assessment of the impact of polymorphisms of cyp3a on the...

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Assessment of the impact of polymorphisms of CYP3A on the formation of α-hydroxy tamoxifen and N-desmethyl

tamoxifen in human liver microsomes

Ganesh M. Mugundu, Larry Sallans, Yingying Guo, Elizabeth A.

Shaughnessy and Pankaj B. Desai

Division of Pharmaceutical Sciences, James L. Winkle College of Pharmacy,

University of Cincinnati Medical Center (GMM, PBD), Mass Spectrometry

Facility (LS), Drug Disposition, Lilly Research Laboratories (YG) and the

Barrett Cancer Center (EAS), University of Cincinnati

DMD Fast Forward. Published on November 17, 2011 as doi:10.1124/dmd.111.039388

Copyright 2011 by the American Society for Pharmacology and Experimental Therapeutics.

This article has not been copyedited and formatted. The final version may differ from this version.DMD Fast Forward. Published on November 17, 2011 as DOI: 10.1124/dmd.111.039388

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Running Title: CYP3A polymorphisms and tamoxifen metabolism

Corresponding Author:

Pankaj B. Desai, Ph.D.

Professor of Pharmacokinetics and Biopharmaceutics

Director, Drug Development Graduate Program

James L. Winkle College of Pharmacy, University of Cincinnati Medical Center

3223 Eden Avenue, Cincinnati, OH 45267-0004

Phone : (513) 558-3870

Fax No. : (513) 558-0978

Email : [email protected]

Manuscript Details: Number of text pages: 29 Number of tables: 3 (including Appendix) Number of figures: 10 Number of references: 39 Number of words in the Abstract: 250 Number of words in the Introduction: 590 Number of words in Results: 884 Number of words in Discussion: 1151 Abbreviations: P450, cytochrome P450; CYP3A, cytochrome P450 3A; rCYP3A, recombinant CYP3A; HLM,

human liver microsomes; TAM, tamoxifen; α-OHT, α-hydroxy tamoxifen; N-DMT, N-

desmethyl tamoxifen, 4-OHT , 4-hydroxy-tamoxifen, CLint, intrinsic clearance


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Abstract

Tamoxifen (TAM), an anti-estrogen used in the prevention and the treatment of breast cancer, is

extensively metabolized by cytochrome P450 enzymes. Its biotransformation to α-hydroxy

tamoxifen (α-OHT), a metabolite that may be genotoxic, and to N-desmethyl tamoxifen (N-

DMT), which is partially hydroxylated to 4-hydroxy-N-DMT (endoxifen), a potent anti-estrogen,

is mediated by CYP3A enzymes. However, the potential contribution of CYP3A5 and the

impact of its low expression variants on the formation of these metabolites are not clear. Thus,

we assessed the contributions of CYP3A4 and CYP3A5, and examined the impact of CYP3A5

genotypes on the formation of α-OHT and N-DMT employing recombinant CYP3A4, CYP3A5

and human liver microsomes (HLMs) genotyped for CYP3A5 variants. We observed that the

catalytic efficiency (intrinsic clearance, CLint) for α-OHT formation by rCYP3A4 was 5-fold

higher than by rCYP3A5 (0.81 Vs 0.16 nl/min/pmol P450). There was no significant difference

in the CLint values between the three CYP3A5 genotyped HLMs (*1/*1, *1/*3 and *3/*3). For

N-DMT formation, CLint by rCYP3A4 was only 1.7 fold higher relative to that by rCYP3A5.

Also, the CLint for N-DMT formation by HLMs with CYP3A5*3/*3 alleles was approximately

3-fold lower than that with HLMs expressing CYP3A5*1/*1. Regression analyses of tamoxifen

metabolism against testosterone 6β- hydroxylation facilitated an assessment of CYP3A5

contribution to the formation of the two metabolites. The CYP3A5 contribution to α-OHT

formation was negligible, whereas it ranged from 51 - 61% for N-DMT formation. Our findings

suggest that polymorphic CYP3A5 expression may impact formation of N-DMT, but not that of

α-OHT.


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Introduction

Tamoxifen (TAM), a selective estrogen receptor modulator (SERM), has been used in the

treatment and prevention of estrogen receptor positive tumors for over three decades (Bao et al.

2006; Fisher et al. 2005). Even with the advent of novel anti-estrogens such as aromatase

inhibitors, TAM continues to be the only endocrine agent approved for use in pre-menopausal

women (Ligibel and Winer 2005). Despite these advantages and a strong track record of

efficacious use, TAM is associated with significant clinical problems. These include extensive

inter-individual variability in its pharmacokinetics and therapeutic outcome, drug-drug

interactions, acquired drug resistance and increased risk of endometrial cancer (Fisher et al.

2005; Ligibel and Winer 2005; White 1999). Given that TAM systemic clearance primarily

entails hepatic metabolism, the observed inter-patient variability may be largely due to

differences in the expression and activity of drug metabolizing enzymes.

