Pharmacokinetic and Pharmacodynamic Studies Of

Home , Glutarimide, Lenalidomide, Pomalidomide

PHARMACOKINETIC AND PHARMACODYNAMIC STUDIES OF

LENALIDOMIDE AND POMALIDOMIDE

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

Yao Jiang, M.S.

Graduate Program in Pharmacy

The Ohio State University

2015

Dissertation Committee:

Dr. Mitch A. Phelps, Advisor

Dr. Robert Lee

Dr. Flavia Pichiorri

Yao Jiang

2015

Abstract

Lenalidomide and pomalidomide are immunomodulatory drugs (IMiDs) and analogues of their predecessor, thalidomide. Compared to thalidomide, lenalidomide and pomalidomide are 100-1000 fold more potent in simulating T cell proliferation and

50,000 times more potent in inhibiting tumor necrosis factor-alpha (TNF-α). These two drugs also have less severe adverse side-effects compared to thalidomide, such as sedation, constipation and neuropathy. Lenalidomide and pomalidomide have been approved by the US Food and Drug Administration for the treatment of multiple myeloma and are now under evaluation in multiple clinical trials for the treatment of other hematological malignancies and solid tumors. However, large variability in clinical outcomes, potential drug-drug interactions and a number of severe toxicities are being observed in these clinical trials. Furthermore, the precise mechanism of action for these two drugs remains unclear and is likely different among various diseases.

Our group recently identified lenalidomide as a substrate of a multi-drug efflux transporter, P-glycoprotein (Pgp) and reported an apparent clinical drug-drug interaction of lenalidomide with temsirolimus. To further characterize the role of Pgp in the disposition and elimination of lenalidomide, we studied its pharmacokinetics (PK) in

FVB wild type (WT) and mdr1a/b knockout (KO) mice with dysfunctional Pgp.

Although we observed 25% increase in plasma area under curve (AUC) in KO mice compared to WT FVB mice (IV injection, 0.5 mg/kg), brain AUC of lenalidomide was only 12% higher in the KO group vs WT group within one hour after drug administration, which was contrary to our expectation that brain penetration would drastically increase in the KO mice as commonly observed with other Pgp substrates, like digoxin. In the same

FVB WT and mdr1a/b KO mice study, pomalidomide results were also contrary to our expectations for AUC brain to plasma ratio. These results indicated other transporters, in addition to Pgp, likely inhibited brain penetration of lenalidomide or pomalidomide.

Given the mouse brain data, we have focused on another multi-drug efflux transporter, the breast cancer resistance protein (BCRP), which is also highly expressed in the blood- brain barrier. Our preliminary in vitro transwell permeability data showed lenalidomide or pomalidomide was effluxed at a higher rate in MDCK overexpressing human BCRP

(MDCKII/BCRP) cells compared to wild-type cells (MCDKII/WT). Further evaluations were performed in the cell uptake studies of lenalidomide and pomalidomide in

MDCKII/WT and MDCKII/BCRP cells. The results indicated there was less lenalidomide or pomalidoimde accumulated inside of MDCKII/BCRP cells than

MDCKII/WT cells. The results from both transwell permeability and cell uptake assay suggested that lenalidomide and pomalidomide are substrates of BCRP.

Lenalidomide was recently demonstrated to upregulate the C/EBPα-P30 isoform, resulting in increased miR-181a expression, which was linked to the improved outcomes in patients with acute myeloid leukemia (AML). Cereblon, a direct target of lenalidmide, is a component of the E3 ubiquitin ligase complex, along with damaged DNA binding iii protein and Cul4A, which target and ubiquitinate select proteins that are subsequently degraded by the proteasome. We hypothesized C/EBPα-P30 is a target of cereblon associated E3 ligase, and lenalidomide binding to cereblon decreases ubiquitination and therefore stabilizes C/EBPα-P30. Furthermore, we hypothesized leukemia cell expression of efflux transporters, Pgp and BCRP, can pump lenalidomide or pomalidomide out of cells, and thus decreasing their anti-leukemic activity. Understanding how these transporters affect intercellular lenalidomide levels and their relationship with miR-181a expression in bone marrow (BM) and peripheral blood mononuclear cell samples (PBMC) of AML patients may help to explain inter-patient variability in outcomes from lenalidomide therapy. We further measured gene expression of efflux transporters

(ABCB1 and ABCG2), lenalidomide direct and downstream targets (CRBN and CEBPA) as well as the pharmacodynamic (PD) endpoint (miR-181a) in AML patients’ BM and

PBMC samples. While no strong correlations were observed between lenalidomide plasma PK, baseline expressions of genes of interest and gene expression changes post treatment, we did observe an anticipated increased expression of ABCB1 in refractory compared to treatment-naïve patients as well as significant upregulation of CRBN post lenalidomide therapy. Further strategies, such as evaluating PK/PD correlation in simpler systems (e.g. AML cell lines in vitro), evaluating protein expression of lenalidomide targets, exploring the role of other drug transporters and gathering polymorphism information on genes of interest, could be employed in future studies to further evaluate the hypotheses that transporter expression on tumor cells may impact IMiD intracellular activity and outcomes from therapy.

Dedication

This document is dedicated to my beloved grandparents, parents, my husband and my son.

Acknowledgments

This thesis would not have been possible without the support of many people.

First and foremost, I would like to express my sincerely appreciation to my adviser, Dr.

Mitch A. Phelps, for his intellectual supervision, extreme patience and enthusiastic encouragement throughout my graduate studies. His wisdom and support, both as a mentor in research and as a friend in life, helped me through hard times and taught me how to face them in the future. My experience here will be a treasure throughout my life.

I especially appreciate my thesis committee members, Dr. Robert Lee and Dr. Flavia

Pichiorri, for their time, invaluable suggestions, and great support.

My grateful thanks also goes to Dr. Guido Marcucci, Dr. William Blum, and Dr.

Hongyan Wang, for sharing patients’ bone marrow and peripheral blood mononuclear cell samples and miR-181a gene expression data to support my research.

I would also like to extend special thanks to Dr. Jiang Wang, Mr. Hao Li, Dr. Yonghua

Ling, and Mr. Jeffrey Cotrill from the Pharamcoanalytical Shared Resource at OSU for their kind help with generation of clinical experimental data and Dr. Christopher Coss, Dr.

Ming Poi, and Dr. Junan Li for their valuable advice.

I also gave my many thanks to all my sweet friends and labmates, Dr. Lei He, Dr.

Xiaoxia Yang, Dr. Xiaojing Yue, Dr. Ying Li, Dr. Youna Zhao, Dr. Yantong Sun, Yu

Kyoung Cho, Dr. Zhiliang Xie, Dr. Yue Gao, Dr. Xiaohua Zhu, Yuan Zhao and

Shamalatha Kolli. It is a great pleasure to work with all of them.

My sincere thanks also go to the late Kathy Brooks, Carol Camm, Mary Kivel, Casey

Hoering, Jennifer Bartlett, Elizabeth G. Bulgrin (Betsy) and Tami Boldman for their kind helps.

Last but not the least, my deepest appreciation goes to my family, my grandparents, my parents, my husband, my son, my uncles and my aunts. Your love supports me in my life abroad!

vii

Vita

October, 1981…..………………………..Born in Jilin, Jilin, P.R. China.

Sept 2000-June 2004……………………B.S. Pharmaceutical Engeering, College of Life Sciences, Jilin University, P.R. China

Sept 2004-June 2007……………………M.S. Pharmaceutics, College of Life Sciences, Jilin University, P.R. China

Sept, 2010-present…………….……….Graduate Teaching and Research Associate, College of Pharmacy, The Ohio State University

Publications

Papers

Maddocks K, Wei L, Rozewski DM, Jiang Y, Zhao Y, Yang X, Phelps MA, Jones JF, Flynn J, Andritsos L, Johnson AJ, Grever M, Byrd JC, and Blum K. Reduced Occurrence of Tumor Flare with Flavopiridol Followed by Combined Flavopiridol and Lenalidomide in Patients with Relapsed Chronic Lymphocytic Leukemia (CLL). American Journal of Hematology, 2015, Jan, Accepted.

Jiang Y, Wang J, Rozewskia DM, Kollia S, Wu C-H, et al. Sensitive Liquid Chromatography/mass Spectrometry Methods for Quantification of Pomalidomide in Mouse Plasma and Brain Tissue. J Pharm Biomed Anal, 2014; 88: 262-268.

Maddocks K, Ruppert A, Browning R, Jones J, Flynn J, Kefauver C, Gao Y, Jiang Y, et al. A Dose Escalation Feasibility Study of Lenalidomide for Treatment of Symptomatic, Relapsed Chronic Lymphocytic Leukemia. Leukemia Research, 2014; 38:1025-1029.

Walker AR, Klisovic R, Johnston JS, Jiang Y, et al. Pharmacokinetics and dose viii escalation of the heat shock protein inhibitor 17-allyamino-17-demethoxygeldanamycin in combination with bortezomib in relapsed or refractory acute myeloid leukemia. Leuk Lymphoma. 2013; 54:1996-2002.

Li H, Zhang C, Wang J, Jiang Y, Fawcett JP, Gu J. Simultaneous quantitation of paracetamol, caffeine, pseudoephedrine, chlorpheniramine and cloperastine in human plasma by liquid chromatography-tandem mass spectrometry. J Pharm Biomed Anal. 2010; 51: 716-722.

Sun Y, Liu M, Zhang J, Jiang Y, Yu W, Fawcett JP, Gu J. Rapid and sensitive assay for trantinterol, a novel beta(2)-adrenoceptor agonist, in human plasma using liquid chromatography-tandem mass spectrometry. J Pharm Biomed Anal. 2009 ;49: 1056- 1059.

Wang J, Jiang Y, Wang Y, et al. A rapid and sensitive LC-MS/MS assay to quantify yonkenafil in rat plasma with application to preclinical pharmacokinetics studies. J Pharm Biomed Anal. 2008; 47: 985-989.

Zhao L, Li H, Jiang Y, et al. Determination of ranolazine in human plasma by liquid chromatographic-tandem mass spectrometric assay. J Chromatogr Sci. 2008; 46: 697- 700.

Zhang D, Du X, Liu M, Li H, Jiang Y, et al. Determination of ecabet in human plasma by high-performance liquid chromatography-tandem mass spectrometry. J. Chromatogr. B 2008; 863:223-228.

Jiang Y, Wang J, Wang Y, et al. Determination of long-acting release octreotide, an octapeptide analogue of somatostation, in human plasma by liquid chromatography- tandem mass spectrometry. Rapid Commun. Mass Spectrom. 2007; 21:3982-3986.

Jiang Y, Wang J, Wang Y, et al. Rapid and sensitive liquid chromatography–tandem mass spectrometry method for the quantitation of colchicine in human plasma. J. Chromatogr. B 2007; 850: 564-568.

Jiang Y, Wang J, Li H, et al. A developed method for the quantification of clarithromycin by liquid chromatography-electrospray ionization tandem mass spectrometry. J. Pharm. Biomed. Anal. 2007; 43: 1460-1464.

Wang J, Jiang Y, Wang Y, et al. Liquid chromatography/tandem mass spectrometry assay for pharmacokinetics of aildenafil in human plasma. J. Pharm. Biomed. Anal. ix

2007; 44: 231-235.

Wang J, Jiang Y, Wang Y, et al. Highly sensitive assay for titropium, a quanternary ammonium, in human plasma by high-performance liquid chromatography/tandem mass spectrometry. Rapid commun. Mass Spectrom. 2007; 21:1755-1758.

Li H, Wang Y, Jiang Y, et al. A liquid chromatography/tandem mass spectrometry method for the simultaneous quantification of valsartan and hydrochlorothiazide in human plasma. J. Chromatogr. B 2007; 852:436-442.

Zhao L, Hu L, Jiang Y, et al. Determination of Captopril in Human Plasma by Liquid Chromatography-Tandem Mass Spectrometry Chin. J. Anal. Chem. 2006; 34:1599-1602.

Presentations

Yao Jiang, Hongyan Wang, Jiang Wang, et al. Pharmacokinetics and Pharmacodynamics of Lenalidomide in a Phase I Dose Escalation Study in Patients with Acute Myeloid Leukemia, American Association of Pharmaceutical Scientists annual meeting, 2014

Darlene M. Rozewski, Xiaoxia Yang, Yonghua Ling, Yao Jiang, et al. Pharmacokinetics of Combined Lenalidomide and Flavopiridol in Patients with Relapsed and Refractory Chronic Lymphocytic Leukemia, OSUCCC James 15th Annual Scientific Meeting, 2013

Yao Jiang, Jiang Wang, Alison Walker, et al. Lenalidomide pharmacokinetics in combination with idarubicin and cytarabine in patients with acute myeloid leukemia, American Society for Clinical Pharmacology and Therapeutics annual meeting, 2013

William Blum, Rebecca Klisovic, Alison Walker, Sebastian Schwind, Chris Hickey, Mitch Phelps, Yao Jiang, et al. Priming of miR-181a in Acute Myeloid Leukemia (AML) to Increase Chemosensitivity: A Phase I Trial of Lenalidomide (LEN) Followed by Idarubicin and Cytarabine, American Society of Hematology, 2012

Yao Jiang, Yonghua Ling, Kelsie Bernot, et al. Bortezomib pharmacokinetics and pharmacodynamics modeling study in acute myeloid leukemia mouse model, Great Lakes Drug Metabolism and Discussion Group Meeting, 2012

Yao Jiang, Yonghua Ling, Kelsie Bernot, et al. Pharmacokinetics and Pharmacodynamics of Bortezomib, OSUCCC James 14th Annual Scientific Meeting, 2012

Jiang Wang, Yao Jiang, Yonghua Ling, et al. Kinetics of Formation and Disposition of Protocatechuic Acid from Black Raspberry (BRB) Anthocyanins in saliva as determined by Liquid Chromatography Tandem Mass Spectrometry, American association of pharmaceutical scientists annual meeting, 2010

Yonghua Ling, U.V.R. Vijaya Saradhi, Ping Pei, Jiang Wang, Yao Jiang, et al. Degradation and Metabolism of Two Black Raspberry (BRB) Anthocyanins in Saliva as Determined by Liquid Chromatography Tandem Mass Spectrometry, American association of pharmaceutical scientists annual meeting, 2010

Fields of Study

Major Field: Pharmacy

Table of Contents

Abstract ...... ii Dedication ...... v Acknowledgments...... vi Vita ...... viii Publications ...... viii Fields of Study ...... xi List of Tables ...... xv List of Figures ...... xviii CHAPTER 1 BACKGROUND AND INTRODUCTION ...... 1 1.1 Immunomodulatory Drugs (IMiDs) ...... 1 1.1.1 Background of IMiDs ...... 1 1.1.2 Pharmaceutical Properties of Lenalidomide ...... 2 1.1.3 Pharmaceutical Properties of Pomalidomide ...... 4 1.2 Clinical application of IMiDs ...... 5 1.2.1 IMiDs in Hematological Malignancies ...... 6 1.2.2 IMiDs in Solid Tumor ...... 11 1.3 Significance ...... 12 1.3.1 Lenalidomide and Renal Function ...... 12 1.3.2 Lenalidomide and P-glycoprotein ...... 13 1.3.3 Drug-Drug Interaction and Significance of This Study ...... 14 CHAPTER 2 PHARMACOKINETIC STUDY OF LENALIDOMIDE AND POMALIDOMIDE IN FVB WILD TYPE AND Mdr1a/b KNOCKOUT MICE ...... 18 2.1 Introduction ...... 18 2.2 Materials and Methods ...... 22 xii

2.2.1 Chemicals and Solvents ...... 22 2.2.2 Animals ...... 22 2.2.3 Sample Collection ...... 23 2.2.4 LC-MS/MS ...... 23 2.2.5 Sample Preparation ...... 24 2.2.6 Data Analysis ...... 25 2.3 Results and Discussion ...... 26 2.3.1 Lenalidomide ...... 26 2.3.2 Pomalidomide ...... 27 2.3.3 Ratio of Brain to Plasma ...... 28 CHAPTER 3 LENALIDOMIDE AND POMALIDOMIDE IN VITRO TRANSPORTER STUDY ...... 44 3.1 Introduction ...... 44 3.1.1 Breast Cancer Resistance Protein ...... 44 3.1.2 Cell Uptake and Transepithelial Bi-direction Permeability Assay ...... 45 3.2 Materials and Methods ...... 47 3.2.1 Chemicals and Solvents ...... 47 3.2.2 Stock Solutions and Handling of Aqueous Solutions ...... 48 3.2.3 Cell Culture ...... 48 3.2.4 Cell Uptake Assay...... 48 3.2.5 Transepithelial Bi-directional Permeability Assay ...... 49 3.2.6 LC-MS/MS ...... 51 3.2.7 Sample Preparation ...... 52 3.2.8 Statistical Analysis ...... 53 3.3 Results and Discussion ...... 53 3.3.1 Cell Uptake Assay...... 53 3.3.2 Transepithelial Bi-directional Permeability Assay ...... 54 CHAPTER 4 PHARMACOKINETICS AND PHARMACODYNAMICS OF LENALIDOMIDE IN A PHASE I CLINICAL TRIAL FOR THE TREATMENT OF ACUTE MYELOID LEUKEMIA ...... 73 xiii

4.1 Introduction ...... 73 4.1.1 Pharmacokinetic study of lenalidomide in OSU10016 ...... 73 4.1.2 Pharmacodynamic study of lenalidomide in OSU10016 ...... 74 4.1.3 Correlation of PK and PD in OSU10016 ...... 77 4.2 Materials and Methods ...... 79 4.2.1 Study Design ...... 79 4.2.2 Sample Collection ...... 80 4.2.3 Sample Measurement ...... 80 4.2.4 Statistical Analysis ...... 81 4.3 Results and Discussion ...... 82 4.3.1 PK ...... 82 4.3.2 PD ...... 83 4.3.3 Correlation of PK and PD ...... 84 CHAPTER 5 SUMMARY AND FUTURE PERSPECTIVES ...... 110 5.1 Summary ...... 110 5.2 Future perspectives ...... 113 Reference ...... 120

xiv

List of Tables

Table 1.1 Cytogenetics and prognosis of AML ...... 16

Table 2.1 PK parameters for lenalidomide in mouse plasma after IV dosing with 0.5 mg/kg ...... 32

Table 2.2 PK parameters for lenalidomide in mouse brain after IV dosing with 0.5 mg/kg .... 33

Table 2.3 Ratios of brain to plasma PK parameters for lenalidomide (IV, 0.5 mg/kg) .... 34

Table 2.4 Non-compartmental PK parameters for pomalidomide in mouse plasma after

IV dosing with 0.5 mg/kg ...... 35

Table 2.5 Non-compartmental PK parameters for pomalidomide in mouse brain after IV dosing with 0.5 mg/kg...... 36

