UNIVERSITY OF CINCINNATI
Date: 7-Dec-2009
I, Ganesh Mugundu , hereby submit this original work as part of the requirements for the degree of: Doctor of Philosophy in Pharmaceutical Sciences/Biopharmaceutics It is entitled: Pharmacogenetic Impact on Metabolism and Cytochrome P450 (CYP)3A
Inductive Effect of Tamoxifen
Student Signature: Ganesh Mugundu
This work and its defense approved by: Committee Chair: Pankaj Desai, PhD Pankaj Desai, PhD
Ranajit Chakraborty, PhD Ranajit Chakraborty, PhD
Ranjan Deka, PhD Ranjan Deka, PhD
Georg Weber, MD, PhD Georg Weber, MD, PhD
Elizabeth Shaughnessy, MD, Ph Elizabeth Shaughnessy, MD, PhD
2/16/2010 213
Pharmacogenetic Impact on Metabolism and Cytochrome P450 (CYP) 3A Inductive Effect of Tamoxifen
A dissertation submitted to the Division of Research and Advanced Studies of the University of Cincinnati
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy (Ph.D.)
in the Department of Pharmaceutical Sciences of the College of Pharmacy
2009
by
Ganesh M. Mugundu
B.Pharm, MGR Medical University, India 1999 M.Pharm (Drug Design and Development), MS University of Baroda, India, 2000
Committee Chair: Pankaj B.Desai, Ph.D.
ABSTRACT
Tamoxifen (TAM) is an effective selective estrogen receptor modulator (SERM) widely used for the treatment and chemoprevention of estrogen receptor (ER) positive tumors.
Notwithstanding the advent of aromatase inhibitors (AIs) and newer SERMs, TAM remains an important member of the armamentarium against breast cancer. Despite its advantages and a strong track record of efficacious use, TAM is associated with significant clinical problems. Its use is associated with a large inter-subject variability in its pharmacokinetics (PK) and resulting therapeutic activity/side effects. It may affect the clearance of co-administered drugs by inducing and/or inhibiting CYP3A. CYP3A plays a central role in TAM metabolism to its major metabolite, N-desmethyl tamoxifen (N-
DMT), and minor metabolites including α-hydroxy tamoxifen (α-OHT), which is implicated in endometrial toxicity. The role of CYP3A5 and the impact of its polymorphic expression on the formation of α-OHT and N-DMT are not known.
Furthermore, previous work in our laboratory indicated that TAM induces CYP3A in human hepatocytes by activating pregnane X receptor (PXR). Therefore, we investigated the genetic influence on TAM metabolism in vitro and CYP3A induction in breast cancer patients undergoing TAM therapy. Using cDNA expressed CYP3A4, CYP3A5,
CYP3A5*8, CYP3A5*9 microsomes and a panel of human liver microsomes genotyped for CYP3A4/5 variants, enzyme kinetics for the formation of α-OHT and N-DMT were determined. Our in vitro findings suggest that the formation of α-OHT is primarily mediated by CYP3A4, and is not affected by CYP3A5 genotype. This is further supported by the lack of association between CYP3A5 genotypes and plasma concentrations of α-OHT in our clinical study. On the other hand, both CYP3A4 and
I CYP3A5 contribute to the formation of N-DMT. The intrinsic clearance for N-DMT formation by cDNA expressed CYP3A4 and CYP3A5 were 0.57 and 0.35 ml/min/pmol
P450, respectively. Furthermore, there was a significant difference in the Vmax of N-
DMT formation between CYP3A5*1/*1 and CYP3A5*3/*3 microsomes (267.63 Vs
101.03 pmol/min/mg).
Employing midazolam (MDZ) as a CYP3A probe, we assessed the induction of CYP3A by TAM in breast cancer patients. Apparent oral clearance of midazolam was determined at the baseline (prior to TAM administration), Day 1 and Day 42 after administration of a
TAM (20 mg/day). In 6 out of 13 patients, we observed an increase in the clearance of
MDZ (mean: 70%, range: 26 to 161%) indicative of CYP3A induction. Furthermore, there was a marked inter-subject variability in the extent of CYP3A induction. Blood samples were genotyped for polymorphisms in CYP3A (CYP3A4*1B and CYP3A5*3) and PXR (-25385C>T, -24381 A>C and 63396 C>T) to investigate their association with
CYP3A induction. We observed a trend towards higher induction in subjects with
CYP3A5 *1/*3 than CYP3A5*3/*3 genotypes. One patient with maximum induction
(2.5 fold) was homozygous to TT and CC variants of PXR (-25385C>T and -24381
A>C). No association was found with CYP3A4*1B, PXR 63396 C>T and CYP3A induction. Overall, our studies provide novel insights into genetic contributions to the formation of CYP3A derived metabolites such as N-DMT and α-OHT, and to the inter- subject variability in CYP3A inductive effect of TAM.
II
III
To my (late) father, mother and brother, for their love, support and encouragement
To my wife for her love, patience, sacrifice and unconditional support in standing by me during all these years
To my son for bringing a new meaning to my life and for all the love and joy
IV
ACKNOWLEDGEMENTS
There have been many people that made the work included and excluded in
this dissertation possible and my stay at University of Cincinnati extremely enjoyable.
First and foremost, I would like to express my deep gratitude to my advisor and mentor
Dr. Pankaj B. Desai, for providing me an opportunity to pursue PhD under his direction
and support. Over the past few years, Dr. Desai’s encouragement and guidance both in
professional and personal matters has helped me in completing my dissertation
successfully. His broad knowledge in the field of clinical pharmacology has been a
valuable source of inspiration and motivation for my study. Thank you for all the
knowledge, opportunities, and most importantly for being a good friend whom I greatly
respect.
I would like to thank Dr. Georg Weber, for serving in my qualifying exam and
dissertation committee. His constructive criticism and valuable inputs during the course
of my research has been immensely helpful. His input and expertise has helped me to
make the best of my research.
I would like to thank Dr. Elizabeth Shaughnessy, for serving in my dissertation
committee and being a wonderful collaborator. She was very generous with her time in supporting the clinical trial, sparing time for all the discussions and providing valuable
inputs to my research.
V
I would like to thank Dr. Ranjan Deka, for serving in my dissertation committee. He was generous in allowing me to work in his lab, where I learnt SNP genotyping procedures required for my dissertation work. He has also been quite generous with his time in supporting and providing suggestions to make the best of my research.
I would like to thank Dr. Ranajit Chakraborty for serving in my qualifying examination and dissertation committee. His expertise in genetics and biostatistics has helped me in understanding about pharmacogenetics and critical data analysis. He has always been kind, helpful and provided insightful suggestions in my research.
I would like to thank my current and previous labmates/friends, Divya Samineni, Nimita
Dave, Ganesh Palanisamy, Fang Li, Niresh Hariparsad and Rucha Sane for their friendship, assistance, and creating a great atmosphere to work in the lab.
I wish to thank all my colleagues/friends at the College of Pharmacy, most notably Philip
Cherian, Amit Kulkarni, Shruthi Vaidyanathan, Nirmal Bhide, Rachna Gajjar , Jodie
Ebanks, Jennifer Karr, Poonam Chopra, Sarah Ibrahim and Kelly Smith for their help and friendship.
I would like to thank the Department of Pharmaceutical Sciences, the College of Pharmacy and the University of Cincinnati for providing me the opportunity and funding for my graduate studies. I would like to thank Dean Dr. Daniel Acosta,
VI Division Chair Dr. Gary Gudelsky, and graduate studies director Dr. Gerald Kasting for
their support. I would also like to thank administrative staff Marcie Silver, Donna Taylor,
and Suzanne Ryan for their kindness, affection and support for past few years.
Finally, completion of this dissertation wouldn’t have been possible without the support
and love from my family.
This work was supported by a grant from Susan G. Komen breast cancer foundation.
VII Table of Contents ABSTRACT ...... I ACKNOWLEDGEMENTS ...... V LIST OF FIGURES ...... X LIST OF TABLES ...... XIV LIST OF ABBREVIATIONS ...... XVI 1. CHAPTER ONE: LITERATURE REVIEW ...... 1
1.1. INTRODUCTION...... 1 1.1.1. Breast Cancer and Endocrine Therapy ...... 1 1.1.2. Tamoxifen ...... 2 1.1.3. Pharmacokinetics of Tamoxifen ...... 4 1.2. VARIABILITY IN PHARMACOKINETICS/PHARMACODYNAMICS OF ANTI-CANCER DRUGS ...... 7 1.3. OVERVIEW OF CYTOCHROME P450 (CYP) 3A ENZYMES ...... 10 1.3.1. Variability in Cytochrome P450 (CYP) 3A Enzymes ...... 12 1.3.2. Induction of CYP3A ...... 13 1.3.2.1. Mechanism of CYP3A Induction – Role of PXR ...... 16 1.3.2.2. Variability in CYP3A Induction ...... 18 1.3.3. Inhibition of CYP3A ...... 19 1.3.3.1. Mechanism of CYP3A Inhibition ...... 21 1.3.3.2. Variability in CYP3A Inhibition ...... 23 1.3.4. Implications of TAM Mediated CYP3A Induction/Inhibition...... 24 1.3.4.1. CYP3A Induction by TAM ...... 24 1.3.4.2. CYP3A Inhibition by TAM ...... 26 1.4. IMPACT OF PHARMACOGENETICS ON PK/PD OF ANTI-CANCER DRUGS ...... 26 1.5. CYP3A POLYMORPHISMS ...... 29 1.5.1. Pharmacogenetics of CYP3A4 ...... 31 1.5.2. Pharmacogenetics of CYP3A5 ...... 32 1.5.3. Pharmacogenetics of CYP3A7 ...... 33 1.5.4. Pharmacogenetics of CYP3A43 ...... 34 1.6. ROLE OF PXR POLYMORPHISMS ...... 34 1.7. TAM AND CYP2D6 POLYMORPHISMS ...... 35 1.8. METHODS TO ASSESS CYP3A INDUCTION ...... 36 1.8.1. IN VITRO METHODS ...... 36 1.8.2. CLINICAL ASSESSMENT OF INDUCTION ...... 38 2. CHAPTER TWO: HYPOTHESIS AND SPECIFIC AIMS ...... 41
2.1. HYPOTHESIS ...... 41 2.2. SPECIFIC AIM 1 ...... 41 2.3. SPECIFIC AIM 2 ...... 42 2.4. SPECIFIC AIM 3 ...... 44 3. CHAPTER THREE: EXPERIMENTAL DESIGN AND METHODS ...... 45
3.1. SPECIFIC AIM 1: ASSESSMENT OF IMPACT OF CYP3A5 ON TAMOXIFEN CLEARANCE IN VITRO .. 45 3.1.1. Materials ...... 45 3.1.2. Incubation of Testosterone with CYP3A Genotyped Microsomes ...... 46 3.1.3. Incubation of Midazolam with CYP3A Genotyped Microsomes ...... 46 3.1.4. Incubation of Tamoxifen with CYP3A Genotyped Microsomes ...... 47 3.1.5. Incubation of Tamoxifen with recombinant CYP3A Supersomes ...... 48 3.1.6. HPLC Analysis of 6-β-Hydroxy Testosterone ...... 48 3.1.7. LC-MS/MS Analysis of α-OHT and N-DMT ...... 49 3.1.8. Data Analysis ...... 50 3.1.9. Statistical Analysis ...... 51
VIII 3.2. SPECIFIC AIM 2: CLINICAL ASSESSMENT OF CYP3A INDUCTION BY TAMOXIFEN ...... 52 3.2.1. Materials ...... 52 3.2.2. Development and Validation of LC-MS/MS Method ...... 52 3.2.3. CYP3A Induction by Tamoxifen in Breast Cancer Patients...... 54 3.3. SPECIFIC AIM 3: IMPACT OF CYP3A AND PXR VARIANTS ON CYP3A INDUCTION ...... 57 3.3.1. Materials ...... 57 3.3.2. DNA Isolation and Quantitation ...... 57 3.3.3. PCR ...... 57 3.3.4. Allelic Discrimination ...... 58 4. CHAPTER FOUR: RESULTS ...... 60
4.1. SPECIFIC AIM 1: ASSESSMENT OF IMPACT OF CYP3A5 ON TAMOXIFEN CLEARANCE IN VITRO .. 60 4.1.1. Contribution of CYP3A4/5 to the formation of α-OHT and N-DMT ...... 60 4.1.2. Effect of CYP3A5*3 genotyped microsomes on the formation of α-OHT ...... 63 4.1.3. Effect of CYP3A5*3 genotyped microsomes on the formation of N-DMT ...... 67 4.1.4. Effect of recombinant CYP3A5*8 and CYP3A5*9 on the formation of N-DMT ...... 69 4.1.5. Effect of novel CYP3A4 intronic variant on the formation of α-OHT and N-DMT ...... 72 4.2. SPECIFIC AIM 2: CLINICAL ASSESSMENT OF CYP3A INDUCTION BY TAMOXIFEN ...... 74 4.2.1. LC-MS/MS method development for quantitation of Midazolam ...... 74 4.2.2. Induction of CYP3A by TAM in Breast Cancer Patients ...... 78 4.3. SPECIFIC AIM 3: IMPACT OF CYP3A AND PXR VARIANTS ON CYP3A INDUCTION ...... 83 4.3.1. Association of CYP3A and PXR Genotypes with Fold Change in Clearance...... 83 5. CHAPTER FIVE: DISCUSSION ...... 87
5.1. CONTRIBUTION OF CYP3A4/5 AND THE IMPACT OF ITS POLYMORPHIC EXPRESSION TO THE FORMATION OF Α-OHT AND N-DMT ...... 91 5.2. CLINICAL ASSESSMENT OF CYP3A INDUCTION BY TAMOXIFEN ...... 93 5.3. INFLUENCE OF CYP3A AND PXR POLYMORPHISMS ON CYP3A INDUCTION BY TAMOXIFEN .... 95 6. CHAPTER SIX: CONCLUSIONS AND FUTURE DIRECTIONS ...... 97 REFERENCES ...... 101
IX List of Figures
Figure 1: Major pathways involved in Tamoxifen metabolism ...... 6
Figure 2: Inter-individual variability in clearance of anti-cancer compounds ...... 9
Figure 3: Potential sources of inter-individual variability in PK of drugs ...... 9
Figure 4: Relative abundance of CYPs in liver microsomes...... 11
Figure 5: Relative contribution of CYPs to drug metabolism...... 12 Figure 6: Schematic representation of ligand mediated PXR activation and CYP3A induction ...... 17
Figure 7: Schematic representation of CYP3A locus on chromosome 7. The ...... 29
Figure 8: Schematic of hepatocyte treatment for CYP3A induction studies...... 37
Figure 9: Metabolism of Midazolam to 1-OH and 4-OH midazolam by CYP3A4/5 ...... 39 Figure 10: A typical HPLC chromatogram of 6-β-hydroxy testosterone and 11 α-hydroxy progesterone (internal standard) in the microsomal incubates...... 49
Figure 11: Study schematics of the pharmacokinetic trial ...... 56
Figure 12: A typical allelic discrimination plot indicating the three genotypes...... 59 Figure 13. A typical LC-MS/MS chromatogram of α-OHT (A) and N-DMT (B) in the microsomal incubates...... 61 Figure 14. The enzyme kinetics of α-hydroxy tamoxifen formation from TAM by the recombinant CYP3A4 (A) and CYP3A5 (B) isoforms. Each data point represents the mean of two 10 minutes incubations of TAM (0-50 µM) with 50 pmol of CYP3A4 or CYP3A5 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from Michaelis-Menten model using WinNonlin 5.2...... 62 Figure 15. The enzyme kinetics of N-desmethyl tamoxifen (N-DMT) formation from TAM by the recombinant CYP3A4 (A) and CYP3A5 (B) isoforms. Each data point represents the mean of two 10 minutes incubations of TAM (0-50 µM) with 50 pmol of CYP3A4 or CYP3A5 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from Michaelis- Menten model using WinNonlin 5.2...... 63
X Figure 16. Comparison of Vmax of α- OHT formation between the three CYP3A5*1/*1, *1/*3 and *3/*3 genotypes. Each point represents the Vmax estimated by fitting the data to Michaelis- Menten kinetics using nonlinear regression analysis. TAM (0-50 µM) was incubated with genotyped human liver microsomes as described in the methodology section. There was no significant difference between the three genotypes...... 64 Figure 17. Correlations between Vmax of α-OHT formation and (A) CYP3A4 protein, (B) CYP3A5 protein in a panel of genotyped human liver microsomes...... 65 Figure 18. Correlations between Vmax of α-OHT formation and (A) testosterone-6-β- hydroxylation, (B) midazolam-1-hydroxylation in genotyped human liver microsomes...... 65 Figure 19. Comparison of Vmax of N-DMT formation between the three CYP3A5*1/*1, *1/*3 and *3/*3 genotypes. Each point represents the Vmax estimated by fitting the data to Michaelis Menten kinetics using nonlinear regression analysis. TAM (0-50 µM) was incubated with genotyped human liver microsomes as described in the methodology section. There was a significant difference between CYP3A5*1/*1 and CYP3A5 *1/*3 or CYP3A5*3/*3 (p<0.05)...... 68 Figure 20. Correlations between Vmax of N-DMT formation and (A) CYP3A4 protein, (B) CYP3A5 protein in a panel of genotyped human liver microsomes...... 68 Figure 21. Correlations between Vmax of α-OHT formation and (A) testosterone-6-β- hydroxylation, (B) midazolam-1-hydroxylation in genotyped human liver microsomes...... 69 Figure 22. The enzyme kinetics of N-desmethyl tamoxifen (N-DMT) formation from TAM by the recombinant CYP3A5, CYP3A5*8 and CYP3A5*9 microsomes. Each data point represents the mean of two 10 minute incubations of TAM (0- 50 µM) with 50 pmol of CYP3A5 or 3A5*8 or 3A5*9 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from Michaelis-Menten model using WinNonlin 5.2...... 71
XI Figure 23. The enzyme kinetics of 1-hydroxy-midazolam formation from midazolam by the recombinant CYP3A5, CYP3A5*8 and CYP3A5*9 microsomes. Each data point represents the mean of two 5 minutes incubations of midazolam (0-400 µM) with 50 pmol of CYP3A5 or 3A5*8 or 3A5*9 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from substrate inhibition model using WinNonlin 5.2...... 71
N Figure 24. A typical chromatogram of a blank plasma spiked with MDZ, labeled 153- MDZ (IS), 4-OH MDZ and 1-OH MDZ...... 75 Figure 25. Representative calibration plasma standard curves for Midazolam (a), and 1- OH-MDZ in human plasma samples...... 77 Figure 26. Plasma concentration time profile of MDZ in breast cancer patients on Day 0 (Blue), Day 1 (Green) and Day 42 (Red) (A). Profile of patient ID= 06 showing induction of CYP3A on Day 42 as seen by decrease in the AUC and Cmax (B)...... 79 Figure 27. Changes in oral clearance (CL/F, L/hr) of MDZ between Day 0 and Day 42, and Day 1 and Day 42 (A). Changes in AUC of MDZ between Day 0 and Day 42, and Day 1 and Day 42 (B). Changes in half life of MDZ between Day 0 and Day 42, and Day 1 and Day 42 (C). CL/F and AUC estimates were determined by noncompartmental analysis using WinNonlin 5.2...... 82 Figure 28. Association of CYP3A5 genotype with CYP3A induction determined as fold change in midazolam oral clearance. DNA was isolated from fresh blood collected in EDTA vacutainers using Puregene kit and genotyped using TaqMan SNP genotyping assay...... 84 Figure 29. Association of PXR -25385C>T genotype with CYP3A induction determined as fold change in midazolam oral clearance. DNA was isolated from fresh blood collected in EDTA vacutainers using Puregene kit and genotyped using TaqMan SNP genotyping assay...... 85 Figure 30. Association of PXR -24381 A>C genotype with CYP3A induction determined as fold change in midazolam oral clearance. DNA was isolated from fresh
XII blood collected in EDTA vacutainers using Puregene kit and genotyped using TaqMan SNP genotyping assay...... 85 Figure 31. Association of mean plasma α-OHT (ng/ml) between CYP3A5*1/*3 vs CYP3A5*3/*3 genotypes on Day 1 and Day 42...... 86
XIII List of Tables
Table 1. List of known CYP3A inducers ...... 15
Table 2. Factors influencing the variability in CYP3A induction by drugs ...... 19
Table 3. List of common reversible and mechanism based inhibitors ...... 22 Table 4. Classification of CYP3A inhibitors based on their potency (Adapted from US FDA Drug Interaction guidance) ...... 23
Table 5. Distribution of important CYP3A polymorphisms in various ethnic groups. ... 30
Table 6. Enzyme kinetic parameter estimates for the formation of α-OHT and N-DMT by recombinant CYP3A4 and CYP3A5. Each incubation contained TAM (0-50 µM), 50 pmol of rCYP3A4 or rCYP3A5 and a NADPH-regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis Menten model using non linear regression analysis. Results are Mean ± SE from duplicate incubations...... 62 Table 7. Enzyme kinetic estimates for the formation of α-OHT and N-DMT in a panel of genotyped human liver microsomes...... 66 Table 8. Enzyme kinetic parameter estimates for the formation of N-DMT and 1-hydroxy midazolam by recombinant CYP3A5, CYP3A5*8 and CYP3A5*9 from TAM and midazolam, respectively. Each incubation contained TAM (0-50 µM) or Midazolam (0-400 µM), 50 pmol of rCYP3A5 or rCYP3A5*8 or rCYP3A5*9 and a NADPH-regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis Menten model for N-DMT formation and substrate inhibition kinetics for 1-hydroxy midazolam formation, using non linear regression analysis. Results are Mean ± SE from duplicate incubations...... 70 Table 9. Enzyme kinetic parameter estimates for the formation of α-OHT and N-DMT by CYP3A4 intronic variant from TAM. Each incubation contained TAM (0-50 µM), 0.1mg/ml of protein and a NADPH-regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis Menten model for α-OHT and N-DMT formation using non linear regression analysis. Each incubation was performed in duplicates...... 72
XIV Table 10. Enzyme kinetic parameter estimates for the formation of 6-β-hydroxy testosterone by CYP3A4 intronic variant from testosterone. Each incubation contained testosterone (0-400 µM), 0.25mg/ml of protein and a NADPH- regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis Menten model for 6-β-hydroxy testosterone formation using non linear regression analysis. Each incubation was performed in duplicates...... 73
Table 11. Demographics of patients enrolled in the PK study ...... 78
Table 12. Changes (%) in Midazolam Pharmacokinetics in Patients (N=6) ...... 80 Table 13. Pharmacokinetic estimates of midazolam after administration of 2 mg oral midazolam syrup in 13 breast cancer patients on three visits...... 81
Table 14. Percent change in midazolam oral clearance due to CYP3A induction by ...... 94
XV LIST OF ABBREVIATIONS
α -OHT Alpha hydroxy tamoxifen 1-OH MDZ 1-hydroxy midazolam 4-OH MDZ 4-hydroxy midazolam 4-OHT 4-hydroxy tamoxifen 6-MP 6-mercaptopurine ACS American Cancer Society AI Aromatase Inhibitor AIC Akaike Information Criteria AUC Area under the concentration-time curve BIC Bayesian Information Criteria BRCA-1 Breast Cancer-1 CAR Constitutive Androstane Receptor CL/F Oral clearance CLint Intrinsic Clearance Cmax Maximum plasma drug concentration Cmin Minimum plasma drug concentration CYP Cytochrome P450 ER Estrogen Receptor FAM 6-carboxyfluorescein FDA Food and Drug Administration FT-ICR Fourier Transform-Ion Cyclotron Resonance FXR Farnesoid X Receptor GCRC General Clinical Research Center HER2 Human Epidermal growth factor Receptor 2 HIV Human Immunodeficiency Virus hPAR Human Proteinase-Activated Receptor HPLC High performance Liquid Chromatography IRB Institutional Review Board IdMOC Integrated discrete multiple organ culture system Km Michealis Menten constant
XVI LC-MS Liquid Chromatography Mass Spectrometry LHRHa Leutinizing hormone analogue LTQ-FT Linear Trap Quadruple-Fourier Transform MDZ Midazolam MDR1 Multi-Drug Resistance 1 MRP2 Multi-Drug Resistance Protein 2 NADPH Nicotinamide Adenine Dinucleotide Phosphate N-DMT N-desmethyl tamoxifen OATP-C Organic Anion-Transporting Polypeptide-C OATP-2 Organic Anion-Transporting Polypeptide2 P-gp P-glycoprotein PK Pharmacokinetics PXR Pregnane X Receptor RT-PCR Reverse transcription polymerase chain reaction RXR Retinoic Acid X Receptor SE Standard Error SERM Selective Estrogen Receptor Modulator SULT Sulfotransferases SXR Steroid X Receptor TAM Tamoxifen Tmax Time to the maximum plasma concentration TPMT Thiopurine Methyl Transferase UGT UDP glucuronosyl transferases UNG Uracil N Glycosylase Vd Volume of distribution VDR Vitamin D Receptor VKORC1 Vitamin K Epoxide Reductase Complex subunit 1 Vmax Maximum reaction rate of enzymes
XVII 1. CHAPTER ONE: LITERATURE REVIEW
1.1. Introduction
1.1.1. Breast Cancer and Endocrine Therapy
Breast cancer is the second most common cancer among women and the second
leading cause of cancer death in the US. During their life time, 1 in 8 (12%) women have the
risk of developing breast cancer with an expected mortality rate of 1 in 35 (3%). According
to the 2009 report of American Cancer Society (ACS), an estimated 192,370 new cases of
invasive breast cancer will be diagnosed, and approximately 40,610 will succumb to the
disease (ACS 2009 statistics).
The various treatment options for breast cancer include a combination of radiation, surgery,
chemotherapy, hormonal and targeted therapy. The therapy depends on the tumor size,
location, stage, age of patient, hormonal receptor and menopausal status. Endocrine
(hormonal) therapy has been widely used for chemoprevention and treatment in patients
expressing estrogen receptor (ER) positive tumors. The role of estrogens in the pathogenesis
of breast cancer is well established. Estradiol binds to ER in the nucleus, and the ER
homodimer complex then binds to the estrogen receptor elements present upstream to the
promoter region of ER target genes. This results in a conformational change, increasing the
transcription of genes responsible for cell proliferation leading to tumor progression (Klein-
Hitpass, et al., 1989;McDonnell and Norris, 2002). Since approximately 70% of the tumors
are positive for ERs, depriving the tumors of estrogen mediated stimulus remains the most
effective and targeted form of therapy. Two main isoforms of ER have been identified - ERα and ERβ with different tissue distribution and affinities to various SERMs (Katzenellenbogen
and Katzenellenbogen, 2000). ERα is widely expressed in breast cancer cells, endometrium,
ovarian cells and hypothalamus, while presence of ER β has been reported in kidney, brain,
bone, heart, lungs, intestinal mucosa and endothelial cells.
The first endocrine therapy developed by Dr. George Beatson in 1896 was by means of
bilateral ovaricectomy (Beatson GT, 1896). Over the past decades, several forms of
endocrine therapy for treatment of ER positive breast cancer have been introduced. These
include a) use of a selective estrogen receptor modulator to block the estrogen receptor
(SERM, eg, Tamoxifen) or down regulate estrogen receptor using estrogen receptor
antagonist (eg, Fulvestrant), b) suppression of estrogen synthesis in postmenopausal women
using aromatase inhibitors (eg, Letrozole), c) hormonal ablation by surgery or radiotherapy
or by administration of leutinizing hormone analogue (LHRHa) eg., Goserelin in
premenopausal women. Despite the availability of several treatment options, there is still a
need to better understand the disposition of these drugs in order to optimize the therapy and
minimize unwanted side effects.