TAM undergoes extensive metabolism via phase 1 and 2 reactions to form a large number of

metabolites. The biotransformation of TAM is primarily mediated by cytochrome-P450

enzymes, mainly through N-demethylation and hydroxylation to form N-desmethyl-TAM (N-

DMT), 4-hydroxy-TAM (4-OHT) and α-hydroxy-TAM (α-OHT). N-DMT is the major

metabolite and with its high abundance and long half-life its steady state plasma levels often

exceed that of TAM (Lonning et al., 1992; Stearns et al., 2003). N-DMT is further hydroxylated

by CYP2D6 to form endoxifen, which is a considerably more potent anti-estrogen than TAM

(Desta et al. 2004, Lim et al., 2006). Several earlier studies have identified the role of CYP3A4

in the formation of N-DMT and α-OHT (Crewe et al., 1997, Desta et.al., 2004 and Notley et al.,


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2005). α-OHT is further activated by sulfotransferases to form electrophilic carbocation that is

capable of reacting with DNA. Formation of such DNA adducts in the endometrium is

postulated to be one of the contributing factors leading to the development of endometrial cancer

(Kim, et al., 2005;Shibutani, et al., 1998). TAM and its metabolites also undergo conjugations

by human UDP glucuronosyl transferases (UGTs) and sulfotransferases before systemic

elimination. (Poon, et al., 1993; Nishiyama, et al., 2002; Ogura, et al., 2006)

A quantitative comparison of the catalytic efficiencies of CYP3A4 and CYP3A5 in the

formation of α-OHT and the potential impact of polymorphic expression of these enzymes on the

formation of α-OHT and N-DMT is lacking. Relative to CYP3A4, the expression of CYP3A5 is

typically low. However, CYP3A5 is polymorphically expressed and in some individuals

CYP3A5 may represent up to 50% of the total hepatic CYP3A content (Kuehl et al. 2001).

Several low expression variants have been identified in CYP3A5. The most common variant,

CYP3A5*3 allele results in a loss of enzyme activity, and is prevalently expressed in most of the

populations studied ( Kuehl et al. 2001; Hustert et al. 2001; Lamba et al. 2002). Numerous

studies have underscored the association between CYP3A5*3 genotype, the most common

nonfunctional variant of CYP3A5 (a G>A change at position 22893), and altered drug

metabolism and pharmacokinetics of various drugs such as tacrolimus, cyclosporine, vincristine

and vardenafil (Thervet et al. 2003; Haufroid et al. 2004; Kivisto et al. 2004; Dennison et al.

2007; Ku et al. 2008). The potential impact of low expression CYP3A5 alleles on N-

demethylation and α-hydroxylation of TAM remains to be delineated. This is important given

the large inter-subject variability in the metabolism of TAM and the pharmacological and

toxicological effects of the metabolites formed. Accordingly, employing in vitro tools, we


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compared the catalytic efficiency of CYP3A4 and CYP3A5 on the formation of N-DMT and α-

OHT and also assessed the impact of CYP3A5 polymorphism on these reactions.


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Materials & Methods

Materials

TAM was purchased from Sigma Chemical Co. (St, Louis, MO) and α-OHT and N-DMT from

Toronto Research Chemicals (Toronto, Canada). Testosterone and 6β-hydroxytestosterone were

purchased from Sigma-Aldrich (St. Louis, MO). Human liver microsomes (HLMs) genotyped

for CYP3A5 *1/*1 (n = 6), CYP3A5 *1/*3 (n = 5), and CYP3A5*3/*3 (n=11), were obtained

either through a collaboration with Eli Lilly & Co., Indianapolis, or purchased from commercial

sources such as BD Gentest (Franklin Lakes, NJ) and Xenotech (Lenexa, KS). Recombinant

CYP3A4 and CYP3A5 enzymes (with P450 reductase and b5) and NADPH regenerating system

were procured from BD Gentest (Franklin Lakes, NJ). HPLC grade methanol and acetonitrile

were purchased from Fischer Scientifics (Santa Clara, CA).

Incubation of TAM with Human Liver Microsomes or recombinant CYPs: Initial

experiments were performed to optimize conditions for tamoxifen metabolism to N-DMT and α-

OHT with regards to microsomal protein and reaction time. For this purpose pooled HLMs at

protein concentration ranging from 0.01 to 1 mg/ml and incubation period from 0 - 60 minutes

were employed. In order to perform incubations under linear reaction conditions and with

consideration of the quantitation limit of the bioanalytical method, microsomal protein

concentration of 0.1 mg/ml (total incubation volume 250 µl) and incubation period of 10 minutes

were employed in further experiments with HLMs. Recombinant CYPs were employed at 50

pmol/ml concentration per manufacturer's suggestion and reactions conditions employed were

the same as those optimized for incubations with HLMs. Methanolic solution of TAM (1-50

μM) was dried under nitrogen in polypropylene vials. The vials were then preincubated with

NADPH regenerating system (1.3 mM β-NADP+, 3.3 mM glucose 6-phosphate, 3.3 mM MgCl2,


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and 0.4 U/ml glucose-6-phosphate dehydrogenase) and 100 mM phosphate buffer for 5 minutes

in a shaking water bath maintained at 370C. The reaction was initiated by the addition of

microsomes or rCYP and terminated 10 minutes later by the addition of 100 μl ice cold

acetonitrile. The incubation mixture was extracted with 2 ml of hexane-butanol (98:2) mixture.