Table 2.6 Ratios of brain to plasma PK parameters for pomalidomide (IV, 0.5 mg/kg) ...... 37

Table 3.1 Characteristics of Three Transwell Membranes* ...... 58

Table 3.2 Lenalidomide intracellular drug concentrations (nmol/mg protein) in cell uptake study ...... 59

Table 3.3 Pomalidomide intracellular drug concentrations (nmol/mg protein) in cell uptake study ...... 60

-7 Table 3.4 Papp value (*10 cm/s) and ERs of lenalidomide in MDCKII/WT and

MDCKII/BCRP cells with 5 to 120 min incubations ...... 61

-7 Table 3.5 Papp value (*10 cm/s) and ERs of lenalidomide in in MDCKII/WT and

MDCKII/BCRP cells with 1.5 to 30 min incubations ...... 62

-7 Table 3.6 Papp value (*10 cm/s) and ERs of pomalidomide in MDCKII/WT,

MDCKII/Pgp and MDCKII/BCRP cells with 1.5 to 30 min incubations ...... 63

-7 Table 3.7 Papp value (*10 cm/s) and ERs of lenalidomide w/ and w/o FTC in transwell permeability assay ...... 65

-7 Table 3.8 Papp value (*10 cm/s) and ERs of pomalidomide w/ and w/o FTC in transwell permeability assay ...... 66

-7 Table 3.9 Papp value (*10 cm/s) and ERs of genistein w/ and w/o FTC in transwell permeability assay ...... 67

Table 4.1 Dosage escalation plan of clinical trial OSU10016 ...... 86

Table 4.2 Noncompartmental Plasma PK parameters of lenalidomide ...... 87

Table 4.3 p-values of lenalidomide PK parameters comparisons between multiple groups

(separated by cohort and day, respectively) ...... 88

Table 4.4 p-values of lenalidomide PK parameters comparisons between multiple groups

(Wilcoxin rank sum test) ...... 89

Table 4.5 ABCB1 relative expression in BM samples ...... 90

Table 4.6 ABCG2 relative expression in BM samples ...... 91

Table 4.7 CEBPA relative expression in BM samples ...... 92

Table 4.8 CRBN relative expression in BM samples ...... 93

Table 4.9 miR-181a relative expression in BM samples ...... 94

Table 4.10 ABCB1 relative expression in PBMC samples ...... 95

Table 4.11 ABCG2 relative expression in PBMC samples ...... 96

Table 4.12 CEBPA relative expression in PBMC samples ...... 97

xvi

Table 4.13 CRBN relative expression in PBMC samples ...... 98

Table 4.14 miR-181a relative expression in PBMC samples ...... 99

Table 4.15 Correlation coefficients of main PK parameters, D0 baseline gene expression vs gene expression change in BM (all patients, n=22, without outlier, pt6) ...... 100

xvii

List of Figures

Figure 1.1 Chemical Structures of thalidomide (A), lenalidomide (B) and pomalidomide (C) . 17

Figure 2.1 PK profile of lenalidomide in mouse plasma after IV dosing with 0.5 mg/kg ... 38

Figure 2.2 Ratios of lenalidomide plasma PK parameters (KO/ WT) after IV dosing with

0.5 mg/kg ...... 39

Figure 2.3 PK profile of pomalidomide in mouse plasma after IV dosing with 0.5 mg/kg ... 40

Figure 2.4 Ratios of pomalidomide plasma PK parameters (KO/ WT) after IV dosing with 0.5 mg/kg ...... 41

Figure 2.5 PK profile of lenalidomide in mouse brain after IV dosing with 0.5 mg/kg ... 42

Figure 2.6 PK profile of pomalidomide in mouse brain after IV dosing with 0.5 mg/kg ...... 43

Figure 3.1 Lenalidomide cell uptake (nmol/mg protein) in MDCKII cell lines ...... 68

Figure 3.2 ERs of lenalidomide in MDCKII/WT and MDCKII/BCRP cells with 5 to 120 min incubations ...... 69

Figure 3.3 ERs of lenalidomide in MDCKII/WT and MDCKII/BCRP cells with 1.5 to 30 min incubations ...... 70

Figure 3.4 ERs of pomalidomide in MDCKII/WT, MDCKII/Pgp and MDCKII/BCRP cells with 1.5 to 30 min incubations ...... 71

xviii

Figure 3.5 ERs of genistein, lenalidomide and pomalidomide in MDCKII/WT and

MDCKII/BCRP cells after 10 min incubation under the conditions w/ and w/o FTC, respectively...... 72

Figure 4.1 Our hypothesis: possible mechanism of action for lenalidomide in AML .... 102

Figure 4.2 OSU10016 Trial design scheme ...... 103

Figure 4.3 PK profiles of lenalidomide in OSU110016 ...... 104

Figure 4.4 Relative gene expressions of ABCB1 (A), ABCG2 (B) and CRBN (C) in BM 105

Figure 4.5 Relative gene expressions of ABCB1 (A), ABCG2 (B) and CRBN (C) in

PBMCs ...... 107

Figure 4.6 Multiple comparisons of gene expressions between different groups...... 109

Figure 5.1 Structures of (A) lenalidomide and (B) purine and pyrimidine nucleobases 119

xix

CHAPTER 1

BACKGROUND AND INTRODUCTION

1.1 Immunomodulatory Drugs (IMiDs)

1.1.1 Background of IMiDs

Immunomodulatory drugs (IMiDs) are a class of drugs that include thalidomide and its analogues, lenalidomide and pomalidomide (Figure 1.1). The common structure of IMiD members contains two portions, phthalimide and glutarimide. The first generation of

IMiDs, thalidomide was synthesized in Germany in 1954 and was used to treat morning sickness for pregnant women. Thalidomide was withdrawn from the market in 1961 due to teratogenic effects [1]. However, because of its anti-inflammatory properties, thalidomide was repurposed in 1965 for the treatment of erythema nodosum leprosum

(ENL, leprosy) [2]. Eventually, the U.S. Food and Drug Administration (FDA) approved thalidomide for the treatment of ENL in 1998. Later, the anti-angiogenic activity of thalidomide discovered in animal models [3] triggered further study of its anti-cancer effects in multiple myeloma (MM) [4-7]. Thalidomide was subsequently approved by the

FDA in 1998 for the treatment of patients with newly diagnostic relapsed/refractory MM.

A newer generation of IMiDs was developed by Celgene Corporation with an attempt to reduce the side effects of thalidomide, e.g. teratogenesis. Lenalidomide (CC-5013,

RevlimidTM) is an analogue of thalidomide with an amino group added to the benzene ring at the 4th position and with only a single oxo group in phthaloyl ring. This simple structural change makes lenalidomide 100-1000 fold more potent in stimulating T cell proliferation and 50,000 times more potent in tumor necrosis factor-alpha (TNFα) inhibition with less severe adverse side-effects relative to thalidomide [4, 8, 9]. In 2006, lenalidomide was approved by the FDA for the treatment of patients with MM, mantle cell lymphoma as well as myelodysplastic syndromes. Pomalidomide (CC-4047,

ActimidTM), like lenalidomide, has an amino group at the 4th position of the benzene ring, which also enhances the expression of transcription factor T-bet besides its similar effects to lenalidomide [10, 11]. Pomalidomide was approved by the FDA in February 2013 for the treatment of relapsed/refractory MM. In addition to MM, IMiDs are currently used for the treatment of other cancers, such as acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), myeolofibrosis (MF) disorders and solid tumors [12].

1.1.2 Pharmaceutical Properties of Lenalidomide

Lenalidomide has the Chemical Abstract Service (CAS) registry number of 191732-72-6 and chemical name of 3-(4’-amino-1, 3-dihydro-1-oxo-2H-isoindol-2-yl)-2, 6- piperidinedione. The empirical formula is C13H13N3O3 with a molecular weight of

259.25 [13].

The pharmacokinetics (PK) of lenalidomide was also evaluated in male beagle dogs, cynomolgus monkeys as well as Sprague-Dawley rats. The Tmax ranged from 0.5 to 1.5 hr and the elimination t1/2 ranged from 1.3 to 3.0 hr. Plasma protein binding ratios were between 18.9% to 19.1% for rats, rabbits and monkeys, and were 22.8% and 29.2% for multiple myeloma patients and healthy volunteers, respectively. Radioactivity studies showed that in Sprague-Dawley rats, [14C]-lenalidomide was mainly excreted in unchanged parent drug form and the hydrolysis of the glutarimide ring. Radioactive dose was excreted equally in Sprague Dawley rats’ urine and feces after oral administration. In cynomolgus monkeys, more than 33% of the total radioactivity was excreted in urine after oral dosing [13].

The study of absorption, metabolism and excretion of lenalidomide in humans was evaluated by Celgene in six healthy male subjects by giving [14C]-lenalidomide [14]. A single oral suspension dose of [14C]-lenalidomide at 25 mg was given to healthy subjects, and blood (plasma) and excreta were collected. This study showed that the absorption of

14 [ C]-lenalidomide was quick (Tmax of 0.77-1.0 hr), and terminal half-life (t1/2) was around 3 hr. More than 88% of the radioactive dose was recovered within the first 24 hrs after administration and about 94% was recovered within 10 days. Over 90% of total radioactivity was excreted in urine, and about 4% was recovered in feces. The two primary metabolites of lenalidomide accounted for less than 5% of the radioactive dose.

Unchanged lenalidomide was the primary radioactive component in both plasma and urine (>92% and >90%, respectively). In summary, human PK study of lenalidmide

3 indicated that lenalidomide can be absorbed rapidly after oral administration and mainly eliminated by the kidney in its unchanged form.

1.1.3 Pharmaceutical Properties of Pomalidomide

The chemical name of pomalidomide is 4-amino-2-(2, 6-dioxopiperidin-3-yl) isoindoline-

1, 3-dione. Its Chemical Abstract Service (CAS) registry number is 19171-19-8. The empirical formula is C13H11N3O4 with a molecular weight of 273.5 [15].

PK studies in rats and monkeys showed that the bioavailability of pomalidomide was dose dependent (15% at dose of 100 mg/kg to almost 100% at a dose 2 mg/kg). In vitro protein binding was low in rats and mice, and it was moderate in human plasma, ranging from 12% to 59% between species over the concentration range from 30 to 1000 ng/mL.

A distribution study of oral [14C]-pomalidomide in pigmented male Long-Evans rats showed that the gastro-intestinal tract and kidneys had the highest tissue concentrations, while the bile, liver, secretory glands and pigmented skin had moderate concentrations. In both rats and monkeys, metabolic pathways were similar with major metabolites of hydrolysis of the gluratimide ring and hydroxylation of phthalimide aryl ring and its glucuronidation. In rats, a majority of the radioactive dose was excreted in feces (>80%) with minor amount found in urine (9%). In monkeys, pomalidomide (primarily metabolites) was predominantly excreted in urine (73%) and in feces (~12%) [15].

Similar to lenalidomide, an absorption, metabolism and excretion study of pomalidomide was conducted in 8 male healthy subjects following a single oral dose of [14C]- pomalidomide at 2 mg [16]. Radioactivity was measured in collected blood (plasma),

4 urine and feces samples. Pomalidomide was well absorbed with Tmax at 3.0 hr and rapidly cleared with elimination t1/2 of 11.2 hr. In blood circulation, approximately 70% of the radioactivity was associated with unchanged parent drugs. About 73% of the total activity was excreted in urine and 15% in feces mainly in metabolites form. Among the excretion of urine and feces, hydroxylation metabolites followed by glucuronidation accounted for

43% of the dose, glutarimide ring hydrolysis accounting for 25%, and unchanged drug was about 10%. The major oxidative metabolite, 5-hydorxy pomalidomide was formed through cytochrom P450 (CYP450) subfamily 1A2 and CYP3A4. In vitro assay indicated that hydroxy and hydrolysis metabolites of pomalidomide were about 26-fold less effective in inhibition of MM cell proliferation and at least 32 fold less potent in elevating productions of IL-2 (interleukin 2) and TNF-α than the parent drug.

1.2 Clinical application of IMiDs

Data within clinicaltrials.gov indicates that there have been approximately 468 clinical trials initiated that include thalidomide, 624 trials with lenalidomide, and 88 trials with pomalidomide (March, 2015). These clinical trials evaluate the effectiveness and safeties of these IMiDs used alone or in combination with other chemotherapeutic agents for the treatments for patients with not only MM, but also other hematological malignancies, like

AML and CLL as well as solid tumors [12].

1.2.1 IMiDs in Hematological Malignancies

1.2.1.1 Multiple Myeloma

Multiple myeloma is a blood cancer formed by malignant plasma cells and is the second most common blood malignancy. Normal plasma cells are part of the immune system and can generate antibodies to fight against infections. Abnormal plasma cells grow out of control and crowd out the normal cells which results in bone lesions. Over time, malignant plasma cells will spill out of bone marrow (BM) and damage other organs, which is sometimes referred to as CRAB features that include hypercalcemia, renal impairment, anemia and bone lesions [17]. Treatments for MM include chemotherapy, bisphosphonates, radiation, surgery and stem cell transplant. Among all of these treatment options, chemotherapy is the most common and may be used within all disease stages.

The earliest treatment for MM can be traced back to 1844, and included use of rhubarb pill and infusion of orange peel [18] as well as phlebotomy in maintenance therapy [19].

From the 1950s, prednisone, a corticosteroid drug, was widely used due to its immunosuppressant effect [20]. After about 10 years, dexamethasone (Dex), another synthetic corticosteroid drug, was 6 fold more potent than prednisone, and it could be given alone or in combination with other chemotherapeutic reagents [21, 22]. Later, melphalan and bortezomib, a proteasome inhibitor, were also used to treat MM [23, 24].

IMiDs were investigated for the treatment of MM since the discovery of thalidomide’s anti-angiogenic activity [25]. The combination strategies of various chemotherapeutic

6 drugs, e.g. bortezomib combined with Dex [26, 27] and lenalidomide combined with Dex

[28] were adopted to evaluate their synergistic effects.

An international phase III trial to compare the outcomes of the combination of lenalidomide plus Dex and Dex alone indicated the median time to progression (TTP) was almost three-fold greater in the lenalidomide plus Dex group compared to that of

Dex alone group. The ratio of partial response (PR) and complete response (CR) patients as well as overall survival (OS) were also significantly improved in the combination treatment compared to the Dex alone group [29]. Several subsequent clinical trials reached similar conclusions when comparing lenalidomide plus Dex with Dex alone [30, 31].

The addition of other chemotherapy drugs to lenalidomide plus Dex, such as bendamustine [32], Adriamycin [33, 34], and cyclophosphamide [35] were also investigated in relapsed or refractory MM patients. All of these trials were found safe and effective. The combinations of lenalidomide with other chemotherapy reagents, like bortezomib [36], mTOR inhibitor CCI-779 [37], melphalan and prednisone [38] were also evaluated. In general, lenalidomide plus low dose Dex becomes a standard of care for newly diagnosed myeloma.

The first phase I study of pomalidomide conducted in relapsed/refractory myeloma patients showed a dose at 2 mg/day was safe in this trial [39]. A second phase I study reported pomalidomide could be tolerated at 5 mg/day on alternate days [40]. Five phase

II studies of pomalidomide plus Dex performed by Lacy et al. evaluated the efficacy of this regimen [41-44], and results indicated that pomalidomide at a dose of 4 mg/day

7 combined with low dose Dex (40 mg/week) was effective in the treatment of relapsed/refractory MM and overcame resistance to lenalidomide and bortezomib [41,

45]. A similar result was also observed by Richardson and colleagues with a dose of pomalidomide at 4 mg/day [46]. Several clinical trials investigated three-drug combination therapy, like pomalidomide with cyclophosphamide and prednisone [47] or pomalidomide and dexamethasone combined with other standard chemotherapeutic agents [48-52]. The first Phase III trial [53] based on 445 patients indicated that the

OS improved 7 months in relapsed or refractory MM by comparing pomalidomide plus low-dose Dex versus high-dose Dex alone. More studies are underway to evaluate other combination therapies with pomalidomide and Dex.

1.2.1.2 Acute Myeloid Leukemia

AML, also known as acute nonlymphocytic leukemia or acute myelogenous leukemia, is a hematologic cancer characterized by the accumulation of immature myeloid cells in

BM. AML diagnosis typically includes a complete blood count revealing an excess of immature white blood cells and sometimes involves decreases in platelets and red blood cells. The incidence of AML increases with age, and it accounts for around 1.2% of cancer deaths in the US [54]. Over the past 15 years it has become clear that cytogenetics of the leukemic AML cells plays an important role in disease prognosis [55-58]. The

French American British (FAB) and World Health Organization (WHO) list a variety of cytogenetic factors (Table 1.1) associated with 5-year survival and relapse rates. In all prognostic risk groups, CN-AML (cytogenetically normal-AML, i.e. disease without cytogenetic abnormalities listed in the table) represented approximately 45% of 8 cases [59]. Several molecular biomarkers harbored by CN-AML patients have been discovered as predictors of outcomes, e.g. FLT3-ITD (fms-like tyrosine kinase/internal tandem duplication), FLT3-TKD (FLT3/tyrosine kinase domain), NPM1 (nucleophosmin) mutation, and CEBPα (CCAAT/enhancer binding protein-α) mutation [60] .

Treatments for AML include chemotherapy, radiation therapy, stem cell transplant and/or immunotherapy. Chemotherapy can be divided into two stages, induction (pre-remission) and consolidation (post-remission) chemotherapies. In the induction stage, cytarabine and an anthracycline drug (daunorubicin or idarubicin) are normally used to reduce the number of leukemia cells (i.e. reduce the tumor size). In consolidation therapy, several cycles of high-dose cytarabine and allogeneic or autologous stem cell transplant will be considered in a subset of patients.

Several phase II clinical trials investigated the efficacy of different doses of lenalidomide in AML patients with abnormal chromosome 5. Lenalidomide at 30 mg/day was successful at achieving a 20% overall response rate (ORR) in AML [61] and another study with lenalidomide administered 50 mg/day showed at least 14% PR in treatment of older naïve AML patients with 5q deletion [62]. In a study by Fehniger and colleagues, the authors indicated 50 mg/day lenalidomide in treatment-naïve patients whose age was greater than 60 years reached approximately 30% overall CR and 53% of CR with incomplete blood count recovery [63]. Blum and colleagues also showed that high dose lenalidomide was effective in treatment of relapsed/refractory AML patients [64]. In addition, this study found that lenalidomide alone can induce complete remission of

AML in patients with isolated trisomy 13 [65]. 9

One study demonstrated pomalidomide could reduce the proliferation of human B cell precursor (BCP) in acute lymphoblastic leukemia (ALL) cell lines and reduce splenic dissemination in BCP-ALL xenograft mouse model [66]. However, so far, for pomalidomide, one clinical trial for the treatment of AML and one for ALL are still under recruiting, and no clinical trial of pomalidomide in AML or ALL has been reported.