1.1.2. Tamoxifen
Tamoxifen (TAM) is a selective estrogen receptor modulator (SERM) that is currently FDA-
approved for the treatment of all stages of hormone-responsive breast cancer and for the
prevention of breast cancer in high-risk women (Jordan, 2003b;Brauch and Jordan, 2009).
Originally tested as a contraceptive in 1976, TAM was later found to suppress breast cancer
proliferation in in vitro studies and was developed into a hormonal therapy for breast cancer.
Since its introduction, TAM has been the first line therapy for patients with estrogen receptor
2 positive tumors for over three decades. A five-year TAM therapy in patients with invasive
breast cancer results in a 31% decrease in the annual death rate and a 40-50% decrease in the
risk of primary breast cancer in high risk women (Jordan, 2003a). Notwithstanding the
advent of aromatase inhibitors (AIs) and newer SERMs like raloxifene, TAM remains an
important member of the armamentarium against breast cancer (Bao, et al., 2006;Fisher, et al.,
2005b;Ligibel and Winer, 2005). It continues to be the only drug available for use in pre-
menopausal women for chemoprevention or treatment of ER-positive breast cancer (White,
1999). TAM acts by competitively binding to ER and blocks the action of estradiol. TAM
also has a mixed ER agonist and antagonist properties depending on the target tissues. By
way of its agonist action, TAM helps to maintain bone mineral density and lower lipid levels
thereby ameliorating bone and cardiovascular diseases in women (Osborne, 1998;Kristensen, et al., 1994). In the uterus, TAM’s agonist action has been reported to increase the risk of developing endometrial cancer in postmenopausal women (Jordan and Morrow, 1994).
Despite its 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 a 2 to 8 fold higher risk of developing endometrial cancer. Only half of the patients treated respond to adjuvant TAM (Jordan, 2000). Clinical studies suggest that plasma concentration of TAM and its metabolites vary widely among patients (Lonning, et al.,
1992;Stearns, et al., 2003). Inter-individual differences in the formation of active/toxic metabolites may be an important source of variability in response to TAM. This variability
3 can be attributed to the factors that impact the basal and induced expression of CYP3A
enzyme.
1.1.3. Pharmacokinetics of Tamoxifen
After an oral administration of 20 mg dose, TAM is rapidly absorbed and the peak plasma
concentrations (Cmax) are achieved within 3-4 hours in healthy volunteers (Guelen, et al.,
1987). Its bioavailability is approximately 100% suggesting minimal first pass metabolism
(Tukker, et al., 1986;Herrlinger, et al., 1992). Due to its high lipophilicity, TAM is
extensively bound (>95%) to the plasma protein albumin (Buckley and Goa, 1989).
Distribution of TAM in 14 patients undergoing long term therapy revealed the presence of
higher concentrations in breast, uterus, liver, lung, ovaries, endometrium and pancreas (Lien,
et al., 1991;Fromson, et al., 1973). The concentrations of TAM and N-DMT were 20-400
fold higher in endometrium and 5-11 higher in breast tissue when compared to plasma levels
(Kisanga, et al., 2004;Giorda, et al., 2000). The apparent volume of distribution of TAM is
50-60L (Lonning, et al., 1992).
TAM is extensively metabolized in humans to form a large number of metabolites. Several
of these metabolites are biologically active contributing to the therapeutic efficacy and/or
toxic side effects. The biotransformation of TAM is primarily mediated by cytochrome-P450
enzymes, mainly through N-demethylation and hydroxylation to form three primary
metabolites, α-hydroxy-TAM (α-OHT), N-desmethyl-TAM (N-DMT), and 4-hydroxy-TAM
(4-OHT) [Fig. 1].
4 Several studies have reported that CYP3A is the major enzyme involved in N-demethylation,
whereas CYP2D6 is the primary catalyst for 4-hydroxylation (Desta, et al., 2004;Williams, et al., 2002). The plasma levels of N-DMT are twofold higher than TAM, since it has a half life twice that of TAM (14 days vs. 7 days). N-DMT and 4-OHT are further metabolized to a recently characterized active metabolite 4-hydroxy–N-desmethyl tamoxifen (endoxifen).
Endoxifen and 4-OHT are the active therapeutic moieties and are formed via 4-hydroxylation of N-DMT and TAM, respectively by CYP2D6. When compared with TAM, these metabolites are at least 100 times more potent in binding to estrogen
5
CYP3A CYP2D6
CYP3A4/5
CYP3A
CYP2D6
Figure 1: Major pathways involved in Tamoxifen metabolism
6 receptor and suppressing breast cancer cell proliferation in vitro (Jordan, 1982). Endoxifen
has a similar affinity to ER receptor as that of 4-OHT, and is present at an average
six fold higher concentrations than 4-OHT (Stearns, et al., 2003;Oseni, et al., 2008). Another
metabolite of significance is α-OHT, a genotoxic compound, which upon further activation
forms DNA adducts and has been proposed to cause endometrial cancer (Crewe, et al.,
1997;Boocock, et al., 2002). α-OHT is exclusively formed from TAM by CYP3A. It
undergoes sulphonation by hydroxysteroid sulfotransferases and binds to the amino groups of
guanine in DNA, leading to the formation of DNA adducts in the endometrium (Kim, et al.,
2005;Shibutani, et al., 1998).
TAM and its metabolites (4-OHT and endoxifen) further undergo Phase II conjugation
reactions by human UDP glucuronosyl transferases (UGTs) UGT1A4, UGT2B15 and
sulfotransferases (SULT) SULT1A1 (Nishiyama, et al., 2002;Ogura, et al., 2006). 4-OHT
was mostly found as glucuronide conjugates in the bile and urine. (Poon, et al., 1993;Sun, et
al., 2006).
1.2. Variability in Pharmacokinetics/Pharmacodynamics of Anti-cancer Drugs
A very high inter-individual variability (25-70%) in the clearance of anticancer drugs has
been reported, resulting in different pharmacokinetic and pharmacodynamic profiles (Fig.
2) (Felici, et al., 2002;Mathijssen, et al., 2007). Such a wide inter-individual variability in
TAM and other anti-cancer agents often results in different therapeutic outcomes in
patients. The primary route of elimination for most anticancer compounds is via hepatic
7 clearance, and is subject to wide variability due to the differences in the expression of
CYPs and UGTs. Recognizing the underlying causes for variability in pharmacokinetics
/pharmacodynamics will help in optimizing dosage regimen and improving the benefit
/risk ratio in patients. Some of the potential sources of variation include differences in absorption, distribution, metabolism and excretion of drugs, genetic polymorphisms in enzymes, transporters and receptors involved in the disposition pathways, physiological factors including age, gender, disease state and organ dysfunction, and drug interactions due to concomitant administration of drugs/herbal remedies (Fig. 3). Furthermore, differences in concentrations of drugs in tumors can also be a significant factor contributing to the variability (Zucchetti, et al., 1999).
Identifying genetic polymorphisms in CYP/UGTs, drug transporters and target receptors that are involved in the drug disposition can aid in individualizing dosage regimen by increasing the number of responders and decreasing the number adverse drug reactions.
Pharmacogenetics has already been implemented in oncology practice to identify patients who respond to trastuzumab (Herceptin) and gefitinib (Iressa) by testing for over expression of HER2/neu oncogenes and mutations in epidermal growth factor, respectively (Frueh, et al., 2008). A detailed account on the impact of pharmacogenetics on the anticancer drugs is provided in section 1.4.
8 Figure 2: Inter-individual variability in clearance of anti-cancer compounds (Adapted from Felici A et al 2002)
Age Alcohol Sex
Smoking Weight
PK Environ- Disease ment
Medic Compliance -ation
Organ Dysfunct- Genetics ion
Figure 3: Potential sources of inter-individual variability in PK of drugs
9 1.3. Overview of Cytochrome P450 (CYP) 3A Enzymes
CYP enzymes play an important role in the metabolism of both endogenous (steroids, bile
acids, cholesterol) and exogenous (drugs, chemicals, environmental toxins) compounds by
converting them into more hydrophilic products, thereby enhancing their elimination from
the body (Coon, 2005;Guengerich, 2006). CYPs belong to a family of membrane bound
heme containing proteins and are localized primarily in the endoplasmic reticulum of the
cell. The human genome is encoded with 57 CYP proteins, and nearly 15 of them are
involved in the biotransformation of xenobiotics and endogenous chemicals. CYP1, 2 and
3 are the primary enzymes involved in the metabolism of xenobiotics (Spatzenegger and
Jaeger, 1995).
Among all the CYP enzymes, CYP3A is most abundantly expressed in liver and intestine,
comprising almost 30-40% of the total hepatic and 80% of intestinal CYP content [Fig. 4]
(Paine, et al., 2006;Shimada, et al., 1994). Furthermore, approximately 50-60% of the
drugs in the market are metabolized by CYP3A enzymes [Fig. 5] (Li, et al., 1995;Evans
and Relling, 1999). Hence inter-individual variability in CYP3A expression can have
significant influence on systemic exposure of the substrate drugs, altering their efficacy
and toxicity. There are four isoforms of CYP3A- CYP3A4, CYP3A5, CYP3A7 and
CYP3A43. In adults, CYP3A4 and CYP3A5 are the major isoforms with approximately
84% amino acid sequence homology and have significant overlapping substrate
specificities. The expression of CYP3A7 is predominant during fetal development and is
silenced or relatively low 1 or 2 years after birth. Conversely, the expression of
CYP3A4/5 is very low during fetal life and reaches 50% of adult levels within a year after
10 birth (Hines, 2007;de Wildt, et al., 1999). Although CYP3A4 is highly expressed in liver and intestine, the expression of CYP3A5 is higher than CYP3A4 in extrahepatic tissues like kidney, lungs and blood. CYP3A43 is a relatively new isoform and is expressed at lower levels in adult and fetal livers (Westlind, et al., 2001a). Moreover, the contribution of CYP3A43 and its functional significance to drug metabolism is not well characterized.
Others CYP3A 26% 28%
CYP2D6 2% CYP1A2 14%
CYP2C CYP1A6 18% 5% CYP2E1 7%
Figure 4: Relative abundance of CYPs in liver microsomes.
11 CYP1A6 2% CYP2E1 2% CYP1A2 4% CYP2C8-10 10% CYP2C19 2%
CYP3A 50%
CYP2D6 30%
Figure 5: Relative contribution of CYPs to drug metabolism.
1.3.1. Variability in Cytochrome P450 (CYP) 3A Enzymes
A substantial inter-individual variation of approximately 40-60 fold, in the expression of
CYP3A enzymes and up to 400 fold in CYP3A activity due to drug interactions (CYP
inhibition/induction) has been reported (Lamba, et al., 2002;Thummel and Wilkinson,
1998). Using midazolam as a probe substrate, Thummel et al determined the inter- and
intra-individual variability in the expression of CYP3A4 in the biopsy tissues of 21 donor
livers. They reported a 37 fold variation with the CYP3A protein levels ranging from 1.1
to 40.8 pmol/mg (Thummel, et al., 1994a). In another study examining the liver and
intestinal CYP3A levels by Paine et al, the CYP3A content was found to be ranging from
12 4.0 to 262.0, 3.0 to 90.8, 2.1 to 98, and <1.9 to 59.5 pmol/mg of protein for liver,
duodenum, jejunum, and ileum, respectively accounting for up to 64 fold variation
(Paine, et al., 1997).
A combination of environmental, genetic, physiological and patho-physiological factors
is responsible for such an extensive variability. Environmental factors such as food
intake, smoking and concomitant drug administration lead to increased or decreased
CYP3A activity. Among all these factors, inhibition/induction of CYP3A and the
presence of single nucleotide polymorphisms in drug metabolizing enzymes (and
transporters) have been considered to be the major sources of variability (Plant, 2007).
1.3.2. Induction of CYP3A
Induction of CYP3A4/5 is an indirect, slow regulatory process occurring at the
transcriptional level and resulting in increased protein expression/activity. From the
evolutionary point of view, induction can be considered as the body’s defense mechanism
against toxic chemicals. The net effect of drug mediated CYP3A induction is alteration in
pharmacokinetics and pharmacodynamics of substrate drugs (Kolars, et al., 1991;Dilger,
et al., 2000). The pharmacokinetic or clinical impact of CYP induction depends on the
duration of exposure to inducer, localization of the protein, enzyme biosynthesis/
degradation and the pharmacological effect of drug/metabolites.
Induction is usually observed after administration of repeated doses of drug. There are
two major consequences of CYP3A induction 1) Increase in the clearance of the substrate
drugs, resulting in decreased plasma concentration and reduced efficacy. 2) Increase in
13 toxicity due to the augmented formation of reactive metabolites or decrease in toxicity
due to enhanced detoxification process (Seeff, et al., 1986). Pharmacokinetically,
induction results in decrease in AUC, half-life, bioavailability and increase in the plasma
clearance of the substrates. If a drug induces its own metabolism, it is known as an auto-
inducer (eg., Carbamazepine, Efavirenz).
Several known CYP3A4/5/7/43 inducers have been presented in Table.1. Rifampicin is
one of the most potent CYP3A inducers and has been implicated in several drug
interactions. In addition to inducing CYP3A, rifampicin also induces CYP1A2, 2A6, 2B6,
2C8, 2C18, 2C19, 3A5 and 3A7 (Niemi, et al., 2003). When co-administered with
rifampicin, a significant decrease in the AUC of oral CYP3A substrates is observed rendering the drugs ineffective. For example, the AUC of the following drugs are suppressed by more than 80% significantly reducing therapeutic efficacy - midazolam
(98%), triazolam (95%), tamoxifen (86%), tormifene (87%), sirolimus (82%), verapamil
(91%), simvastatin (81%), nifedipine (92%), warfarin (85%), indinavir (92%), nelfinavir
(82%) (Niemi et al 2003). Co-administration of rifampicin also decreased the plasma
concentration of immunosuppressive agent cyclosporine in transplant patients, resulting
in acute allograft rejection (Modry, et al., 1985;Riva, et al., 1996;Hebert, et al.,
1992;Hebert, et al., 1999;Chenhsu, et al., 2000). Another clinically important interaction
that led to undesirable consequences was unwanted pregnancies observed in women who
were administering oral contraceptives with CYP3A inducers like rifampicin or St.John’s
Wort (Heimark, et al., 1987). Hence, CYP3A induction has been considered to be an
undesirable property and many pharmaceutical companies routinely evaluate CYP
14 induction potential of new drugs in the discovery stage as a part of selection of lead
candidates (Smith, 2000;Lin, 2006).
Table 1. List of known CYP3A inducers
CYP3A Inducers References
CYP3A4 Rifampicin, Carbamazepine, Phenytoin Krusekopf et al. 2003, Luo Dexamethasone, Phenobarbital, Efavirenz, et al. 2002, Usui et al 2003 Sulfinpyrazone, St. Johns Wort, Ritonavir Hariparsad N et al 2004 Troglitazone, Taxol, Topiramate Nallani SC et al 2003 CYP3A5 Rifampicin, Dexamethasone, Phenytoin, Roberts PJ et al 2008, Burk Carbamazepine, Cyclosporin O et al 2004, Usui et al 2003, Krusekopf et al. 2003 CYP3A7 Rifampicin, Phenytoin, Clotrimazole, Usui et al 2003 Cyclosporin, Dexamethasone Maruyama et al 2007 CYP3A43 Dexamethasone Krusekopf et al. 2003
In the case of rifampicin, the maximum CYP3A induction occurs within a day, reaching plateau after a weak of rifampicin treatment and the enzyme activity returns to the baseline activity within two weeks after discontinuation of therapy (Tran, et al., 1999).
Furthermore, the influence of CYP3A induction by rifampicin was found to be greater with orally administered compounds that undergo extensive first pass metabolism than intravenous administration. Understanding the time course of induction and de induction will help the clinician in modifying the dosage of CYP3A substrates.
15 1.3.2.1. Mechanism of CYP3A Induction – Role of PXR
The expression of CYP3A is regulated by an orphan nuclear receptor Pregnane X receptor
(PXR) (Lamba, et al., 2002). In 1998, three different groups identified the same nuclear receptor responsible for regulating the expression of CYP3A4 and named it PXR, Steroid
X receptor (SXR) and human proteinase-activated receptor (hPAR) (Kliewer, et al.,
1998;Blumberg, et al., 1998;Bertilsson, et al., 1998). PXR is highly expressed in liver and intestine. Notably, CYP3A is also found at higher levels in the same tissues and is induced by several exogenous and endogenous compounds. When a ligand binds to PXR in cytoplasm, this ligand-PXR complex translocates to the nucleus of the cell and heterodimerizes with 9-cis retinoic acid receptor (RXR) (Kliewer, et al., 2002b). The PXR
RXR heterodimer then binds to a PXR response element upstream to the promoter region of CYP3A leading to a change in conformation, thereby increasing the transcription of
CYP3A4 and enhancing the metabolism of several drugs [Fig. 6] (Willson and Kliewer,
2002;Baes, et al., 1994). The response elements to which PXR binds can be a direct repeat with 3 or 4 nucleotide spacer (DR3 or DR4) or an everted repeat with a 6 nucleotide spacer (ER6). Some of the well known ligands for PXR include rifampicin, paclitaxel, nifedipine, phenobarbital, ritonavir, St. John’s Wort, troglitazone, endogenous compounds like estradiol, corticosterone and bile acids. (Kliewer, et al., 2002a). In addition, PXR is known to regulate the expression of CYP3A5, CYP3A7, CYP2B6, CYP2C9, UDP- glucuronyltransferases (UGT) UGT1A1, 1A3, 1A4, 1A6, glutathione S-transferase A2
(GSTA2) and sulfotransferase (SULT) 1A1 and drug transporters (P-glycoprotein
(MDR1), multidrug-resistance-associated protein 2 (MRP2) and organic anion transporter polypeptide 2 (OATP2)) (Burk, et al., 2004;Gardner-Stephen, et al., 2004;Gerbal-Chaloin,
16 et al., 2001;Xie, et al., 2003;Duanmu, et al., 2002;Goodwin, et al., 2001). Hence PXR has been known as “Master Regulator” of drug metabolizing enzymes and transporters.
(Dussault and Forman, 2002)
Ligand Hepatocyte
Cytoplasm
RXR PXR
PXR RXR Drug Nucleus
CYP3A4
PXR RXR Drug OH PXR-RE CYP3A4 Endoplasmic Reticulum mRNA
CYP3A4 mRNA
PXR- Pregnane X Receptor, PXR – Retinoic Acid X Receptor, PXR- RE- PXR Response Elements
Figure 6: Schematic representation of ligand mediated PXR activation and CYP3A induction
Though PXR activation is mainly responsible for the induction of CYP3A enzymes, other
nuclear receptors known to modulate CYP3A expression include constitutive androstane receptor (CAR), vitamin D receptor (VDR) and Farnesoid X receptor (FXR).
Other mechanisms that can result in enhanced expression of CYP3A are increased
mRNA stability or translational efficiency and protein stabilization induced by
posttranslational modifications (Lin and Lu, 2001). For example troleandomycin does not
result in increased production of CYP3A4 protein, but decreases its rate of degradation.
(Watkins, et al., 1986;Danan, et al., 1981).
17
Inhibition of PXR activity has been considered as a strategy to overcome drug resistance
by attenuating the expression of drug metabolizing enzymes in tumor tissues (Masuyama,
et al., 2007). Some of the compounds that are known to inhibit PXR include sulforaphane,
ketoconazole, antineoplastic agent trabectedin and HIV protease inhibitor A-792611
(Wang, et al., 2007;Synold, et al., 2001;Healan-Greenberg, et al., 2008). However, the
clinical utility of PXR antagonists in vivo is not known and requires further research
(Biswas, et al., 2009).
1.3.2.2. Variability in CYP3A Induction
A large variability has been observed in the levels of CYP3A protein or mRNA and its
activity post induction. Using 6-β-hydroxycortisol/cortisol ratio as a marker, Ged et al
evaluated the CYP3A induction potential by rifampicin (600 mg/day for 4 days) in 18
patients. A 2-30 fold change was observed in the induction with the extent of increase in
the protein levels ranging from 160% to 2900% (Ged, et al., 1989;Lin and Lu, 2001).
Similarly, Kolars et al reported a 0-12 fold change in intestinal CYP3A4 mRNA levels
after treatment of rifampicin 600mg/7days (Kolars, et al., 1992).
18 Table 2. Factors influencing the variability in CYP3A induction by drugs (Adapted from (Tang, et al., 2005))
Factors Consequences Variable transport and metabolism of Variable tissue and intracellular inducers in vivo inducer concentrations resulting in different extent of induction Genetic variations of P450 genes and their Altered pattern of induction regulatory regions Genetic variations of receptors and Altered pattern of induction regulatory proteins required for induction Physiological factors: disease states Altered response to inducers (inflammation, infection, and liver dysfunction), gender, hormonal homeostasis Environmental factors: dietary components, Altered response to inducers environmental contaminants
The extent of decrease in AUC of verapamil and midazolam caused by CYP3A induction
due to rifampicin ranged from 5 to 60 fold and 11.5 to 55 fold, respectively. (Fromm, et
al., 1998;Backman, et al., 1996). Various factors contributing to variability in CYP3A
induction have been tabulated in Table.2 above. Identifying the factors that result in
induction of an enzyme and determining their contribution will result in modifying the
treatment regimen accordingly.
1.3.3. Inhibition of CYP3A
Inhibition of CYP3A enzyme is the most common cause of observed clinical drug
interactions and has led to withdrawal of several drugs from the market eg., terfenadine,
mibefradil and cisapride (Lasser, et al., 2002). Unlike induction, CYP3A inhibition is an
instantaneous process and usually occurs after a single dose administration of the
19 inhibitor. As a result of inhibition, there is an increase in plasma concentration of the
substrate drugs and their bioavailability, leading to undesirable prolongation of pharmacological effects (Lin and Lu, 1998;Lin and Lu, 2001). For example, torsades de pointes or fatal ventricular arrhythmia have been reported to occur with co-administration of nonsedating anti-histamines like terfenadine or astemizole with potent CYP3A inhibitors like ketoconazole, clarithromycin, erythromycin and grapefruit juice (Dresser, et al., 2000). Other examples of inhibition mediated clinical drug interaction resulting
due to co-administration of CYP3A inhibitors includes severe rhabdomyolysis with
statins (cerivastatin, atorvastatin and lovastatin), symptomatic hypotension with calcium channel antagonists (nifidepine, felodipine, mibefradil) and excessive sedation with benzodiazepines (midazolam, diazepam), (Neuvonen and Suhonen, 1995;Madsen, et al.,
1996;Olkkola, et al., 1993;Ozdemir, et al., 1998;Wysowski and Swartz, 2005)
Although most of the interactions have negative consequences, CYP3A inhibition has also been found to be beneficial for certain compounds. Ritonavir, a potent CYP3A4 inhibitor has been employed successfully to boost the bioavailability of other protease inhibitors used widely for treatment of HIV infection (Cooper, et al., 2003). Addition of ritonavir to patients undergoing saquinavir therapy resulted in 33 and 58 fold greater
Cmax and AUC, respectively (Merry, et al., 1998;Merry, et al., 1997). Another good example is cyclosporin, a calcineurin inhibitor and an immunosuppressive agent, is a substrate of CYP3A4. Similar to other immunosuppressive agents, the high cost associated with the use of cyclosporin has been a barrier to its use (Evans and Manninen,
1988). By inhibiting CYP3A4 and increasing the bioavailability of cyclosporin, it has
20 been demonstrated that ketoconazole substantially (approx. 60 to 80%) reduced the dosage required to maintain adequate immunosuppression and therefore its cost (Keogh, et al., 1995;Gomez, et al., 1995;Martin, et al., 1999).
1.3.3.1. Mechanism of CYP3A Inhibition
The mechanisms involved in CYP3A inhibition include reversible, quasi-irreversible and irreversible (mechanism based) inhibition (Vanden, et al., 1995;Murray, 1997;Ortiz de
Montellano, 1995). Reversible inhibition has been the most common cause of drug-drug interaction. It is transient and occurs when an inhibitor forms weak bonds with CYP enzymes without inactivating it permanently. The enzyme activity usually returns to normal after removal of the inhibitor (Lin and Lu, 2001). Reversible inhibition can be further classified into competitive (substrate and inhibitor bind to the same active site at the enzyme), non-competitive (substrate and inhibitor bind to the different sites at the enzyme) and mixed type of inhibition (Rodriguez-Antona, et al., 2002). Some of the compounds that are known to exhibit reversible CYP3A inhibition are listed in Table 3.
Based on the potency and their ability to increase the AUC of co-administered compounds in vivo, USFDA has classified inhibitors as strong, moderate and weak inhibitors (Table 4).
In the case of irreversible mechanism based inhibition (suicide inhibition), the drug gets converted into a metabolic intermediate complex that results in a covalent modification of the catalytic site and leads to permanent inactivation of enzyme activity (eg., ritonavir,
21 verapamil, tamoxifen, clarithromycon, erythromycin) (Zhou, et al., 2005;Wang, et al.,
2005;Galetin and Houston, 2006;Polasek and Miners, 2006).
Table 3. List of common reversible and mechanism based inhibitors
Mechanism of Inhibitors References Inhibition
Reversible Fluconazole, Itraconazole, Dresser et al 2000 Ketoconazole, Quinidine, Indinavir Pelkonen et al 2008
Mechanism Based Ritonavir, Nelfinavir, Irinotecan Zhou S et al 2005 (Suicide) Bergamottin and Dihydroxy Dresser et al 2000 bergamottin (Grape fruit juice), Pelkonen et al 2008 Erythromycin, Clarithromycin, Verapamil, Mibefradil, Isoniazid, Diltiazem, Saquinavir
The covalent binding can occur either with the haem or the protein. The functional CYP activity is not restored by the removal of inhibitor, but only by de novo synthesis of enzymes (Lin and Lu, 2001). Some of the salient features of mechanism based inhibition are a) Time dependent inhibition b) Dose/concentration dependent inhibition c) NADPH dependent inhibition in vitro.
22 Table 4. Classification of CYP3A inhibitors based on their potency (Adapted from US
FDA Drug Interaction guidance)
Strong CYP3A Moderate CYP3A Weak CYP3A inhibitors inhibitors inhibitors ≥ 5-fold increase in AUC ≥ 2 but <5-fold increase in ≥ 1.25 but <2-fold increase in AUC AUC Atazanavir, Clarithromycin, Amprenavir, Aprepitant, Cimetidine Indinavir, Itraconazole, Diltiazem, Erythromycin, Ketoconazole, Nefazodone, Fluconazole, Fosamprenavir, Nelfinavir, Ritonavir, Grapefruit juice, Verapamil Saquinavir, Telithromycin
1.3.3.2. Variability in CYP3A Inhibition
Since the pharmacokinetic and clinical consequences are different for reversible and
irreversible inhibitors, there is considerable emphasis on the need to understand the
mechanism of CYP3A inhibition (Lin, et al., 2000). Furthermore, significant inter-
individual variability has been reported in drug-drug and food-drug interactions due to
CYP3A inhibition. With ketoconazole terfenadine interaction, a five-fold variation was observed in response to ketoconazole inhibition resulting in 1500% to 7200% increase in
AUC of terfenadine (Honig, et al., 1993). Similarly, a 20-fold difference was reported in the extent of increase in AUC of venlafaxine when co-administered with quinidine
(Lessard, et al., 1999). Bergamottin and dihydroxy bergamottin, components of grape fruit juice are inhibitors of intestinal CYP3A4 and have been reported to increase the
AUC of midazolam and cyclosporine by 26 to 100% and -16 to 200%, respectively (Yee, et al., 1995;Kupferschmidt, et al., 1995). The reasons for this variability can be attributed
23 to the differences in in vivo inhibitor concentrations, Ki values (inhibition constant),
substrate pharmacokinetics (high or low clearance compounds), basal level of enzymes
and the presence of genetic polymorphisms (Lin and Lu, 2001).