The tubes were shaken vigorously and centrifuged at 12,000 rpm for 5 minutes. The supernatant

was evaporated to dryness under a gentle stream of nitrogen and reconstituted with 250 μl of the

mobile phase acetonitrile/H2O (8:2, v/v). 30 µl of this sample was injected into LC-MS/MS for

analysis. Control incubations where the reactions were carried in the absence of microsomes, or

NAPDH and/or substrate were also performed simultaneously. All incubations were performed

in duplicates.

LC-MS/MS Analysis of TAM Metabolites: The separation of analytes, TAM, α-OHT and N-

DMT for the analysis was performed using Waters® XBridge™ (C18 column, particle size-3.5

μm, dimensions-2.1 x 100 mm) column, a Thermo Scientific® Surveyor MS™ pump and

MicroAS autosampler. The mobile phase consisted of solution A (acetonitrile, 0.1% formic

acid) and solution B (water, 0.1% formic acid) and separation was achieved using a gradient

program of 20-95% B for 20 min, held at 100% B for 10 min, 100-20% B in 2 min and held at

20% B for 8 min. The flow rate was 0.2 ml/min. Analyses was performed using a Thermo

Scientific LTQ-FT™ operated in positive ion electrospray mode. MS spectra were produced by

collision-induced dissociation (CID) and recorded in a scan range of m/z 100-400 using nitrogen

as the sheath and auxiliary gas. The source voltage was held at 4.70 kV with a capillary

temperature of 290°C. Sheath Gas was set to 30, Aux Gas to 5 and CID Isolation Widths to 1.5.

High mass accuracy measurements were performed in the Fourier transform ion cyclotron

resonance (FT-ICR) portion of the LTQ-FT™ with the resolution set at 25,000 for faster duty


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cycles. The mass transitions for α-OHT and N-DMT were 388 > 325 (retention time 7.39

minutes) and 358 > 207(retention time 13.55 minutes), respectively. The data analysis was

performed using Thermo Scientific® Xcalibur™ 2.0 software.

Assessment of CYP3A activity (testosterone 6β-hydroxylation and midazolam 1'-

hydroxylation)

CYP3A activity in the genotyped microsomes was determined by measuring the rates of

testosterone 6-ß-hydroxylation, which is suggested to be mediated primarily by CYP3A4 and

midazolam 1’-hydroxylation, which is mediated by both CYP3A4 and CYP3A5 (Williams et.al.,

2002). The reaction conditions employed here were optimized for linear conditions and similar

to those employed earlier (Desai et al., 2002 and Hariparsad et.al, 2004). Testosterone (5-400

μM) was incubated with HLMs at a protein concentration of 0.25 mg/ml in the presence of

NADPH regenerating system and 100 mM phosphate buffer for 10 minutes. The reaction was

terminated by addition of 100 µl ice cold acetonitrile and 6-ß-hydroxy testosterone in the

incubation mixture was extracted with 2.5 mL of dichloromethane. 11α-hydroxyprogesterone was

used as an internal standard. The solvent was evaporated under nitrogen; the residue was then

reconstituted in 60:40 vol/vol methanol/water and quantitated for 6β-hydroxytestosterone levels

employing a validated HPLC method (Nallani et al., 2001). Briefly, Waters 510 pumps were

used to elute the 60:40 methanol/water mobile phase at 1 mL/min through a C18 µ-bondapak

column (3.9 x 30 mm). A Waters 2487 dual wavelength detector set at 250 nm was used for the

detection of 6ß-hydroxy testosterone. The retention time for 6-β-hydroxy testosterone and 11α-

hydroxyprogesterone were 2.8 and 5.6 minutes, respectively. The standard concentrations of 6-β-

hydroxy testosterone ranged from 0.1 – 50 µM. The inter-day and intra-day variability in the


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HPLC analysis was <5% and the detection limit was 0.05µM for 6ß-hydroxytestosterone.

HLMs H860, HH739, HH785, HH189 and HH507 were from BD Gentest and the Vmax values

used were those provided by the vendor. For midazolam 1'-hydroxylation, in vitro incubations

(100 µL) were performed with a single concentration of midazolam (6 µM) for 1 minute at 37ºC

with HLMs 5 µg protein, under linear rate conditions, in 100 mM sodium phosphate buffer, pH

7.4. Reactions were initiated with the addition of 2 mM NADPH. After terminating the

reaction, denatured protein was removed by centrifugation, and supernatants were assayed for 1’-

hydroxymidazolam formation using a validated LC-MS/MS method.

Data Analysis: Enzyme kinetic parameters (Vmax and Km) were determined by non-linear

regression analysis using Prism 5 (GraphPad Software, San Diego, CA). Data were fitted to

Michaelis-Menten, sigmoidal and substrate inhibition kinetics models. The best model was

selected based on the distribution of residuals, standard error of the estimates and statistical

criteria (AIC- Akaike Information Criteria and BIC- Bayesian Information Criteria). Intrinsic

formation clearance of α-OHT and N-DMT were determined as the ratio of Vmax/Km. For a low

extraction compound such as TAM (Morello et al., 2003) the in vivo formation hepatic clearance

(CLH) for each metabolite can be estimated using the well stirred model (Eqn.1) in conjunction

with estimates of unbound plasma fraction (fup) of 0.05 (Morello et al., 2003), hepatic blood

flow (QH) of 1500 ml/min for a 70-kg individual, liver mass of 1.5 kg and a microsomal mass of

45 mg per 1 g of liver (Rowland et al., 1973, Langenegger et al., 2006, Houston and Carlile,

1997).