1.2.1.3 Chronic Lymphocytic Leukemia

CLL is a malignant hematological disease that occurs in blood and BM. It is one of the most common leukemias in adults, and it rarely occurs in children. Based on the age, health conditions and other prognostic factors, patients can be divided into different risk groups according to the Rai Staging system and various treatment options would be implemented [67]. The treatments for CLL include chemotherapy, monoclonal antibodies, therapy, and stem cell transplant. Drug relapse is a marked problem in CLL, and therapeutic options for refractory patients are limited. IMiDs have been shown to change the microenvironment of tumors by modulation of cytokines, and this has rendered

IMiDs a potentially useful component to therapy for CLL, especially for relapsed or refractory patients [68-73].

Multiple clinical trials with lenalidomide have been evaluated in untreated CLL or relapsed/refractory CLL patients [68, 74, 75]. The ORR could reach at least of 38%. A study of lenalidomide in relapsed/refractory CLL with high risk showed a ORR of 31% with median PFS of 12.2 months and estimated 2-year survival probability of 58% [76].

Lenalidomide therapy in treatment-naïve elderly CLL patients was well-tolerated with 65%

ORR and an estimated 2-year PFS of 60% [77]. Chen et al. reported a similar study with

56% ORR [78]. Unlike the treatment of AML or ALL, the dose of lenalidomide used in

CLL is much lower than that in MM, AML or ALL due to severe toxicities, especially the tumor flare reaction (TFR) [79, 80]. The mechanism of this is still unclear, but it may be related to B-cell activation [81] or the up-regulation of interleukins (ILs) and tumor necrosis factor receptor-1 [75]. No clinical trial of pomalidomide in CLL has been initiated thus far.

1.2.2 IMiDs in Solid Tumors

In general, the outcome of IMiDs in treatment of solid tumors was not as promising as that in hematological malignances. A phase I study of lenalidomide conducted in London,

UK, enrolled patients with malignant melanoma, carcinoma of the pancreas, non-small- cell lung cancer (NSCLC), renal carcinoma and breast carcinoma. This was a non- randomized, open-label within-patient dose escalation study to evaluate the maximum tolerated dose (MTD) of lenalidomide [82]. A phase I trial from the National Cancer

Institute (NCI) in patients with gliomas and refractory CNS malignancies [83] indicated no peripheral neuropathy, skin rash or constipation were observed at the dose levels evaluated. Another phase I trial recruiting patients with metastatic androgen independent prostate cancer [84] reached their MTD at 20 mg/day. Two phase II and III studies indicated that no significant improvement in response rate or time to progression were observed with lenalidomide at 25 mg daily in relapsed or refractory stage IV melanoma [85, 86].

The studies of pomalidomide in solid tumors mainly stay in the phase I study stage. One paper published in 2011 reported a phase I MTD study of pomalidomide combined with gemcitabine for the treatment of metastatic pancreas cancer [87]. In this study, a MTD of

10 mg/day was given to twenty-three patients for 21 days, and it was well tolerated with

38% of patients. Some patients experienced dose-limiting toxicity. Twenty two (22) % of patients had deep vein thrombosis (DVT) and 9% had anaemia. Another phase I study of pomalidomide was conducted in patients with advanced solid tumors including colon, sarcoma, lung and pancreas cancers [88]. In this study, two dosing regimens were evaluated. In cohort A, pomalidomide was well tolerated at a dose of 5 mg/day for 21 days followed by a 7-day rest, and this dose was recommended to escalate to 7 mg/day for a phase II study. In cohort B, pomalidomide given at 4mg/day could be safely used for 28 consecutive days.

1.3 Significance

1.3.1 Lenalidomide and Renal Function

Renal function is crucial in lenalidomide clearance since more than 90% of lenalidomide is excreted in urine. Lenalidomide PK study in subjects with renal impairment demonstrated that urinary recovery of lenalidomide dropped from 84% of the dose to

69%, 38% and 43% in terms of normal renal function to mild, moderate and serve renal impairment, respectively [89]. Normal, mild, moderate and severe renal impairments were defined as creatinine clearance (CLcr) >80 mL/min, 50< CLcr < 80 mL/min, 30<

CLcr < 50 mL/min and CLcr < 30mL/min, respectively. However, renal impairment would

12 not be expected to affect lenalidomide absorption, protein binding ratio and non-renal elimination.

Another study of lenalidomide combined with Dex in patients with MM who had renal impairment showed that the combination was effective and well tolerated. However, patients with renal impairment tended to have significant shorter overall survival (p=.006) and increased incidence of toxicities, like thrombocytopenia. They also required more frequent dose reduction or interruption [90]. In summary, moderate or severe renal impairment or other end-stage renal disease will result in dramatically decreased lenalidomide clearance. The AUC of lenalidomide could increase by 185% to 420% with terminal half-life increasing by 6 to 12 hrs [89].

1.3.2 Lenalidomide and P-glycoprotein

The clearance of lenalidomide is greater than 2-fold of glomerular filtration rate (GFR), which suggests an active tubular secretion. The active secretion accounts for around 40% of total clearance with another 40% clearance from passive filtration and 20% from non- renal clearance [89], which raises the question of the contribution of transporters in the kidney for lenalidomide clearance. A study from Celgene Corporation [91] indicated their in vitro studies demonstrated that lenalidomide is not a substrate of human organic anionic transporter (OAT)1, OAT3, Organic anion-transporting polypeptide (OATP)2, organic cation transporter (OCT)1 as well as efflux transporters multidrug resistance- related protein (MRP)1, MRP2 and MRP3. However, their data did suggest lenalidomide is a weak substrate of P-glycoprotein (Pgp).

Pgp also known as Multi Drug Resistance Protein 1 (MDR1) plays an important role in drug absorption, distribution and elimination, and thus becomes a point of interest in lenalidomide development. Pgp is a 170 kDa adenosine triphosphate (ATP)–dependent plasma membrane glycoprotein responsible for extruding xenobiotics and toxins out of cells [92]. The gene family which encodes Pgp has two genes in human and three genes in rodents. The Class I and III genes (human MDR1/ABCB1, mouse mdr1/Abcb1a and mdr3/Abcb1b) encode drug transporters, while the Class II genes (human

MDR2/3/ABCB4, mouse mdr2/Abcb4) encode genes responsible for phosphatidylcholine export into the bile [93]. Henceforth, all references to “Pgp” indicate drug transporters that are the product of ABCB1 (human) or Abcb1a/b (mouse). Pgp is expressed extensively in proximal tubules of the kidney, luminal membrane of the small intestine, blood–brain barrier as well as uterus, placenta and testes, the apical membranes of hepatocytes and bronchial cells [94].

1.3.3 Drug-Drug Interaction and Significance of This Study

The drug resistance and drug-drug interaction induced by Pgp have been extensively studied. One recent publication reported a drug-drug interaction in a phase I clinical trial of lenalidomide for the treatment of patients with MM [37]. In this trial, lenalidomide was co-administrated with CCI-779 (temsirolimus), and the PK profiles of both drugs were apparently altered in the presence of the other drug. CCI-779 is a known Pgp substrate [95-97]. The clinical PK data combined with the in vitro experimental results in this paper lead to the conclusion that the apparent drug-drug interaction observed in this trial was mediated via Pgp. However, Celgene debated that lenalidomide is a weak 14 substrate of Pgp and emphasized a lack of in vivo data to demonstrate how significantly

Pgp can contribute to lenalidomide PK [98].

To further evaluate the role of Pgp in lenalidomide PK and subsequently address the question from Celgene, an in vivo study in Pgp wild type and knockout mice was conducted. Since there were no prior reports of pomalidomide is a substrate of Pgp, and given the similar structures of pomalidomide and lenalidomide, pomalidomide was also included in this preclinical study (Chapter 2). Based on the results of the Pgp knockout mouse study, another efflux transporter, BCRP was also evaluated through in vitro cell studies (Chapter 3). However, the mechanism of lenalidomide action is still largely unknown. How the transporter study findings contribute to lenalidomide PK and what PK factors contribute in the clinical setting to variability in clinical outcomes warrants further investigation. In Chapter 4, a hypothesis of the possible mechanism of lenalidomide action was proposed. Through this transporter mechanism, the PK and PD study of one lenalidomide clinical trial was evaluated. This comprehensive study covered pre-clinical

PK, in vitro cell study and clinical PK and PD studies. Collectively, the findings herein help to further understand the variability of lenalidomide in clinical trials and could be used to predict the potential drug-drug interactions as well as a prognosis for clinical response.

Risk Category Cytogenetic Abnormality

Good t(8;21), t(15;17), inv(16)

Normal cytogenetics, +8, +21, +22, del(7q), del(9q), Abnormal Intermediate 11q23, all other structural or numerical changes

Poor -5, -7, del(5q), Abnormal 3q, Complex cytogenetics

From http://en.wikipedia.org/wiki/Acute_myeloid_leukemia

Table 1.1 Cytogenetics and prognosis of AML

Figure 1.1 Chemical Structures of thalidomide (A), lenalidomide (B) and pomalidomide (C)

CHAPTER 2

PHARMACOKINETIC STUDY OF LENALIDOMIDE AND

POMALIDOMIDE IN FVB WILD TYPE AND Mdr1a/b KNOCKOUT

MICE

2.1 Introduction

Each year, more than 2,210,000 serious adverse drug reactions (ADR) happen in hospitalized patients with over 106,000 deaths, which make ADR become the 4th cause of death [99-101]. DDI accounting for 20-30% of all ADR may significantly affect trial outcomes or threaten patients’ safety [102-105]. When DDI occurs, drug PK and/or PD is altered by co-administration with another drug(s). In some cases, PK and/or PD are altered for two or more drugs in the combined therapy. PK changes could occur in any of the processes of absorption, distribution, metabolism or elimination (ADME). More than

80% of observed DDI occurs through metabolic processes which reflects the the important role of hepatic cytochrome (CYP) P450 enzymes as the major pathway for drug clearance [106]. DDI may also be mediated by transporter proteins. Pgp, also called

MDR1, is an ATP-dependent glycoprotein belonging to the ABC superfamily of transporters. It works as an efflux pump with broad substrate specificity and is the most commonly evaluated efflux transporter [107, 108].

Among the lenalidomide clinical trials at OSU which include lenalidomide treatment for patients with MM, AML and CLL, an unexpected, apparent DDI was observed in one clinical trial of lenalidomide combined with CCI-779 (temsirolimus) for the treatment of relapsed MM. The PK of both lenalidomide and temsirolimus appeared to be altered as a function of dose for each drug. The AUC of CCI-779 increased at a fixed dose with an increase in lenalidomide dosage, and vice versa. Since CCI-779 is a Pgp substrate

[95, 96], and lenalidomide is mainly excreted by the kidney in unchanged form [13], our lab proposed this apparent DDI may be mediated by Pgp. The results from translational in vitro cell experiments evaluating the interaction of these two drugs through Pgp demonstrated lenaliomide is a Pgp substrate and that temsirolimus can modulate Pgp mediated efflux of lenalidomide [37].

After publication of these results, Celgene, owner of lenaliomide, suggested lenalidomide is a weak substrate of Pgp and highlighted the lack of in vivo data to support our conclusion that the observed, apparent DDI between lenalidomide and CCI-779 was caused by Pgp [98]. Furthermore, Celgene conducted a phase I study in healthy volunteers and observed some evidence of DDI between lenalidomide and several Pgp substrates and inhibitors, including temsirolimus, although the magnitude of observed changes in PK was small and considered clinically insignificant [109]. Their trial included two studies: Study 1 was the evaluation of lenalidomide interacting with digoxin

(a Pgp substrate), designed as a double-blind, placebo-controlled, randomized, 2-period, crossover trial (17 subjects finished). Study 2 was composed of two parts: Part 1 was lenalidomide interacting with quinidine (a Pgp inhibitor), an open-label, fixed-sequence, 19

2-period, crossover trial (14 subjects finished). Part 2 was lenalidomide interacting with temsirolimus (a Pgp inhibitor/substrate), an open-label, fixed-sequence, 3-period, crossover trial (11 subjects finished). By comparing the key PK parameters of lenalidomide, no difference was observed in Tmax and t1/2 when lenalidomide was given alone or in combination with any of other drugs tested in this paper. Cmax and AUC were within 80-125% range in the comparison between lenalidomide alone and lenalidomide plus other drug groups [109]. The range 80-125% is common criteria used for two treatments comparison in clinical trials, e.g DDI or bioequivalence studies [110, 111]. A systemic drug exposure difference over 20% will be considered clinically significant by the FDA because the variability from experiment error could be within 20% range. Since

AUC and Cmax (PK parameters describing drug exposure) are log-normally distributed,

80-125% is the final range for PK parameters when the symmetrical difference ±20% is for the log-transformed range of these PK parameters.

Our group has some other opinions about their debates. Published data and data [13, 112] from the Investigator’s Brochure for lenalidomide indicate that 90% of lenalidomide is excreted in urine, and the clearance of lenalidomide is greater than 2-fold of glomerular filtration rate (GFR). The higher than GFR renal drug clearance suggests an active tubular secretion, which is estimated to account for around 40% of total clearance. They also state that the in vitro studies indicating lenalidomide is not a substrate OAT1, OAT3,

OATP2, OCT1 and MRP1-3, which may suggest a larger role for Pgp in lenalidomide clearance.

Notably, many of the published studies for IMiDs drug PK have been in healthy volunteers. Cancer patients often experience comorbidities related to their disease and/or to drug therapy, included bacterial and fungal infections, depression, insomnia and anxiety, gastrointestinal symptoms, diarrhea, cardiovascular events and renal impairment.

These all could impact drug disposition to varying degrees. In particular, MM patients develop renal insufficiency due to filtration of excess antibody fragments that ultimately clog renal clearance pathways. This impairs renal elimination of drugs, and thus Pgp may contribute to a greater extent in drug clearance. Several publications have demonstrated the importance of renal function in lenalidomide disposition. They indicated the AUC of lenalidomide increased by 185% to 420% in patients with moderate or severe renal impairment [89, 90]. However, in their phase I study in healthy volunteers [109], all subjects had renal and hepatic functions that were within normal institutional limits, which may not represent cancer patients, especially for diseases where renal impairment is common and related to disease progression. Thus, further evaluation is warranted to determine the significance of Pgp in lenalidomide disposition and excretion.

To further evaluate the impact of Pgp in lenalidomide disposition, we conducted a study evaluating pharmacokinetics of lenalidomide in FVB WT and mdr1a/b KO mice. We also evaluated pharmacokinetics of pomalidomide to determine if this structurally similar

IMiD is also a substrate of Pgp. Mdr1a and mdr1b are the genes encoding Pgp in mouse, and mdr1a/b (-/-) knockout mice do not express functional Pgp. This mouse model has proven to be a useful tool for evaluating the impact of Pgp on the disposition of other

21 agents, and it was used in this study to evaluate the role of Pgp in the distribution and elimination of lenalidomide and pomalidomide.

2.2 Materials and Methods

2.2.1 Chemicals and Solvents

Lenalidomide was purified from commercial capsules, and pomalidomide was synthesized using a modified method based on a previously published assay [113]. The purity of both drugs were confirmed >95% by nuclear magnetic resonance and high- performance liquid chromatography (HPLC)-UV analysis. Dimethyl sulfoxide (DMSO) and phosphate buffered saline (PBS) were purchased from Life Technologies (Carlsbad,

CA). Dosing stock solutions (1 mg/mL) of lenalidomide and pomalidomide were prepared using sterile DMSO. Dosing solutions of 0.1 mg/mL lenalidomide or pomalidomide were freshly prepared in PBS from stock solutions. Hesperetin, used as the internal standard (IS) in liquid chromatography tandem mass spectrometry (LC-MS/MS) quantification, was purchased from Sigma (St. Louis, MO). Acetonitrile used in LC-

MS/MS analysis was HPLC grade and purchased from Thermo Fisher Scientific

(Waltham, MA).

2.2.2 Animals

Mdr1a/b gene knockout mice were obtained from Taconic Biosciences, Inc. Mice were bred and proliferated with agreement contract with Taconic. Mice (male and female) used in this study were 6 to 11 weeks old, and gender and age matched FVB WT mice were purchased from Harlan Laboratories. Mice were kept in the facility for at least 48 hrs

22 with access to soft food diets before study initiation. Food was removed one half hour ahead of the dark cycle on the day before the experiment; food was returned 5 hrs after drug administration. The study design was approved and performed in compliance with the OSU Institutional Animal Care and Use Committee guidelines.

2.2.3 Sample Collection

FVB WT mice and Mdr1a/b KO mice were assigned with gender and age uniformly representative among all the time points. Lenalidomide and pomalidomide were given intravenously (tail vein bolus injection) at a dose of 5 mg/kg with a dosing volume of

5 μL/g mouse. Whole blood and brain samples were collected after mice were sacrificed at 5, 10, 20, 30, 45, 60, 90, 150, 240 and 360 minutes after lenalidomide was given, and an additional 540 mins time point was included for pomalidomide. There were five mice for each time point in each group. Plasma samples were obtained by centrifugation of the heparinized blood collection tubes. Plasma and brain samples were placed on dry ice immediately and stored in a -80 °C freezer.

2.2.4 LC-MS/MS

Pomalidomide was determined using a recently published validated LC-MS/MS method [114]. Lenalidomide concentrations in plasma and brain samples were measured employing a modified LC-MS/MS method based on a previous publication using hesperetin as the internal standard [115]. Briefly, lenalidomide and pomalidomide were separated on a reverse phase C18 column and detected by a triple quadrupole mass spectrometer (TSQ Quantum Discovery) with positive an atmospheric pressure chemical

23 ionization (APCI) ionization source. A gradient mobile phase comprising water and acetonitrile with 0.1% formic acid was used for analyte elution. Transition channels of the protonated molecular ions were 260.01→149.01 for lenalidomide, 274.02→201.00 for pomalidomide, and 303.06→153.01 for hesperetin, respectively. The linear range was

0.3-3000 nM in mouse plasma and 0.6-6000 pmol/g in brain tissue for both lenalidomide and pomalidomide, respectively.