1.3.4. Implications of TAM Mediated CYP3A Induction/Inhibition
1.3.4.1. CYP3A Induction by TAM
Co-administration of TAM has been shown to markedly reduce the plasma concentration
and the area under the plasma concentration curve (AUC) of several drugs. The most
striking effects have been observed in clinical trials with TAM and aromatase inhibitors,
letrozole and anastrozole, wherein a mean reduction of 37% and 27% was observed in the
plasma levels of letrozole and anastrozole, respectively (Dowsett, et al., 1999;Dowsett, et
al., 2001). In case of TAM and letrozole interaction, AUC decreased in some subjects by
more than 60%. Such a decrease in concentration may have resulted in the overall lack of
therapeutic benefits. Since both TAM and letrozole are substrates of CYP3A, induction of
CYP3A by TAM could be one of the possible reasons to the decreased plasma levels of
letrozole. In addition, TAM can also induce its own metabolism, leading to different
plasma levels of active/toxic metabolites further contributing to the variability observed in
TAM therapy. The fact that CYP3A4 induction may have a profound influence on TAM
activity is supported by earlier studies where pre-administration of rifampicin, one of the
most potent CYP3A4 inducer known, resulted in reduced plasma levels and efficacy of
anti-estrogens TAM and toremifene (Kivisto, et al., 1998).
24 The potential of TAM to induce CYP3A in animal models and in vitro cell lines has been well established. In female rats treated with TAM, White et al observed up-regulation of
CYP3A activity as measured by the increase in 6- and 16 alpha hydroxylation of testosterone (White, et al., 1993). In another study, Nuwaysir et al observed dose- dependent increase in the expression of CYP2B1, CYP2B2, CYP3A after 7 days of administration of TAM to male and female rats (Nuwaysir, et al., 1995). A trend towards increase in clearance of midazolam (a probe substrate for CYP3A) in preclinical rat studies further supported the induction of CYP3A by TAM (Cotreau, et al., 2001). In previous studies from our laboratory, it was observed that TAM and 4-OHT up regulate the expression of CYP3A4 transcripts and activity in primary cultures of human hepatocytes, (Desai, et al., 2002). Furthermore, silencing hPXR employing siRNA sequence was found to abrogate hPXR activation and CYP3A4 induction by TAM, indicating the critical involvement of hPXR in mediating the inductive effect of TAM
(Sane, et al., 2008). In addition, TAM is also known to augment the expression of Phase
II enzymes (sulfotransferase, glutathione transferases) and drug transporters (P- glycoprotein, multidrug resistance protein2) (Hellriegel, et al., 1996;Nuwaysir, et al.,
1996;Nuwaysir, et al., 1998;Gant, et al., 1995;Riley, et al., 2000)
Despite the confirmation from in vitro and preclinical studies, clinical evidence showing induction of CYP3A by TAM in breast cancer patients is lacking. Furthermore, genetic variability in the expression of PXR is likely to impact the extent of CYP3A4 induction by TAM, which may result in alteration in its own metabolism to N-DMT and α-OHT
(auto-induction, also known as time-dependent changes) or that of other co-administered
25 drugs. Auto-induction can result in higher levels of N-DMT and α-OHT producing
different outcomes in patients.
1.3.4.2. CYP3A Inhibition by TAM
In human liver microsomes and cDNA expressed human CYP3A4/5 enzymes, TAM and
its metabolites N-DMT, 4-OHT and 3-OHT inhibited CYP3A activity measured as
midazolam-1-hydoxylation and testosterone-6β-hydroxylation (Zhao, et al., 2002).
Though TAM and N-DMT have been reported to be mechanism based CYP3A inhibitors
in vitro, so far there is paucity in data on inhibition mediated clinical drug - drug
interactions with other CYP3A substrates (Zhou, et al., 2005).
1.4. Impact of Pharmacogenetics on PK/PD of Anti-Cancer Drugs
The word “Pharmacogenetics” was first coined in 1959 and is defined as the study of
genetic influence on drug response (Kalow W 1962; Meyer UA 2004). Variability occurs
because of variations in DNA such as polymorphisms in a single gene, or a limited set of
multiple genes, sequences that influence enzyme or receptor activity. In the past few
decades, there have been several investigations documenting the influence of genetic
polymorphisms in drug metabolism enzymes to the variability in pharmacokinetics and
drug response. (Huang RS and Ratain MJ 2009; Gardiner SJ and Begg EJ 2006; Marsh S
and Liu G 2009; Tan SH et al 2008). Pharmacogenetics has already been implemented in
guiding dosage regimens for 6 mercaptopurine (6-MP), irinotecan and warfarin by
genotyping for thiopurine methyl transferase (TPMT), UGT1A1, CYP2C9 and vitamin k
epoxide reductase subunit 1 (VKORC1) polymorphisms, respectively. For example, 6-MP
26 is a prodrug and is metabolized to form thioguanine nucleotides, the active metabolites that kill tumor cells by inhibiting DNA and RNA synthesis. Thiopurine methyl transferase
(TPMT) is an enzyme that inactivates 6-MP preventing the formation of active metabolites. A trimodal distribution is observed with TPMT activity, with 90% individuals exhibiting high, 10% intermediate and 0.3% low enzyme activity (Maitland
ML et al 2006, Smith NF et al 2004; Innocenti F et al 2000). Individuals with low levels of TPMT require a modified dose of 6-MP to avoid the oxicity (severe myelosuppression) associated with higher levels of 6-MP (Maitland ML et al 2006; Huang SM et al 2006).
Recently dosage reduction has been recommended for individuals undergoing irinotecan therapy and expressing UGT1A1*28 allele (Frueh, et al., 2008). Presence of this allele leads to decreased glucuronidation of irinotecan leading to accumulation of the active metabolite SN-38 and resulting in grade 4 neutropenia (Innocenti and Ratain, 2002).
Thus, there is increasing evidence that simple genetic tests may be applied to minimize side effects that may be more deleterious than the health complaint, and identify patients with intrinsic resistance to commonly prescribed drugs so that an alternative drug can be selected (Blackhall, et al., 2006). Two pharmacogenetic tests have been recently approved by US FDA for clinical use. One is Roche’s AmplichipTM that permits detecting of
CYP2D6 and 2C19 polymorphisms (29 CYP2D6 and 2 CYP2C19 SNPs) when using drugs that are substrates or inhibitors of these enzymes. The other test involves assessment of UGT1A1*28 polymorphism for safer delivery of irinotecan using Invader AssayTM
(Vizirianakis, 2007).
In addition to polymorphisms in drug metabolism enzymes, SNPs in drug targets, receptors and transporters (P-glycoprotein, human organic anion transporting polypeptide-
27 C (OATP-C)) can also result in variable response to drug therapy. In fact, genotyping has been suggested for determining the choice of treatment agents (HLA-B*1502 for carbamazepine, Herceptin for HER2/neu expressors) and for identification of disease risk
(BRCA1 mutation for testing breast cancer risk) (Huang and Ratain, 2009). Thus understanding how genetic variations in individuals contribute to differences in therapeutic response can assist in personalizing therapy based on an individual’s genotype. Towards achieving this goal, Huang and Ratain suggest five stages of pharmacogenetics in cancer therapy starting from 1) determining the role of genetics in drug response, 2) screening and identifying genetic markers, 3) validating genetic markers, 4) clinical utility assessment and 5) pharmacoeconomic impact. Screening and identifying genetic markers can be accomplished by either a candidate gene approach, which focuses on the genetic variations in enzymes/transporters/targets involved in the disposition of drugs or a genome wide approach, where genome wide association studies
(GWAS) are conducted scanning markers across genomes in a large population to find genetic variations associated with a disease or drug treatment. For anticancer drugs like 6-
MP and irinotecan, a candidate gene approach has provided valid markers that have been validated and successfully used to personalize treatment. A recent example of a genome wide approach includes identification of variants in SLCO1B1 (solute carrier organic anion transporter family, member 1B1) that were strongly associated with increased risk of statin-induced myopathy. SLCO1B1 encodes the organic anion–transporting polypeptide OATP1B1, which is known to regulate the hepatic uptake of statins. (Link, et al., 2008)
28 1.5. CYP3A Polymorphisms
All the four CYP3A isoforms are located in tandem CYP3A43-CYP3A4-CYP3A7-
CYP3A5 on chromosome 7q21.1-q22.2, consisting of 13 exons each encoding an open
reading frame of 503 amino acids ([Fig. 7], Adapted from (Wojnowski, 2004)). Here
CYP3A43 is in head to head orientation with CYP3A4, while the other three genes are in
head to tail orientation. Single nucleotide polymorphisms in CYP3A can result in variants
with higher, lower or lack of enzyme activity, thereby requiring dose modifications for
substrate drugs. Several investigators have suggested that genetic polymorphisms in
CYP3A genes can contribute to at least 90% of the variability observed in CYP3A
expression. A list of important SNPs in CYP3A with their reported frequencies in
different populations is presented in Table 5.
CYP3A43 CYP3A4 CYP3A7 CYP3A5
Figure 7: Schematic representation of CYP3A locus on chromosome 7. The vertical bars indicate boundaries of the individual gene cassettes.
29 Table 5. Distribution of important CYP3A polymorphisms in various ethnic groups. (Adapted from Burk et al 2004)
Expression: Genetic Allele Frequency (%) CYP3A Level/ Contribution Variants Mechanism References Gene Distribution to Variability Caucasians Africans Other CYP3A4 Strong / Strong Japanese 0%; Lamba et al., 2002 -392A>G Rebbeck et al., 1998 Unimodal CYP3A4*1B 2-9.6% 35-67% Chinese 0% (increased activity) Walker et al., 1998 Hispanic 9-11% Paris et al., 1999 CYP3A4*6 Frame Shift NK NK Chinese 0.5% Hsieh et al., 2001 Phe189Ser Dai et al 2001 CYP3A4*17 2.1% 0% -- alteration. CYP3A4*20 Frame Shift 6% 26% Chinese 22% Lakhman et al 2009 CYP3A5 Medium / Strong Japanese 71- Hustert et al., 2001 Bimodal 85%; Kuehl et al., 2001 Splice Defect CYP3A5*3 90% 27-50% Chinese 65-73%; (loss of activity) Koreans 70% Mexicans 75% Splice Defect Hustert et al., 2001 CYP3A5*6 0 13% 0 (loss of activity) Kuehl et al., 2001 CYP3A5*7 Frame Shift 0 10% 0 Hustert et al., 2001 CYP3A5*8 R28C NK NK NK Lee et al 2003 CYP3A5*9 A337T NK NK NK Lee et al 2003 CYP3A7 Medium / Strong CYP3A7*1B NA 0% 1% NK Kuehl et al., 2001 Bimodal CYP3A7*1C NA 6% 3% NK Kuehl et al., 2001
NK Kuehl et al., 2001 CYP3A7*1D NA 0% 1% CYP3A7*1E NA 8% 0% NK Kuehl et al., 2001 CYP3A43 Low/ Unknown Gellner et al. 2001; Stone et al 2005 Trimodal? CYP3A43*3 Missense Variant ------Westlind- Johnsson et al. 2003 NK- Not Known 1.5.1. Pharmacogenetics of CYP3A4
To date, more than 39 SNPs have been published on the home page of the Human
Cytochrome P450 (CYP) Allele Nomenclature Committee (http://www.cypalleles.ki.se/).
Most of the identified SNPs have been reported to occur at low frequencies (<2%) and
only a few are known to alter the activity. The most common variant A-392G transition
(CYP3A4*1B) located in the promoter region has been associated with an increased
transcriptional activity in in vitro studies (Amirimani, et al., 2003). However, conflicting
results regarding its in vivo effect have been reported in clinical studies. This variant has
been associated with increased clearance in patients undergoing docetaxel treatment
(Amirimani, et al., 2003;Tran, et al., 2006;Amirimani, et al., 2003). Rodriguez-Antona et
al have shown that individuals expressing CYP3A4*1B (−392A>G) had significantly
lower enzyme activity than CYP3A4*1A (Rodriguez-Antona, et al., 2005). Some
investigators have reported significant association of CYP3A4*1B to decreased clearance
of thiotepa and cyclosporine, while others have shown no effect (Ekhart, et al., 2009;Min
and Ellingrod, 2003;He, et al., 2005;Spurdle, et al., 2002). In addition, several studies
have implicated CYP3A4*1B to greater risk of prostate cancer, lung cancer and reduced
risk for leukemia (Rebbeck, et al., 1998;Felix, et al., 1998). The allelic frequency varies
among different ethnic groups – Caucasian (2-9%), African Americans (35-67%) and
Hispanic Americans (9-11%) (Lamba, et al., 2002). Other alleles with decreased activity
include CYP3A4*5, *6, *11, *16 and *17 but are expressed in relatively lower
frequencies (Westlind-Johnsson, et al., 2006b;Zeigler-Johnson, et al., 2004;Murayama, et
al., 2002). Recently, CYP3A4*20 the first null allele in CYP3A4 was identified and was
found to be devoid of any enzyme activity (Westlind-Johnsson, et al., 2006a). Furthermore, a novel intronic variant identified by Dr. Wolfgang Sadee’ group at the
University of Ohio was associated with reduced mRNA expression and lower statin dose
requirement (personal communication). Information on the frequency of this
polymorphism is not yet available. The presence of lower frequency non functional
polymorphisms identified so far suggest that the variability in CYP3A expression cannot
be explained by these polymorphisms alone, and requires further studies to determine the
contribution of these polymorphisms to metabolism of drugs.
1.5.2. Pharmacogenetics of CYP3A5
Considerable effort has been made to identify the mutations in the CYP3A genes that
might affect the expression and function of the CYP3A enzymes. The expression of
CYP3A5 has been found to be polymorphic and can account for up to 50% of the total
CYP3A content especially in individuals expressing the wild type CYP3A5*1/*1 alleles.
A number of genetic polymorphisms with functional significance have been identified in
CYP3A5 that include CYP3A5*3, CYP3A5*5, CYP3A5*6, CYP3A5*7 and
CYP3A5*11 (Lamba, et al., 2002;Lee, et al., 2003). The most frequent and functionally
important polymorphism consists of an 6986A>G transition within intron 3 is
CYP3A5*3. This polymorphism creates an alternative splice site resulting in a frame
shift, and truncation of the protein, leading to loss of CYP3A5 activity (Kuehl, et al.,
2001;Hustert, et al., 2001a). As a result, the expression of CYP3A5 is found to exhibit
bimodal distribution, with individuals being categorized as “high expressors” or “low
expressors”, depending on the ethnic distribution. Significant association has been
reported between CYP3A5*3 genotype and decreased clearance of tacrolimus, sirolimus,
32 cyclosporine and saquinavir (Dai, et al., 2006;Mouly, et al., 2005). The variant
CYP3A5*3 (G6986) allele is very common in all the ethnic groups studied and is actually
more prevalent than the wild-type allele for most populations. The allelic frequency is as
follows - Caucasians 91%, African Americans 40-60%, Asians 75% and Europeans 70 %
(Lamba, et al., 2002;Roy, et al., 2005). CYP3A5*6 is also a splice variant resulting in the
deletion of exon 7, further leading to lower CYP3A5 expression and activity (Kuehl, et
al., 2001). This variant is found in 13% of Africans and has not been detected in other
population. Other variants reported to have decreased activity include CYP3A5 *7,
CYP3A5*8 and CYP3A5*9.
1.5.3. Pharmacogenetics of CYP3A7
CYP3A7 was originally identified to be predominantly expressed in the fetal liver and its
levels were reported to be either low or undetectable in adults. However, recent reports
indicate the expression of CYP3A7 in 54-78% of adult livers (Schuetz, et al.,
1994;Greuet, et al., 1996). To date, 6 CYP3A7 alleles have been identified and listed on
the home page of the Human Cytochrome P450 (CYP) Allele Nomenclature Committee
(http://www.cypalleles.ki.se/). The functional significance of all these polymorphisms is
not known yet. Most of the individuals genotyped for CYP3A7 carry either CYP3A7*1C
or CYP3A7*1B promoter allele (Kuehl, et al., 2001;Sim, et al., 2005). In fact
CYP3A7*1C has been found to be a marker for higher expression of CYP3A7 in the
intestine (Burk, et al., 2002). Furthermore, there is limited data on the substrates of
CYP3A7. All-trans and cis-retinoic acid that are used in the treatment of promyelocytic
33 leukemia and acne respectively, have been reported to be metabolized by CYP3A7
(Marill, et al., 2002;Niles, 2004;Jimenez-Lara, et al., 2004;Cooper, 2003). In a recent
investigation, Crettol S et al reported that CYP3A7*1C carriers require 1.4-1.6 fold
higher cyclosporine dose post transplantation than the wild type carriers (Crettol, et al.,
2008). Given the fact that the role of CYP3A7 in the metabolism of compounds has not
been studied well in comparison to CYP3A4 or CYP3A5, its importance to the variability
in CYP3A expression needs further examination.
1.5.4. Pharmacogenetics of CYP3A43
CYP3A43 is the newest member of CYP3A family and was identified, cloned and
characterized only in the last decade (Domanski, et al., 2001;Gellner, et al.,
2001;Westlind, et al., 2001b). It is expressed in liver, kidney, prostrate and pancreas.
CYP3A43 also has an amino acid sequence similar to 75% of CYP3A4/5 and 71% to that
of CYP3A7 (Domanski, et al., 2001). Screening for sequence variations resulted in the
identification of three variants in the coding region, one silent, one missense and a
frameshift mutation (Cauffiez, et al., 2004). Recently, CYP3A43*3 a missense variant
was found to be associated with increased prostate cancer risk (Stone, et al., 2005). The
significance of the CYP3A43 and its polymorphisms on the disposition of drugs in not
known.
1.6. Role of PXR Polymorphisms
Since CYP3A expression is largely regulated by hPXR, there is a strong likelihood that
polymorphisms in human PXR will contribute to CYP3A variability (Zhang, et al.,
2001;Hustert, et al., 2001b;Koyano, et al., 2002). Attempts to delineate polymorphic
34 expressions in these nuclear receptors were initiated in the past few years (Zhang, et al.,
2001;Lamba, et al., 2008;Koyano, et al., 2004). Thus far, more than 90 SNPs have been
identified in hPXR (www.pharmgkb.org). Several of these have been associated with
reduced ligand activation in transient transfection experiments. Basal CYP3A4 activity
was related to SNP 25385C>T and 24381 A>C in the PXR promoter region, 63396 C>T
in putative HNF (human necrosis factor) binding site (Lamba, et al., 2008). Moreover, the
T allele of 63396 was associated with higher level of CYP3A induction by rifampicin and
increased CYP3A4 activity in primary human hepatocytes. In fact, in clinical studies PXR
63396C>T has been associated with reduced concentrations of unboosted atazanavir, a
CYP3A substrate used in treatment of HIV infection (Siccardi, et al., 2008). The clinical
impact of other polymorphisms is not known and is being investigated by several
researchers.
1.7. TAM and CYP2D6 Polymorphisms
CYP2D6 is another cytochrome P450 isoform that is responsible for catalyzing the
conversion of TAM to 4-OHT and N-DMT to endoxifen. In a study evaluating the effect
of paroxetine, a CYP2D6 inhibitor on the disposition of TAM in 12 patients, Stearns et al
report that women expressing CYP2D6 variants (*4, *6 and *8) had lower levels of
endoxifen (one of the active metabolites) than who had the wild type variant (Stearns, et
al., 2003). In another study, Jin et al. observed that patients who carried either the
homozygous (*4/*4) or the heterozygous (wt/*4) variant genotype of CYP2D6 had
statistically significantly lower mean plasma endoxifen levels (20.0 and 43.1 nM,
respectively) than those who carried the homozygous wild-type (wt/wt) genotype (78.0
nM) (Jin, et al., 2005). These patients also had fewer incidences of hot flashes. Recently,
35 further evidence was provided on the association between CYP2D6 genotype and
endoxifen concentrations in 158 patients in various ethnic groups, emphasizing the
relationship between CYP2D6 genotype, CYP2D6 inhibitor and endoxifen plasma levels
(Borges, et al., 2006). However, mechanistic studies showing the differences in clinical
outcome due to the impact of CYP2D6 genotype or CYP2D6 inhibitors are lacking.
1.8. Methods to Assess CYP3A Induction
1.8.1. In vitro Methods
CYP3A inductive effect of compounds can be assessed by both in vitro and in vivo
methodology. Previously, animal models were treated with the test compounds and
expression of CYP enzymes ex vivo was determined to assess the fold induction.
However, the major drawback with the animal models was the inter-species differences in
the CYP expression making the extrapolation to humans unreliable. To overcome this
difficulty, primary culture of human hepatocyte that mimic in vivo conditions have been
used extensively to identify compounds that induce CYP3A, and is considered to be the
“gold standard” method. Some of its limitations include non availability of hepatocytes,
high inter individual variation, rapid decline of enzyme expression and high cost (Brandon,
et al., 2003). An illustration of a typical CYP induction study schema using hepatocytes is
presented in [Fig. 8]. This method entails determining CYP3A activity using a probe
substrate (testosterone), quantifying mRNA levels by real time PCR (RT-PCR) and
protein levels after 72 hours of drug treatment. A positive control such as rifampicin is
usually included to account for any variability between the hepatocyte preparations. As
per the FDA drug interaction guidance, a drug that produces changes in CYP3A activity
36 equal to or greater than 40% of the positive control (rifampicin) is considered to be
inducer in vitro and requires further in vivo induction studies.
Collagenase treatment of human liver
Primary Human Hepatocytes plated on Type Activity Assay Intact cells 1 collagen coated plates Testosterone-6-β- Hydroxylation
48 hrs Microsomes 1-4 hr drug free medium Protein Detection Western Blot Drug/Solvent treatment for 72 hrs S9 fractions
mRNA Detection RNA isolation Real Time - Polymerase Chain Reaction Figure 8: Schematic of hepatocyte treatment for CYP3A induction studies.
In the last decade, there has been a significant improvement in our understanding of the
molecular mechanisms of CYP3A induction. The discovery of PXR led to the
development of rapid and high throughput receptor assays to determine the potential of a
compound to activate PXR and induce CYP3A4. However, the results of PXR activation
assays may not be reliable for compounds that exhibit complex CYP3A inhibition and
induction eg. Ritonavir. Other methods to assess CYP3A induction include in silico
37 assays, alternative human hepatoma cell lines like HepG2, HepaRG and integrated
discrete multiple organ co-culture (IdMOC) system.
1.8.2. Clinical Assessment of Induction
Determination of CYP3A activity in vivo entails the use of marker substrates that are
specifically metabolized by CYP3A. The test compound is administered daily to achieve
steady state, when the maximum impact on CYP3A induction can be determined. CYP3A
activity is then ascertained by administering the probe substrate at the baseline prior to test
drug administration and at the steady state. Changes in the pharmacokinetic parameter
estimates (eg, increase in CL/F or decrease in AUC) of the probe provides indication of
CYP3A induction.
Several compounds have been indentified and validated as a marker for CYP3A activity
including midazolam, testosterone, urinary 6-hydroxy cortisol/cortisol ratio, 14C-
erythromycin, triazolam, alfentanil, nifedipine, dextromethorphan and lidocaine
(Streetman, et al., 2000;Liu, et al., 2007). Midazolam is the most commonly used probe
for the determination of CYP3A activity both in vitro and in vivo. Midazolam has several
advantages over other probe substrates. It is a chemically stable, readily measurable
analyte in plasma, absorbed completely from the gastrointestinal tract, and eliminated
rapidly after intravascular or oral administration.
38 Midazolam
CYP3A4/5
1-OH-Midazolam 4-OH-Midazolam
Figure 9: Metabolism of Midazolam to 1-OH and 4-OH midazolam by CYP3A4/5
It is exclusively metabolized by CYP3A4/5 to its primary metabolite 1-OH-Midazolam and to a lesser extent to 4–OH-Midazolam [Fig. 9]. Furthermore, midazolam undergoes significant first-pass intestinal metabolism. Therefore, any changes in the CYP3A activity would be reflected in the pharmacokinetics of midazolam. Apparent oral clearance of midazolam has been used as a standard criterion for assessing in vivo CYP3A activity, and provides a measure of both hepatic and intestinal CYP3A function. Whereas, systemic clearance after IV administration of MDZ reflects only the hepatic activity (Thummel, et
39 al., 1994b). MDZ is not a substrate of the efflux transporter P-glycoprotein and hence is considered to be a “pure” CYP3A probe (Kim, et al., 1999). The major drawback associated with midazolam is the sedative effect observed in patients, when used in the dose range of 2-10 mg.
40 2. CHAPTER TWO: HYPOTHESIS AND SPECIFIC AIMS
2.1. Hypothesis
The central hypothesis of this thesis is “Tamoxifen metabolism as well as the extent of
CYP3A induction by Tamoxifen is impacted by pharmacogenetic factors”. To test this
hypothesis we pursued the following three specific aims
2.2. Specific Aim 1
To evaluate the effect of CYP3A polymorphisms on tamoxifen metabolic clearance in vitro.
Rationale: The role of CYP3A5 in the formation of α-OHT, the genotoxic metabolite has not
been specifically addressed. Given the extensive substrate overlap of CYP3A4 and 3A5, it is
likely that the later is also involved in the conversion of TAM to α-OHT. Furthermore,
CYP3A also plays an important role in the demethylation of TAM to N-DMT, which is the
precursor for the active metabolite endoxifen. Inheritance of CYP3A5*1 has been strongly
correlated with enhanced CYP3A5 dependent metabolism in the liver in vitro, while presence
of CYP3A5*3 accounts for markedly reduced level of CYP3A5 protein expression and
function in approximately 85% of Caucasians and 55% of African Americans (Kuehl, et al.,
2001). Other CYP3A5 alleles that are reported to result in decreased enzyme activity include
CYP3A5*8 and CYP3A5*9 (Lee, et al., 2003;Lee, et al., 2003). Recently, a novel CYP3A4
intronic variant was identified by Wolfgang Sadee, Ph.D (personal communication) at Ohio
State University, and was associated with decreased statin maintenance dose. The effect of
all these variants on TAM metabolism is not known. Individuals with CYP3A
polymorphisms have the ability to produce different levels of α -OHT and N-DMT
41 contributing to inter-individual variability with TAM therapy. Hence we pursued the
following aims employing human liver microsomes as an in vitro model.
a) To determine the role of CYP3A5 to the formation of α-OHT and N-DMT using
recombinant CYP3A4 and CYP3A5.
b) To evaluate the impact of intronic CYP3A4 and CYP3A5 variants (CYP3A5*1/*1, *1/*3
and *3/*3) on the formation of α-OHT and N-DMT using a panel of pre-genotyped
human liver microsomes.
c) To assess the effect of recombinant CYP3A5*8 and CYP3A5*9 on the formation of α-
OHT and N-DMT.
This aim also involves LC-MS/MS and HPLC method development for quantitation of α-
OHT and N-DMT, 1-hydroxy midazolam and 6-β-hydroxy testosterone, respectively.