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Correlation between enzyme activity and metabolite formation was assessed using Pearson

correlation. Comparison of intrinsic clearance values and the estimated formation clearance of

N-DMT and α-OHT between genotypes were performed using one way ANOVA followed by

Tukey’s test. A p <0.05 was considered to be significant.


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Results

Contribution of CYP3A4 and CYP3A5 to the formation of α-OHT and N-DMT

The reaction velocity vs. substrate concentration plots for α-OHT and N-DMT formation in

incubation with rCYP3A4 and rCYP3A5 are shown in Figures 1A and 1B, respectively, and the

kinetic parameters estimated by fitting data to Michaelis-Menten kinetic model are listed in

Table 1. The Vmax of the α-OHT formation by rCYP3A5 was markedly lower than that for

rCYP3A4 (2.17 ± 0.24 vs. 15.59 ± 3.08 fmol/min/pmol P450) while the Km values were similar

(19.28 ± 8.8 vs. 13.4 ± 3.9 µM; statistically indistinct with p = 0.41). Thus, it is apparent that the

CLint for the formation of α-OHT with rCYP3A4 was approximately 5-fold higher than that with

rCYP3A5. The CLint for the formation of N-DMT was 0.14 and 0.08 µl/min/pmol P450 with

rCYP3A4 and rCYP3A5, respectively.

Effect of CYP3A5*3 genotyped microsomes on the formation of α-OHT and N-DMT

We next assessed the impact of CYP3A5 polymorphisms on the formation of α-OHT and N-

DMT using a panel of genotyped human liver microsomes (CYP3A5*1/*1 (n=6), CYP3A5*1/*3

(n=5) and CYP3A5 *3/*3 (n=11)). The rates of testosterone 6β-hydroxylation, which is thought

to be primarily mediated by CYP3A4 and midazolam 1'-hydroxylation, which is catalyzed by

both CYP3A4 and CYP3A5, were also determined in these microsomal fractions. The Vmax, Km

and CLint for the formation of the two tamoxifen metabolites and the rates of testosterone 6β-

hydroxylation and midazolam 1-hydroxylation are listed in Table 2. In Figure 2 the CLint values

for α-OHT formation as a function of the CYP3A5 genotypes are plotted. The mean CLint

values for α-OHT formation by CYP3A5*1/*1, CYP3A5*1/*3 and CYP3A5*3/*3 were 0.89±

0.64, 0.22 ± 0.06, 0.75 ± 0.89 µl/min/mg, respectively, and were not significantly different.


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Similarly, the mean α-OHT formation clearance (CLH) scaled from CLint was not significantly

different between the three genotypes (3 ± 2.15, 0.75 ± 0.22 and 2.53 ± 2.99 ml/min). There was

considerable inter-subject variability in the kinetics of α-OHT formation, which is expected of

CYP3A4/5 substrates and, therefore, we compared the rates of α-OHT formation with

testosterone 6-β-hydroxylation and midazolam 1'-hydroxylation (Figures 3A and 3B). Overall,

we observed a significant correlation between Vmax of α-OHT formation and testosterone-6β

hydroxylation activity (r=0.6039, p=0.0171). HH-860 and HH-189 had extremely high values

for testosterone 6β-hydroxylation and were excluded from the regression analysis. In general,

individuals with low testosterone 6-β-hydroxylation activity also had lower rates of α-OHT

formation. The levels of α-OHT production in three CYP3A5*3/*3 HLMs (HH-507, XENO and

HH-689), that also had low testosterone 6β-hydroxylation, were below the limit of our

quantitation. The correlation of α-OHT formation rate with 1’- hydroxy midazolam activity was

not significant with r=0.2388 and p = 0.4109.

In the case of N-DMT formation, there was a significant difference in the CLint values between

CYP3A5*1/*1 (48.65 ±26.64 µl/min/mg) and CYP3A5*1/*3 (7.004± 3.13 µl/min/mg) or

CYP3A5*3/*3 (12.33 ± 6.634 µl/min/mg) HLMs (p<0.05) (Figure 4). Similarly, the mean N-

DMT formation clearance (CLH) scaled from CLint was significantly different between

CYP3A5*1/*1 (144.88 ±72.43 ml/min) and CYP3A5*1/*3 (23.22± 10.18 ml/min) or

CYP3A5*3/*3 (40.23 ± 20.84 ml/min) genotype. Again there was a marked variability in Vmax

(53 to 359.11 pmol/min/mg) and Km values (3.32 to 21.52 µM) of N-DMT formation by the

genotyped HLMs. However, the Vmax of N-DMT formation correlated well with both,

testosterone-6-β-hydroxylation (r=0.6884, p=0.0017) and 1'- hydroxy midazolam activity


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(0.7758, p=0.0004) [Figures 5A and 5B]. The correlation analysis does not appear to go through

origin because N-DMT formation may also be impacted by enzymes other than CYP3A4/5. We

did not observe a statistically significant difference in the Vmax and CLint of N-DMT formation

between CYP3A5*1/*3 vs. CYP3A5*3/*3 expressers, which would typically be expected for

compounds metabolized by CYP3A5. This may be due to both CYP3A4 and CYP3A5

exhibiting marked inter-subject variability and that the heterozygous CYP3A5*1/*3 HLMs

employed in our study appear to be those with lower CYP3A5 activity as evidenced by low Vmax

of midazolam 1'-hydroxylation.