2.2.5 Sample Preparation

2.2.5.1 Standard and Quality Control Samples Preparation

Lenalidomide, pomalidomide and hesperetin powder were first dissolved in DMSO to get high concentration solutions (10mM for lenalidomide and pomalidomide and 10ng/mL for hesperetin). These high concentration solutions were then diluted by 50% methanol to

1 mM for lenalidomide and pomalidomide, respectively, and 1 mg/mL for hesperetin as stock solutions. Serial standard neat solutions (10x) were diluted from the stock solution daily. Standard curves were prepared by spiking 10 μL of IS working solution (10 µg/mL) and 10 μL of 10x standard neat solutions to 100 μL of blank plasma or 50 mg of homogenized blank brain tissue to achieve a final standard curve with concentrations from 0.3 to 3000 nM in plasma and 0.6 to 6000 pmol/g tissue in brain, respectively.

Quality control (QC) samples were prepared in a similar way but at 3, 100, 800 and

2400 nM for plasma and 2, 60 and 2000 pmol/g for brain tissue.

2.2.5.2 Plasma Sample Preparation

For plasma samples, 10 µL of IS working solution was added into 100 μL of plasma.

Proteins in samples were precipitated by adding 1 mL of acetonitrile. After 30 seconds vortex- mixing and centrifugation at 18,000 g for 10 mins at 4 °C, the supernatant was moved to a glass tube and dried by a nitrogen gas stream. 120 μL of 5% acetonitrile was used to reconstitute the residue, and 20 μL of the supernatant from the reconstituted solution after centrifugation was used for LC-MS/MS analysis.

2.2.5.3 Brain Sample Preparation

First, 50 mg of brain sample was homogenized by adding 1mL of acetonitrile. Then

10 µL of IS (10 µg/mL) was added to the homogenate followed by vortex-mixing for 30 seconds and centrifugation at 18,000 g for 10 min at 4°C. Subsequent steps were the same as those in plasma sample preparation.

2.2.6 Data Analysis

LC Quan Xcalibur software was used for LC-MS/MS system control and data processing.

Pharmacokinetic analysis was performed using non-compartmental methods in Phoenix

WinNonlin 6.3.0.395 (Pharsight Corporation, Mountain View, CA, USA). The area under the concentration vs. time curve (AUC) was estimated with a linear up/log down method.

The PK parameters reported here include maximum observed concentration (Cmax), time to maximum concentration (Tmax), Area under the concentration-time curve (AUC), clearance (CL), half-life (t1/2) and volume of distribution (Vz).

2.3 Results and Discussion

2.3.1 Lenalidomide

2.3.1.1 Lenalidomide in Plasma

Lenalidomide was given at a dose of 0.5mg/kg to FVB WT and mdr1a/b KO mice. Mice were gender and age matched by time point between WT and KO mice to minimize the variability from mice between groups. Plasma samples were collected at multiple time points (n=5 per time point) after administration as described in section 2.3. Plasma concentration vs time curves are shown in Figure 2.1. Results from non-compartmental analysis are displayed in Table 2.1 . Observed Cmax of WT and KO mice were 2092 and

1535 nM, respectively, and Tmax occurred at the first sample collection time. Drug exposures were 1044 and 1296 hr*nM for WT and KO groups, respectively, which was

25% higher in Pgp KO mice. PK parameters comparison is displayed in Table 2.1 as well as in a plot in Figure 2.2.

2.3.1.2 Lenalidomide in Brain

Brain samples were also collected and measured from intravenously administrated groups

(WT and KO). Brain lenalidomide Cmax in KO (88.8 pmol/g) was about 1.3 fold higher compared to that in WT (68.7 pmol/g) and was reached at an earlier time (KO, 0.17 vs

WT, 0.33 hr, Table 2.2). Estimated AUClast for KO and WT were 219 and 194 hr*pmol/g, respectively. Half-lives were 4.38 hr in KO and 5.4 hr in WT, respectively. AUClast

KO/WT ratios were 1.24 in plasma and 1.12 in brain.

2.3.2 Pomalidomide

2.3.2.1 Pomalidomide in Plasma

Pomalidomide was given by IV injection at a dose of 0.5 mg//kg to FVB WT and mdr1a/b KO mice to evaluate if pomalidomide is a substrate of Pgp. At the time of this work, no publication was reported regarding pomalidomide as a substrate of Pgp. Non- compartmental analysis in WinNonlin was employed to estimate PK parameters. PK plots and PK parameters for both WT and KO mice are displayed in Figure 2.3 and Table 2.4.

The Cmax was observed at 5 mins (the earliest sample collection time). A second peak was observed around 1.5 hrs after a ‘dip’ at about 30mins for both WT and KO groups, which suggested potential enterohepatic recycling; the ‘dip’ and second peak was not observed with lenalidmide. Cmax in KO group is about 3 times higher compared to that in WT the group, and the total drug exposure was close to 3 fold comparing KO to WT mice. The clearance of KO mice was therefore decreased by 64% (0.40 L/hr/kg and 1.09 L/hr/kg for

KO and WT mice, respectively). Other PK parameters, half-life and volume of distribution, could be found in Table 2.4.

2.3.2.2 Pomalidomide in Brain

Similar to lenalidomide study, to evaluate how pomalidomide brain penetration is affected by Pgp, brain samples were also collected and determined from both WT and

KO mice in intravenously administrated groups (0.5 mg/kg pomalidomide, 55 mice per group). Mean maximum brain concentration in KO mice was 1.3 fold that of WT, reaching 1117 vs 869 pmol/g, respectively. Maximum concentrations were also achieved

27 earlier in KO mice at 0.08 hr relative to 0.17 hr in WT mice. Estimated AUClast were

2134 hr*pmol/g for KO mice and 1464 hr*pmol/g for WT mice (Table 2.5). The increased drug exposure was consistent with the hypothesized decrease in clearance in mdr1a/b knock mice compared to normal mice. A longer half-life was observed in KO compared to WT mice (KO vs WT, 1.86 vs 1.45 hr, respectively).

2.3.3 Ratio of Brain to Plasma

To evaluate the amount of lenalidomide that could penetrate the blood brain barrier, brain to plasma ratios were calculated in KO and WT groups, respectively. The ratios of Tmax in brain/plasma were 3.96 and 2.04 for WT and KO, respectively (Table 2.3). Their results

(>1) indicated that first, lenalidomide needs more time to penetrate various barriers to reach brain. Second, lenaliomide can reach brain faster in KO than WT mice, which might be caused by mdr1a/b knocking out. Brain to plasma ratios for AUClast were similar in KO (0.17) and WT (0.19) mice

Brain to plasma ratios for pomalidomide PK paramters were also calculated within each group. Brain to plasma ratios for Tmax were 1 for both WT and KO mice. In WT mice, brain to plasma ratios for Cmax and AUClast were 0.81 and 0.89, respectively (Table 2.6).

In the KO group, brain to plasma ratios for Cmax and AUClast were 0.34 and 0.48, respectively. Notably, while these ratios suggested a lower proportion of total pomalidomide reached the brain in KO vs. WT mice, the absolute concentration and

AUC values in brain of KO mice were similar or even higher than those in WT mouse.

The increased concentrations of pomalidomide in plasma in KO vs. WT mice yielded the lower brain to plasma ratios for Cmax and AUC.

A similar study with digoxin, a well-known substrate of Pgp, was completed by Mayer and colleagues [116]. [3H]-digoxin was administered to wild type and mdr1a/b (-/-) mice at a dose of 0.2 mg/kg. After a single IV injection, [3H]-digoxin was accumulated in Pgp knockout mice brain for over 3 days and reached concentrations that were 200 fold higher than those in wild type mice [116]. Based on this study and Pgp distribution in the blood- brain barrier, higher concentration of lenalidomide or pomalidomide in Pgp KO mice was initially expected. However, a high KO/WT ratio of drug exposure in brain was not observed. Furthermore, the KO/WT ratios of exposures in brain (Cmax and AUClast) were lower than the same ratios in plasma.

In summary, two observations were unexpected. First, we anticipated brain concentrations of these two drugs in KO mice would be much higher than those in WT mice due to a compromised blood-brain barrier caused by the lack of Pgp in KO mice.

Brain AUCs were in fact higher in KO vs. WT for lenaliomide (KO/WT ratio 1.12) and pomalidomide (KO/WT ratio 1.46). However, these differences in brain concentration between KO and WT were not as large as anticipated based on similar studies with other

Pgp substrates in mdr1a/b (-/-) mice. Also, with the similar structures of lenalidomide and pomalidomide (Figure 1.1), we expected these two drugs would have similar PK in both

WT and KO mice. However, the drug exposure of pomalidomide in brain was

29 significantly higher than that of lenalidomide, especially in KO mice (KO mice: pomalidomide vs lenaliomide, 2134 hr*pmol/g vs 219 hr*nM).

These substantial differences in PK between these two structurally very similar IMiDs may be explained by various factors. First, we considered the possibility that these two

IMiDs have distinctly different membrane diffusion characteristics. The parallel artificial membrane permeability assay (PAMPA) was then used to measure the permeability of these two drugs separately. The PAMPA method employs an artificial membrane to mimic the phospholipid composition of cell membranes, which enables direct evaluation of passive permeability of compounds without confounding active or facilitated transport mediated by transporters and receptors found on cell membranes. Our preliminary results from the PAMPA assay suggested there is no significant difference in passive transport permeability of these two drugs. These results will be replicated in subsequent studies to confirm these initial findings.

Another factor that may explain the observed differences in PK between lenalidomide and pomalidomide is that one or more transporters other than Pgp are involved in their apparent differential membrane penetration. According to known transporter distribution in various tissues [94], some transporters are highly expressed in brain, including influx transporters like OATP1A2, OATP2B1 and efflux transporters, MRP4, MRP5, Pgp and

BCRP. Since prior studies indicated lenalidomide is not a substrate of OAT1, OAT3,

OATP2, OCT1, MRP1, MRP2 and MRP3 [91], we have narrowed the list of transporters that would likely be involved to OATP1A2, MRP4-5 and BCRP. Among these, BCRP is

30 considered an important efflux transporter involving drug elimination and resistance, and it is a major component of the blood-brain barrier. For these reasons, we chose to focus first on BCRP as discussed in the next chapter.

PK Parameters Unit WT KO KO/WT

Tmax hr 0.08 0.08 1.00 Cmax nM 2092 1535 0.73 AUClast hr*nM 1044 1296 1.24 CL L/hr/kg 1.83 1.48 0.81 Vss L/kg 1.12 1.59 1.42 t1/2 hr 0.57 0.82 1.43 Sample analysis and PK parameter estimates were completed by Dr. Rozewski [117] Table 2.1 PK parameters for lenalidomide in mouse plasma after IV dosing with 0.5 mg/kg

PK Parameters Unit WT KO KO/WT

Tmax hr 0.33 0.17 0.52 Cmax pmol/g 68.7 88.8 1.29 AUClast hr*pmol/g 194 219 1.12 t1/2 hr 5.40 4.38 0.81

Table 2.2 PK parameters for lenalidomide in mouse brain after IV dosing with 0.5 mg/kg

Brain to plasma ratio WT KO

Tmax 3.96 2.04 Cmax 0.03 0.06 AUClast 0.19 0.17 t1/2 9.39 5.31

Table 2.3 Ratios of brain to plasma PK parameters for lenalidomide (IV, 0.5 mg/kg)

PK Parameters Unit WT KO KO/WT

Tmax hr 0.17 0.08 0.47 Cmax nM 1067 3243 3.04 AUClast hr*nM 1642 4448 2.71 CL_obs L/hr/kg 1.09 0.40 0.36 Vz_obs L/kg 2.93 1.19 0.41 t1/2 hr 1.86 2.10 1.13

Table 2.4 Non-compartmental PK parameters for pomalidomide in mouse plasma after IV dosing with 0.5 mg/kg

PK Parameters Unit WT KO KO/WT

Tmax hr 0.17 0.08 0.47 Cmax pmol/g 869 1117 1.29 AUClast hr*pmol/g 1464 2134 1.46 t1/2 hr 1.45 1.86 1.28

Table 2.5 Non-compartmental PK parameters for pomalidomide in mouse brain after IV dosing with 0.5 mg/kg

Brain to Plasma Ratio WT KO

Tmax 1.00 1.00 Cmax 0.81 0.34 AUClast 0.89 0.48 t1/2 0.78 0.88

Table 2.6 Ratios of brain to plasma PK parameters for pomalidomide (IV, 0.5 mg/kg)

Figure 2.1 PK profile of lenalidomide in mouse plasma after IV dosing with 0.5 mg/kg

Data was generated by Dr. Rozewski [117].

Figure 2.2 Ratios of lenalidomide plasma PK parameters (KO/ WT) after IV dosing with 0.5 mg/kg

Data was generated by Dr. Rozewski [117].

Figure 2.3 PK profile of pomalidomide in mouse plasma after IV dosing with 0.5 mg/kg

Figure 2.4 Ratios of pomalidomide plasma PK parameters (KO/ WT) after IV dosing with 0.5 mg/kg

Figure 2.5 PK profile of lenalidomide in mouse brain after IV dosing with 0.5 mg/kg

Figure 2.6 PK profile of pomalidomide in mouse brain after IV dosing with 0.5 mg/kg

CHAPTER 3

LENALIDOMIDE AND POMALIDOMIDE IN VITRO

TRANSPORTER STUDY

3.1 Introduction

3.1.1 Breast Cancer Resistance Protein

The in vivo study of lenaliomide and pomalidomide in FVB WT and mdr1a/b KO mice in

Chapter 2 showed us two interesting things: (1) Pomalidomide concentrations in brain tissue was much higher than lenalidomide brain concentrations. (2) The brain to plasma ratio of drug exposure was smaller than what we expected based on the previous similar studies of other Pgp substrates, such as digoxin. The first possible cause of the large difference in brain penetration between lenalidomide and pomalidomide is a potential inherent permeability difference of these two drugs. However, our preliminary data of

PAMPA indicate lenalidomide and pomalidomide have similar passive transport permeability through artificial membranes. This led us to consider other transporters, e.g other efflux transports or influx transporters relevant in the blood-brain barrier, might be involved in the disposition of lenalidomide or pomalidomide. Studies from Celgene evaluating other transporters in the OAT, OATP, OCT and MRP families, showed that

44 lenalidomide is not a substrate of OAT1, OAT3, OATP2, OCT1 and MRP1-3 [91]. Based on these data, we chose to focus on another important efflux transporter, the breast cancer resistance protein, BCRP.

BCRP is the second member of ATP-binding cassette (ABC) sub-family G (encoded by

ABCG2). It is a 72 kDa plasma membrane protein with 655-amino acids. The name

BCRP originated from the resistance breast cancer cell lines MCF-7/AdrVp in which

BCRP was first identified in 1998 [118]. In these studies, the MCF-7/AdrVp cell lines did not express Pgp or MRP1 but were resistant to several chemotherapeutic drugs, which ignited interest to investigate the role of BCRP in drug resistance. Previous leukemia clinical trial studies have indicated the possible role of BCRP as an efflux transporter involved in drug resistance [119, 120]. The regular function of BCRP is to eliminate toxins or xenobiotics, including drugs. The expression of BCRP in different organs can affect the absorption, distribution, metabolism and excretion of drugs. BCRP is enriched in a population of stem cells, known as the “side population” [121-122], and this BCRP expression protects them from xenobiotics. BCRP is also highly expressed in the small intestine (drug absorption), the liver and kidney (drug metabolism and elimination), and the blood-brain barrier (drug distribution).

3.1.2 Cell Uptake and Transepithelial Bi-direction Permeability Assay

To evaluate if lenalidomide or pomalidomide were substrates of BCRP, cell uptake and transwell permeability (transepithelial bi-direction permeability) assays were employed.

The cell lines, MDCKII/WT, MCDKII/Pgp and MDCKII/BCRP were used in these cell

45 uptake studies. A sensitive and validated LC-MS/MS method was used to measure the amount of drugs accumulated in the cells [114,115].

The transwell permeability assay was used to measure the bi-directional permeability of lenalidomide and pomalidomide in cells. Membrane filters were first used as cell growth supports in the studies of transfilter metanephric induction by Grobstein in 1953 [123].

Over several years of study, permeable supports over solid and impermeable cell growth substrates have shown significant advantages for cell growth and evaluation of transport properties. Currently, permeable supports with microporous membranes are a standard method for specialized cell growth and the study of the movement of exogenous and endogenous components through epithelial cell layers. These permeable supports are particularly beneficial for polarized cells since the supports allow cells to uptake and secrete molecules on both apical and basolateral surfaces [124].

Transwell inserts, on which the cells grow, are available in a range of membrane materials, pore size and diameters, and selection of appropriate transwell membranes and pore sizes can be critical for assay success. Three available membrane materials are polyester (PET), polycarbonate (PC) and collagen-coated polytetrafluoroethylene (PTFE).

The properties of these three membranes are list in Table 3.1. Generally, PET membranes are microscopically clear membrane that is suitable for visual check of tissue culture treated for optimal cell attachment and growth. PC membrane is treated for general optimal cell attachment. Cell attachment and spreading are greatly promoted in transwell inserts with PTFE membrane, and cells can be visualized during culture. Pore sizes are available from 0.4 to 3.0 µm in PTFE and 0.4 to 8.0 µm in the other two materials. The 46 smallest pore size, 0.4 µm, is mainly used in drug transport studies. Membranes with pore size 3.0 µm or lager are usually used in cell invasion, motility and chemotaxis studies.

For our study, transwells with 0.4 μm pore PC membrane inserts were chosen as the material with the optimal combination of cell adhesion, growth and small-molecule transport properties.

3.2 Materials and Methods

3.2.1 Chemicals and Solvents

Lenalidomide was purified from commercial capsules, and pomalidomide was synthesized using a modification of our previously published methods [113]. The purity of both drugs were confirmed >95% by nuclear magnetic resonance and HPLC-UV analysis. Hesperetin was purchased from Sigma-Aldrich (St. Louis, MO). Other solvents used in LC-MS/MS analysis were all HPLC grade and purchased from Thermo Fisher

Scientific (Waltham, MA).

Suppliers purchased from Life Technologies (Carlsbad, CA) for cell culturing include

Dulbecco’s modified Eagle’s medium (DMEM), penicillin (10,000 units/mL)- streptomycin (10,000 μg/mL), 0.25% Trypsin-EDTA, fetal bovine serum (FBS), L- glutamine (200 mM, 100×), PBS versene solution (0.48 mM) and Hanks’ balanced salt solution (HBSS). Bovine serum albumin (BSA), DMSOgenistein and fumitremorgin C

(FTC) were purchased from Sigma-Aldrich (Saint Louis, MO). Transwells with 0.4-μm pore polycarbonate membrane insert (6.5 mm in diameter) were from Corning (Lowell,

MA).

