William D. Hedrich Email: William.Hedrich@Bms.Com

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The Role of the Constitutive Androstane Receptor in Cyclophosphamide-based Treatment of Lymphomas

Item Type dissertation

Authors Hedrich, William Dominic

Publication Date 2018

Abstract Cyclophosphamide (CPA) is an alkylating prodrug which has been utilized extensively in combination chemotherapies for the treatment of cancers and autoimmune disorders since its introduction to the market in the late 1950s. The metabolic conversion o...

Keywords constitutive androstane receptor; CYP2B6; drug-drug interactions; Cyclophosphamide; Cytochrome P-450 CYP2B6; Drug Interactions

Download date 07/10/2021 19:53:39

Link to Item http://hdl.handle.net/10713/8006 William D. Hedrich Email: [email protected]

EDUCATION: Degree Institution Field of Study Date Bachelor of The Pennsylvania State Toxicology 2013 Science University Bachelor of The Pennsylvania State Biology-Vertebrate 2013 Science University Physiology Doctor of University of Maryland, Pharmaceutical 2018 Philosophy Baltimore Sciences

______RESEARCH EXPERIENCE Graduate Research Assistant Wang Lab, University of Maryland School of Pharmacy • The role of the constitutive androstane receptor in cyclophosphamide-based treatment of lymphomas • Inductive expression of drug metabolizing enzymes and transporters in human primary hepatocytes • Metabolism-mediated drug-drug interactions • In-vivo tumor xenograft models

Hassan Lab, University of Maryland School of Pharmacy • Pharmacokinetics of l-THP as an experimental therapy for cocaine addiction • In-vivo pharmacokinetics of l-THP and its major metabolites in rats • In-vivo drug-drug interactions of cocaine and synthetic opioids in rats • Pharmacokinetics of cyclophosphamide and its major metabolites in mice

Undergraduate Research Assistant Omiecinski Lab, The Pennsylvania State University • Differential metabolism of polycyclic aromatic hydrocarbons by polymorphic microsomal epoxide hydrolase (EPX1) • Methylation profiles of CpG islands in the upstream promoter regions of the human microsomal epoxide hydrolase gene ______PUBLICATIONS • Hedrich, WD., Xiao, J. et al. (2016). “Activation of the Constitutive Androstane Receptor Increases the Therapeutic Index of CHOP in Lymphoma Treatment. Mol Cancer Ther 15(3): 392-401.

• Hedrich, WD., Hassan, HE, Wang, H (2016). “Insights into CYP2B6-mediated drug-drug interactions”. Review. Acta Pharmaceutica Sinica B. 6(5): 413-425.

• Hedrich, WD et al. “In vitro and in vivo characterization of levo- tetrahydropalmatine, a compound with anti-addictive properties: Gene induction, cytotoxicity, metabolism, pharmacokinetics, and drug-drug interaction studies.” Submitted to the International Journal of Pharmaceutics.

• Hedrich, WD. et al. “Targeting transcription factors to improve CHOP-based treatment of lymphomas: Roles of CAR and Nrf2”. In preparation.

• Gharavi, R. Hedrich, WD. et al. (2015). “Transporter-mediated Disposition of Opioids: Implications for Clinical Drug Interactions.” Review. Pharm Res 32(8):2477-502.

• Hedrich, WD. et al. “Antibody Drug Conjugates: PK/PD Modeling, Preclinical Characterization, Clinical Studies, and Lessons Learned”. Clinical Pharmacokinetics. In press.

• Hedrich, WD., et al. “Genotyping your own DNA in pharmacy education and personalized medicine”. Submitted to Currents in Pharmacy Teaching and Learning.

• Zaw, MN., Munuhe, T., Hedrich, WD., et al. (2017) “Thermal Analysis of PDMS-Based Casting Proess with a 3D-Printed Mold”. Submitted to Applied Thermal Engineering.

• Andar, A., Ram, K., Pecher, W. Hedrich, WD., et al. (2017) “Microneedle- Assisted Skin Permeation by Non-toxic Bioengineerable Gas Vesicle Nanoparticles”. Mol Pharmaceutics. In press.

• Hedrich, WD. et al. “Administration of methadone and oxycodone alters the expression of drug metabolizing enzymes and transporters affecting the disposition of cocaine”. In preparation for submission to Molecular Pharmaceutics. ______PRESENTATIONS

• William D. Hedrich, Linhao Li, Daochuan Li, Yuanfu Lu, Hazem E. Hassan, and Hongbing Wang. “Characterization of CITCO and Implications for Lymphoma Treatment”. Meeting of the American College of Clinical Pharmacology (ACCP). San Diego, CA. 2017.

• William D. Hedrich, Linhao Li, Daochuan Li, Yuanfu Lu, Hazem E. Hassan, and Hongbing Wang. “Characterization of CITCO and Implications for Lymphoma Treatment”. Gordon Research Conference on Drug Metabolism. Holderness, NH. 2017.

• William D. Hedrich, Linhao Li, Daochuan Li, Yuanfu Lu, Hazem E. Hassan, and Hongbing Wang. “Characterization of CITCO and Implications for Lymphoma Treatment”. Frontiers at the Chemistry-Biology Interface Symposium. University of Delaware. 2017. 2nd Place Best Poster Award.

• William D. Hedrich, David S. Nakhla, Hongbing Wang, and Hazem E. Hassan. "Administration of methadone and oxycodone alters the expression of drug metabolizing enzymes and transporters affecting the disposition of cocaine." Annual meeting of the American Association of Pharmaceutical Scientists (AAPS). Denver, CO. 2016. Poster. PPDM Section Travel Award.

• William D. Hedrich, Linhao Li, Scott Heyward, Maria R. Baer, Hazem E. Hassan, and Hongbing Wang. "Targeting the constitutive androstane receptor as a novel method for treating hematologic malignancies." Annual meeting of the American Association of Pharmaceutical Scientists (AAPS). Denver, CO. 2016. Poster.

• William D. Hedrich, Linhao Li, Scott Heyward, Maria R. Baer, Hazem E. Hassan, and Hongbing Wang. "Targeting the constitutive androstane receptor as a novel method for treating hematologic malignancies". Meeting of the Globalization of Pharmaceutics Education Network (GPEN). Lawrence, KS. 2016. Oral presentation.

• William D. Hedrich, Shamia L. Faison, Robert Gharavi, Hongbing Wang, Hazem E. Hassan, Jia Bei Wang. "Levo-tetrahydropalmatine does not affect the pharmacokinetics of concomitantly administered cocaine in rats." Annual Meeting of the American College of Clinical Pharmacology (ACCP). Bethesda, MD. 2016. Poster.

• William D. Hedrich, Jingwei Xiao, Scott Heyward, Yao Zhang, Junran Zhang, Maria R. Baer, Hazem E. Hassan, and Hongbing Wang. “Combination of CHOP and an agonist of the constitutive androstane receptor increases the therapeutic index of lymphoma treatment”. Graduate Research Conference, University of Maryland, Baltimore 2016. Poster. Outstanding Presentation Award.

• William D. Hedrich, Jingwei Xiao, Scott Heyward, Michael D. Mitchell, Hazem E. Hassan, and Hongbing Wang. “Activation of the constitutive androstane receptor increases the benefit-risk ratio of CHOP-based treatment of lymphomas. Annual Meeting of the International Society for the Study of Xenobiotics (ISSX), San Francisco, CA, October, 2014. Poster.

• William D. Hedrich, Jingwei Xiao, Scott Heyward, Yao Zhang, Junran Zhang, Maria R. Baer, Hazem E. Hassan, and Hongbing Wang. “Combination of CHOP and an agonist of the constitutive androstane receptor increases the therapeutic index of lymphoma treatment”. Frontiers at the Chemistry-Biology Interface Symposium, Johns Hopkins University. 2016. Poster.

INVITED TALKS • “Targeting the constitutive androstane receptor as a novel method for treating hematologic malignancies”. GPEN Conference. Cell culture models of pharmacokinetics short course. 2016.

• “Targeting CAR as a novel method for treating hematologic malignancies.” University of Maryland School of Pharmacy Research Day. 2017.

• “Impact of philanthropy on graduate student educations”. David Stewarts Associates Dinner. 2017.

AWARDS AND HONORS • PhRMA Foundation Pre-doctoral Fellowship in Pharmacology/Toxicology. 2017. • University of Maryland President’s Entrepreneurial Fellow. 2016-2017. • Department of Pharmaceutical Sciences Graduate Student Fellowship and Merit Award. 2016-2017. • Graduate Student Travel Award. Meeting of the American College of Clinical Pharmacology (ACCP). San Diego, CA. 2017. • 2nd Place Best Poster. Frontiers at the Chemistry/Biology Interface Symposium. University of Delaware. 2017. • AAPS PPDM Section Travel Award. Annual meeting of the American Association of Pharmaceutical Scientists (AAPS). Denver, CO. 2016. • Outstanding Presentation Award. Graduate Research Conference. University of Maryland, Baltimore. Baltimore, MD. 2016. ______

EXTRACURRICULAR AFFILIATIONS • Graduate Student Representative, SOP Assessment Committee 2016-present • President, Pharmacy Graduate Student Association 2015-2016 • Vice President, Pharmacy Graduate Student Association 2014-2015 • First-Year Representative, Pharmacy Graduate Student Association 2013-2014

Abstract

Title of Dissertation The Role of the Constitutive Androstane Receptor in Cyclophosphamide-based Treatment of Lymphomas

Author William D. Hedrich, PhD Candidate, 2018

Dissertation Directed by: Hongbing Wang, PhD Professor and Program Chair University of Maryland School of Pharmacy Department of Pharmaceutical Sciences

Hazem E. Hassan, PhD, MS, RCDS, RPh Assistant Professor and Director Pharmacokinetics and Biopharmaceutics Laboratory University of Maryland School of Pharmacy Department of Pharmaceutical Sciences

Cyclophosphamide (CPA) is an alkylating prodrug which has been utilized extensively in combination chemotherapies for the treatment of cancers and autoimmune disorders since its introduction to the market in the late 1950s. The metabolic conversion of CPA to its pharmacologically active metabolite 4-OH-CPA is catalyzed primarily by cytochrome P450

(CYP) 2B6. CPA is also subject to metabolism by CYP3A4 to an inactive metabolite, N- dechoroethyl-CPA (N-DCE-CPA), and a neurotoxic byproduct, chloroacetaldehyde. CPA is the backbone of the frontline chemotherapeutic regimen used for the treatment of non-Hodgkin lymphoma which combines the CHOP (CPA-doxorubicin-vincristine-prednisone) regimen with rituximab, a monoclonal CD20 antibody. The constitutive androstane receptor (CAR, NR1I3), an orphan nuclear receptor, is recognized as the key mediator of xenobiotic-induced expression of CYP2B6, Importantly, mounting evidence suggests that activation of hCAR leads to preferential induction of CYP2B6 over CYP3A4 which suggests that selective hCAR activation may enhance

CPA bioactivation and enhance the efficacy:toxicity ratio of CHOP chemotherapy for NHL.

CHOP chemotherapy has been associated with severe and cumulative cardiotoxicity arising from the doxorubicin component of the regimen and it is recommended that lymphoma patients with existing heart conditions avoid treatment with the full CHOP combination. Recently, it has been demonstrated that Nrf2 (nuclear factor (erythroid-derived 2))-like 2, NFE2L2) plays a key role in governing doxorubicin-induced cardiotoxicity. Nrf2 regulates the expression of important antioxidant genes and proteins which protect tissues from damage due to oxidative stress and inflammation. It has been shown both that insufficient Nrf2 expression results in hypersensitivity to doxorubicin cardiotoxicity and that stimulation of Nrf2 by small molecule activators can provide protection from doxorubicin-mediated toxicity. Our hypothesis was that hCAR activation will increase hepatic expression of CYP2B6 while having a negligible impact on other genes responsible for the disposition of CHOP drugs. Further, activation of Nrf2 in cardiac tissue may provide protection against cardiotoxicity induced by the doxorubicin component of CHOP.

Together, these gene expression alterations will lead to augmented antineoplastic activity of

CHOP in target lymphoma cells while alleviating the untoward cardiotoxicity associated with this regimen.

This hypothesis was tested with a variety of methods including a novel hepatocyte-lymphoma- cardiomyocyte cell co-culture system as an in vitro model for studying the biotransformation of

CPA and therapeutic effects of CHOP as well as the off-target toxicity in healthy tissues in an environment that closely resembles the in vivo condition. Using this system we successfully demonstrated that activation of hCAR with small molecule activators can significantly increase the anticancer activity of the CHOP regimen in lymphoma cells. Additionally, activation of Nrf2 in cardiomyocytes in co-culture significantly reduced the doxorubicin-induced cardiotoxicity of

CHOP. Utilizing a hCAR-transgenic mouse model, we were able to show in vivo that the combination of a selective hCAR activator alongside CHOP significantly increases the anticancer activity of CHOP in a lymphoma tumor xenograft study.

Taken together, these results implicate hCAR and Nrf2 as drug targets for facilitating CHOP- based treatment of lymphomas. We were able to identify several compounds from the NIH

Chemical Genomics Center Pharmaceutical Collection which activate both hCAR and Nrf2 and have provided preliminary evidence for their utility in CHOP-based lymphoma treatment.

The Role of the Constitutive Androstane Receptor in Cyclophosphamide-based Treatment of Lymphomas

by William D. Hedrich

Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, Baltimore in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2018

Acknowledgments

I would firstly like to express my sincere gratitude to my two PhD mentors, Drs. Hongbing

Wang and Hazem Hassan. Over the past four and a half years, Drs. Wang and Hassan have provided me with immeasurable guidance, encouragement, advice, and wisdom, and without their dedication and leadership the completion of this dissertation would not have been possible.

They have shown unending patience while also providing incredible opportunities to work on exciting research projects and to lay the foundation of my scientific career. I will forever be grateful to them for this experience.

The success of this project would also not have been possible without the support, criticism, advice, and long list of suggestions from my thesis committee members. Drs. Maureen Kane,

Paul “Coach” Shapiro, Yan Shu, and Maria Baer have consistently made themselves available to assist in my research endeavors in any way necessary for my progress. Their comments, critiques, and thoughts have been invaluable, and I am very appreciative of their time and efforts as well.

I must also thank my lab members for their help, support, and entertainment in the lab. I have had the enormous pleasure of working with far too many people to list here, but everyone involved will know who they are; from those who first helped me get started in the lab to those who carried me through to the end, I will be forever grateful of our time together in the

“trenches” of HSFII 522 and PH N406.

I would be remiss if I did not also thank my first research mentors Drs. Curt Omiecinski and

Xiaokun Cai for kickstarting my research goals and providing me with my first real-life laboratory experiences. It was also a friendship and research connection between Dr. Omiecinski

iii and Dr. Wang which first brought me to the University of Maryland which has truly been a life- altering experience.

To my friends in the department, thank you for making this experience everything it was. From the members of my school band (Bryan, Nisha, John, Scott, and Abhay) to those who got whooped by me in fantasy football this year (you know who you are), I would not trade a single experience in the department of Pharmaceutical Sciences at the University of Maryland for anything.

Lastly, I must thank my family and friends outside of the PSC family. I would not be the man, scientist, or anything else that I am without your unending love, support, common sense, motivation, and companionship. This is the greatest achievement thus far in my life, and none of it would have been possible without each and every one of you. The saying goes “no one achieves anything alone”, and I am living proof of that.

PS: Nate - I win.

Table of Contents Acknowledgments...... iii List of Tables ...... xii List of Figures ...... xiii List of Abbreviations ...... xv 1. Insights into CYP2B6-mediated Drug-drug Interactions ...... 1 1.1 Introduction ...... 1 1.2 CYP2B6 Polymorphisms ...... 7 1.2.1 Nonsynonymous SNPs in CYP2B6 ...... 7 1.2.2 SNPs in the Promoter Region of CYP2B6 ...... 11 1.3 Transcriptional Regulation of CYP2B6 ...... 12 1.3.1 CAR- and PXR-mediated Induction of CYP2B6 ...... 15 1.3.2 Induction of CYP2B6 Expression by other Nuclear Receptors ...... 18 1.4 Implications for clinical drug-drug interactions and adverse events ...... 21 1.5 Concluding Remarks ...... 27 1.6 References ...... 29 2. The Roles of Nrf2 as a Drug Target ...... 40 2.1 Introduction ...... 40 2.2 Nrf2 as a drug target to combat multidrug resistance in cancer cells ...... 41 2.3 Targeting the Nrf2-ARE pathway in non-cancer disease states ...... 48 2.3.1 Targeting Nrf2 in Neurodegenerative Diseases ...... 48 2.3.2 Targeting Nrf2 in Diabetes ...... 50 2.3.3 Targeting Nrf2 in cardiovascular disease ...... 52 2.4 Anthracycline Therapeutics...... 53 2.4.1 Anthracycline mechanism(s) of action ...... 54 2.4.2 Anthracycline-induced cardiotoxicity ...... 55 2.5 Nrf2 Expression mediates DOX-induced cardiotoxicity ...... 57 2.5.1 Activation of Nrf2 by small molecules attenuates DOX-induced cardiotoxicity ...... 58 2.6 Conclusions ...... 61 2.7 Research Objective ...... 61 2.8 References ...... 63

3. Activation of the constitutive androstane receptor increases the therapeutic index of CHOP in lymphoma treatment...... 69 3.1 Introduction ...... 69 3.2 Methods & Materials ...... 72 3.2.1 Chemicals and Reagents ...... 72 3.2.2 Human Primary Hepatocytes and HepaRG Cells ...... 72 3.2.3 Culture and Treatment of Lymphoma Cells ...... 72 3.2.4 Quantitative PCR Analysis ...... 73 3.2.5 Hepatocyte/SU-DHL-4 co-culture ...... 74 3.2.6 Multi-organ Co-culture System ...... 75 3.2.7 Western Blotting Analysis in whole cell lysates ...... 75 3.2.8 Western blotting in proteins isolated from harvested tissues ...... 75 3.2.9 Cell Viability Assays ...... 76 3.2.10 Phosphorylated H2AX Imaging ...... 76 3.2.11 Oxidative Stress Imaging...... 77 3.2.12 Animal Subjects ...... 77 3.2.13 Serial Sampling and PK Study ...... 78 3.2.14 LC-MS/MS Analysis Method ...... 78 3.2.15 Statistical Analysis ...... 79 3.3 Results ...... 79 3.3.1 CAR activation enhances CHOP anticancer activity towards SU-DHL-4 cells co- cultured with HPH ...... 79 3.3.2 CITCO alters the expression of genes responsible for CHOP disposition in HPH, but not in target lymphoma cells ...... 80 3.3.3 The role of CITCO in CHOP-based treatment is CAR-dependent ...... 83 3.3.4 Activation of CAR selectively induces CHOP-mediated cytotoxicity in SU-DHL-4, but not in H9c2 cells ...... 86 3.3.5 Reduced CHOP load attenuates H2AX phosphorylation and oxidative stress in H9c2 cells ...... 89 3.3.6 CITCO selectively induces Cyp2b10 in hCAR-tg mice but not WT mice ...... 89 3.3.7 Inclusion of CITCO with CHOP increases cytotoxicity in EL-4 cells in hCAR- transgenic MPH/lymphoma co-cultures ...... 92 3.3.8 CITCO/CHOP combination improves anti-tumor activity over CHOP alone in EL-4 tumor xenografts in hCAR-tg mice ...... 92

3.3.9 CITCO/CHOP combination diminishes expression of important cell survival and proliferation genes in treated tumor tissue ...... 95 3.3.10 CITCO/CHOP combination increases apoptosis in tumor tissue but not in off-target cardiac tissue ...... 95 3.3.11 Combination with CITCO significantly increases exposure to 4-OH-CPA in hCAR-tg mice ...... 98 3.4 Discussion ...... 98 3.5 References ...... 108 4. Targeting Transcription Factors to Improve CHOP-based treatment of lymphomas: Roles of CAR and Nrf2 ...... 112 4.1 Introduction ...... 112 4.2 Materials and Methods ...... 115 4.2.1 Materials ...... 115 4.2.2 High-throughput screening of hCAR and Nrf2 activators...... 115 4.2.3 Culture of Primary Human Hepatocytes ...... 116 4.2.4 Hepatococyte/Lymphoma Co-culture ...... 116 4.2.5 Multi-cell co-culture ...... 117 4.2.6 CCK8 Cytotoxicity Assays ...... 117 4.2.7 RT-qPCR Analysis ...... 118 4.2.8 Statistical Analyses ...... 118 4.3 Results ...... 120 4.3.1 High-throughput screening reveals several dual-activators of CAR and Nrf2 ...... 120 4.3.2 FRE and PIF significantly increase expression of Nrf2 target genes in H9c2 cells but not in lymphoma cells...... 120 4.3.3 Activation of Nrf2 by PIF and FRE protects against doxorubicin-induced toxicity in H9c2 cardiomyoblast cells but not in lymphoma cells ...... 121 ...... 121 4.3.4 PIF/CHOP or FRE/CHOP combination significantly increases cytotoxicity in target lymphoma cells but not in off-target H9c2 cells in co-culture ...... 121 4.4 Discussion ...... 124 4.5 References ...... 135 5. Conclusions ...... 138 5.1 References ...... 142

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Appendix A: Transporter-Mediated Disposition of Opioids: Implications for Clinical Drug Interactions ...... 144 A.1 Introduction ...... 144 A.2 Opioids of Abuse ...... 146 A.2.1 Morphine...... 146 A.2.2 Codeine ...... 150 A.2.3 Diacetylmorphine ...... 151 A.2.4 Oxycodone ...... 153 A.2.5 Oxymorphone ...... 156 A.2.6 Fentanyl ...... 157 A.2.7 Methadone ...... 160 A.2.8 Buprenorphine ...... 165 A.2.9 Tramadol ...... 169 A.2.10 Hydrocodone...... 172 A.2.11 Hydromorphone ...... 173 A.3 Transporter-mediated DDIs ...... 174 A.3.1 P-glycoprotein (P-gp) ...... 174 A.3.2 Breast cancer resistance protein (BCRP) ...... 174 A.3.3 Organic anion transporting polypeptides (OATPs) ...... 175 A.3.4 Organic anion transporters (OATs) ...... 176 A.3.5 Organic cation transporters (OCTs) ...... 177 A.3.6 Multidrug resistance proteins (MRPs) ...... 178 A.3.7 Proton-coupled organic cation antiporters at the BBB ...... 179 A.4 Emerging transporters ...... 181 A.5 Transporter Polymorphisms ...... 182 A.6 Other contributors to opioid disposition and addiction ...... 183 A.6.1 Drug Metabolizing Enzymes ...... 183 A.6.2 Metabolizing Enzyme Polymorphisms ...... 185 A.6.3 Opioid Receptor Polymorphisms ...... 186 A.7 Implications for cancer therapy ...... 187 A.8 Conclusions ...... 189 A.9 References ...... 206

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Appendix B: In Vitro and In Vivo Characterization of levo-tetrahydropalmatine, a compound with anti-addictive properties: Gene Induction, Cytotoxicity, Metabolism, Pharmacokinetics, and Drug-drug Interaction Studies ...... 223 B.1 Introduction ...... 223 B.2 Methods and Materials ...... 225 B.2.1 Culture of HepG2 and H9c2 cells ...... 226 B.2.2 MTT assays with HepG2/H9c2 cells ...... 226 B.2.3 Rat subjects ...... 226 B.2.4 Catheter implantation for IV pharmacokinetics studies ...... 227 B.2.5 HPLC Quantitation Method for Metabolism Studies ...... 227 B.2.6 Quantitation of IV cocaine and l-THP administration using a validated UPLC method ...... 228 B.2.7 Drug-stimulated ATPase assay ...... 228 B.2.8 Rat liver microsome metabolism studies ...... 230 B.2.9 In-vivo pharmacokinetics studies ...... 231 B.2.10 Gene induction in treated rat tissue ...... 232 B.2.11 Statistical analyses ...... 233 B.3 Results ...... 235 B.3.1 l-THP is non-toxic at pharmacologically-relevant concentrations...... 235 B.3.2 Metabolic stability of l-THP and cocaine ...... 235 B.3.3 l-THP does not alter the PK profile of cocaine in rats...... 238 B.3.4 l-THP does not induce the expression of key drug metabolizing enzymes and transporters in rats...... 238 B.3.5 Activity of P-gp is not altered by l-THP at physiologically-relevant concentrations. 241 B.4 Discussion ...... 241 B.5 References ...... 250 Appendix C: Administration of Methadone and Oxycodone Alters the Expression of Drug Metabolizing Enzymes and Transporters Affecting the Disposition of Cocaine in Rats ... 254 C1. Introduction ...... 254 C.2 Materials and Methods ...... 258 C.2.1 Materials ...... 258 C.2.2 Animal Subjects ...... 259 C.2.3 Quantification of Cocaine, Methadone, and Oxycodone ...... 259 C.2.4 Evaluation of gene induction with RT-qPCR ...... 261

C.2.6 Western blotting analysis ...... 263 C.2.7 Statistical analyses ...... 263 C.3 Results ...... 263 C.3.1 Administration of oxycodone and methadone alters the expression of drug metabolizing enzymes and transporters in rats...... 264 C.3.2 Quantification of cocaine, oxycodone, and methadone in rat serum and brain tissue homogenate ...... 267 C.3.3 Changes in expression of drug metabolizing enzymes and transporters by oxycodone and methadone alters the PK of cocaine in rats ...... 267 C.4 Discussion ...... 273 C.5 References ...... 276 Appendix D: Antibody-Drug Conjugates: PK/PD modeling, preclinical characterization, clinical studies, and lessons learned ...... 279 D.1 Introduction ...... 279 D.2 Gemtuzumab ozogamicin ...... 294 D.2.1 Clinical studies with gemtuzumab ozogamicin ...... 295 D.2.2 Impact of age, ethnicity, and gender on gemtuzumab ozogamicin PK/PD ...... 296 D.2.3 Lessons learned from gemtuzumab ozogamicin ...... 297 D.3 Brentuximab vedotin ...... 298 D.3.1 Early clinical studies with brentuximab vedotin ...... 298 D.3.2 PK/PD modeling of brentuximab vedotin ...... 299 D.3.3 Lessons learned from brentuximab vedotin ...... 301 D.4 Trastuzumab emtansine ...... 301 D.4.1 Preclinical characterization and modeling of trastuzumab emtansine ...... 302 D.4.2 Clinical studies of trastuzumab emtansine ...... 303 D.4.3 PK/PD modeling of trastuzumab emtansine ...... 306 D.4.4 Lessons learned from trastuzumab emtansine ...... 309 D.5 Inotuzumab Ozogamicin ...... 310 D.5.1 Preclinical characterization of inotuzumab ozogamicin ...... 310 D.5.2 Clinical studies with inotuzumab ozogamicin ...... 311 D.5.3 PK/PD modeling of inotuzumab ozogamicin ...... 315 D.5.4 Lessons learned from inotuzumab ozogamicin ...... 315 D.6 Conclusions ...... 316

D.7 References ...... 318 Appendix E: Bringing Interprofessional Faculty Together for an Innovative Elective in Pharmacogenomics: Genotyping your own DNA ...... 326 E.1 Background and Purpose ...... 326 E.2 Educational Activity and Setting ...... 329 E.3 Findings ...... 335 E.4 Discussion ...... 338 E.5 References ...... 340 F: Comprehensive List of References ...... 342

List of Tables

Table 1.1 Clinically utilized CYP2B6-substrate drugs...... 5 Table 3.1 Quantitative proportion of cyclophosphamide (CPA), doxorubicin (DOX), vincristine (VCN) and prednisone (Pred) in the CHOP Regimen...... 81 Table 4.1 Primers used in qPCR studies in HPH and H92 cells...... 119 Table A1: Summary of opioid-drug transporter interactions and their potential implications ...... 192 Table B.1 Primers utilized for qPCR studies in rat brain tissue...... 234 Table B.2 Pharmacokinetic parameters of cocaine in the presence or absence of cocaine in rats...... 242 Table B.3 Pharmacokinetic parameters of l-THP in rats...... 243 Table C.1: Primers utilized in qPCR studies in treated rat liver, kidney, and brain tissue...... 262 Table C.2: PK parameters of oxycodone, methadone, and cocaine alone or with oxycodone or methadone...... 272 Table D.1: Structure and targets of clinically approved ADCs...... 285 Table D.2: Clinical studies performed with approved ADCs...... 287 Table E.1: Student responses to survey questions prior to genotyping activity...... 332 Table E.2: Student responses to survey questions following participation in the genotyping activity. ... 334 Table E.3: Student willingness to include pharmacogenomics data in their own medical records...... 337

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List of Figures

Figure 1.1 Activation of PXR in cell-based reporter assays...... 14 Figure 1.2 Schematic illustration of CPA metabolism and the potential role of CAR in CPA bioactivation ...... 23 Figure 3.1. Activation of CAR improves the anticancer activity of the CHOP regimen in HPH/SU-DHL-4 coculture...... 82 Figure 3.2. Activation of CAR improves the anticancer activity of the FC (fludarabine, cyclophosphamide) regimen in HPH/HL-60 co-culture ...... 84 Figure 3.3 Effects of CAR activation on the expression of genes responsible for CHOP disposition in HPH and lymphoma cell lines ...... 85 Figure 3.4 CITCO-enhanced CHOP anticancer activity is CAR dependent ...... 87 Figure 3.5 CHOP- and DOX-induced cytotoxicity in H9c2 cells...... 88 Figure 3.6 CITCO enhances CHOP-mediated cytotoxicity in SU-DHL-4 but not in H9c2 cells 90 Figure 3.7 Effects of CAR activation on the expression of genes responsible for CHOP disposition in H9c2 cells and rat liver...... 91 Figure 3.8 CITCO did not enhance CHOP-induced H2AX phosphorylation and oxidative stress in H9c2 cells...... 93 Figure 3.9: Treatment with CITCO induces expression of CAR target genes in hCAR-transgenic mice but not wild-type mice...... 94 Figure 3.10: CAR activation increases the anticancer activity of CHOP in co-cultures with MPH and EL4 lymphoma cells ...... 96 Figure 3.11: Combination with CITCO increases the anticancer activity of CHOP without affecting off-target toxicity in hCAR-transgenic mice with EL4 lymphoma xenografts...... 97 Figure 3.12: Inclusion of CITCO significantly alters the PK of CPA and 4-OH-CPA in hCAR- transgenic mice...... 99 Figure 3.13 Schematic illustration of CITCO-mediated enhancement of CHOP antineoplastic activity in targeted (SU-DHL-4) but not side-toxic (H9c2) cells...... 100 Figure 4.1: High-throughput screening reveals several compounds which activate hCAR in hCAR-CYP2B6-HepG2 cells...... 122 Figure 4.2: High-throughput screening reveals several compounds which activate Nrf2 in ARE.bla cells...... 123 Figure 4.3: Lead compounds from HTS induce expression of hCAR target genes in HPH and Nrf2 target genes in H9c2 cells ...... 125 Figure 4.4: PIF and FRE do not significantly induce the expression of Nrf2 target genes in lymphoma cell lines...... 126 Figure 4.5: Treatment with Nrf2 activators provides significant protection from DOX- and CHOP-induced cardiotoxicity in H9c2 cultures...... 128 Figure 4.6: SFN, PIF, and FRE pre-treatment does not offer protection against DOX- and CHOP-induced cytotoxicity in SU-DHL-4 cells...... 129

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Figure 4.7: SFN, PIF, and FRE pre-treatment does not offer protection against DOX- and CHOP-induced cytotoxicity in SU-DHL-6 cells ...... 131 Figure 4.8: SFN, PIF, and FRE pre-treatment does not offer protection against DOX- and CHOP-induced cytotoxicity in OCI-LY-3 cells...... 133 Figure 4.9: In multi-organ co-cultures with HPH, lymphoma cells, and cardiomyocytes, PIF and FRE significantly enhance cytotoxicity in target cells while alleviating off-target toxicity ...... 134 Figure A.1 Distribution of key opioid transporters...... 191 Figure B.1 l-THP is non-toxic at pharmacologically-relevant concentrations in human and rat cell lines ...... 236 Figure B.2 Metabolism of cocaine is not altered by l-THP in microsomes while cocaine changes clearance of l-THP ...... 237 Figure B.3 Plasma concentration profile of cocaine is unchanged in the presence of l-THP. ... 239 Figure B.4 Brain concentrations of cocaine were elevated with l-THP co-treatment...... 240 Figure B.5: l-THP does not alter the expression of key drug metabolizing enzymes and transporters in rat brains...... 245 Figure B.6: l-THP does not alter human or rat P-gp function at pharmacologically-relevant concentrations...... 246 Figure C.1: Repeated administration of oxycodone and methadone alters the expression of drug metabolizing enzymes and transporters in rat liver...... 265 Oxycodone and methadone treatment changes the mRNA and protein expression of important drug transporters and metabolizing enzymes in rat kidney ...... 266 Figure C.3: Expression of drug metabolizing enzymes and transporters in rat brain is altered by repeated administration of methadone and oxycodone...... 268 Figure C.4: Baseline plasma and brain concentration profiles of cocaine, oxycodone, and methadone in rats...... 269 Figure C.5: Altered expression of drug metabolizing enzymes and transporters by oxycodone and cocaine alters the pharmacokinetics of cocaine ...... 271 Figure D.1: Timeline of the US Food and Drug Administration approval of monoclonal antibody therapeutics and antibody–drug conjugates...... 281 Figure D.2: Antibody–drug conjugate (ADC) assembly and interaction with target cells...... 283 Figure E.1: Understanding of pharmacogenomics testing and confidence in implementing pharmacogenomics in practice...... 336

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List of Abbreviations

4-OH-CPA - 4-hydroxycyclophosphamide ACN – acetonitrile AD – Alzheimer’s disease AKR – aldo-keto reductase ALA - α-Lineoic acid ALL – acute lymphoblastic leukemia AML – acute myeloid leukemia ARE – antioxidant responsive element AUC - area under the curve bZIP – basic leucine zipper CAR - constitutive androstane receptor CAT – catalase CCK8 – cell counting kit 8 CHOP – cyclophosphamide, doxorubicin, vincristine, prednisone CITCO – (6-(4-chlorophenyl)imidazo[2,1-b][1,3]thiazole-5-carbaldehyde-O-(3,4- dichlorobenzyl)oxime) CLL - chronic lymphocytic leukemia

Cmax - maximum observed concentration CML – chronic myeloid leukemia CMZ - clotrimazole COUP-TF - chicken ovalbumin upstream promoter transcription factor CPA - cyclophosphamide CYP - cytochrome P450 DDI – drug-drug interactions DEX - dexamethasone DIM - 3,3’-diindolylmethane DLBCL – diffuse large B-cell lymphoma

DME - drug-metabolizing enzymes DOX - doxorubicin EFV - efavirenz FRE - frentizole GST – glutathione-S-transferase HAART - highly active antiretroviral therapy hCAR-tg – human CAR transgenic HIV -human immunodeficiency virus HNF-4 - hepatocyte nuclear factor – 4 HO-1 – heme oxygenase 1 HPH - human primary hepatocytes HTS - high-throughput Screen IFA - ifosfamide Keap1 - Kelch like-ECH-associated 1 LXR - liver X receptor MAOI - monoamine oxidase inhibitor MDR1 – multidrug-resistance gene 1 MPH - mouse primary hepatocyte MRP – multidrug resistance-associated protein NHL - non-Hodgkin lymphoma NNRTI - non-nucleotide reverse transcriptase inhibitor NQO1 -` NAD(P)H:quinone oxido-reductase 1 NR1/2 - nuclear receptor binding site 1/2 Nrf2 – nuclear factor (erythroid-derived 2)-like 2 NVP - nevirapine PBRE - phenobarbital-responsive element PBRU - phenobarbital-responsive unit PCN - pregnenolone 16 alpha-carbonitrile

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Pcna – proliferating cell nuclear antigen PD – Parkinson’s disease P-gp – P-glycoprotein PIF - pifexole PK – pharmacokinetics PXR - pregnane X receptor RIF - rifampin ROS – reactive oxygen species SFN - sulforaphane shRNA – short hairpin RNA siRNA – small interfering RNA SNP - single nucleotide polymorphism SOD – superoxide dismutase tBHQ – tert-butylhydroquinone TCPOBOP - 1,4-Bis-[2-(3,5-dichloropyridyloxy)]benzene, 3,3′,5,5′-Tetrachloro-1,4- bis(pyridyloxy)benzene TDM - therapeutic drug monitoring TR - thyroid receptor UGT - UDP-glucuronosyl transferase WT – wild-type

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1. Insights into CYP2B6-mediated Drug- drug Interactions 1.1 Introduction

The human cytochrome P450 superfamily is made up of 18 families and 43 subfamilies containing 57 genes and 59 pseudogenes (Nelson et al., 1996; Estabrook, 2003; Nelson et al.,

2004). Cytochrome P450 (CYP) 2B6 is expressed primarily in the liver and represents one of the approximately fifteen CYP enzymes, distributed amongst P450 families 1-4, predominantly responsible for xenobiotic metabolism (Hidestrand et al., 2001; Purnapatre et al., 2008).