We also attempted a quantitative assessment of the CYP3A5 contribution to α-OHT and N-DMT

formation applying the method of Dennison (2007). For HLMs with low expression

CYP3A5*1/*3 and CYP3A5*3/*3 alleles, Vmax of α-OHT and N-DMT were plotted against the

Vmax of testosterone 6β-hydroxylation (n = 13). For these HLMs, the formation of tamoxifen

metabolites was presumed to be primarily catalyzed by CYP3A4. The regression lines with 95%

prediction intervals for α-OHT and N-DMT are shown in Figures 6A and 6B, respectively. The

Vmax of wild-type CYP3A5 expressers that had testosterone 6β-hydroxylase activity in the same

range exhibited by low CYP3A5 low expressers (0.36 to 2.83 nmol/min/mg protein) were also

plotted (shown as open circles). HLMs, CD-8002, CD-8052 and HH-739 had testosterone 6β-

hydroxylase activity in the aforementioned range. For these HLMs, the contribution of CYP3A5

was estimated as the difference between the observed Vmax and that estimated from these

regression curves which reflects the contribution of CYP3A4. Based on this computation,

CYP3A5 made no discernable contribution in the formation of α-OHT in incubations with

HH739, CD-8002 and CD-8052 HLMs. The Vmax values of α-OHT formation in these HLMs


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were well within the 95% prediction interval limits of the regression curve. On the other hand,

the Vmax values for N-DMT formation for the high expressers, HH-739, CD-8002 and CD-8052,

were above the 95% prediction intervals and estimated to be 51, 57 and 61%, respectively.


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Discussion

Given the large inter-subject variability in the metabolism of TAM and the pharmacological and

toxicological effects of the metabolites formed, extensive efforts have been made in the past to

delineate the contribution of various clinically relevant enzymes in TAM metabolism. Recently,

significant advances have been made in understanding the clinical impact of the polymorphic

expression of CYP2D6 on the efficacy and safety of TAM (Goetz et al. 2007; Kiyotani et al.

2008; Schroth et al. 2009). The formation of endoxifen, the secondary metabolite that appears to

be 100-fold more potent than TAM, is predominantly catalyzed by CYP2D6, a highly

polymorphic enzyme (Stearns et al. 2003; Lim et al. 2006). Several studies have shown that low

expression variants are associated with lower endoxifen plasma levels, an increased risk of breast

cancer relapse and a shorter time to recurrence during TAM therapy (Stearns et al. 2003; Goetz

et al. 2005; Xu et al. 2008). The potential contribution of CYP3A5 genetic variants on clinical

pharmacokinetics of TAM is not well understood. Individuals deficient in N-DMT production

may also have lower endoxifen levels. In particular, an enhanced understanding of the factors

that contribute to the inter-subject variability in the formation of α-OHT is essential to better

understand the risk for endometrial carcinogenesis associated with the long term use of TAM.

There are conflicting results regarding the influence of CYP3A5 polymorphisms on the clinical

pharmacokinetics of TAM. Jin et al. ( 2005) reported that individuals with CYP3A5*1/*1 alleles

had higher plasma levels of endoxifen than those with CYP3A5*3/*3 alleles. On the other hand,

Tucker et al ( 2005) and Goetz et al ( 2005) showed that there was no significant influence of

CYP3A5 polymorphisms on TAM metabolism or overall survival. In another study, Wegman et

al ( 2007) reported that patients with CYP3A5*3/*3 polymorphism had increased risk of

recurrence after two years of TAM treatment. Clinical studies are often confounded as numerous


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factors simultaneously impact the inter-subject variability in the pharmacokinetics and

efficacy/toxicity of drugs. Thus, in vitro investigations may aid in better understanding the

mechanisms underlying this variability.

In the present study, we employed a three- pronged approach to discern the relative contribution

of CYP3A4 and CYP3A5 to the formation of α-OHT and N-DMT. First, employing

recombinant CYP3A4 and CYP3A5 we observed that the catalytic efficiency of tamoxifen α-

hydroxylation by CYP3A5 is markedly (~ 5fold) lower than that by CYP3A4 while this

difference for tamoxifen N-demethylation was only 1.7 fold. Secondly, we compared the impact

of CYP3A5 genotype on the formation of these two metabolites. As noted earlier, there was no

significant difference in the formation CLint or CLH of α-OHT between microsomes genotyped

for CYP3A5*1/*1, CYP3A5*1/*3 and CYP3A5*3/*3, whereas there was a marked decrease in

the tamoxifen N-demethylation in heterozygous and homozygous low expression alleles,