3.2.2 Stock Solutions and Handling of Aqueous Solutions

Lenalidomide and pomalidomide are unstable in aqueous solutions due to rapid hydrolysis. At pH 7.0, lenalidomide is completely hydrolyzed in phosphate buffered saline within 12-24 hours (unpublished data from our lab). Stock solutions of lenalidomide produced in DMSO have been shown to be stable for several months at

80 °C and for several weeks at room temperature. Both agents are soluble up to 10 mg/mL or greater in DMSO and only up to ~ 3 mg/mL in buffered aqueous solution at pH ~2 according to our previous tests. Solubility and stability both decrease in aqueous solution as pH increases from 2 to 7. Lenalidomide stability improves in the presence of protein (e.g. in plasma or in buffer with serum or albumin supplement). Therefore, all sample processing steps of lenalidomde or pomalidomide in aqueous media were performed as quickly as possible and maintained at low temperature.

3.2.3 Cell Culture

MDCKII/WT, MCDKII/Pgp and MDCKII/BCRP cell lines were purchased form The

Netherlands Cancer Institute, Amsterdam, the Netherlands. Cells were grown in DMEM containing 2mM glutamine, 10% FBS, 100 units/mL of penicillin and 100 μg/mL of streptomycin, and were cultured in 5% CO2 and 95% air at 37 °C. Viable cells were counted using trypan blue exclusion.

3.2.4 Cell Uptake Assay

MDCKII/WT, MDCKII/BCRP and MDCKII/Pgp cells were revitalized and cultured for several days prior to use in experiments. Pre-existing media were removed from cells, and cell pellets were washed with PBS before dosing solutions were added. Lenalidomide 48 dosing solutions were prepared freshly using culture media with 4% BSA (stabilizing lenalidodmide and pomalidomide). The final concentrations for lenalidomide dosing solution were 0.1, 0.3 and 3 μM, respectively. Cells were incubated for 2 hours at 37 °C, and incubations were ceased by placing samples on ice for 10 minutes. Dosing media were then removed and cell pellets were washed twice with cold (4 °C) versene buffer.

Approximately 107 cells were harvested for measuring the intercellular level of lenalidomide. Triplicates were collected for each sample. Cell pellets were re-suspended in 150 µL cold (4 °C) versene buffer, 50 µL was used for protein concentration measurement using the bicinchoninic acid assay, and 100 µL of samples were used for lenalidomide or pomalidomide quantification.

Blank cell pellets (wild type parent cell) were also collected under the same condition as the intracellular accumulation assay, only without any drug treatment, to prepare standard curves and QC samples for LC-MS/MS measurement to control for matrix effects.

3.2.5 Transepithelial Bi-directional Permeability Assay

MDCKII/WT, MDCKII/BCRP and MDCKII/Pgp cells were seeded onto polycarbonate membrane Transwell inserts (Corning Co., Corning, NY) at a density of 0.85 x 105 cells per well. Monolayer transepithelial electric resistance (TEER) was measured using the epithelial volt-ohm-meter EVOM2 from World Precision Instruments before and after each experiment. Transport studies were performed on cell monolayers 3-4 days after seeding when TEER values reached around 110 for a 24-well plate. Cell monolayers were washed with HBSS (pH 7.4) twice before the assay, and transport was initiated with the application of the test drug to the donor side [either the apical (A) or basal (B) 49 chamber]. Volumes of the A and B chambers were 0.2 and 0.6 mL, respectively. After incubation at 37°C for a designated time period, aliquots of 100 µL were collected from the receiver sides, and concentrations of the test drug were determined using LC-MS/MS methods. Triplicates were performed in each assay.

Study 1 aimed to test if lenalidomide is a substrate of BCRP using MDCKII/WT and

MDCKII/BCRP cells under the conditions of multiple time points (5, 10, 30, 60 and 120 min). Subsequently, the first assay was repeated but at with inclusion of shorter incubation time points (1.5, 3, 5, 10 and 30 min). The evaluation of whether pomalidomide is a substrate of Pgp and BCRP was also included in study 2. Based on the results from the first two experiments, study 3 was performed with 10 mins incubation time. Genistein, a known BCRP substrate, was used as a positive control in this study as well as FTC, a BCRP inhibitor, as a negative control. The detailed conditions for these three assays are described below:

1. Study 1, 5 to 120 min incubations with lenalidomide

Lenalidomide (10 μM) at 5, 10, 30, 60 and 120 min in MDCKII/WT and

MDCKII/BCRP

2. Study 2, 1.5 to 30 min incubations with lenalidomide and pomalidomide a. Lenalidomide (10 μM) at 1.5, 3, 5, 10 and 30 min in MDCKII/WT and

MDCKII/BCRP b. Pomalidomide (10 μM) at 1.5, 3, 5, 10 and 30 min in MDCKII/WT,

MDCKII/BCRP and MDCKII/Pgp cells 50

3. Study 3, 10 min incubation with genistein, lenalidomide and pomalidomide with

(w/) and without (w/o) FTC a. Genistein (3 μM) w/ and w/o FTC (5 μM ) at 10 min in MDCKII/WT and

MDCKII/BCRP b. Lenalidomide (10μM) w/ and w/o FTC (5 μM) at 10 min in MDCKII/WT and

MDCKII/BCRP c. Pomalidomide (10μM) w/ and w/o FTC (5 μM) at 10 min in MDCKII/WT and

MDCKII/BCRP

The apparent permeability coefficients (Papp, expressed as cm/sec) for both apical to basolateral (A→B) and basolateral to apical (B→A) directional transport were calculated according to the following equation: Papp = (ΔQ/Δt)×(1/60)×(1/S)×(1/C0), where S is the insert membrane surface area, expressed in cm2; ΔQ/Δt is the linear flux of lenalidomide across the MDCKII monolayer from donor to receiver compartment as a function of time

(pmol/min); and C0 is the initial concentration in the donor chamber (μM). The efflux ratio (ER) was determined as the ratio of Papp in the secretory (B to A) over Papp in the absorptive (A to B) direction according to the equation: ER = (Papp, B→A)/ (Papp, A→B).

3.2.6 LC-MS/MS

The quantifications of lenalidomide and pomalidomide were achieved using validated

LC-MS/MS methods from published literature [88, 89].

3.2.7 Sample Preparation

3.2.7.1 Standard and Quality Control Samples Preparation

The preparation of standard and QC samples were similar to ‘2.2.5.1 Standard and

Quality Control Samples preparation’ section in Chapter 2 but with blank cell pellets for the cell uptake assay and blank HBSS for the transwell assay as matrices to prepare standard and QC samples. The linear range was 0.3 to 3000 nM with concentrations at

0.3, 1, 3, 10, 30, 100, 300, 1000 and 3000 nM. QC samples at 3, 100 and 1000 nM as low, medium and high concentration levels were prepared in a similar way from an independently prepared stock solution.

3.2.7.2 Cell pellet samples:

Cell pellets were collected from the cell uptake assay. There were 10 million cells in each sample. LC-MS/MS sample preparation steps for these samples were: 10 µL of IS working solution (10 µg/mL) was spiked into each sample and followed by 1 mL acetonitrile for protein precipitation. The sample was vortex-mixed for 30 seconds and centrifuged at 18,000 g for 10 min at 4°C. Then the supernatant was transferred to a glass tube and evaporated under a gentle nitrogen gas stream. The residue was reconstituted with 120 µL 5% ACN with 0.1% FA. After centrifugation at 18,000 g for 10 min at 4°C,

20 µL of supernatant was injected into the LC–MS/MS system.

3.2.7.3 Cell medium samples

In the transwell permeability assay, HBSS medium from the receiver chamber was collected. After samples were thawed on ice, 10 µL of IS working solution (10 µg/mL) was spiked into 100 µL HBSS medium samples and 1 mL acetonitrile was added for 52 protein precipitation. The mixture was vortex-mixed for 30 seconds and centrifuged at

18,000 g for 10 min at 4°C. The following steps were the same as those in the cell pellet sample preparations.

3.2.8 Statistical Analysis

LC Quan Xcalibur software was used for LC-MS/MS system control and data processing.

Comparisons of non-compartmental pharmacokinetic parameters between groups were conducted using the Mann–Whitney U test (nonparametric t-test) and Wilcoxon signed rank test (nonparametric paired t-test).

3.3 Results and Discussion

3.3.1 Cell Uptake Assay

Drug concentrations used in the cell uptake assay were all clinically relevant concentrations. For lenalidomide we used 3 µM as a clinically equivalent dose based on previously published studies in AML and MM patients [14, 64]. Dose concentration of

0.3 µM was also used and deemed relevant for the lower doses used in chronic lymphocytic leukemia patients comparing to that used for AML or MM patients [80, 125].

For pomalidomide, the information for PK data in humans is limited. Based on the study of radio-labeled pomalidomide in healthy volunteers published by Celgene [16] and FDA guidance, we decided to use 0.1 µM as a clinically relevant dose of pomalidomide. To compare lenalidomide and pomalidomide, 0.1, 0.3 and 3 µM as the final concentrations were used in the cell uptake study for both drugs.

The final result was normalized by protein concentration in the unit of nmol/mg protein since the cell number was different in each sample. Results for lenalidomide intracellular drug concentrations are displayed in Table 3.2 and Figure 3.1. The intracellular concentrations in MDCKII/Pgp and MDCKII/BCRP cells were below the LLOQ (0.3 nM) at doses of 0.1 µM. Statistical analysis of the comparisons between MDCKII/WT and

MDCKII/Pgp and MDCKII/WT and MDCKII/BCRP cell lines showed the intracellular drug concentrations were significantly (p<0.05) different in different cell types (Figure

3.1). In Pgp or BCRP overexpressing cell lines, the intracellular drug concentrations were significantly lower than those in WT. This is consistent with our previous work with Pgp, and these results also suggest lenalidomide is a substrate of BCRP as well. Results for pomalidomide uptake are shown in Table 3.3. The intracellular concentrations were not measurable in the most samples at doses of 0.1 and 0.3 µM.

3.3.2 Transepithelial Bi-directional Permeability Assay

3.3.2.1 Study 1, 5 to 120 min incubations with lenalidomide

In this assay, MDCKII/WT and MDCKII/BCRP cell lines were seeded onto the transwell inserts. Ten micromolar (10 μM) of lenalidomide in HBSS was added into the donor side

(either apical or basolateral). Drug concentrations in the receiver side were measured by

LC-MS/MS. Papp B→A, Papp A→B, and ER were calculated subsequently based on LC-

MS/MS results (Table 3.4). The ER ratio of MDCKII/BCRP cell to MDCKII/WT suggested that lenalidomide is a substrate for BCRP (Figure 3.2). All BCRP/WT ER ratios (BCRP over expressed cell to wild type) were over 1, from 1.45 to 11.47. Within the incubation time points we chose, 30 mins showed the smallest difference regarding to

54 the ER ratios. However, the ER values for WT cells were well below 1. A second study was therefore conducted with different incubation times.

3.3.2.2 Study 2, 1.5 to 30 min incubations with lenalidomide and pomalidomide, respectively

For lenalidomide, similar to last experiment, the ER for MDCKII-BCRP over expressing cells were higher than that of WT (Table 3.5 and Figure 3.3), except the 30min data (also smallest ER difference between BCRP and WT in the last assay), which suggested that lenalidomide is a substrate of BCRP. The absolute ER values for WT MDCKII cells were still significantly lower than 1, except for the 30 minute time point.

For pomalidomide, comparing BCRP and WT data, ER were higher than that of WT at all 5 incubation times, which suggested that pomalidomide is also a substrate of BCRP

(Table 3.6 and Figure 3.4). For Pgp, ERs were higher than that of WT at all incubation times except 5 and 30 mins. Although our data was not sufficient to draw conclusions regarding the pomalidomide substrate status for Pgp given that at time points 5 and 30 mins, ER of MDCKII/BCRP cell were smaller than that of MDCKII/WT. However, the data from the mdr1a/b KO mouse study in the previous chapter and a recent report of pomalidomide in the Journal of Clinical Pharmacology [126] all indicated pomalidomide is a substrate of Pgp.

3.3.2.3 Study 3, 10 min incubation with genistein lenalidomide and pomalidomide w/ and w/oFTC, respectively

The major problem of the first two studies is that the ERs of MDCKII/ WT cell were below 1. Thus, in study 3, a known BCRP substrate, genistein (Genis), was included as a positive control. The ER of Genis in MDCKII/BCRP cell lines was much higher than that 55 of MDCKII/WT, which indicated our transwell system was functional (Table 3.9). FTC, a common inhibitor of BCRP was also used to further evaluate the transwell permeability

(Table 3.9). Both the MDCKII/WT and MDCKII/BCRP cells were pre-treated with FTC for 2hrs, then 3 µM of genistein was added into either apical or basolateral champter followed by 10mins incubation. Compared to genistein without FTC pre-treatment group, it is very obviously that the ER difference between WT and BCRP over-expressed cell lines was much smaller in the Genis+FTC group (Figure 3.5), which made this a very good control and demonstrated that the cell lines worked well. However, the problem was

ERs for MDCKII/WT were still below 1, which was basically consistent in all the samples (27 samples) we conducted in all three assays. In addition, when we compared these three studies with our previously published tranwell permeability assay [37], the difference in tranwell inserts materials and diameters might be a reason.

Comparing lenalidomide and lenalidomide plus FTC group (Table 3.7 and Figure 3.5), the ER difference decreased in the lenalidomide+ FTC group, similar to the positive control group, which suggested that lenalidomide is the substrate of BCRP. However, in the lenalidomide group, the ERwas larger in BCRP over-expressed MDCKII cell than that of WT group. Consider the variations of samples, no significant difference of ERs were seen in this group samples. Further evaluation was suggested for drawing solid conclusion. Similar to the previous study with lenalidomide, comparing pomalidomide and pomalidomide+ FTC group (Table 3.8 and Figure 3.5), the ER difference decreased in the pomalidomide+ FTC group, which suggested that pomalidomide is the substrate of

BCRP.

In summary, in this chapter, we aimed to evaluate if lenalidomide and pomalidomide were the substrates of Pgp and BCRP through in vitro cell uptake and transport studies.

Cell lines, MCKII/WT, MCDKII/Pgp and MDCKII/BCRP were used in these two studies.

Cell uptake studies showed significant lower intracellular accumulation of lenalidomide in Pgp and BCRP overexpressing cells compared to WT cells. This was consistent with the results from FVB mice study in Chapter 2 as well as our previous published data in one clinical trial [37], and it suggested BCRP may also play a role in lenalidomide efflux from cells. Results based on around 250 samples from transwell permeability assays suggested that BCRP could alter the permeability of lenalidomide and pomalidomide through epithelial membranes.

Table 3.1 Characteristics of Three Transwell Membranes*

* Transwell® Permeable Supports Selection and Use Guide, Corning, 2013

MDCKII MDCKII/Pgp MDCKII/BCRP

Dose Mean STD Mean STD Mean STD

0.1 µM 0.025 0.007 n.d. n.d.

0.3 µM 0.076 0.015 0.039 0.005 0.015 0*

3 µM 0.496 0.154 0.199 0.022 0.085 0.012

Table 3.2 Lenalidomide intracellular drug concentrations (nmol/mg protein) in cell uptake study n.d.: not detectable. STD: standard deviation

0*: STD was calculated based on triplicate of each sample. With 0.3μM lenalidomide incubation, only one

MDCKII/BCRP sample was measurable, and the other two samples were not detectable. Thus, the STD of intracellular drug concentration for MDCKII/BCRP cells at 0.3 μM was 0.

MDCKII MDCKII/Pgp MDCKII/BCRP

Dose Mean STD Mean STD Mean STD

0.1 µM n.d. n.d. n.d.

0.3 µM n.d. 0.022 0.008 n.d.

3 µM 0.084 0.015 0.304 0.146 0.073 0.007

Table 3.3 Pomalidomide intracellular drug concentrations (nmol/mg protein) in cell uptake study n.d.: not detectable. STD: standard deviation

MDCKII/WT MDCKII/BCRP

A to SD B to A A to B Efflux B to A B Efflux of ER ratio Time (min) Papp SD Papp SD Ratio SD of ER Papp SD Papp SD Ratio ER (BCRP/WT)

5 1.52 0.93 4.76 5.28 0.32 0.40 6.19 4.10 1.69 1.46 3.66 3.99 11.5

10 1.59 0.54 3.17 1.88 0.50 0.34 2.43 0.21 1.12 1.17 2.17 2.27 4.33

30 2.86 1.21 3.83 4.69 0.75 0.97 3.72 1.96 3.44 3.94 1.08 1.36 1.45

60 1.78 0.64 4.82 5.14 0.37 0.42 3.42 0.52 3.88 1.48 0.88 0.36 2.39

120 2.98 0.39 5.83 2.81 0.51 0.26 4.89 0.93 1.89 1.10 2.59 1.58 5.06

Average 2.15 4.48 0.49 4.13 2.40 2.08 4.24

SD 0.71 1.02 1.45 1.19

-7 Table 3.4 Papp value (*10 cm/s) and ERs of lenalidomide in MDCKII/WT and MDCKII/BCRP cells with 5 to 120 min

incubations

Results were from study 1, 5 to 120 min incubations with lenalidomide in MDCKII/WT and MDCKII/BCRP cells. SD: standard deviation.

MDCKII/WT MDCKII/BCRP

A to Time B to A A to B Efflux SD of B to A B Efflux SD of ER ratio (min) Papp SD Papp SD Ratio ER Papp SD Papp SD Ratio ER (BCRP/WT)

1.5 0.97 0.21 20.3 23.1 0.05 0.06 1.24 0.40 2.01 1.30 0.62 0.45 12.9

3 1.04 0.21 6.65 4.97 0.16 0.12 1.10 0.68 3.21 2.88 0.34 0.37 2.19

5 0.67 0.13 5.01 5.56 0.13 0.15 1.48 0.64 2.82 3.56 0.52 0.70 3.92

10 0.89 0.58 1.98 1.85 0.45 0.51 1.84 2.27 1.14 1.17 1.61 2.59 3.59

2 30 2.24 1.79 1.17 0.42 1.92 1.68 1.12 0.96 1.44 1.75 0.78 1.16 0.41

Average 1.16 7.03 0.54 1.36 2.12 0.78 1.43

SD 0.62 7.77 0.31 0.88

-7 Table 3.5 Papp value (*10 cm/s) and ERs of lenalidomide in in MDCKII/WT and MDCKII/BCRP cells with 1.5 to 30 min

incubations

Results were from study 2, 1.5 to 30 min incubations with lenalidomide in MDCKII/WT and MDCKII/BCRP cells. SD: standard deviation.