2.3. Specific Aim 2
To assess the extent of CYP3A induction in breast cancer patients using midazolam (MDZ)
as a probe substrate.
Rationale: Co-administration of TAM has been shown to markedly reduce the plasma
concentrations and AUC of several co-administered drugs. The most striking effects have
been observed during clinical trials of TAM and aromatase inhibitors, letrozole and
anastrozole, where TAM administration caused a mean 37 and 27 % reduction in the levels
of letrozole and anastrozole, respectively (Dowsett, et al., 1999;Dowsett, et al., 2001). An
important point to note here is that the inductive response varied markedly and in some cases
the net reduction in AUC was much higher. For instance, in case of TAM and letrozole
interaction, AUC decreased in some subjects by more than 60%. Such a decrease in
42 concentration may have resulted in the overall lack of therapeutic benefits. The
mechanism(s) of this interaction have not been explored. The lack of an understanding of these interactions has been cited as a formidable barrier to the successful use of TAM with newer agents. As discussed earlier, since anastrozole and letrozole are both metabolized extensively by CYP3A4, we hypothesized that TAM induces CYP3A4. Previous findings from our laboratory suggest that TAM and 4-OHT induce CYP3A4 in vitro in primary cultures of human hepatocytes (Desai, et al., 2002). On one hand, individuals with higher
CYP3A4 activity will have increased capacity for TAM conversion to N-DMT. On the other hand, increased CYP3A4 levels may lead to greater production of the genotoxic α-OHT, which may ultimately lead to higher risk of endometrial carcinogenesis. Therefore, increase in the production of α-OHT and N-DMT upon sustained TAM use, as a result of CYP3A4 auto-induction may be an important contributory factor to endometrial carcinogenesis and variability in TAM therapy. Hence we pursued the following sub aims.
a) To assess the potential of TAM to induce CYP3A in breast cancer patients in vivo using
midazolam (2 mg, oral syrup) as a probe substrate. Single dose pharmacokinetics of
MDZ and 1’–OH-MDZ was evaluated following MDZ administration before and after
initiation of TAM regimen (one day versus steady state).
b) To develop a LC-MS/MS methodology for the analysis of MDZ and 1-OH MDZ in
plasma samples.
43 2.4. Specific Aim 3
To conduct preliminary investigation on the impact of CYP3A and PXR polymorphisms on
the CYP3A induction by TAM
Rationale: The impact of polymorphic expression on the induction of CYP3A genes is
poorly understood. CYP3A5 is generally considered to be a non-inducible CYP3A isoform.
A recent study does suggest that CYP3A5 may also be regulated by hPXR and is inducible
by hPXR ligands (Burk et al 2004). Even so, the induction appears to be mainly at the
intestinal CYP3A5 expression. However, it is feasible that the extent of induction may be
associated with the CYP3A4 and CYP3A5 polymorphisms. Furthermore, since CYP3A
expression is largely controlled by PXR, there is a strong likelihood that polymorphisms in
PXR may also contribute to the CYP3A variability. Several of the identified SNPs have been
associated with reduced ligand activation in transient transfection experiments.
Polymorphisms in PXR (-25385C>T, -24381 A>C and 63396 C>T) have been associated
with basal CYP3A4 activity (Lamba, et al., 2008;Siccardi, et al., 2008). Thus, genotypes with
lower basal activity will have higher induction and vice versa. CYP3A4*1B, a promoter
variant has been associated with an increased transcription in vitro. We assessed the in vivo
effect of these polymorphisms on the extent of CYP3A induction by TAM. Taken together,
this aim will provide us preliminary evidence on the clinical impact of various
polymorphisms on the pharmacokinetics of TAM.
44 3. CHAPTER THREE: EXPERIMENTAL DESIGN AND METHODS
3.1. Specific Aim 1: Assessment of impact of CYP3A5 on Tamoxifen Clearance in vitro
3.1.1. Materials
3.1.1.1. Chemicals
TAM, N-DMT and α-OHT were obtained from Sigma Chemical Co. (St. Louis, MO)
and Toronto Research Chemicals (Toronto, ON, Canada). NADPH regenerating
system Solution A (1.3 mM -β NADP+, 3.3 mM glucose 6-phosphate, 3.3 mM
MgCl2) and Solution B (0.4 U/ml glucose 6-phosphate dehydrogenase) were
obtained from BD-Biosciences.
3.1.1.2. Biologicals
Pooled human liver microsomes were obtained from BD Biosciences (Woburn, MA).
CYP3A5 genotyped microsomes and heterologous baculovirus-insect cell expressing
human CYP3A4 , CYP3A5, CYP3A5 *8 and CYP3A5*9 supplemented with P450
reductase and cytochrome b5 were obtained through a collaboration with Eli Lilly
(Indianapolis, IN) and partly procured from BD Biosciences (Woburn, MA). The
HPLC-grade methanol, acetonitrile, hexane and butanol were purchased from Fisher
Scientifics (Santa Clara, CA). All other chemicals and reagents used were of the
highest commercially available quality.
45 3.1.2. Incubation of Testosterone with CYP3A Genotyped Microsomes
The linearity of formation of 6-β-hydroxy testosterone in human liver microsomes was
established by incubating testosterone with varying incubation times (5-45 minutes) and
microsomal protein concentrations (0.01-1 mg/ml). A protein concentration of 0.25 mg/ml
and an incubation time of 10 minutes were chosen based on the preliminary experiments. For
microsomal incubations, methanolic solution of testosterone (0-400 μM) in a polypropylene
tube was evaporated under a gentle stream of nitrogen gas. The vials were then preincubated
with NADPH regenerating system (1.3 mM -β NADP+, 3.3 mM glucose 6-phosphate, 3.3
mM MgCl2, 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 addition of 0.25 mg/ml of microsomes and allowed to proceed for 10 minutes. The total
volume of incubation was 100 μl. Ice cold methanol (50 μl) was added to the vials to
terminate the reaction, vortexed and centrifuged at 13000 rpm for 5 minutes. 100 μl of the
supernatant was injected into HPLC for quantitation of 6-β-hydroxy testosterone. Control
incubations with no protein, no NADPH and/or no substrate were performed concurrently.
All the incubations were performed in duplicates
3.1.3. Incubation of Midazolam with CYP3A Genotyped Microsomes
The linearity of formation of midazolam metabolites in human liver microsomes was
established with varying incubation times and protein concentrations. A protein
concentration of 0.125 mg/ml and an incubation time of 5 minutes were chosen based on the
46 preliminary experiments. Briefly, methanolic solution of midazolam (0-400 μM) in a
polypropylene tube was evaporated under a gentle stream of nitrogen gas. The vials were
then preincubated with NADPH regenerating system (1.3 mM -β NADP+, 3.3 mM glucose
6-phosphate, 3.3 mM MgCl2, 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 addition of 0.125 mg/ml of microsomes and allowed to proceed for 5
minutes. The total volume of incubation was 200 μl. Ice cold methanol (100 μl) was added
to the vials to terminate the reaction, vortexed and centrifuged at 13000 rpm for 5 minutes.
120 μl of the supernatant was injected into LC-MS/MS for quantitation of 1-hydroxy and 4
hydroxy midazolam. Control incubations with no protein, no NADPH and/or no substrate
were performed concurrently. All the incubations were performed in duplicates.
3.1.4. Incubation of Tamoxifen with CYP3A Genotyped Microsomes
Incubation conditions were performed according to a previously reported methodology
(Desta, et al., 2004). Initial conditions for linearity of metabolite formation were assessed
with regards to varying protein concentration (0-1 mg/ml) and time (0-60 minutes) using
human liver microsomes. Final incubations with CYP3A5 genotyped liver microsomes were
performed using the following conditions. Briefly, methanolic solution of TAM (0-50 μM)
was dried under nitrogen in polypropylene vials. The vials were then preincubated with
NADPH regenerating system and 100 mM phosphate buffer for 5 minutes in a shaking water
bath maintained at 370C. The reaction was initiated by the addition of 0.1 mg/ml of
microsomes and allowed to proceed for 10 minutes. The total volume of incubation was
47 250 µl. Reaction was terminated by the addition of 100 µl ice cold acetonitrile. The
incubation mixture was extracted with hexane-butanol mixture; supernatant was dried under
nitrogen and reconstituted with 250 μl of the mobile phase (acetonitrile-water, 80/20) for LC-
MS/MS analysis. 10 μl of the sample was injected into LC-MS/MS for quantitation of α-
OHT and N-DMT. Control incubations with no protein, no NADPH and/or no substrate were
performed concurrently. All the incubations were performed in duplicates.
3.1.5. Incubation of Tamoxifen with recombinant CYP3A Supersomes
Incubation conditions for recombinant CYPs were similar to that of genotyped microsomes.
Briefly, the reaction mixture contained 50 pmol of either rCYP3A4 or rCYP3A5
supplemented with P450 reductase and cytochrome b5, NADPH regenerating system,
phosphate buffer 100 mM and TAM (0-50 μM). The mixture was incubated in a water bath
for 10 minutes maintained at 370C. The reaction was terminated by the addition of ice cold
acetonitrile. The metabolites formed were extracted, dried, and reconstituted with 250 μl of
the mobile phase (acetonitrile-water, 80/20) for LC-MS/MS analysis. 10 μl of the sample was
injected into LC-MS/MS for quantitation of α-OHT and N-DMT.
3.1.6. HPLC Analysis of 6-β-Hydroxy Testosterone
6-ß-hydroxy testosterone levels were quantitated employing a published HPLC method
validated and routinely used in our laboratory (Nallani, et al., 2001;Hariparsad, et al.,
2004;Desai, et al., 2002). 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).
48 A Waters 2487 dual wavelength detector set at 250 nm was used for the detection of 6ß-
hydroxy testosterone.
Figure 10: A typical HPLC chromatogram of 6-β-hydroxy testosterone and 11 α-hydroxy progesterone (internal standard) in the microsomal incubates.
The total run lasted for 6 minutes, with 6-β-hydroxy testosterone and 11α-hydroxy
progesterone eluting at 2.8 and 5 minutes, respectively [Fig. 10]. The standard concentrations
of 6-β-hydroxy testosterone ranged from 0.1 – 50µM. The interday and intraday variability
in the HPLC analysis was <5% and the detection limit was 0.05µM for 6ß-hydroxy
testosterone.
3.1.7. LC-MS/MS Analysis of α-OHT and N-DMT
The HPLC separation for the analysis of α-OHT and N-DMT was performed using a Thermo
Scientific® Surveyor MS™ pump and MicroAS autosampler. Waters® XBridge™ (C18
column, particle size-3.5 μm, dimensions-2.1 x 100 mm) column was used for the separation
49 of analytes. The mobile phase consisted of solution A (acetonitrile, 0.1% formic acid) and
solution B (water, 0.1% formic acid). 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. 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 100-380 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 cycles. Data
analysis was performed using Thermo Scientific® Xcalibur™ 2.0 software. Analytes were
quantified using peak area ratios of standard curves. The retention times for α-OHT, N-DMT
and TAM were 7.3, 13.55 and 14.06 minutes, respectively. Standard curves were linear over
the ranges of 0.5 – 600 ng/ml.
3.1.8. Data Analysis
Data from recombinant CYP and microsomal experiments were analysed using three enzyme
kinetic models – Michaelis-Menten (A), Sigmoidal (B) and Substrate inhibition kinetics (C).
V max*C Rate = (A) + Km C
V max*Cγ Rate= (B) Km+ Cγ
V max*C Rate= (C) Km+C*(1+C/ Ki)
50 Where Vmax is the maximum rate of formation of the metabolite and reflects the maximum
metabolic capacity, Km is the Michaelis–Menten constant and represents the concentration of
the substrate at half maximum rate, C is the substrate concentration, γ is the Hill coefficient –
a measure of steepness of curve and presence of co-operativity, and Ki is the dissociation
constant for substrate binding to an enzyme. Final parameter estimates of Km and Vmax
were determined by nonlinear regression analysis using WinNonlin 5.2 (Pharsight
Corporation, Inc., Mountain View, CA, USA). 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).
The estimates of the Michaelis–Menten parameters were then used to calculate in vitro
intrinsic clearance using equation (Eqn. D).
V max CLint = (D) Km
3.1.9. Statistical Analysis
Formation of N-DMT and α-OHT in human liver microsomes genotyped for CYP3A5*1/*1,
CYP3A5*1/*3 and CYP3A5*3/*3 were analyzed using ANOVA followed by post hoc
Tukey’s test. A p value less than 0.05 was considered statistically significant. The formation
of metabolites was calculated and expressed as picomoles per minute per mg protein for
microsomes and picomoles per minute per picomole protein for recombinant CYPs. All the
analyses were performed using the mean values obtained from duplicate incubations. Data
has been presented as mean ± S.D (n=2).
51 3.2. Specific Aim 2: Clinical Assessment of CYP3A Induction by Tamoxifen
3.2.1. Materials
3.2.1.1. Chemicals
MDZ, 1-OH MDZ and 4-OH MDZ were obtained from Sigma Chemical Co. (St.
Louis, MO) and Toronto Research Chemicals (Toronto, ON, Canada). The HPLC-
grade methanol, acetonitrile, hexane and butanol were purchased from Fisher
Scientifics (Santa Clara, CA). All other chemicals and reagents used were of the
highest commercially available quality.
3.2.1.2. Biologicals
Blank plasma samples for standard curve generation were obtained from Hoxworth
Blood Center (Cincinnati, OH).
3.2.2. Development and Validation of LC-MS/MS Method
3.2.2.1. Stock Solution and Calibration Standards
Standard solutions of MDZ, 1-OH-MDZ, 4-OH-MDZ were prepared by dissolving 1 mg
15 of each compound in 1 ml of methanol. The internal standard (IS) stock solution of N3-
MDZ was also prepared similarly in methanol. The calibration standards were prepared
by spiking appropriate volumes in plasma to yield final concentrations ranging from 0.08
to 50 ng/ml for MDZ and its metabolites. All stock solutions and plasma standards were
stored at −20oC until analysis.
52 3.2.2.2. Plasma Sample Processing
All plasma samples were allowed to thaw at room temperature. One ml of plasma was
15 placed into a clean polypropylene tube, and IS solution of N3-MDZ (4 ng/ml) was added to each tube and mixed. To this mixture, 200 μl of NaOH solution (NaOH in methanol) with a concentration of 1 mm was added, vortex-mixed for 30 seconds, and allowed to stand for at least 5 min before extraction with 5 ml mixture of hexane–butanol
(98:2, v/v). The tubes were shaken for 30 minutes and the supernatant was collected. A second extraction was performed with 5 ml of hexane–chloroform (70:30, v/v) following the same procedure. The organic phase was collected and evaporated under dry nitrogen.
The dry residue was re-dissolved in 250 μl of acetonitrile: water (80:20) and 10 μl was injected onto the column.
3.2.2.3. LC-MS/MS Conditions
The HPLC separation for the analysis was performed using a Thermo Scientific®
Surveyor MS™ pump and MicroAS autosampler. The details of chromatography conditions were similar to that described in section 3.1.7. The retention times for 4-OH-
MDZ, 1-OH-MDZ and MDZ were 4.27, 4.88 and 5.36 minutes, respectively. The linear regressions of ratios versus concentrations were fitted over the concentration range of
0.08 to 50 ng/ml for MDZ & its metabolites in human plasma.
53 3.2.2.4. Data Analysis: Calibration Curves and Weighting
Data analysis was performed using Thermo Scientific® Xcalibur™ 2.0 software. The
spiked calibration standards were extracted and analysed in duplicates. Calibration curves
were generated daily based on the peak area ratios of the MDZ or 1-OH MDZ to IS
versus the concentration of MDZ or 1-OH MDZ, respectively. A quadratic fit with 1/x2
weighting best fit the data.
3.2.3. CYP3A Induction by Tamoxifen in Breast Cancer Patients
3.2.3.1. Study Design
The protocol for this study was approved by University of Cincinnati (UC) and Veteran
Affairs Institutional Review Boards (IRB). All participating volunteers had signed an informed consent before starting any study related procedures. Each subject stayed at
Veteran Affairs General Clinical Research Center (VA-GCRC) for at least 8 hours during PK sample collection on three different days. TAM therapy (20 mg, oral tablet, once daily) was initiated on day 0 and the volunteers made visits to the GCRC as per the following schedule.
[Fig. 11]
Visit 1 - One week prior to initiating TAM therapy (day – 7) for MDZ samples
Visit 2 – One day after starting TAM therapy (day 1) – sample collection for MDZ
Visit 3 - 42 days after starting TAM therapy (this will ensure that TAM and its metabolites reached steady state drug levels).
54 On each visit, MDZ 2 mg oral syrup was administered for assessing CYP3A activity. Patients were instructed to avoid ingesting any CYP3A4 modulating agents (grapefruit juice, alcohol) at least 24 hours before taking MDZ. Patients were also restricted from consuming products containing St. John’s Wort (CYP3A inducer) for the entire duration of study since this may obscure the data collected. Smoking and drinking alcohol were also restricted for at least one day prior to their hospital visit and until last blood sample collection.
For pharmacokinetic analysis, blood samples (10 ml) were collected in heparin/EDTA- containing vacutainers through an intravenous catheter, before and at 5, 15, 30 min, 1, 2, 3, 4,
5, 6, 7 and 8 hr after MDZ administration. For visits 2 and 3, samples at 3, 4, 5, 6, 7 and 8 hrs were utilized for TAM assays. Additionally, samples were collected at 24 hrs post TAM administration (i.e., immediately before consumption of the next TAM dose). Immediately after withdrawal, blood samples were centrifuged at 4000 rpm for 10 minutes in a refrigerated centrifuge. Plasma was aliquoted in labeled polypropylene tubes and stored at
-80oC until analysis by LC-MS/MS method.
55 Predose Sample Predose Sample 0750 0750 * Vital Signs & * Vital Signs Genomic Sample Midazolam 2 mg Midazolam 2 mg 0800 0800 **PK Sample **PK Sample Tamoxifen Dose 2 hr Fasting 1000 1000 2 hr Fasting SAME AS IN DAY +1 DAY AS INSAME
Low Fat Lunch Low Fat Lunch 1200 1200 4 hr Post Dose 4 hr Post Dose Snacks Snacks 1600 1600 8 hr Post Dose 8 hr Post Dose 1000 24 hr PK Sample (Next Day)
Baseline Day 1 Day 42
* Vital signs include blood pressure, ** Predose, 5, 15, 30 min, 1, 2, 3, 4, 5, 6, 7 and 8 hr post pulse rate, respiratory rate, pulse oximetry midazolam dose. and oxygen saturation
Figure 11: Study schematics of the pharmacokinetic trial
3.2.3.2. Pharmacokinetic Analysis
Peak plasma levels (Cmax), time to Cmax (Tmax), oral clearance (CL/F; where F is the
bioavailability of MDZ), AUC0-last : area under the plasma concentration curve from time 0
to last time point, AUC0-∞ was calculated by dividing the last measured concentration by λ
(elimination rate constant, obtained from slope of terminal log-linear portion of concentration
versus time curve), volume of distribution (Vd) and elimination half-life (t1/2) for Midazolam
and 1-OH- Midazolam were determined for each treatment day by non compartmental
analysis using WinNonlin 5.2 (Pharsight Inc.).
56 3.3. Specific Aim 3: Impact of CYP3A and PXR Variants on CYP3A Induction
3.3.1. Materials
TaqMan SNP assay components for each of the SNPs – CYP3A4*1B, CYP3A5*3, PXR
variants (25385C>T, 24381 A>C and 63396 C>T) were procured from Applied Biosystems
(Foster City, USA). TaqMan Universal PCR Master Mix, and 384 well plates for PCR were
procured from Applied Biosystems (Foster City, USA)
3.3.2. DNA Isolation and Quantitation
A single blood sample (10 ml) was collected from each subject for genotyping
polymorphisms in CYP3A4, CYP3A5 and PXR. DNA was extracted from whole blood
samples using the Gentra Pure Gene Kit, as per the manufacturer’s instructions. The purity of
DNA sample was quantitated using the NanoDrop spectrophotometer (NanoDrop
Technologies). The 260/280 nm ratio calculated by the NanoDrop spectrophotometer was
used to evaluate the DNA purity. The ratio of 260/280 was between 1.8-2.0 for all the
samples.
3.3.3. PCR
For PCR, 2 μl of DNA sample was mixed with 2.5 μl 2x TaqMan® Universal PCR Master
Mix, 0.125 μl of 20x TaqMan SNP genotyping Assay Mix and 0.375 μl of water (Total
57 volume - 5 μl). DNA amplification was performed in a Geneamp 9700 thermal cycler using the following conditions:
UNG Incubation 500C – 2 min Amplitaq DNA Activation 950C - 10 min
Denature 0 92 C - 15 sec 40 cycles Anneal/Extension 600C - 1 min Hold 40 C
UNG-Uracil N Gycosylase
3.3.4. Allelic Discrimination
ABI PRISM 7900HT Sequence Detection System (Applied Biosystems, Foster City, CA) was used for allelic discrimination and determining the genotypes. A typical allelic discrimination plot indicating the ratio of fluorescence intensities of VIC or FAM dye to the passive reference is presented on the x and y axis [Fig. 12]. Each dot represents a patient and the color distinguishes each patient of different genotypes (blue – homozygous wild type, green - heterozygous and red-homozygous mutant).
58
Figure 12: A typical allelic discrimination plot indicating the three genotypes.
59 4. CHAPTER FOUR: RESULTS
4.1. Specific Aim 1: Assessment of impact of CYP3A5 on Tamoxifen Clearance in vitro
As discussed earlier, there is a paucity of data on the role of CYP3A4/5 and the impact of its
genetic polymorphisms on the formation of α-OHT, a genotoxic metabolite implicated in
endometrial cancer and N-DMT, an active metabolite. Inheritance of CYP3A5*1 is
associated with enhanced CYP3A5 dependent metabolism in the liver and has been reported
to influence the disposition of CYP3A substrates (Kuehl, et al., 2001). Using cDNA
expressing specific CYP3A isoforms and human liver microsomes genotyped for
CYP3A5*1/*1, CYP3A5*1/*3 and CYP3A5*3/*3 variants, we elucidated the relative
contribution of CYP3A4 and CYP3A5, and assessed the impact of polymorphic expression
of CYP3A5 on the formation of α-OHT and N-DMT.
4.1.1. Contribution of CYP3A4/5 to the formation of α-OHT and N-DMT
The kinetic parameters for the formation of α-OHT and the impact of polymorphic CYP3A5
expression on its formation have not been reported. Therefore, we investigated the formation
of α-OHT and N-DMT using baculovirus cell line expressing CYP3A4 and CYP3A5. Both
rCYP3A5 and rCYP3A5 were supplemented with cytochrome b5 and oxido-reductase. The
concentrations of TAM used were in the range of 0-50 µM. The metabolites in the
microsome samples were extracted and quantitated using LC-MS/MS [Fig. 13]. The Vmax
and Km values were calculated by fitting the data to Michaelis-Menten equation using
WinNonlin 5.2. The mean estimates for Vmax and Km with the standard errors are listed in
Table 6. In the case of α-OHT, the intrinsic formation clearance (CLint) with rCYP3A4 was
60 approximately 6-fold higher than with rCYP3A5, indicating a relatively minor role for
CYP3A5 (3.32 vs 0.65 µl/min/pmol P450). Representative kinetic plots for the formation of
α-OHT by rCYP3A4 and rCYP3A5 are shown in [Fig. 14].
For N-DMT, the CLint values for rCYP3A4 and rCYP3A5 were 0.57 and 0.35 ml/min/pmol
P450 respectively. This corroborates to the previously reported observation that CYP3A5 contributes to the formation of N-DMT (Desta, et al., 2004;Williams, et al., 2002). The Km values estimated were similar for both the enzymes (7.18 vs 6.87μM, Table 6, [Fig. 15]).
Figure 13. A typical LC-MS/MS chromatogram of α-OHT (A) and N-DMT (B) in the microsomal incubates.
61 Table 6. Enzyme kinetic parameter estimates for the formation of α-OHT and N-DMT by recombinant CYP3A4 and CYP3A5. Each incubation contained TAM (0-50 µM), 50 pmol of rCYP3A4 or rCYP3A5 and a NADPH-regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis-Menten model using non linear regression analysis. Results are Mean ± SE from duplicate incubations.
Recombinant Vmax CLint Km (μM) CYP (pmol/min/pmol P450) (μl /min/pmol P450) α-OHT rCYP3A4 62.36 ± 12.3 19.28 ± 4.2 3.23 rCYP3A5 8.66 ± 0.97 13.4 ± 1.9 0.65 N-DMT Recombinant Vmax CLint Km (μM) CYP (nmol/min/pmol P450) (ml/min/pmol P450) rCYP3A4 4.06 ± 0.28 7.18 ± 1.5 0.57 rCYP3A5 2.14 ± 0.06 6.87 ± 0.7 0.35
Vmax, maximum velocity; Km, substrate concentration at which the reaction velocity is 50% of Vmax; CLint, intrinsic clearance. Estimates are Mean±SE from duplicate incubations.
(A) (B)
50 8
40 6 30 4 20 2 10 -Hydroxy tamoxifen -Hydroxy tamoxifen α α (pmol/min/pmol P450) (pmol/min/pmol P450) 0 0 0 20 40 60 0 20 40 60 Tamoxifen (μM) Tamoxifen (μM)
Figure 14. The enzyme kinetics of α-hydroxy tamoxifen formation from TAM by the recombinant CYP3A4 (A) and CYP3A5 (B) isoforms. Each data point represents the mean of two 10 minutes incubations of TAM (0-50 µM) with 50 pmol of CYP3A4 or CYP3A5 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from Michaelis-Menten model using WinNonlin 5.2.
62 (A) (B)
4 2.0
3 1.5
2 1.0
1 0.5 (nmol/min/pmol P450) (nmol/min/pmol P450) N-Desmethyl tamoxifen N-Desmethyl tamoxifen 0 0.0 0 20 40 60 0 20 40 60 Tamoxifen (μM) Tamoxifen (μM)
Figure 15. The enzyme kinetics of N-desmethyl tamoxifen (N-DMT) formation from TAM by the recombinant CYP3A4 (A) and CYP3A5 (B) isoforms. Each data point represents the mean of two 10 minutes incubations of TAM (0-50 µM) with 50 pmol of CYP3A4 or CYP3A5 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from Michaelis-Menten model using WinNonlin 5.2.
4.1.2. Effect of CYP3A5*3 genotyped microsomes on the formation of α-OHT
We next assessed the impact of CYP3A5 polymorphisms on the formation of α-OHT using a
panel of 20 human liver microsomes. The linearity of the formation of α-OHT with respect
to varying protein concentration and time of incubation was established in preliminary
experiments. The Vmax and Km values were estimated by fitting the data to Michaelis-
Menten model using non linear regression analysis (Table.7). The data on CYP3A4/5
protein content, testosterone 6-β-hydroxylation and midazolam 1-hydroxylation in same set
of microsomes are also presented in Table 7.