Alongside CYP2B7, a related pseudogene, CYP2B6 is located on the long arm of chromosome

19 within a CYP2B cluster (Hoffman et al., 2001; Nelson et al., 2004). Orthologs of the human

CYP2B6 genes can be found in other species including rats, mice, and dogs, which are termed

CYP2B1, Cyp2b10, and CYP2B11, respectively (Nelson et al., 2004). Notably, unlike in other species, CYP2B6 is the only isozyme of the CYP2B subfamily with metabolic function in humans (Nelson et al., 2004).

Historically, CYP2B6 has been believed to be relatively inconsequential with respect to human xenobiotic metabolism (Mimura et al., 1993; Shimada et al., 1994). However, in recent years, the discovery of important substrates, robust chemical-mediated induction, and genetic polymorphisms of this CYP isozyme has triggered significant academic and industrial research interests. The number of drugs known to be metabolized by this enzyme has drastically increased since the development of effective monoclonal antibodies, the establishment of bupropion as a selective marker of CYP2B6 catalytic activity, and the utilization of recombinant DNA techniques (Stresser and Kupfer, 1999; Faucette et al., 2000). Current estimates indicate that

CYP2B6 accounts for 2-10% of total hepatic CYP content and is, in fact, involved in the metabolism of a significant number of drugs in humans, estimated to be around 8% of all commercially available drugs (Code et al., 1997b; Hanna et al., 2000; Hesse et al., 2000; Rendic,

2002; Wang and Tompkins, 2008). Known CYP2B6 substrates include but are not limited to a number of clinically utilized therapeutic agents such as cyclophosphamide (CPA), ifosfamide

(IFA), tamoxifen, coumarins, artemether, artemisinin, lidocaine, bupropion, ketamine, pethidine, propofol, mexilitine, methadone, mephenytoin, mephobarbital, aminopyrene, antipyrene, clotiazepam, diazepam, temazepam, testosterone, valproic acid, tazofelone, nevirapine (NVP), and efavirenz (EFV) (Table 1.1), as well as an increasing number of recreational drugs, endogenous chemicals, and environmental compounds (Svensson and Ashton, 1999; Faucette et al., 2000; Hesse et al., 2000; Court et al., 2001; Yanagihara et al., 2001; Ward et al., 2003a; Xie et al., 2003; Kharasch et al., 2004b; Ramirez et al., 2004; Yamada et al., 2006; Hodgson and

Rose, 2007; Saitoh et al., 2007)

Metabolism of the same compounds is often achieved by several CYP enzymes generating similar or various intermediate metabolites, which contribute to the biotransformation of substrates to different extents (Wang and Tompkins, 2008; Zhou, 2008). In the case of CYP2B6, although it shares the same substrates with several other CYP enzymes, most notably CYP3A4, there are some biotransformation reactions for which CYP2B6 is the predominant or only known catalyst. For instance, CYP2B6 is the sole enzyme which mediates N-demethylation of mephobarbital, while the 4-hydroxylation biotransformation reaction of this molecule is mediated by the CYP2C family of enzymes (Kobayashi et al., 1999; Kobayashi et al., 2001).

Further, it was shown that CYP2B6 is the only enzyme capable of mediating both O- demethylation and ortho-hydroxylation of the endocrine disruptor methoxychlor, while other

P450 isoforms may contribute only to one biotransformation reaction (Dehal and Kupfer, 1994;

Hu and Kupfer, 2002a; Hu and Kupfer, 2002b).

Predominantly expressed in the liver, CYP2B6 has been estimated to contribute to between 2-

10% of the overall pool of microsomal P450s, with significant inter-individual variability (Code et al., 1997b; Ekins et al., 1998; Stresser and Kupfer, 1999; Hanna et al., 2000; Hesse et al.,

2000; Lang et al., 2001; Lamba et al., 2003; Hesse et al., 2004). A major contributing factor to the variability observed in CYP2B6 expression and function is induction of the enzyme, which results in de novo synthesis of the protein after exposure to particular chemicals (Remmer et al.,

1973). The constitutive androstane receptor (CAR, NR1I3) and the pregnane X receptor (PXR,

NR1I2) are key modulators governing the inductive expression of CYP2B6 (Goodwin et al.,

2001; Faucette et al., 2006b). Activation or inhibition of these receptors by known compounds including rifampin (RIF), phenobarbital (PB), dexamethasone (DEX), and phenytoin can have a significant impact on the downstream expression of important drug-metabolizing enzymes and drug transporters (Willson and Kliewer, 2002; Honkakoski et al., 2003; Chai et al., 2013).

Studies have illustrated that selective activation of CAR over PXR provides preferential induction of CYP2B6 over CYP3A4, while activation of PXR induces both enzymes with less discernible differences (Faucette et al., 2006b). Interestingly, the selective transcription of

CYP2B6 over CYP3A4 by CAR may have clinical relevance with respect to drugs that are predominantly metabolized by CYP2B6, and activators of CAR may function as co-administered facilitators for such biotransformation (Lu et al., 2013b).

Expression of CYP2B6 exhibits significant inter- and intra-individual variability and up to 250- fold of CYP2B6 expression between individuals has being observed (Code et al., 1997b; Hanna et al., 2000). The highly variable enzyme expression arises from multiple factors including

3 genetic polymorphisms, non-genetic factors such as disease conditions, gender differences, and transcriptional induction or suppression by xenobiotics and cytokines (Hesse et al., 2004; Wang and Tompkins, 2008). Though there are several sources, genetic polymorphisms and transcriptional gene regulation are believed to be the major contributors to the observed variability of CYP2B6 expression.

Single nucleotide polymorphisms (SNPs) within the CYP2B6 gene have been shown to be indicative of drug response and pharmacokinetics of administered CYP2B6-substrate drugs

(Ekins and Wrighton, 1999; Zanger et al., 2007; Wang and Tompkins, 2008). The most common such polymorphism is CYP2B6*6 (Q172H, K262R), which occurs at frequencies ranging from

15-60% amongst various populations and results in a functionally deficient allele (Xie et al.,

2003; Guan et al., 2006; Mehlotra et al., 2007). To date, up to 63 alleles covering both coding and non-coding regions of CYP2B6 gene have been identified

(http://www.cypalleles.ki.se/cyp2b6.htm), including more than 30 non-synonymous SNPs which result in amino-acid replacement.

Given the highly inducible and polymorphic nature of the CYP2B6 gene, dramatic individual variability in hepatic CYP2B6 expression has been recognized in humans. Such variation is closely associated with the variable systemic exposure and therapeutic response to a growing list of CYP2B6 substrates. Here we discuss recent developments in areas which exemplify the potential for clinically significant drug-drug interactions (DDI) that arise from both pharmacological and genetic modulations of CYP2B6.

Table 1.1 Clinically utilized CYP2B6-substrate drugs.

Class Substrate Contribution of Ref. Anesthetic Ketamine Major, CYP3A4 Yanagihara, Y. et al. 2001, Minor,CYPs CYP2B6, 2C9 Hijazi, Y. et al. 2001.

Lidocaine Major, CYP2B6, 2A6 Imaoka, S. et al. 1996. Minor, CYP2B6

Propofol Major, CYP2B6 Court, MH. et al. 2001, Minor, CYP2C9 Oda, Y. et al. 2001

Antiarrhythmic Mexiletine Major, CYP2A1 Labbe, L. et al. 2003. Minor, CYP2B6, 2E1

Anticoagulant Coumarins Major, CYP2B6 Ekins, S. et al. 1997, Lake, Minor, CYP2E1, 2C19 BG. et al. 1999. Anticonvulsant Mephenytoin Major, CYP2B6 Ramirez, J. et al. 2004, Ko, Minor, CYP2C9 JW. et al. 1998.

Antidepressant Bupropion Major, CYP2B6 Faucette, SR. et al. 2000, Minor, CYP2D6, 3A4 Hesse, LM. et al. 2000, Turpeinen, M. et al. 2005, Loboz, KK. et al. 2006, Turpeinen, M. et al. 2004. Antiepileptic Mephobarbital Major, CYP2B6 Kobayashi, K. et al. 1999.

Valproic Acid Major, CYP2A6 Kiang, TK. et al. 2006. Minor, CYP2B6, 1A1

Anti- Aminopyrine Major, CYP2B6, 2C19 Niwa, T. et al. 1999, Niwa, inflammatory Minor, CYP2C8, 2D6 T. et al. 2000.

Antipyrine Major, CYP3A4, 2C Engel, G. et al. 1996. Minor, CYP2B6, 1A2

Tazofelone Major, CYP3A4 Surapaneni, SS. et al. 1997. Minor, CYP2B6

Antimalarial Artemether Major, CYP2B6 Honda, M. et al. 2011. Minor, CYP3A4

Artemisinin Major, CYP2B6 Svensson, US. et al. 1999, Minor, CYP3A4 Burk, O. et al. 2005.

Table 1.1 continued

Antiretroviral Efavirenz Major, CYP2B6, Ward, BA. et al. 2003, Minor, CYP3A Tsuchiya, K. et al. 2004, Desta, Z. et al. 2007.

Nevirapine Major, CYP2B6, 3A4 Rotge r, M. et al. 2005, Minor, CYP2D6 Erickson, DA. et al. 1999. Chemotherapy Cyclophosphamide Major, CYP2B6 Xie, HJ. et al. 2003, Minor, CYP3A4, 2C9 Lindley, C. et al. 2002, Huang, Z. et al. 2000, Roy, P. et al. 1999a.

Ifosfamide Major, CYP2B6, 3A4 Huang, Z. et al. 2000, Roy, Minor, CYP2C9, P. et al. 1999a. Roy, P. et 2C19 al. 1999b.

Tamoxifen Major, CYP2E1, 2D6 Coller, JK. et al. 2002, Minor, CYP2B6, 3A4 Styles, JA. et al. 1994.

MAOI Selegiline Major, CYP2B6, 2C19 Hidestrand, M, et al. 2001, Minor, CYP3A4, 1A2 Salonen, et al. 2003.

Opioid Methadone Major, CYP2B6, 3A4 Kharasch, ED. et al. 2004, Gerber, JG. et al. 2004.

Pethidine Major, CYP2B6 Ramirez, J. et al. 2004. Minor, CYP3A4, 2C19 Psychotropic Clotiazepam Major, CYP2B6, 3A4 Niwa, T. et al. 2005. Minor, CYP2C18, 2C19

Diazepam Major, CYP2B6, 2C19 Onof, S. et al. 1996, Yang, Minor, CYP3A4 TJ. et al. 1998, Ekins, S. et al. 1998.

Temazepam Major, CYP2B6 Onof, S. et al. 1996, Ekins, Minor, CYP2C, 3A S. et al. 1998.

Steroid Testosterone Major, CYP3A4 Imaoka, S. et al. 1996. Minor, CYP2B6

1.2 CYP2B6 Polymorphisms

Although pharmacogenetics of genes encoding drug-metabolizing enzymes has been the subject of intensive studies for many years, only within the last ten years or so has the analysis of

CYP2B6 genetic variations been examined and partially elucidated. The first systematic investigation of genetic polymorphism in the CYP2B6 gene was conducted by Lang, T. et al., in

2001 using cDNA derived from 35 German Caucasians (Lang et al., 2001). This early study, with the focus on all exons, resulted in the identification of nine novel SNPs, of which five are nonsynonymous mutations in exon 1 (C64T, Arg22Cys), exon 4 (G516T, Gln172His), exon 5

(C777A, Ser259Arg and A785G, Lys262Arg) and exon 9 (C1459T, Arg487Cys) and four are silent mutations (C78T, G216C, G714A and C732T) (Lang et al., 2001; Lang et al., 2004). In

2003, a more comprehensive analysis of SNPs in the coding region, introns, or 5’-flanking sequences of CYP2B6 gene from 80 DNA samples of Caucasian, African, and Hispanic

Americans has found 10 SNPs in the CYP2B6 promoter, seven in the coding region, and one in intron 3 (Lamba et al., 2003). With additional subsequent investigations, a much-improved understanding of CYP2B6 genotype-phenotype associations has been achieved. Clearly, polymorphisms of CYP2B6 contribute significantly to a number of clinical important DDI.

1.2.1 Nonsynonymous SNPs in CYP2B6

CYP2B6*6, defined by the 516G>T and 785A>G mutations, has been elucidated as the most clinically relevant polymorphism of CYP2B6. These particular mutations harboring two amino acid (Q172H and K262R) replacements result in decreased levels of expression and function of

CYP2B6 protein (Hofmann et al., 2008). CYP2B6*6 and the anti-HIV EFV probably represent the most convincing gene-drug pair in elucidating the clinical influence of CYP2B6

7 polymorphisms on drug administration. EFV is a widely used non-nucleoside reverse- transcriptase inhibitor (NNRTI) utilized as part of a highly active anti-retroviral therapy

(HAART) for treatment of HIV-1 infections alongside emtricitabine and tenofovir within the

Atripla regimen. Compared with other hepatic CYPs, CYP2B6 is the main catalyst of EFV primary and secondary metabolism (Ogburn et al., 2010). Importantly, individuals expressing this variant of CYP2B6 have demonstrated significantly decreased rates of 8-hydroxylation of

EFV and increased circulating plasma concentrations of the parent drug (Xu et al., 2012a). Many studies have explored the impact of the 516G>T polymorphism on EFV pharmacokinetics and have associated this mutation with elevated plasma levels resulting in neurotoxicity and CNS side effects (Haas et al., 2004; King and Aberg, 2008; Lubomirov et al., 2010; Ribaudo et al.,

2010; Maimbo et al., 2012), liver injury (Yimer et al., 2012) , and acquired drug resistance

(Ribaudo et al., 2006; Lubomirov et al., 2011; Wyen et al., 2011). Genotyping for this particular

CYP2B6 variant has been proposed as a method to aid in personalizing EFV dosages for individual patients. Genotyping would also assist in identifying individuals who may be classified as poor metabolizers or ultra-rapid metabolizers of EFV, and who may benefit from early therapeutic drug monitoring (Nolan et al., 2006; Cabrera Figueroa et al., 2010). A retrospective study reported that therapeutic drug monitoring and dose reduction in patients with the CYP2B6*6 homozygotes reduced the EFV plasma concentration from toxic levels back into normal therapeutic levels. This study further revealed that those patients with the homozygous

CYP2B6*6 genotype receiving lower EFV doses experienced fewer adverse events following treatment, and increased the proportion of patients exhibiting an undetectable HIV viral load

(Martin et al., 2014). To date, multiple clinical studies consistently indicate that CYP2B6*6 is associated with high EFV plasma concentration and increased central nervous toxicity (Nolan et

8 al., 2006). Thus, it is reasonable to speculate that implementation of CYP2B6 genotyping test clinically would benefit HIV-infected patients receiving an EFV-based regimen.

NVP, another NNRTI, has been associated with significant toxicities including, in some cases, life threatening rashes and/or hepatotoxicity during the early weeks of therapy (Rivero et al.,

2007; Ciccacci et al., 2010). Similarly to EFV, the 516G>T polymorphism of CYP2B6 has been studied with respect to its impact on NVP pharmacokinetics. In individuals with the CYP2B6

*6/*6 or *6/*18 haplotype, NVP clearance is significantly decreased and circulating plasma concentrations are elevated (Schipani et al., 2011; Brown et al., 2012a; Heil et al., 2012). The

983T>C nonsynonymous SNP has been shown to affect NVP pharmacokinetics in a similar manner (Wyen et al., 2008; Schipani et al., 2011). While literature regarding chemical alteration of CYP expression and its resulting impact on NVP disposition is currently lacking, it is expected that increased expression of CYP2B6 and CYP3A4 would increase the metabolism and clearance of NVP, potentially resulting in non-therapeutic plasma concentrations, while inhibition of these enzymes may result in increased circulating levels and potential serious toxicities.

Comparatively, the role of CYP2B6*6 in CPA application appears to be less convincing. CPA is an alkylating prodrug requiring hepatic bioactivation and a CYP2B6 substrate. To date, the impact of polymorphisms of CYP2B6 on hepatic metabolism of CPA remains a conflicted topic.

It has been demonstrated in vitro that human livers expressing CYP2B6*6 exhibit markedly enhanced catalytic activity in CPA 4-hydroxylation although these individual samples also expressed comparatively low levels of CYP2B6 protein (Ariyoshi et al., 2011). Studies performed by Xie et al. concluded that although there are differences in CYP2B6 protein expression and function, there is no significant difference in overall 4-hydroxylation of CPA

9 between liver donors (Xie et al., 2003). However, clinically it has been reported that CYP2B6*6 itself is a determinant of poor response to FC (fluradabine, CPA) therapy in the treatment of chronic lymphocytic leukemia (Johnson et al., 2013).

Like CPA, ifosfamide (IFA) is another commonly prescribed antitumor prodrug within the oxazaphosphorine class of alkylating agents. It is frequently utilized in the treatment of solid tumors and hematologic malignancies (Chugh et al., 2007). The bioactivation of IFA in the liver is catalyzed by multiple CYP isoforms with CYP2B6 and CYP3A4 being the most prevalent contributors to its metabolism; each isoform contributes roughly equivalently to the 4- hydroxylation of IFA to yield its active metabolite, 4-hydroxyifosfamide (Roy et al., 1999a;

Zhang et al., 2005b). Up to 20-fold interpatient differences have been reported in the pharmacokinetics of IFA and are likely attributable to pharmacogenetic differences (Aleksa et al., 2005). CYP2B6*6 heterozygous and homozygous carriers have been linked with decreased catalytic activity and hepatic expression of CYP2B6 functional protein, increased IFA plasma concentrations, and increased toxicities as compared with reference phenotypes (Xie et al., 2003;

Aleksa et al., 2005).

CYP2B6*5, designated by a C>T SNP in exon 9, has also been examined with respect to its impact on CPA (Xie et al., 2003; Bachanova et al., 2015). Lymphoma patients with this CYP2B6 variant have demonstrated significantly altered remission rates and clinical outcomes. Patients expressing the CYP2B6*1/*5 genotype exhibited a greater 2-year relapse rate and diminished overall survival as compared to those with the reference allele. Bachanova, et al. suggested that the CYP2B6*5 variant is an independent indicator of a patient’s chance of successful treatment when utilizing autologous hematopoetic cell transplantation and high dose CPA-based chemotherapy (Bachanova et al., 2015). Similar to CYP2B6*6, Caucasian female carriers of the

CYP2B6*5 variant exhibit decreased protein expression which may result in decreased bioactivation of CPA (Lang et al., 2001; Lamba et al., 2003; Helsby et al., 2010).

Additionally, CYP2B6*18, defined by the T983C SNP (I328T, exon 7), is found with relative frequency of 4-12% in African populations, though not in Caucasians and Asians (Klein et al.,

2005; Mehlotra et al., 2007). This particular allele exhibits a loss of functional protein (Klein et al., 2005; Zhang et al., 2012). This SNP was associated with a three-fold increase in mean plasma EFV concentrations in African HIV patients (Wang et al., 2006). When combined with the A785G SNP, these mutations together make up the CYP2B6*16 allele which has been associated with an even greater increase (5-fold) in mean plasma EFV concentrations, indicating a synergistic effect between the two SNPs (Wang et al., 2006).

1.2.2 SNPs in the Promoter Region of CYP2B6

In addition to the identified genetic variations in the coding regions of the CYP2B6 gene, polymorphisms within the noncoding region may influence the overall expression of this gene

(Lamba et al., 2003; Zukunft et al., 2005; He et al., 2006). Interestingly, some of the SNPs identified in the promoter region of CYP2B6 lay within the binding sites of several transcription factors (Li et al., 2010; Zhang et al., 2011a). For example, the SNP at -2320T>C is located in a putative hepatocyte nuclear factor (HNF4)-binding site, the -750T>C and -575C>T are within binding sites for HNF1 and Sp-1, respectively, while the -82T>C generates a novel CCAAT- enhancer-binding protein (C/EBP)α binding site (Lamba et al., 2003; Hesse et al., 2004; Zukunft et al., 2005). Notably, the -82T>C substitution not only introduces a functional C/EBP binding site into the CYP2B6 promoter, but also shifts the transcriptional starting site approximately 30

11 base pairs (bp) downstream (Zukunft et al., 2005). Further analysis revealed that livers genotyped -82T>C were associated with an approximately 2-fold higher CYP2B6 mRNA expression in comparison to the reference -82T/T carriers. In exploring whether this polymorphism could affect drug-induced expression of CYP2B6, Li et al., demonstrated a strong synergism between -82T>C mutation and the activation of PXR by ligand binding via cell-based reporter assays in HepG2 and Huh7 cells (Figure 1.1) (Li et al., 2010). Mechanistic studies revealed that the -82-bound C/EBPα can interact with PXR and loops the PXR bound distal phenobarbital-responsive enhancer module (PBREM) toward the proximal CYP2B6 transcriptional start site. These findings suggest that individuals carrying -82T>C mutant might be hypersensitive to drugs that are CYP2B6 substrates when co-administered with PXR-type inducers. In CYP2B6 promoter, the most frequent SNPs identified was the -750T>C mutation that occurred in close to 50% or more of all ethnic groups studied (Lamba et al., 2003). In a 2007 study, Nakajima et al. described the impact of the -750T>C substitution on CPA hydroxylation by CYP2B6 (Nakajima et al., 2007). Patients possessing this SNP exhibited significantly decreased area under the concentration-time curve (AUC) ratios of 4-OH-CPA/CPA, indicating decreased enzyme activity. A decrease in CPA hydroxylation and bioactivation by this genetic mutation can significantly alter the potency of CPA and detection of this polymorphism may be valuable as an early predictor of adverse effects or diminished therapy (Nakajima et al., 2007).

1.3 Transcriptional Regulation of CYP2B6

Transcriptional regulation of CYP2B6 has been implicated as one of the major contributing factors to the observed inter- and intra-individual variations in the expression of this CYP

12 isozyme. For many years, the inducibility of its rodent counterparts, particularly in mice and rats, has been studied as the model gene for PB-mediated CYP induction phenomenon(Hardwick et al., 1983; Sueyoshi and Negishi, 2001). However, significant species differences exist in the induction of CYP enzymes limiting the utility of these models for direct human extrapolation.

For example, 1,4-bis[3,5-dichloropyridyloxy]benzene (TCPOBOP) and pregnenolone 16 alpha- carbonitrile (PCN) are known to significantly induce CYP3A and CYP2B in rodents, but have no effects on related humans CYPs. On the other hand, 6-(4-chlorophenyl)imidazo[2,1- b][1,3]thiazole-5-carbaldehyde-O-(3,4-dichlorobenzyl)-oxime (CITCO) and RIF potently induce human CYP2B6 and CYP3A4 without affecting the expression of their rodent counterparts

(Kolars et al., 1992; Honkakoski et al., 1996; Lake et al., 1998; Maglich et al., 2003).

In humans, cultured primary hepatocytes are widely accepted as the most appropriate in vitro model for assessing the induction of hepatic drug-metabolizing enzymes as nearly all immortalized hepatic cell lines express significantly lower levels of drug-metabolizing enzymes as well as key liver-enriched transcriptional factors (LeCluyse, 2001a). In human primary hepatocyte (HPH) cultures, expression of CYP2B6 is well-maintained and robust induction in response to prototypical inducers has been observed. In fact, in certain liver donors, CYP2B6 can be induced to such a high level that is comparable to that of CYP3A4, which is widely accepted as the most abundant CYP isoform expressed in the human liver. Utilizing HPH as an in vitro model of the human liver, several known CYP3A4 and CYP2C inducers have been shown to simultaneously augment the expression of CYP2B6 (Pascussi et al., 2000; Goodwin et al., 2001), suggesting these CYP enzymes may share common transcriptional regulation mechanisms and coordinate a defensive hepatic responsive network to xenobiotic challenges.

Figure 1.1 Activation of PXR in cell-based reporter assays. Synergistic activation of CYP2B6 reporter by -82T4C mutation and PXR activation. The SNP -82T4C introduced a C/EBPα binding site in the CYP2B6 promoter (A). The presence of this mutation and RIF-mediated activation of PXR synergistically enhanced the transcriptional activity of CYP2B6 in both HepG2 (B) and Huh7 cells (C). This figure was adopted from Li et al., 2010, Mol. Pharmacol. and used with permission from the copyright holder, Elsevier Publishing Group.

1.3.1 CAR- and PXR-mediated Induction of CYP2B6

Over the years, researchers have observed potent induction of CYP2B genes by barbiturates in the liver of many different species. The first study illustrating molecular mechanisms behind this induction came in 1995 using cultured adult rat hepatocytes (Trottier et al., 1995). A functional analysis of the 5’ flanking promoter region of rat CYP2B1 and CYP2B2 has linked PB-mediated induction to a 163-bp DNA sequence, termed the PB-responsive element (PBRE) or PB- responsive unit (PBRU), located -2155-2318-bp from the transcription start site of CYP2B1/2

(Trottier et al., 1995; Park et al., 1996). Subsequent investigations led to the localization of a 51- bp similar sequence named PBREM at positions of -2339/-2289 and -1733/-1683 within the promoters of mouse Cyp2b10 and human CYP2B6, respectively (Honkakoski et al., 1998b;

Inoue and Negishi, 2008). Later, in the distal upstream region of CYP2B6 gene, a xenobiotic- responsive enhancer module (XREM) located around -8.5 kb from the transcriptional start site of

CYP2B6 was also identified and functionally evaluated (Wang et al., 2003b). Together, these response elements coordinate the optimal induction of CYP2B genes by PB-like inducers.

Another important milestone in our understanding of the mechanisms underlying drug-induced

CYP2B expression was achieved when the nuclear receptor CAR was functionally linked to

CYP2B transcription (Honkakoski et al., 1998b). In HepG2 cell-based reporter assays, nuclear receptors including liver X receptor , retinoid X receptor (RXR), CAR, thyroid hormone receptor, HNF4, and chicken ovalbumin upstream promoter-transcription factor were initially screened to examine potential transactivation of a luciferase reporter construct containing the mouse PBREM (Honkakoski et al., 1998b). Of these receptors, only CAR demonstrated robust transactivation of the responsive elements identifying it as the first nuclear receptor able to activate PBREM-mediated gene transcription (Honkakoski et al., 1998b). CAR exhibits this

15 regulatory function by binding to the nuclear receptor binding site 1 (NR1) and NR2 motifs within the PBREM as a heterodimer with RXR in the nucleus of cells. The affinity of this binding is increased significantly by treatment with PB. In mouse hepatocytes, as well as HepG2 cells, reporter constructs containing the Cyp2b10 reporter or CYP2B6 reporter, respectively, were activated by a myriad of compounds including PB, TCPOBOP, clotrimazole, metyrapone, and chlorpromazine (Honkakoski et al., 1998a; Sueyoshi et al., 1999b). Downstream, these compounds induced the expression of Cyp2b10 in mouse hepatocytes and CY2B6 in HPH. The

CAR-mediated induction of CYP2B gene by PB-type compounds was definitively established by experiments in CAR-null mice, in which loss of CAR completely eliminated the induction of

Cyp2b10 by PB and TCPOBOP (Wei et al., 2000).

Around the same time, a novel orphan nuclear receptor, PXR, was cloned and firmly established as the primary modulator for drug-induced expression of CYP3A genes in different species

(Goodwin et al., 2001; Smirlis et al., 2001). Evolutionarily, CAR and PXR represent the two closest members in the whole nuclear receptor superfamily, sharing approximately 40% amino acid identity in their ligand binding domains. Although CYP2B and CYP3A are the primary targets of CAR and PXR, respectively, accumulating evidence reveals that CAR and PXR can regulate each other’s transcriptional targets through cross-talk (Moore et al., 2000; Kodama et al., 2004). Like CAR, the PXR-RXR heterodimer binds to the PBREM in the CYP2B promoter with greater affinity to the NR1 site than the NR2 site (Goodwin et al., 2001). In mice, known

PXR ligands such as DEX and PCN significantly increased the expression of Cyp2b10 while this induction was not observed in PXR-null mice (Honkakoski and Negishi, 1998; Maglich et al.,

2002). Notably, both these nuclear receptors display significant promiscuity in their ligand recognition and downstream target gene regulation, mediating the transcription of numerous

16 genes involving drug metabolism and transport, energy homeostasis, and cell proliferation (Zhou et al., 2006; Roth et al., 2008; Li et al., 2015b). Known CYP2B6 inducers such as PB, RIF, clotrimazole, phenytoin, and carbamazepine have also been shown to induce CYP3A4, CYP2C9,

UDP-glucuronosyltransferase 1A1 (UGT1A1), and the important efflux transporter, multidrug resistance protein 1 (MDR1) (Geick et al., 2001; Sugatani et al., 2001; Ferguson et al., 2002;

Wang et al., 2003c).

It is important to note that recognizing the role of CAR and PXR in CYP regulation not only provides a rational explanation for which many drugs can induce the same class of drug- metabolizing genes such as CYP2B6 and CYP3A4, but also supports the existence of a metabolic protection network coordinated by both receptors. Moreover, such findings also offer a mechanistic justification for the observed species-specific induction of CYP2B and CYP3A between human and rodents. For instance, TCPOBOP and PCN are selective activators of mouse

CAR and PXR, respectively, and induce the expression of Cyp2b10 and Cyp3a11 but not their human counterparts (Moore et al., 2000; Kodama et al., 2004). On the other hand, CITCO and

RIF activate human CAR and PXR and induce the expression of human but not mouse CYP2B and CYP3A genes, respectively (LeCluyse, 2001b; Maglich et al., 2003). In CAR- and PXR- humanized mice with their rodent counterparts being knocked out, induction of Cyp2b10 and

Cyp3a11 was achieved by CITCO and RIF but not TCPOBOP and PCN, suggesting CAR and

PXR are the xenobiotic dictators that convey the observed species-specific induction of CYP2B and CYP3A genes (Xie et al., 2000b; Zhang et al., 2013). Interestingly, human (h) PXR appears to have evolved into an extremely promiscuous xenobiotic sensor and almost all known hCAR activators activate hPXR as well. For example, PB is a rather selective activator of rodent CAR not PXR, while it exhibits effective activation of both human CAR and PXR (Kawamoto et al.,

1999; LeCluyse, 2001b). Importantly, although each of these nuclear receptors holds an impact on the expression of these target genes, their respective contributions to the induction of individual genes can vary. It has been well-recognized that the selective activation of CAR preferentially induces the expression of CYP2B6 over CYP3A4 while activation of PXR induces both P450 enzymes in concert (Faucette et al., 2006b).

1.3.2 Induction of CYP2B6 Expression by other Nuclear Receptors

To date, it has been clearly established that induction of the CYP2B6 gene by xenobiotics is mediated predominantly by hCAR and hPXR through interactions with the PBREM and XREM located upstream of the CYP2B transcriptional start site (Honkakoski et al., 1998b; Goodwin et al., 2001; Smirlis et al., 2001). However, the dramatic interindividual variability in CYP2B6 gene induction cannot be fully explained by a simple PXR/CAR-based induction model. For instance, the majority of PXR/CAR target genes (e.g CYP2Cs and UGT1A1) are induced relatively moderately. This is in stark contrast to the potent induction of CYP2B6 and CYP3A4 genes observed clinically and in HPH cultures. On the other hand, over-expression of CAR and/or PXR alone failed to fully restore the basal and inductive expression of CYP2B6 in non-hepatic or hepatoma cell lines (Gervot et al., 1999). Accumulating evidence suggests that other nuclear receptors and liver enriched transcriptional factors may also be involved in the transcription of

CYP2B6 and contribute to the large individual variations of CYP2B6 expression in the human population.

The role of the glucocorticoid receptor (GR) in CYP2B regulation has been more firmly established in rodents than in humans. DEX, a synthetic glucocorticoid and GR activator, efficiently induced the expression of rat CYP2B2 and mouse Cyp2b10 both in vivo and in cultured primary hepatocytes (Honkakoski et al., 1996). Importantly, in GR-deficient mice, not

18 only did treatment with DEX fail to induce Cyp2b10 expression, but the basal level of Cyp2b10 was also significantly decreased (Audet-Walsh and Anderson, 2009). Further in silico analysis resulted in the identification of putative glucocorticoid responsive elements (GRE) in the promoters of mouse Cyp2b10 and rat CYP2B1/2, but not in the promoter of CYP2B6. Although sub-micromolar concentrations of DEX dose-dependently induce the expression of CYP3A4 but not CYP2B6 in HPH, co-treatment PB and RIF with the same concentration range of DEX enhanced the induction of both CYP enzymes (Pascussi et al., 2000; Wang et al., 2003c; Faucette et al., 2004). Interestingly, DEX increases the expression of CAR and PXR in a GR-dependent manner and a functional GRE was later located in the promoter of CAR itself, suggesting GR activation may indirectly regulate CYP2B6 by facilitating the availability of CAR and PXR.

Initial screening for potential endogenous CAR activators by Negishi and colleagues resulted in the identification of estradiol (E2) and estrone as effective mouse CAR (mCAR) activators at pharmacological concentrations (Kawamoto et al., 2000). In mouse primary hepatocytes, these estrogens increased the expression of Cyp2b10 and nuclear accumulation of mCAR, the first step of CAR activation. It appears that this estrogen-dependent induction of Cyp2b10 is specific to mice and most likely ER-independent given that there is no estrogen responsive element (ERE) identified in the Cyp2b10 promoter. Further, not all ER agonists enhance Cyp2b10 expression.