MDCKII/WT MDCKII/BCRP

SD Time B to A A to B Efflux of B to A A to B Efflux SD of ER ratio (min) Papp SD Papp SD Ratio ER Papp SD Papp SD Ratio ER (BCRP/WT)

1.5 73.55 46.7 404 249 0.18 0.16 174 153 163 116 1.07 1.21 5.88

3 216 32.8 419 97.70 0.52 0.14 177 34.5 194 25.0 0.91 0.21 1.77

5 362 61.7 147 61.62 2.46 1.11 364 42.3 91.4 8.53 3.99 0.59 1.62

10 201 4.45 319 18.61 0.63 0.04 316 79.1 188 11.0 1.68 0.43 2.66

30 138 13.7 116 10.10 1.19 0.16 200 43.0 97.4 14.5 2.05 0.54 1.72

63 Average 198 281 1.00 246 147 1.94 2.73

SD 107 142 87.8 49.4

Continued

-7 Table 3.6 Papp value (*10 cm/s) and ERs of pomalidomide in MDCKII/WT, MDCKII/Pgp and MDCKII/BCRP cells with

1.5 to 30 min incubations

Results were from study 2, 1.5 to 30 min incubations with pomalidomide in MDCKII/WT, MDCKII/Pgp and MDCKII/BCRP cells.

SD: standard deviation.

Continued Table 3.6

MDCKII/Pgp

ER ratio Time (min) B to A Papp SD A to B Papp SD Efflux Ratio SD of ER (Pgp/WT)

1.5 42.6 47.9 138 105 0.31 0.42 1.70

3 96.4 17.7 157 30.2 0.62 0.16 1.19

5 205 85.3 152 80.4 1.35 0.91 0.55

10 162 6.03 124 37.6 1.31 0.40 2.08

30 77.5 7.75 69.5 21.1 1.11 0.36 0.93

Average 117 128 0.94 1.29

SD 65.6 35.0

MDCKII/WT MDCKII/BCRP

SD SD B to A A to B Efflux of B to A A to B Efflux of ER ratio Time (min) Papp SD Papp SD Ratio ER Papp SD Papp SD Ratio ER (BCRP/WT)

WT 110 40.0 66.4 27.5 1.66 0.91 90.9 25.5 87.6 41.0 1.04 0.57 0.63

WT+FTC 63.7 17.8 53.7 9.07 1.19 0.39 71.0 17.2 67.3 25.0 1.05 0.47 0.89

Average 83.4 60.0 1.37 77.6 66.1 1.24 0.93

SD 23.9 6.35 11.5 22.1

-7 Table 3.7 Papp value (*10 cm/s) and ERs of lenalidomide w/ and w/o FTC in transwell permeability assay

Results were from study 3, 10 min incubation with lenalidomide in MDCKII/WT and MDCKII/BCRP cells under the conditions w/ and w/o FTC,

respectively. SD: standard deviation.

MDCKII/WT MDCKII/BCRP

SD A to SD B to A A to B Efflux of B to A B Efflux of ER ratio Time (min) Papp SD Papp SD Ratio ER Papp SD Papp SD Ratio ER (BCRP/WT)

Pomalidomide 648 48.0 395 50.5 1.64 0.24 818 56.0 307 6.37 2.66 0.19 1.62

Pomalidomide+FTC 671 136 380 150 1.77 0.78 636 109 344 30.9 1.85 0.36 1.05

Average 592 361 1.63 664 359 1.93 1.17

SD 117 47.08 142 60.4

-7 Table 3.8 Papp value (*10 cm/s) and ERs of pomalidomide w/ and w/o FTC in transwell permeability assay

Results were from study 3, 10 min incubation with pomalidomide in MDCKII/WT and MDCKII/BCRP cells under the conditions w/ and w/o FTC,

respectively. SD: standard deviation.

MDCKII/WT MDCKII/BCRP

SD B to A to SD B to A A to B Efflux of A B Efflux of ER ratio Time (min) Papp SD Papp SD Ratio ER Papp SD Papp SD Ratio ER (BCRP/WT)

Genis 38.4 13.0 136 9.63 0.28 0.10 232 101 43.1 19.80 5.38 3.41 19.06

Genis+FTC 81.8 35.3 159 27.10 0.51 0.24 129 54.5 98.1 24.60 1.31 0.65 2.56

Average 60.1 148 0.40 181 70.6 3.35 10.8

SD 30.7 16.3 72.83 38.9

-7 Table 3.9 Papp value (*10 cm/s) and ERs of genistein w/ and w/o FTC in transwell permeability assay

Results were from study 3, 10 min incubation with genistein in MDCKII/WT and MDCKII/BCRP cells under the conditions w/ and w/o FTC,

respectively. SD: standard deviation.

Figure 3.1 Lenalidomide cell uptake (nmol/mg protein) in MDCKII cell lines

Figure 3.2 ERs of lenalidomide in MDCKII/WT and MDCKII/BCRP cells with 5 to

120 min incubations

Figure 3.3 ERs of lenalidomide in MDCKII/WT and MDCKII/BCRP cells with 1.5 to 30 min incubations

Figure 3.4 ERs of pomalidomide in MDCKII/WT, MDCKII/Pgp and

MDCKII/BCRP cells with 1.5 to 30 min incubations

Figure 3.5 ERs of genistein, lenalidomide and pomalidomide in MDCKII/WT and MDCKII/BCRP cells after 10 min

incubation under the conditions w/ and w/o FTC, respectively.

CHAPTER 4

PHARMACOKINETICS AND PHARMACODYNAMICS OF

LENALIDOMIDE IN A PHASE I CLINICAL TRIAL FOR THE

TREATMENT OF ACUTE MYELOID LEUKEMIA

4.1 Introduction

4.1.1 Pharmacokinetic study of lenalidomide in OSU10016

Lenalidomide (Revlimid®, Celgene), with its unique immunomodulatory, anti- angiogenic and anti-neoplastic properties, is approved by FDA for treatment of MM and myelodysplastic syndromes. However, lenalidomide is increasingly evaluated and used in therapeutic regimens for numerous hematologic and solid cancers. Lenalidomide alone and in combination presents serious and potentially life-threatening toxicities, such as venous thromboembolism, myelosuppression, tumor flare, and secondary malignancies.

So far, causes for the significant variability of lenalidomide in efficacy and toxicity are still poorly understood.

At OSU, there are currently ten active lenalidomide clinical trials including its usage in the treatments for hodgkins lymphoma, AML, CLL and MM etc. Our group has reported an apparent clinical drug-drug interaction of lenalidomide with temsirolimus through Pgp 73 in one of these clinical trials for the treatment of relapsed MM patients [37]. The study in this chapter will focus on another clinical trial, a phase I study of lenalidomide in combination with conventional chemotherapy (idarubicin and cytarabine) for the treatment of AML (trial OSU10016). Patients enrolled in this trial were divided into two cohorts. Patients in cohort 1 were relapsed or refractory AML patients, while patients in cohort 2 were treatment-naïve patients who had never received treatment for their disease prior to this trial. The PK parameters comparison between the two cohorts (relapsed vs treatment naïve) was evaluated to see if previous treatment would affect PK behavior of lenalidomide. Since idarubicin used in this trial is also a Pgp substrate [127, 128], it was necessary to consider a potential drug-drug interaction between lenalidomide and idarubicin, which could potentially impact whole body disposition and/or tumor cell penetration of these agents.

4.1.2 Pharmacodynamic study of lenalidomide in OSU10016

4.1.2.1 AML, miR-181a and CEBPA

AML, characterized by the accumulation of immature myeloid cells in BM and interference with normal function of blood cells, is the most common acute leukemia and accounts for 1.2% of cancer deaths in the U.S [54]. Studies in the past 15 years found that cytogenetics of the leukemic cell play a very important role in AML prognosis [55-58].

Cytogenetically normal acute myeloid leukemia (CN-AML), up to around 45% of cases, shows an intermediate risk in clinical outcomes with an approximate 48% 5-year survival rate and almost 50% relapse rate [59].

MicroRNAs (miRNAs) are small non-coding RNAs that can result in gene silencing by pairing with complementary sequences in messenger RNAs (mRNAs) and causing translational repression or degradation of target mRNAs. This class of genes has been shown to play an important role in carcinogenesis [129]. miR-181a, which is involved in regulating B cell development, sensitizing T cell to peptide antigens and early steps of hematopoiesis, has tumor suppressor activity in multiple cancers, like CLL [130], gliomas [131], AML [131, 132] and astrocytomas [133]. The most recent studies of miR-181a in AML indicated the association of miR-181a expression and favorable clinical outcomes in CN-AML patients as well as patients with cytogenetic abnormalities [132,134,135]. Therefore, miR-181a could be used as a PD biomarker for clinical response prediction.

Further study indicated miR-181a expression is directly modulated by the C/EBPα-P30 isoform [136]. Patients with N-terminal CEBPA mutations leading to truncated C/EBPα-

P30 had high miR-181a levels and improved outcomes [137]. This observation has led to the evaluation of compounds that can modulate C/EBPα protein expression to improve clinical outcomes of AML patients with wild-type CEBPA.

4.1.2.2 Lenalidomide, C/EBPα-P30 and miR-181a

Mouse xenograft studies indicated lenalidomide alone could up-regulate miR-181a expression and decrease tumor size in xenografted mice with AML tumors [117]. An ex vivo study indicated that lenalidomide can enhance translation of CEBPA and subsequently up-regulate miR-181a expression [137]. At OSU, lenalidomide was evaluated as a chemotherapy sensitizer in trial OSU10016, a phase I study of

75 lenalidomide in combination with conventional chemotherapy (idarubicin and cytarabine) for the treatment of AML. Preliminary data from a small subset of 6 patients (pts) indicated increased miR-181a expression after lenalidomide treatment was greater in patients who achieved CR compared with those who did not [138]. The data from this small subset of patients displays the variability in miR-181a expression between patients.

4.1.2.3 Lenalidomide and Cereblon

The study of immunomodulatory drugs (IMiDs) mechanisms of action related to cereblon

(encoding gene CRBN) originated from thalidomide teratogenicity. Dr. Ito et al. found

CRBN combined with damaged DNA binding protein (DDB1) and Cul4A forms an E3 ubiquitin ligase [139]. Thalidomide binds to cereblon and inhibits the ubiquitin ligase activity and subsequently initiates the teratogenic effects of thalidomide [139]. Further studies of cereblon and IMiDs efficacy as antitumor agents showed that myeloma cells resistant to IMiDs frequently have down regulated cereblon [140-143]. Myeloma cells with high cereblon concentrations are associated with increased response to IMiDs [144,

145]. Increasingly more studies have shown that IMiDs binding to cereblon, mediating the E3 ligase and subsequent ubiquitination and proteasome degradation resulted in diverse clinically relevant effects [140, 146-148]. One study showed cereblon expression is required for lenalidomide and pomalidomide antimyeloma effect, which appeared to be mediated through cereblon downstream target, interferon regulatory factor 4 (IRF4) [142].

Another recent published paper in Science indicated the cereblon dependent loss of

Ikaros family zinc finger protiens 1 and 3 (IKZF1 and IKZF3) are necessary for lenalidomide’s antitumor effect [149].

A recent study attempted to understand the mechanism of lenalidomide inhibiting the proliferation of CLL cells [150]. The study showed that lenalidomide could induce the expression of P21 (WAF1/Cip1) though cereblon, which would subsequently inhibit

CLL-cell proliferation. Furthermore, this proliferation inhibition was through a cereblon/P21 but P53-independent manner. Another study recently published [151] demonstrated cereblon expression could be used to predict clinical response in the treatment of CLL with thalidomide and fludarabine. The study was based on 27 patients.

About two-fold higher CRBN expression (gene expression) were found in responders group (PR or CR) rather than non-responders group. To evaluate drug resistance in myeloma, Ocio and colleagues developed a xenograft mouse model by injecting subcutaneous MM1S plasmacytomas [152]. The mice did not show cross-resistance to lenalidomide plus Dex and pomalidomide plus Dex combinations when they were given after a wash-out period which suggested different downstream key targets of cereblon,

Aiolos and Ikaros. However, the precise mechanism of how cereblon downstream targets are linked to IMiDs’ therapeutic effect is still not fully understood.

4.1.3 Correlation of PK and PD in OSU10016

Lenalidomide has been shown to up-regulate miR-181a expression, which is associated with more favorable clinical outcomes in AML by enhancing the translation of the promoter of miR-181a, the C/EBPα-P30 isoform. Our previous studies suggest that the efflux transporters, Pgp and BCRP, mediate lenalidomide elimination. Understanding how these transporters affect intracellular lenalidomide levels and their relationship with cereblon, C/EBPα and miR-181a expression in AML patient BM or PBMC may help to

77 explain inter-patient variability in outcomes from lenalidomide therapy. Therefore, we proposed a hypothesis connecting all the pieces of the puzzle together (Figure 4.6). In our hypothesis, the intracellular lenalidomide concentrations directly correlate with systemic lenalidomide concentration (plasma concentration) as well as membrane Pgp and BCRP expression. Patients with higher expression level of Pgp and BCRP would have less lenalidomide in cells if they have same systemic lenalidomide exposure. Lenalidomide binding to its direct target, cereblon, results in the inhibition of C/EBPα degradation followed by upregulated miR-181a expression, which is associated with clinical outcome.

Thus, patients with high intracellular level of lenaliomide would theoretically have favorable response. In summary, patients’ plasma lenalidomide PK and expression levels of Pgp, BCRP, cereblon, C/EBPα and miR-181a will all contribute to clinical response.

In this chapter, we aim to expand on work conducted in OSU10016, a phase 1 study of lenalidomide and conventional chemotherapy (idarubicin and cytarabine) in AML, to determine if the expression of Pgp and BCRP transporters may influence lenalidomide tumor penetration and outcomes from therapy. Specifically, we propose to evaluate the hypothesis that tumor cell miR-181a expression will be impacted through cereblon by expression of Pgp and BCRP (efflux) transporters, which collectively modulate intracellular lenalidomide levels. Furthermore, we hypothesize lenalidomide and idarubicin intracellular levels may be further modulated by drug-drug interactions since they have overlapping substrate specificity for the transporters under study.

4.2 Materials and Methods

4.2.1 Study Design

Patients enrolled in this study (age>18) were divided into two cohorts. Cohort 1 included relapsed or refractory AML patients, while cohort 2 enrolled treatment-naïve patients.

Patients with core binding factor AML (i.e., t (8; 21) or inv (16)) were not included in this study. Therefore, patients in this trial were all cytogenetically normal. Patients with chemotherapy or radiotherapy within 2 weeks, other active malignancies or other uncontrolled medical illness were also excluded. Informed written consent approved by

OSU institutional review board (IRB) was obtained from all patients prior to study entry.

During the study, unanticipated problems involving risks to subjects or others must be reported to OSU IRB.

In this clinical trial, one cycle included 21 days. Oral lenalidomide was given daily starting on day 1. Beginning on day 5, cytarabine was administered daily by intravenous

(IV) infusion till day 11. Idarubicin was also given as a 1 hr IV infusion daily on days 5-7.

When idarubicin and cytarabine were given, they were administered immediately after lenalidomide was taken. Lenalidomide was escalated at 5 mg increments starting from

25 mg. The detail treatment plan is illustrated in Table 4.1. Dose level 1 (25 mg) was the starting dose of the trial. Patients responding to this induction therapy received a follow up consolidation therapy. For patients from cohort 1, consolidation therapy included lenalidomide given on the same schedule and dose level as the induction therapy, and idarubicin was infused on days 5-6, while cytarabine was given on days 5-7. For cohort 2

79 patients in the consolidation therapy, lenalidomide was administrated on days 1-14, idarubicin on days 5-6 and cytarabine on days 5-9.

4.2.2 Sample Collection

Plasma samples were collected at pre-dose, 0.25, 0.5, 0.75, 1, 2, 2.5, 3, 4, 6, 8, 24 hrs after administration on cycle 1, day 1 (C1D1) and cycle 1 day 5 (C1D5). Lenalidomide plasma concentrations were measured in all plasma samples.

BM and peripheral blood mononuclear cell (PBMC) samples were collected on Day 0

(pre-treatment), Day 5 (prior to dosing), and post-treatment upon disease reassessment.

4.2.3 Sample Measurement

4.2.3.1 Lenalidomide quantification in Plasma Sample

Lenalidomide plasma concentrations were measured using a LC-MS/MS method within the OSU Comprehensive Cancer Center Pharmacoanalytical Shared Resource.Please refer to sections “2.2.4 LC-MS/MS” and “2.2.5 Sample Preparation” in Chapter 2 for the detailed LC-MS/MS conditions and plasma sample preparation method.

4.2.3.2 mRNA expression measurement in BM and PBMC Sample

Taqman quantitative real-time polymerase chain reaction (qPCR) method was employed to measure mRNA levels of our genes of interest in patient BM and PBMC samples on

Day 0 and Day 5. The method for gene expression quantification of ABCB1 has been previously published by our lab [37], and methods for quantification of ABCG2 gene expression has been successfully developed in our group. First, total RNAs were isolated from patient BM and PBMC samples using TRIzol®, and they were used as templates for

80 reverse transcription to get cDNA using the High Capacity RNA to cDNATM kit from

Invitrogen. Primers and probes for Taqman qPCR methods were purchased from Life technologies (Applied Biosystems Brand). ABI assay identification numbers for human

ABCB1, ABCG2, CEBPA, CRBN and GAPDH (internal control) were Hs00184500_m1,

Hs01053790_m1, Hs00269972_s1, Hs00372271_m1 and Hs02758991_g1, respectively. qPCR was performed in a total volume of 20 μL solution containing 2µL of cDNA obtained from reverse transcription according to the instruction of the TaqMan Gene

Expression Assay. All samples were quantified using the comparative CT method for relative quantification of gene expression, normalized to the internal control,

GAPDH [153, 154]. The miR-181a relative expression data in patient samples was provided by our collaborator, Dr. Hongyan Wang.

4.2.4 Statistical Analysis

Pharmacokinetic parameters for lenalidomide and idarubicin were estimated using non- compartmental methods in Phoenix WinNonlin 6.3.0.395 (Pharsight Corporation,

Mountain View, CA, USA). AUC was estimated with a linear up/log down method. The

PK parameters reported here include Cmax, Tmax, AUC, CL, t1/2 and Vz. Statistical analysis was completed using the R 2.15.2 software package for all PK parameter comparisons for lenalidomide. Comparisons of non-compartmental PK parameters between groups were conducted using the Mann–Whitney U test (nonparametric t-test) and Wilcoxon signed rank test (nonparametric paired t-test).