In the case of α-OHT, there was no significant difference in the Vmax values between the
three CYP3A5 genotypes [Fig. 16]. We observed a 28-fold variation in the Vmax values
63 ranging from 1.8 to 49.6 pmol/min/mg and a 9-fold variation in the Km values ranging from
0.7 to 29.2 µM. Furthermore, the Vmax values from genotyped microsomes were compared
with the protein contents of CYP3A4, CYP3A5 and the CYP3A activity determined as
testosterone 6-β-hydroxylation and midazolam 1-hydroxylation in the same set of
microsomes. The correlation between Vmax of TAM α-hydroxylation and CYP3A4 protein
(r=0.80, p=0.0002) was significant and was greater than the correlation with CYP3A5 protein
(r=0.47, p=0.062) [Fig. 17]. In addition, we also observed a significant correlation between
Vmax and testosterone-6β hydroxylation activity (r=0.79, p=0.0002), a marker specific to
CYP3A4 than CYP3A5. The correlation with 1- hydroxy midazolam was less significant
with r=0.44 and p = 0.0314 [Fig. 18].
60
40
20 -OHT (pmol/min/mg) -OHT α 0 *1/*1 *1/*3 *3/*3 CYP3A5
Figure 16. Comparison of Vmax of α- OHT formation between the three CYP3A5*1/*1, *1/*3 and *3/*3 genotypes. Each point represents the Vmax estimated by fitting the data to Michaelis- Menten kinetics using nonlinear regression analysis. TAM (0-50 µM) was incubated with genotyped human liver microsomes as described in the methodology section. There was no significant difference between the three genotypes.
64
A B
Figure 17. Correlations between Vmax of α-OHT formation and (A) CYP3A4 protein, (B) CYP3A5 protein in a panel of genotyped human liver microsomes.
Figure 18. Correlations between Vmax of α-OHT formation and (A) testosterone-6-β-hydroxylation, (B) midazolam-1-hydroxylation in genotyped human liver microsomes.
65 Table 7. Enzyme kinetic estimates for the formation of α-OHT and N-DMT in a panel of genotyped human liver microsomes.
1-hydroxy 6-β-hydroxy CYP3A4a CYP3A5a CYP3A5 N-DMT α-OHT Liver ID midazolam testosterone Protein Protein Genotype Vmax* Km** CLint Vmax* Km** CLint (nmol/min/mg) (nmol/min/mg) (pmol/mg) (pmol/mg) HH-1019 *1/*1 408.98 6.94 58.91 49.55 14.21 3.49 8.15 13.16 116.9 29.4 HH-860 *1/*1 227.14 10.58 21.48 5.65 7.65 0.74 2.245 2.65 20.8 16.3 MCV-36 *1/*1 244.59 7.86 31.13 17.69 10.45 1.69 1.74 5.12 57.5 18.5 CD-8002 *1/*1 236.19 10.66 22.15 1.76 12.65 0.14 0.9 1.27 13.7 13.6 CD-8052 *1/*1 279.36 11.08 25.21 5.44 7.65 0.71 1.1 1.60 34.4 9.6 HH 739 *1/*1 223.41 4.15 53.83 2.71 5.97 0.4 1.2 1.6 11 6 HH 785 *1/*1 253.76 3.32 76.53 4.2 6 0.7 4.1 5.8 13 Mean 267.63 7.80 41.32 12.43 9.23 1.12 2.78 4.46 60.62 15.20 SD 65.09 3.18 21.72 17.21 3.27 1.15 2.61 4.24 60.66 7.50 HH-1044 *1/*3 107.41 19.42 5.53 8.49 25.82 0.33 0.841 1.22 14.2 4.1 HH-525 *1/*3 135.96 16.00 8.50 4.23 22.91 0.18 0.499 1.18 18.0 8.4 HL-G *1/*3 112.92 21.52 5.25 3.20 16.52 0.19 0.7945 14.1 4.7 HL-W *1/*3 92.35 7.86 11.74 3.89 16.76 0.23 1.15 19.4 8.8 HH-776 *1/*3 69.90 17.53 3.99 5.26 29.24 0.18 0.8745 1.56 34.9 1.1 Mean 103.71 16.47 7.00 5.02 22.25 0.22 0.75 1.28 20.11 5.41 SD 24.55 5.24 3.12 2.08 5.59 0.06 0.17 0.19 8.59 3.21 HH189 *3/*3 112.42 3.89 28.87 2.07 0.71 2.81 2.8 13.60 120 ND HH507 *3/*3 89.09 5.2 17.13 ND ND -- 0.40 15 ND XENO *3/*3 52.99 4.4 12.03 ND ND -- 0.6 0.60 ND HL-D *3/*3 97.32 17.44 5.58 1.80 9.62 0.19 0.253 0.59 8.3 0.3 HL-J *3/*3 122.67 9.84 12.47 5.90 8.16 0.72 0.7975 2.23 20.9 0.4 HL-P *3/*3 106.09 7.64 13.88 4.39 7.96 0.55 0.945 19.3 1.1 HH-689 *3/*3 73.99 9.30 7.96 ND ND -- 0.135 0.23 8.4 0.4 HL-R *3/*3 153.66 13.72 11.20 7.09 12.99 0.55 0.8355 2.83 33.3 0.3 Mean 101.03 8.93 13.64 4.25 7.89 0.96 0.91 2.93 32.18 0.49 SD 30.68 4.75 7.08 2.32 4.49 1.05 0.89 4.81 39.65 0.35 * pmol/min/mg, ** µM, ND – Not Detected, a – Data from Lilly
4.1.3. Effect of CYP3A5*3 genotyped microsomes on the formation of N-DMT
In the case of N-DMT formation, there was a significant difference in the Vmax values
between CYP3A5*1/*1 (267.63 pmol/min/mg) and CYP3A5*1/*3 (103.71
pmol/min/mg) or CYP3A5*3/*3 (101.03 pmol/min/mg) microsomes (p<0.05) [Fig. 19]. A
7- and 5- fold variation in the Vmax values (53 to 408 pmol/min/mg) and Km values (3.3 to
17.4 µM) were observed. We then compared Vmax of N-DMT formation with the protein
content of CYP3A4 (r=0.56, p=0.04) and CYP3A5 (r=0.81, p<0.0001), and the correlations
were significant [Fig. 20]. Moreover, the correlation between Vmax and midazolam
hydroxylation ( r=0.79, p=0.0002), Vmax and testosterone-6-β-hydroxylation (r=0.68,
p=0.002 ) were also significant further suggesting the role of CYP3A5 in N-DMT formation
[Fig. 21]. This observed difference in intrinsic clearance between the wild type and the
mutant CYP3A5 variant may be an important contributor to the variability observed with
TAM pharmacokinetics. 600 *1/*1 Vs *1/*3, p<0.05 *1/*1 Vs *3/*3, p<0.05 400
200 N-DMT (pmol/min/mg) N-DMT 0
3 3 /* /* *1/*1 *1 *3 CYP3A5
Figure 19. Comparison of Vmax of N-DMT formation between the three CYP3A5*1/*1, *1/*3 and *3/*3 genotypes. Each point represents the Vmax estimated by fitting the data to Michaelis Menten kinetics using nonlinear regression analysis. TAM (0-50 µM) was incubated with genotyped human liver microsomes as described in the methodology section. There was a significant difference between CYP3A5*1/*1 and CYP3A5 *1/*3 or CYP3A5*3/*3 (p<0.05).
A B
Figure 20. Correlations between Vmax of N-DMT formation and (A) CYP3A4 protein, (B) CYP3A5 protein in a panel of genotyped human liver microsomes.
68 A B
Figure 21. Correlations between Vmax of α-OHT formation and (A) testosterone-6-β-hydroxylation, (B) midazolam-1-hydroxylation in genotyped human liver microsomes.
4.1.4. Effect of recombinant CYP3A5*8 and CYP3A5*9 on the formation of N-DMT
CYP3A5*8 and CYP3A5*9 have been reported to have decreased enzyme activity when
compared to the wild type CYP3A5 (Lee, et al., 2003). Using recombinant CYP3A5*8
and CYP3A5*9, we determined the enzyme kinetic estimates for N-DMT formation. The
data was best described by Michaelis-Menten model using non-linear regression analysis.
Vmax and Km estimates for N-DMT and the Michaelis-Menten plots are presented in
Table 8 and [Fig. 22], respectively. The intrinsic clearance for the formation of N-DMT
by rCYP3A5*8 was half of that observed for rCYP3A5 (0.28 vs 0.15 ml/min/pmol). On
the other hand, the intrinsic clearance for N-DMT formation by rCYP3A5*9 was not
significantly different from rCYP3A5 (0.24 vs 0.28 ml/min/pmol P450). However, the
estimates of Vmax and Km were significantly higher with rCYP3A5*9 in comparison to
the wild type allele (7.62 vs 2.68 nmol/min/pmol P450 and 31.39 vs 9.28 µM),
respectively. We also evaluated the enzyme kinetics for 1-hydroxy midazolam formation
69 from midazolam, a known substrate for CYP3A4 and 3A5. A similar trend was observed
in the formation clearance of 1-hydroxy midazolam. The intrinsic formation clearance
was lower with rCYP3A5*8 than with rCYP3A5 (1.84 vs 3.31 ml/min/pmol P450). The
Vmax and Km values estimated were higher with rCYP3A5*9 than that of rCYP3A5
(69.24 vs 36.06 nmol/min/pmol P450 and 20.42 vs 10.89 µM) as seen in Table 8 and [Fig.
23].
Table 8. Enzyme kinetic parameter estimates for the formation of N-DMT and 1-hydroxy midazolam by recombinant CYP3A5, CYP3A5*8 and CYP3A5*9 from TAM and midazolam, respectively. Each incubation contained TAM (0-50 µM) or Midazolam (0- 400 µM), 50 pmol of rCYP3A5 or rCYP3A5*8 or rCYP3A5*9 and a NADPH- regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis-Menten model for N-DMT formation and substrate inhibition kinetics for 1-hydroxy midazolam formation, using non linear regression analysis. Results are Mean ± SE from duplicate incubations.
Recombinant Vmax Km CLint CYP3A5 (nmol/min/pmol P450) (µM) (ml/min/pmol P450) N-DMT rCYP3A5 2.68 ± 0.16 9.28 ± 1.5 0.28 rCYP3A5*8 1.53 ± 0.21 10.25 ± 2.1 0.15 rCYP3A5*9 7.62 ± 1.4 31.39 ± 6.1 0.24 1-Hydroxy midazolam rCYP3A5 36.06 ± 4.6 10.89 3.31 rCYP3A5*8 9.8 ± 2.5 5.3 ± 0.8 1.84 rCYP3A5*9 69.24 ± 6.1 20.42 ± 4.3 3.39
Vmax, maximum velocity; Km, substrate concentration at which the reaction velocity is 50% of Vmax; CLint, intrinsic clearance
70
6 rCYP3A5*8 rCYP3A5*9 4 rCYP3A5
N-DMT 2 (nmol/min/pmol P450) 0 0 20 40 60 Tamoxifen (μM)
Figure 22. The enzyme kinetics of N-desmethyl tamoxifen (N-DMT) formation from TAM by the recombinant CYP3A5, CYP3A5*8 and CYP3A5*9 microsomes. Each data point represents the mean of two 10 minute incubations of TAM (0-50 µM) with 50 pmol of CYP3A5 or 3A5*8 or 3A5*9 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from Michaelis-Menten model using WinNonlin 5.2.
60 rCYP3A5*8 rCYP3A5*9 40 rCYP3A5
20 1-hydroxy midazolam (nmol/min/pmol P450) (nmol/min/pmol 0 0 100 200 300 400 500 Midazolam (μM)
Figure 23. The enzyme kinetics of 1-hydroxy-midazolam formation from midazolam by the recombinant CYP3A5, CYP3A5*8 and CYP3A5*9 microsomes. Each data point represents the mean of two 5 minutes incubations of midazolam (0-400 µM) with 50 pmol of CYP3A5 or 3A5*8 or 3A5*9 in the presence of NADPH regenerating system. Solid line represents the simulated curve generated from substrate inhibition model using WinNonlin 5.2.
71 4.1.5. Effect of novel CYP3A4 intronic variant on the formation of α-OHT and N-DMT
We then investigated the effect of a novel intronic variant in CYP3A4 on the formation of
α-OHT and N-DMT. Enzyme kinetic estimates were determined by incubating TAM with
the genotyped microsomes as described in the experimental section. The three sets of
genotyped human liver microsomes (HL-Q, HH-639, HH-1123) available were of
CYP3A5*3/*3 and CYP3A4*1 (intronic SNP). Hence, we compared the data on α-OHT
and N-DMT formation by these microsomes with the data from the microsomes that were
of CYP3A5*3/*3 and CYP3A4*1 wild type genotype. The Vmax and Km estimates for
the formation of α-OHT in the wild type (4.17 pmol/min/mg and 9.68 µM) and mutant
variant (3.13 pmol/min/mg and 10.79 µM) were not significantly different (Table 9).
However, the Vmax of N-DMT was lower in the mutant variant (73.16 pmol/min/mg)
Table 9. Enzyme kinetic parameter estimates for the formation of α-OHT and N-DMT by CYP3A4 intronic variant from TAM. Each incubation contained TAM (0-50 µM), 0.1mg/ml of protein and a NADPH-regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis-Menten model for α-OHT and N-DMT formation using non linear regression analysis. Each incubation was performed in duplicates.
CYP3A5 CYP3A4 CYP3A4 CYP3A5 N-DMT Vmax Km CLint α-OHT Vmax Km CLint Liver ID Genotype Ge notype Protein* Protein* (pmol/min/mg) (µM) (µl/min/mg) (pmol/min/mg) (µM) (µl/min/mg) HL-D *3/*3 *1/*1 8.3 0.3 97.32 17.44 5.58 1.80 9.62 0.19 HL-J *3/*3 *1/*1 20.9 0.4 122.67 9.84 12.47 5.90 8.16 0.72 HL-P *3/*3 *1/*1 19.3 1.1 106.09 7.64 13.88 4.39 7.96 0.55 HH-689 *3/*3 *1/*1 8.4 0.4 73.99 9.30 7.96 HL-R *3/*3 *1/*1 33.3 0.3 153.66 13.72 11.20 7.09 12.99 0.55 Mean 18.1 0.49 110.7 11.59 10.22 4.79 9.68 0.50 SD 10.4 0.35 29.7 3.96 3.39 2.28 2.32 0.23 HL-Q *3/*3 *1/*1 (intronic) 27.3 1.0 64.99 7.34 8.85 3.45 6.43 0.54 HH-639 *3/*3 *1/*1 (intronic) 16.5 0.4 76.39 5.76 13.25 2.30 6.17 0.37 HH-1123 *3/*3 *1/*1 (intronic) 14.0 0.0 78.11 17.63 4.43 3.65 19.77 0.18 Mean 19.29 0.45 73.16 10.25 8.84 3.13 10.79 0.36 SD 7.05 0.48 7.13 6.45 4.41 0.73 7.78 0.18
72 Table 10. Enzyme kinetic parameter estimates for the formation of 6-β-hydroxy testosterone by CYP3A4 intronic variant from testosterone. Each incubation contained testosterone (0-400 µM), 0.25mg/ml of protein and a NADPH-regenerating system in 100 mM phosphate buffer. Data was fitted to Michaelis Menten model for 6-β-hydroxy testosterone formation using non linear regression analysis. Each incubation was performed in duplicates.
6-β-hydroxy testosterone CYP3A5 CYP3A4 Vmax Km CLint Liver ID Genotype Genotype (nmol/min/mg) (µM) (ml/min/mg) HL-D *3/*3 *1/*1 0.59 10.42 0.06 HL-J *3/*3 *1/*1 2.23 58.75 0.04 HL-P *3/*3 *1/*1 1.78 72.52 0.02 HH-689 *3/*3 *1/*1 0.23 36.18 0.01 HL-R *3/*3 *1/*1 2.83 69.95 0.04 Mean 1.53 49.56 0.03 SD 1.10 26.16 0.02 HL-Q *3/*3 *1/*1 (intronic) 0.39 26.58 0.01 HH-639 *3/*3 *1/*1 (intronic) 0.37 22.81 0.02 HH-1123 *3/*3 *1/*1 (intronic) 0.52 13.92 0.04 Mean 0.43 21.10 0.02 SD 0.08 6.50 0.01
expressors than the wild type CYP3A4 (110.7 pmol/min/mg), but was not statistically
significant (p=0.055).
Furthermore, we evaluated the formation of 6-β-hydroxy testosterone in the same set of
microsomes. There was a clear trend towards lower Vmax and Km values for the
formation of 6-β-hydroxy testosterone in the microsomes expressing the intronic variant.
However, the differences were not statistically significant as seen from the CLint (0.03 vs
0.02 ml/min/mg) (Table 10).
73 4.2. Specific Aim 2: Clinical Assessment of CYP3A Induction by Tamoxifen
Previous findings from our laboratory indicated that TAM and 4-OHT induce CYP3A in
primary cultures of human hepatocytes via activation of PXR (Desai et al 2002). This
raises the possibility that TAM enhances its own metabolism – a phenomenon known as
auto-induction of clearance or time-dependent pharmacokinetics. CYP3A4 auto-
induction upon prolonged TAM use may result in increased conversion of TAM to α-
OHT and N-DMT, contributing to differences in TAM pharmacokinetics as well as
efficacy and endometrial toxicity. Employing MDZ as a probe substrate to determine
changes in CYP3A activity, we determined the potential of TAM to induce CYP3A in
breast cancer patients.
4.2.1. LC-MS/MS method development for quantitation of Midazolam
4.2.1.1. Chromatography
Chromatographic conditions and the composition of mobile phase in particular, were
optimized to achieve good sensitivity and peak shapes for the compounds. No
interference peaks were detected for the analytes or the internal standard from the
different sources of plasma. The retention times for 4-OH-MDZ, 1-OH-MDZ and MDZ
were 4.27, 4.88 and 5.36 minutes, respectively. Typical chromatograms for a blank
15 plasma spiked with MDZ, the IS N3 MDZ and its metabolites are shown in [Fig. 24].
74 The mass transitions monitored for MDZ, 1-OH MDZ and 4-OH MDZ were m/z 326 → 291,
15 m/z 342 → 324 and m/z 342 → 325, respectively. The IS N3 MDZ was monitored at m/z
329 → 294.
RT: 0.00 - 20.01 16.23 NL: 7.79E6 100 Base Peak F: FTMS + p 90 ESI Full ms [300.00-400.00] MS 80 16.05 Serum-STD6-007-R02 70
60
50 5.67 14.06
40 5.38 13.71 19.49 30 13.12 20 4.49 1.00 6.82 8.24 1.24 11.38 14.89 10 17.18 19.35 0.08 1.56 2.533.81 6.99 8.43 10.94 12.30 0 5.36 NL: 3.03E3 100 m/z= 289.50-291.70 F: 90 5.30 ITMS + p ESI Full ms2 0.625 ng/ml MDZ [email protected] 80 [200.00-340.00] MS Serum-STD6-007-R02 70 60 MS/MS 5.54 50 326 290-291 40
Relative Abundance Relative 30
20 5.13 1.20 5.66 10 4.74 0.61 1.64 2.36 4.30 5.75 6.23 0 5.36 NL: 5.92E4 100 m/z= 292.60-294.70 F: 90 15 ITMS + p ESI Full ms2 4.0 ng/ml N3-MDZ [email protected] 80 [200.00-340.00] MS Serum-STD6-007-R02 70
60 5.57 MS/MS 50 329 293-294 40
30
20
10 4.57 1.18 1.67 4.04 5.86 6.32 0 0 2 4 6 8 10 12 14 16 18 20 Time (min)
N Figure 24. A typical chromatogram of a blank plasma spiked with MDZ, labeled 153-MDZ (IS), 4-OH MDZ and 1-OH MDZ.
75 4.2.1.2. Linearity of Calibration Curves
The linear regression of the peak area ratios versus concentrations were fitted over the concentration range of 0.08 to 50 ng/ml for MDZ, 1-OH MDZ and 4-OH MDZ human plasma. The correlation coefficients of the 1/x2weighted calibration curves for MDZ and 1-
OH MDZ were r2= 0.99. Good linearity was seen in the concentration ranges of 0.1-50 ng/ml
[Fig. 25].
4.2.1.3. Extraction and Recovery
Recovery of all compounds of interest was tested in quality control (QC) samples. QC samples were made in plasma at three concentrations and were analyzed between each set of samples. The present method produced a satisfactory recovery of 87–105%, thus implying that extraction of the plasma did not result in any substantial loss of the chemical constituents.
76 A
MDZ Midazolam Y = -0.000749654+0.0570619*X+0.000347826*X^2 R^2 = 0.9956 W: 1/X^2
4.0
3.5 3.0 2.5
2.0
Area Ratio 1.5 1.0 0.5
0.0 0 10 20 30 40 50 ng/ml
B
1-OH MDZ 1-Hydroxy_midazolam Y = 0.000761295+0.0680331*X+0.000702475*X^2 R^2 = 0.9937 W: 1/X^2
5 b
4
3 Area Ratio 2
1
0 0 10 20 30 40 50 ng/ml
Figure 25. Representative calibration plasma standard curves for Midazolam (a), and 1-OH- MDZ in human plasma samples.
77 4.2.2. Induction of CYP3A by TAM in Breast Cancer Patients
CYP3A induction by TAM was assessed using oral MDZ (2 mg, oral syrup) as a probe
substrate. As discussed before, MDZ is exclusively metabolized by CYP3A4/5 to its
primary metabolite 1-OH MDZ. Any changes in CYP3A activity will be reflected in oral
clearance, a criterion widely used to assess CYP3A activity. The demographic details of
the 13 patients enrolled in the pharmacokinetic study are presented in Table 11. The
mean age and weights of the patients enrolled were 49 ± 7 yrs and 75 ± 17 kg,
respectively. All the 13 patients completed the three visits and provided approximately a
total of 35 blood samples for MDZ pharmacokinetic analysis as per the protocol. No
major adverse events were reported during the course of the trial. The plasma samples
collected for pharmacokinetic analysis were subject to double extraction procedure and
quantitated for MDZ and 1-OH MDZ using the validated LC-MS/MS methodology
(detailed in methodology section).
Table 11. Demographics of patients enrolled in the PK study
ID AGE (yrs) WT (kg) 1 44 73 3 57 53 4 49 68 5 53 82 6 50 100 7 52 79 8 52 57 9 50 79 10 44 63 11 64 98 12 55 60 14 35 64 15 38 107 Mean 49.46 75.60 SD 7.77 17.30
78 A
37 37
ID: 1 ID: 3 ID: 4 ID: 5 30
10
ID: 6 ID: 7 ID: 8 ID: 9 30
10
ID: 10 ID: 11 ID: 12 ID: 14 30
10 Midazolam (ng/ml) Conc. ID: 15 30 Day 0 Time(hrs) Day 1 10 Day 42
37 B
8
Baseline Day +1 6 Day +42
4
2 Midazolam Plasma Conc(ng/ml)
0 012345678 Time (hrs)
Figure 26. Plasma concentration time profile of MDZ in breast cancer patients on Day 0 (Blue), Day 1 (Green) and Day 42 (Red) (A). Profile of patient ID= 06 showing induction of CYP3A on Day 42 as seen by decrease in the AUC and Cmax (B).
79 The concentration data of each patient was used to estimate the pharmacokinetic
parameters for MDZ by non compartmental analysis employing WinNonlin 5.2. There
was no statistically significant difference in mean CL/F, AUC and half life estimates
betweeen Day 0 and Day 42 or Day 1 and Day 42. However, in 6 out of the 13 patients, a
mean increase of 70% (range 6 to 161%) in the oral clearance of MDZ was observed
between Day 0 to Day 42. The corresponding mean decrease in AUC0-∞ and half life for
those 6 patients were 31% (range 4 to 59%) and 30% (range 19 to 71%), respectively
(Table 12). The parameter estimates of CL/F, AUC0-last, AUC0-∞, Vd, Tmax, Cmax and
half life for all the treatment days have been tabulated in table 13. The plasma
concentration Vs time profiles of MDZ for all the patients are presented in [Fig. 26A]. As
an example, MDZ concentration time profile of patient ID=06 is presented in [Fig. 26B]
to indicate the significant decrease in AUC and Cmax on day 42 in comparison to Day 0
or Day 1. The changes in CL/F, AUC0-∞ and half life of MDZ between Day 0 and Day
42, Day 1 and Day 42 are presented in [Fig. 27A, B and C]. Thus, our data clearly
shows significant CYP3A induction in some patients. Furthermore, extensive inter-
individual variability in CYP3A induction was observed
Table 12. Changes (%) in Midazolam Pharmacokinetics in Patients (N=6)
% Increase in CL/F % Decrease in AUC % Decrease in Half life ID Day 0 to 42 Day 1 to 42 Day 0 to 42 Day 1 to 42 Day 0 to 42 Day 1 to 42 4 76 57 36 43 19 33 6 132 103 56 44 29 6 8 6 10 4 3 19 4 10 26 49 20 34 23 39 14 161 145 59 62 71 46 15 21 61 13 35 20 5 Mean 70 71 31 37 30 22 SD 64 47 23 19 20 19
80 Table 13. Pharmacokinetic estimates of midazolam after administration of 2 mg oral midazolam syrup in 13 breast cancer patients on three visits.
Midazolam PK Parameter Estimates Half life Tmax Cmax AUClast AUCinf Vd CL/F Subject Visits (hr) (hr) (ng/mL) (ng.hr/ml) (ng.hr/mL) (L) (L/hr) Day 0 1.3 0.5 11.9 28.69 31.41 123.76 63.68 1 Day 1 1.2 0.5 16.9 41.79 44.57 78.08 44.87 Day 42 3.3 0.5 9.4 41.37 51.26 183.61 39.02 Day 0 1.8 0.5 33.5 55.11 58.84 90.43 33.99 3 Day 1 3.2 0.5 51.6 115.01 151.04 61.96 13.24 Day 42 4.8 0.5 39.4 170.94 254.84 54.86 7.85 Day 0 2.3 1.0 10.4 31.93 41.52 174.10 48.16 4 Day 1 2.8 0.5 14.2 41.07 46.64 171.52 42.99 Day 42 1.8 0.5 10.7 25.44 26.51 200.28 75.46 Day 0 3.7 1.0 4.7 22.46 31.51 338.00 63.46 5 Day 1 2.3 0.3 7.5 18.39 19.38 342.14 103.18 Day 42 2.8 2.0 4.8 18.21 21.80 366.19 91.75 Day 0 1.6 0.5 7.1 15.78 18.13 287.46 122.71 6 Day 1 1.2 0.5 7.1 13.01 14.24 271.30 140.40 Day 42 1.2 1.0 3.4 6.96 7.96 473.60 284.90 Day 0 1.4 0.5 8.8 20.70 22.98 190.70 94.77 7 Day 1 1.7 0.5 6.7 16.05 17.48 272.56 114.38 Day 42 1.3 1.0 6.5 18.10 19.40 199.09 103.00 Day 0 1.5 1.0 12.5 35.63 38.29 115.76 54.70 8 Day 1 1.2 0.5 23.4 35.38 38.01 94.4 52.60 Day 42 1.2 0.5 16.8 34.26 36.68 99.26 57.80 Day 0 1.6 0.5 15.9 31.16 34.39 34.38 58.16 9 Day 1 1.5 0.5 10.7 27.81 30.01 147.80 70.28 Day 42 1.4 0.5 13.5 30.46 32.42 129.50 64.30 Day 0 1.78 2 7.1 27.85 30.75 167.00 65.04 10 Day 1 3.58 1 12.7 29.98 37.11 278.12 54.90 Day 42 2.19 0.5 8.2 18.08 24.48 258.41 81.68 Day 0 1.45 0.5 5.18 11.46 12.79 327.24 156.31 11 Day 1 2.36 0.5 8.9 17.33 18.36 370.38 108.90 Day 42 1.53 0.08 9.3 18.86 19.84 222.5 100.80 Day 0 1.5 0.50 3.66 6.94 7.07 618.18 282.82 12 Day 1 1.0 1 4.99 8.31 8.33 337.17 240.10 Day 42 1.4 0.5 7.20 10.38 10.45 395.08 191.46 Day 0 2.2 1.00 4.4 8.87 9.02 700.61 216.98 14 Day 1 0.4 0.5 5.4 9.82 9.84 130.36 203.33 Day 42 0.6 0.25 4.9 3.73 3.73 496.96 531.48 Day 0 2.0 0.5 6.74 13.01 14.20 409.08 140.83 15 Day 1 1.7 0.5 15.52 18.54 18.96 258.20 105.50 Day 42 1.6 0.5 5.83 11.38 12.35 396.56 169.97
81 A
600 600
400 400
200 200 Midazolam CL/F (L/hr) CL/F Midazolam Midazolam CL/F (L/hr) CL/F Midazolam 0 0 Day 0 Day 42 Day 1 Day 42
B
60 60
40 40
20 20
Midazolam AUC (ng.hr/ml) AUC Midazolam 0 (ng.hr/ml) AUC Midazolam 0 Day 0 Day 42 Day 1 Day 42
C
4 4
3 3
2 2
1 1 Midazolam Half Life (hr) Life Half Midazolam (hr) Life Half Midazolam 0 0 Day 0 Day 42 Day 1 Day 42
Figure 27. Changes in oral clearance (CL/F, L/hr) of MDZ between Day 0 and Day 42, and Day 1 and Day 42 (A). Changes in AUC of MDZ between Day 0 and Day 42, and Day 1 and Day 42 (B). Changes in half life of MDZ between Day 0 and Day 42, and Day 1 and Day 42 (C). CL/F and AUC estimates were determined by noncompartmental analysis using WinNonlin 5.2.