However, such contention may not apply to the case for human CYP2B6. It has been known that a greater level of CYP2B6 is expressed in ERα-positive compared to ERα-negative breast tumor tissues (Bieche et al., 2004). In a chromatin immunoprecipitation and promoter focused microarray (ChIP-on-chip)-based screening in T-47D human breast cancer cells, multiple ERα- bound regions were located in the upstream regulatory sequences of the CYP2B gene cluster (Lo et al., 2010). Further analysis revealed a functional ERE located at -1669/-1657 right next to the

PBREM of CYP2B6. Luciferase reporter assays demonstrated that both ERα and ERβ are capable of stimulating CYP2B6 transactivation, while such activation was completely abolished when the ERE was deleted. Moreover, physiological level of E2 significantly induced the expression of CYP2B6 in T-47D cells (Lo et al., 2010). Compared with extrahepatic cells, E2 was rapidly metabolized in primary hepatocytes with a first order elimination half-life of 37 min

(Koh et al., 2012). To overcome this rapid clearance, Jeong and colleagues replenished E2 regularly during the treatment of HPH to achieve an average concentration of ~ 100 nM, which reflects the plasma concentration reached at term pregnancy. Under such experimental condition, the authors observed that E2 robustly increased the expression of CYP2B6 and activation of both

CAR and ER. Moreover, concurrent activation of both ER and CAR by E2 enhanced CYP2B6 expression in a synergistic manner, suggesting a positive cross-talk between these two receptors

(Koh et al., 2012).

Knowledge of transcriptional regulation of CYP2B6 expression has grown substantially in the past two decades. In addition to its known transcriptional regulators such as nuclear receptors including CAR, PXR, GR, and ER, recently, several studies demonstrated that expression of the

CYP2B6 gene can be influenced by interactions between nuclear receptors and liver-enriched transcriptional factors such as HNF4α, C/EBPα, and HNF3β (Jover et al., 1998; Inoue and

Negishi, 2009; Li et al., 2016b). Multiple responsive elements for different liver-enriched transcriptional factors have been identified in the promoter of CYP2B6. Importantly, with the presence of CAR/PXR agonists or other transcription factors like early growth response 1, the distally recruited nuclear receptor can be efficiently looped to the proximate promoter of

CYP2B6 and synergistically enhance the CYP2B6 transcription (Inoue and Negishi, 2009).

1.4 Implications for clinical drug-drug interactions and adverse events

CYP2B6 shares an overlapping substrate spectrum with other CYP enzymes including, in particular, CYP3A4. Its pharmacological/toxicological significance is, however, distinguished by a distinct affinity for specific drug substrates and unique enzymatic biotransformation reactions.

As increasing numbers of substrates of CYP2B6 are identified, it becomes more likely that we will uncover significant DDI mediated by this enzyme. It is not uncommon for multiple drugs to be administered simultaneously to an individual. Combination therapies have proven to be rather effective in combatting cancers, autoimmune disorders, and other prevalent diseases. As such, it is important to understand the impact drugs may have on the expression and function of genes responsible not only for their own disposition, but the metabolism and clearance of any co- administered agents.

Two of the most well-studied and better understood drugs with respect to CYP2B6 metabolism are EFV and CPA. Both of these widely used drugs have very narrow therapeutic indices, associated toxicities, and variations in CYP2B6 expression and function lead to significantly altered drug plasma concentrations of each agent (Desta et al., 2007; Nakajima et al., 2007). In the case of CPA increased expression or function of CYP2B6 may be beneficial as it may result in an increase in circulating concentrations of the active moiety (Lu et al., 2013b; Hedrich et al.,

2016b). However, in the case of EFV, increased metabolism may lead to non-therapeutic concentrations in circulation (Desta et al., 2007). Conversely, decreased metabolic capacity of the enzyme may result in toxic concentrations of EFV in circulation or non-therapeutic concentrations of the active CPA moiety.

CPA has been used extensively for the treatment of various cancers and autoimmune disorders for more than half a century. CPA is metabolized to its active form, 4-OH-CPA in the liver primarily by CYP2B6, with moderate contributions from CYP2C9, CYP2C19, and CYP3A4

(Clarke and Waxman, 1989; Griskevicius et al., 2003; Xie et al., 2003). Following the metabolism of CPA to 4-OH-CPA, it produces a DNA alkylating phosphoramide mustard which yields therapeutic cytotoxicity. Alternatively, CPA may be metabolized via N-dechloroethylation exclusively by CYP3A4 yielding a neurotoxic metabolite, chloroacetaldehyde, which contributes to the narrow therapeutic index of CPA (Clarke and Waxman, 1989; Yu et al., 1999). Thus, it has been hypothesized that selective induction of CYP2B6 over CYP3A4 could significantly increase the beneficial biotransformation of CPA to 4-OH-CPA without concomitant augmentation of the formation of the toxic chloroacetaldehyde (Fig. 1.2) (Lu et al., 2013b).

Recently, we have demonstrated that selective activation of CAR and downstream preferential induction of CYP2B6 over other enzymes and transporters with a selective small molecule activator can facilitate the bioactivation of CPA to 4-OH-CPA and improve the therapeutic index of CHOP chemotherapy for the treatment of non-Hodgkin lymphoma(Hedrich et al., 2016b). It is expected that if such interactions held true in vivo, inclusion of a selective hCAR activator in the CHOP regimen may significantly reduce the dose of the chemotherapeutic agents and side toxicity without sacrificing therapeutic efficacy. By manipulating the expression of the CYP2B6 isozyme, we may be able to alter the front-line strategies employed to treat hematopoetic malignancies(Lu et al., 2013b; Hedrich et al., 2016b). EFV is a frequently prescribed NNRTI utilized as a treatment for HIV-1 infections. EFV has a very narrow therapeutic index as

Figure 1.2 Schematic illustration of CPA metabolism and the potential role of CAR in CPA bioactivation. This ﬁgure was adopted from Wang et al. with minor modiﬁcation and used with permission from the copyright holder, Elsevier Publishing Group.

23 increased plasma concentrations of EFV have been shown to result in toxicities while insufficient plasma concentrations do not achieve anti-viral therapy (Ward et al., 2003a; Nolan et al., 2006; Rakhmanina and van den Anker, 2010). CYP2B6 is the primary catalyst of EFV metabolism and the function of this enzyme, as well as its induction or inhibition, plays an important role in maintaining therapeutic yet non-toxic concentrations of the drug in circulation

(Ward et al., 2003a). EFV is thought to auto-induce its own metabolism by increasing the expression of CYP2B6 via activation of CAR and PXR (Robertson et al., 2008). Further, EFV has been shown to competitively inhibit bupropion metabolism by CYP2B6 and to inhibit several CYP2C isoforms including CYP2C8, 2C9, and 2C19 (Xu and Desta, 2013). Together, the impact EFV has on important metabolizing enzymes can result in significant DDI with other antiretrovirals or medications commonly taken concurrently with EFV therapy.

Artemisinin is an extract obtained from the Chinese herb Artemisia annua and is utilized as an antimalarial agent, though poor bioavailability limits its efficacy (Medhi et al., 2009). The metabolism of artemisinin is mediated primarily by CYP2B6 in the liver with some contribution from CYP3A4, though it has been proposed that their relative contributions are reversed in patients with low levels of functional CYP2B6 (Svensson and Ashton, 1999). Inhibition of

CYP2B6 in vitro by orphenadrine has been shown to decrease artemisinin disappearance rates by

75% (Svensson et al., 1998). This result indicates that inhibition of CYP2B6 may result in increased plasma concentrations of drug which would, in turn, increase the risk of adverse events. While there is currently no literature available regarding the impact of CYP2B6 pharmacogenetics on artemisinin disposition, it is reasonable to anticipate that polymorphisms which result in decreased expression or function of CYP2B6 may potentially contribute to decreased metabolism and clearance of the drug, and potentially increased toxicities.

Bupropion, an antidepressant which is often utilized as a non-nicotine aid to quit smoking, is metabolized to hydroxybupropion in human liver microsomes predominantly by CYP2B6 with only negligible contribution from CYP2E1 (Faucette et al., 2000; Hesse et al., 2000; Zhang et al.,

2011a). Long-term use of bupropion has been associated with select toxicities including seizures

(Davidson, 1989). In vivo, plasma concentrations of bupropion are typically less than that of hydroxybupropion, indicating that it may be the metabolite which is responsible for the associated toxicity of this drug. Thus, chemical activation or genetic variations resulting in increased CYP2B6 activity that enhances the metabolism of bupropion and, in turn, increased circulation of the hydroxylated moiety could lead to increased risk for adverse event s(Hesse et al., 2000). Further, bupropion has been demonstrated to be an effective inhibitor of other important CYP isoforms in vitro including CYP2D6 which is responsible for an estimated 25% of clinically utilized drugs (Pollock et al., 1996; Kotlyar et al., 2005). This indicates that co- administration of bupropion alongside a drug that is a CYP2D6 substrate could result in harmful

DDI due to varied circulating drug levels which may cause unexpected toxicities.

Ketamine has multiple clinical uses including analgesia and moderate stimulation of the cardiovascular system. CYP2B6 is the primary enzyme responsible for the N-demethylation of ketamine enantiomers to pharmacologically active products (Yanagihara et al., 2001). Currently, limited literature is available regarding DDI involving ketamine in humans. However, it has been demonstrated that co-administration of ketamine with diazepam, a substrate of CYP2C19 and

CYP3A4, or secobarbital, a CYP2B6 inhibitor, significantly increased the plasma half-life of ketamine (Lo and Cumming, 1975; Idvall et al., 1983).

Methadone is a synthetic opioid, which is administered as a racemic mixture for the treatment of chronic pain. CYP2B6 mediates a stereo-selective metabolism reaction of methadone towards

25 the (S)-enantiomer (Totah et al., 2008). The (R)-enantiomer of methadone produces the analgesic effects of the drug by binding to and activating the μ-opioid receptor while the (S)-enantiomer produces undesirable cardiotoxicity by inhibiting the cardiac potassium channel (Karch and

Stephens, 2000; Totah et al., 2008). As such, decreased CYP2B6 activity is associated with decreased metabolism of the (S)-enantiomer of methadone and increased plasma concentrations of this enantiomer. Elevated levels of (S)-methadone in circulation are associated with a greater risk of cardiac side effects and death (Eap et al., 2007).

Pethidine, also known as meperidine, another synthetic opioid, is also metabolized in the human liver by CYP2B6, CYP3A4 and CYP2C19 accounting for 57, 28, and 15% of its total intrinsic clearance, respectively (Ramirez et al., 2004). The major metabolite of pethidine, norpethidine, can accumulate in the brain and lead to significant central nervous toxicities when pethidine is administered at high dosage (Holmberg et al., 1982; McHugh, 1999). The rates of formation and clearance of norpethidine from pethidine can be difficult to anticipate due to the highly polymorphic and inducible nature of CYP2B6 (Ramirez et al., 2004). Increased expression of

CYP2B6 can result in an increase in the formation of norpethidine and a resultant increase in adverse events, most frequently manifesting as convulsions (Stone et al., 1993). Due to the unpredictable nature of pethidine metabolism and disposition, it is often withheld from elderly patients or patients with compromised liver or kidney function (Stone et al., 1993; Ramirez et al.,

2004).

Selegiline is frequently used in the treatment of Parkinson’s disease. Sridar et al. have shown selegiline to be a strong inhibitor of CYP2B6-mediated metabolism of bupropion in vitro, increasing the Km of bupropion from 10 to 92 µM and decreasing the k(cat) by approximately

50% (Sridar et al., 2012). This strong inhibition of CYP2B6 by selegiline highlights a serious potential of DDI for combination therapies involving bupropion.

Collectively, along with increased understanding of the transcriptional regulation of CYP2B6 and its pharmacogenetics, the potential clinical implication of CYP2B6 in the context of DDIs is escalating. Altered expression of CYP2B6 could result in unexpected drug-drug and gene-drug interactions which may be either harmful or beneficial.

1.5 Concluding Remarks

Although historically believed to be relatively inconsequential with respect to human drug metabolism, over the past two decades CYP2B6 has been identified as a catalyst for many biotransformation reactions. CYP2B6 is both highly inducible and polymorphic resulting in widely varied expression and function of the enzyme between individuals leading to differential drug metabolism and disposition. Polymorphisms of CYP2B6 are often associated with loss-of- function and can result in elevated plasma concentrations of drugs and enhanced toxicity.

Many drugs and chemicals have demonstrated the ability to either induce or inhibit the expression of CYP2B6 whether directly or through the transcriptional activation of nuclear receptors. Recent studies have begun to explore the potential of these nuclear receptors as targets for combination therapies in the hopes of altering the expression of drug-metabolizing enzymes and transporters in a manner that is beneficial for the treatment of cancers and other disorders.

As more substrates of CYP2B6 are identified, greater interest is generated in the impact of both genetic and pharmacological modulation of CYP2B6 expression on the disposition of drugs. We

27 have highlighted the impact of CYP2B6 modulation and its potential for clinically significant

DDI. It is important to point out that although many drugs exhibit the potential for CYP2B6- associated DDI based mostly on in vitro experimental results, clinically significant DDI mediated by CYP2B6 are limited. To this end, the role of CYP2B6*6 in the therapeutic efficacy and toxicity of EFV appears to be the only CYP2B6-drug pair that is supported by compelling clinical evidence across different ethnic groups. Given that EFV continues to be in the front line for HIV therapy, clinical implementation of a CYP2B6 genotyping test would eventually benefit patients undergoing EFV-based treatment.

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1.The Roles of Nrf2 as a Drug Target 2.1 Introduction

Nuclear factor (erythroid-derived2)-like 2 (Nrf2) is a basic leucine zipper (bZIP) transcription factor which governs the expression of several antioxidant proteins. Induction of these antioxidant proteins protects against oxidative damage in cells and tissue which can be induced by injury, inflammation, or chemical stimulation. Under normal cellular conditions, Nrf2 resides in the cytoplasm where it is held in a complex by Kelch like-ECH-associated protein 1 (Keap1) and Cullin 3 which regulate the Nrf2 protein via ubiquitination (Itoh et al., 1999). Following ubiquitination, Nrf2 is shuttled to the proteasome for degradation and recycling. The half-life of

Nrf2 under normal conditions is approximately 20 minutes (Kobayashi et al., 2004). Under stress conditions, including oxidative or electrophilic stress, integral cysteine residues in the Keap1 protein are disrupted, interrupting the ubiquitination of Nrf2 resulting in its accumulation in the cytoplasm and subsequently translocates to the nucleus of cells where it heterodimerizes with a small Maf protein and binds to the antioxidant response element (ARE) in the promoter region upstream from several antioxidative genes, initiating transcription (Itoh et al., 1997; Yamamoto et al., 2008; Sekhar et al., 2010).

Until about two decades ago, few groups focused their research on understanding the roles of

Nrf2 in protecting cells against oxidative and electrophilic stresses and its inhibitory effects on carcinogenesis. More recently, however, many groups have put forth significant effort in understanding the numerous functions and regulatory controls of this protein. To date, the overall role of Nrf2 remains largely debated with some claiming it suppresses tumor growth and

40 carcinogenesis while others state that is plays an oncogenic role. Thus, its role as a therapeutic target remains controversial.

Oxidative stress refers to the balance between the production of reactive oxygen species (ROS) and the ability of a cell or biological system to eliminate or detoxify the reactive intermediates or to repair itself following damage. Imbalance in the normal redox state in cells can lead to toxic effects due to the production of peroxides and radicals which can damage cellular proteins, lipids, and DNA. Oxidative stress in cells can result in DNA strand breaks and, in some cases,

ROS can behave as cellular messengers in redox signaling pathways disrupting normal cellular signaling.

In humans, oxidative stress has been implicated in numerous disease states including Asperger syndrome, cancer, Parkinson’s disease, Alzheimer’s disease, atherosclerosis, fragile X syndrome,

Sickle Cell Disease, myocardial infarction, heart failure, ADHD, depression, and more (Amer et al., 2006; Halliwell, 2007; Valko et al., 2007; Bonomini et al., 2008; de Diego-Otero et al., 2009;

Dean et al., 2011; Tsutsui et al., 2011; Parellada et al., 2012; Hwang, 2013; Ramond et al., 2013;

Jimenez-Fernandez et al., 2015; Joseph et al., 2015). However, some studies have indicated that

ROS in humans can be beneficial as they can be utilized by the body’s immune system to fight pathogens (Segal, 2005). Further, short-term oxidative stress may play a role in the induction of mitohormesis, a coordinated response to mitochondrial stresses, and the prevention of aging

(Gems and Partridge, 2008; Yun and Finkel, 2014).

2.2 Nrf2 as a drug target to combat multidrug resistance in cancer cells

While Nrf2 plays an essential role in the survival of healthy cells in response to oxidative stress, its signaling and transcription can prove to be detrimental in the face of chemotherapeutic intervention in unhealthy tissue. Cancerous and otherwise diseased cells often exhibit dysfunctional Nrf2 regulation and overexpression of Nrf2 in the nucleus of cells and elevated transcription of antioxidant response and cell survival genes often leading to drug insensitivity or resistance. This has become a common area of research for many groups and several small molecule inhibitors of Nrf2 have been discovered and implicated in overcoming multidrug resistance in cancer. Among these, trigonelline, a coffee alkaloid, was able to significantly reduce tBHQ-induced activity of Nrf2 in multidrug-resistant pancreatic cell lines Panc1,

Colo357, and MiaPaca2, which each exhibit high Nrf2 activity. The sensitivity of each of these cell lines to anti-cancer drugs was increased with trigonelline treatment (Arlt et al., 2013).

5,7-dihydroxyflavone (chrysin) is a flavonoid found in the extracts of many plant species. In

BEL-7402/ADM DOX-resistant hepatocellular carcinoma cells chrysin has been demonstrated to significantly reduce Nrf2 expression by downregulating the PI3K-Akt and ERK pathways, in turn downregulating Nrf2 target genes HO-1, AKR1B10, and MRP5, restoring sensitivity to doxorubicin (DOX) (Gao et al., 2013a). This group also investigated another natural flavone found in several fruits and vegetables with known anti-inflammatory and antioxidant properties,

4’,5,7-trihydroxyflavone (apigenin). In the same DOX-resistant hepatocellular carcinoma cells, apigenin reduced the expression of Nrf2 as well as its downstream target genes. Treatment with apigenin and DOX had a synergistic anti-tumor effect in BEL-7402/ADM cells leading to inhibited cell proliferation and enhanced apoptosis (Gao et al., 2013b).

3’4’5’7-tetrahydroxyflavone (luteolin) is a naturally occurring polyphenolic flavonoid found abundantly in celery, parsley, and green pepper. Using a cell-based ARE-reporter assay Tang et

42 al. demonstrated that luteolin is a potent inhibitor of Nrf2 (Tang et al., 2011). Further, luteolin significantly increased the sensitivity of A549 cells to several anticancer drugs including DOX, oxaliplatin, and bleomycin indicating that luteolin may be utilized as a natural sensitizer of cancer cells to chemotherapeutic treatment (Tang et al., 2011).

Ascorbic acid is a known antioxidant that has demonstrated inhibitory effects on the expression of Nrf2. In KCL22/SR imatinib-resistant chronic myelogenous leukemia cells, Nrf2 binding to the ARE in the promoter region of the γ-glutamylcysteine synthetase gene is much stronger than in the parental KCL22 cell line which remains sensitive to imatinib treatment (Tarumoto et al.,

2004). Tarumoto et al. demonstrated that treatment of imatinib-resistant KCL22/SR cells with ascorbic acid resulted in decreased DNA binding by Nrf2 and restoration, though partial, of imatinib sensitivity (Tarumoto et al., 2004).

In 2011, Ren et al. examined the effect of brusatol, a quassinoid extracted from Brucea javanica on Nrf2 expression levels and sensitivity to several anticancer agents (carboplatin, 5-fluorouracil, etoposide, and paclitaxel) in HeLa, MDA-MB-231, and A549 cells (Ren et al., 2011). Brusatol significantly reduced expression of Nrf2 in these cell lines without altering the expression level of Keap1. The authors further investigated the anticancer effect of brusatol in a tumor xenograft study and concluded that brusatol has utility in combatting intrinsic drug resistance brought on by elevated Nrf2 expression (Ren et al., 2011).

In addition to inhibition of Nrf2 by small molecules, decreasing Nrf2 by other means including shRNA and siRNA has been investigated for its potential benefits in overcoming multidrug resistance in cancer cells. In 2008, Wang et al. demonstrated the utility of Nrf2 as a therapeutic target for combating chemoresistance in cancers (Wang et al., 2008). These authors showed that the stable over-expression of Nrf2 in cancer cells lead to enhanced resistance of cancer cells to

43 anticancer agents including cisplatin, DOX, and etoposide. On the other hand, downregulation of the Nrf2-dependent response by overexpression of Keap1 or transient transfection with Nrf2 siRNA restored sensitivity of cancer cells to the investigated antineoplastic agents. Further, upregulation of Nrf2 by tBHQ enhanced the resistance of cancer cells indicating that using small molecule inhibitors of Nrf2 to increase the sensitivity of cells to chemotherapy may be a feasible treatment strategy. Finally, the authors concluded that this strategy of inhibiting Nrf2 to sensitize cells to treatment is not specific to certain cancer types or drugs and may have wide applications in oncology (Wang et al., 2008).

In 2009, Shim et al. showed that acquired resistance to DOX in ovarian carcinoma cells was related to increased activation of the Nrf2 pathway (Shim et al., 2009). In their study, A2780 human ovarian cancer cells, known to be highly sensitive to DOX, demonstrated low levels of

ARE binding and ARE-driven luciferase activity. Further, expression of NRF2 target genes in these cells was significantly repressed compared to DOX-resistant SKOV3 and OV90 cells. The authors induced doxorubicin resistance in A2780 cells by exposing the cells to stepwise increasing DOX concentrations and ultimately resisted DOX-induced cell death. This acquired resistance in A2780 corresponded with an elevation in Nrf2 activity and a corresponding increase in the expression of the catalytic subunit of γ-glutamylcysteine ligase and total glutathione (GSH) content. In the DOX-resistant cells, inhibition of Nrf2 via shRNA restored the doxorubicin sensitivity, while in the originally sensitive cells Nrf2 inhibition did not further enhance sensitivity to DOX. The authors suggested that these results indicate that the level of

Nrf2 activity may in fact be a determining factor for DOX sensitivity in ovarian carcinoma cell lines (Shim et al., 2009).

In a 2010 study, Manandhar et al. examined the impact of stably inhibiting Nrf2 on DOX sensitivity in OV90 human ovarian carcinoma cells (Manandhar et al., 2010). In this study, the authors generated a stable cell line expressing Nrf2 shRNA in OV90 cells. By utilizing a NRF2- specific shNrf2-expressing lentiviral plasmid, the authors observed significant inhibition of

ARE-driven luciferase activity and Nrf2 target gene expression compared to nonspecific scrambled (scRNA) expressing cells. Further, cells expressing shNrf2 demonstrated an 82% reduction in overall GSH levels and retarded cell growth. This knockdown of Nrf2 sensitized the cells to doxorubicin treatment in MTT cell viability assays and propidium iodide cell sorting assays. The sensitized cells showed increased cell death and apoptosis following DOX treatment as compared with OV90-scRNA cells (Manandhar et al., 2010).

These authors further investigated the utility of Nrf2 knockdown with shRNA in BALBc (nu/nu) mice. OV90 cells were xenografted onto the flanks of these mice and the tumors were injected with viral particles containing Nrf2 shRNA or scRNA and the mice were treated with DOX.

Tumors treated with Nrf2 shRNA demonstrated slower growth than was observed in the scRNA treated group, though their result was not statistically significant. Overall, the authors concluded that Nrf2 signaling may be a promising target for repressing tumor growth and sensitizing cancer cells to cytotoxic effects of drugs (Manandhar et al., 2010).

In 2010, Hong et al. investigated the role Nrf2 plays in conferring drug resistance upon pancreatic cancer cells (Hong et al., 2010a). In this study, the authors analyzed the expression levels of Nrf2 and ABCG2 (BCRP) in pancreatic cancer tissues and cell lines, and a correlation between Nrf2 activation and drug resistance was established. In pancreatic cancer tissues and cell lines, elevated Nrf2 protein levels were observed as compared to normal pancreatic tissues.

Increasing the expression of Nrf2 protein by either over-expression of exogenous Nrf2 or

45 activation of endogenous Nrf2 led to increased drug resistance. Further, the authors examined the impact of knocking down Nrf2 in pancreatic cancer tissue and cell lines. They reported that knockdown of Nrf2 with siRNA significantly reduced the expression of several multidrug resistance genes including glutamate-cysteine ligase catalytic subunit (GCLC), ABCG2, and several ABCC-family efflux transporter genes. These reduced mRNA levels correlated with reduced protein expression as well (Hong et al., 2010a).

Multidrug-resistance-associated protein-1 (MRP1) has long been associated with multi-drug resistance. However, the mechanisms of regulation of this efflux transporter remain poorly understood. In 2013, Ji et al elucidated the role of the Nrf2-ARE pathway on the expression and function of MRP1 (Ji et al., 2013). The authors compared H69AR multidrug resistant lung cancer cells with the more sensitive parent H69 cell line. They demonstrated that the H69AR cells showed significantly greater Nrf2-ARE pathway activity and subsequent expression of

MRP1. Following knockdown of Nrf2 in the resistant H69AR cells, this elevated expression of

MRP1 was decreased towards the basal level observed in H69 cells. Further, this knockdown of

Nrf2 restored the sensitivity of the previously resistant H69AR cells to chemotherapeutic cell death (Ji et al., 2013).

Daunorubicin and cytarabine are commonly administered together in the treatment of acute myeloid leukemia treatment. However, drug resistance and untoward toxic side effects significantly limit treatment success. Nrf2 is well-known as a master regulator of antioxidant response and has been implicated in multidrug resistance in solid tumors, however, there remains little known regarding Nrf2 in bloodborne cancers and its impact on chemoresistance in AML.

To address this, Karathedath et al. explored the impact of treating primary AML cells with a

Nrf2 inhibitor, brusatol (Karathedath et al., 2017). Primary AML cells with high ex-vivo

46 resistance to cytarabine, arsenic trioxide, and daunorubicin exhibited high basal levels of Nrf2 mRNA expression. Gene-specific knockdown of Nrf2 increased the sensitivity of these previously resistant cells to treatment by decreasing the expression of downstream antioxidant target genes of Nrf2, thus compromising the ability of the AML cells to scavenge the ROS generated by the chemotherapeutic agents. Treatment of the primary AML cells with brusatol increased their sensitivity to cytarabine, arsenic trioxide, and daunorubicin and reduced the cells’ ability to form colonies. This study implicated Nrf2 as a druggable target for modulating drug resistance in AML treatment (Karathedath et al., 2017).

Additionally, these authors investigated the mechanism by which the Nrf2-ARE pathway regulates MRP1 expression. Upon searching the promoter region of the MRP1 gene, the authors identified two putative AREs, ARE1 and ARE2. In subsequent reporter gene and ChIP assays, the authors demonstrated that both ARE1 and ARE2 interacted with Nrf2. Further, the authors reported the expression levels of Nrf2 and MRP1 in 40 cancerous tissue as measured by immunohistochemistry (IHC), revealing that both Nrf2 and MRP1 demonstrated significantly elevated expression in tumor tissue as compared with adjacent non-cancerous tissue. Correlation analysis of their expression levels indicated that their expression was correlative indicating that the Nrf2-ARE pathway is necessary for regulating the expression of MRP1 and implicated Nrf2 as a potential target for multi-drug resistance in cancer cells (Ji et al., 2013).

A recent study by Gu et al. investigated arsenic trioxide (ATO) resistance in lung cancer cells and the role of Nrf2 (Gu et al., 2017). These authors identified elevated expression of miR-155 in

A549R lung cancer cells which demonstrates resistance to ATO. This high level of miR-155 was associated with greater cell survival, colony formation, cell migration, and reduced levels of cellular apoptosis, mediated by high levels of Nrf2 and its target genes NQO-1 and HO-1,

47 accompanied by a high ratio of Bcl-2/Bax. By inhibiting miR-155 in cells, significantly decreased the expression levels of Nrf2, HO-1, and NQO-1 as well was the Bcl-2/Bax ratio and facilitated ATO-induced apoptosis and decreased colony formation and cell migration. Together, these results indicate that ATO-resistance is conferred by miR-155 overexpression and a subsequent upregulation of Nrf2 signaling and implicate miR-155 as a therapeutic target in overexpressing cancer tissues (Gu et al., 2017).

2.3 Targeting the Nrf2-ARE pathway in non-cancer disease states

In addition to cancer, the Nrf2-ARE pathway has been investigated for its roles in other disease states including neurodegenerative diseases including Alzheimer’s and Parkinson’s diseases, multiple sclerosis, chronic kidney disease, diabetes, and cardiovascular disease. Many groups have investigated the role of Nrf2 in these conditions and its potential as a pharmacological target to facilitate disease prevention or treatment (Al-Sawaf et al., 2015). While the goal in treating cancer is often to inhibit the expression of Nrf2, many studies have demonstrated beneficial effects of increasing Nrf2 expression in other disease states.

2.3.1 Targeting Nrf2 in Neurodegenerative Diseases Oxidative damage is commonly associated with Alzheimer (AD) and Parkinson Diseases (PD).

The role of Nrf2 in mediating this oxidative stress was investigated in a 2007 study by Ramsey et al (Ramsey et al., 2007). In this study, Nrf2 localization in affected brain regions of AD, Lewy body variant of AD (LBVAD), and PD. Their results indicated that Nrf2 is expressed in neurons

48 both in the cytoplasm and nucleus in normal hippocampi, and that nuclear expression is significantly greater than that in the cytoplasm. In diseased brains, Nrf2 was predominantly found in the cytoplasm of hippocampal neurons and was not abundantly found in beta amyloid plaques or neurofibrillary tangles. With further analysis with immunoblotting, the authors observed a significant decreased in nuclear Nrf2 levels in AD cases. However, in PD nigral neurons, Nrf2 was strongly expressed in the nucleus and not the cytoplasm whereas is predominantly resided in the cytoplasm in the substantia nigra of normal, AD, and LBVAD cases. Together, these results indicate that Nrf2-mediated transcription is not induced in neurons in AD despite the prevalence of oxidative stress and damage. In PD, Nrf2 is strongly activated as evidenced by its high nuclear expression but this activation may not be sufficient to prevent neuronal degradation (Ramsey et al., 2007).

In a 2011 study, Barone et al. examined genetic activation of Nrf2 signaling and its impact on neurodegenerative phenotypes in a Drosophila model of PD (Barone et al., 2011). In their studies, upregulation of the Nrf2 signaling pathway by overexpression of Nrf2 or Maf-S, the

DNA-binding dimerization partner of Nrf2, was able to restore the locomotor activity of flies expressing α-synuclein. A similar restoration of locomotor activity was observed following downregulation of Keap1 by RNA-interference. These authors concluded that upregulation of the

Nrf2 signaling pathway is a viable neuroprotective strategy against PD and also established an accessible in vivo system for assessing the Nrf2 pathway as regulators and therapeutic targets in

PD (Barone et al., 2011).

Mutations in leucine-rich repeat kinase 2 (LRRK2) and α-synuclein have been demonstrated to lead to PD. In 2017 Skibinski et al. examined whether activation of Nrf2 could reduce neuron toxicity associated with PD by modulating the protein homeostasis network (Skibinski, et al.,

2017). In longitudinal imaging studies the authors were able to visualize the metabolism and location of mutant LRRK and α-synuclein in living neurons down to the single-cell level. In their experiment, Nrf2 reduced PD-associated protein toxicity by a time-dependent autonomous mechanism. Additionally, Nrf2 activated specific mechanisms designed to mediate different misfolded proteins. Steady-state levels of α-synuclein were decreased by Nrf2 in part by an increase in degradation of α-synuclein. Additionally, Nrf2 sequestered misfolded LRRK2 into insoluble and homogeneous inclusion bodies. Together, these results demonstrate stress response strategies employed by Nrf2 which may be therapeutic enhanced as a mechanism to treat PD

(Skibinski et al., 2017).

Also in 2017 Moreira et al. demonstrated that Nrf2 activation by tauroursodeoxycholic acid

(TUDCA) was able to reduce oxidative damage in SH-SY5Y neuroblastoma cells induced by α- synuclein and 1-methyl-4-phenylpyridinium (MPP+) by Nrf2 activation (Moreira et al., 2017).

Further, in mice treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), TUDCA increased expression of Nrf2, the Nrf2-stabilixing gene DJ-1, and Nrf2 target genes HO-1 and glutathione peroxidase (GPx). The authors also reported that TUDCA enhanced GPx activity in the brain. The authors concluded that their results indicate that TUDCA is a promising therapeutic agent for the treatment of PD via activation of Nrf2 in diseased cells and tissue

(Moreira et al., 2017).

2.3.2 Targeting Nrf2 in Diabetes Diabetes is the leading source of chronic kidney disease worldwide (Stenvinkel, 2010).

Currently, treatments for diabetes focus mainly on controlling blood glucose levels, blood pressure, lipids, and the blockade of the renin-angiotensin system (Mann et al., 2008). Despite

50 these treatment options, the decline in kidney function that often accompanies diabetes commonly progresses to overt kidney failure, demonstrating the need for improved therapies and treatment strategies for patients (Navaneethan et al., 2009; de Haan, 2011). One such proposed strategy is targeting Nrf2 to upregulate genes which mediate detoxification, antioxidant, and anti- inflammatory responses to protect against inflammation and oxidative stress common in diabetes

(de Haan, 2011).

Many small molecule activators of Nrf2 have demonstrated positive activity in alleviating diabetic complications. In 2008, Xue et al. demonstrated that activation of Nrf2 by SFN in

HMEC-1 human microvascular endothelial cells induced the nuclear translocation of Nrf2 increasing the expression of ARE-linked genes, including 3-5-fold induction of transketolase and glutathione reductase (Xue et al., 2008). Hyperglycemia, a common condition in diabetic patients, has been linked with increased formation of ROS which is known to be prevented by

SFN. Treatment with SFN further prevented activation of the hexosamine and PKC pathways induced by hyperglycemia (Xue et al., 2008).

Zheng et al. published a preclinical study investigating the impact of Nrf2 activators SFN and cinnamic aldehyde on the metabolic profile and reduced renal injury in mice with streptozotocin- induced diabetes (Zheng et al., 2011). Treatment with these compounds led to reduced oxidative stress and decreased levels of transforming growth factor-β, a profibrotic mediator, p21, and extracellular matrix proteins in the kidneys of diabetic mice. These protective effects induced by

SFN and cinnamic aldehyde were abolished in Nrf2 knockout mice providing evidence that their activities are dependent on the activation of Nrf2 (Zheng et al., 2011).

In a clinical study in 2011, Pergola et al. reported the utility of bardoxolone methyl, an activator of the Keap1-Nrf2 pathway, in maintaining kidney function and structure (Pergola et al., 2011).

In this randomized, placebo-controlled 52-week clinical study, rapid improvement was reported in the glomerular filtration rate of patients with type 2 diabetes and impaired renal function following treatment with bardoxolone methyl. These effects were observed within 4 weeks of beginning treatment and rapidly disappeared when drug was discontinued showing a direct effect of this treatment (Pergola et al., 2011).

2.3.3 Targeting Nrf2 in cardiovascular disease Many activators of Nrf2 have been investigated for their potential therapeutic effects in cardiac remodeling and heart failure. SFN has been shown to decrease infarct size, limit the elevation in left ventricular end-diastolic pressure, and improve coronary blood flow in mice following myocardial infarction. The authors of this study concluded that these effects are due at least in part through elevated expression of Nrf2 target genes HO-1, SOD, and catalase (CAT) (Piao et al., 2010).