With data for mRNA expression levels of ABCB1 (encoding Pgp) and ABCG2 (encoding

BCRP), intracellular lenalidomide accumulation, and miR-181a expression, we compared 81 each variable to identify associations and test our hypotheses that patient tumor cells overexpressing Pgp and BCRP at baseline would have relatively low lenalidomide uptake and low miR-181a expression change. Due to small sample size, nonparametric t tests were used for comparison of two group samples (significance level at 0.05), e.g. pre- and post- treatment miR-181a expression. Linear regression (Pearson product-moment correlation coefficient) was employed to explore the association between main PK parameters, baseline expression and expression changes of ABCB1, ABCG2, CEBPA,

CRBN and miR-181a.

4.3 Results and Discussion

4.3.1 PK

PK samples were available from a total of 56 patients, including C1D1 (n=56) and C1D5

(n=46). On C1D1, 28 of 56 patients were from cohort 1, and the remaining 28 were from cohort 2. On C1D5, 24 patients were from cohort 1, and 22 patients were from cohort 2.

In the 56 patients on C1D1, 43 patients received 25 mg lenalidomide while the other 7 patents received 30 mg. On C1D5, 39 out of 46 patients received 25 mg lenalidomide, and the remaining 13 patents received 30 mg. Concentration data obtained from sample analysis was used to generate non-compartmental PK parameter estimates for all patients

(see Table 4.2). Figure 4.3 displays the average concentration-time curves with outliers at

24 hrs excluded (outliers were caused by patients receiving their day 2 or day 6 lenalidomide dose prior to trough blood sample collection). Lenalidomide Tmax estimates were shifted for one patient (3.02 hrs for C1D1 and 6 hrs for C1D5), which may suggest slower lenalidomide absorption for this patient compared to others. 82

Overall, the data appears similar to historical reports for lenalidomide. Comparisons of

PK parameters were evaluated between days, cohorts and dose levels. No significant

(p<0.05) differences were found within these comparisons. Table 4.3 and Table 4.4 shows PK parameter comparison results based on data from all patients. Although there appears to be a trend for longer half-life on Day 5 vs. Day1, these results were not statistically significant (p-values .073 and .064 for cohorts 1 and 2, respectively, Table

4.4). These data suggest there was no significant drug-drug interaction between lenalidomide and idarubicin. Interim analyses during the trial suggested there were differences in lenalidomide PK between cohorts 1 and 2, and these final results from non- compartmental analysis indicated AUC for cohort 2 was higher than that for cohort 1

(11546±6986 vs 9919±7546 hr*nM, p-value = .0518). As anticipated, there was no significant difference in PK between the 25 mg and 30 mg dose groups (Table 4.3 and

Table 4.4).

4.3.2 PD

Lenalidomide was given four days prior to administration of the traditional chemotherapy,

BM and PBMC samples were collected before (Day 0) and after 4 daily doses of lenalidomide (Day 5, prior to lenalidomide and chemotherapy dosing) for analysis for those patients who consented to this part of the protocol and had aspirable marrow. There were totally 26 patients’ BM samples collected on both Day 0 and Day 5. More than half,

16 of them were from cohort 1 (relapsed or refractory patients) and the other 10 from treatment-naïve patients. PBMC samples (both Day 0 and Day 5) were collected from 27

83 patients, with 13 from cohort 1 and 14 from cohort 2. There were 7 patients who had both

BM and PBMC samples collected.

Gene expression data from qPCR is presented in relative expression to internal control,

GAPDH. This enabled us to compare the data between cohorts. ABCB1, ABCG2,

CEBPA, CRBN and mir-181a expression data in BM for both cohorts are displayed from

Table 4.5 to Table 4.8. Gene expression data in PBMC for both cohorts are displayed in

Table 4.10 to Table 4.13.

Statistical comparisons were done within and between cohorts. The ones with significant results are shown in Figure 4.4 for BM and Figure 4.5 for PBMCs. ABCB1, ABCG2 and

CRBN were significantly more highly expressed in previously-treated patients’ BM than that in treatment-naïve patients on either D0 or D5. CRBN expression was significantly increased on D5 compared to D0 in both cohorts. The results for BM and PBMCs were not completely consistent, even when we compared the BM and PBMC samples from the same patients. This is presumably due to the different cell composition of BM and PBMC samples. BM has more immature cells and leukemic cells, and is more representative regarding tumor characterization.

4.3.3 Correlation of PK and PD

Multiple factors contribute to the variabilities in lenalidomide exposure and miR-181a expression in tumors of AML patients. We evaluated the correlation between lenalidomide PK in plasma and the baseline gene expression of transporters, direct targets

(cereblon) and miR-181a as well as the change (Day 5 vs. Day 0) of these genes. Figure

4.6 demonstrated the multiple comparisons between different groups. Correlation coefficients and p-values between PK from C1D1, baseline gene expressions (Day 0), and relative gene expression changes Δ [(Day 5-Day0)/Day0] in BM are shown in Table

4.15. Although some p-values for the correlation coefficients indicated the association was significant, the magnitudes of the correlation coefficients were quite small. This is not surprising since gene expression does not always equate to protein expression or functional protein levels. According to our hypothesis, functional transporter protein expression on the cell surface should be more associated with the intracellular drug concentrations rather than mRNA level of these transporter genes. Unfortunately, our correlative studies of transporter gene expression were added after the trial was well underway. We therefore did not have adequate sample quantities to assess membrane expression of transporter proteins. Furthermore, other factors not controlled for within this study would likely influence lenalidomide intracellular levels, such as co- medications. These other medicines may affect the expression of our genes of interest, or the medications may inhibit transporter mediated uptake or efflux of lenalidomide.

Cohort1 Cohort2 Dose Lenalidomide Idarubicin Cytarabine Lenalidomide Idarubicin Cytarabine 2 2 2 2 Level (mg) (mg/m ) (g/m ) (mg) (mg/m ) (g/m ) -2 20 8 1.0 10 8 0.1 -1 25 8 1.0 20 8 0.1 1 25 12 1.5 25 12 0.1 2 30 12 1.5 30 12 0.1 3 35 12 1.5 35 12 0.1 4 50 12 1.5 50 12 0.1

Table 4.1 Dosage escalation plan of clinical trial OSU10016

Pharmacokinetic Parameters of Lenalidomide (Mean±SD) PK Cohort1 Cohort2 Units parameters Day1 Day5 Day1 Day5

t1/2 hr 3.50±0.87 4.41±2.12 3.84±1.21 4.69±1.98

Tmax hr 1.71±1.20 3.32±4.75 2.86±4.70 2.28±1.66

Cmax nM 1,901±976 1,626±871 1,986±1,119 1,838±1,008

AUCall hr*nM 10,132±8,916 9,670±5,728 11,246±7,184 11,928±6,874

Vz_F_obs mg/(nM) 0.02±0.01 0.02±0.01 0.02±0.01 0.02±0.01

Cl_F_obs mg/(hr*nM) 0.003±0.002 0.003±0.002 0.003±0.003 0.003±0.003

Table 4.2 Noncompartmental Plasma PK parameters of lenalidomide

p-values of Pharmacokinetic Parameters Cohort1 vs Cohort2 Day1 vs Day5 PK parameters Units Day1 Day5 Cohort1 Cohort2

t1/2 hr 0.257 0.251 0.073 0.064

Tmax hr 0.282 0.724 0.102 0.992

Cmax nM 0.715 0.342 0.303 0.594

AUCall hr*nM 0.148 0.185 0.806 0.779

Vz_F_obs mg/(nM) 0.200 0.939 0.630 0.210

Cl_F_obs mg/(hr*nM) 0.162 0.365 0.630 0.691

Table 4.3 p-values of lenalidomide PK parameters comparisons between multiple groups (separated by cohort and day, respectively)

p-values of Pharmacokinetic Parameter Comparisons

PK parameters t1/2 Tmax Cmax AUCall Vz_F_obs Cl_F_obs Units hr hr nM hr*nM mg/(nM) mg/(hr*nM) Day1 vs Day5 0.1051 0.2522 0.2865 0.6693 0.1886 0.4949 Cohort1 vs Cohort2 0.1417 0.4355 0.4355 0.0518 0.2948 0.1089 25mg vs 30 mg 0.2714 0.9899 0.7971 0.5694 0.3473 0.4356

Table 4.4 p-values of lenalidomide PK parameters comparisons between multiple groups (Wilcoxin rank sum test)

ABCB1 Relative Gene Expression [2^(-dCt)] Treated Naive (n=10) Previously Treated (n=16) ID D0 D5 ID D0 D5 8 0.0028 0.0027 1 0.0095 0.0094 12 0.0179 0.0125 2 0.0227 0.0095 14 0.0072 0.0173 3 0.0213 0.0102 15 0.0003 0.0005 4 0.0823 0.0657 16 0.0105 0.0047 5 0.0014 0.0009 20 0.0013 0.0019 6 0.0518 0.0167 35 0.0003 0.0071 10 0.0065 0.0093 37 0.0039 0.0086 17 0.0211 0.0259 44 0.0013 0.0017 18 0.0112 0.0130 48 0.0026 0.0090 26 0.0551 0.0615 28 0.0005 0.0010 30 0.0089 0.0339 36 0.0095 0.0112 45 0.0180 0.0272 46 0.0054 0.0098 47 0.0086 0.0054 Mean±SD 0.0048±0.0056 0.0066±0. 0054 Mean±SD 0.0209±0.0228 0.0194±0.0195

Table 4.5 ABCB1 relative expression in BM samples

ABCG2 Relative Gene Expression [2^(-dCt)] Treated Naive (n=10) Previously Treated (n=16) ID D0 D5 ID D0 D5 8 0.0001 0.0001 1 0.0121 0.0085 12 0.0010 0.0012 2 0.0001 0.0004 14 0.0012 0.0007 3 0.0016 0.0007 15 0.0001 0.0000 4 0.0002 0.0004 16 0.0002 0.0001 5 0.0001 0.0010 20 0.0001 0.0011 6 0.0011 0.0019 35 0.0000 0.0005 10 0.0026 0.0035 37 0.0004 0.0005 17 0.0012 0.0049 44 0.0001 0.0004 18 0.0048 0.0045 48 0.0010 0.0002 26 0.0041 0.0032 28 0.0001 0.0002 30 0.0102 0.0025 36 0.0065 0.0027 45 0.0000 0.0001 46 0.0030 0.0005 47 0.0004 0.0019 Mean±SD 0.0004±0.0005 0.0005±0.0004 Mean±SD 0.0030±0.0037 0.0023±0.0023

Table 4.6 ABCG2 relative expression in BM samples

CEBPA Relative Gene Expression [2^(-dCt)] Treated Naive (n=10) Previously Treated (n=16) ID D0 D5 ID D0 D5 8 0.0448 0.0566 1 0.0977 0.0953 12 0.0321 0.0368 2 0.0785 0.1387 14 0.0330 0.0367 3 0.0685 0.1063 15 0.0232 0.0957 4 0.0116 0.0154 16 0.0330 0.0374 5 0.0315 0.0524 20 0.0742 0.1369 6 0.0544 0.0899 35 0.0995 0.0453 10 0.0213 0.0988 37 0.0575 0.0306 17 0.0172 0.0308 44 0.0882 0.0957 18 0.0166 0.0207 48 0.1055 0.1211 26 0.0224 0.0246 28 0.0127 0.0519 30 0.0565 0.0396 36 0.0609 0.1189 45 0.0816 0.0643 46 0.0374 0.1007 47 0.0568 0.1008 Mean±SD 0.0591±0.0307 0.0693±0.0395 Mean±SD 0.0453±0.0276 0.0718±0.0389

Table 4.7 CEBPA relative expression in BM samples

CRBN Relative Gene Expression [2^(-dCt)] Treated Naive (n=10) Previously Treated (n=16) ID D0 D5 ID D0 D5 8 0.0014 0.0015 1 0.0048 0.0084 12 0.0019 0.0032 2 0.0172 0.0113 14 0.0015 0.0003 3 0.0032 0.0108 15 0.0005 0.0019 4 0.0015 0.0069 16 0.0006 0.0023 5 0.0005 0.0028 20 0.0008 0.0031 6 0.0057 0.0070 35 0.0003 0.0009 10 0.0020 0.0246 37 0.0014 0.0010 17 0.0034 0.0113 44 0.0011 0.0029 18 0.0072 0.0182 48 0.0002 0.0007 26 0.0040 0.0034 28 0.0004 0.0028 30 0.0039 0.0017 36 0.0010 0.0061 45 0.0015 0.0019 46 0.0016 0.0021 47 0.0011 0.0062 Mean±SD 0.0010±0.0006 0.0018±0.0011 Mean±SD 0.0037±0.0041 0.0078±0.0063

Table 4.8 CRBN relative expression in BM samples

miR-181a Gene Expression [2^(-dCt)] Treated Naive (n=10) Previously Treated (n=16) ID D0 D5 ID D0 D5 8 0.0031 0.0051 1 0.1700 0.0487 12 0.3290 0.2519 2 0.0515 1.0849 14 0.0576 0.1035 3 0.6940 0.0226 15 0.0355 0.0300 4 0.0645 0.1298 16 0.7797 0.0080 5 0.1212 0.0232 20 0.2022 0.3074 6 0.0551 0.2311 35 0.0174 0.0088 10 0.0175 0.0091 37 0.1183 0.4094 17 0.0811 0.3365 44 0.1703 0.6375 18 0.8721 2.1495 48 1.9346 0.0845 26 1.1337 0.2915 28 0.2563 0.0875 30 0.1373 0.0276 36 0.0385 0.0476 45 0.0305 0.0038 46 0.0502 0.0443 47 0.1225 0.0239 Mean±SD 0.3648±0. 5979 0.1846±0.21 35 Mean±SD 0.2435±0.3409 0.2851±0.5646

Table 4.9 miR-181a relative expression in BM samples

* miR-181a data [2^(-dCt)] was provided by our collaborator, Dr. Hongyan Wang

ABCB1 Relative Gene Expression [2^(-dCt)] Treated Naive (n=14) Previously Treated (n=13) ID D0 D5 ID D0 D5 8 0.0038 0.0035 3 0.0037 0.0024 14 0.0079 0.0193 4 0.0124 0.0063 15 0.0004 0.0010 5 0.0001 0.0003 19 0.0168 0.0199 6 0.0040 0.0017 20 0.0036 0.0124 10 0.0010 0.0010 22 0.0052 0.0056 18 0.0003 0.0005 23 0.0019 0.0002 26 0.0190 0.0213 24 0.0057 0.0041 30 0.0046 0.0042 25 0.0086 0.0133 36 0.0015 0.0011 37 0.0049 0.0082 39 0.0003 0.0001 38 0.0088 0.0130 45 0.0009 0.0029 40 0.0117 0.0091 46 0.0002 0.0002 44 0.0002 0.0019 47 0.0003 0.0021 48 0.0172 0.0123 Mean±SD 0.0069±0.0054 0.0088±0.0064 Mean±SD 0.00371±0.00570 0.0034±0.0057

Table 4.10 ABCB1 relative expression in PBMC samples

ABCG2 Relative Gene Expression [2^(-dCt)] Treated Naive (n=14) Previously Treated (n=13) ID D0 D5 ID D0 D5 8 0.00014 0.00013 3 0.00002 0.00003 14 0.00151 0.00080 4 0.00001 0.00001 15 0.00001 0.00008 5 0.00000 0.00003 19 0.00041 0.00101 6 0.00005 0.00004 20 0.00005 0.00016 10 0.00028 0.00038 22 0.00037 0.00203 18 0.00009 0.00013 23 0.01050 0.01192 26 0.00021 0.00017 24 0.00022 0.00008 30 0.00003 0.00005 25 0.00219 0.00067 36 0.00013 0.00010 37 0.00003 0.00006 39 0.00002 0.00000 38 0.00031 0.00048 45 0.00001 0.00000 40 0.00044 0.00016 46 0.00003 0.00002 44 0.00004 0.00015 47 0.00000 0.00004 48 0.00136 0.00034 Mean±SD 0.0013±0.0027 0.0013±0.0031 Mean±SD 0.00007±0.00009 0.00008±0.00010

Table 4.11 ABCG2 relative expression in PBMC samples

CEBPA Relative Gene Expression [2^(-dCt)] Treated Naive (n=14) Previously Treated (n=13) ID D0 D5 ID D0 D5 8 0.0453 0.0497 3 0.0093 0.0316 14 0.0238 0.0367 4 0.0069 0.0133 15 0.0592 0.0471 5 0.0221 0.0186 19 0.0171 0.0373 6 0.0218 0.0350 20 0.0685 0.0855 10 0.0130 0.0394 22 0.0200 0.0144 18 0.0272 0.0235 23 0.0084 0.0122 26 0.0069 0.0079 24 0.0515 0.0402 30 0.0451 0.0088 25 0.0219 0.0225 36 0.0184 0.0211 37 0.0741 0.1573 39 0.0265 0.0085 38 0.0212 0.0181 45 0.0163 0.0275 40 0.0363 0.0272 46 0.1167 0.0315 44 0.0133 0.0334 47 0.0139 0.0299 48 0.2283 0.3404 Mean±SD 0.0492±0.0557 0.0658±0.0874 Mean±SD 0.0265±0.0290 0.0228±0.0107

Table 4.12 CEBPA relative expression in PBMC samples

CRBN Relative Gene Expression [2^(-dCt)] Treated Naive (n=14) Previously Treated (n=13) ID D0 D5 ID D0 D5 8 0.0004 0.0006 3 0.0066 0.0294 14 0.0014 0.0002 4 0.0030 0.0027 15 0.0004 0.0009 5 0.0011 0.0057 19 0.0027 0.0061 6 0.0064 0.0206 20 0.0006 0.0076 10 0.0185 0.0590 22 0.0006 0.0034 18 0.0058 0.0200 23 0.0012 0.0034 26 0.0199 0.0352 24 0.0034 0.0040 30 0.0387 0.0067 25 0.0010 0.0007 36 0.0019 0.0096 37 0.0022 0.0018 39 0.0105 0.0011 38 0.0013 0.0008 45 0.0011 0.0033 40 0.0009 0.0029 46 0.0036 0.0066 44 0.0009 0.0032 47 0.0014 0.0203 48 0.0016 0.0033 Mean±SD 0.0013±0.0009 0.0028±0.0022 Mean±SD 0.0091±0.0109 0.0169±0.0166

Table 4.13 CRBN relative expression in PBMC samples

miR-181a Relative Gene Expression [2^(-dCt)] Treated Naive (n=14) Previously Treated (n=13) ID D0 D5 ID D0 D5 8 0.0026 0.0026 3 0.0112 0.0035 14 0.2003 0.2144 4 0.0251 0.0846 15 0.0823 0.0419 5 0.0098 0.0039 19 0.0253 0.0246 6 0.0270 0.0049 20 0.1141 0.1020 10 0.0072 0.0094 22 0.0110 0.0128 18 0.0083 0.0073 23 0.0190 0.0366 26 0.0098 0.0051 24 0.1570 0.0806 30 0.0254 0.0129 25 0.0182 0.0139 36 0.0098 0.0009 37 0.1160 0.2977 39 0.0143 0.0119 38 0.0184 0.0118 45 0.0155 0.0205 40 0.0143 0.0132 46 0.0205 0.0185 44 0.0718 0.0487 47 0.0124 0.0098 48 0.2131 0.1480 Mean±SD 0.0760±0.0733 0.0749±0.0884 Mean±SD 0.0151±0.0 070 0.0149±0.02 17