82 4.3. Specific Aim 3: Impact of CYP3A and PXR Variants on CYP3A Induction
The impact of polymorphic expression on the induction of CYP3A is poorly understood.
CYP3A5 is generally considered to be a non-inducible CYP3A isoform in comparison to
CYP3A4. A recent study does suggest that CYP3A5 may also be regulated by hPXR and
is inducible by hPXR ligands (Burk et al 2004). Even so, the induction appears to be
mainly at the intestinal CYP3A5 expression. However, it is feasible that the extent of
induction may be associated with the CYP3A4 and CYP3A5 polymorphisms.
Furthermore, polymorphisms in PXR have been associated with higher induction in
CYP3A activity following treatment with rifampicin (Lamba et al 2008). Individuals
expressing these variants are likely to exhibit higher level of CYP3A induction as a result
of TAM therapy, which may be reflected in higher levels of N-DMT or α-OHT and
increased propensity for drug interactions. Therefore, a preliminary assessment on the
impact of CYP3A4*1B, CYP3A5*3 and PXR polymorphisms on CYP3A induction was
conducted.
4.3.1. Association of CYP3A and PXR Genotypes with Fold Change in Clearance
To investigate the genetic basis for the observed differences in CYP3A induction, a 10 ml
of blood sample was collected from each patient and was genotyped for polymorphisms
in CYP3A and PXR using TaqMan SNP chemistry as described in the methodology
section. Specifically, we genotyped for CYP3A4*1B, CYP3A5*3 and the three PXR
variants (63396T>C, -24381A>C, -25385C>T) that have been previously known to
modulate CYP3A activity (Lamba et al 2008, Siccardi M et al 2008). Association of
83 CYP3A5 genotypes with fold change in MDZ clearance revealed a trend towards higher induction in individuals with CYP3A5*1/*3 vs. CYP3A5*3/*3 genotypes [Fig. 28].
Furthermore, one individual with maximum increase (2.5 fold) in midazolam CL/F was homozygous to C and T alleles of PXR -24381A>C and -25385C>T variants, respectively [Fig. 29 and 30]. No association was observed between CYP3A4*1B and fold change in midazolam clearance. In addition, there was no significant difference in α-
OHT mean plasma concentrations between individuals expressing CYP3A5*1/*3 vs
CYP3A5*3/*3 [Fig. 31].
3 2.5 *p<0.05 2 1.5 * 1
Fold Change in in Change Fold 0.5
Midazolam Clearance Midazolam 0 *1/*3 *3/*3 N=2 N=6 CYP3A5
Figure 28. Association of CYP3A5 genotype with CYP3A induction determined as fold change in midazolam oral clearance. DNA was isolated from fresh blood collected in EDTA vacutainers using Puregene kit and genotyped using TaqMan SNP genotyping assay.
84 3 2.5 2 1.5 1 0.5 Fold Change in in Change Fold
Midazolam Clearance Midazolam 0 CC CT TT N=5 N=2 N=1 PXR 25385C>T
Figure 29. Association of PXR -25385C>T genotype with CYP3A induction determined as fold change in midazolam oral clearance. DNA was isolated from fresh blood collected in EDTA vacutainers using Puregene kit and genotyped using TaqMan SNP genotyping assay. .
3 2.5 2 1.5 1
Fold Change in in Change Fold 0.5
Midazolam Clearance Midazolam 0 AA AC CC N=4 N=3 N=1
PXR 24381A>C
Figure 30. Association of PXR -24381 A>C genotype with CYP3A induction determined as fold change in midazolam oral clearance. DNA was isolated from fresh blood collected in EDTA vacutainers using Puregene kit and genotyped using TaqMan SNP genotyping assay.
85 CYP3A5*3/*3 0.6 CYP3A5*1/*3
0.5 -OHT α 0.4
0.3 (ng/ml)
0.2 Mean Plasma 0.1
0 Day 1 Day 42
Figure 31. Association of mean plasma α-OHT (ng/ml) between CYP3A5*1/*3 vs CYP3A5*3/*3 genotypes on Day 1 and Day 42.
86 5. CHAPTER FIVE: DISCUSSION
TAM is a widely used and highly effective endocrine agent for the treatment of breast cancer
in the adjuvant and metastatic settings and for chemoprevention. Originally tested as an oral
contraceptive, TAM was later found to be an effective “antiestrogen”. Since its introduction
in 1970, TAM has been the first line of therapy in treating patients with ER positive tumors.
TAM has a mixed ER agonist and antagonist properties depending on the target tissues. By
way of its agonist action, TAM helps to maintain bone mineral density and lower lipid levels
thereby ameliorating bone and cardiovascular diseases in women (Osborne, 1998;Kristensen,
et al., 1994). In the uterus, TAM’s agonist action has been reported to increase the risk of
developing endometrial cancer in postmenopausal women (Jordan and Morrow, 1994). It was
in the pursuit of understanding these estrogenic effects like uterine lining growth, α and β
isoforms of ER were identified.
Notwithstanding the advent of aromatase inhibitors (AIs) and newer selective estrogen
receptor modulators (SERMs), TAM remains an important member of the armamentarium
against breast cancer. TAM continues to be the single drug available for pre-menopausal
women who wish to pursue chemoprevention or in the treatment of pre-menopausal women
with estrogen receptor-positive breast cancer (Bao, et al., 2006;Fisher, et al., 2005a). Many
physicians prefer TAM due to its record of effectiveness and in instances where patients do
not favorably respond to other endocrine agents including aromatase inhibitors or present
with osteoporosis. Despite being successfully used for more than 30 years, some of the
clinical problems associated with the use of TAM include high inter-individual variability in
its pharmacokinetics and therapeutic outcome, drug-drug interactions, acquired drug
87 resistance and increased risk of endometrial cancer. Other commonly observed side effects of
TAM therapy are hot flushes, vaginal bleeding and discharge, and thromboembolism (Perez,
2007).
The ability of TAM to induce endometrial cancer has been a great concern for the past few decades. Patients on TAM therapy have a 2-6 fold higher risk of developing endometrial cancer, with a even greater risk in women older than 50 (Bergman, et al., 2000;Reddy and
Chow, 2000). This poses a huge dilemma to the patients and to the physicians. It is important to indicate that the exact mechanism of TAM-induced carcinogenesis remains unresolved, and in fact, somewhat controversial. Endometriosis may be linked to the estrogenic activity of TAM in the uterus. The other major proposed hypothesis suggests that TAM is metabolically activated to genotoxic species (Brown, 2009). α-OHT, one of the primary metabolites formed by hydroxylation of TAM undergoes activation to form DNA adducts resulting in endometrial cancer. Infact, several investigators have identified TAM- DNA adducts in rats, monkeys and women treated with TAM (Carthew, et al., 2000;Shibutani, et al., 2000;Hemminki, et al., 1996;Orton and Topham, 1997;Shibutani, et al., 2003;Martin, et al., 2003). Inspite of several other treatment modalities for breast cancer in postmenopausal patients, TAM (20 mg/day for 5 years) is still being recommended as the drug of choice to reduce the risk of invasive ER-positive tumors, with benefits for at least 10 years
(Visvanathan, et al., 2009). Furthermore, its use has been more cost effective than other drugs. Therefore, attempts to better understand some of the unresolved issues and to optimize the use of TAM continues to be a high priority.
88 The impact of CYP2D6 polymorphisms on the disposition of TAM has been investigated by several investigators over the last few years. CYP2D6 is the cytochrome P450 isoform that is mainly responsible for catalyzing the conversion of TAM to 4-OHT and N-DMT to endoxifen, the active metabolite. Plasma levels of endoxifen have been linked to CYP2D6 genotype and higher incidences of hot flushes (Goetz, et al., 2005;Jin, et al., 2005;Stearns, et al., 2003;Borges, et al., 2006). Jin et al. observed that patients who carried either the homozygous (*4/*4) or the heterozygous (wt/*4) variant genotype of CYP2D6 had statistically significantly lower mean plasma endoxifen levels (20.0 and 43.1 nM, respectively) than those who carried the homozygous wild-type (wt/wt) genotype (78.0 nM).
These patients also had fewer incidences of hot flashes. Furthermore, individuals with
CYP2D6 *4/*4 genotype have been associated with poor patient outcome, worse relapse-free and disease-free survival (Goetz, et al., 2008;Goetz and Ingle, 2007;Brauch and Jordan,
2009).
However, there is paucity of data on the impact of CYP3A activity and its polymorphic expression on the diposition of TAM. The major metabolite, N-DMT and the genotoxic product, α-OHT are exclusively formed by CYP3A. On one hand, individuals with higher
CYP3A activity will have increased capacity for TAM conversion to N-DMT, contributing to variability in the plasma levels of endoxifen. On the other hand, increased CYP3A levels, may lead to increased production of the genotoxic α-OHT, which may ultimately lead to increased chances of endometrial carcinogenesis (Shibutani, et al., 2000). In addition, co- administration of TAM has been shown to markedly reduce the plasma concentrations and
AUC of letrozole and anastrozole, causing a mean 37 and 27 % reduction in the levels of
89 letrozole and anastrozole, respectively (Dowsett, et al., 1999;Dowsett, et al., 2001). Indeed, previous investigations from our laboratory indicated that TAM and 4-OHT induced
CYP3A4 activity in primary human hepatocytes via activation of PXR (Desai, et al.,
2002;Sane, et al., 2008). Furthermore, there is increasing evidence that contribution of
CYP3A5 activity is equal to that of CYP3A4 for the metabolism of several compounds including tacrolimus, cyclosporine, vincristine, ethylmorphine, lidocaine, testosterone, sildenafil and alfentanil (Klees, et al., 2005;Gillam, et al., 1995;Huang, et al., 2004;Dai, et al., 2006;Dennison, et al., 2007). For tacrolimus, vincristine and sidenafil, polymorphic expression in CYP3A5 have been associated with lower metabolism in individuals expressing CYP3A5*3/*3 (Dennison, et al., 2007;Chandel, et al., 2009;Tirelli, et al.,
2008;Ferraresso, et al., 2007;Ku, et al., 2008).
Based on the current literature, and given the major role played by CYP3A in the metabolism of TAM, there is a strong likelihood that changes in CYP3A activity due to genetics or induction has the potential to impact TAM activation/ detoxification and its efficacy/toxicity in vivo. Therefore, the current study was undertaken a) to determine the relative contribution of CYP3A4/5 and to assess the impact of CYP3A5 polymorphic expression to the formation of α-OHT and N-DMT, b) to evaluate the extent to which TAM induces CYP3A in women initiating TAM therapy using MDZ as probe substrate, and c) to conduct preliminary assessment on the impact of genetic variability on CYP3A induction by TAM.
90 5.1. Contribution of CYP3A4/5 and the impact of its polymorphic expression to the
formation of α-OHT and N-DMT
Employing cDNA expressed CYP3A4 and CYP3A5, we demonstrated that the formation
of α-OHT is primarily mediated by CYP3A4. The intrinsic formation clearance
(Vmax/Km) of α-OHT was 6 fold higher with rCYP3A4 than rCYP3A5 (3.23 vs 0.65
µl/min/pmol P450) indicating the limited contribution by CYP3A5. This is further
substantiated by the lack of difference in Vmax of α-OHT between microsomes
genotyped for CYP3A5*1/*1, CYP3A5*1/*3 and CYP3A5*3/*3. Furthermore, we
observed significant correlations between Vmax and CYP3A4 protein content and, Vmax
and CYP3A4 activity (testosterone 6-β-hydroxylation) implying that the formation of α-
OHT is principally catalyzed by CYP3A4. This is also supported by the poor correlation
between Vmax and CYP3A5 protein content. Previous studies have investigated the
involvement of CYP3A4 in α-OHT of TAM (Crewe, et al., 1997;Notley, et al.,
2005;Desta, et al., 2004). However, the kinetic parameters for the formation of α-OHT
and the role of polymorphic CYP3A5 on α-OHT have not been reported. Moreover, the
TAM concentrations (18 and 250 µM) used by Notley et al are significantly higher than
the reported plasma concentration of TAM (0.1-1µM). In our studies, the concentration
of TAM used ranges from 0-50 µM simulating the plasma and hepatic levels.
Since CYP3A4 is found to be the major enzyme involved in the formation of α-OHT,
polymorphisms in CYP3A4 may provide an explanation to why only some patients
develop endometrial cancer. Recently, a novel intronic variant was identified in CYP3A4
by Wolfgang Sadee, Ph.D, at the Ohio State University (personal communication). This
91 variant results in decreased mRNA expression and has been associated with reduced statin maintenance dose. Using human liver microsomes genotyped for the novel variant, we investigated its impact on the intrinsic formation clearance of α-OHT. Though there was no significant difference in CLint between the wild type and variant microsomes, a trend towards lower Vmax was observed in the microsomes genotyped for the intronic variant. A similar observation was seen for N-DMT. Given the small sample size (n=3), we did not see a statistically significant difference between the genotypes and warrants further investigation.
In the case of N-DMT, the formation intrinsic clearance (CLint) by recombinant
CYP3A4 and CYP3A5 were similar (0.57 vs 0.35 ml/min/pmol P450). This implies that both CYP3A4 and CYP3A5 play an equal role in the formation of N-DMT. In addition, a threefold difference was observed in the Vmax of N-DMT between CYP3A5*1/*1 and
CYP3A5*1/*3 or CYP3A5*3/*3 genotyped microsomes suggesting that CYP3A5 variants may contribute to the variability observed in TAM therapy. Furthermore, a significant correlation was observed between Vmax and CYP3A4 (r=0.56, p=0.04), and
CYP3A5 (r=0.81, p<0.0001) protein content. This data, taken together with the significant association between Vmax and CYP3A activity suggests that polymorphisms in CYP3A5 may contribute to the variability in plasma N-DMT levels. Since N-DMT is present in higher concentrations in plasma and is the precursor to the active metabolite endoxifen, polymorphic expression of CYP3A5 may play an important role in TAM therapy. We then assessed the effect of other variants, CYP3A5*8 and CYP3A5*9 on the formation of N-DMT using cDNA expressed isoforms. A 50% reduction in CLint was
92 observed with rCYP3A5*8 in comparison to the wildtype rCYP3A5 allele. In fact, Lee et
al had reported ~90% reduction in CLint of testosterone and nifedipine oxidation with
this particular variant (Lee et al 2003). Overall, there have been some conflicting results
on the influence of CYP3A5 polymorphisms on the pharmacokinetics of TAM. Jin et al.,
reported that individuals with CYP3A5*1/*1 alleles had higher plasma levels of
endoxifen than those with CYP3A5*3/*3 alleles (Jin, et al., 2005). On the other hand,
Tucker et al and Goetz et al., showed that there was no influence of CYP3A5
polymorphisms on TAM metabolism or overall survival (Tucker, et al., 2005). In another
study, Wegman et al., reported that patients with CYP3A5*3/*3 polymorphism had
increased risk of recurrence after two years of TAM treatment (Wegman, et al., 2007).
Using recombinant CYP3A and a panel of genotyped microsomes, our systematic in vitro
study provides evidence to the impact of CYP3A5 polymorphic expression on the
formation of N-DMT.
5.2. Clinical Assessment of CYP3A induction by Tamoxifen
Based on our in vitro findings that TAM and 4-OHT induce CYP3A4 in primary human
hepatocytes, we undertook clinical assessment of CYP3A induction by TAM in breast
cancer patients using MDZ as the probe substrate. Our findings are the first report on the
induction of CYP3A by TAM in clinical settings. In 6 out of 13 patients, we observed a
mean increase in oral midazolam CL/F of 70% (range 21-161%) between Day 0 and Day
42. This increase in CL/F observed in 6 patients is similar to the reported percent increase
seen with induction of CYP3A by St. Johns Wort as (see table 14 below). A
corresponding decrease in AUC and half life by ~30% was observed in these patients.
93 Such an induction would result in higher levels of α-OHT, increasing the risk of endometrial toxicity in patients undergoing TAM therapy.
Table 14. Percent change in midazolam oral clearance due to CYP3A induction by St. Johns Wort
Midazolam % Change in MDZ Inducer Population References Dose Oral Clearance/AUC 5 mg N=12, Men, 20-33 yrs 33 % ↑ (Imai, et al., 2008) 4 mg N=21, 52% Female, 20-55 yrs 168 % ↑ (Dresser, et al., 2003) St. Johns 5 mg N=12, Female, 20-34 yrs 53% ↑ (Hall, et al., 2003) Wort 5 mg N=12, 42% Female, 23-35 yrs 109% ↑/50%↓ (Wang, et al., 2001) 5 mg N=30, 26% Female,19-51 yrs 56 % ↑ (Xie, et al., 2005)
Clearly, our data strongly underscores the hypothesis that TAM therapy leads to induction of CYP3A in some patients, and it also suggests that there is extensive variability in the extent of induction. Other factors that may confound the observed induction include diet, disease condition, CYP3A inhibitory effect of TAM and the fact that midazolam may be a
P-glycoprotein substrate. The dietary effect was minimized by restricting patients from consuming products containing St. John’s Wort (CYP3A inducer) for the entire duration of study. Smoking and drinking alcohol were also restricted for at least one day prior to their hospital visit and until last blood sample collection. TAM is reported to inhibit
CYP3A in human liver microsomes, but there are no reports on clinical drug - drug interactions with other CYP3A substrates (Zhou, et al., 2005;Zhao, et al., 2002). In our study, we observed a marginal increase in Cmax and AUC of MDZ on Day 1 after a single dose of TAM. As seen in table 12, this does not change our interpretation because the mean percent changes in MDZ pharmacokinetics are similar. For eg, mean percent increase in CL/F from Day1 to Day 42 (71%) is similar to that observed between Day 0 to
94 Day 42 (70%). Another confounding issue may be induction of P-glycoprotein and/or
CYP3A in the gut, which may influence MDZ pharmacokinetics. However, based on our
preliminary studies of TAM effects of intestinal CYP3A or P-gp and known mechanism
of MDZ absorption, this is unlikely.
The major limitation of our clinical study is the small sample size of 13 patients. Over the
last few years, there has been a shift in the standard of care with many patients opting for
AIs like letrozole and anastrozole. This has resulted in a slow accrual rate and a decline in
availability of the patients willing to volunteer for the study. The study is still ongoing
with the objective of meeting the estimated sample size of 18.
5.3. Influence of CYP3A and PXR polymorphisms on CYP3A induction by Tamoxifen
We then investigated the genetic basis for the above indicated differences in CYP3A
induction by genotyping the blood samples for polymorphisms in CYP3A and PXR using
TaqMan SNP genotyping assays. Association of genotypes with fold change in midazolam
clearance suggested a trend towards higher induction in individuals with CYP3A5*1/*3
vs. CYP3A5*3/*3 genotypes. One individual with maximum fold increase in midazolam
CL/F was also homozygous to C and T alleles of PXR -24381A>C and -25385C>T
variants, respectively. This is in agreement with the previously reported observation that
individuals with -24381CC variant have higher CYP3A4 mRNA levels (King, et al.,
2007). No association was observed between CYP3A4*1B, PXR 63396T>C variants and
fold increase in midazolam clearance. Furthermore, we observed no relationship between
plasma α-OHT (ng/ml) and CYP3A5 genotypes, supporting our in vitro findings that
95 CYP3A5 has a limited role in the formation of α-OHT. As mentioned previously, the main drawback for our analysis is the small sample size.
96 6. CHAPTER SIX: CONCLUSIONS AND FUTURE DIRECTIONS
This doctoral dissertation research has provided novel insights on genetic contribution to the
formation of CYP3A derived metabolites such as N-DMT and α-OHT, and to the inter-
subject variability in CYP3A inductive effects of TAM. Firstly, employing cDNA expressed
CYP3A and human liver microsomes genotyped for CYP3A5, we have shown that the
formation of α-OHT is primarily mediated by CYP3A4 with a limited contribution by
CYP3A5. Furthermore, with the growing recognition on the importance of CYP3A5
polymorphisms in the metabolism of CYP3A substrates, our in vitro data demonstrates that
individuals expressing CYP3A5*1/*1 alleles may have higher levels of N-DMT than the non
carriers (CYP3A5*3/*3). This result supports the observation that polymorphic expression
of CYP3A5 may contribute to the observed variability in CYP3A expression (Huang, et al.,
2004;Dai, et al., 2006;Kamdem, et al., 2004).
Though the plasma concentrations of N-DMT at steady state are 1.5- 2 fold higher than the
parent compound, its ER binding affinity is lower than TAM (Morello, et al., 2003).
Furthermore, as N-DMT is metabolized by CYP2D6 to a recently characterized active
metabolite endoxifen, inter-individual variability in plasma levels of N-DMT may contribute
to the differences in efficacy and safety observed after TAM therapy. A prospective
controlled clinical study to assess the impact of CYP3A5 polymorphisms on TAM
pharmacokinetics will aid in translating our in vitro findings to clinical situation. A positive
association in clinical studies may facilitate recommendations to prospectively genotype
patients for CYP3A5 polymorphisms, in addition to the current proposal for identifying
individuals based on CYP2D6 genotype prior to initiation of TAM therapy.
97 In the clinical pharmacology study, we observed a significant CYP3A induction by TAM in
6 patients with an average of 70% increase in CL/F and approximately 30% decrease in AUC and half life of MDZ. Our data provides evidence that TAM induces CYP3A supporting the previously observed drug interactions of TAM with AIs like letrozole and anastrozole.
Furthermore, this may aid in devising strategies to circumvent such interactions. For instance, aromatase inhibitors or other co-administered drugs that are not CYP3A substrates may be used in preference to those that are metabolized by CYP3A. In addition, based on the observations by Kisanga et al., that TAM treatment may be improved by administering lower doses (1 mg or 5 mg daily instead of the current regimen of 20 mg) and that dose dependent
CYP3A induction was noted in primary human hepatocytes, smaller doses may be advocated to reduce side effects and induction mediated drug interactions (Kisanga, et al., 2004;Sane, et al., 2008).
In light of our evidence that TAM induces CYP3A, the possibility that increased levels of genotoxic TAM metabolites can contribute to endometrial toxicity should be considered. In fact, endometrial tissues have been reported to express CYP3A4/5/7 and PXR, which participate in the biotransformation of TAM to α-OHT and N-DMT (Hukkanen, et al.,
1998;Sharma, et al., 2003;Masuyama, et al., 2003). Besides, the concentrations of TAM and
N-DMT have been reported to be 22-400 fold, and 5-11 folds higher in endometrium, and breast tissue, respectively than in plasma (Giorda, et al., 2000;Kisanga, et al., 2004). Such high concentrations of TAM may lead to greater production of α-OHT and increase the risk of toxicity in endometrium and breast tissues. The next steps based on the results of our studies would be to assess the potential of TAM to activate PXR and induce CYP3A in
98 endometrial and breast tissues. Such mechanistic studies will aid in confirming the role of genotoxic α-OHT in mediating endometrial cancer.
Moreover, preliminary examination on the impact of genetic polymorphisms revealed that
CYP3A5 carriers may have higher propensity to undergo TAM mediated CYP3A induction than individuals expressing CYP3A5*3/*3. Based on the findings of genetic influence of
CYP3A/PXR on the CYP3A induction, prospectively designed larger studies can be undertaken to establish a confirmatory link between these factors and the risk for drug interactions. Alternatively, in vitro studies employing hepatocytes genotyped for PXR variants can be used to delineate the genetic influence on induction of CYP3A by TAM, in place of a clinical trial. Such in vitro studies will provide insights on the effect of PXR polymorphisms, prior to embarking on a larger scale clinical study. Furthermore, such studies will aid in identifying individuals such as those that have higher CYP3A/PXR activity and are likely to have higher exposure to α-OHT or N-DMT.
Overall, our in vitro and clinical studies provide insights on genetic contribution to the formation of CYP3A derived metabolites such as α-OHT and N-DMT, and to the inter- subject variability in CYP3A inductive effects of TAM. Using genotyped human liver microsomes and cDNA expressing CYP3A isoforms, we demonstrated that a) formation of
α-OHT is not impacted by CYP3A5 genotypes and, b) formation of N-DMT was dependent on CYP3A5 genotype, with a threefold higher Vmax in individuals expressing
CYP3A5*1/*1 vs CYP3A5*3/*3 variants. Clinical assessment of CYP3A induction by
TAM demonstrated that 6 out of 13 patients had a mean 70% increase in MDZ clearance,
99 with an extensive variability observed in the induction (range: 26-161%). Furthermore, individuals expressing CYP3A5*1/*3 had a trend towards higher induction than those carrying CYP3A5*3/*3. One patient with the maximal induction (2.5 fold) was also homozygous to TT and CC variants of PXR (-25385C>T and -24381 A>C). No association was found with CYP3A4*1B, PXR 63396 C>T and CYP3A induction. These findings form a basis for future undertakings that include assessment of CYP3A induction in breast and endometrial tissues, evaluating the association of PXR variants on CYP3A induction by
TAM employing hepatocytes genotyped for specific variants, and confirming these results in a prospective clinical study. Ultimately, these studies will assist in optimizing TAM therapy by minimizing the adverse events and maximizing the therapeutic benefits.
100 REFERENCES Reference List
Amirimani B, Ning B, Deitz AC, Weber BL, Kadlubar FF and Rebbeck TR (2003) Increased transcriptional activity of the CYP3A4*1B promoter variant. Environ Mol Mutagen 42:299-305.
Backman JT, Olkkola KT and Neuvonen PJ (1996) Rifampin drastically reduces plasma concentrations and effects of oral midazolam. Clin Pharmacol Ther 59:7-13.
Baes M, Gulick T, Choi HS, Martinoli MG, Simha D and Moore DD (1994) A new orphan member of the nuclear hormone receptor superfamily that interacts with a subset of retinoic acid response elements. Mol Cell Biol 14:1544-1552.
