (Supplementary Table 1).
The study has some limitations that should be acknowledged. First, this is a single-dose study in which we evaluated the variance in the pharmacokinetics of bicalutamide associated with different ABCB1 and ABCG2 genotypes. Second, to exclude confounding factors affecting its pharmacokinetics, the present study was conducted in healthy subjects rather than in patients [4]. However, considering the comparable pharmacokinetics between healthy subjects and patient groups [4], we believe the effects of these polymorphisms on the bicalutamide pharmacokinetics in patients are similar to healthy subjects. Additionally, owing to a relatively small number of participants (n = 27) in this study, we could not perform haplotype analysis for both ABCB1 and ABCG2 polymorphisms on the pharmacokinetic characteristics of bicalutamide. In conclusion, the ABCG2 c.421C N A genetic polymorphism is a main factor to influence plasma levels and pharmacokinetics of bicalutamide. However, ABCB1 genetic polymorphisms including c.1236C N T, c.2677G/T/A, c.3435C N T, and ABCG2 c.34G N A played minor roles in the bicalutamide pharmacokinetics in this study. These findings suggest that the ABCG2 c.421C N A genetic polymorphism affects the disposition of bicalutamide and provides a plausible explanation for inter-individual variation in the disposition of this drug.
Table 2 Pharmacokinetic parameters of bicalutamide after a single dose of 150 mg of bicalutamide according to ABCG2 genetic polymorphisms. ABCG2 c.421C N A
c.421CC (n = 17)
c.421CA (n = 6)
c.421AA (n = 4)
P-value
ke (hr−1) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
0.006 125 31 1.7 337 353 0.44
0.005 151 40 1.8 442 458 0.33
0.005 148 48 2.2 552 567 0.27
0.041 0.015 0.036# 0.016#,§ b0.001⁎,#,§ b0.001⁎,#,§
ABCG2 c.34G N A
c.34GG (n = 19)
c.34GA (n = 5)
c.34AA (n = 3)
0.005 135 35 1.8 390 406 0.39
0.005 133 41 1.8 428 443 0.34
0.005 129 32 1.7 350 365 0.42
−1
ke (hr ) half-life (hr) tmax (hr) Cmax (μg/ml) AUCall (μg · hr/ml) AUCinf (μg · hr/ml) CL/F (L/hr)
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 22 9 0.3 61 59 0.07
0.001 24 14 0.4 109 107 0.10
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 15 6 0.1 47 43 0.03
0.001 24 7 0.1 62 60 0.05
± ± ± ± ± ± ±
± ± ± ± ± ± ±
0.001 16 26 0.4 61 59 0.03
0.001 16 18 0.2 73 69 0.08
b0.001#,§ P-value 0.997 0.926 0.596 0.879 0.561 0.556 0.465
Data are given as mean ± SD. ke, elimination rate constant; Cmax, peak plasma concentration; tmax, time to peak plasma concentration; AUClast, area under plasma concentration-time curve from time 0 to 768 hours (last available measurement); AUCinf, area under plasma concentration-time curve from time 0 to infinity; CL/F, oral clearance. ⁎ P b 0.05 by ANOVA with post hoc comparisons between ABCG2 c.421CC and c.421CA genotype groups. # P b 0.05 by ANOVA with post hoc comparisons between ABCG2 c.421CC and c.421AA genotype groups. § P b 0.05 by ANOVA with post hoc comparisons between ABCG2 c.421CA and c.421AA genotype groups.
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Fig. 3. Box plots for the comparisons of Cmax (A), AUCinf (B), and CL/F (C) of bicalutamide according to the ABCG2 c.421C NA polymorphism.
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