In 2012, Gorbunov et al found that treating rat cardiac stem cells from a rat left anterior descending occlusion model with resveratrol significantly improved cardiac function by increasing Nrf2 expression and further significantly enhanced the survival and engraftment of implanted cardiac stem cells in the host (Gorbunov et al., 2012). Similar effects have been seen in the same animal model using gavage administration of resveratrol (Gurusamy et al., 2010).

Mounting evidence has demonstrated that MG132, a potent and reversible proteasome inhibitor, is able to protect cells and tissues from oxidative damage via activation of the Nrf2-ARE signaling pathway (Sahni et al., 2008; Dreger et al., 2009). In a pressure-overload-induced heart failure rodent mode, treatment with MG132 was able to significantly reduce cardiac hypertrophy and cardiac fibrosis while simultaneously improving cardiac function. The effects have been

52 demonstrated to occur through activation of the Nrf2-ARE pathway accompanied by simultaneous inhibition of NF-κB-mediated inflammation (Yu et al., 2013).

Many other Nrf2-activating compounds have been investigated for their utility in the treatment of cardiovascular disease. Compounds that have been shown to generate responses similar to those described above by SFN, MG132, and resveratrol include allicin, α-lipoic acid, hydrogen sulfate, and 4-HNE (Calvert et al., 2009; Zhang et al., 2010; Li et al., 2012; Deng et al., 2013).

2.4 Anthracycline Therapeutics

Anthracycline drugs date back to the 1950s when daunorubicin was identified from the bacterium Streptoyces peucetius (Di Marco et al., 1981). Initially used in the 1960s, daunorubicin showed potent efficacy in the treatment of hematologic malignancies (Tan et al.,

1967). Around this time, 14-hydroxydaunoycin (Adriamycin), later referred to as doxorubicin

(DOX), was identified and proven to be more effective as an anticancer therapeutic (Arcamone et al., 1969; Di Marco et al., 1969). Today, anthracycline drugs are utilized in the treatment of various solid tumors and bloodborne malignancies including leukemia and lymphoma, lung cancer, breast cancer, sarcoma, and multiple myeloma, and are recognized on the World Health

Organization (WHO) list of essential medicines (Volkova and Russell, 2011; (WHO). 2017).

Commonly prescribed anthracycline drugs include DOX and its derivative, epirubicin, which are used in breast cancers, pediatric solid tumors, soft tissue sarcomas, and aggressive lymphomas.

Daunorubicin, the first discovered anthracycline agent, is still utilized in treatment of acute lymphoblastic or myeloblastic leukemias and idarubicin, a derivative or daunorubicin is used to treat multiple myeloma, non-Hodgkin lymphoma, and breast cancer. Other anthracycline agents

53 on the market include nemorubicin, pixantrone, sabarubicin, and valrubicin, which are used to treat a wide range of cancers.

2.4.1 Anthracycline mechanism(s) of action Though anthracycline drugs have been used extensively for several decades, their mechanism of anticancer activity still has not been definitively elucidated. Several groups investigating this issue have demonstrated that they may in fact follow several mechanisms, accounting for the high potency of these drugs in cancer. Initially, anthracycline agents were believed to intercalate

DNA preventing replication of cancer cells (Sinha et al., 1984). Recent studies however have demonstrated that this mechanism is unlikely to be a major pathway by which anthracycline agents elicit their antitumoral effects. Instead, topoisomerase II is currently believed to be the major target of anthracycline drugs in tumor cells as these agents stabilize an intermediate species in cells and DNA strands are cut and linked to tyrosine residues of topoisomerase II, inhibiting re-ligation of DNA preventing the relaxing of supercoiled DNA and blocking transcription and replication (Binaschi et al., 2001). Additionally, breaks in DNA caused by anthracyclines have been demonstrated to induce apoptosis in cancer cells via the p53-dependent pathway (Ruiz-Ruiz et al., 2003). Several groups previously demonstrated that the generation of

ROS by anthracyclines as well as lipid peroxidation contribute to the anticancer agents of these drugs (Muindi et al., 1984). However, recent studies have shown that this may indeed not be the case and that oxidative stress is not likely to be a major mechanism of anthracycline antineoplastic activity (Myers et al., 1977; Gewirtz, 1999; Minotti et al., 2004; Wu and Hasinoff,

2005).

2.4.2 Anthracycline-induced cardiotoxicity It is well known that use of anthracycline drugs is often accompanied by cardiotoxicity. This cardiotoxicity can be caused by several mechanisms including free radical formation in heart tissue, buildup of metabolic products of the anthracycline in the heart, inhibition and/or dysregulation of topoisomerase-IIB in cardiac cells, and interference with ryanodine receptors in the sarcoplasmic reticulum (Zhang et al., 2012). Most commonly this cardiotoxicity presents as variation in the QRS complex and arrhythmias, or in more severe cases, as cardiomyopathy leading to eventual heart failure (Cardinale et al., 2013). In some cases, these phenotypes of cardiotoxicity do not present until years after treatment (Minotti et al., 2004; Zhang et al., 2012).

Anthracycline cardiotoxicity has been correlated with patients’ cumulative lifetime dose of the drug. During treatment, the cumulative dose administered to a patient is calculated, and once the maximum cumulative dose of the anthracycline agent is neared or reached, the treatment is stopped or evaluated by the medical team. Some studies have indicated that the effects of anthracycline cardiotoxicity increase over time in long-term survivors from around 2% after 2 years to 5% after 15 years (Kremer et al., 2001).

In some cases, physicians may take preventative measures or prescribe cardioprotective drugs to alleviate unwanted cardiotoxicity associated with anthracycline therapy. Throughout the course of anthracycline use, cardiac monitoring is recommended every 3 months. Further, use of dexrazoxane, a cardioprotective drug, may be implemented. Dexrazoxane has been demonstrated to reduce the risk of anthracycline-induced cardiotoxicity by about one-third while having no impact on patient response to chemotherapy (Minotti et al., 2004). In addition, various formulations have been developed for targeted delivery of anthracycline agents to localize their effects in an effort to abolish unwanted side-effects in non-target tissues. These include

55 liposomal formulations for DOX and daunorubicin and longer infusion rates for DOX administration, both designed to limit peak concentrations of anthracycline in the cardiac tissue

(Forssen and Tokes, 1979; Minotti et al., 2004).

DOX is currently utilized extensively as one of the most effective chemotherapeutic drugs on the market. However, throughout the lifespan of its use it has been associated with chronic heart failure in patients (Lefrak et al., 1973; Von Hoff et al., 1979). Van Hoff et al performed a retrospective analysis of more than 4000 patients receiving DOX treatment for various disease states in which the authors concluded that more than 2% of patients developed symptoms of congestive heart failure (Von Hoff et al., 1979). The authors of this study determined that one of the strongest determinants of heart failure is the total dose of DOX administered to a patient showing a dramatic increase in adverse cardiac events in patients receiving a cumulative dose of

550 mg/m2. Though this study was published nearly 40 years ago, this cumulative anthracycline dose is still used to predict heart failure occurrence (Volkova and Russell, 2011).

In 2003, Swain et al. examined data from three prospective studies to examine the incidence of

DOX-induced chronic heart failure and the cumulative dose at which DOX treatment caused chronic heart failure [76]. In this study, 630 patients were randomized to a DOX-plus-placebo arm of three Phase III studies (two studies in breast carcinoma patients and one in small cell lung carcinoma patients). Of the 630 patients examined, 32 had a diagnosis of chronic heart failure.

Further analysis predicted that approximately 26% of patients involved in the trials would experience DOX-induced chronic heart failure at the previously reported limit of 550 mg/m2.

Further, this analysis by Swain et al. reported that patient age was a significant risk factor associated with DOX-associated chronic heart failure after a lower cumulative dose of 400 mg/m2. Patients older than 65 years of age showed a significantly greater incidence rate of

56 chronic heart failure than those younger than 65 (Swain et al., 2003). This study further demonstrated that 5.1% of patients had some evidence of congestive heart failure or decline in left ventricular function. These adverse events were related to the previously reported cumulative dose-dependence of DOX cardiotoxicity. In contract to the previously suggested total cumulative limit of 550 mg/m2, these authors reported an increased risk of cardiotoxicity at DOX doses of

300 mg/m2 or greater that had previously been believed unlikely to hinder left ventricular function. Further, Endocardial biopsy specimens from patients receiving as little as 240 mg/m2 of

DOX have shown histopathologic changes (Billingham et al., 1978; Bristow et al., 1978).

2.5 Nrf2 Expression mediates DOX-induced cardiotoxicity

Nrf2 expression and activation has been implicated in the protection of cardiac cells against anthracycline-induced cardiotoxicity. In 2014, Li et al reported that Nrf2-deficient mice were more susceptible to DOX-induced cardiotoxicity and cardiac dysfunction (Li et al., 2014). In their studies, wild-type (WT) mice were injected with an acute administration of DOX (25 mg/kg i.p.) which rapidly induced necrosis in cardiomyocytes and cardiac dysfunction associated with oxidative stress, impaired autophagy, and accumulation of polyubiquintinated protein aggregates.

In Nrf2 knockout (Nrf2(-/-)) mice, these effects were exaggerated, suggesting that Nrf2 is an endogenous mediator of DOX-induced cardiotoxicity as a master regulator of oxidative stress and autophagy in the heart (Li et al., 2014).

2.5.1 Activation of Nrf2 by small molecules attenuates DOX-induced cardiotoxicity Several small molecules have been demonstrated to alleviate DOX-induced cardiotoxicity by activating Nrf2 and stimulation the expression of its downstream target genes. Curcumin is a well-known chemopreventive natural product which has been reported to activate Nrf2 (Balogun et al., 2003). Curcumin has been used to limit acute DOX-induced cardiomyopathy in rats. Here, rats pretreated with curcumin exhibited significantly decreased lipid peroxidation ad a decrease in overall GSH content and GPx activity in cardiac tissues following treatment with DOX

(Venkatesan, 1998).

In 2013, Yu et al first examined the impact of co-administering DOX with a well-known cardioprotective agent, α-Lineoic acid (ALA) on cardiotoxicity in rats (Yu et al., 2013). In their study, rats were treated with vehicle control (saline), ALA alone (500 µg/kg), DOX (2.5 mg/kg), or ALA (500 µg/kg) plus DOX (2.5 mg/kg) for 17 days. Their results showed a significant increase in heart weight/body weight, liver wet weight (WW)/dry weight (DW), lung WW/DW, serum levels of brain natriuretic peptide, creatine kinase-MD, lactate dehydrogenase, and cardiac troponin I, myocardial necrosis and myocardial malondialdehyde dehydrogenase, and also induced the mRNA expression of Nrf2 in the nucleus as well as cleaved caspase-3, Bax, and superoxide dismutase (SOD). Further, administration of doxorubicin drastically cardiac output as demonstrated by decreased left ventricular end-diastolic volume, stroke volume, ejection fraction, SOD, glutathione-peroxidase, catalase, and the expression of Keap1 in cytoplasm, phospho-AKT, phosphor-ERK, and Bcl-2. When DOX was co-administered with ALA, most of these observed changes were significantly diminished. However, in the co-treated rats, the authors reported that the expression of Keap1 was further reduced in the cytoplasm and the expression of Nrf2 and SOD mRNA was further increased. They postulated that the mechanisms behind the cardioprotection and differential gene expression may be associated with the

58 enhancement of the endogenous antioxidant response system via the Keap1/Nrf2 pathway and anti-apoptosis through activation of the B/extracellular signal regulated kinase pathway (Yu et al., 2013).

Li et al examined the impact of pretreatment with sulforaphane (SFN) on DOX-induced oxidative stress and cytotoxicity in rat-derived H9c2 cells (Li et al., 2015a). In this study, the authors pre-treated H9c2 cell with SFN followed by a challenge with DOX. Cells pre-treated with SFN showed a significantly reduced number of apoptotic cells and diminished expression of pro-apoptotic proteins Bax, caspase-3, and cytochrome c. Further, SFN stimulated the expression of Nrf2-target gene HO-1 which consequently resulted in reduced levels of ROS induced by

DOX (Li et al., 2015a).

Singh et al provided evidence both in vitro and in vivo that stimulation of Nrf2 by SFN can protect the heart from DOX-induced cardiotoxicity (Singh et al., 2015). In rat-derived H9c2 cardiomyoblast cells, SFN treatment pretreatment offered protection from DOX cytotoxicity. In

129/sv mice, pre-treatment with SFN restored cardiac function and resulted in significantly reduced cardiomyopathy in DOX-treated mice. In SFN-treated mice, accumulation of 4- hydroxynonenal (4-HNE) protein adducts due to lipid peroxidation following DOX-induced oxidative stress was significantly reduced via SFN treatment. Further, cardiac mitochondrial function was significantly repressed by treatment with DOX alone but what restored significantly by concomitant administration of SFN. Lastly, these authors demonstrated that the co- administration of SFN with DOX reversed the reduction in Nrf2 binding activity caused by DOX and restored expression of Nrf2-regulated genes both at the mRNA level and protein level (Singh et al., 2015).

In 2015, Wang et al investigated whether tert-butylhydroquinone (tBHQ) could provide protection against DOX-induced cardiotoxicity in vivo and whether these protective effects were associated with an up-regulation of the Nrf2 signaling pathway in mice (Wang et al., 2015).

Their results indicated that administration of tBHQ significantly decreased the DOX-induced cardiac injury in WT-mice. Further, DOX-induced oxidative stress and apoptosis was ameliorated in animals treated with tBHQ. Moreover, the authors showed that tBHQ increased the accumulation of Nrf2 in the nucleus as well as the expression of Nrf2-target genes heme oxygenase-1 (HO-1) and NAD(P)H:quinone oxido-reductase 1 (NQO-1). Nrf2-null mice (Nrf2(-

/-) did not show any protective effect of tBHQ on DOX-induced cardiotoxicity, indicating that tBHQ has a beneficial effect on DOX-induced cardiotoxicity, and these effects are contingent upon Nrf2 expression and activation (Wang et al., 2015).

More recently, Hajra et al demonstrated that 3,3’0diindolylmethane (DIM), a naturally-occurring plant alkaloid, elicits protective effects in cardiac tissue in mice against the damaging effects of

DOX (Hajra et al., 2017). The authors showed that concomitant administration of DIM and DOX resulted in significantly attenuated DOX-induced oxidative stress in cardiac tissues. These toxicities were reduced by alleviating the levels of free radicals and lipid peroxidation as well as augmenting the level of reduced glutathione and the activity of antioxidant enzymes. DIM was able to significantly reduce DOX-induced clastogenicity, apoptosis, DNA damage, and myeloid hyperplasia in bone marrow. Further, the authors demonstrated that oral administration of DIM significantly induced the expression of Nrf2-target genes HO-1, NQO-1, and glutathione-S- transferase (GST). Additionally, Bcl-2 expression was upregulated while Bax and caspase-3 expression were downregulated following DIM administration attenuating DOX-induced apoptosis (Hajra et al., 2017).

2.6 Conclusions

The overall role of Nrf2 in disease treatment remains largely controversial. In many instances, inhibition of Nrf2 is essential to sensitize cells to therapy for patient treatment. On the other hand, Nrf2 activation often conveys protective and restorative effects in tissues. The impact of

Nrf2 and its benefits or hindrances largely depend on the disease state and treatment options for patients. While treatment with inhibitors of Nrf2 sensitizes many cancer cells to chemotherapy drugs, further activation of Nrf2 in cancer cells in generally modest to non-existent with treatment with Nrf2 activators, owing to the high basal levels of Nrf2 in cancerous tissue. To this end, administration of Nrf2 activating compounds alongside chemotherapy drugs may offer some protection to healthy tissue while not desensitizing the cancerous cells to treatment.

2.7 Research Objective

This dissertation project was carried out to further investigate the role of CAR as a novel target facilitating the treatment of hematologic malignancies. Preliminary research from our lab focused on the regulation of relevant CYP enzymes in the bioactivation of CPA and proposed a novel therapeutic strategy via selective induction of CYP2B over CYP3A in human liver samples. In this dissertation, the impact of hCAR activation on the anticancer activity of the front-line chemotherapy regimen for non-Hodgkin lymphoma, the CHOP regimen. Further, novel mechanisms for alleviating the dose-limiting cardiotoxicity of CHOP were investigated.

In chapter 3, we first utilized a novel hepatocyte-lymphoma-cardiomyocyte co-culture system to examine anticancer activity of the CITCO/CHOP combination as well as its impact on off-target toxicity. In these studies, we hypothesized that selective activation of hCAR with CITCO would

61 preferentially CYP2B6, facilitating the bioactivation of CPA to its active form, 4-OH-CPA, while having a negligible impact on the expression of other enzymes and transporters responsible for the disposition of the CHOP drugs. Building upon these preliminary results, the

CITCO/CHOP combination was investigated in a lymphoma xenograft study in hCAR- transgenic mice. Further, the pharmacokinetics of CPA and its 4-OH-CPA were examined in hCAR-transgenic mice in the presence and absence of CITCO.

In addition to increasing the therapeutic efficacy of the CHOP regimen in lymphoma cells, we aimed to alleviate the severe, cumulative, and dose-limiting cardiotoxicity associated with the doxorubicin component of the CHOP regimen. In chapter 4 we focused in identifying clinically utilized compounds which activate both hCAR in human liver cells and Nrf2 in cardiomyocytes.

The overall hypothesis for this section of the dissertation was that compounds with dual activity may both increase the antineoplastic activity of CHOP by increasing the bioactivation of CPA, and also provide some protection against doxorubicin-induced cardiotoxicity by activation Nrf2 and stimulation expression of its downstream target genes in cardiomyocytes.

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2. Activation of the constitutive androstane receptor increases the therapeutic index of CHOP in lymphoma treatment 3.1 Introduction

Non-Hodgkin lymphoma encompasses diverse cancers of the lymphatic system, including the nodes, spleen, and other organs that mediate immune responses. The most common such malignancy is diffuse large B-cell lymphoma. In the United States there were over 70,000 new cases of non-Hodgkin lymphoma and roughly 20,000 deaths due to the disease in 2014 (Itoh et al., 1999). Many therapies, including combination chemotherapy regimens, have been utilized to treat non-Hodgkin lymphoma, yet more than 30% of patients diagnosed with the disease do not survive longer than five years (Teras et al., 2016).

CHOP chemotherapy, composed of cyclophosphamide (CPA), doxorubicin, vincristine, and prednisone, is the current front-line therapy for diffuse large B-cell lymphoma (Michallet and

Coiffier, 2009b), frequently in combination with an anti-CD20 antibody, rituximab (1997;

Mounier et al., 2003). This combination therapy has provided significant improvement in the long-term survival of patients diagnosed in the early stages of the disease, with relapse-free survival achieved in 80-90% of patients (Sehn, 2010; Tomita et al., 2013). However, patients diagnosed with stage III or IV disease have significantly lower survival rates (Michallet and

Coiffier, 2009b; Sehn, 2010). Thus, there is a need to optimize the front-line therapy for advanced-stage lymphomas.

CPA, one of the primary components of the CHOP regimen, is an alkylating agent that has been used in combination therapies for the treatment of various cancers as well as disorders of the

69 immune system for many years (Bonadonna et al., 1995b; Coiffier, 2005b). CPA is a prodrug that undergoes oxidation in the liver to form its therapeutically active metabolite 4- hydroxycyclophosphamide (4-OH-CPA) (Fenselau et al., 1977; Giraud et al., 2010). This oxidation reaction is primarily mediated by cytochrome P450 (CYP) 2B6, with a less significant contribution from CYP2C9 and CYP3A4, though CYP3A4-mediated metabolism of CPA may also yield a therapeutically inactive byproduct, dechloroethyl-CPA (Code et al., 1997a; Huang et al., 2000b). An important toxicity of CHOP arises from another important component of this regimen, doxorubicin, a widely used anthracycline with cumulative and severe cardiotoxicity, which most frequently manifests as congestive heart failure (Chlebowski, 1979). Although the mechanism of doxorubicin cardiotoxicity has yet to be definitively elucidated, higher doses of doxorubicin result in increased DNA damage, apoptosis, and oxidative stress in cardiomyocytes

(Zhou et al., 2001a; Ma et al., 2013b). For lymphoma patients with pre-existing heart conditions, limitation of exposure to doxorubicin mandates avoiding the use of the CHOP regimen (Limat et al., 2003a).

The constitutive androstane receptor (CAR, NR1I3), a xenobiotic sensor expressed primarily in the liver, is the predominant modulator for the inductive expression of CYP2B6 (Sueyoshi et al.,

1999a; Wang and Negishi, 2003). Selective activation of CAR allows for the preferential induction of CYP2B6 over CYP3A4, promoting the formation of the 4-OH-CPA alkylating moiety in cultures of isolated human primary hepatocytes (HPH) (Faucette et al., 2006a).

Previous investigation in our laboratory has illustrated that selective induction of CYP2B6 by

CAR activation in HPH enhances the metabolism of CPA to 4-OH-CPA and increases the cytotoxicity of CPA toward HL-60 human leukemia cells (Wang et al., 2013a). Although these proof-of-concept findings are intriguing, in clinical application CPA is often co-administered

70 with other chemotherapeutic agents in combination treatment, including the CHOP regimen for non-Hodgkin lymphoma. Thus, it is critical to investigate whether inclusion of a selective human

CAR activator in the full CHOP regimen would increase the therapeutic index of CHOP-based treatment of lymphoma.

In the present studies, we sought to elucidate the effects of a selective CAR activator, 6-(4- chlorophenyl)imidazo[2,1-b][1,3]thiazole-5-carbaldehyde-O-(3,4-dichlorobenzyl)oxime

(CITCO), on the anticancer activity of the leading treatment for non-Hodgkin lymphoma, the

CHOP regimen. To examine this scenario, we have employed a novel multi-organ co-culture model providing a cellular environment that incorporates metabolism-capable HPH, lymphoma cells, which are the drug targets, and cardiomyocytes, which are a target for toxicity. This unique model offers an in vitro system that resembles the in vivo cellular environment and allows for examination of the impact of hepatic drug-drug interactions on CHOP anticancer activity and extrahepatic targets concurrently. Further, in a hCAR-transgenic mouse model, we demonstrated that the combination of CHOP with CITCO provides significantly improved anti-cancer activity in lymphoma tumor xenografts over CHOP alone. In a pharmacokinetic study, we show that this increased anti-cancer activity arises from an increase in exposure to the active 4-OH-CPA metabolite of CPA following concomitant administration with CITCO. Taken together, we provide experimental evidence that inclusion of CITCO significantly enhances the cytotoxicity of CHOP-based treatment in lymphoma, but not in cardiomyocytes and cardiac tissue. These results also indicate that co-administration of a CAR agonist with low toxicity in conjunction with CHOP may lower the required overall load of chemotherapeutic agents and alleviate toxicities without jeopardizing antineoplastic activity.

3.2 Methods & Materials

3.2.1 Chemicals and Reagents CPA, doxorubicin, vincristine, prednisone, and 2’,7’-dichlorofluorescein diacetate were purchased from Sigma-Aldrich (St. Louis, MO). CITCO was acquired from BIOMOL research laboratories (Plymouth Meeting, PA). Oligoniclueotide primers were synthesized by and purchased from Integrated DNA Technologies. Insulin, Matrigel, and ITS+ culture supplies were obtained from BD Biosciences (Bedford, MA).

3.2.2 Human Primary Hepatocytes and HepaRG Cells HPH were obtained from Bioreclamation, IVT (Baltimore, MD). Hepatocytes with viability over

90% were seeded at 1.5x106 or 7.5x105 cells/well in 6- or 12-well collagen-coated plates. After 4 h of attachment, cells were overlaid with Matrigel (0.25 mg/ml) in serum-free Williams E medium to form the sandwich culture, as described previously (LeCluyse et al., 2005b).

Following incubation for 36 h, HPH were treated with DMSO (0.1%) or CITCO (1 µM) for 24 or 72 h for mRNA and protein detection, respectively. In separate experiments, wild-type (WT) and CAR-knockout (KO) HepaRG cells obtained from Sigma-Aldrich were cultured in 6- or 12- well collagen-coated plates as described previously (Antherieu et al., 2010). Cells were further treated with DMSO or CITCO, as above.

3.2.3 Culture and Treatment of Lymphoma Cells Immortalized lymphoma cell lines SU-DHL-4 and SU-DHL-6 were obtained from ATCC in

2012 (Rockville, MD). The OCI-LY-3 cell line was kindly provided by Dr. Ronald Gartenhaus in 2012 (Department of Medicine, University of Maryland). All cell lines were cultured in

RPMI-1640 medium containing 10% fetal bovine serum and 1% penicillin/streptomycin. The cell lines were used for less than 40 passages. The authenticity of the cell lines were confirmed

72 by short tandem repeat polymorphism profiling (DDC Medical, Fairfield, OH). Cells were treated with DMSO (0.1%) or CITCO (1 µM) for 24 h before harvesting for total RNA extraction.

3.2.4 Quantitative PCR Analysis Total RNA from HPH and lymphoma cells was isolated with TRIzol Reagent (Life

Technologies) and reverse transcribed using a High Capacity cDNA Archive kit (Applied

Biosystems) following the manufacturers’ instructions. mRNA expression of CYP2B6,

CYP3A4, CYP3A5, carbonyl reductase 1 (CBR1), CBR3, and MDR1 was normalized against that of GAPDH. Real-time PCR assays were performed in 96-well optical plates on a

StepOnePlus Real-Time PCR System with SYBR Green PCR Master Mix (Applied Biosystems).

The primer sequences used for real-time PCR analyses were acquired from previous reports

(Tada et al., 2000; Lin et al., 2002; Tsikitis et al., 2005; Su et al., 2011; Xu et al., 2011; Zhang et al., 2011b; Deng et al., 2013; Quinones-Lombrana et al., 2014; Zarrouki et al., 2014). These sequences included: CYP2B6: 5’-AGACGCCTTCAATCCTGACC-3’ (forward), 5’-

CCTTCACCAAGACAAATC-CGC-3’ (reverse); CYP3A4: 5’-

GTGGGGCTTTTATGATGGTCA-3’ (forward), 5’GCGTCAGATTTCTCACCAACACA-3’

(reverse); CYP3A5: 5’-GGGTCTCTGGAAATTTGACACAGAG-3’ (forward), 5’-

CTGTTCTGATCACGTCGATCT-3’ (reverse); CBR1: 5′-CCCCTGACTGCCCTTTCTTA-3′

(forward), 5′-TCACCAGCGCTACATGGAT-3′ (reverse); CBR3: 5′-

AACCTCATGGGAGAGTGGTG-3′(forward), 5′-TCCTCGATAAGACCGTGACC-3′

(reverse); MDR1: 5′-CACGTGGTTGGAAGCTAACC-3′ (forward), 5′-

GAAGGCCAGAGCATAAGATGC-3′ (reverse); Cyp2b10: 5’-

AAGGAGAAGTCCAACCAGCA -3’ (forward), 5’- CTCTGCAACATGGGGGTACT-3’

(reverse); Cyp3a11: 5’- ACAAACAAGCAGGGATGGAC-3’ (forward), 5’-

GGTAGAGGAGCACCAAGCTG-3’ (reverse); Abcb1a: 5’- GCCCTGTTCTTGGACTGT-3’

(forward), 5’- GGCCGTGATAGCTTTCTT-3’ (reverse); Ki-67: 5’-

CTGCCTGCGAAGAGAGCATC-3’ (forward), 5’- AGCTCCACTTCGCCTTTTGG-3’

(reverse); Cyclin-D1: 5’- CTTCCTCTCCAAAATGCCAG-3’ (forward), 5’-

AGAGATGGAAGGGGGAAAGA-3’ (reverse); Pcna: 5’- TAAAGAAGAGGAGGCGGTAA-

3’ (forward), 5’- TAAGTGTCCCATGTCAGCAA-3’ (reverse); Gapdh: 5’-

GGTGAAGGTCGGTGTGAACG-3’ (forward), 5’- CTCGCTCCTGGAAGATGGTG-3’

(reverse). Fold induction of genes over control was determined as 2ΔΔCt, where ΔCt is representative of the cycle threshold number difference between the target gene and GAPDH and

ΔΔCt represents the relative change in the intergroup variations.

3.2.5 Hepatocyte/SU-DHL-4 co-culture HPH were cultured in collagen-coated 12-well plates and pre-treated with vehicle control (0.1%

DMSO) or CITCO (1 µM) for 24 h. The wells were then separated with 3.0 µm polycarbonate membrane inserts (Sigma-Aldrich). 0.5 x 106 SU-DHL-4 cells suspended in supplemented

Williams’ Medium E were transferred into the insert chamber with a final volume of 2 mL/well.

In separate co-culture experiments, HPH were replaced with either wild-type (WT) or CAR knockout (CAR-KO) HepaRG cells. The co-cultures were exposed to designated concentrations of the chemotherapy drugs in CHOP in the presence or absence of CITCO for various time intervals, as indicated.

3.2.6 Multi-organ Co-culture System In addition to the co-culture system described above, H9c2 cells (a rat cardiomyoblast cell line obtained from ATCC in 2014) were plated on modified coverslips at 1x105 cells and allowed to attach overnight at 37°C and 5% CO2. Following attachment, the coverslips were inserted in each well between the sandwich-cultured HPH and the transwell insert, as depicted in Fig. 4A.

The cultures were exposed to designated concentrations of the chemotherapy drugs in CHOP in the presence or absence of CITCO (1 µM). Both SU-DHL-4 and H9c2 cells were harvested at the indicated time points and assessed for viability, apoptosis, DNA damage, and oxidative stress, as detailed below.

3.2.7 Western Blotting Analysis in whole cell lysates Homogenate proteins from treated HPH, H9c2 or HepaRG cells were resolved on NuPAGE

Novex Bis-Tris 4-12% gels (Life Technologies) and electrophoretically transferred onto immobilon-P polyvinylidene difluoride membranes. Membranes were incubated with specific antibodies against human CAR (Perseus Proteomics), cleaved caspase-3 (Cell Signaling

Technology), or γ-H2AX (Millipore), diluted 1:1000, 1:1000, and 1:400, respectively. β-actin was used to normalize protein loading. Following incubation with horseradish peroxidase goat anti-mouse or anti-rabbit IgG antibody, membranes were developed using SuperSignal West

Pico Chemiluminescent Substrate (Thermo Scientific). Western blot signals were quantified by densitometry using ImageJ software from the National Institutes of Health.

3.2.8 Western blotting in proteins isolated from harvested tissues Homogenate proteins from tumor and heart tissue isolated from mice were resolved on NuPAGE

Bis-Tris gels (Thermo Scientific) and electrophoretically transferred onto immobilon-P polyvinylidene difluoride membranes. Membranes were incubated with specific antibodies

75 against cleaved caspase 3 (Cell Signaling Technologies) diluted 1:1000. Following incubation with HRP-conjugated goat anti-mouse antibody, membranes were developed with SuperSignal

West Pico or Femto Chemiluminescent Substrate (Thermo Scientific). Protein loading was normalized to β-actin. Western blot signals were quantified by densitometry using ImageStudio

Software.

3.2.9 Cell Viability Assays Human primary hepatocytes and H9c2 rat cardiomyocytes were seeded at 7.5 × 104 cells/well in

96-well plates. HPH were cultured for 24 h before treatment with CITCO (1 μM) or vehicle control (0.1% DMSO), followed by treatment with the chemotherapy drugs included in CHOP at a range of concentrations. Culture medium containing CHOP drugs and metabolites was exchanged between the cell types at pre-determined time points. A typical 3-[4,5- dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay was carried out as described previously (Wang et al., 2013a). Cell viability was expressed as percent of vehicle control (0.1% DMSO). Co-cultured cells were assembled and treated as described above. The viability of the SU-DHL-4 cells was determined at selected time points with a Cellometer Auto

T4 (Nexcelom Biosciences) utilizing trypan blue exclusion.

3.2.10 Phosphorylated H2AX Imaging The H9c2 cells plated on cover slips were removed from the previously described multiple-organ co-cultures after 24 h of treatment with CHOP chemotherapy drugs at a range of concentrations in the presence or absence of CITCO (1 µM). Immunofluorescence assays were performed as published (Zhang et al., 2005a). In brief, the cells were fixed with 4% paraformaldehyde in PBS

76 at room temperature for 15 min. The fixed cells were then permeabilized with 0.5% Triton X-

100 for 15 min, washed three times in PBS for 5 min, blocked using 15% fetal bovine serum in

PBS, and then incubated with primary antibody to mouse anti-γ-H2AX (Ser139, clone JBW301,

Millipore, 1:500 dilution) overnight. Subsequently, cells were incubated for 50 min with second antibody goat-anti-mouse IgG Alexa fluor 594 (1:500 dilution) for 1 h at room temperature.

Nuclear DNA was stained using DAPI at 50 ng/ml. The slides were visualized at 1000× magnification on a NIKON 90i fluorescence microscope (photometric cooled mono CCD camera).

3.2.11 Oxidative Stress Imaging Cover slips with H9c2 cells attached from the multiple-organ co-culture model were removed after 24 h of indicated treatments and placed in fresh 12-well plates and washed three times with

PBS. Subsequently, 1 mL of PBS containing 10 μM 2’,7’-dichlorofluorescein diacetate (DFDA) was added to each well. The cells were incubated at 37°C and 5% CO2 for 40 min. The oxidation of DFDA to the fluorescent dichlorofluorescein was viewed via fluorescence microscopy (Nikon

Eclipse Ti) with a FITC filter at 900 nm and quantified using NIH Image J.

3.2.12 Animal Subjects Male hCAR-transgenic mice generated on the C57BL/6 background were obtained from the laboratory of Dr. Curtis Klaassen. The mice were housed in AAALAC accredited facilities under the supervision of licensed veterinarians. These facilities are in compliance with the Animal

Care Welfare Act and other federal regulations. All animal procedures were approved by the

Institutional Animal Care and Use Committee at the University of Maryland School of Medicine.

3.2.13 Serial Sampling and PK Study Mice were treated with CITCO (20 mg/kg) 24h prior to beginning the PK study to allow for induction of Cyp2b10. Our preliminary results indicate that maximum induction of Cyp2b10 in hCAR-transgenic mice occurs within 8 hours of treatment and lasts for greater than 24 hours

(data not shown). On the day of the study, mice were treated with CHOP (80 mg/kg). Blood samples were collected from mice via serial sampling from the tail vein as described previously with minor modifications (Rana Said, 2007; Watanabe et al., 2015). Briefly, samples were collected at 0.25, 0.5, 1, 2, 4, 8, and 12h post-CPA administration. At the first sampling time point, the mice were restrained, and a slight incision was made with a razor in the lateral tail vein. Blood (~25 µL) was collected using a heparinized capillary tube. After blood collection, the bleeding was stopped with the application of cotton with light pressure to the incision site. At subsequent time points, the incision scab was gently removed with cotton and blood was collected with a heparinized capillary tube following gently stroking of the tail. Following collection, blood was transferred to tubes containing 80 µL EDTA (0.5 M). Following centrifugation, plasma (~10 µL) was transferred to a new rube containing 1 µL of 2 M semicarbazide to stabilize the 4-OH-CPA metabolite, vortexed for 10 minutes at room temperature, and stored at -80°C until LC-MS/MS analysis. Following LC-MS/MS analysis, PK analysis was performed using Phoenix WinNonlin.