Bao T, Prowell T and Stearns V (2006) Chemoprevention of breast cancer: tamoxifen, raloxifene, and beyond. Am J Ther 13:337-348.
Beatson GT (1896) On the treatment of inoperable cases of carcinogen of the mamma: suggestions for a new method of treatment with illustrative cases. Lancet162-167.
Bergman L, Beelen ML, Gallee MP, Hollema H, Benraadt J and van Leeuwen FE (2000) Risk and prognosis of endometrial cancer after tamoxifen for breast cancer. Comprehensive Cancer Centres' ALERT Group. Assessment of Liver and Endometrial cancer Risk following Tamoxifen. Lancet 356:881-887.
Bertilsson G, Heidrich J, Svensson K, Asman M, Jendeberg L, Sydow-Backman M, Ohlsson R, Postlind H, Blomquist P and Berkenstam A (1998) Identification of a human nuclear receptor defines a new signaling pathway for CYP3A induction. Proc Natl Acad Sci U S A 95:12208- 12213.
Biswas A, Mani S, Redinbo MR, Krasowski MD, Li H and Ekins S (2009) Elucidating the 'Jekyll and Hyde' nature of PXR: the case for discovering antagonists or allosteric antagonists. Pharm Res 26:1807-1815.
Blackhall FH, Howell S and Newman B (2006) Pharmacogenetics in the management of breast cancer -- prospects for individualised treatment. Fam Cancer 5:151-157.
Blumberg B, Sabbagh W, Jr., Juguilon H, Bolado J, Jr., van Meter CM, Ong ES and Evans RM (1998) SXR, a novel steroid and xenobiotic-sensing nuclear receptor. Genes Dev 12:3195-3205.
Boocock DJ, Brown K, Gibbs AH, Sanchez E, Turteltaub KW and White IN (2002) Identification of human CYP forms involved in the activation of tamoxifen and irreversible binding to DNA. Carcinogenesis 23:1897-1901.
Borges S, Desta Z, Li L, Skaar TC, Ward BA, Nguyen A, Jin Y, Storniolo AM, Nikoloff DM, Wu L, Hillman G, Hayes DF, Stearns V and Flockhart DA (2006) Quantitative effect of CYP2D6 genotype and inhibitors on tamoxifen metabolism: implication for optimization of breast cancer treatment. Clin Pharmacol Ther 80:61-74.
101 Brandon EF, Raap CD, Meijerman I, Beijnen JH and Schellens JH (2003) An update on in vitro test methods in human hepatic drug biotransformation research: pros and cons. Toxicol Appl Pharmacol 189:233-246.
Brauch H and Jordan VC (2009) Targeting of tamoxifen to enhance antitumour action for the treatment and prevention of breast cancer: the 'personalised' approach? Eur J Cancer 45:2274- 2283.
Brown K (2009) Is tamoxifen a genotoxic carcinogen in women? Mutagenesis 24:391-404.
Buckley MM and Goa KL (1989) Tamoxifen. A reappraisal of its pharmacodynamic and pharmacokinetic properties, and therapeutic use. Drugs 37:451-490.
Burk O, Koch I, Raucy J, Hustert E, Eichelbaum M, Brockmoller J, Zanger UM and Wojnowski L (2004) The induction of cytochrome P450 3A5 (CYP3A5) in the human liver and intestine is mediated by the xenobiotic sensors pregnane X receptor (PXR) and constitutively activated receptor (CAR). J Biol Chem 279:38379-38385.
Burk O, Tegude H, Koch I, Hustert E, Wolbold R, Glaeser H, Klein K, Fromm MF, Nuessler AK, Neuhaus P, Zanger UM, Eichelbaum M and Wojnowski L (2002) Molecular mechanisms of polymorphic CYP3A7 expression in adult human liver and intestine. J Biol Chem 277:24280- 24288.
Carthew P, Edwards RE, Nolan BM, Martin EA, Heydon RT, White IN and Tucker MJ (2000) Tamoxifen induces endometrial and vaginal cancer in rats in the absence of endometrial hyperplasia. Carcinogenesis 21:793-797.
Cauffiez C, Lo-Guidice JM, Chevalier D, Allorge D, Hamdan R, Lhermitte M, Lafitte JJ, Colombel JF, Libersa C and Broly F (2004) First report of a genetic polymorphism of the cytochrome P450 3A43 (CYP3A43) gene: identification of a loss-of-function variant. Hum Mutat 23:101.
Chandel N, Aggarwal PK, Minz M, Sakhuja V, Kohli KK and Jha V (2009) CYP3A5*1/*3 genotype influences the blood concentration of tacrolimus in response to metabolic inhibition by ketoconazole. Pharmacogenet Genomics 19:458-463.
Chenhsu RY, Loong CC, Chou MH, Lin MF and Yang WC (2000) Renal allograft dysfunction associated with rifampin-tacrolimus interaction. Ann Pharmacother 34:27-31.
Coon MJ (2005) Cytochrome P450: nature's most versatile biological catalyst. Annu Rev Pharmacol Toxicol 45:1-25.
Cooper AJ (2003) Treatment of acne with isotretinoin: recommendations based on Australian experience. Australas J Dermatol 44:97-105.
Cooper CL, van Heeswijk RP, Gallicano K and Cameron DW (2003) A review of low-dose ritonavir in protease inhibitor combination therapy. Clin Infect Dis 36:1585-1592.
102 Cotreau MM, von Moltke LL, Harmatz JS and Greenblatt DJ (2001) Molecular and pharmacokinetic evaluation of rat hepatic and gastrointestinal cytochrome p450 induction by tamoxifen. Pharmacology 63:210-219.
Crettol S, Venetz JP, Fontana M, Aubert JD, Pascual M and Eap CB (2008) CYP3A7, CYP3A5, CYP3A4, and ABCB1 genetic polymorphisms, cyclosporine concentration, and dose requirement in transplant recipients. Ther Drug Monit 30:689-699.
Crewe HK, Ellis SW, Lennard MS and Tucker GT (1997) Variable contribution of cytochromes P450 2D6, 2C9 and 3A4 to the 4-hydroxylation of tamoxifen by human liver microsomes. Biochem Pharmacol 53:171-178.
Dai Y, Hebert MF, Isoherranen N, Davis CL, Marsh C, Shen DD and Thummel KE (2006) Effect of CYP3A5 polymorphism on tacrolimus metabolic clearance in vitro. Drug Metab Dispos 34:836-847.
Danan G, Descatoire V and Pessayre D (1981) Self-induction by erythromycin of its own transformation into a metabolite forming an inactive complex with reduced cytochrome P-450. J Pharmacol Exp Ther 218:509-514. de Wildt SN, Kearns GL, Leeder JS and van den Anker JN (1999) Glucuronidation in humans. Pharmacogenetic and developmental aspects. Clin Pharmacokinet 36:439-452.
Dennison JB, Jones DR, Renbarger JL and Hall SD (2007) Effect of CYP3A5 expression on vincristine metabolism with human liver microsomes. J Pharmacol Exp Ther 321:553-563.
Desai PB, Nallani SC, Sane RS, Moore LB, Goodwin BJ, Buckley DJ and Buckley AR (2002) Induction of cytochrome P450 3A4 in primary human hepatocytes and activation of the human pregnane X receptor by tamoxifen and 4-hydroxytamoxifen. Drug Metab Dispos 30:608-612.
Desta Z, Ward BA, Soukhova NV and Flockhart DA (2004) Comprehensive evaluation of tamoxifen sequential biotransformation by the human cytochrome P450 system in vitro: prominent roles for CYP3A and CYP2D6. J Pharmacol Exp Ther 310:1062-1075.
Dilger K, Hofmann U and Klotz U (2000) Enzyme induction in the elderly: effect of rifampin on the pharmacokinetics and pharmacodynamics of propafenone. Clin Pharmacol Ther 67:512-520.
Domanski TL, Finta C, Halpert JR and Zaphiropoulos PG (2001) cDNA cloning and initial characterization of CYP3A43, a novel human cytochrome P450. Mol Pharmacol 59:386-392.
Dowsett M, Cuzick J, Howell A and Jackson I (2001) Pharmacokinetics of anastrozole and tamoxifen alone, and in combination, during adjuvant endocrine therapy for early breast cancer in postmenopausal women: a sub-protocol of the 'Arimidex and tamoxifen alone or in combination' (ATAC) trial. Br J Cancer 85:317-324.
Dowsett M, Pfister C, Johnston SR, Miles DW, Houston SJ, Verbeek JA, Gundacker H, Sioufi A and Smith IE (1999) Impact of tamoxifen on the pharmacokinetics and endocrine effects of the
103 aromatase inhibitor letrozole in postmenopausal women with breast cancer. Clin Cancer Res 5:2338-2343.
Dresser GK, Schwarz UI, Wilkinson GR and Kim RB (2003) Coordinate induction of both cytochrome P4503A and MDR1 by St John's wort in healthy subjects. Clin Pharmacol Ther 73:41-50.
Dresser GK, Spence JD and Bailey DG (2000) Pharmacokinetic-pharmacodynamic consequences and clinical relevance of cytochrome P450 3A4 inhibition. Clin Pharmacokinet 38:41-57.
Duanmu Z, Locke D, Smigelski J, Wu W, Dahn MS, Falany CN, Kocarek TA and Runge-Morris M (2002) Effects of dexamethasone on aryl (SULT1A1)- and hydroxysteroid (SULT2A1)- sulfotransferase gene expression in primary cultured human hepatocytes. Drug Metab Dispos 30:997-1004.
Dussault I and Forman BM (2002) The nuclear receptor PXR: a master regulator of "homeland" defense. Crit Rev Eukaryot Gene Expr 12:53-64.
Ekhart C, Rodenhuis S, Beijnen JH and Huitema AD (2009) Pharmacokinetics of cyclophosphamide and thiotepa in a conventional fractionated high-dose regimen compared with a novel simplified unfractionated regimen. Ther Drug Monit 31:95-103.
Evans RW and Manninen DL (1988) Economic impact of cyclosporine in transplantation. Transplant Proc 20:49-62.
Evans WE and Relling MV (1999) Pharmacogenomics: translating functional genomics into rational therapeutics. Science 286:487-491.
Felici A, Verweij J and Sparreboom A (2002) Dosing strategies for anticancer drugs: the good, the bad and body-surface area. Eur J Cancer 38:1677-1684.
Felix CA, Walker AH, Lange BJ, Williams TM, Winick NJ, Cheung NK, Lovett BD, Nowell PC, Blair IA and Rebbeck TR (1998) Association of CYP3A4 genotype with treatment-related leukemia. Proc Natl Acad Sci U S A 95:13176-13181.
Ferraresso M, Tirelli A, Ghio L, Grillo P, Martina V, Torresani E and Edefonti A (2007) Influence of the CYP3A5 genotype on tacrolimus pharmacokinetics and pharmacodynamics in young kidney transplant recipients. Pediatr Transplant 11:296-300.
Fisher B, Costantino JP, Wickerham DL, Cecchini RS, Cronin WM, Robidoux A, Bevers TB, Kavanah MT, Atkins JN, Margolese RG, Runowicz CD, James JM, Ford LG and Wolmark N (2005b) Tamoxifen for the prevention of breast cancer: current status of the National Surgical Adjuvant Breast and Bowel Project P-1 study. J Natl Cancer Inst 97:1652-1662.
Fisher B, Costantino JP, Wickerham DL, Cecchini RS, Cronin WM, Robidoux A, Bevers TB, Kavanah MT, Atkins JN, Margolese RG, Runowicz CD, James JM, Ford LG and Wolmark N
104 (2005a) Tamoxifen for the prevention of breast cancer: current status of the National Surgical Adjuvant Breast and Bowel Project P-1 study. J Natl Cancer Inst 97:1652-1662.
Fromm MF, Dilger K, Busse D, Kroemer HK, Eichelbaum M and Klotz U (1998) Gut wall metabolism of verapamil in older people: effects of rifampicin-mediated enzyme induction. Br J Clin Pharmacol 45:247-255.
Fromson JM, Pearson S and Bramah S (1973) The metabolism of tamoxifen (I.C.I. 46,474). II. In female patients. Xenobiotica 3:711-714.
Frueh FW, Amur S, Mummaneni P, Epstein RS, Aubert RE, DeLuca TM, Verbrugge RR, Burckart GJ and Lesko LJ (2008) Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use. Pharmacotherapy 28:992-998.
Galetin A and Houston JB (2006) Intestinal and hepatic metabolic activity of five cytochrome P450 enzymes: impact on prediction of first-pass metabolism. J Pharmacol Exp Ther 318:1220- 1229.
Gant TW, O'Connor CK, Corbitt R, Thorgeirsson U and Thorgeirsson SS (1995) In vivo induction of liver P-glycoprotein expression by xenobiotics in monkeys. Toxicol Appl Pharmacol 133:269-276.
Gardner-Stephen D, Heydel JM, Goyal A, Lu Y, Xie W, Lindblom T, Mackenzie P and Radominska-Pandya A (2004) Human PXR variants and their differential effects on the regulation of human UDP-glucuronosyltransferase gene expression. Drug Metab Dispos 32:340- 347.
Ged C, Rouillon JM, Pichard L, Combalbert J, Bressot N, Bories P, Michel H, Beaune P and Maurel P (1989) The increase in urinary excretion of 6 beta-hydroxycortisol as a marker of human hepatic cytochrome P450IIIA induction. Br J Clin Pharmacol 28:373-387.
Gellner K, Eiselt R, Hustert E, Arnold H, Koch I, Haberl M, Deglmann CJ, Burk O, Buntefuss D, Escher S, Bishop C, Koebe HG, Brinkmann U, Klenk HP, Kleine K, Meyer UA and Wojnowski L (2001) Genomic organization of the human CYP3A locus: identification of a new, inducible CYP3A gene. Pharmacogenetics 11:111-121.
Gerbal-Chaloin S, Pascussi JM, Pichard-Garcia L, Daujat M, Waechter F, Fabre JM, Carrere N and Maurel P (2001) Induction of CYP2C genes in human hepatocytes in primary culture. Drug Metab Dispos 29:242-251.
Gillam EM, Guo Z, Ueng YF, Yamazaki H, Cock I, Reilly PE, Hooper WD and Guengerich FP (1995) Expression of cytochrome P450 3A5 in Escherichia coli: effects of 5' modification, purification, spectral characterization, reconstitution conditions, and catalytic activities. Arch Biochem Biophys 317:374-384.
105 Giorda G, Franceschi L, Crivellari D, Magri MD, Veronesi A, Scarabelli C and Furlanut M (2000) Determination of tamoxifen and its metabolites in the endometrial tissue of long-term treated women. Eur J Cancer 36 Suppl 4:S88-S89.
Goetz MP and Ingle J (2007) Early discontinuation of tamoxifen: a lesson for oncologists. Cancer 110:2595-2596.
Goetz MP, Kamal A and Ames MM (2008) Tamoxifen pharmacogenomics: the role of CYP2D6 as a predictor of drug response. Clin Pharmacol Ther 83:160-166.
Goetz MP, Rae JM, Suman VJ, Safgren SL, Ames MM, Visscher DW, Reynolds C, Couch FJ, Lingle WL, Flockhart DA, Desta Z, Perez EA and Ingle JN (2005) Pharmacogenetics of tamoxifen biotransformation is associated with clinical outcomes of efficacy and hot flashes. J Clin Oncol 23:9312-9318.
Gomez DY, Wacher VJ, Tomlanovich SJ, Hebert MF and Benet LZ (1995) The effects of ketoconazole on the intestinal metabolism and bioavailability of cyclosporine. Clin Pharmacol Ther 58:15-19.
Goodwin B, Moore LB, Stoltz CM, McKee DD and Kliewer SA (2001) Regulation of the human CYP2B6 gene by the nuclear pregnane X receptor. Mol Pharmacol 60:427-431.
Greuet J, Pichard L, Bonfils C, Domergue J and Maurel P (1996) The fetal specific gene CYP3A7 is inducible by rifampicin in adult human hepatocytes in primary culture. Biochem Biophys Res Commun 225:689-694.
Guelen PJ, Stevenson D, Briggs RJ and de VD (1987) The bioavailability of Tamoplex (tamoxifen). Part 2. A single dose cross-over study in healthy male volunteers. Methods Find Exp Clin Pharmacol 9:685-690.
Guengerich FP (2006) Cytochrome P450s and other enzymes in drug metabolism and toxicity. AAPS J 8:E101-E111.
Hall SD, Wang Z, Huang SM, Hamman MA, Vasavada N, Adigun AQ, Hilligoss JK, Miller M and Gorski JC (2003) The interaction between St John's wort and an oral contraceptive. Clin Pharmacol Ther 74:525-535.
Hariparsad N, Nallani SC, Sane RS, Buckley DJ, Buckley AR and Desai PB (2004) Induction of CYP3A4 by efavirenz in primary human hepatocytes: comparison with rifampin and phenobarbital. J Clin Pharmacol 44:1273-1281.
He P, Court MH, Greenblatt DJ and von Moltke LL (2005) Genotype-phenotype associations of cytochrome P450 3A4 and 3A5 polymorphism with midazolam clearance in vivo. Clin Pharmacol Ther 77:373-387.
Healan-Greenberg C, Waring JF, Kempf DJ, Blomme EA, Tirona RG and Kim RB (2008) A human immunodeficiency virus protease inhibitor is a novel functional inhibitor of human pregnane X receptor. Drug Metab Dispos 36:500-507.
106 Hebert MF, Fisher RM, Marsh CL, Dressler D and Bekersky I (1999) Effects of rifampin on tacrolimus pharmacokinetics in healthy volunteers. J Clin Pharmacol 39:91-96.
Hebert MF, Roberts JP, Prueksaritanont T and Benet LZ (1992) Bioavailability of cyclosporine with concomitant rifampin administration is markedly less than predicted by hepatic enzyme induction. Clin Pharmacol Ther 52:453-457.
Heimark LD, Gibaldi M, Trager WF, O'Reilly RA and Goulart DA (1987) The mechanism of the warfarin-rifampin drug interaction in humans. Clin Pharmacol Ther 42:388-394.
Hellriegel ET, Matwyshyn GA, Fei P, Dragnev KH, Nims RW, Lubet RA and Kong AN (1996) Regulation of gene expression of various phase I and phase II drug-metabolizing enzymes by tamoxifen in rat liver. Biochem Pharmacol 52:1561-1568.
Hemminki K, Rajaniemi H, Lindahl B and Moberger B (1996) Tamoxifen-induced DNA adducts in endometrial samples from breast cancer patients. Cancer Res 56:4374-4377.
Herrlinger C, Braunfels M, Fink E, Kinzig M, Metz R, Sorgel F and Vergin H (1992) Pharmacokinetics and bioavailability of tamoxifen in healthy volunteers. Int J Clin Pharmacol Ther Toxicol 30:487-489.
Hines RN (2007) Ontogeny of human hepatic cytochromes P450. J Biochem Mol Toxicol 21:169-175.
Honig PK, Wortham DC, Zamani K, Conner DP, Mullin JC and Cantilena LR (1993) Terfenadine-ketoconazole interaction. Pharmacokinetic and electrocardiographic consequences. JAMA 269:1513-1518.
Huang RS and Ratain MJ (2009) Pharmacogenetics and pharmacogenomics of anticancer agents. CA Cancer J Clin 59:42-55.
Huang W, Lin YS, McConn DJ, Calamia JC, Totah RA, Isoherranen N, Glodowski M and Thummel KE (2004) Evidence of significant contribution from CYP3A5 to hepatic drug metabolism. Drug Metab Dispos 32:1434-1445.
Hukkanen J, Mantyla M, Kangas L, Wirta P, Hakkola J, Paakki P, Evisalmi S, Pelkonen O and Raunio H (1998) Expression of cytochrome P450 genes encoding enzymes active in the metabolism of tamoxifen in human uterine endometrium. Pharmacol Toxicol 82:93-97.
Hustert E, Haberl M, Burk O, Wolbold R, He YQ, Klein K, Nuessler AC, Neuhaus P, Klattig J, Eiselt R, Koch I, Zibat A, Brockmoller J, Halpert JR, Zanger UM and Wojnowski L (2001a) The genetic determinants of the CYP3A5 polymorphism. Pharmacogenetics 11:773-779.
Hustert E, Zibat A, Presecan-Siedel E, Eiselt R, Mueller R, Fuss C, Brehm I, Brinkmann U, Eichelbaum M, Wojnowski L and Burk O (2001b) Natural protein variants of pregnane X receptor with altered transactivation activity toward CYP3A4. Drug Metab Dispos 29:1454- 1459.
107 Imai H, Kotegawa T, Tsutsumi K, Morimoto T, Eshima N, Nakano S and Ohashi K (2008) The recovery time-course of CYP3A after induction by St John's wort administration. Br J Clin Pharmacol 65:701-707.
Innocenti F and Ratain MJ (2002) Update on pharmacogenetics in cancer chemotherapy. Eur J Cancer 38:639-644.
Jimenez-Lara AM, Clarke N, Altucci L and Gronemeyer H (2004) Retinoic-acid-induced apoptosis in leukemia cells. Trends Mol Med 10:508-515.
Jin Y, Desta Z, Stearns V, Ward B, Ho H, Lee KH, Skaar T, Storniolo AM, Li L, Araba A, Blanchard R, Nguyen A, Ullmer L, Hayden J, Lemler S, Weinshilboum RM, Rae JM, Hayes DF and Flockhart DA (2005) CYP2D6 genotype, antidepressant use, and tamoxifen metabolism during adjuvant breast cancer treatment. J Natl Cancer Inst 97:30-39.
Jordan VC (1982) Metabolites of tamoxifen in animals and man: identification, pharmacology, and significance. Breast Cancer Res Treat 2:123-138.
Jordan VC (2000) Antiestrogens: clinical applications of pharmacology. J Soc Gynecol Investig 7:S47-S48.
Jordan VC (2003a) Tamoxifen: a most unlikely pioneering medicine. Nat Rev Drug Discov 2:205-213.
Jordan VC (2003b) Tamoxifen: a most unlikely pioneering medicine. Nat Rev Drug Discov 2:205-213.
Jordan VC and Morrow M (1994) Should clinicians be concerned about the carcinogenic potential of tamoxifen? Eur J Cancer 30A:1714-1721.
Kamdem LK, Meineke I, Koch I, Zanger UM, Brockmoller J and Wojnowski L (2004) Limited contribution of CYP3A5 to the hepatic 6beta-hydroxylation of testosterone. Naunyn Schmiedebergs Arch Pharmacol 370:71-77.
Keogh A, Spratt P, McCosker C, Macdonald P, Mundy J and Kaan A (1995) Ketoconazole to reduce the need for cyclosporine after cardiac transplantation. N Engl J Med 333:628-633.
Kim RB, Wandel C, Leake B, Cvetkovic M, Fromm MF, Dempsey PJ, Roden MM, Belas F, Chaudhary AK, Roden DM, Wood AJ and Wilkinson GR (1999) Interrelationship between substrates and inhibitors of human CYP3A and P-glycoprotein. Pharm Res 16:408-414.
Kim SY, Laxmi YR, Suzuki N, Ogura K, Watabe T, Duffel MW and Shibutani S (2005) Formation of tamoxifen-DNA adducts via O-sulfonation, not O-acetylation, of alpha- hydroxytamoxifen in rat and human livers. Drug Metab Dispos 33:1673-1678.
King CR, Xiao M, Yu J, Minton MR, Addleman NJ, Van Booven DJ, Kwok PY, McLeod HL and Marsh S (2007) Identification of NR1I2 genetic variation using resequencing. Eur J Clin Pharmacol 63:547-554.
108 Kisanga ER, Gjerde J, Guerrieri-Gonzaga A, Pigatto F, Pesci-Feltri A, Robertson C, Serrano D, Pelosi G, Decensi A and Lien EA (2004) Tamoxifen and metabolite concentrations in serum and breast cancer tissue during three dose regimens in a randomized preoperative trial. Clin Cancer Res 10:2336-2343.
Kivisto KT, Villikka K, Nyman L, Anttila M and Neuvonen PJ (1998) Tamoxifen and toremifene concentrations in plasma are greatly decreased by rifampin. Clin Pharmacol Ther 64:648-654.
Klees TM, Sheffels P, Thummel KE and Kharasch ED (2005) Pharmacogenetic determinants of human liver microsomal alfentanil metabolism and the role of cytochrome P450 3A5. Anesthesiology 102:550-556.
Klein-Hitpass L, Tsai SY, Greene GL, Clark JH, Tsai MJ and O'Malley BW (1989) Specific binding of estrogen receptor to the estrogen response element. Mol Cell Biol 9:43-49.
Kliewer SA, Goodwin B and Willson TM (2002b) The nuclear pregnane X receptor: a key regulator of xenobiotic metabolism. Endocr Rev 23:687-702.
Kliewer SA, Goodwin B and Willson TM (2002a) The nuclear pregnane X receptor: a key regulator of xenobiotic metabolism. Endocr Rev 23:687-702.
Kliewer SA, Moore JT, Wade L, Staudinger JL, Watson MA, Jones SA, McKee DD, Oliver BB, Willson TM, Zetterstrom RH, Perlmann T and Lehmann JM (1998) An orphan nuclear receptor activated by pregnanes defines a novel steroid signaling pathway. Cell 92:73-82.
Kolars JC, Awni WM, Merion RM and Watkins PB (1991) First-pass metabolism of cyclosporin by the gut. Lancet 338:1488-1490.
Kolars JC, Schmiedlin-Ren P, Schuetz JD, Fang C and Watkins PB (1992) Identification of rifampin-inducible P450IIIA4 (CYP3A4) in human small bowel enterocytes. J Clin Invest 90:1871-1878.
Koyano S, Kurose K, Ozawa S, Saeki M, Nakajima Y, Hasegawa R, Komamura K, Ueno K, Kamakura S, Nakajima T, Saito H, Kimura H, Goto Y, Saitoh O, Katoh M, Ohnuma T, Kawai M, Sugai K, Ohtsuki T, Suzuki C, Minami N, Saito Y and Sawada J (2002) Eleven novel single nucleotide polymorphisms in the NR1I2 (PXR) gene, four of which induce non-synonymous amino acid alterations. Drug Metab Pharmacokinet 17:561-565.
Koyano S, Kurose K, Saito Y, Ozawa S, Hasegawa R, Komamura K, Ueno K, Kamakura S, Kitakaze M, Nakajima T, Matsumoto K, Akasawa A, Saito H and Sawada J (2004) Functional characterization of four naturally occurring variants of human pregnane X receptor (PXR): one variant causes dramatic loss of both DNA binding activity and the transactivation of the CYP3A4 promoter/enhancer region. Drug Metab Dispos 32:149-154.
Kristensen B, Ejlertsen B, Dalgaard P, Larsen L, Holmegaard SN, Transbol I and Mouridsen HT (1994) Tamoxifen and bone metabolism in postmenopausal low-risk breast cancer patients: a randomized study. J Clin Oncol 12:992-997.
109 Ku HY, Ahn HJ, Seo KA, Kim H, Oh M, Bae SK, Shin JG, Shon JH and Liu KH (2008) The contributions of cytochromes P450 3A4 and 3A5 to the metabolism of the phosphodiesterase type 5 inhibitors sildenafil, udenafil, and vardenafil. Drug Metab Dispos 36:986-990.
Kuehl P, Zhang J, Lin Y, Lamba J, Assem M, Schuetz J, Watkins PB, Daly A, Wrighton SA, Hall SD, Maurel P, Relling M, Brimer C, Yasuda K, Venkataramanan R, Strom S, Thummel K, Boguski MS and Schuetz E (2001) Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression. Nat Genet 27:383-391.