Table 4.14 miR-181a relative expression in PBMC samples

* miR-181a data [2^(-dCt)] was provided our collaborator, Dr. Hongyan Wang

Pgp BCRP CEBPa CRBN miR-181a ΔPgp ΔBCRP ΔCEBPa ΔCRBN ΔmiR-181a HL Tmax Cmax AUCall

BCRP 0.019*

0.932**

CEBPa -0.339 0.226

0.123 0.313

CRBN 0.201 0.185 0.179

0.369 0.41 0.427

miR-181a 0.304 0.121 -0.243 0.115

0.169 0.592 0.276 0.612

ΔPgp -0.191 -0.087 0.404 -0.172 -0.196

0.395 0.701 0.062 0.443 0.383

ΔBCRP -0.234 -0.345 0.195 -0.157 -0.248 0.4

0.294 0.116 0.385 0.487 0.265 0.065

ΔCEBPa -0.184 -0.195 -0.436 -0.105 -0.205 -0.237 -0.061

100 0.413 0.384 0.042 0.643 0.361 0.288 0.788

ΔCRBN -0.112 -0.16 -0.29 -0.345 -0.184 -0.049 0.226 0.73

0.62 0.477 0.191 0.115 0.413 0.83 0.312 0 Continued

Table 4.15 Correlation coefficients of main PK parameters, D0 baseline gene expression vs gene expression change in BM

(all patients, n=22, without outlier, pt6)

100

Continued Table 4.15

Pgp BCRP CEBPa CRBN miR-181a ΔPgp ΔBCRP ΔCEBPa ΔCRBN ΔmiR-181a HL Tmax Cmax AUCall

ΔmiR-181a 0.055 0.154 0.003 -0.043 -0.099 -0.184 -0.225 -0.127 -0.065 0.808 0.494 0.991 0.849 0.661 0.411 0.314 0.574 0.775 HL -0.099 0.031 -0.066 0.368 0.037 -0.22 -0.264 -0.155 -0.328 0.223

0.662 0.891 0.771 0.092 0.872 0.324 0.234 0.491 0.136 0.319

Tmax -0.201 -0.079 0.142 -0.081 -0.224 0.24 0.394 0.295 0.046 -0.155 -0.2 0.369 0.726 0.53 0.719 0.316 0.282 0.069 0.182 0.837 0.492 0.372

Cmax 0.024 -0.249 -0.068 0.009 0.261 0.041 -0.327 0.071 0.097 -0.404 -0.241 -0.35

0.914 0.264 0.765 0.969 0.241 0.856 0.137 0.754 0.667 0.062 0.279 0.11

AUCall -0.005 -0.252 0.317 0.02 0.113 0.522 0.061 -0.12 -0.084 -0.483 -0.309 -0.01 0.631

0.984 0.258 0.151 0.93 0.618 0.013 0.788 0.595 0.712 0.023 0.162 0.965 0.002

Cl -0.1 0.189 -0.132 -0.15 -0.025 -0.247 0.14 -0.055 0.029 0.678 0.154 -0.112 -0.619 -0.721

1 0.659 0.399 0.558 0.506 0.91 0.268 0.535 0.807 0.897 0.001 0.493 0.62 0.002 0

*: Correlation coefficient; **: p-values

0.019* and 0.932** is a representative result set to demonstrate this table. It means the correlation coefficient between baseline level (Day 0) of Pgp and

BCRP is 0.019 and the p-value for this correlation is 0.932. Δ is the relative change of gene expression which is the expression of (Day5-Day0)/Day0.

101

Figure 4.1 Our hypothesis: possible mechanism of action for lenalidomide in AML

In our hypothesis, the intracellular lenalidomide concentrations directly correlate with systemic lenalidomide concentration (plasma concentration) as well as membrane Pgp and BCRP expression. Patients with higher expression level of Pgp and BCRP would have less lenalidomide in cells if they have same systemic lenalidomide exposure.

Lenalidomide binding to its direct target, cereblon, results in the inhibition of C/EBPα degradation followed by upregulated miR-181a expression, which is associated with clinical outcome. Thus, patients with high intracellular level of lenaliomide would theoretically have favorable response. In summary, patients’ plasma lenalidomide PK and expression levels of Pgp, BCRP, cereblon, C/EBPα and miR-181a will all contribute to clinical response. 102

Figure 4.2 OSU10016 Trial design scheme

In this clinical trial, one cycle included 21 days. Oral lenalidomide was given daily starting on day 1. Beginning on day 5, cytarabine was administered daily by intravenous

(IV) infusion till day 11. Idarubicin was also given as a 1 hr IV infusion daily on days 5-7.

When idarubicin and cytarabine were given, they were administered immediately after lenalidomide was taken.

103

Figure 4.3 PK profiles of lenalidomide in OSU110016

Figure A is the PK plot of lenalidomide on C1D1 from 56 AML patients. Cohort 1 is the relapsed or refractory patients and cohort 2 is treatment-naïve patients. Figure B is the PK profile of patients on C1D5.

104

Continued

Figure 4.4 Relative gene expressions of ABCB1 (A), ABCG2 (B) and CRBN (C) in

*: p<0.05; **: p<0.01 105

Continued Figure 4.4

106

Continued

Figure 4.5 Relative gene expressions of ABCB1 (A), ABCG2 (B) and CRBN (C) in

PBMCs

*: p<0.05; **: p<0.01

107

Continued Figure 4.5

108

Figure 4.6 Multiple comparisons of gene expressions between different groups

Multiple comparisons were done within the gene expressions data. First, data on D0 and

D5 from same patient was compared to check if the current therapy would alter gene expressions. To evaluate if previous treatment would affect gene expression levels, data on same day was compared between patients from different cohorts, e.g. D0 (cohort 1) vs

D0 (cohort 2). Finally, BM and PBMC samples from same patient were compared to see if different sample types would affect the results.

109

CHAPTER 5

SUMMARY AND FUTURE PERSPECTIVES

5.1 Summary

Lenalidomide and pomalidomide are members of the immunomodulatory drug family.

Their slight structural modifications relative to the first generation family member, thalidomide, make them more potent in simulating T cell proliferation and inhibiting

TNF-α. Lenalidomide and pomalidomide are also less toxic and produce fewer and less severe adverse side-effects compared to thalidomide. Lenalidomide was approved by the

FDA in 2006 for the treatment of MM, mantle cell lymphoma and myelodysplastic syndromes. Seven years later, pomalidomide was approved by the FDA for the treatment of relapsed or refractory MM patients who have already received at least two prior treatments. According to clinicaltrials.gov (March, 2015), there have been more than 600 trials for lenalidomide and more than 80 trials for pomalidomide to evaluate the safety and efficacy of these two drugs administrated alone or, in most cases, with other chemotherapeutic agents for the treatments of diverse hematological malignancies and solid tumors. However, the precise mechanism of action of IMiDs remains unclear.

Our group was the first to identify the role of Pgp in lenalidomide disposition, and we reported an apparent clinical DDI of lenalidomide with temsirolimus [37]. In this

110 dissertation, the role of Pgp in lenalidomide elimination was further evaluated in FVB

WT and mdr1a/b KO mice. We also identified BCRP as another potentially important player in lenalidomide and pomalidomide disposition. This led us to question if Pgp and

BCRP were associated with intracellular drug concentrations, which hypothetically could impact the IMiD target, cereblon, as well as downstream biomarkers, such as miR-181a expression, and outcomes in a clinical trial we conducted with lenalidomide in AML patients.

In Chapter 2, the pre-clinical study of lenalidomide and pomalidomide in FVB WT and mdr1a/b KO (Pgp non-functional) mice was performed to evaluate the impact of Pgp on in vivo disposition of these two drugs. Consistent with our previously published in vitro data [37], lenalidomide plasma data from WT and KO mice groups in this study suggested dysfunctional Pgp does impact plasma pharmacokinetics of lenalidomide but did not enhance brain penetration, as we had hypothesized. Plasma data for pomalidomide also suggested that pomalidomide is a substrate of Pgp, which was further supported by a recent report from Kasserra and colleagues [126]. Brain distribution data for both lenalidomide and pomalidomide suggested other transporters might be involved in the overall disposition of these two drugs, and we therefore turned our attention to

BCRP, a multi-drug resistance transporter important in the blood-brain barrier.

In Chapter 3, we utilized cell lines MDCKII/WT, MCDKII/Pgp and MDCKII/BCRP to conduct uptake and transport studies. Results of the cell uptake assays showed significant lower intracellular accumulation of lenalidomide in Pgp and BCRP overexpressing cells compared to WT cells. This was consistent with our previous data that confirmed 111 lenalidomide is a substrate of Pgp, and it suggested BCRP may also play a role in lenalidomide efflux from cells [37]. The transwell permeability assay was then conducted to evaluate if BCRP could impact the transepithelial transport of lenalidomide or pomalidomide. Results from these studies suggested that BCRP could alter the permeability of lenalidomide through epithelial membranes, although the data for pomalidomide was less convincing.

In Chapter 4, PK data analysis of lenalidomide was completed on 56 AML patients and was similar to previous reports [37, 64]. The PK comparison between lenalidomide alone and lenalidomide combined with idarubicin (another Pgp substrate) and cytarabine showed that no significant, direct drug-drug interactions were observed in this study.

Although no statistically significant differences in lenalidomide PK parameters were observed between the two cohorts (treatment-naïve vs previously treated groups), drug

AUC was trending higher in the treatment-naïve group (p=0.0518, Day 1 and Day 5 combined data). This may have been reflective of the renal function difference of patients in the two cohorts, where the treatment-naïve group patients were overall older than treatment-naïve patients.

While this trial was not originally designed to evaluate the impact of lenalidomide plasma

PK and leukemic cell transporter expression on molecular PD endpoints within this trial, we were able to obtain from 26 BM samples and 27 PBMC samples collected on both

Day 0 and Day 5, gene expression data for efflux transporters (ABCB1 and ABCG2), and lenalidomide direct and downstream targets, cereblon and C/EBPα (CRBN and CEBPA), as well as our PD endpoint, miR-181a.. Expression of multi-drug resistance transporter 112

(ABCB1 and ABCG2) and CRBN were higher in the BM of previously treated compared to treatment-naïve patients. However, this was not correlated with the observed variability in miR-181a expression. The results from PBMC samples differed compared with those of the BM samples, which was not surprising given the differing cell populations and relatively low number of immature cells in PBMC compared to BM. No correlations were observed between lenalidomide plasma PK, baseline expressions of genes of interest and gene expression changes during the treatment. This does not however rule out transporter modulation of IMiD activity within leukemic cells. These ad-hoc evaluations were limited by a lack of sample quantities which enabled us to only evaluate transporter gene expression, which may not be representative of functional transporter protein expression on the cell surface. In addition, many other factors

(pharmacogenetics, expression of other relevant transporters, variability in leukemic cell populations among patients, co-medications, etc.) likely contribute to the observed variability in lenalidomide PK and miR-181a expression.

5.2 Future perspectives

Since we observed the apparent drug-drug interaction of lenalidomide and temsirolimus within the clinical trial in 22 refractory MM patients in 2010 [37], we have been studying the broader impact of Pgp and other transporters on IMiD disposition and activity. Based on the clinical results observed, we hypothesized IMiD plasma PK and tissue distribution would likely be impacted by co-administration of other Pgp substrates or inhibitors and that other transporters also play a role. As the studies described within the dissertation confirm, Pgp does impact IMiD plasma PK, although to a lesser extent than we had

113 expected, as observed in the Pgp KO mouse studies. Our clinical results from MM patients prompted Celgene to conduct a follow-up study evaluating the potential drug- drug interaction of lenalidomide and temsirolimus in healthy volunteers. Results from their study suggested very minimal and clinically insignificant interactions occur when lenalidomide is combined with temsirolimus [109]. Furthermore, based on plasma PK data for both lenalidomide and idarubicin, our recent study combining lenalidomide, cytarabine and idarubucin (a known Pgp substrate) did not reveal any evidence of drug- drug interaction in AML patients. Collectively, the data that has been generated over the past 5 years suggests Pgp may not be a major factor in plasma pharmacokinetics of lenalidomide. However, based on our Pgp KO mouse data presented in Chapter 2, and based on recent published clinical studies [109], Pgp is likely more important for pomalidomide with respect to plasma PK.

As this data was being generated over the past 5 years, we observed an opportunity to ask a related, but distinctly different question with respect to the impact of Pgp on lenalidomide therapy. Our collaborators were conducting a clinical trial to evaluate lenalidomide combined with standard chemotherapy in two cohorts of AML patients, those who were treatment-naïve and those who were relapsed or refractory from prior therapy. Within this trial, our collaborators were focused on the ability of lenalidomide, when given 5 days prior to chemotherapy, to increase the expression of miR-181a and thus sensitize patients to chemotherapy. As we were already producing lenalidomide plasma pharmacokinetic data, we hypothesized the ability of lenalidomide to modulate miR-181 expression within leukemic cells in blood and BM would be modulated by the

114 expression of Pgp and potentially other transporters within the leukemic cell population.

As an ad-hoc correlative component to this trial, we obtained from our collaborators cDNA and miR-181a expression data from a subset of the patients. This enabled us to take a first look at the interplay between these variables (plasma lenalidomide PK, transporter gene expression, and miR-181a expression). As we had already produced in vitro uptake and transport data suggesting BCRP transports lenalidomide, we evaluated gene expression for both ABCB1 and ABCG2. Furthermore, we evaluated gene expression of the IMiD target, cereblon, along with the CEBPA transcription factor gene known to be important in AML, potentially through its modulation of miR-181a expression. Within this limited, ad hoc study we did not find an association between transporter gene expression and miR-181a expression. We did however observe increased

CRBN expression after 4 days of lenalidomide therapy, and we also observed higher

ABCB1 and ABCG2 expression in the relapsed/refractory cohort relative to the treatment-naïve cohort.

The work presented in this dissertation adds some definitive data to the study of IMiD disposition, and it presents new findings relative to IMiD brain penetration in mice,

BCRP-mediated transport, and the impact of clinical lenalidomide therapy on CRBN gene expression. Our observation that lenalidomide has poor brain penetration while pomalidomide has good brain distribution, yet the brain penetration of neither agent is impacted by Pgp, reveals a paradox that warrants further evaluation. We are still generating PAMPA data to confirm these two agents do not have significantly different membrane diffusion characteristics. If this is confirmed, then what is the cause of the

115 drastically different brain penetration for these agents? We hypothesize this must be related to one or more other transporters that significantly inhibit lenaliomide penetration in brain, or alternatively, other transporters that uptake pomalidomide into brain tissue.

Future work aimed at identifying which transporters are involved will be needed. Our preliminary data indicating lenalidomide is a BCRP substrate could be followed up with

BCRP KO mouse studies to determine if BCRP is responsible for the brain exclusion of lenalidomide.

As we have generally concluded plasma disposition of lenalidomide may not be impacted to a degree that is clinically relevant by Pgp-mediated drug interactions, we have begun to explore the role of Pgp and other transporters in excluding IMiDs from tissues, including tumor cells. First, we are attempting to understand if lenalidomide and pomalidomide are the substrates of some influx transporters. In particular, we will evaluate the seven members of the nucleoside transporter family due to the structure similarity of lenalidomide to both purine and pyrimidine nucleobases (Figure 5.1). Our preliminary data in the study of nucleoside transporters (cell uptake study in human promyelotic leukemia cell, HL-60 with dimethylforamide) actually suggested lenalidomide was a substrate of equilibrative nucleoside transporter (ENT) 2 (coding gene, SLC29A2). Second, in the PK and PD of the clinical trial, even though no strong correlation of PK and PD was observed in this lenalidomide trial with AML patients due to the uncontrollable complex conditions in patients, we can still evaluate the hypothesis of PK and PD correlating through transporter mediated intracellular drug concentrations in a more efficient evaluation model by using AML cell lines, e.g MV4-11, THP-1 and

116

Kasumi-1. By incubating the AML cells with lenalidomide, we can measure the intracellular drug concentrations and gene expressions of efflux transporters, lenalidomide direct target cereblon and final PD biomarkers miR-181a to monitor the correlation in this simple system. In addition, besides gene expressions, protein quantification can also be performed in the experiments mentioned above. Gene expression levels cannot reflect the actual membrane protein levels. The functional protein expression would be more relevant to intracellular drug concentrations.

Furthermore, the most prevalent, known, functional single-nucleotide polymorphisms

(SNPs) of our genes of interest could be determined to see if they can explain the variability, e.g. ABCB1 SNPs, C1246C>T, 3435C>T and 2677G>TA [155-157] and

ABCG2 SNPs, 421C>A and 34G>A [158].

Lastly, besides the new system we can explore, we can still work more on our current clinical trial data. A PK/PD model could be built up to evaluate all the associations. We know that multiple factors contribute to the variability in lenalidomide exposure and miR-

181a expression in tumors of AML patients. We can evaluate the relative contributions of multiple variables, including lenalidomide plasma PK, gene and protein expression of transporters, lenalidomide accumulation in tumor, and patient-specific factors, such as renal function and disease cytogenetics, on miR-181a expression in tumors. So far, a fully developed PK model has been built based on another clinical trial of lenalidomide with

AML and CLL patients. This model could be adapted to OSU10016 as a base of PK/PD model. MiR-181a expression will be the PD endpoint in this PK/PD model and various factors (transporter expression and patient demographic information) will be incorporated

117 into the PK/PD model as multivariable. The transporter pharmacogenomics (PG) information may also be important, which likely will modulate the absorption of lenalidomide in the gastrointestinal tract, kidney and blood-brain barrier. We don’t have this information and will not be able to add this as a covariate in this trial. However, we can still use the PG information from the cell system mentioned in last paragraph, add it as a covariate and verify this in the future clinical trial.

In summary, a thorough understanding of the role of efflux transporters (Pgp and BCRP) on lenalidomide disposition, tumor penetration and their relationship to plasma PK as well as PD biomarkers (cereblon or miR-181a expression) will help us understand the mechanism of lenalidomide action, which may facilitate the clinical decision for inclusion of lenalidomide in chemotherapy regimens for AML patients.

118

Figure 5.1 Structures of (A) lenalidomide and (B) purine and pyrimidine nucleobases

119

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