3.2.14 LC-MS/MS Analysis Method Plasma samples from the serial sampling method described above were analyzed for CPA and 4-

OH-CPA concentrations as described previously with some modifications. Beginning with the prepared samples stored at -80°C, 10 µL of the plasma plus semicarbazide solution was aliquoted into a fresh tube. 2 µM hexamethylphosphoramide was added as the internal standard. 40 µL of

78 acetonitrile was added to precipitate proteins and samples were vortexed for 10 minutes at room temperature. Following centrifugation, the supernatant was extracted twice with ethyl acetate.

The organic phase was evaporated to dryness under a nitrogen stream and reconstituted in mobile phase. The mobile phase consisted of ACN:H2O (0.05% TFA) 80:20 v/v. 10µL of sample was injected for analysis on a Waters TQD triple quadrupole mass spectrometer operatd with positive electrospray ionization (+ESI). The liquid chromatography separation was performed on an

Agilent Xorbax C18 (100mm x 2.1mm, particle size 3.5 µm) with a flow rate of 0.4 mL/min.

The total run time was 5 minutes. Using multiple reaction monitoring mode, the mass transitions for each compound were monitored at m/z: 261 → 140 for CPA, m/z: 334 → 221 for 4-OH-

CPA-semicarbazide, and m/z: 180 → 135 for hexamethylphosphoramide.

3.2.15 Statistical Analysis All data are presented as the mean of triplicate measurements ± S.D. unless noted otherwise.

Comparisons were made via one-way analysis of variance (ANOVA) utilizing post-hoc

Dunnett’s analysis. Significance was determined at P <0.05 (*).

3.3 Results

3.3.1 CAR activation enhances CHOP anticancer activity towards SU-DHL-4 cells co- cultured with HPH The chemotherapeutic benefit of combining the CHOP regimen with a selective CAR activator,

CITCO, was initially examined using a HPH/SU-DHL-4 co-culture system as depicted in Fig.

3.1A. The composition of four drugs in CHOP was estimated based on literature and clinical

79 instructions (Table 3.1) (Freedman et al., 1997). In the current study, 100 µM of CHOP indicates the combination of CPA (100 µM), doxorubicin (5 µM), vincristine (0.14 µM), and prednisone

(10 µM). As demonstrated in Fig. 3.1B, both CPA and the CHOP regimen increased the cytotoxicity toward the target SU-DHL-4 cells in a concentration-dependent manner. Clearly, full CHOP achieved higher anticancer activity than CPA alone, as expected. Inclusion of CITCO with CHOP significantly enhanced cytotoxicity in SU-DHL-4 cells. In addition to the concentration-dependent cytotoxicity of CHOP with and without CITCO, time-dependent effects of this combination were observed. As shown in Figure 3.1C, similar beneficial effects were observed in the co-culture model 24 h after CITCO/CHOP treatment in a time-dependent manner. On the other hand, CITCO alone showed no effect on viability of SU-DHL-4 cells, indicating that the augmented cytotoxicity was not a direct result of the presence of CITCO.

Importantly, 100 µM of CHOP in the presence of CITCO resulted in equal or greater anticancer activity than 500 µM of CHOP alone. These findings suggest the potential to lower the overall

CHOP dosage by co-administration of CITCO. It is worth noting that although the current study centers on CHOP-based lymphoma treatment, a similar CITCO-mediated augmentation of cytotoxicity of the FC (fludarabine, cyclophosphamide) regimen in leukemia cells was observed when co-cultured with HPH (Fig. 3.2), suggesting this strategy may hold potential application in multiple hematological malignancies.

3.3.2 CITCO alters the expression of genes responsible for CHOP disposition in HPH, but not in target lymphoma cells Key genes responsible for the disposition of the CHOP drugs, including CYP2B6, CYP3A4,

CYP3A5, CBR1, CBR3, and MDR1 were measured in HPH and three lymphoma cell lines following incubation with CITCO, as detailed in the methods. As shown in Fig. 3.3, basal

CHOP Compositions

CPA (C) DOX (H) VCN (O) Pred (P)

500 25 0.7 50

250 12.5 0.35 25 100 5 0.14 10

50 2.5 0.07 5

5 0.25 0.007 0.5

* All values are micromolar (µM)

Table 3.1 Quantitative proportion of cyclophosphamide (CPA), doxorubicin (DOX), vincristine (VCN) and prednisone (Pred) in the CHOP Regimen.

Figure 3.1. Activation of CAR improves the anticancer activity of the CHOP regimen in HPH/SU- DHL-4 coculture. Schematic representation of the HPH/SU-DHL-4 coculture model used in the current studies (A). Concentration (B)- and time-dependent (C) anticancer activity of CPA and CHOP chemotherapy in the presence and absence of CITCO. Cells in coculture were treated with CPA or CHOP (5, 50, 100, 250, 500 µmol/L) in the presence of CITCO (1 µmol/L) or vehicle control (0.1% DMSO) as detailed in Materials and Methods. Viability of SU-DHL-4 cells under these treatments was determined at 0, 24, 48, and 72 hours. Data, mean ± SD of three independent measurements normalized as the percentage of viability of vehicle control. Statistical signiﬁcance between the treatment groups 0.1% DMSO/CHOP and CITCO/CHOP were analyzed; *, P < 0.05. Figure used with permission from the copyright holder, AACR.

82 expression of CYP2B6, CYP3A4, CYP3A5, CBR1, CBR3, and MDR1 in lymphoma cells was negligible or significantly lower in comparison with that in HPH, supporting the notion that biotransformation of CHOP relies predominantly on hepatic metabolism. In HPH, CITCO treatment robustly induced the expression of CYP2B6 (17-fold) with moderate augmentation of

CYP3A4 (4-fold), and MDR1 (4-fold), respectively (Fig. 3.3A, B, F). Expression of all tested genes in three lymphoma cell lines, on the other hand, was not altered significantly by CITCO, most likely due to the lack of CAR expression in these cells (Fig. 3.3G). Preferential induction of hepatic CYP2B6 over other tested genes favors CYP2B6-mediated oxidation of CPA to 4-OH-

CPA. Additionally, based on lack of in situ increase of efflux transporter expression in lymphoma cells by CITCO, enhanced resistance to CHOP would not be expected.

3.3.3 The role of CITCO in CHOP-based treatment is CAR-dependent The HepaRG cell line has emerged as a promising alternative to HPH, exhibiting characteristic hepatic gene expression and metabolism capability (Marion et al., 2010). To further investigate whether the beneficial impact of CITCO on CHOP-based treatment is CAR-dependent, similar co-culture models were employed, with the replacement of HPH by WT or CAR-KO HepaRG cells. With the lack of functional CAR expression, induction of CYP2B6 by CITCO was completely abolished in CAR-KO HepaRG cells (Fig. 3.4A, B). CITCO significantly enhanced

CHOP cytotoxicity in SU-DHL-4 cells co-cultured with WT-HepaRG cells in both concentration- and time-dependent manners (Fig. 3.4C, D), similarly to the beneficial response observed in the HPH-based model. In contrast, in the co-culture model containing CAR-KO

HepaRG, CHOP-induced cytotoxicity of SU-DHL-4 cells was not altered regardless of the presence or absence of CITCO (Fig. 3.4E,F). These data clearly establish that the enhanced

FC Concentration Profile A 100 0.1% DMSO + CPA 80 1 M CITCO + CPA * 0.1% DMSO + FC 60 * 1 M CITCO + FC * * 40 *

20 HL-60 Cell Viability (%) Viability Cell HL-60 0 0 50 100 250 500 1000 FC Concentration (M) FC Time Profile B 100

80 0.1% DMSO 1M CITCO 60 0.1% DMSO + CPA * 1 M CITCO + CPA 40 0.1% DMSO + FC * 1 M CITCO + FC 20 *

HL-60 Cell Viability (%) Viability Cell HL-60 0 0 24 36h 48 Time(h)

Figure 3.2. Activation of CAR improves the anticancer activity of the FC (fludarabine, cyclophosphamide) regimen in HPH/HL-60 co-culture. Co-cultured HPH and HL-60 leukemia cells were treated with CPA or FC at indicated concentrations in the presence of CITCO (1 µM) or vehicle control (0.1% DMSO). Viability of HL-60 cells under these treatments was determined at 0, 24, 36, and 48 h. Concentration-(A) and time-dependent (B) anticancer activity of CPA and FC chemotherapy in the presence and absence of CITCO were analyzed. Data represent the mean ± S.D. of three independent measurements normalized as percent viability of vehicle control. Statistical significance between the treatment groups 0.1% DMSO/FC and CITCO/FC were analyzed (*, p < 0.05). Figure used with permission from the copyright holder, AACR.

Figure 3.3 Effects of CAR activation on the expression of genes responsible for CHOP disposition in HPH and lymphoma cell lines. The expression of CYP2B6, CYP3A4, CYP3A5, CBR1, CBR3, MDR1, and CAR mRNA was measured in HPHs as well as three representative lymphoma cell lines (SU-DHL-4, SU-DHL-6, and OCI-L-Y-3) following treatment with vehicle control (0.1% DMSO) or CITCO (1 µmol/L) as described in the Materials and Methods. Expression of these genes was analyzed with RT-PCR. Data, mean ± SD of three independent experiments; ***, P < 0.001. Figure used with permission from the copyright holder, AACR.

85 efficacy of the CHOP regimen in lymphoma cells induced by CITCO is primarily CAR- dependent.

3.3.4 Activation of CAR selectively induces CHOP-mediated cytotoxicity in SU-DHL-4, but not in H9c2 cells An important off-target side effect of the CHOP regimen is cardiotoxicity, which is attributed primarily to doxorubicin (Fig. 3.5) (Limat et al., 2003a). To examine the effects of CITCO on the cardiotoxicity associated with the CHOP treatment, we developed a novel multi-organ co-culture system, depicted in Fig. 3.6A, which incorporates cardiomyoblast H9c2 cells into the HPH/SU-

DHL-4 co-culture, and in which the cells can be easily separated from one another and harvested for further analysis. Akin to other non-hepatic cells, expression of genes associated with CHOP disposition in H9c2 cells are generally low and non-responsive to CITCO treatment (Fig. 3.7).

Results from cell viability assays demonstrated that CITCO treatment selectively increased

CHOP-mediated cytotoxicity in SU-DHL-4 cells, but not in H9c2 cells (Fig.3.6B, C). Apoptosis is one of the major modes of action of the CHOP regimen (Schwartz and Waxman, 2001). As such, we further sought to examine the large fragment of activated caspase 3, a well-accepted biomarker for apoptosis, in SU-DHL-4 and H9c2 cells. As shown in Fig. 3.6D, CITCO markedly increased CHOP-induced expression of cleaved caspase-3 protein in the targeted SU-DHL-4 cells, in that 100 µM CHOP + CITCO resulted in a similar apoptotic response as 500 µM CHOP alone. On the other hand, presence of CITCO had no measurable effects on cleaved caspase 3 expression in H9c2 cells treated with CHOP at comparable concentrations (Fig. 3.6E). Notably, in the off-target cells, cytotoxicity induced by 100 µM CHOP + CITCO was significantly lower than that induced by 500 µM CHOP.

Figure 3.4 CITCO-enhanced CHOP anticancer activity is CAR dependent. WT and CAR- KO HepaRG cells were treated with vehicle control (0.1% DMSO) or CITCO (1 µmol/L) for 24 hours for mRNA or 72 hours for protein analysis. Expression of CAR protein (A) and CYP2B6 mRNA (B) was measured via Western blot analysis and RT-PCR, respectively. Coculture and treatment of WT-HepaRG/SU-DHL-4 or CAR-KO-HepaRG/SU-DHL-4 were detailed in the Materials and Methods. Anticancer activity of CHOP in SU-DHL-4 cells was demonstrated in concentration (C and E)- and time (D and F)-dependent manners in the presence and absence of CITCO (1 µmol/L). Data, mean ± SD of three independent experiments; *, P < 0.05; **, P < 0.01; ***, P < 0.001. Figure used with permission from the copyright holder, AACR.

A B

100 100

50 50 Cell Viability (% DMSO) of Viability Cell 0 (% DMSO) of Viability Cell 0 1 5 10 50 1 5 CT 100 250 500 CT 0.1 0.5 2.5 25 50 1000 2000 4000 12.5 100 200 CHOP Concentration (M) DOX Concentration (M)

Figure 3.5 CHOP- and DOX-induced cytotoxicity in H9c2 cells. H9c2 cells seeded in 96 well plates were treated with vehicle control (0.1% DMSO) or various concentrations of CHOP (A) and DOX (B) for 24 hours. Cytotoxicity of H9c2 cells were analyzed using MTT assay following the manufacturer’s instructions. Figure used with permission from the copyright holder, AACR.

3.3.5 Reduced CHOP load attenuates H2AX phosphorylation and oxidative stress in H9c2 cells DNA double-strand breaks (DSB) caused by chemotherapeutic intervention result in rapid onset of phosphorylation of a variant of histone H2A, H2AX, and this phosphorylation has been shown to be representative of the extent of DSB in cells (Kuo and Yang, 2008). Utilizing immunochemical staining and immunoblotting, we demonstrated that CHOP treatment markedly increased the phosphorylation of histone H2AX in H9c2 cells and that addition of CITCO did not further alter the induced H2AX expression (Fig. 3.8A, B). In treated SU-DHL-4 cells, however, CITCO effectively enhanced CHOP-induced DNA damage, measured by increasing histone H2AX expression (Fig. 5C). Oxidative stress and modulation of intracellular redox states can be important players in apoptotic signaling cascades (Kannan and Jain, 2000). Doxorubicin has been shown to produce reactive oxygen species (ROS) in cardiac cells (Tsang et al., 2003;

Kim et al., 2006). In our experiments, we aimed to examine the oxidative stress in H9c2 cells induced by the CHOP regimen. As shown in Fig. 3.8D and E, CHOP treatment resulted in a concentration-dependent increase in oxidative stress in H9c2 cells, inclusion of CITCO did not alter the oxidative stress in these cells, in that 100 µM CHOP + CITCO led to only marginal oxidative stress in comparison with 500 µM CHOP. Collectively, consistent with our earlier findings, these results support that inclusion of CITCO resulted in significantly greater DNA damage in target, but not off-target, cells.

3.3.6 CITCO selectively induces Cyp2b10 in hCAR-tg mice but not WT mice Following liver perfusion and isolation of primary hepatocytes from wild-type (WT) and hCAR- transgenic mice as described in the materials and methods, MPH were treated with vehicle control (0.1% DMSO) or CITCO (1 µM) or TCPOBOP (250 nm) for 24 hours. CITCO treatment

Figure 3.6 CITCO enhances CHOP-mediated cytotoxicity in SU-DHL-4 but not in H9c2 cells. Schematic illustration of the multiorgan coculture model containing HPH, SU-DHL-4, and H9c2 cells (A). In the coculture model, CHOP-induced cytotoxicity in SU-DHL-4 (B) or H9c2 (C) cells was measured as detailed in the Materials and Methods in the presence and absence of CITCO (1 µmol/L). Western blotting assay was performed to measure cleaved caspase-3 protein in SU-DHL-4 (D) and H9c2 (E) cells harvested from the treated cocultures. Densitometry of cleaved caspase-3 was normalized to that of β-actin. Data, mean ± SD of three independent experiments; **, P < 0.01; ***, P < 0.001; N.S., not signiﬁcant. Figure used with permission from the copyright holder, AACR.

Cyp2b2 Cyp3a1 Cyp3a23/3a1 25 30 20

20 15 20 15 10 10 10 5 5

0 0 0

Relative mRNA Expression mRNA Relative Relative mRNA Expression mRNA Relative Expression mRNA Relative

M PB M PB M PB    M CITCO Rat Liver M CITCO Rat Liver M CITCO Rat Liver  1000  1000  1000 0.1% DMSO1 0.1% DMSO1 0.1% DMSO1 250 nM TCPOBOP 250 nM TCPOBOP 250 nM TCPOBOP

Cbr1 Cbr3 Abcb1a 15 10 30 8 10 20 6

4 5 10 2

0 0 0

Relative mRNA Expression mRNA Relative Relative mRNA Expression mRNA Relative Expression mRNA Relative M PB M PB M PB    M CITCO Rat Liver M CITCO Rat Liver M CITCO Rat Liver  1000  1000  1000 0.1% DMSO1 0.1% DMSO1 0.1% DMSO1

250 nM TCPOBOP 250 nM TCPOBOP 250 nM TCPOBOP

Figure 3.7 Effects of CAR activation on the expression of genes responsible for CHOP disposition in H9c2 cells and rat liver. The expression of Cyp2b2, Cyp3a1, Cyp3a23/3a1, Cbr1, Cbr3, and Abcb1a was measured using total RNA extracted from H9c2 cells following treatment with vehicle control (0.1% DMSO), CITCO (1 μM), TCPOBOP (250 nM), or phenobarbital (1 mM)*. Expression of these genes was analyzed with RT-PCR. Data represent the mean ± S.D. of three independent experiments. Figure used with permission from AACR.

91 resulted in a significant induction of the expression of Cyp2b10 of approximately 10-fold with only modest induction of Cyp3a11 (3-fold) and Abcb1a (2-fold) (Fig. 3.9A-C). No changes in gene expression were observed following treatment with TCPOBOP indicating that the hCAR-tg

MPH respond to the typical hCAR activator CITCO, but not the mCAR activator TCPOBOP. In

WT mice, no changes were observed in the expression of Cyp2b10, Cyp3a11, or Abcb1a following treatment with CITCO. However, treatment with typical mCAR activator TCPOBOP induced these genes approximately 11-. 2-, and 5-fold, respectively (Fig 3.9D-E).

3.3.7 Inclusion of CITCO with CHOP increases cytotoxicity in EL-4 cells in hCAR- transgenic MPH/lymphoma co-cultures In order to verify the sensitivity of mouse-derived T-cell lymphoma cells isolated from the

C57BL/6 line and syngeneic to our hCAR-tg mice prior to xenograft studies, co-culture studies with both HPH and hCAR-tg MPH were performed as illustrated in Figure 3.10A-F. At each concentration of CHOP and over the full 72-hour time course of the study, the CITCO/CHOP combination was demonstrated greater anti-cancer activity than CHOP alone in co-cultures with

HPH or hCAR-tg MPH. In co-culture studies with WT-MPH and EL4 lymphoma cells, the inclusion of CITCO had no impact on the viability of EL4 cells. However, inclusion of

TCPOBOP significantly increased the cytotoxicity of CHOP in these target cells (Fig. 3.10E, F).

3.3.8 CITCO/CHOP combination improves anti-tumor activity over CHOP alone in EL-4 tumor xenografts in hCAR-tg mice Following confirmation that EL4 T-cell lymphoma cells are indeed sensitive to the

CITCO/CHOP combination in hCAR-transgenic mice, an in vivo xenograft study was performed to examine the efficacy of CITCO (20 mg/kg) plus CHOP (40 mg/kg) in animals. Beginning after the first round of treatment on day 9, the CITCO and CHOP combination exhibited

Figure 3.8 CITCO did not enhance CHOP-induced H2AX phosphorylation and oxidative stress in H9c2 cells. HPH/SU-DHL-4/H9c2 coculture was treated with 0.1% DMSO, CITCO (1 µmol/L), 0.1% DMSO/CHOP, or CITCO/CHOP at indicated concentrations for 24 hours. H9c2 cells removed from the coculture system were fixed with 4% paraformaldehyde, then immune- stained and imaged for phosphorylation at the serine-139 position of histone H2AX as detailed in the Materials and Methods. Relative H2AX phosphorylation was quantified using ImageJ Software from the NIH and normalized to vehicle control (A). In separate experiments, Western blot analysis was performed in H9c2 (B) and SU-DHL-4 (C) cells isolated from co-cultures following 24 hours treatment of CHOP in the presence of absence of CITCO (1 µmol/L). To assess oxidative stress in H9c2 cells under the same treatments, H9c2 cells were incubated with 10 µmol/L DFDA at 37°C and 5% CO2 for 40 minutes. The oxidation of DFDA to the fluorescent dichlorofluorescein was quantified using NIH ImageJ Software (D). Representative images via fluorescence microscopy are shown in E. Figure used with permission from the copyright holder, AACR.

Figure 3.9: Treatment with CITCO induces expression of CAR target genes in hCAR- transgenic mice but not wild-type mice. Primary hepatocytes isolated from both hCAR- transgenic and wild-type mice were treated with the typical hCAR activator, CITCO (1 µM), or the typical mCAR activator, TCPOBOP (250 nM), for 24 h. The inductive expression of Cyp2b10, Cyp3a11, and Abcb1a was examined and normalized to that of the vehicle control (0.1% DMSO). ***, p < 0.001.

94 significantly improved anti-tumor activity as compared to CHOP alone (Fig. 3.11A). Treatment with CITCO alone did not exhibit any anti-cancer activity. After the 20-day time course of the study, tumor tissue was isolated and weighed (Figure 3.11B). The resulting tumor mass in the

CITCO/CHOP treated group was significantly reduced compared to that of the CHOP alone group. Encouragingly, in the CITCO/CHOP group, 3 of the 7 mice did not have any detectable tumor remaining.

3.3.9 CITCO/CHOP combination diminishes expression of important cell survival and proliferation genes in treated tumor tissue mRNA was isolated from tumor tissue isolated at the conclusion of the xenograft study and analyzed for the expression of three key genes responsible for cell cycle progression and cell prolifteration: proliferating cell nuclear antigen (Pcna), Ki-67, and Cyclin D1. While CHOP alone was able to reduce the expression of these genes in the tumor tissue, this reduction was further augmented with the inclusion of CITCO. In the case of all three genes, expression was significantly reduced in the CITCO/CHOP treated group beyond the level observed in CHOP- treated tumor tissue (Fig. 3.11C).

3.3.10 CITCO/CHOP combination increases apoptosis in tumor tissue but not in off-target cardiac tissue Cleaved caspase-3 is often used as a marker of apoptosis in cell lines and tissues. After the tumor xenograft study in hCAR-transgenic mice, tumor and heart tissue were harvested for to determine the relative levels of apoptosis occurring in these tissues following treatment with

CITCO and/or CHOP. In tumor tissue, CHOP alone significantly increased the expression of cleaved caspase 3 in tumor tissue as compared with control or CITCO alone. Treatment with

CITCO and CHOP together increased the cleaved caspase 3 expression significantly beyond that

Figure 3.10: CAR activation increases the anticancer activity of CHOP in co-cultures with MPH and EL4 lymphoma cells. Co-cultures with MPH isolated from both hCAR-transgenic and WT-mice were treated with vehicle (0.1% DMSO), CITCO (1 µM), TCPOBOP (250 nM), and CHOP (5-500 µM) for up to 72 hours. Cell viability of EL4 cells was examined at a range of CHOP concentrations after 24 hours of treatments, and at 100 µM CHOP for up to 72 hours. *, p < 0.05; **, p < 0.01; p < 0.001.

Figure 3.11: Combination with CITCO increases the anticancer activity of CHOP without affecting off-target toxicity in hCAR-transgenic mice with EL4 lymphoma xenografts. Mice bearing xenografted EL4 tumors were randomly divided into four groups and received treatment with vehicle control (corn oil and saline), CITCO (20 mg/kg in corn oil), CHOP (40 mg/kg in saline), or CITCO (20 mg/kg in corn oil) plus CHOP (40 mg/kg in saline) and tumor growth was monitored up to day 11 following the initiation of treatment (A). At the conclusion of the study, tumor tissue was isolated from all mice and weighed (B). The expression of key genes governing cell survival and proliferation Cyclin D-1, Pcna, and Ki-67 were examined with qPCR in isolated tumor tissue (C). Total protein was isolated from tumor and heart tissue and western blotting was performed to examine the expression of cleaved caspase-3 in these tissues (D, F). Western blots were quantified with ImageStudio Software. *, p < 0.05; **, p < 0.01; ***, p < 0.001.

97 of the CHOP alone group (Fig. 3.11D, E). In heart tissue, while there was an increase in cleaved caspase 3 between the control and CITCO alone groups compared to CHOP and CITCO plus

CHOP, the addition of CITCO did not increase the expression of cleaved caspase 3 beyond the levels observed in the CHOP alone treatment group (Fig. 3.11F, G).

3.3.11 Combination with CITCO significantly increases exposure to 4-OH-CPA in hCAR- tg mice We performed a pharmacokinetic study in hCAR-transgenic mice to examine the impact of hCAR activation on the pharmacokinetics of CPA and its pharmacologically active metabolite,

4-OH-CPA (Fig. 3.12A, B). In the presence of CITCO, the Cmax of CPA was significantly decreased from 81.3 ± 10.9 to 65.5 ± µg/mL and the AUC was decreased almost 2-fold from

2577 ± 455.9 to 1471.3 ± 290.9 min*µg/mL (Fig. 3.12C). Conversely, the Cmax of 4-OH-CPA was increased in the presence of CITCO from 5.4 ± 2.0 to 9.3 ± 1.2 µg/mL and the AUC was increased from 169.9 ± 45.3 to 292.7 ± 70.9 min*µg/mL (Fig 3.12D). The ratio of the active metabolite:parent (4-OH-CPA:CPA) increased approximately 3-fold in the presence of CITCO

(Fig. 3.12E).

3.4 Discussion

Currently, the CHOP regimen remains the standard first-line choice for the treatment of aggressive non-Hodgkin lymphoma, the most common hematological malignancy worldwide

(Itoh et al., 1999). Despite well-documented progress in the application of this regimen, significant numbers of patients are still not cured due to the development of drug resistance and/or intolerable toxicities that result in premature termination of the chemotherapy. As a primary component of this regimen and alkylating prodrug, CPA undergoes hepatic metabolism

Figure 3.12: Inclusion of CITCO significantly alters the PK of CPA and 4-OH-CPA in hCAR- transgenic mice. Plasma concentration profiles of CPA (A) and 4-OH-CPA (B) in the presence and absence of CITCO in hCAR-transgenic mice. Pharmacokinetic parameters were analyzed using Phoenix WinNonlin (C, D). The metabolite:parent AUC ratio was also calculated (E).

Figure 3.13 Schematic illustration of CITCO-mediated enhancement of CHOP antineoplastic activity in targeted (SU-DHL-4) but not side-toxic (H9c2) cells. Figure used with permission from the copyright holder, AACR.

100 to its pharmacologically active form, 4-OH-CPA, via oxidation catalyzed primarily by CYP2B6.

In addition, the anthracycline doxorubicin appears to be responsible for the risk of cardiotoxicity related to the CHOP regimen (Limat et al., 2003a; Nickenig et al., 2006). We previously showed that activation of the nuclear receptor CAR selectively induces CYP2B6 and increases the biotransformation of CPA to 4-OH-CPA (Wang et al., 2013a). In the present study, we demonstrated that a selective human CAR activator, CITCO, synergistically enhanced CHOP- mediated cytotoxicity in therapeutically targeted lymphoma cells, but not in cardiomyocytes.

Importantly, combination of CITCO with CHOP allows for comparable antineoplastic activity achieved at significantly lower concentrations of CHOP chemotherapy drugs, and alleviates the cardiotoxicity of the regimen (Fig. 3.13). The relationship between CAR and the key genes responsible for the disposition of the standard CHOP drugs remains incompletely understood.

Interestingly, although targets of CHOP treatment are often extrahepatic, drug-metabolizing enzymes and transporters associated with CHOP disposition, including CYP2B6, CYP3A4 and

CYP3A5, CBR1, CBR3, and MDR1, are expressed predominantly in the liver, where CAR is also highly expressed (Wang and LeCluyse, 2003; Dennison et al., 2007; Gonzalez-Covarrubias et al., 2009). In the CHOP regimen, CYP2B6 is primarily responsible for bioactivation of CPA to 4-OH-CPA, while CYP3A4 plays akey role in the formation of the undesirable inactive metabolite dechloroethyl-CPA, as well as the neurotoxic byproduct chloroacetaldehyde (Chang et al., 1993; Su et al., 2011). Additionally, CYP3A4 plays an important role in the metabolism of prednisone which, like CPA, is a prodrug requiring metabolic conversion to its active form, prednisolone (Whirl-Carrillo et al., 2012). CYP3A5 is involved in the hepatic metabolism and clearance of vincristine (Dennison et al., 2007). Metabolism of doxorubicin is mediated primarily by CBR1 and CBR3, though in the heart this reaction is catalyzed predominantly by

101 aldo-keto reductase 1A (Pirolli et al., 2012). Conversely, lymphoma cells express negligible levels of CHOP-metabolizing enzymes and CAR (Wang et al., 2013a). As a promiscuous xenobiotic receptor, CAR plays an important role in coordinating cellular responses to stimulation by xenobiotic chemicals by regulating the expression of numerous genes encoding drug-metabolizing enzymes and transporters in the liver, with CYP2B6 as its primary target

(Wang and LeCluyse, 2003; Faucette et al., 2006a). The clinical importance of CYP2B6, in relation to other cytochrome P450 enzymes, was only recognized recently based on findings indicating that it plays a critical role in the biotransformation of several important drugs, such as

CPA, efavirenz, ifosfamide, tamoxifen, and artemisinin (Huang et al., 2000b; Crewe et al., 2002;

Ward et al., 2003b). We found that CITCO, a known selective activator of human CAR, elicited a strong induction of hepatic CYP2B6 but moderate to no induction of other genes involved in

CHOP disposition. Thus, combination of CITCO with CHOP enhances the bioactivation of CPA, while may only marginally influence the disposition of other drugs in the regimen. Moreover,

CITCO did not alter the expression of any key CHOP-metabolizing enzymes nor drug transporters in target lymphoma cells. In line with these findings, addition of CITCO to CHOP combination therapy significantly enhanced cytotoxicity toward SU-DHL-4 cells, when co- cultured with functional HPH. Importantly, in a similar co-culture model containing HepaRG cells, a promising surrogate of HPH, the beneficial effects of CITCO on the CHOP regimen were abolished when CAR was knocked out, further confirming the pivotal role of CAR in this new therapeutic combination.

Although this initial hepatocyte/lymphoma co-culture model has demonstrated promising antineoplastic activity in SU-DHL-4 cells by inclusion of CITCO in the CHOP regimen, this rather simplified model does not include the major off-target toxic sites of this regimen.

102

Clinically, CHOP-related late cardiotoxicity is a major concern for aggressive non-Hodgkin lymphoma patients (Limat et al., 2003a). It was estimated that over 20% of patients experience cardiac events after CHOP chemotherapy (Chlebowski, 1979; Limat et al., 2003a) and cardiac failure appeared to be the most important cause of death of patients in complete remission after

CHOP (Habermann et al., 2006). In this study, we have developed a multi-organ co-culture model incorporating HPH, SU-DHL-4, and H9c2 cells in different chambers, with shared culture medium. Building upon our previous co-culture model, this new design enabled synchronous monitoring of CHOP-mediated antineoplastic activity in SU-DHL-4 cells and cardiotoxicity in

H9c2 cells in the presence of functional human hepatocytes. The H9c2 cell line, though originated from rat myocardium, has been broadly accepted as an in vitro cell model for investigating drug-induced cardiotoxicity (Turakhia et al., 2007). Notably, our results with this novel co-culture model revealed that co-treatment with CITCO and CHOP led to selectively enhanced cytotoxicity in SU-DHL-4, but not in H9c2, cells. Moreover, it appears that a synergistic effect between CITCO and CHOP exists, with 100 µM CHOP + CITCO achieving comparable cytotoxicity in SU-DHL-4 cells as was observed with 500 μM CHOP alone.

Whereas this in vitro cell-based synergy cannot precisely predict clinical benefit, it indicates the potential that inclusion of CITCO may improve the therapeutic index of CHOP by lowering the doses of the regimen drugs required to achieve efficacy in non-Hodgkin lymphoma patients.

In accordance with these findings, the selective antineoplastic benefit of the CITCO/CHOP combination was illustrated further by examining apoptosis, DNA damage, and oxidative stress, which are associated with mechanisms of CHOP chemotherapy drug action (Mohammad et al.,

2003). Cleavage of caspase 3 is a common mechanism of apoptosis induced by CPA, doxorubicin and vincristine (Schwartz and Waxman, 2001; Rebbaa et al., 2003). The life-

103 threatening cardiotoxicity related to doxorubicin is associated with its ability to intercalate into

DNA, causing DNA damage and redox cycling activity, and thereby generating reactive oxidative species and oxidative stress (Tsang et al., 2003; Kim et al., 2006). In fact, doxorubicin- induced phosphorylation of histone H2AX, a marker for DNA double strand breaks, and oxidative stress in H9c2 cells have been extensively used to investigate cardiotoxicity of doxorubicin-containing regimens (Ma et al., 2013b). We found that the CITCO/CHOP combination exhibited selective toxicity in SU-DHL-4 cells, manifested by increased caspase 3 cleavage, H2AX phosphorylation, and oxidative stress. Clearly, in the presence of CITCO, lower doses of CHOP chemotherapy drugs decrease its off-target cardiotoxicity in H9c2 cells.

Building upon these in vitro results, we sought to move these studies one step further by performing an in vivo xenograft study in hCAR-transgenic mice. However, prior to tumor cell implantation in mice, preliminary gene induction studies were performed and the sensitivity of

EL4 mouse-derived lymphoma cells to the CITCO/CHOP combination had to be examined. In hepatocytes isolated from hCAR-transgenic mice, we observed a significant induction in

Cyp2b10 (mouse ortholog of human CYP2B6) following treatment with CITCO (1 µM), and modest induction of Cyp3a11 (mouse ortholog of human CYP3A4) and Abcb1a; indicative of response to a selective hCAR activator, as CITCO activates hCAR but has no impact on activity of mCAR. Further, the typical mCAR activator, TCPOBOP, had no effect on the expression of these target genes. In primary hepatocytes isolated from wild-type mice, we observed the opposite trend; these target genes were induced by the mCAR activator TCPOBOP but the hCAR activator CITCO had no effect. These results indicated that the hCAR transgenic mouse model was performing as expected.

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Using primary hepatocytes isolated from both WT- and hCAR-transgenic mice, we performed co-culture studies with EL4 lymphoma cells isolated from the same mouse strain as our hCAR- transgenic mice, C57BL/6. In line with our gene induction data, we observed in culture with hCAR-transgenic MPH, the CITCO/CHOP combination was more cytotoxic towards the EL4 lymphoma cells than CHOP alone or CHOP administered with TCPOBOP. In cultures with WT-

MPH, no difference was observed between CHOP alone and the CITCO/CHOP combination but combining CHOP with mCAR activator TCPOBOP increased the anticancer activity of CHOP in culture. Together with our gene induction studies, these results indicate both that our hCAR- transgenic mice are suitable for studying the impact of hCAR activation on the disposition of

CHOP and that EL4 mouse-derived lymphoma cells are sensitive to the CITCO/CHOP combination and are therefore suitable for use in a tumor xenograft study.

Our xenograft study included four treatment groups: vehicle control (corn oil and saline, CITCO alone (20 mg/kg in corn oil), CHOP along (40 mg/kg in saline), and CITCO (20 mg/kg in corn oil) plus CHOP (40 mg/kg in saline). Our results indicated that CITCO has no anti-cancer activity on its own in xenografted tumors in mice as there was no difference between the

CITCO-treated group and the control group, At the time of each tumor measurement, the

CITCO/CHOP combination was the most effective in the xenografted EL4 tumors. Further, by the end of the 20-day study, 3 of the mice in the CITCO/CHOP group did not bear measurable tumors; an additional improvement over CHOP treatment alone. At the cessation of the study, the tumors were isolated from the mice and weighed. The overall mass of the isolated tumors was significantly decreased beyond that of the CHOP-alone treatment group.