CYP3A5*1/*3 and CYP3A5*3/*3, relative to the wild type CYP3A5*1/*1. Thirdly, we

attempted to quantitatively discern the contribution of CYP3A5 in HLMs with high expression

of this enzyme. The Vmax values for α-OHT or N-DMT formation in CYP3A5 low expressers

(CYP3A5*1/*3 and CYP3A5*3/*3) were correlated to testosterone 6β-hydroxylation, which is

reported to be primarily metabolized by CYP3A4. The Vmax values for α-OHT and N-DMT

formation in CYP3A5 high expressers were then compared to low CYP3A5 expressers with

similar testosterone 6β-hydroxylation activity. This comparison indicated that the contribution

of CYP3A5 for α-OHT production was minimal in the wild type CYP3A5*1/*1 expressing

HLMs. The contribution of CYP3A5 to N-DMT formation in these HLMs was substantial

ranging from 51-61%.


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While we observed a distinct difference in the CLint of tamoxifen N-demethylation by HLMs

expressing CYP3A5*1/*1 and both low expression alleles, the difference between the

heterozygous CYP3A5*1/*3 and CYP3A5*3/*3 was not statistically significant. In general, it

is well appreciated that CYP3A4 and CYP3A5 expression and activity exhibit striking inter-

subject variability and it is likely that all CYP3A5*1/*3 HLMs used in our study have low

overall CYP3A enzymatic activity. Indeed this is supported by the fact that these HLMs also

have lower midazolam hydroxylation activity relative to HLMs expressing CYP3A5*1/*1.

However, a limitation of our study is that we did not measure the levels of endoxifen in our

HLM incubations. Since N-DMT is sequentially metabolized by CYP2D6 to endoxifen the

genetic variability in expression of this enzyme may impact the observed N-DMT levels. As

such, HLMs with CYP2D6 genotype associated with extensive or ultrarapid metabolism may

have low N-DMT. The overall distribution of CYP2D6 genotype, CYP2D6 predicted

metabolizer groups and activity (measured as bufuralol 1’-hydroxylase) between livers with

CYP3A5*1/*1 vs CYP3A5*1/*3 are shown in Appendix I. As is evident there is comparable

distribution of CYP2D6 genotype and minimal differences in CYP2D6 activity for the three

CYP3A5 variant groups of HLMs. Taken together these factors suggest that the differences in

CYP2D6 genotype and activity are likely to make minimal contribution to the observed

differences in the N-DMT formation.

Overall, our findings are consistent with those reported earlier. For instance, Desta (2004)

evaluated the kinetics of N-DMT formation by expressed CYP3A4 and CYP3A5, which fitted a

single-site enzyme model. They reported Km values of 12.6 and 19.4 µM and CLint values of 0.12

and 0.08 µl/min/pmolP450, for CYP3A4 and CYP3A5, respectively, which are similar to those


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determined in our experiments. These investigators carried out microsomal incubations at

tamoxifen concentrations ranging from 0 to 100 µM and the N-DMT formation fitted a two-site

binding model. However, they noted that the high-affinity model is more relevant at lower

concentrations and thus their results at lower concentration are comparable to those obtained in

our studies. Further, they employed three HLM incubations and the intrinsic clearance for the

high affinity component ranged from 6.4 to 43.0 µl/min/mg protein, which is similar to the range

of 3.99 to 83.15 µl/min/mg protein we observed. The kinetics of tamoxifen α-hydroxylation by

recombinant CYP3A4 and CYP3A5 were not reported. However, the CLint for tamoxifen α-

hydroxylation in HLMs from one donor was 4.5 µl/min/mg protein, which is not far from the

range (0.18 to 2.91 µl/min/mg protein) observed in our studies.

In conclusion, an assessment of the kinetics of tamoxifen metabolism by expressed P450

enzymes suggest that tamoxifen α-hydroxylation is primarily mediated by CYP3A4, while

tamoxifen N-demethylation is efficiently mediated by both CYP3A4 and CYP3A5. These

findings further corroborate previously published findings (Desta et.al. 2004; Crewe et.al. 1997

and Notley et.al.2005). More importantly, our assessment employing genotyped HLMs strongly

suggests that polymorphic expression of CYP3A5 significantly impacts the in vitro clearance of

N-DMT formation, but not that of α-OHT formation. Formation of both metabolites exhibited

large inter-subject variability, which is typical of CYP3A4/5 substrates. In the clinical setting,

factors other than CYP3A5 polymorphism are likely to contribute to the variability in α -OHT

formation. However, with regards to N-DMT formation individuals expressing non-functional

CYP3A5 variants such as CYP3A5*3/*3 may have markedly lower production of N-DMT.


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Thus, the potential clinical impact of CYP3A5 polymorphic expression on the formation of N-

DMT and subsequently to endoxifen warrants further investigation.