Kupferschmidt HH, Ha HR, Ziegler WH, Meier PJ and Krahenbuhl S (1995) Interaction between grapefruit juice and midazolam in humans. Clin Pharmacol Ther 58:20-28.
Lamba J, Lamba V, Strom S, Venkataramanan R and Schuetz E (2008) Novel single nucleotide polymorphisms in the promoter and intron 1 of human pregnane X receptor/NR1I2 and their association with CYP3A4 expression. Drug Metab Dispos 36:169-181.
Lamba JK, Lin YS, Schuetz EG and Thummel KE (2002) Genetic contribution to variable human CYP3A-mediated metabolism. Adv Drug Deliv Rev 54:1271-1294.
Lasser KE, Allen PD, Woolhandler SJ, Himmelstein DU, Wolfe SM and Bor DH (2002) Timing of new black box warnings and withdrawals for prescription medications. JAMA 287:2215-2220.
Lee SJ, Usmani KA, Chanas B, Ghanayem B, Xi T, Hodgson E, Mohrenweiser HW and Goldstein JA (2003) Genetic findings and functional studies of human CYP3A5 single nucleotide polymorphisms in different ethnic groups. Pharmacogenetics 13:461-472.
Lessard E, Yessine MA, Hamelin BA, O'Hara G, LeBlanc J and Turgeon J (1999) Influence of CYP2D6 activity on the disposition and cardiovascular toxicity of the antidepressant agent venlafaxine in humans. Pharmacogenetics 9:435-443.
Li AP, Kaminski DL and Rasmussen A (1995) Substrates of human hepatic cytochrome P450 3A4. Toxicology 104:1-8.
Lien EA, Wester K, Lonning PE, Solheim E and Ueland PM (1991) Distribution of tamoxifen and metabolites into brain tissue and brain metastases in breast cancer patients. Br J Cancer 63:641-645.
Ligibel JA and Winer EP (2005) Aromatase inhibitors as adjuvant therapy for postmenopausal women: a therapeutic advance but many unresolved questions. Breast Cancer Res 7:255-257.
Lin JH (2006) CYP induction-mediated drug interactions: in vitro assessment and clinical implications. Pharm Res 23:1089-1116.
Lin JH, Chen IW, Chiba M, Nishime JA and Deluna FA (2000) Route-dependent nonlinear pharmacokinetics of a novel HIV protease inhibitor: involvement of enzyme inactivation. Drug Metab Dispos 28:460-466.
110 Lin JH and Lu AY (1998) Inhibition and induction of cytochrome P450 and the clinical implications. Clin Pharmacokinet 35:361-390.
Lin JH and Lu AY (2001) Interindividual variability in inhibition and induction of cytochrome P450 enzymes. Annu Rev Pharmacol Toxicol 41:535-567.
Link E, Parish S, Armitage J, Bowman L, Heath S, Matsuda F, Gut I, Lathrop M and Collins R (2008) SLCO1B1 variants and statin-induced myopathy--a genomewide study. N Engl J Med 359:789-799.
Liu YT, Hao HP, Liu CX, Wang GJ and Xie HG (2007) Drugs as CYP3A probes, inducers, and inhibitors. Drug Metab Rev 39:699-721.
Lonning PE, Lien EA, Lundgren S and Kvinnsland S (1992) Clinical pharmacokinetics of endocrine agents used in advanced breast cancer. Clin Pharmacokinet 22:327-358.
Madsen JK, Jensen JD, Jensen LW and Pedersen EB (1996) Pharmacokinetic interaction between cyclosporine and the dihydropyridine calcium antagonist felodipine. Eur J Clin Pharmacol 50:203-208.
Marill J, Capron CC, Idres N and Chabot GG (2002) Human cytochrome P450s involved in the metabolism of 9-cis- and 13-cis-retinoic acids 2. Biochem Pharmacol 63:933-943.
Martin EA, Brown K, Gaskell M, Al-Azzawi F, Garner RC, Boocock DJ, Mattock E, Pring DW, Dingley K, Turteltaub KW, Smith LL and White IN (2003) Tamoxifen DNA damage detected in human endometrium using accelerator mass spectrometry. Cancer Res 63:8461-8465.
Martin JE, Daoud AJ, Schroeder TJ and First MR (1999) The clinical and economic potential of cyclosporin drug interactions. Pharmacoeconomics 15:317-337.
Masuyama H, Hiramatsu Y, Kodama J and Kudo T (2003) Expression and potential roles of pregnane X receptor in endometrial cancer. J Clin Endocrinol Metab 88:4446-4454.
Masuyama H, Nakatsukasa H, Takamoto N and Hiramatsu Y (2007) Down-regulation of pregnane X receptor contributes to cell growth inhibition and apoptosis by anticancer agents in endometrial cancer cells. Mol Pharmacol 72:1045-1053.
Mathijssen RH, de Jong FA, Loos WJ, van der Bol JM, Verweij J and Sparreboom A (2007) Flat-fixed dosing versus body surface area based dosing of anticancer drugs in adults: does it make a difference? Oncologist 12:913-923.
McDonnell DP and Norris JD (2002) Connections and regulation of the human estrogen receptor. Science 296:1642-1644.
Merry C, Barry MG, Mulcahy F, Ryan M, Heavey J, Tjia JF, Gibbons SE, Breckenridge AM and Back DJ (1997) Saquinavir pharmacokinetics alone and in combination with ritonavir in HIV- infected patients. AIDS 11:F29-F33.
111 Merry C, Barry MG, Mulcahy F, Tjia JF, Halifax KL, Heavey J, Kelly C and Back DJ (1998) Ritonavir pharmacokinetics alone and in combination with saquinavir in HIV-infected patients. AIDS 12:325-327.
Min DI and Ellingrod VL (2003) Association of the CYP3A4*1B 5'-flanking region polymorphism with cyclosporine pharmacokinetics in healthy subjects. Ther Drug Monit 25:305- 309.
Modry DL, Stinson EB, Oyer PE, Jamieson SW, Baldwin JC and Shumway NE (1985) Acute rejection and massive cyclosporine requirements in heart transplant recipients treated with rifampin. Transplantation 39:313-314.
Morello KC, Wurz GT and DeGregorio MW (2003) Pharmacokinetics of selective estrogen receptor modulators. Clin Pharmacokinet 42:361-372.
Mouly SJ, Matheny C, Paine MF, Smith G, Lamba J, Lamba V, Pusek SN, Schuetz EG, Stewart PW and Watkins PB (2005) Variation in oral clearance of saquinavir is predicted by CYP3A5*1 genotype but not by enterocyte content of cytochrome P450 3A5. Clin Pharmacol Ther 78:605- 618.
Murayama N, Nakamura T, Saeki M, Soyama A, Saito Y, Sai K, Ishida S, Nakajima O, Itoda M, Ohno Y, Ozawa S and Sawada J (2002) CYP3A4 gene polymorphisms influence testosterone 6beta-hydroxylation. Drug Metab Pharmacokinet 17:150-156.
Murray M (1997) Drug-mediated inactivation of cytochrome P450. Clin Exp Pharmacol Physiol 24:465-470.
Nallani SC, Genter MB and Desai PB (2001) Increased activity of CYP3A enzyme in primary cultures of rat hepatocytes treated with docetaxel: comparative evaluation with paclitaxel. Cancer Chemother Pharmacol 48:115-122.
Neuvonen PJ and Suhonen R (1995) Itraconazole interacts with felodipine. J Am Acad Dermatol 33:134-135.
Niemi M, Backman JT, Fromm MF, Neuvonen PJ and Kivisto KT (2003) Pharmacokinetic interactions with rifampicin : clinical relevance. Clin Pharmacokinet 42:819-850.
Niles RM (2004) Signaling pathways in retinoid chemoprevention and treatment of cancer. Mutat Res 555:81-96.
Nishiyama T, Ogura K, Nakano H, Ohnuma T, Kaku T, Hiratsuka A, Muro K and Watabe T (2002) Reverse geometrical selectivity in glucuronidation and sulfation of cis- and trans-4- hydroxytamoxifens by human liver UDP-glucuronosyltransferases and sulfotransferases. Biochem Pharmacol 63:1817-1830.
Notley LM, Crewe KH, Taylor PJ, Lennard MS and Gillam EM (2005) Characterization of the human cytochrome P450 forms involved in metabolism of tamoxifen to its alpha-hydroxy and alpha,4-dihydroxy derivatives. Chem Res Toxicol 18:1611-1618.
112 Nuwaysir EF, Daggett DA, Jordan VC and Pitot HC (1996) Phase II enzyme expression in rat liver in response to the antiestrogen tamoxifen. Cancer Res 56:3704-3710.
Nuwaysir EF, Dragan YP, Jefcoate CR, Jordan VC and Pitot HC (1995) Effects of tamoxifen administration on the expression of xenobiotic metabolizing enzymes in rat liver. Cancer Res 55:1780-1786.
Nuwaysir EF, Dragan YP, McCague R, Martin P, Mann J, Jordan VC and Pitot HC (1998) Structure-activity relationships for triphenylethylene antiestrogens on hepatic phase-I and phase- II enzyme expression. Biochem Pharmacol 56:321-327.
Ogura K, Ishikawa Y, Kaku T, Nishiyama T, Ohnuma T, Muro K and Hiratsuka A (2006) Quaternary ammonium-linked glucuronidation of trans-4-hydroxytamoxifen, an active metabolite of tamoxifen, by human liver microsomes and UDP-glucuronosyltransferase 1A4. Biochem Pharmacol 71:1358-1369.
Olkkola KT, Aranko K, Luurila H, Hiller A, Saarnivaara L, Himberg JJ and Neuvonen PJ (1993) A potentially hazardous interaction between erythromycin and midazolam. Clin Pharmacol Ther 53:298-305.
Ortiz de Montellano PR (1995) The 1994 Bernard B. Brodie Award Lecture. Structure, mechanism, and inhibition of cytochrome P450. Drug Metab Dispos 23:1181-1187.
Orton TC and Topham JC (1997) Correspondence re: K. Hemminki et al., Tamoxifen-induced DNA adducts in endometrial samples from breast cancer patients. Cancer Res., 56: 4374-4377, 1996. Cancer Res 57:4148.
Osborne CK (1998) Tamoxifen in the treatment of breast cancer. N Engl J Med 339:1609-1618.
Oseni T, Patel R, Pyle J and Jordan VC (2008) Selective estrogen receptor modulators and phytoestrogens. Planta Med 74:1656-1665.
Ozdemir M, Aktan Y, Boydag BS, Cingi MI and Musmul A (1998) Interaction between grapefruit juice and diazepam in humans. Eur J Drug Metab Pharmacokinet 23:55-59.
Paine MF, Hart HL, Ludington SS, Haining RL, Rettie AE and Zeldin DC (2006) The human intestinal cytochrome P450 "pie". Drug Metab Dispos 34:880-886.
Paine MF, Khalighi M, Fisher JM, Shen DD, Kunze KL, Marsh CL, Perkins JD and Thummel KE (1997) Characterization of interintestinal and intraintestinal variations in human CYP3A- dependent metabolism. J Pharmacol Exp Ther 283:1552-1562.
Perez EA (2007) Safety profiles of tamoxifen and the aromatase inhibitors in adjuvant therapy of hormone-responsive early breast cancer. Ann Oncol 18 Suppl 8:viii26-viii35.
Plant N (2007) The human cytochrome P450 sub-family: transcriptional regulation, inter- individual variation and interaction networks. Biochim Biophys Acta 1770:478-488.
113 Polasek TM and Miners JO (2006) Quantitative prediction of macrolide drug-drug interaction potential from in vitro studies using testosterone as the human cytochrome P4503A substrate. Eur J Clin Pharmacol 62:203-208.
Poon GK, Chui YC, McCague R, Llnning PE, Feng R, Rowlands MG and Jarman M (1993) Analysis of phase I and phase II metabolites of tamoxifen in breast cancer patients. Drug Metab Dispos 21:1119-1124.
Rebbeck TR, Jaffe JM, Walker AH, Wein AJ and Malkowicz SB (1998) Modification of clinical presentation of prostate tumors by a novel genetic variant in CYP3A4. J Natl Cancer Inst 90:1225-1229.
Reddy P and Chow MS (2000) Safety and efficacy of antiestrogens for prevention of breast cancer. Am J Health Syst Pharm 57:1315-1322.
Riley J, Styles J, Verschoyle RD, Stanley LA, White IN and Gant TW (2000) Association of tamoxifen biliary excretion rate with prior tamoxifen exposure and increased mdr1b expression. Biochem Pharmacol 60:233-239.
Riva R, Albani F, Contin M and Baruzzi A (1996) Pharmacokinetic interactions between antiepileptic drugs. Clinical considerations. Clin Pharmacokinet 31:470-493.
Rodriguez-Antona C, Donato MT, Boobis A, Edwards RJ, Watts PS, Castell JV and Gomez- Lechon MJ (2002) Cytochrome P450 expression in human hepatocytes and hepatoma cell lines: molecular mechanisms that determine lower expression in cultured cells. Xenobiotica 32:505- 520.
Rodriguez-Antona C, Sayi JG, Gustafsson LL, Bertilsson L and Ingelman-Sundberg M (2005) Phenotype-genotype variability in the human CYP3A locus as assessed by the probe drug quinine and analyses of variant CYP3A4 alleles. Biochem Biophys Res Commun 338:299-305.
Roy JN, Lajoie J, Zijenah LS, Barama A, Poirier C, Ward BJ and Roger M (2005) CYP3A5 genetic polymorphisms in different ethnic populations. Drug Metab Dispos 33:884-887.
Sane RS, Buckley DJ, Buckley AR, Nallani SC and Desai PB (2008) Role of human pregnane X receptor in tamoxifen- and 4-hydroxytamoxifen-mediated CYP3A4 induction in primary human hepatocytes and LS174T cells. Drug Metab Dispos 36:946-954.
Schuetz JD, Beach DL and Guzelian PS (1994) Selective expression of cytochrome P450 CYP3A mRNAs in embryonic and adult human liver. Pharmacogenetics 4:11-20.
Seeff LB, Cuccherini BA, Zimmerman HJ, Adler E and Benjamin SB (1986) Acetaminophen hepatotoxicity in alcoholics. A therapeutic misadventure. Ann Intern Med 104:399-404.
Sharma M, Shubert DE, Sharma M, Lewis J, McGarrigle BP, Bofinger DP and Olson JR (2003) Biotransformation of tamoxifen in a human endometrial explant culture model. Chem Biol Interact 146:237-249.
114 Shibutani S, Dasaradhi L, Terashima I, Banoglu E and Duffel MW (1998) Alpha- hydroxytamoxifen is a substrate of hydroxysteroid (alcohol) sulfotransferase, resulting in tamoxifen DNA adducts. Cancer Res 58:647-653.
Shibutani S, Ravindernath A, Suzuki N, Terashima I, Sugarman SM, Grollman AP and Pearl ML (2000) Identification of tamoxifen-DNA adducts in the endometrium of women treated with tamoxifen. Carcinogenesis 21:1461-1467.
Shibutani S, Suzuki N, Laxmi YR, Schild LJ, Divi RL, Grollman AP and Poirier MC (2003) Identification of tamoxifen-DNA adducts in monkeys treated with tamoxifen. Cancer Res 63:4402-4406.
Shimada T, Yamazaki H, Mimura M, Inui Y and Guengerich FP (1994) Interindividual variations in human liver cytochrome P-450 enzymes involved in the oxidation of drugs, carcinogens and toxic chemicals: studies with liver microsomes of 30 Japanese and 30 Caucasians 5. J Pharmacol Exp Ther 270:414-423.
Siccardi M, D'Avolio A, Baietto L, Gibbons S, Sciandra M, Colucci D, Bonora S, Khoo S, Back DJ, Di PG and Owen A (2008) Association of a single-nucleotide polymorphism in the pregnane X receptor (PXR 63396C-->T) with reduced concentrations of unboosted atazanavir. Clin Infect Dis 47:1222-1225.
Sim SC, Edwards RJ, Boobis AR and Ingelman-Sundberg M (2005) CYP3A7 protein expression is high in a fraction of adult human livers and partially associated with the CYP3A7*1C allele. Pharmacogenet Genomics 15:625-631.
Smith DA (2000) Induction and drug development. Eur J Pharm Sci 11:185-189.
Spatzenegger M and Jaeger W (1995) Clinical importance of hepatic cytochrome P450 in drug metabolism. Drug Metab Rev 27:397-417.
Spurdle AB, Goodwin B, Hodgson E, Hopper JL, Chen X, Purdie DM, McCredie MR, Giles GG, Chenevix-Trench G and Liddle C (2002) The CYP3A4*1B polymorphism has no functional significance and is not associated with risk of breast or ovarian cancer. Pharmacogenetics 12:355-366.
Stearns V, Johnson MD, Rae JM, Morocho A, Novielli A, Bhargava P, Hayes DF, Desta Z and Flockhart DA (2003) Active tamoxifen metabolite plasma concentrations after coadministration of tamoxifen and the selective serotonin reuptake inhibitor paroxetine. J Natl Cancer Inst 95:1758-1764.
Stone A, Ratnasinghe LD, Emerson GL, Modali R, Lehman T, Runnells G, Carroll A, Carter W, Barnhart S, Rasheed AA, Greene G, Johnson DE, Ambrosone CB, Kadlubar FF and Lang NP (2005) CYP3A43 Pro(340)Ala polymorphism and prostate cancer risk in African Americans and Caucasians. Cancer Epidemiol Biomarkers Prev 14:1257-1261.
115 Streetman DS, Bertino JS, Jr. and Nafziger AN (2000) Phenotyping of drug-metabolizing enzymes in adults: a review of in-vivo cytochrome P450 phenotyping probes. Pharmacogenetics 10:187-216.
Sun D, Chen G, Dellinger RW, Duncan K, Fang JL and Lazarus P (2006) Characterization of tamoxifen and 4-hydroxytamoxifen glucuronidation by human UGT1A4 variants. Breast Cancer Res 8:R50.
Synold TW, Dussault I and Forman BM (2001) The orphan nuclear receptor SXR coordinately regulates drug metabolism and efflux. Nat Med 7:584-590.
Tang C, Lin JH and Lu AY (2005) Metabolism-based drug-drug interactions: what determines individual variability in cytochrome P450 induction? 9. Drug Metab Dispos 33:603-613.
Thummel KE, Shen DD, Podoll TD, Kunze KL, Trager WF, Bacchi CE, Marsh CL, McVicar JP, Barr DM, Perkins JD and . (1994a) Use of midazolam as a human cytochrome P450 3A probe: II. Characterization of inter- and intraindividual hepatic CYP3A variability after liver transplantation. J Pharmacol Exp Ther 271:557-566.
Thummel KE, Shen DD, Podoll TD, Kunze KL, Trager WF, Hartwell PS, Raisys VA, Marsh CL, McVicar JP, Barr DM and . (1994b) Use of midazolam as a human cytochrome P450 3A probe: I. In vitro-in vivo correlations in liver transplant patients. J Pharmacol Exp Ther 271:549- 556.
Thummel KE and Wilkinson GR (1998) In vitro and in vivo drug interactions involving human CYP3A. Annu Rev Pharmacol Toxicol 38:389-430.
Tirelli S, Ferraresso M, Ghio L, Meregalli E, Martina V, Belingheri M, Mattiello C, Torresani E and Edefonti A (2008) The effect of CYP3A5 polymorphisms on the pharmacokinetics of tacrolimus in adolescent kidney transplant recipients. Med Sci Monit 14:CR251-CR254.
Tran A, Jullien V, Alexandre J, Rey E, Rabillon F, Girre V, Dieras V, Pons G, Goldwasser F and Treluyer JM (2006) Pharmacokinetics and toxicity of docetaxel: role of CYP3A, MDR1, and GST polymorphisms. Clin Pharmacol Ther 79:570-580.
Tran JQ, Kovacs SJ, McIntosh TS, Davis HM and Martin DE (1999) Morning spot and 24-hour urinary 6 beta-hydroxycortisol to cortisol ratios: intraindividual variability and correlation under basal conditions and conditions of CYP 3A4 induction. J Clin Pharmacol 39:487-494.
Tucker AN, Tkaczuk KA, Lewis LM, Tomic D, Lim CK and Flaws JA (2005) Polymorphisms in cytochrome P4503A5 (CYP3A5) may be associated with race and tumor characteristics, but not metabolism and side effects of tamoxifen in breast cancer patients. Cancer Lett 217:61-72.
Tukker JJ, Blankenstein MA and Nortier JW (1986) Comparison of bioavailability in man of tamoxifen after oral and rectal administration. J Pharm Pharmacol 38:888-892.
116 Vanden BH, Koymans L and Moereels H (1995) P450 inhibitors of use in medical treatment: focus on mechanisms of action. Pharmacol Ther 67:79-100.
Visvanathan K, Chlebowski RT, Hurley P, Col NF, Ropka M, Collyar D, Morrow M, Runowicz C, Pritchard KI, Hagerty K, Arun B, Garber J, Vogel VG, Wade JL, Brown P, Cuzick J, Kramer BS and Lippman SM (2009) American society of clinical oncology clinical practice guideline update on the use of pharmacologic interventions including tamoxifen, raloxifene, and aromatase inhibition for breast cancer risk reduction. J Clin Oncol 27:3235-3258.
Vizirianakis IS (2007) Clinical translation of genotyping and haplotyping data: implementation of in vivo pharmacology experience leading drug prescription to pharmacotyping. Clin Pharmacokinet 46:807-824.
Wang H, Huang H, Li H, Teotico DG, Sinz M, Baker SD, Staudinger J, Kalpana G, Redinbo MR and Mani S (2007) Activated pregnenolone X-receptor is a target for ketoconazole and its analogs. Clin Cancer Res 13:2488-2495.
Wang YH, Jones DR and Hall SD (2005) Differential mechanism-based inhibition of CYP3A4 and CYP3A5 by verapamil. Drug Metab Dispos 33:664-671.
Wang Z, Gorski JC, Hamman MA, Huang SM, Lesko LJ and Hall SD (2001) The effects of St John's wort (Hypericum perforatum) on human cytochrome P450 activity. Clin Pharmacol Ther 70:317-326.
Watkins PB, Wrighton SA, Schuetz EG, Maurel P and Guzelian PS (1986) Macrolide antibiotics inhibit the degradation of the glucocorticoid-responsive cytochrome P-450p in rat hepatocytes in vivo and in primary monolayer culture. J Biol Chem 261:6264-6271.
Wegman P, Elingarami S, Carstensen J, Stal O, Nordenskjold B and Wingren S (2007) Genetic variants of CYP3A5, CYP2D6, SULT1A1, UGT2B15 and tamoxifen response in postmenopausal patients with breast cancer. Breast Cancer Res 9:R7.
Westlind A, Malmebo S, Johansson I, Otter C, Andersson TB, Ingelman-Sundberg M and Oscarson M (2001a) Cloning and tissue distribution of a novel human cytochrome p450 of the CYP3A subfamily, CYP3A43. Biochem Biophys Res Commun 281:1349-1355.
Westlind A, Malmebo S, Johansson I, Otter C, Andersson TB, Ingelman-Sundberg M and Oscarson M (2001b) Cloning and tissue distribution of a novel human cytochrome p450 of the CYP3A subfamily, CYP3A43. Biochem Biophys Res Commun 281:1349-1355.
Westlind-Johnsson A, Hermann R, Huennemeyer A, Hauns B, Lahu G, Nassr N, Zech K, Ingelman-Sundberg M and von RO (2006a) Identification and characterization of CYP3A4*20, a novel rare CYP3A4 allele without functional activity. Clin Pharmacol Ther 79:339-349.
Westlind-Johnsson A, Hermann R, Huennemeyer A, Hauns B, Lahu G, Nassr N, Zech K, Ingelman-Sundberg M and von RO (2006b) Identification and characterization of CYP3A4*20, a novel rare CYP3A4 allele without functional activity. Clin Pharmacol Ther 79:339-349.
117 White IN (1999) The tamoxifen dilemma. Carcinogenesis 20:1153-1160.
White IN, Davies A, Smith LL, Dawson S and De MF (1993) Induction of CYP2B1 and 3A1, and associated monoxygenase activities by tamoxifen and certain analogues in the livers of female rats and mice. Biochem Pharmacol 45:21-30.
Williams JA, Ring BJ, Cantrell VE, Jones DR, Eckstein J, Ruterbories K, Hamman MA, Hall SD and Wrighton SA (2002) Comparative metabolic capabilities of CYP3A4, CYP3A5, and CYP3A7. Drug Metab Dispos 30:883-891.
Willson TM and Kliewer SA (2002) PXR, CAR and drug metabolism. Nat Rev Drug Discov 1:259-266.
Wojnowski L (2004) Genetics of the variable expression of CYP3A in humans. Ther Drug Monit 26:192-199.
Wysowski DK and Swartz L (2005) Adverse drug event surveillance and drug withdrawals in the United States, 1969-2002: the importance of reporting suspected reactions. Arch Intern Med 165:1363-1369.
Xie R, Tan LH, Polasek EC, Hong C, Teillol-Foo M, Gordi T, Sharma A, Nickens DJ, Arakawa T, Knuth DW and Antal EJ (2005) CYP3A and P-glycoprotein activity induction with St. John's Wort in healthy volunteers from 6 ethnic populations. J Clin Pharmacol 45:352-356.
Xie W, Yeuh MF, Radominska-Pandya A, Saini SP, Negishi Y, Bottroff BS, Cabrera GY, Tukey RH and Evans RM (2003) Control of steroid, heme, and carcinogen metabolism by nuclear pregnane X receptor and constitutive androstane receptor. Proc Natl Acad Sci U S A 100:4150- 4155.
Yee GC, Stanley DL, Pessa LJ, Dalla CT, Beltz SE, Ruiz J and Lowenthal DT (1995) Effect of grapefruit juice on blood cyclosporin concentration. Lancet 345:955-956.
Zeigler-Johnson C, Friebel T, Walker AH, Wang Y, Spangler E, Panossian S, Patacsil M, Aplenc R, Wein AJ, Malkowicz SB and Rebbeck TR (2004) CYP3A4, CYP3A5, and CYP3A43 genotypes and haplotypes in the etiology and severity of prostate cancer. Cancer Res 64:8461- 8467.
Zhang J, Kuehl P, Green ED, Touchman JW, Watkins PB, Daly A, Hall SD, Maurel P, Relling M, Brimer C, Yasuda K, Wrighton SA, Hancock M, Kim RB, Strom S, Thummel K, Russell CG, Hudson JR, Jr., Schuetz EG and Boguski MS (2001) The human pregnane X receptor: genomic structure and identification and functional characterization of natural allelic variants. Pharmacogenetics 11:555-572.
Zhao XJ, Jones DR, Wang YH, Grimm SW and Hall SD (2002) Reversible and irreversible inhibition of CYP3A enzymes by tamoxifen and metabolites. Xenobiotica 32:863-878.
Zhou S, Yung CS, Cher GB, Chan E, Duan W, Huang M and McLeod HL (2005) Mechanism- based inhibition of cytochrome P450 3A4 by therapeutic drugs. Clin Pharmacokinet 44:279-304.
118 Zucchetti M, Boiardi A, Silvani A, Parisi I, Piccolrovazzi S and D'Incalci M (1999) Distribution of daunorubicin and daunorubicinol in human glioma tumors after administration of liposomal daunorubicin. Cancer Chemother Pharmacol 44:173-176.
119