Following this tumor growth study, tumor and heart tissue were harvested for further gene and protein expression analysis. In tumor tissue, we examined the expression of several genes

105 responsible for cell proliferation and cell cycle progression including Pcna, Ki-67, and Cyclin D-

1. No difference was observed in the expression of these genes between the control and CITCO- treated groups. Treatment with CHOP significantly inhibited the expression of these genes in tumor tissue. The expression of these genes was inhibited by the CITCO/CHOP combination beyond the levels observed in the CHOP alone group. Further, western blotting analysis revealed that the CITCO/CHOP treated tumor tissue expressed significantly greater levels of cleaved caspase 3, a commonly utilized marker of apoptosis. Further, in heart tissue, while there was an increase in cleaved caspase 3 expression between the control and CHOP alone-treated groups, no difference was observed in the cleaved caspase 3 levels in the heart tissue of the CHOP alone and CITCO/CHOP treated mice.

To gain a better understanding of the mechanism by which CITCO increases the anticancer activity of the CHOP regimen we performed a pharmacokinetic study in hCAR mice to examine the overall exposure of 4-OH-CPA in the presence or absence of CITCO. In this study we performed serial sampling of blood from the lateral tail vein of mice as described in the materials and methods to limit the number of subjects necessary to perform this study while maintaining a sufficient number of samples at each time point (n=5/time point) to establish significance. We observed that the inclusion of CITCO roughly decreased the exposure to the parent CPA molecule in mice 2-fold, while exposure to the active metabolite, 4-OH-CPA was increased approximately 2-fold as well, following treatment with CITCO. Further, the 4-OH-CPA:CPA ratio was more than doubled in the CITCO-treated cohort.

Collectively, our results show that selective activation of CAR improves the overall cytotoxicity of CHOP chemotherapy toward its target non-Hodgkin lymphoma cells. The beneficial impact of

CAR activation in CHOP-based treatment in hematopoietic malignancies derived primarily from

106 enhanced formation of the active metabolite of CPA, the backbone of CHOP, via selective induction of CYP2B6 expression in human hepatocytes, and from the selective cytotoxicity toward lymphoma cells, in relation to cardiomyocyte cells. The newly established multi-organ co-culture model provides an excellent in vitro cellular environment allowing simultaneous investigation of hepatic metabolism, target therapeutic activity, and off-target toxicity of chemotherapeutic regimens. In the meantime, we do realize that cell-based in vitro models are associated with inherent limits and only reflect parts of the whole picture. Results from animal studies usually offer more physiologically relevant outcomes. However, it is important to point out that although hCAR exhibits several shared features with its rodent counterparts, marked differences between rodent and human CAR exist (Maglich et al., 2003; Wang and LeCluyse,

2003). CITCO has been demonstrated to activate human but not mouse CAR. Importantly, phenobarbital, a pan activator of CAR across multiple species, promotes liver tumor formation in mice but not humans (Elcombe et al., 2014). Overall, our current promising findings warrant further investigation, including identifying a clinically approved selective hCAR activator, as

CITCO is currently only a research compound.

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3.Targeting Transcription Factors to Improve CHOP-based treatment of lymphomas: Roles of CAR and Nrf2

4.1 Introduction

Hematologic malignancies include a wide range of clinical conditions with highly variable prognoses depending on the type of disease, stage at diagnosis, and choice of treatment. The two most common hematologic malignancies are lymphoma and leukemia and these are also the seventh and ninth most often diagnosed cancers, respectively, in the United States (Siegel et al.,

2017). Together, a projected 142,630 new diagnoses and 45,710 related deaths will occur in the

United States in 2017 (Teras et al., 2016; Siegel et al., 2017). Although many advancements have been made in patient screening, surveillance, diagnosis, and treatment, many patients do not optimally respond to currently available chemotherapeutic regimens (Cummin and Johnson,

2016). This illustrates the current need for further optimization of treatment options.

Cyclophosphamide (CPA) is an alkylating agent that has been used extensively in combination therapies with other antineoplastic drugs for the treatment of various cancers including the non-

Hodgkin lymphoma (NHL) and chronic lymphocytic leukemia (CLL) (Bonadonna et al., 1995a;

Mounier et al., 2003; Coiffier, 2005a; Badoux et al., 2011). Specifically, CPA is the main component of the front-line chemotherapy combination for NHL, the CPA-doxorubicin- vincristine-prednisone (CHOP) regimen with or without the addition of anti-CD20 monoclonal antibody rituximab (Mounier et al., 2003; Michallet and Coiffier, 2009a). While this treatment has provided significant improvement in the long-term survival of patients diagnosed with early-

112 stage NHL, patients diagnose with stage III or IV disease have markedly decreased survival rates

(Michallet and Coiffier, 2009a; Sehn, 2010). Further, over 30% of patients with diffuse large B cell lymphoma (DLBCL), the most frequently diagnosed form of NHL, eventually relapse following treatment with the CHOP regimen (Falduto et al., 2017). Thus, there is a clear unmet need for improving the efficacy while minimizing the toxicity of this regimen for patients. A potential means for accomplishing this improvement in the efficacy:toxicity ratio of CPA- containing chemotherapy regimens is to enhance the metabolic conversion of CPA to its pharmacologically active form, 4-hydroxycyclophosphamide (4-OH-CPA), without a concomitant increase in the non-therapeutic or toxic byproducts.

CPA is a prodrug belonging to the oxazaphosphorine class of alkylating agents which have a broad spectrum of activity against various types of cancer (Solomon et al., 1963; Brock, 1989).

As it is a prodrug, the therapeutic efficacy of CPA depends on drug metabolizing enzyme

(DME)-mediated bioactivation to produce the active form of drug (Fenselau et al., 1977). The conversion of CPA to 4-OH-CPA is mediated predominantly by cytochrome P450 2B6

(CYP2B6) with minor contributions from CYP2C9 and 2C19 (Roy et al., 1999b; Huang et al.,

2000a; Wang and Wang, 2012; Hedrich et al., 2016a). Alternatively, CPA can be converted to an inactive metabolite, N-dechloroethyl-cyclophosphamide (N-DCE-CPA) and a neurotoxic compound, chloroacetaldehyde, exclusively by CYP3A4 in humans (Yu and Waxman, 1996).

Therefore, selective induction of CYP2B6 expression in cancer patients could potentiate CPA- based chemotherapy without a concomitant increase in untoward toxicities.

The constitutive androstane receptor (CAR, NR1I3) and the pregnane X receptor (PXR, NR1I2) are recognized as the primary mediators of the inductive expression of CYP2B6 and CYP3A4, respectively (Lehmann et al., 1998; Sueyoshi et al., 1999b). Importantly, while human PXR

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(hPXR) activation induces the expression of both CYP3A4 and CYP2B6 in concert, selective activation of human CAR (hCAR) results in the preferential induction of CYP2B6 over CYP3A4

(Faucette et al., 2006b; Faucette et al., 2007). For our purposes, this selective induction of

CYP2B6 may facilitate CPA bioactivation and improve the efficacy:toxicity ratio of CPA-based chemotherapy. Previously in our lab we demonstrated that activation of hCAR by a potent and selective activator, 6-(4-Chlorophenyl)imidazo[2,1-b][1,3]thiazole-5-carbaldehyde O-(3,4- dichlorobenzyl)oxime (CITCO), increases CPA-based antineoplastic activity in both leukemia and lymphoma cells by facilitating CYP2B6-mediated bioactivation of CPA without augmenting unwanted side-toxicities (Wang et al., 2013a; Hedrich et al., 2016b). These findings suggest that the inclusion of a selective hCAR activator alongside a clinically used CPA-containing regimen could benefit cancer patients.

A major side toxicity that occurs from CHOP treatment is cumulative cardiotoxicity arising from the doxorubicin component of the regimen (Zhou et al., 2001b; Ma et al., 2013a). Doxorubicin has been shown to illicit increased oxidative stress, DNA damage, and apoptosis in cardiomyocytes and it is recommended that lymphoma patients with pre-existing heart conditions avoid receiving treatment with the full CHOP combination (Limat et al., 2003b).

Recently, mounting evidence has demonstrated that the nuclear factor (erythroid-derived 2)-like

2 (NFE2L2, Nrf2) plays a key role in governing doxorubicin-mediated cardiotoxicity(Li et al.,

2014). Nrf2 regulates the expression of important antioxidant genes and proteins that protect tissues from damage due to oxidative stress and inflammation (Ma, 2013). It has been demonstrated both that insufficient expression of Nrf2 results in exaggerated cardiotoxicity following doxorubicin treatment and that stimulation of Nrf2 by small molecule activators can provide protection from doxorubicin-mediated toxicity (Wang et al., 2015; Hajra et al., 2017).

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In the present study, we sought to advance upon our findings presented in chapter 3 which implicate hCAR as a target for facilitating CHOP-based chemotherapy in vitro and in vivo in lymphomas. We recognize that CITCO is not a clinically utilized or approved mediation. To this end, we have also identified a number of approved drugs which exhibit CITCO-like activation of hCAR. Going one step further, we have identified multiple compounds which can activate both hCAR and Nrf2 in cardiac cells which, in in vitro cytotoxicity and co-culture studies, provides for both improved anticancer activity in NHL cells while offering significant protection against toxicity in cardiomyoblast cells. Taken together, these results have the potential to provide rapid and significant improvement in cancer treatment and diminished toxicity from treatment.

4.2 Materials and Methods

4.2.1 Materials CPA, doxorubicin, vincristine, prednisone, CITCO, MTT reagent, and semicarbazide hydrochloride were purchased from Sigma-Aldrich (St. Louis, MO). 4- hydroperoxycyclophosphamide was purchased from Santa Cruz Biotechnology. Oligonucleotide primers were synthesized by and purchased from Integrated DNA Technologies. Insulin,

Matrigel, and ITS+ culture supplies were purchased from BD Biosciences. Pifexole was purchased from Key Organics. CCK8 kit was obtained from Enzo Life Sciences.

4.2.2 High-throughput screening of hCAR and Nrf2 activators High-throughput screening of a library of approximately 2800 compounds from the NIH

Chemical Genomics Center Pharmaceutical Collection was performed in a stable hCAR-

CYP2B6-HepG2 cell line for hCAR activation as well as an ARE.bla cell line for Nrf2 activation as previously reported (Lynch et al., 2015; Lynch et al., 2016). Briefly, cells seeded in 1536-well

115 plates were treated with a range of concentrations of compounds. In hCAR-CYP2B6-HepG2 cells, CITCO (1 µM) was used as a positive control for hCAR activation In ARE.bla cells, β- napthoflavone was used as a positive control for Nrf2 activity.

4.2.3 Culture of Primary Human Hepatocytes HPH were obtained from Bioreclamation, IVT. Hepatocytes with viability greater than 90% were seeded at 7.5 x 105 cells per well in 12-well collagen-coated plates. Following 4 hours for attachment, cells were overlaid with Matrigel (0.25 mg/mL) in serum-free Williams Medium E to form the typical sandwich culture as previously described (LeCluyse et al., 2005a). Following incubation for 24 hours, HPH were treated with various compounds for 24 h for mRNA analysis or 72 h for protein.

4.2.4 Hepatococyte/Lymphoma Co-culture The hepatocyte/lymphoma co-culture studies were performed as described previously (Wang et al., 2013a). Briefly, HPH or MPH were cultured in collagen-coated 12-well plates and treated with vehicle control (0.1% DMSO) or other various treatments for 24 hours. Following this pre- treatment, the wells were separated with 3.0 µm polycarbonate membrane inserts (Sigma-

Aldrich). A total of 0.5 x 106 lymphoma cells suspended in supplemented Williams E Medium were added inside of the insert such that the final volume of medium in each well was 2 mL. The cocultures were exposed to designated concentrations of the CHOP drugs in the presence or absence of pre-treatment compounds for various time intervals, as indicated. For all studies, medium and treatments were replaced every 24 hours.

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4.2.5 Multi-cell co-culture In addition to the two-cell co-culture described above, we utilized H9c2 cardiomyoblast cells to assess the off-target cardiotoxicity of our drug treatments as described previously (Hedrich et al.,

2016b). In short, H9c2 cells were plated on modified coverslips at 1 x 105 cells/mL and allowed to attach overnight at 37°C and 5% CO2. Following attachment, the coverslips were inserted into each co-culture well between the sandwich-cultured hepatocytes and the Transwell® insert. The cultures were exposed to designated concentrations of CHOP drugs in the presence and absence of CITCO, PIF, and FRE. Both lymphoma cells and H9c2 cells were harvested at the indicated time points and assessed for viability.

4.2.6 CCK8 Cytotoxicity Assays H9c2 cells were seeded in 96-well plates at a density of 7.5 x 104 cells/well and incubated for 24 hours at 37°C and 5% CO2. Additionally, several lymphoma and leukemia cell lines were seeded at the same density in 96-well plates. However, as these are suspension cell lines, 24-hour incubation was not necessary to allow for cell attachment. Cells were serum-starved for 6 hours to sensitize them to Nrf2-activating compounds and were then treated for 24 hours with vehicle control (0.1% DMSO), 0.1% Triton X-100 as a positive control for cell death, and a range of concentrations of SFN, PIF, and FRE (each 1, 5, 10, and 20 µM) to allow for the activation of

Nrf2 and induction of its target genes. Following this 24-hour incubation, cells were treated with doxorubicin (1 or 2.5 µM) or CHOP (20 or 50 µM) for an additional 24 hours at 37°C and 5%

CO2. After this treatment period 10 µL of CCK8 reagent was added to each well and the cells were incubated for 3 hours at 37°C and 5% CO2. The plate was read directly on a SpectraMax

384 Plus plate reader (Molecular Devices) with the absorbance determined at 450 nm. Cell viabilities were normalized to the vehicle control (DMSO).

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4.2.7 RT-qPCR Analysis Total RNA from HPH, MPH, lymphoma cells, and H9c2 cells was isolated with TRIzol Reagent

(Life Technologies) and reverse transcribed using a High Capacity cDNA Archive kit (Applied

Biosystems) following the manufacturers’ instructions. mRNA expression of CYP2B6,

CYP3A4, MDR1, HO-1, Nqo1, Cyp2b10, Cyp3a11 was normalized against that of GAPDH (or

Gapdh in rat- derived samples). Real-time PCR assays were run on a StepOnePlus Real-Time

PCR System (Applied Biosystems) in 96-well optical plates with SYBR Green PCR Master Mix

(Applied Biosystems). The primer sequences used for real-time PCR analyses are listed in Table

4.1(Yeligar et al., 2010; Yang et al., 2014; Zarrouki et al., 2014). Fold induction of genes versus the control was determined as 2∆∆Ct where ∆Ct is representative of the difference in cycle threshold number between the target gene and housekeeping gene while ∆∆Ct indicates the relative change in the intergroup variations. In order to stimulate responsiveness to Nrf2- activating compounds in H9c2 cells, the cells were serum-starved for 6 hours prior to 24-hour treatment with various compounds. All experiments were performed in triplicate unless otherwise specified in the described experimental techniques.

4.2.8 Statistical Analyses All data are presented as the mean of triplicate measurements ± SD unless otherwise noted.

Comparisons were made via one-way ANOVA using post hoc Dunnett’s analysis. Significance was determined at *, p < 0.05.

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Table 4.1 Primers used in qPCR studies in HPH and H92 cells.

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4.3 Results

4.3.1 High-throughput screening reveals several dual-activators of CAR and Nrf2 We screened a library of approximately 2800 compounds from the NIH Chemical Genomics

Center Pharmaceutical Collection for their activity in both ARE.bla cells and HepG2 cells stably expressing CYP2B6 to identify any compounds that could potently activate both Nrf2 as well as

CAR (Fig. 4.1, 4.2). Ten compounds with at least modest dual activity were identified. Among them, frentizole (FRE) and pifexole (PIF) achieved the greatest activation of both Nrf2 and CAR and were carried forward for mRNA analysis of their induction of CYP2B6 and CYP3A4 in

HPH (Fig. 4.3A,B) and Nrf2 target genes HO-1 and Nqo1 in H9c2 cells (Fig. 4.3C,D). In HPH,

PIF demonstrated strong induction of CYP2B6 and only modest induction of CYP3A4 while

FRE induced each to a similar extent, and not as potently as the positive control (CITCO) nor

PIF. In H9c2 cells, PIF induced each HO-1 and Nqo1 in a concentration-dependent manner, though the maximum effect of PIF was greater than that achieved by FRE (Fig. 4.3C,D).

4.3.2 FRE and PIF significantly increase expression of Nrf2 target genes in H9c2 cells but not in lymphoma cells In H9c2 cells, PIF and FRE induce the expression of Nrf2 target genes HO-1 and Nqo1 in a concentration-dependent (1-20 µM) manner (Fig. 4.3C, D). However, in a panel of lymphoma cells, the expression of these genes is not altered significantly by PIF or FRE at the same concentrations. The typical Nrf2 activator SFN (10 µM) was used as a positive control in these studies and showed strong induction of HO-1 and Nqo1 in H9c2 cells, but not in any of the three lymphoma cell lines (SU-DHL-4, SU-DHL-6, OCI-LY-3) tested (Fig. 4.4A,B).

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4.3.3 Activation of Nrf2 by PIF and FRE protects against doxorubicin-induced toxicity in H9c2 cardiomyoblast cells but not in lymphoma cells In order to examine the impact of activating Nrf2 and inducing its downstream target antioxidant genes on the toxicity of doxorubicin in both cardiac (H9c2) and lymphoma (SU-DHL-4, SU-

DHL-6, OCI-LY-3) cells, CCK8 assays were carried out as described in the materials and methods. In H9c2 cells, pre-treatment with a Nrf2 activator such as SFN, PIF, or FRE resulted in a concentration-dependent recovery in cell viability following doxorubicin or CHOP treatment.

However, under the same conditions, the viability of the target lymphoma cells was not altered by the Nrf2 activators (Fig. 4.5-4.8). Concentrations of doxorubicin were selected from literature or preliminary experiments (data not shown) to achieve ~50% viability in target cells. CHOP concentrations utilized corresponded with the total CHOP drug load containing the same amount of doxorubicin used in the doxorubicin-alone studies.

. 4.3.4 PIF/CHOP or FRE/CHOP combination significantly increases cytotoxicity in target lymphoma cells but not in off-target H9c2 cells in co-culture Utilizing our multi-organ co-culture system (Fig. 4.9A) we examined the impact of combining

PIF and CHOP on both the anti-cancer activity of the regimen as well as the cardiotoxicity associated with it. Co-cultures were treated with the designated concentrations of CHOP and

CITCO, PIF, or FRE. After 24 hours, the viability of both target lymphoma cells and off-target

H9c2 cells were examined. At all drug concentrations, the addition of each PIF or FRE (20 µM each) increased the anti-cancer activity of CHOP in lymphoma cells to an extent similar to that seen with the CITCO/CHOP combination (Fig. 4.9B-E). Further, the addition of PIF and FRE significantly increased the viability of the off-target cardiac cells (Fig. 4.9F).

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hCAR Activators Identified with High-Throughput Screening

Figure 4.1: High-throughput screening reveals several compounds which activate hCAR in hCAR-CYP2B6-HepG2 cells. High-throughput screening of approximately 2800 compounds from from the NIH Chemical Genomics Center Pharmaceutical Collection. CITCO (1 µM) was used as a positive control for hCAR activation.

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Nrf2 Activators Identified with High-Throughput Screening

Figure 4.2: High-throughput screening reveals several compounds which activate Nrf2 in ARE.bla cells. Compounds which activated hCAR in a HTS were also screened for their Nrf2 activation profiles in ARE.bla cells. β-napthoflavone was used as a positive control for Nrf2 activation.

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4.4 Discussion

NHL and other hematologic malignancies remain a significant health concern and the need to improve current treatment options is evident. Currently, the CHOP regimen, with or without rituximab, remains the front-line therapy for aggressive NHL (Mounier et al., 2003; Michallet and Coiffier, 2009a). While significant progress has been made in the use of this treatment and development of alternatives, many patients still are not cured of their disease due to acquired drug resistance and/or drug-related toxicities requiring premature withdrawal from therapy.

CPA, a primary component of this CHOP regimen, is a prodrug which requires hepatic oxidation primarily via CYP2B6 to its pharmacologically active form, 4-OH-CPA. Further, another main component of this regimen, doxorubicin, appears to be the main source of the severe and cumulative cardiotoxicity commonly related with CHOP treatment (Limat et al., 2003b;

Nickenig et al., 2006). In our previous work we have demonstrated that activation of CAR in human primary hepatocytes selectively and significantly induces the expression of CYP2B6, increasing the oxidative metabolism of CPA to 4-OH-CPA (Wang et al., 2013a). Further, in co- cultures with human primary hepatocytes for drug metabolism, lymphoma cells as a model drug target, and H9c2 cells as an indicator of off-target toxicity, we previously showed that the inclusion of CITCO, a selective hCAR activator, increases the anti-cancer activity of CHOP while not affecting its off-target toxicity. These results have also been observed in tumor xenograft studies in hCAR-tg mice as illustrated in Chapter 3. Here, we have provided preliminary evidence for the utility of combining CHOP with small molecule therapeutics with activation activity towards both CAR in liver cells and Nrf2 in cardiac cells to increase anticancer activity in lymphoma cells while also offering protection from oxidative damage in cardiac tissue.

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Figure 4.3: Lead compounds from HTS induce expression of hCAR target genes in HPH and Nrf2 target genes in H9c2 cells. Two compounds identified as dual activators of hCAR and Nrf2 in HTS were carried forward for gene induction studies in HPH and H9c2 cardiomyocyte cells. HPH were treated with CITCO (1 µM) as a positive control for hCAR activation and CYP2B6 induction as well as PIF (10, 20 µM) and FRE (10, 20 µM) (A, B). H9c2 cells were treated with SFN (10 µM) as a positive control for Nrf2 activation and HO-1 and Nqo1 induction as well PIF and FRE (10, 20 µM each) (C, D). *, p < 0.05; **, p < 0.01; ***, p < 0.001.

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Figure 4.4: PIF and FRE do not significantly induce the expression of Nrf2 target genes in lymphoma cell lines. Three lymphoma cell lines, SU-DHL-4, SU-DHL-6, and OCI-LY-3 were treated with SFN (10 µM) as a positive control for Nrf2 activation, and a range of PIF and FRE concentrations (5-20 µM). The effects of these compounds on the expression of Nrf2 target genes HO-1 (A) and Nqo1 (B) were modest and induction by SFN, though statistically significant, was less than 2-fold. *, p < 0.05.

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Despite the promising initial findings that hCAR activation leads to improved anti-cancer activity both in vitro and in vivo presented in Chapter 3, there remains the challenge of improving the toxicity profile of the CHOP regimen. Treatment with CHOP has been associated with severe and cumulative cardiotoxicity arising from another major component, doxorubicin.

To date, several studies have revealed that Nrf2 plays a significant role in mediating responses to doxorubicin-induced stressed in cardiac tissue and that activation or over-expression of Nrf2 can provide protection against doxorubicin-induced cardiotoxicity. To this end, we have sought to identify currently approved compounds with dual activity towards both hCAR and Nrf2, as such a compound could improve the activity and safety profile of the two major components of the

CHOP regimen by increases CPA bioactivation and protecting against doxorubicin-mediated cardiotoxicity.

From our high-throughput screening of a library of roughly 2800 compounds, we identified several compounds with dual activity towards hCAR and Nrf2 in reporter assays. Two compounds which demonstrated potent activation of each transcription factor, pifexole and frentizole, were carried forward for qPCR analysis of gene induction in HPH, H9c2 cardiomyoblast cells, and several non-Hodgkin lymphoma cell lines including SU-DHL-4, SU-

DHL-6, and OCI-LY-3 cells. Our studies revealed that pifexole and frentizole are each able to induce the expression of hCAR target genes, in particular, CYP2B6 in HPH, and Nrf2 target genes, specifically HO-1 and Nqo1 in H9c2 cells. Importantly, treatment with these compounds did not induce the expression of Nrf2 target genes in the lymphoma cell lines to a significant extent. This may be due to very high basal levels of Nrf2 in cancer cells rendering them insensitive to Nrf2 activators and further induction of its target genes.

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Figure 4.5: Treatment with Nrf2 activators provides significant protection from DOX- and CHOP-induced cardiotoxicity in H9c2 cultures. H9c2 cells were treated with a range of SFN, PIF, and FRE concentrations (1-20 µM) for 24 hours followed by treatment with DOX (1 µM) (A-C) or CHOP (20 µM) (D-F) for an additional 24 hours. Following this treatment incubation, viability of H9c2 cells was examined with prototypical CCK8 assays as detailed in the materials and methods. Treatment with Nrf2 activating compounds was non-toxic over the utilized range of concentrations. DOX and CHOP treatment significantly reduced the viability of the H9c2 cells by about 50 and 60%, respectively. Treatment with Nrf2 activating compounds demonstrated concentration-dependent cardioprotection in these cultures. *, p < 0.05; **, p < 0.01; ***, p < 0.001.

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Figure 4.6: SFN, PIF, and FRE pre-treatment does not offer protection against DOX- and CHOP-induced cytotoxicity in SU-DHL-4 cells. SU-DHL-4 cells were pretreated for 24 hours with SFN, PIF, and FRE (1-20 µM) before being treated with DOX (2.5 µM) (A-C) or CHOP (50 µM) (D-F). Following treatment, prototypical CCK8 assays were carried out to examine the viability of the SU-DHL-4 cells. Treatment with SFN, PIF, and FRE had no impact on the viability of the lymphoma cells while DOX and CPA significantly reduced their viability. Pre- treatment with SFN, PIF, and FRE did not have any impact on the viability of the cells later treated with DOX or CHOP.

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To examine the direct impact of Nrf2 activation by these two compounds, PIF and FRE, we carried out prototypical CCK8 cytotoxicity assays to examine the protective effects against doxorubicin toxicity in cardiomyoblasts and lymphoma cells. Each cell type was pre-treated with a range of PIF, FRE, and SFN (positive control for Nrf2 activation) concentrations for 24 hours to allow for induction of Nrf2 target genes. Following this pre-treatment, the cells were challenged with either DOX (1 or 2.5 µM) alone or the full CHOP (20 or 50 µM) regimen. This

CHOP concentration was chosen as the concentration of the individual DOX component is 1

µM. In cardiomyocytes, PIF, FRE, and SFN remained non-toxic over the full concentration range (1-20 µM) while DOX and CHOP concentrations were selected to reduce the viability of cells to approximately 50%. Pre-treatment with these compounds resulted in a significant recovery of the viability of cardiomyoblast cells in a concentration-dependent manner. In line with our preliminary results which indicated that treatment with Nrf2 activators did not dramatically stimulate the expression of Nrf2 target genes, pre-treatment with PIF, FRE, and

SFN did not have any significant impact on the viability of any screened lymphoma cell line.

These results indicate that these newly identified compounds with dual activity towards hCAR and Nrf2 may augment the anticancer activity of CHOP through CPA bioactivation, and also improve the safety profile of the regimen by alleviating the dose-limiting cardiotoxicity from doxorubicin.

Previously, we utilized a novel co-culture system containing HPH, target lymphoma cells, and off-target H9c2 cardiomyocyte cells to examine the impact of hCAR activation on anticancer activity in NHL cells and off-target toxicity in cardiac cells. These studies demonstrated that while hCAR activation in HPH significantly increased the expression of CYP2B6 and subsequent biotransformation of CPA to 4-OH-CPA, there was no impact on the toxicity in

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Figure 4.7: SFN, PIF, and FRE pre-treatment does not offer protection against DOX- and CHOP-induced cytotoxicity in SU-DHL-6 cells. SU-DHL-6 cells were pretreated for 24 hours with SFN, PIF, and FRE (1-20 µM) before being treated with DOX (2.5 µM) (A-C) or CHOP (50 µM) (D-F). Following treatment, prototypical CCK8 assays were carried out to examine the viability of the SU-DHL-6 cells. Treatment with SFN, PIF, and FRE had no impact on the viability of the lymphoma cells while DOX and CPA significantly reduced their viability. Pre- treatment with SFN, PIF, and FRE did not have any impact on the viability of the cells later treated with DOX or CHOP.

131 cardiac tissue. Here, using this same co-culture model, we were able to investigate, in a single culture well: the impact of these dual activators on the activation hCAR and expression of its target genes in HPH, activation of Nrf2 and expression of its downstream target genes in H9c2 cardiomyoblast cells, the impact of these activators on the anti-cancer activity of CHOP in target lymphoma cells, and the viability of off-target cardiac cells following combined treatment.

Taken together these results offer a strong foundation for utilizing hCAR as a novel target for facilitating CPA-based treatment of lymphomas. We have demonstrated that the inclusion of a selective hCAR activator increases the antineoplastic activity of the CHOP regimen both in vitro in a novel co-culture model and in vivo in a hCAR-transgenic mouse xenograft model. Further, we have provided preliminary evidence for utilizing currently approved compounds with dual activity towards both hCAR and Nrf2 as a means to significantly improve the therapeutic ratio of

CHOP treatment by increasing the efficacy of the drug combination while simultaneously diminishing the untoward side effects.

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Figure 4.8: SFN, PIF, and FRE pre-treatment does not offer protection against DOX- and CHOP-induced cytotoxicity in OCI-LY-3 cells. OCI-LY-3 cells were pretreated for 24 hours with SFN, PIF, and FRE (1-20 µM) before being treated with DOX (2.5 µM) (A-C) or CHOP (50 µM) (D-F). Following treatment, prototypical CCK8 assays were carried out to examine the viability of the OCI-LY-3 cells. Treatment with SFN, PIF, and FRE had no impact on the viability of the lymphoma cells while DOX and CPA significantly reduced their viability. Pre- treatment with SFN, PIF, and FRE did not have any impact on the viability of the cells later treated with DOX or CHOP.

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Figure 4.9: In multi-organ co-cultures with HPH, lymphoma cells, and cardiomyocytes, PIF and FRE significantly enhance cytotoxicity in target cells while alleviating off-target toxicity. Multi-organ co-cultures (A) were utilized to examine the impact of PIF and FRE (20 µM each) on the anticancer activity of CHOP in lymphoma cells as well as the off-target toxicity of the regimen in H9c2 cardiomyoblast cells. At all CHOP concentrations, anticancer activity of CHOP was enhanced in the presence of PIF and FRE (B, D). This enhanced cytotoxicity was also observed in a time-dependent manner (C, E). CITCO (1µM) was used as a positive control for improving the anticancer activity in these cultures. After 24 hours, the viability of H9c2 cells in culture with PIF, FRE, and CHOP (100 µM) was examined (F). **, p < 0.01’ ***, p < 0.001.

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4.Conclusions

Hematologic malignancies encompass a wide range of clinical conditions with variable prognoses depending upon the type of disease, stage at diagnoses, and choice of treatment. The two most common hematologic malignancies are lymphoma and leukemia which also represent the seventh and ninth most commonly diagnosed cancers in the US (Michallet and Coiffier,

2009a; Sehn, 2010; Siegel et al., 2017). Despite many advancements in patient screening, surveillance, and treatment, many patients still ultimately succumb to their disease (Cummin and

Johnson, 2016). Thus, the need for improved therapeutic agents and strategies is evident. In this dissertation, we have examined multiple transcription factors, namely the constitutive androstane receptor (CAR, NR1I3) and nuclear factor (erythroid-derived 2)-like 2 (NFE2L2, Nrf2), as targets facilitating lymphoma treatment with the CHOP (cyclophosphamide-doxorubicin- vincristine-prednisone) chemotherapy regimen.

The CHOP regimen, with or without CD20 monoclonal antibody rituximab, is currently the front-line therapy for treatment of non-Hodgkin lymphoma (Mounier et al., 2003; Michallet and

Coiffier, 2009a). A major component of this regimen, cyclophosphamide (CPA), is a prodrug belonging to the oxazaphosphorine class of alkylating agents which exhibit a broad spectrum of activity against many cancers (Solomon et al., 1963; Brock, 1989). As a prodrug, CPA required bioactivation to its active form by hepatic metabolism (Fenselau et al., 1977). The bioconversion of CPA to 4-OH-CPA is carried out predominantly by CYP2B6 with minor contributions from

CYP2C9 and 2C19 (Roy et al., 1999b; Huang et al., 2000a). However, CPA can also be metabolized to an inactive byproduct, N-dechloeoethyl-cyclophosphamide (N-DCE-CPA) and a neurotoxic byproduct, chloroacetaldehyde, exclusively by CYP3A4 (Yu and Waxman, 1996).

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Therefore, selective induction of CYP2B6 expression in cancer patients could potentiate CPA- based chemotherapy without a concomitant increase in untoward toxicities. The constitutive androstane receptor (CAR, NR1I3) and the pregnane X receptor (PXR, NR1I2) are recognized as the predominant mediators of the inductive expression of CYP2B6 and CYP3A4, respectively

(Lehmann et al., 1998; Sueyoshi et al., 1999b). Importantly, selective activation of hCAR leads to preferential induction of CYP2B6 over CYP3A4 while activation of hPXR induces each enzyme to a similar extent (Faucette et al., 2006b; Faucette et al., 2007).

Cardiotoxicity is a well-documented side effect of CHOP chemotherapy which arises from the doxorubicin component of the regimen (Zhou et al., 2001b; Ma et al., 2013a). Doxorubicin is known to cause oxidative stress, DNA damage, and apoptosis in cardiomyocytes. As such, it is recommended that lymphoma patients with pre-existing heart conditions do not receive treatment with the full CHOP combination (Limat et al., 2003b). Nrf2 plays a key role in governing the expression of important antioxidant genes and proteins which can protect tissues from damage caused by oxidative stress and inflammation (Ma, 2013; Li et al., 2014). Insufficient Nrf2 expression has been associated with exacerbated cardiotoxic effects of doxorubicin. However, it has also been demonstrated that stimulation of Nrf2 by small molecule activators can provide protection from doxorubicin-induced cardiotoxicity in heart cells (Wang et al., 2015; Hajra et al.,

2017).

In chapter 3, we investigated this hypothesis using a novel hepatocyte-lymphoma-cardiomyocyte co-culture system which closely mimics the in vivo lymphoma condition. Based on this system, selective CAR activation with a small molecule, CITCO, selectively increased expression of hepatic CYP2B6 and enhanced the anticancer activity of CHOP towards lymphoma cells. The

CITCO/CHOP combination was able to achieve comparable anti-cancer activity as CHOP alone

139 at 20% of the overall drug load. The difference in overall drug load also lead to a decrease in the untoward cardiotoxicity associated with CHOP treatment. To investigate this finding further, we examined the CITCO/CHOP combination in vivo in an hCAR-transgenic (hCAR-tg) mouse model. In isolated primary hepatocytes from hCAR-tg mice, CITCO selectively stimulated the expression of Cyp2b10 over Cyp3a11, consistent with the trend observed in human primary hepatocytes. In a xenograft study, hCAR-tg mice bearing EL4 cell-derived tumors were treated with CITCO/CHOP to examine the impact of hCAR activation on anticancer activity of CHOP in vivo. We demonstrated that the CITCO/CHOP combination has significantly greater antitumoral activity than CHOP alone while not impacting the off-target toxicity of the regimen.