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Authorship Contributions Participated in research design: Mugundu, Sallans, Shaughnessy, Guo and Desai. Conducted experiments: Mugundu, Sallans, Guo and Desai Contributed new reagents or analytic tools: Guo. Performed data analysis: Mugundu, Sallans, and Desai. Wrote or contributed to the writing of the manuscript: Mugundu, Shaughnessy, Guo and Desai


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Footnote: a) Supported by a grant to PBD by Komen G Breast Cancer Foundation. b) Reprint requests: Pankaj B. Desai, Ph.D., Department of Pharmacokinetics and

Biopharmaceutics, James L Winkle College of Pharmacy, University of Cincinnati Medical Center, 3225 Eden Avenue, Cincinnati, OH 45267-0004. [email protected]

c) Part of this work was presented at the American Association of Pharmaceutical Scientist Annual Meeting and Exposition, Los Angeles, CA, USA November 2009.


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Figure Legends

Figure 1: Kinetic plots for the formation of α-OHT (Fig. 1A) and N-DMT (Fig.1B) from TAM employing rCYP3A4(•) and rCYP3A5(▲). Each data point represents the mean of two 10- minute incubations of TAM (1-50 µM) with 50 pmol/ml of rCYP3A4 or rCYP3A5 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from Michaelis-Menten model. Figure 2: Comparison of intrinsic clearance (CLint) of α-OHT formation by human liver microsomes genotyped for CYP3A5*1/*1(•), *1/*3(■) and *3/*3(▲). Each point represents the CLint estimated by fitting the data to Michaelis-Menten kinetics using nonlinear regression analysis, with mean ± standard deviation. Figure 3: Correlations between the formation rate of α-OHT with Vmax of testosterone-6-β-hydroxylation (Fig. 3A) and midazolam-1-hydroxylation (Fig. 3B) in a panel of genotyped human liver microsomes. Figure 4: Comparison of intrinsic clearance (CLint) of N-DMT formation by human liver microsomes genotyped for CYP3A5*1/*1(•), *1/*3(■) and *3/*3(▲). Each point represents the CLint estimated by fitting the data to Michaelis-Menten kinetics using nonlinear regression analysis, with mean ± standard deviation. Figure 5: Correlations between the formation rate of N-DMT with Vmax of testosterone-6-β-hydroxylation (Fig 5A) and midazolam-1-hydroxylation (Fig. 5B) in a panel of genotyped human liver microsomes. Figure 6: Regression of maximal formation rate of α-OHT (6A) and N-DMT (6B) with that of testosterone-6-β-hydroxylation. Dotted lines represent the 95% prediction interval around the regression line. Microsomes separated as low expressers CYP3A5*1/*3 and 3/*3 (closed circles) and high expressers CYP3A5*1/*1(open circles).


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Table 1: Kinetic parameter estimates for the formation of α-OHT and N-DMT by rCYP3A4 and rCYP3A5.

Recombinant CYP

Vmax (fmol/min/pmol P450) Km (μM)

CLint (nl/min/pmol P450)

α-OHT

rCYP3A4 15.59 ± 3.08 19.28 ± 8.8 0.81

rCYP3A5 2.17 ± 0.24 13.4 ± 3.9 0.16

N-DMT Recombinant

CYP Vmax

(pmol/min/pmol P450) Km (μM) CLint

(μl/min/pmol P450) rCYP3A4 1.013 ± 0.07 7.16 ± 1.5 0.14

rCYP3A5 0.533 ± 0.01 6.87 ± 0.7 0.08 Vmax, maximum velocity; Km, substrate concentration at which the reaction velocity is 50% of Vmax; CLint, intrinsic clearance (Vmax/Km)


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Table 2: Kinetic parameters for the formation of α-OHT and N-DMT from TAM, 6-β hydroxy testosterone from testosterone, and 1-hydroxy midazolam from midazolam by CYP3A5 genotyped human liver microsomes.

* pmol/min/mg protein, ** µM, ND – Not Detected, NA-Not Available, # µl/min/mg protein, Scaled formation clearance (CLH) - ml/min

Liver ID CYP3A5 Genotype

N-DMT α-OHT Midazolam 1-hydroxylation (nmol/min/mg)

Testosterone 6β-hydroxylation (nmol/min/mg) Vmax* Km** CLint

# formation

CLH Vmax* Km** CLint#

formation CLH

HH-860 *1/*1 359.11 4.32 83.15 237.24 7.31 4.55 1.65 5.55 3.25 11.5 MCV-36 *1/*1 244.59 7.86 31.12 98.16 17.69 10.45 1.69 5.68 1.74 5.12 CD-8002 *1/*1 236.19 10.66 22.16 71.24 1.76 12.65 0.14 0.47 NA 1.27 CD-8052 *1/*1 279.36 11.08 25.21 80.52 5.44 7.65 0.71 2.39 NA 1.6 HH-739 *1/*1 223.41 4.15 53.83 162.05 2.71 5.97 0.45 1.52 1.2 1.6 HH-785 *1/*1 253.76 3.32 76.43 220.10 4.2 6.0 0.7 2.36 4.1 5.8

Mean

266.07 6.9 48.65 144.88 6.52 7.88 0.89 3.00 2.57 4.48 SD

49.31 3.45 26.64 72.43 5.82 3.09 0.64 2.15 1.34 3.96

HH-1044 *1/*3 107.41 19.42 5.53 18.43 8.49 25.82 0.33 1.11 0.841 1.22 HH-525 *1/*3 135.96 16 8.5 28.15 4.23 22.91 0.18 0.61 0.5 1.18 HL-G *1/*3 112.92 21.52 5.25 17.51 3.2 16.52 0.19 0.64 0.8 ND HL-W *1/*3 92.35 7.86 11.75 38.63 3.89 16.76 0.23 0.78 ND 1.15