This increase in anticancer activity corresponded well with the findings of a PK study in hCAR- tg mice which revealed that the inclusion of CITCO significantly increases the exposure of mice to the active 4-OH-CPA metabolite of CPA.

In chapter 4 we built upon the findings in chapter 3 that activation of hCAR improves the efficacy:toxicity ratio of CHOP in lymphoma treatment in vitro and in vivo. We had demonstrated that with the inclusion of CITCO, significantly decreased doses of CHOP were required to achieve comparable anticancer activity. However, doxorubicin-associated cardiotoxicity remains a major issue with CHOP chemotherapy. To this end, we sought to identify compounds with dual activity towards hCAR and Nrf2 to both facilitate CPA bioactivation and provide cellular protection in cardiac cells. In a high-throughput screen with hCAR-CYP2B6-HepG2 cells and ARE.bla cells, several lead compounds were identified which exhibited activation of each of these transcription factors. The best of which, pifexole and frentizole, were carried forward for further characterization. Again utilizing our hepatocyte- lymphoma-cardiomyocyte co-culture system, we were able to demonstrate that concomitant

140 treatment of pifexole or frentizole alongside CHOP both increases the anticancer activity of

CHOP while alleviating some of the untoward cardiotoxicity of the regimen. While these experiments provide proof-of-concept findings for the utility of these compounds in vitro, further characterization of these drugs as potential therapeutic agents in combination with CHOP are warranted.

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Brock N (1989) Oxazaphosphorine cytostatics: past-present-future. Seventh Cain Memorial Award lecture. Cancer Res 49:1-7. Cummin T and Johnson P (2016) Lymphoma: turning biology into cures. Clin Med (Lond) 16:s125-s129. Faucette SR, Sueyoshi T, Smith CM, Negishi M, Lecluyse EL, and Wang H (2006) Differential regulation of hepatic CYP2B6 and CYP3A4 genes by constitutive androstane receptor but not pregnane X receptor. J Pharmacol Exp Ther 317:1200-1209. Faucette SR, Zhang TC, Moore R, Sueyoshi T, Omiecinski CJ, LeCluyse EL, Negishi M, and Wang H (2007) Relative activation of human pregnane X receptor versus constitutive androstane receptor defines distinct classes of CYP2B6 and CYP3A4 inducers. J Pharmacol Exp Ther 320:72-80. Fenselau C, Kan MN, Rao SS, Myles A, Friedman OM, and Colvin M (1977) Identification of aldophosphamide as a metabolite of cyclophosphamide in vitro and in vivo in humans. Cancer Res 37:2538-2543. Hajra S, Basu A, Singha Roy S, Patra AR, and Bhattacharya S (2017) Attenuation of doxorubicin-induced cardiotoxicity and genotoxicity by an indole-based natural compound 3,3'-diindolylmethane (DIM) through activation of Nrf2/ARE signaling pathways and inhibiting apoptosis. Free Radic Res 51:812-827. Huang Z, Roy P, and Waxman DJ (2000) Role of human liver microsomal CYP3A4 and CYP2B6 in catalyzing N-dechloroethylation of cyclophosphamide and ifosfamide. Biochem Pharmacol 59:961-972. Lehmann JM, McKee DD, Watson MA, Willson TM, Moore JT, and Kliewer SA (1998) The human orphan nuclear receptor PXR is activated by compounds that regulate CYP3A4 gene expression and cause drug interactions. J Clin Invest 102:1016-1023. Li S, Wang W, Niu T, Wang H, Li B, Shao L, Lai Y, Li H, Janicki JS, Wang XL, Tang D, and Cui T (2014) Nrf2 deficiency exaggerates doxorubicin-induced cardiotoxicity and cardiac dysfunction. Oxid Med Cell Longev 2014:748524. Limat S, Demesmay K, Voillat L, Bernard Y, Deconinck E, Brion A, Sabbah A, Woronoff- Lemsi MC, and Cahn JY (2003) Early cardiotoxicity of the CHOP regimen in aggressive non-Hodgkin's lymphoma. Ann Oncol 14:277-281. Ma J, Wang Y, Zheng D, Wei M, Xu H, and Peng T (2013) Rac1 signalling mediates doxorubicin-induced cardiotoxicity through both reactive oxygen species-dependent and - independent pathways. Cardiovasc Res 97:77-87. Ma Q (2013) Role of nrf2 in oxidative stress and toxicity. Annu Rev Pharmacol Toxicol 53:401- 426. Michallet AS and Coiffier B (2009) Recent developments in the treatment of aggressive non- Hodgkin lymphoma. Blood Rev 23:11-23. Mounier N, Briere J, Gisselbrecht C, Emile JF, Lederlin P, Sebban C, Berger F, Bosly A, Morel P, Tilly H, Bouabdallah R, Reyes F, Gaulard P, and Coiffier B (2003) Rituximab plus CHOP (R-CHOP) overcomes bcl-2--associated resistance to chemotherapy in elderly patients with diffuse large B-cell lymphoma (DLBCL). Blood 101:4279-4284.

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Roy P, Yu LJ, Crespi CL, and Waxman DJ (1999) Development of a substrate-activity based approach to identify the major human liver P-450 catalysts of cyclophosphamide and ifosfamide activation based on cDNA-expressed activities and liver microsomal P-450 profiles. Drug Metab Dispos 27:655-666. Sehn LH (2010) A decade of R-CHOP. Blood 116:2000-2001. Siegel RL, Miller KD, and Jemal A (2017) Cancer Statistics, 2017. CA Cancer J Clin 67:7-30. Solomon J, Alexander MJ, and Steinfeld JL (1963) Cyclophosphamide. A clinical study. JAMA 183:165-170. Sueyoshi T, Kawamoto T, Zelko I, Honkakoski P, and Negishi M (1999) The repressed nuclear receptor CAR responds to phenobarbital in activating the human CYP2B6 gene. J Biol Chem 274:6043-6046. Wang LF, Su SW, Wang L, Zhang GQ, Zhang R, Niu YJ, Guo YS, Li CY, Jiang WB, Liu Y, and Guo HC (2015) Tert-butylhydroquinone ameliorates doxorubicin-induced cardiotoxicity by activating Nrf2 and inducing the expression of its target genes. Am J Transl Res 7:1724-1735. Yu L and Waxman DJ (1996) Role of cytochrome P450 in oxazaphosphorine metabolism. Deactivation via N-dechloroethylation and activation via 4-hydroxylation catalyzed by distinct subsets of rat liver cytochromes P450. Drug Metab Dispos 24:1254-1262. Zhou S, Palmeira CM, and Wallace KB (2001) Doxorubicin-induced persistent oxidative stress to cardiac myocytes. Toxicol Lett 121:151-157.

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Appendix A: Transporter-Mediated Disposition of Opioids: Implications for Clinical Drug Interactions

A.1 Introduction

Chronic pain is reported to affect more than 116 million Americans and opioids are the standard analgesics of choice for the treatment of chronic and severe pain, as well as cancer-pain management (Pizzo and Clark, 2012; Steglitz et al., 2012). In addition to their clinical applications in pain management, opioids have a long history of illicit abuse. Opioids comprise a large family of both naturally occurring and synthetic molecules that are classified by their interactions with the three opioid receptors: µ, δ, and κ (Inturrisi, 2002). µ-opioid receptor (MOR) agonists are known to produce the euphoric and analgesic effects most commonly associated with physical dependence and abuse (Mercer and Coop, 2011).

The United States is presently facing a severe epidemic of drug overdose deaths which appears to be driven primarily by opioid abuse (Gilson and Kreis, 2009; Manchikanti et al., 2012; Beauchamp et al., 2014; Fischer et al., 2014). The number of deaths related to opioid overdose has more than quadrupled since 1999, directly correlating with the dramatic increase in the sale of opioid pharmaceuticals (Manchikanti et al., 2012; Jones et al., 2013; Volkow et al., 2014). In 2010 an estimated 46 Americans were dying each day from opioid overdoses while 210 million opioid prescriptions were dispensed by U.S. retail pharmacies (Jones et al., 2013; (NIDA), 2014). Further, in 2011 alone, over 190,000 emergency department visits were believed to be due to adverse events resulting from narcotic pain relieving medications, and 400,000 emergency department visits were

144 related to opioid analgesic abuse ((SAMHSA), 2013b). Greater measures are therefore urgently needed to increase the drug safety of opioids, including greater understanding of their pharmacokinetic mechanisms and potential drug-drug interactions (DDIs)

Although not as well recognized as metabolizing enzymes, membrane drug transporters are being increasingly acknowledged as important determinants of drug pharmacokinetics (PK), pharmacodynamics (PD) and DDIs (Zhang, 2010). Drug transporters are broadly categorized in two major classes of efflux and uptake transporters (Ho and Kim, 2005). The 2012 FDA Guidance for Industry on drug interaction studies outlined 7 transporters with which a developing drug should be evaluated for interactions with. These transporters of interest are P-gp, Breast Cancer

Resistant Protein (BCRP), the hepatic uptake Organic Anion Transporting Polypeptides (OATP)

1B1 and 1B3, and the renal Organic Anion Transporter (OAT) 1 and 3, and Organic Cation

Transporter 2 (OCT2) ((FDA), 2012). The antidiarrheal loperamide is a prime example of the impact drug transporters may have on the PK/PD opioids, whereby it exhibits minimal central nervous system (CNS) activity due to being a substrate of P-glycoprotein (P-gp), an efflux transporter with broad substrate specificity, at the blood-brain barrier (BBB) (Vandenbossche et al., 2010). Clinically significant transporter-mediated DDIs have already been demonstrated for a number of commonly used medications including a number of statins, cimetidine, digoxin, metformin, and methotrexate, to name a few ((FDA), 2012), and that list is likely to expand.

Thus, the role of drug transporters in drug PK/PD, toxicity, human disease, and inter-individual variability in drug response is an emerging field of interest, however their contributions to the disposition of opioids remain largely unexplored (Ho and Kim, 2005). A greater understanding of these drug transporters may provide a mechanistic approach towards predicting DDIs and

145 improving their drug safety and efficacy. This information could also assist in providing more personalized opioid pain management for patients based on their disease state, concomitant medications, and even transporter genotypes. Furthermore, comprehensive drug transporter knowledge could assist in identifying potential targets for addiction therapies as well as educating patients and healthcare professions about dangerous drug combinations. The purpose of this review article is to compile current literature available on the drug transporters of the major opioids of abuse and predict potential clinical implications that may arise from their transporter interactions.

This article will provide a novel approach in evaluating potential DDIs with opioids, as well as highlight areas for future research.

A.2 Opioids of Abuse

A.2.1 Morphine

Morphine is considered the prototypical opioid and gold standard to which other strong analgesics are compared (Katzung, 2011). The major metabolite of morphine is morphine-3-glucoronide

(M3G), which has no analgesic properties but elicits neuro-excitatory effects. Approximately 10% of morphine is metabolized to morphine-6-glucoronide (M6G) which has much greater analgesic effects than its parent compound. Although markedly more potent than morphine at the µ-opioid receptor, M6G has exhibits poor blood-brain barrier (BBB) permeability (De Gregori et al., 2012).

An estimated 4 million morphine containing prescriptions were dispensed in 2009 ((FDA), 2011).

In 2011 nearly 35,000 ED visits were reportedly due to abuse of morphine products, representing an over 100% increase from 2004 ((SAMHSA), 2013b).

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A number of in vitro studies have demonstrated that morphine (Callaghan and Riordan, 1993;

Schinkel et al., 1995; Letrent et al., 1999; Crowe, 2002; Wandel et al., 2002) and M6G (Huwyler et al., 1996) are likely P-gp substrates. Conversely, Tournier et al., suggested morphine is neither a P-gp or BCRP substrate (Tournier et al., 2010), while Wandel et al., suggested that neither M3G or M6G are P-gp substrates (Wandel et al., 2002). Both Morphine and codeine were shown to inhibit OCT-1 mediated uptake in HEK293 cells overexpressing OCT1 (Ahlin et al., 2008), while morphine, but not codeine, was shown to be an OCT1 substrate in this same model cell line as well as in primary hepatocytes. Further, a number of drugs commonly administered with morphine that are cationic at physiological pH, such as irinotecan, verapamil, and ondansetron, were shown to inhibit morphine’s OCT-1 mediated uptake in a concentration-dependent manner (Tzvetkov et al.,

2013). In vitro studies have also suggested that M6G and M3G are both MRP2 and MRP3 substrates in hepatocytes (Zelcer et al., 2005; van de Wetering et al., 2007).

A host of in vivo studies have demonstrated morphine to be a likely P-gp substrate. P-gp inhibitors were shown to increase CNS concentrations and antinocipetive effects of morphine (Letrent et al.,

1998; Aquilante et al., 2000; Fujita-Hamabe et al., 2012). Similarly, P-gp knock-out mice administered morphine had significantly increased analgesia (Thompson et al., 2000; Zong and

Pollack, 2000) and brain distribution (Schinkel et al., 1995; Xie et al., 1999; Dagenais et al., 2001).

A negative correlation was also found between P-gp expression levels in the brains of rats and morphine-induced analgesia (Hamabe et al., 2007). Correspondingly, P-gp was found to be upregulated in the brains of morphine tolerant rats (Aquilante et al., 2000) and the down-regulation of rat Pgp1 with antisense prevented morphine tolerance development and reduced morphine’s brain-to-blood efflux (King et al., 2001). Morphine was also shown to inhibit the proton-coupled antiporter transport of clonidine at the BBB of mice (Andre et al., 2009).

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Rats administered M6G intravenously along with a known P-gp inhibitor were found to have significantly increased M6G antinociception and a 3-fold increase in CNS M6G relative to those not administered the inhibitor (Lotsch et al., 2002). However, Bourasset et al., demonstrated M6G to be neither a P-gp or Mrp1 substrate, but rather a GLUT1 and/or possibly a weak Oatp2-like substrate at the BBB in mice (Bourasset et al., 2003). Other knockout mice studies have suggested that Mrp2 and Mrp3 play important roles in the hepatic excretion of M3G and M6G and modulate the antinociception of M6G (Zelcer et al., 2005; van de Wetering et al., 2007). Another group found that probenecid decreased the systemic elimination but had no effect on the BBB transport of M6G in rats, suggesting M6G may be a substrate of a probenecid-sensitive transporter (OAT) outside the CNS (Tunblad et al., 2005).

A number of clinical studies have supported the hypothesis that morphine and its glucoronide metabolites are P-gp substrates. One case report noted that concomitant administration of known

P-gp inducer rifampin with morphine resulted in noticeably decreased morphine blood levels

(Fudin et al., 2012). Patients deemed to have P-gp positive tumors from immunohistochemistry

(IHC) results were found to require higher doses of morphine for pain control, relative to those with P-gp negative tumors (Wang et al., 2012). However, another study investigating the CNS effects of morphine coadministered with a known P-gp inhibitor found no clinically significant differences relative to controls. The plasma pharmacokinetics of morphine and M6G were unaffected by P-gp inhibition, while the area-under-the-curve (AUC) and half-life (t1/2) of M3G were significantly increased (Drewe et al., 2000). Concomitant use of known P-gp inhibitor cyclosporine with morphine in healthy volunteers resulted in significantly increased morphineAUC relative to controls, though the authors proposed this may not have any major clinical effects

(Meissner et al., 2013).

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ABCB1, the gene that encodes P-gp, has been reported to have certain polymorphisms which may predispose patients to morphine-induced adverse events (Fujita et al., 2010) and variable pain relief

(Campa et al., 2008). However, Coulbault et al., demonstrated that ABCB1 polymorphisms appeared to have no association with morphine doses post-operatively, and only borderline association (p=0.07) with morphine-induced side effects (Coulbault et al., 2006). In line with the group’s in vitro findings, Tzvetkov et al., demonstrated that following oral administration of codeine, the AUC of morphine, but not codeine, was greatly affected by OCT1 polymorphisms.

Patients homozygous for OCT1 loss-of-function polymorphisms were found to have 1.5 fold higher morphineAUC relative to those heterozygous and homozygous for functional OCT1 alleles

(Tzvetkov et al., 2013). Similarly, a clinical study of children undergoing adenotonsillectomy found that those homozygous for OCT1 loss-of-function variants had significantly lower (20%) morphine clearances than wild-types or those heterozygous for such variants (Fukuda et al., 2013).

Despite numerous studies there currently appears to be no definitive consensus regarding the role of P-gp in the disposition of morphine or its glucoronidated metabolites. Preclinical evidence mostly suggests morphine is a likely P-gp substrate, while clinical data appears more divided. One transporter of increasing interest in morphine’s disposition, particularly its hepatic efflux, is OCT1.

In vitro and clinical data are in agreement that OCT1 plays an important role in the pharmacokinetics of morphine. These findings may imply a host of potential transporter-based clinical DDIs with other OCT1 substrates and warrants further investigation (Table 1). MRP2 and

MRP3 may be important transporters in the hepatic efflux of M3G and M6G and could also be sources of serious transporter-mediated DDIs. The clinical utility of the highly potent analgesic

M6G is limited by its poor BBB permeability, and pre-clinical evidence appears conflicting on which transporter(s) may be involved in its efflux from the BBB. Further investigation into these

149 transport mechanisms is essential for any further clinical development of this potentially powerful analgesic. Given the frequent clinical use of morphine, a greater understanding of its transport mechanisms and that of its metabolites is essential for improving clinical outcomes.

A.2.2 Codeine

Like morphine, codeine is a naturally occurring opiate found in Papaver somniferum. Codeine is the pro-drug of morphine and considered the gold standard of cough suppressants (Bolser and

Davenport, 2007). Codeine is primarily metabolized to codeine 6-glucoronide with less than 10% of codeine being metabolized to morphine (Chen et al., 1991). Although not among the most frequently abused opioids, codeine overdose remains a serious public health concern. In 2011 an estimated 1.7 million codeine containing prescriptions were dispensed (Informatics, 2012), and the abuse of codeine products accounted for nearly 10,000 ED visits. In 2009 adverse reactions to codeine containing pharmaceuticals accounted for over 18,000 ED visits ((SAMHSA), 2013b).

Greater understanding of the drug transporters involved in the disposition of codeine may aid in improving the overall safety of this commonly used opioid.

Codeine was shown to inhibit OCT-1 mediated uptake in HEK293 cells over-expressing OCT1

(Ahlin et al., 2008). However, another in vitro study found that codeine uptake was not affected by OCT1 overexpression, but rather that codeine exhibits a high level of transporter-independent cell permeability relative to morphine (Tzvetkov et al., 2013). In addition, codeine uptake in intestinal and brain endothelial cells was found to be pH dependent and possibly mediated through a yet fully identified proton coupled anti-porter (Fischer et al., 2010). In vivo evidence from an in situ mouse brain perfusion study supported this finding, as codeine was found to significantly

150 inhibit the BBB transport of nicotine, which may also be a substrate of this antiporter (Cisternino et al., 2013).

From the limited information available, codeine appears to undergo a large degree of passive diffusion and is not a substrate of the same transporters as morphine. There appears to be contrasting evidence on the role of OCT-1 in codeine’s disposition. In vitro and in vivo evidence suggest that codeine may be a substrate of a yet identified pH dependent proton-coupled antiporter at the BBB. This transporter appears to share similarities with the clonidine and pyrilamine proton- coupled antiporters previously described, and could be a source of clinical DDIs warranting further investigation (Okura et al., 2008; Andre et al., 2009; Nakazawa et al., 2010).

A.2.3 Diacetylmorphine

Diacetylmorphine (heroin) was originally synthesized from morphine in the early 20th century as a classical analgesic. Today heroin is a schedule I controlled substance and considered one of the most addictive and problematic drugs of abuse ((UNODC), 2013; Murphy et al., 2014). Despite its highly addictive properties, heroin exhibits only low-binding affinity and efficacy at µ-opioid receptors (Gottas et al., 2013). Thus, it has been proposed that heroin behaves primarily as highly lipophilic pro-drug, able to cross the BBB (Oldendorf et al., 1972) and is subsequently converted to active metabolites with high µ-opioid receptor affinities (Gottas et al., 2012). Heroin is rapidly deacetylated to its more active metabolites 6-monoacetylmorphine (6-MAM) and then morphine within 10 minutes of administration (Hutchinson and Somogyi, 2002; Rook et al., 2006). There were an estimated 12-14 million heroin users world-wide in 2009 ((UNODC), 2013). Addiction to heroin has shown an alarming increase in the US with an estimated 500,000 addicts in 2009

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((SAMHSA), 2013a). Between 2002 and 2010, the number of reported users grew by over 50%, and in 2011 over 4.2 million Americans 12 years of age and over had tried heroin, with an estimated 23% of users becoming dependent ((NIDA), 2013). Furthermore, over 258,000 ED visits were reported in 2011 due to heroin use, representing 20.6% of all ED visits due to illicit drug use

((SAMHSA), 2013b).

Presently there is very limited research into the drug transporters which interact with diacetylmorphine or 6-MAM. One in situ mouse brain perfusion study concluded that diacetylmorphine inhibited the proton-coupled antiporter transport of clonidine (Andre et al.,

2009). Another animal study found that in the post-natal development of mice, the BBB penetration of morphine decreased while that of diacetylmorphine did not, indicating a possible greater passive diffusion capacity of diactylemorphine (Loh et al., 1971). Although morphine is often assumed to be the active metabolite responsible for heroin’s pharmacodynamic effects, a number of animal studies have proposed that in fact 6-MAM may be more important (Andersen et al., 2009; Gottas et al., 2014).

From the limited research available, diactylemorphine appears to be highly lipophilic and able to cross the BBB rapidly. Once it has crossed the BBB it may be metabolized to more active opioids, possibly behaving as a lipophilic pro-drug. More research into the transporters involved in heroin and its active metabolites, particularly 6-MAM, are necessary to develop a clearer understanding of heroin’s potential DDIs as well as in developing possible interventions into heroin addiction and overdoses.

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A.2.4 Oxycodone

Oxycodone is among the most frequently prescribed opioids in the US ((DEA), 2014b). Orally administered oxycodone has also been shown to have the highest abuse liability of the commonly prescribed opioids (Wightman et al., 2012). Though first synthesized from a minor component of opium (thebaine) in 1917, full investigation of oxycodone’s pharmacological properties has only occurred recently (Olkkola et al., 2013). Structurally similar to codeine, oxycodone shares a similar clinical profile to morphine, though estimated to exhibit 5-40 fold lower affinity for the µ-opioid receptor (Lalovic et al., 2006; Olkkola et al., 2013). Nearly 60 million oxycodone prescriptions were dispensed in 2013 in the U.S. and the 2014 production quota is nearly 150,000 kg ((DEA),

2014b). An estimated 16 million Americans used oxycodone for non-medical purpose in 2012. In

2011 over 150,000 ED visits and 43 deaths were reported due to oxycodone abuse, 65,000 ED visits were due to adverse reactions to oxycodone-containing products, and nearly 14,000 ED visits were due to oxycodone-related suicide attempts ((NSDUH), 2006; (SAMHSA), 2013b).

In vitro permeability studies have demonstrated that oxycodone has a high passive permeability rate, greater than the suggested cut-off value for CNS penetration (Mahar Doan et al., 2002).

Oxycodone was shown to stimulate P-gp ATPase activity in a concentration dependent manner and pre-incubation with the P-gp inhibitor verapamil significantly reduced oxycodone secretory transport in Caco-2 monolayer studies (Hassan et al., 2007). Abcg2 (BCRP) ATPase assay results suggest oxycodone is also an Abcg2 substrate at high concentrations (>500µM) (Hassan et al.,

2010).

Other in vitro transport studies in rat brain capillary endothelial cells demonstrated that oxycodone shares a pH and energy dependent antiporter with radiolabeled pyrilamine, and that the BBB

153 uptake of oxycodone was significantly inhibited in the presence of quinidine, verapamil, and amantadine (Okura et al., 2008). This same transporter was later shown to be inhibited at supra- therapeutic concentrations by a number of antidepressants such as amitriptyline and ketamine

(Nakazawa et al., 2010). Transport studies in different cell lines have shown that oxycodone and diphenhydramine competitively inhibited the uptake of one another (Sadiq et al., 2011; Shimomura et al., 2013). These results suggest the two share a common proton-coupled antiporter at the BBB, possibly similar to ones involved in the transport of MDMA (Kuwayama et al., 2008), clonidine

(Andre et al., 2009; Sadiq et al., 2011), and a number of other drugs.

A sheep study showed that oxycodone has 7-fold higher BBB permeability than morphine and a greater cerebral volume of distribution (Villesen et al., 2006). Similarly, a rat study demonstrated that unbound oxycodone had a much greater influx rate across the BBB and 6 times the brain concentration relative to morphine, suggesting an active uptake transporter is likely involved in oxycodone’s BBB disposition (Bostrom et al., 2005). Another study by the same group demonstrated that rats pre-treated with a known P-gp inhibitor had no difference in their plasma pharmacokinetics or brain concentrations of oxycodone relative to controls, suggesting oxycodone is likely not a P-gp substrate (Bostrom et al., 2006). Conversely, in another study, brain levels of oxycodone were not detectable in wild-type mice, while mdr1a knock-out mice averaged over 100 ng/ml. Oxycodone treated rats also demonstrated an up to 4-fold increase in protein levels of P-gp in various tissues, corresponding with decreased tissue concentrations of the known P-gp substrate paclitaxel (Hassan et al., 2007). Nakazawa et al., demonstrated in another mouse study that coadministration of likely P-gp substrate amitriptyline at clinical doses with oxycodone increased anti-nociception without affecting the brain pharmacokinetics of oxycodone (Nakazawa et al.,

2010). An in situ rat brain perfusion study supported in vitro findings whereby the brain uptake of

154 oxycodone was inhibited by pyrilamine, suggesting oxycodone shares the same proton-coupled antiporter at the BBB (Okura et al., 2008). Yet another rat study demonstrated that 8 days of repeated oxycodone administration up-regulated the expression of Abcg2 based on microarray data, qPCR, and western blot analyses, and that this up-regulation resulted in decreased brain accumulation of known Abcg2 ABCG2 substrate mitoxantrone (Hassan et al., 2010).

In a clinical study of 33 participants exposed to experimental pain, a strong association was found between carriers of variant alleles C3435T and G2677T/A in the ABCB1 gene and fewer adverse drug effects following oxycodone administration(Zwisler et al., 2010). Conversely, another clinical study of 76 mother-infant breast feeding pairs found mothers carrying at least one copy of the ABCB1 2677 T variant had an increased risk of experiencing oxycodone induced sedation

(Lam et al., 2013). Yet another clinical study found that cancer patients with the C3435T polymorphism of ABCB1 had little effect on the plasma disposition of oxycodone (Naito et al.,

2011). The clinical implications of these variant alleles on P-gp function do not appear to be presently well understood.

In conclusion, the role P-gp in the transport of oxycodone is appears to be highly controversial

(Olkkola et al., 2013). In vitro and in vivo studies suggest other transporters such as BCRP and the yet identified proton-coupled antiporters of pyrilamine and diphenhydramine may have important roles in oxycodone’s disposition. The emerging role of proton-coupled antiporters in the disposition of oxycodone warrants further investigation, as there appears a number of potentially harmful DDIs that may result from concomitant use of common substrates/inhibitors (Table 1).

Additional research, especially clinical investigation, is needed to clarify these transporter mechanisms. Considering oxycodone is often prescribed in cancer-pain management, the role of

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P-gp and BCRP in its disposition are of particular interest. The number of adverse events from oxycodone-containing pharmaceuticals is also alarming. Greater understanding of the mediators of oxycodone transport is necessary for elucidating the pathophysiology behind these reactions and ensuring the most safe and efficacious use of oxycodone-containing products.

A.2.5 Oxymorphone

Oxymorphone is an active primary metabolite of oxycodone that has been available on the US market since 1959 ((DEA), 2013e). It is estimated to have a 10-45 fold greater affinity for the µ- opioid receptor than oxycodone (Peckham and Traynor, 2006) and to be 9-times more potent than morphine in producing analgesia in humans (Beaver et al., 1977). Oxymorphone is believed to exert its analgesic effects through both µ and δ opioid receptors (Ananthan et al., 2004). Over 1 million prescriptions for oxymorphone were written in 2012 and over 12,000 reported ED visits were due to oxymorphone abuse – more than twice the number in 2010 (Informatics, 2012; (DEA),

2013e). Thus, both oxycodone and oxymorphone are highly addictive substances showing alarming increases in abuse.

Despite the prevalence of oxymorphone use and adverse events, there appears to be limited investigation into its drug transporters at the current time. One in vitro study demonstrated that oxymorphone does not significantly stimulate P-gp ATPase activity (Hassan et al., 2009), while a rat study demonstrated active transport is involved in the BBB uptake of oxymorphone through an unidentified transporter (Sadiq et al., 2013). More research is needed into the drug transporters of this highly potent opioid.

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A.2.6 Fentanyl

Fentanyl is a highly potent synthetic opioid analgesic that has been available on the US market since the 1960s. Estimated to be more than 100 times more potent than morphine, fentanyl is highly lipophilic and can rapidly cross the BBB (Peng and Sandler, 1999). Fentanyl is a Schedule II controlled substance and is available in a number of formulations including lozenges or “lollipops”

(Actiq), buccal tablets (Fentora), transdermal patches (Duragesic), and injectable solutions.

Reports of fentanyl abuse date back to the 1970s. In 2012 nearly 7 million prescriptions were written for fentanyl, and 3.4 million were written in the first half of 2013. The CDC reported over

1,000 deaths from non-pharmaceutical fentanyl-related abuse between 2005 and 2007 ((DEA),

2013b)[178]. In 2011 over 20,000 ED visits were reportedly due to fentanyl abuse in the US, more than twice the amount reported in 2004 ((SAMHSA), 2013b). Fentanyl is thus a highly addictive and potentially dangerous substance with increasing rates of abuse.

Pulmonary endothelial transport studies demonstrated that fentanyl likely undergoes both passive and saturable active transport during pulmonary uptake (Waters et al., 1999). To investigate the active transport mechanisms further, another uptake study using radiolabeled fentanyl and primary cultured bovine brain microvessel endothelial cell (BBMEC) monolayers was conducted. Results indicated that fentanyl is a likely P-gp substrate, but that a yet identified fentanyl uptake transporter has a prominent role in fentanyl’s BBB uptake (Henthorn et al., 1999). Fentanyl was also shown to significantly increase P-gp ATPase activity in mouse brain capillary endothelial cells (Hamabe et al., 2006). However, results from another study demonstrated that fentanyl does not behave as a P-gp substrate in LLC-PKI monolayers but does inhibit P-gp mediated transporter of digoxin in

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Caco-2 cells (Wandel et al., 2002). In vitro transport studies in HEK293 cells overexpressing

OATP1B1 found no difference in fentanyl uptake relative to controls, suggesting it is not an

OATP1B1 substrate (Ziesenitz et al., 2013).

Pretreatment of mice with the P-gp substrate and inhibitor cyclosporine A was found to significantly increase the analgesic effects of fentanyl, without affecting its plasma pharmacokinetics (Cirella et al., 1987). Similarly, another mice study demonstrated that coadministration of fentanyl with a cyclosporine A analog increased sensitivity to fentanyl (Mayer et al., 1997). P-gp deficient mice were found to have significantly increased fentanyl antinociceptive and analgesic effects (Thompson et al., 2000; Hamabe et al., 2006), as well as significantly increased (24%) fentanyl brain uptake (Dagenais et al., 2004), relative to wild-type mice. The coadministration of known P-gp substrate verapamil with fentanyl in rats had only modest effects on fentanyl pharmacokinetics. However, the brain/plasma and lung/plasma ratios of fentanyl in rats were reduced 4-fold and 6-fold, respectively, when co-administered with known

Oatp substrates pravastatin and naloxone (Elkiweri et al., 2009).

Two randomized, double-blind studies in healthy volunteers found that pre-treatment with known

P-gp inhibitor quinidine resulted in increased oral fentanyl plasma concentrations, but did not affect fentanyl pharmacodynamics. These results suggest quinidine may inhibit P-gp efflux during intestinal absorption but does not have much effect on fentanyl’s BBB disposition (Kharasch et al., 2004a). Another clinical study of 126 patients undergoing spinal anesthesia found certain

ABCB1 genotypes were linked with increased fentanyl-induced respiratory depression. Patients with the genotypes 1236TT, 2677TT, and 3435TT were found to have early and profound respiratory depression (65-73% of initial respiratory rate) following intravenous fentanyl

158 administration, suggesting ABCB1 polymorphisms may have important clinical implications in fentanyl safety (Park et al., 2007). However, another clinical study of 83 patients also undergoing intravenous fentanyl treatment for spinal anesthesia concluded that ABCB1 polymorphisms had no effect on fentanyl-induced sedation or respiratory depression (Kesimci et al., 2012). ABCB1 and ABCG2 polymorphisms were also found to have no relation with the clinical manifestations of fentanyl-induced delirium or coma (Skrobik et al., 2013). One randomized crossover study found no significant differences in fentanyl pharmacokinetics between carriers of SLCO1B1*1a or SLCO1B1*15 (OATP1B1) haplotypes. Further, coadministration with known OATP1B1 inhibitor rifampicin also had no effect on fentanyl pharmacokinetics in either haplotype, supporting the observation that fentanyl is likely not an OATP1B1 substrate (Ziesenitz et al.,

2013).

In vitro study results appear to conflict on the role of P-gp in fentanyl’s disposition. A number of in vivo studies have concluded that fentanyl is a P-gp substrate while one suggested it is rather an

Oatp substrate (Elkiweri et al., 2009). Clinical results are not in consensus either, with some suggesting P-gp function has a significant role in the pharmacodynamics of fentanyl (Kharasch et al., 2004a; Park et al., 2007), while others suggest otherwise (Kesimci et al., 2012; Skrobik et al.,

2013). Clinical evidence also suggests fentanyl is not an OATP substrate (Ziesenitz et al., 2013).

In conclusion, there appears to be some controversy over the role of P-gp in fentanyl’s transport.

Further studies into the role of P-gp and other transporters in the disposition of fentanyl are needed to clarify this matter.

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A.2.7 Methadone

Methadone is the oldest of the synthetic opioids and has been used for decades in the detoxification and treatment of opioid addiction (Tetrault et al., 2013; (DEA), 2014a). Its demonstrated clinical efficacy and cost-effectiveness have made methadone an increasingly prescribed opioid, particularly in treating moderate-to-severe pain in recent years (Nicholson, 2007; (DEA), 2014a).

Methadone consists of a racemic mix of R- and S-methadone (Rainey et al., 2002), though the R- isomer is believed to account for its opioid effects (Kreek et al., 2010). Methadone is also lipophilic, highly protein bound (85%), and known for its relatively long half-life (Armstrong et al., 2009) and often unpredictable pharmacokinetics (McCance-Katz and Mandell, 2010).

Methadone has unique analgesic properties in both its full µ-opioid receptor agonism and NMDA- receptor antagonism.

The drug raised concerns after reports of patients experiencing greater incidences of QT prolongation and Torsades de Pointes (Justo, 2006; Ehret et al., 2007). A sharp increase in methadone related deaths and poisonings led the FDA to issue a black box warning and public health advisory recommending methadone doses in pain relief be carefully chosen and monitored by the prescriber. As well as being used in opioid detoxification, methadone has an extensive history of abuse and dependence. According to the 2012 NSDUH, nearly 2.5 million Americans aged 12 and over had used methadone for non-medical purposes in their lifetime ((SAMHSA),

2013a). In 2011 nearly 67,000 ED visits were due to non-medical methadone use, representing an

82% increase from 2004 ((SAMHSA), 2013b). The American Association for Poison Control

Centers (AAPCC) also reported 51 methadone related deaths in 2012 (Bronstein et al., 2012). The unpredictable pharmacokinetics and potentially fatal consequences of methadone use has led to a number of studies investigating its transport mechanisms.