HH-776 *1/*3 69.9 17.53 3.99 13.35 5.26 29.24 0.18 0.61 0.88 1.56 Mean

103.71 16.47 7 23.22 5.02 22.25 0.22 0.75 0.75 1.28

SD

24.55 5.24 3.12 10.18 2.08 5.59 0.06 0.22 0.17 0.19 HH-189 *3/*3 112.42 3.89 28.87 91.49 2.07 0.71 2.91 9.76 2.89 13.6 HH-507 *3/*3 89.09 5.2 17.13 55.67 ND ND -- -- ND 0.4 XENO *3/*3 52.99 4.4 12.04 39.56 ND ND -- -- 0.54 0.13 HL-D *3/*3 97.32 17.44 5.58 18.60 1.8 9.62 0.19 0.64 0.25 0.59 HL-J *3/*3 122.67 9.84 12.47 40.94 5.9 8.16 0.72 2.43 0.79 2.23 HL-P *3/*3 106.09 7.64 13.89 45.46 4.39 7.96 0.55 1.85 0.95 ND

HH-689 *3/*3 73.99 9.3 7.96 26.39 ND ND -- -- 0.14 0.23 HL-R *3/*3 153.66 13.72 11.2 36.87 7.09 12.99 0.55 1.85 0.84 2.83 HL-Q *3/*3 64.99 7.34 8.85 29.29 3.45 6.43 0.54 1.82 0.25 0.36

HH-639 *3/*3 76.39 5.76 13.26 43.46 2.3 6.17 0.37 1.25 0.24 0.38 HH-1123 *3/*3 78.11 17.63 4.43 14.80 3.65 19.77 0.18 0.61 0.67 0.52

Mean

93.43 9.29 12.33 40.23 3.83 8.98 0.75 2.53 0.75 2.13 SD

28.96 4.95 6.63 20.84 1.89 5.57 0.89 2.99 0.8 4.13

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Appendix I: CYP2D6 genotype, predicted metabolizer group and activity in HLMs with CYP3A5 variants

a data from Eli Lilli and Company; b data from BD Gentest; cnot available a,dCYP2D6 activity was measured as the velocity of bufuralol 1’-hydroxylation. Microsomal metabolism was carried out in duplicates using a substrate concentration of 10 µM, protein concentration of 0.1 mg/ml and incubation time of 15 mins. These reaction conditions were initially optimized for linearity and to reflect initial rate conditions. The analyte (1’hydroxybufuralol) was measured using a validated LC/MS method. The analytical separation was achieved using a Varian MonoChrom C18 column (5 microns, 50 x 2.00 mm) and a solvent system (A: 5 mM NH4OAc in 5% MeOH and B:5 mM NH4OAc in 95% MeOH, used at gradient - 2.7 min escalation from 10% B to 98% B and back to 10% B) at a flow rate of 0.50 mL/min. The metabolite and the internal standard ([d9] 1'-hydroxybufuralol) were detected using an ESI positive ionization (ions monitored (m/z) 277.8 → 185.8 for 1'-hydroxybufuralol; 287 → 185.8 for the IS). e the means do not include the data from BD Gentest

Liver ID CYP3A5 Genotype

CYP2D6

Genotypea Predicted

Metabolizer Group

Activitya,d (1-hydroxybufuralol

formation) (nmol/min/mg)

HH-860 *1/*1 *35/*41 IM 0.0333 ± 0.0037 MCV-36 *1/*1 *1/*36 IM 0.0442 ± 0.0104 CD-8002 *1/*1 nac na na CD-8052 *1/*1 na na na HH-739 *1/*1 *1/*41 IM 0.0327 ± 0.0001 HH-785 *1/*1 0.046b

Mean 0.038e SD 0.0072 e

HH-1044 *1/*3 *41/*41 IM 0.0116 ± 0.002 HH-525 *1/*3 *1/*4 IM 0.0455 ± 0.0006 HL-G *1/*3 *1/*2 EM 0.0394 ± 0.0033 HL-W *1/*3 *1/*41 IM 0.0394 ± 0.0014

HH-776 *1/*3 *4/*4 PM 0.065 ± 0.0107 Mean 0.039 e

SD 0.019 e HH-189 *3/*3 na na 0.00372b HH-507 *3/*3 na na 0.0052b XENO *3/*3 na na na HL-D *3/*3 */1*1 EM 0.1087 ± 0.0288 HL-J *3/*3 *2/*2 EM 0.0251 ± 0.0026 HL-P *3/*3 *1/*4 IM 0.0363 ± 0.0055

HH-689 *3/*3 *2/*2 EM 0.0629 ± 0.0021 HL-R *3/*3 *9/*41 IM 0.0385 ± 0.0005 HL-Q *3/*3 *1/*2 EM 0.0558 ± 0.0007

HH-639 *3/*3 *2/*9 IM 0.0385 ± 0.0005 HH-1123 *3/*3 *1/*35 EM 0.0679 ± 0.0185

Mean 0.054 e SD 0.026 e


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