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Methadone was found to increase the accumulation of known P-gp substrate vinblastine in multidrug resistant Chinese hamster ovary cells (B30) (Callaghan and Riordan, 1993). An in vitro gut sac model confirmed that methadone was a P-gp substrate and that its transport was increased in the presence of P-gp inhibitors verapamil and quinidine (Bouer et al., 1999). Caco-2 monolayer transport of P-gp substrate rhodamine 123 was found to be inhibited by methadone at intraluminal concentrations (Stormer et al., 2001), and methadone was also found to increase rhodamine123 accumulation in human trophoblasts (Beghin et al., 2010). The intra/extra cellular ratio of methadone was significantly decreased in human ABCB1 transfected cells relative to controls

(Crettol et al., 2007). An in vitro model of transplacental transport found the P-gp inhibitor

GF120918 increased the transfer of methadone by 30%, and that uptake of methadone in the Be-

Wo cell line was increased in the presence of P-gp inhibitor cyclosporine A (Nanovskaya et al.,

2005). The same group demonstrated that methadone transfer was significantly higher in the fetal to maternal direction, likely due to the unidirectional activity of P-gp (Nekhayeva et al., 2005).

Methadone was also shown to inhibit the transfer of paclitaxel in human placental inside-out vesicles, demonstrating a greater affinity for P-gp than the classic inhibitor verapamil (Hemauer et al., 2009). Similarly, methadone was shown to stimulate P-gp activity at higher concentrations, and Caco-2 monolayer transport studies demonstrated that verapamil and GF120918 significantly reduced methadone efflux (Hassan et al., 2009). Methadone was also found to significantly inhibit

P-gp in HEK 293 cells transfected with hMDR1, and demonstrated P-gp mediated transport in hMDR-MDCKII bidirectional transport studies (Tournier et al., 2010). Equine intestinal mucosa transport studies also indicated that the intestinal transport of methadone is likely mediated by P- gp(Linardi et al., 2013). A more recent in vitro study utilizing cells stably transfected with various genotypes of ABCB1 (P-gp) found that methadone most potently inhibited wild-type P-gp, while

161 the genotypes 1236T-2677T-3435T and 1236T-2677A-3435T exhibited much less inhibition. The study also confirmed that methadone stimulated P-gp ATPase activity and inhibited verapamil

(Hung et al., 2013).

Methadone-induced analgesia was higher in P-gp knock-out mice relative to wild types, and pretreatment with P-gp inhibitor cyclosporine markedly increased the analgesic effects of methadone in wild-type mice, but not in P-gp knockout mice (Thompson et al., 2000). Brain concentrations of both R- and S-methadone were found to be 15 to 23-fold higher in P-gp knockout mice relative to wild-types (Wang et al., 2004) and P-gp knock-out mice were shown to have a 2.6-fold increase in brain uptake of methadone relative to wild types (Dagenais et al., 2004).

Similarly, P-gp knock-out mice were found to have significantly increased methadone brain uptake and methadone-induced antinociceptive effects (Hassan et al., 2009). Exposure of P-gp inhibitor rifampin to transgenic mice expressing human pregnane X receptor (hPXR) resulted in increased expression of P-gp in the brain endothelium and correspondingly attenuated methadone antinociceptive effects by ~70% (Bauer et al., 2006). Pre-treatment of rats with the P-gp inhibitor valspodar was found to increase the brain concentrations of methadone 6-fold and 4-fold following oral and intravenous administration relative to controls, respectively (Rodriguez et al., 2004).

Valspodar was also found to increase the bioavailability and analgesic effects of methadone in rats

(Ortega et al., 2007). Conversely, the pharmacokinetics of methadone in dogs was unaffected by

P-gp inhibition (Kukanich et al., 2005).

Extensive clinical research has been performed aiming to elucidate the role of P-gp in the pharmacokinetics (PK) and pharmacodynamics (PD) of methadone with often inconsistent results.

There have been case reports of DDIs between P-gp inducers rifampicin (Kreek et al., 1976; Niemi

162 et al., 2003) and St John’s Wort (Eich-Hochli et al., 2003) with methadone, resulting in increased opioid withdrawal symptoms. A double-blind, placebo controlled crossover study in healthy volunteers showed that the P-gp inhibitor quinidine did not alter the PK or PD of intravenous methadone, but did increase plasma concentrations following oral methadone ingestion. These results may suggest that P-gp has a large effect on intestinal methadone absorption but not its BBB transport (Kharasch et al., 2004a). However, a number of consequent clinical studies demonstrated that methadone bioavailability was largely unchanged in the presence of a number of antiretrovirals believed to inhibit (ritonavir, indinavir, ritonavir-lopinavir) and induce (nelfinavir, and efavirenz) P-gp activity. Together these results suggest that P-gp may not play a prominent role in intestinal methadone absorption or in the mechanism(s) behind well-noted methadone- antiretroviral drug interactions (Kharasch et al., 2004a; Kharasch et al., 2008; Kharasch et al.,

2009; Kharasch et al., 2012; Kharasch and Stubbert, 2013).

A number of clinical studies have investigated the potential role of ABCB1 polymorphisms on methadone pharmacokinetics. An Australian study comparing opioid-dependent and non- dependent patients found ABCB1 polymorphisms had no influence on the development of opioid dependence, but may have an influence on daily methadone dose requirements. Patients carrying

2 copies of the wild-type haplotype (AGCGC) were found to require significantly higher maintenance methadone doses relative to those carrying 1 or 0 copies. Additionally, carriers of the

AGCTT haplotype (SNPs at 2677 and 3435 loci) were found to require significantly lower

(approximately 50%) daily doses of methadone (Coller et al., 2006). However, the same group later performed an expanded study of methadone maintenance therapy (MMT) patients (doses ranging from 15-300 mg/day) and found no significant associations between any one ABCB1 haplotype and methadone dosing. When controlling for ORMP1 (encodes µ-opioid receptor)

163 variation, AGCTT carriers had significantly lower methadone doses and trough concentrations

(Ctrough) relative to wild-type subjects. These results suggest a number of genetic factors besides

ABCB1 are likely to contribute towards the PK/PD of methadone (Barratt et al., 2012).

The ABCB1 polymorphisms 2677G>T and 3435C>T were found to have no influence on the plasma pharmacokinetics of levomethadone following a single dose (Lotsch et al., 2006). The same 2 polymorphisms as well as the 61A>G polymorphism were associated with lower methadone Ctrough, but had no effect on peak concentrations in another study of patients undergoing

MMT (Crettol et al., 2006). A follow up study found no significant associations between ABCB1 haplotypes and methadone dose requirements (Crettol et al., 2008). Similarly, a Spanish study of opioid dependent patients on methadone maintenance found no relationships between ABCB1 allelic variations and the use of illicit opioid substances or methadone dosages (Fonseca et al.,

2011), and a Danish postmortem study of drug users found no associations between ABCB1 genotypes and methadone concentrations (Buchard et al., 2010).

Alternatively, significant associations were found between certain ABCB1 polymorphisms and methadone maintenance dose requirements in a clinical study of formerly severe heroin-dependent

Israeli patients. Patients homozygous for the ‘T’ allele in SNP 1236C>T and carriers of the 3-locus genotype pattern of ‘TT-TT-TT’ (3435C > T, 2677G > T and 1236C > T polymorphisms) were estimated to have an approximately 7-fold and 5-fold increased chance of requiring higher (>150 mg/day) maintenance methadone doses relative to non-carriers, respectively (Levran et al., 2008).

A Swiss study of 14 MMT subjects found the ABCB1 genotypes 3435 TT, CT, and CC resulted in 3%, 23% and 33% increases in (R)-methadone concentration/dose ratios following administration of P-gp substrate quetiapine, respectively (Uehlinger et al., 2007). Carriers of the

164 variant ABCB1 3435C>T were found to require higher doses of methadone than non-carriers among a population of Han Chinese patients (Hung et al., 2011), and a pilot study of 178

Taiwanese patients in a MMT program found the ABCB1 2677T allele had positive effects on methadone plasma concentration (Lee et al., 2013).

In conclusion, in vitro and in vivo studies appear to overwhelmingly suggest that methadone is a

P-gp substrate, while clinical studies investigating the effects of ABCB1 polymorphisms are severely divided on the matter. Some clinical studies have suggested there is a likely relationship

(Coller et al., 2006; Uehlinger et al., 2007; Levran et al., 2008; Hung et al., 2011; Lee et al., 2013), while others have suggested there is likely not (Lotsch et al., 2006; Crettol et al., 2008; Buchard et al., 2010; Fonseca et al., 2011), and still others propose that ABCB1 polymorphisms are only one of a number of interacting pharmacogenetic determinants influencing methadone pharmacokinetics (Barratt et al., 2012). Despite extensive research, there remains considerable controversy over the functional consequences of various ABCB1 polymorphisms (Kim et al.,

2001; Kroetz et al., 2003; Marzolini et al., 2004; Takane et al., 2004). There currently does not appear to be any investigations (preclinical or clinical) into the role other transporters besides P- gp may play in the disposition of methadone. Thus, methadone is a potentially highly dangerous drug with large inter-patient variability, and further research into the transporter(s) involved in its disposition may assist in elucidating its often unpredictable pharmacokinetics.

A.2.8 Buprenorphine

Like methadone, buprenorphine has been marketed as an effective maintenance medication for treating opioid addiction (Gowing et al., 2009). Buprenorphine is a semi-synthetic partial µ-opioid

165 receptor agonist and κ-opioid receptor antagonist (Brown et al., 2011). Buprenorphine has an estimated 20-30 times greater analgesic potency than morphine ((DEA), 2013a) and a half-life greater than 24 hours (Guo et al., 2013). Buprenorphine’s unique pharmacological properties among µ-opioid agonists include an apparent “ceiling effect” at higher doses, reducing the risk of respiratory depression and opioid withdrawal symptoms (Cowan et al., 1977; Walsh et al., 1994;

Brown et al., 2011). Such characteristics have made buprenorphine an attractive alternative to methadone in treating opioid addiction and moderate pain ((DEA), 2013a; Guo et al., 2013). The primary metabolite of buprenorphine in humans is norbuprenorphine, which exhibits plasma concentrations similar to those of buprenorphine (Moody et al., 2002). Norbuprenorphine is pharmacologically active and demonstrates a high affinity for all 3 opioid receptors (Huang et al.,

2001; Brown et al., 2011). However, norbuprenorphine has minimal antinociceptive effects

(Ohtani et al., 1997) and causes greater respiratory depression than buprenorphine (Brown et al.,

2011).

As of July 2013, it is estimated that around 15,700 physicians are approved by the Substance Abuse and Mental Health Services Administration (SAMSHA) and DEA to prescribe buprenorphine treatments in the U.S. In 2012 over 9 million buprenorphine prescriptions were dispensed in the

US ((DEA), 2013a). An estimated 21,483 ED visits were related to buprenorphine abuse in 2011, representing a nearly 5-fold increase from 2006 ((SAMHSA), 2013b). The 2011 AAPCC annual report estimated that nearly 4,000 Poison Control Center cases and 3 deaths related to buprenorphine abuse ((DEA), 2013a). Although intended to help in treating opioid addiction, buprenorphine, like many prescription opioids, is showing an alarming trend of increasing abuse.

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Both human P-gp and BCRP stably transfected in HEK293 cells were significantly inhibited in a concentration dependent manner by norbuprenorphine and buprenorphine, while only norbuprenorphine demonstrated P-gp mediated transport (Tournier et al., 2010). MDCK cells stably transfected with human P-gp demonstrated significantly increased net efflux of norbuprenorphine, but not of buprenorphine nor 2 of its glucoronidated metabolites, relative to untransfected cells (Brown et al., 2012b). Buprenorphine did not demonstrate P-gp mediated transport in human placental lobules (Nekhayeva et al., 2006) or Caco-2 cells, nor did it stimulate

P-gp ATPase activity (Hassan et al., 2009).

Buprenorphine has demonstrated the ability to rapidly cross the BBB of rats (Ohtani et al., 1997).

P-gp inhibitors were also found to increase brain uptake and decrease brain efflux of radiolabeled buprenorphine in rats (Suzuki et al., 2007). Conversely, no changes were found between brain distribution and antinociceptive effects of buprenorphine in P-gp knock-out mice relative to wild- types (Hassan et al., 2009). Another P-gp knock-out mouse study demonstrated that the brain/plasma ratio of norbuprenorphine was significantly greater, as was the magnitude and duration of its antinociceptive effects, relative to wild-types. These results suggest that P-gp plays a major role in limiting the BBB access of norbuprenorphine, potentially explaining its minimal antinociceptive effects (Brown et al., 2012b). Administration of the P-gp inhibitor PSC833 in mice was found to significantly increase the respiratory depressive effects of buprenorphine and norbuprenorphine, as well as significantly increase plasma concentrations and reduce brain efflux of norbuprenorphine. Similar effects were also seen in P-gp knock-out mice, suggesting that P-gp plays an important role in the BBB disposition of norbuprenorphine, and that its inhibition can lead to major respiratory side effects (Alhaddad et al., 2012). A follow up study by the same group found no differences in P-gp mediated BBB transport of buprenorphine or norbuprenoprhine

167 among different strains and genders of mice, despite their variable buprenorphine-induced respiratory toxicities (Alhaddad et al., 2013).

One clinical study compared the analgesic effects of buprenorphine and morphine in the palliative care of patients with confirmed P-gp+ or P-gp- malignant tumors, based on IHC results of tumor samples. The results demonstrated that P-gp expression had no influence on buprenorphine’s analgesic effects, while P-gp+ patients required higher doses of morphine for analgesic effects

(Wang et al., 2012). However, other groups have questioned these findings, citing the 10% IHC cut-off value for P-gp +/- categorization as arbitrary and the unknown correlation between P-gp expression in tumor cells and that of the BBB, as potential shortcomings (Megarbane and

Alhaddad, 2013). A retrospective study analyzing the co-use of illicit and non-prescribed drug use in buprenorphine patients found that cocaine and marijuana were the most commonly co- administered illicit drugs, while benzodiazepines were the most commonly co-administered non- prescription drugs (Guo et al., 2013). These results are concerning as other studies have shown that frequent and heavy cocaine use inhibits the pharmacokinetics of buprenorphine, triggering opioid withdrawal symptoms possibly by P-gp induction (McCance-Katz et al., 2010). Further, there have been numerous reports of severe respiratory depression and death from concomitant use of buprenorphine with CNS depressants, particularly benzodiazepines (Kintz, 2001; Lai et al.,

2006; McCance-Katz and Mandell, 2010; Selden et al., 2012; (DEA), 2013a). However, the role of drug transporters in these dangerous DDIs has yet to be investigated.

In vitro studies appear in agreement that buprenorphine is most likely not a P-gp substrate

(Nekhayeva et al., 2006; Hassan et al., 2009; Brown et al., 2012b), while nobuprenorphine is

(Tournier et al., 2010; Brown et al., 2012b). The apparent P-gp mediated efflux of

168 norbuprenorphine at the BBB may explain its minimal antinociceptive effects, despite its opioid receptor affinities. In vivo studies largely demonstrated the same findings, except one mouse study which suggested that buprenorphine BBB transport may be P-gp-dependent (Suzuki et al., 2007).

There appears to be only one clinical study to date addressing P-gp mediated transport of buprenorphine (Wang et al., 2012), and its findings have been contested (Megarbane and

Alhaddad, 2013). Most concerning is the fact that buprenorphine has been shown to be commonly co-abused with illicit drugs and prescription medications, often leading to dangerous DDIs (Guo et al., 2013). Of particular concern is the apparent prevalent co-abuse of buprenorphine with benzodiazepines, potentially causing fatal DDIs through a yet established mechanism. The only other transporter besides P-gp investigated to date appears to be BCRP, which one in vitro study suggests both buprenorphine and norbuprenorphine may be inhibitors of (Tournier et al., 2010).

This finding could have major implications on buprenorphine’s role in cancer patients. Thus, there is an urgent need for further investigation into other transporters and additional clinical studies into the role of P-gp and BCRP in buprenorphine’s disposition. Considering buprenorphine’s alarming increase in abuse and co-abuse with other drugs, greater understanding of its transport mechanisms is necessary to improve clinical outcomes and avoid DDIs.

A.2.9 Tramadol

Tramadol is a Schedule IV controlled substance ((DEA), 2014c) that is generally administered as a racemic mixture of (+) and (-) enantiomers, both of which have analgesic effects by inhibiting neuronal monoamine uptake. However, in vitro evidence suggests it is only the active CYP2D6 metabolite (+)-O-desmethyltramadol that is a µ-opioid receptor agonist (Tzvetkov et al., 2011).

Tramadol is well absorbed orally and generally administered every 4 to 6 hours for moderate to moderately-severe pain management. An estimated 43.8 million tramadol prescriptions were

169 dispensed in the U.S. in 2013 and over 13,000 tramadol exposures were reported to the American

Association of Poison Centers in 2012, 9 of which resulted in deaths ((DEA), 2014c). In 2011, an estimated 20,000 emergency room visits were due to non-medical use of tramadol ((SAMHSA),

2013b) and in 2012, an estimated 3.2 million Americans used tramadol for non-medical purposes

((SAMHSA), 2013a). Therefore, there are millions of Americans using tramadol both for licit and illicit purposes and so a clear understanding of the transporter interactions of tramadol may assist in improving its drug safety and efficacy.

Caco-2 monolayer transport studies of (+)-tramadol, (-)-tramadol and (+)-O-desmethyltramadol reported that none appeared to be P-gp substrates, while a proton-based efflux transporter was likely involved in restricting their GI absorption enhancing their renal excretion (Kanaan et al.,

2009). Transport studies in immortalized brain capillary endothelial cells (hCMEC/D3) demonstrated that tramadol uptake was significantly inhibited by other opioids that are cationic at physiological pH such as morphine, codeine, and oxycodone, as well as other organic cations including apomorphine, clonidine, diphenhydramine, quinidine, and pyrilamine. However, tramadol uptake was not significantly affected by substrates of OCT or OCTN2 but was altered by changes in transmembrane pH gradients. Together these results suggest that tramadol is a substrate of a proton-coupled organic cation antiporter at the BBB (Kitamura et al., 2014). Tramadol uptake was found to be unaffected by OCT1 overexpression in HEK293 cells while that of O- desmethyltramadol was increased 2.4-fold. This increased uptake was reversed in the presence of

OCT1 inhibitors and in cells overexpressing loss-of-function OCT1 variants (Tzvetkov et al.,

2011).

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In line with their in vitro findngs, rat brain microdialysis studies by Kitamura et al., reported that tramadol had a 2.3-fold higher concentration in the brain than plasma, suggesting an active tramadol uptake transporter at the BBB (Kitamura et al., 2014). In situ rat brain perfusion studies by Cisternino et al., showed that tramadol likely shared the same hypothetical proton-coupled amine transporter as nicotine and diphenhydramine at the BBB (Cisternino et al., 2013). Another rat study found that P-gp inhibition through verapamil pre-treatment had no effect on the brain concentration of tramadol, suggesting it is not a likely P-gp substrate (Sheikholeslami et al., 2012).

Initial studies by Slanar et al., in 21 healthy volunteers reported that MDR1 C3435T polymorphissm affected the PK of tramadol and O-desmethyltramadol, specifically their maxiumum concentration (Cmax), in subjects deemed poor metabolizers based on their CYPD26 genotype (Slanar et al., 2007). However, a following study by the same group in 156 post-operative patients investigated the possible impact of MDR1 C3435T polymorphisms on tramadol-induced analgesia found no significant differences among subgroups (Slanar et al., 2012). Another clinical study investigated the effects that co-administration of the potent P-gp inhibitor ketoconazole may have on the DDI between tramadol and the CYP2B6 inhibitor ticlopidine. Results found that ketoconazole had no effect on the PK of tramadol or ticlopidine nor did it modify their interaction

(Hagelberg et al., 2013). In line with their in vitro findings, Tzvetkov et al., demonstrated in healthy volunteers that OCT1 polymorphisms had no effect on the PK or PD of tramadol, while loss-of-function OCT1 polymorphisms correlated with elevated plasma concentrations of O- desmethyltramadol and prolonged miosis; a surrogate PD marker of opioids (Tzvetkov et al.,

2011).

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In conclusion, neither enantiomer of tramadol nor the active metabolite O-desmethyltramadol appear to be substrates of P-gp. All three do appear to be substrates of pH-dependent active transporters during their gastric efflux and renal excretion. Similarly, tramadol also appears to be a substrate of an emerging proton-coupled anitporter at the BBB that could result in a number of

DDIs with fellow substrates or inhibitors (Table 1). Tzvetkov et al., have also reported in vitro and clinical evidence that tramadol is a likely OCT1 substrate.

A.2.10 Hydrocodone

Hydrocodone is the most frequently prescribed opioid as well as the most associated with drug abuse and diversion ((DEA), 2013c). In the U.S. hydrocodone has been in the spotlight recently as congress changed its status from a Schedule III to Schedule II controlled substance in 2014.

Hydrocodone is a semi-synthetic opioid most structurally similar to codeine. Hydrocodone is believed to be at least as potent as codeine as an antitussive, and nearly as potent as morphine in producing analgesia. In 2012 an estimated 143 million hydrocodone containing prescriptions were dispensed in the US ((DEA), 2013c). Reports of hydrocodone abuse and addiction date back to the

1960s, and in 2011 an estimated 23.2 million people in the US aged 12 or older had used hydrocodone products for non-medical purposes ((SAMHSA), 2013a). In the same year, over

80,000 ED visits (representing a 107% increase in the number from 2004) and 37 deaths were reported from non-medical use of hydrocodone ((SAMHSA), 2013a). Additionally over 12,000

ED visits were reportedly due to hydrocodone-related suicide attempts, and over 74,000 ED visits were due to adverse reactions to hydrocodone products ((SAMHSA), 2013b). Hydrocodone abuse

172 shows an alarming increase in abuse trends and accounts for the most ED visits due to adverse reactions of all narcotic analgesics.

To date there has been no investigation into the transporters involved in the disposition of hydrocodone. Considering hydrocodone is addictive, frequently prescribed and abused, and recently available on the U.S. market in a new sole formulation, greater understanding of its transport mechanisms is urgently needed.

A.2.11 Hydromorphone

Hydromorphone is a potent Schedule II semi-synthetic opioid which is derived from and displays greater analgesic potency than morphine. In 2012 nearly 4 million hydromorphone prescriptions were dispensed in the U.S. and the aggregate production quota of hydromorphone in 2013 was almost 6,000 kg. Known to be highly addictive, hydromorphone abuse has been a continuing problem in the US for decades. Hydromorphone IR formulations were once among the leading opioid products of abuse and diversion ((DEA), 2013d). The 2011 NSDUH reported over 1 million

Americans aged 12 or over had tried hydromorphone for non-medical purposes, and over 18,000

ED visits related to hydromorphone abuse were reported in the US, representing an over 400% increase from 2004 ((SAMHSA), 2013a; (SAMHSA), 2013b). Hydromorphone remains a major prescription opioid of abuse with increasing trends of hospital visits from its misuse ((DEA),

2013d).

Despite the increasing prevalence of hydromorphone licit and illicit use, there currently does not appear to be any literature available on its transport mechanisms. This offers opportunities for future research that are urgently needed.

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A.3 Transporter-mediated DDIs

A.3.1 P-glycoprotein (P-gp)

P-gp (ABCB1) is by far the most thoroughly investigated drug transporter in current literature. The transporter is most highly expressed in the kidneys and liver (Morrissey et al., 2012), and to a lesser extent in the small intestine and brain (Nishimura and Naito, 2005) where it generally plays the role of an efflux pump. Despite the prevalence of P-gp literature, its role remains unclear with respect to the disposition of morphine, oxycodone, fentanyl, and methadone. In fact, the role of P- gp in the fate of oxycodone (Olkkola et al., 2013) and methadone appears particularly controversial. The uncertain role of P-gp in the disposition of some of the most frequently used and abused opioids is cause for concern. Given the large and expanding list of P-gp substrates, there is a real potential for transporter-mediated DDIs with these opioids that could have dangerous clinical consequences. Buprenorphine does not appear to be a P-gp substrate at the BBB while norbuprenorphine does, while neither tramadol or its active metabolite O-desmethyltramadol appear to be substrates either (Sheikholeslami et al., 2012; Hagelberg et al., 2013). These preliminary findings could have important implications in cancer pain management, as well as provide a mechanistic explanation for why norbuprenorphine produces minimal antinociceptive effects.

A.3.2 Breast cancer resistance protein (BCRP)

Another frequently investigated drug transporter is BCRP (ABCG2). First discovered in multidrug resistant breast cancer cell lines, BCRP was found to extrude chemotherapeutic agents such as mitoxantrone, methotrexate, imatinib, lapatanib, irinotecan, and topotecan from cancer cells

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((FDA), 2012). In addition, BCRP has also been shown to eliminate a number of non- chemotherapy medications (Ni et al., 2010; (FDA), 2012). BCRP appears most heavily expressed in hepatocytes, but may also be expressed in the renal tubule cells, enterocytes, and at the BBB

(Nishimura and Naito, 2005; Morrissey et al., 2012). Increased BCRP expression has been implicated in resistant forms of a number of hematological malignancies, head and neck, breast, lung, GI, esophageal and brain cancers (Natarajan et al., 2012).

In vitro has suggested that buprenorphine and norbuprenorphine are likely BCRP inhibitors

(Tournier et al., 2010). If clinically accurate, this finding could potentially suggest a beneficial transporter-mediated DDI in cancer pain management. Concomitant administration of buprenorphine with a chemotherapy agent which is a substrate of BCRP could increase the chemotherapy’s efficacy by decreasing BCRP-mediated efflux, while also providing pain relief.

Conversely, oxycodone appears to induce BCRP expression (Hassan et al., 2007), implying its long-term use in cancer pain management may incur adverse DDIs, rendering BCRP substrate chemotherapeutic agents less efficacious.

A.3.3 Organic anion transporting polypeptides (OATPs)

Organic anion transporting polypeptide (OATP) 1B1 and 1B3 are primarily expressed at the basolateral membrane of hepatocytes and are involved in hepatic uptake of xenobiotics from the blood for excretion in bile (Morrissey et al., 2012). In vitro and clinical data has suggested that fentanyl is not an OATP1B1 substrate and likely undergoes hepatic uptake by a different transporter (Ziesenitz et al., 2013). Conversely, in vivo has suggested that M6G is a likely

OATP1B1 at the BBB (Bourasset et al., 2003). This finding may be surprising as OATP1B1 does

175 not appear to be highly expressed in the brain (Nishimura and Naito, 2005). If accurate, co- administration of morphine (and by association, heroin) with OATP1B1 substrates could lead to adverse transporter-mediated DDIs, resulting in decreased systemic elimination and efficacy, as well as increased toxicity. OATP1B1 substrates may include a number of chemotherapy agents such as docetaxel (Malingre et al., 2001) and paclitaxel (Meerum Terwogt et al., 1999), as well as a number of antiretrovirals (Ding et al., 2004; Annaert et al., 2010) (Table 1). This finding could have important implications for the use of morphine in the pain management of cancer and HIV patients. Additionally, intravenous drug use is frequently associated with HIV+ patients, thus the risk of DDIs between heroin and antiretrovirals may also be worth noting.

There currently does not appear any literature regarding interactions between OATP1B3 and opioids despite being highlighted as an important drug transporter by the 2012 FDA guidance on drug-drug interactions.

A.3.4 Organic anion transporters (OATs)

The organic anion transporters OAT1 (SLC22A6) and OAT3 (SLC22A8) are primarily expressed in renal cells (Morrissey et al., 2012) and are involved in the uptake of drugs from the blood for excretion in the urine. The uricosuric agent probenecid is an established in vitro OAT1 (Cutler et al.; Elsby et al.; Cihlar and Ho, 2000; Ho et al., 2000; Mulato et al., 2000; Jung et al., 2001; Takeda et al., 2002; Chu et al., 2007) and OAT3 (Cutler et al.; Jung et al., 2001; Takeda et al., 2002; Tahara et al., 2005; Chu et al., 2007) inhibitor. Additionally, probenecid may also be a non-specific OAT inhibitor influencing the BBB permeability of OAT substrate drugs (Wong et al., 1993; Xie et al.,

2000a; Tunblad et al., 2005). In vivo findings have demonstrated that OATs influence the

176 disposition of M6G at tissues outside the brain, such as the kidneys where their inhibition would cause decreased uptake and systemic elimination (Tunblad et al., 2005). These results may suggest transporter-mediated DDIs between morphine (and by association, heroin) with other potential

OAT substrates, which may include commonly prescribed medications such as acyclovir (Laskin et al., 1982), famotidine (Inotsume et al., 1990), furosemide (Vree et al., 1995), and a number of cephalosporins (Welling et al., 1979; Pitkin et al., 1981; Stoeckel et al., 1988; Jaehde et al., 1995), to name a few (Table 1). In addition, likely OAT inhibitors such as probenecid (Liu et al., 2008) and sulfamethoxazole-trimethoprim (Shiveley et al., 2008) could restrict the renal elimination of

M6G. Considering the frequent use of some of these OAT substrates and inhibitors as well as morphine, there is a real possibility of adverse DDIs between them that warrants further investigation.

A.3.5 Organic cation transporters (OCTs)

The final transporter outlined in the 2012 FDA guidance is the organic cation transporter 2 (OCT2).

There currently does not appear to be any literature regarding the interaction of OCT2 with opioids.

However, there are reports regarding OCT1 and OCT3 interactions with opioids. Both OCT1 and

OCT3 appear to be predominantly expressed in the liver (Nishimura and Naito, 2005), where they behave as hepatic uptake transporters.

Morphine and tramadol appear to be likely OCT1 substrates (Tzvetkov et al., 2011; Tzvetkov et al., 2013), implying a host of potential clinical DDIs with other OCT1 substrates and inhibitors

(Table 1). Some OCT1 substrates based on in vitro evidence include acyclovir (Takeda et al.,

2002), metformin (Kimura et al., 2005; Choi et al., 2007; Ahlin et al., 2011), oxaliplatin (Zhang et

177 al., 2006), and ranitidine (Bourdet et al., 2005), to name a few. Potential OCT1 inhibitors also based on in vitro evidence includes amantadine (Minematsu et al., 2010), amitriptyline (Ahlin et al., 2011), clonidine, diphenhydramine (Muller et al., 2005), famotidine (Bourdet et al., 2005), cimetidine (Minematsu et al., 2010), glyburide (Ahlin et al., 2011), metformin (Bourdet et al.,

2005), quinidine (Bourdet et al., 2005; Minematsu et al., 2010), and verapamil (Zhang et al., 1998).

Therefore, co-administration of any of the above agents with codeine, morphine or tramadol could potentially result in decreased hepatic elimination of opioid substrate and/or the co-administered agent. Such transporter-mediated DDIs could incur dangerous clinical consequences, increasing the risk of adverse events such as respiratory and CNS depression. These findings also suggest that concomitant administration of morphine with tramadol in pain management could incur adverse

DDIs due to impaired hepatic elimination of either medication.

A.3.6 Multidrug resistance proteins (MRPs)

The human multidrug resistance-associated proteins (MRP) are a family of organic anion transporters whose presence in tumors has been associated with resistance to a number of chemotherapy agents (Borst et al., 2000). MRP2 appears primarily expressed in the apical domain of polarized hepatocytes, and to a lesser extent in renal proximal tubule cells, enterocytes, and at the BBB (Jedlitschky et al., 1996; Nishimura and Naito, 2005; Morrissey et al., 2012). MRP2 may play important roles in detoxification and chemo-protection processes, especially in transporting phase II metabolites (Jedlitschky et al., 1996). Potential MRP2 substrates also include a number of chemotherapeutic agents such as etoposide (Guo et al., 2002), irinotecan (Chu et al., 1997; Luo et al., 2002), methotrexate (El-Sheikh et al., 2007), and vinblastine (Tang et al., 2002), as we all

178 as a number of other frequently used medications such as olmesartan (Yamada et al., 2007), valsartan (Yamashiro et al., 2006), ciprofloxacin (Jaehde et al., 1995), and furosemide (Vree et al.,

1994).

MRP3 is mainly expressed in bile-duct epithelial cells of the liver, and to a lesser extent in the colon, intestine, and adrenal gland (Kool et al., 1997). Like MRP1 and MRP2, MRP3 is also an organic anion transporter whose expression has been linked to cancer resistance to a number of medications such as methotrexate and etoposide (Kool et al., 1999). Potential MRP3 substrates include fexofenadine (Matsushima et al., 2008), methotrexate, folic acid, and leucovorin (Zeng et al., 2001) and potential inhibitors include efavirenz, emtricitabine, delavirdine (Weiss et al., 2007)

Preclinical data has suggested that MRP2 and MRP3 are involved in the hepatic excretion of morphine’s glucoronidated metabolites M3G and M6G. If accurate, this could result in transporter- mediated DDIs with other MRP2 and MRP3 substrates and inhibitors mentioned above and in

Table 1. Impaired hepatic elimination of the M3G, M6G, or the concomitantly administered

MRP2/MRP3 substrate or inhibitor could incur dangerous clinical consequences that warrant further investigation.

A.3.7 Proton-coupled organic cation antiporters at the BBB

There appears to be an emerging class of pH dependent proton-coupled/organic cation antiporters that have yet to be fully identified but may play prominent roles in the disposition of a number of drugs at the BBB. Okura et al., demonstrated both in vitro and in vivo that oxycodone BBB transport was mediated via a pH and energy dependent proton-coupled antiporter shared with pyrilamine. In vitro findings have suggested that a number of medications, including quinidine,

179 verapamil, amantadine (Okura et al., 2008), the antidepressants amitriptyline, imipramine, clomipramine, amoxapine, and fluvoxamine, as well as the antiarrhythmics mexiletine, lidocaine, and flecainide, and ketamine (Nakazawa et al., 2010) may also be substrates of this transporter. A proton-coupled antiporter was also reported to be responsible for the luminal BBB transport of clonidine, diphenhydramine, tramadol, and nicotine. Further, a number of secondary and tertiary amine drugs of abuse including oxycodone, codeine, morphine, diacetylmorphine, cocaine, and

MDMA appear to inhibit or interact with this transporter (Andre et al., 2009; Cisternino et al.,

2013). Fischer et al., suggested that codeine may also be a substrate of a proton-coupled antiporter during intestinal and brain uptake with strong similarities to the pyrilamine transporter described by Okura et al. The cellular uptake of codeine was potently inhibited by pyrilamine, clonidine, diphenhydramine, propranolol, verapamil, as well as a numbers of drugs of abuse, including D- and L-amphetamine, cocaine, and methamphetamine (Fischer et al., 2010). However, Sadiq et al., have suggested that any clinical DDI between oxycodone and diphenhydramine was unlikely

(Sadiq et al., 2011).

The functional expression of a proton-coupled organic cation antiporter was demonstrated in an in vitro human BBB model, but its molecular identity remains unknown (Shimomura et al., 2013).

Due to the lack of molecular information it is presently unclear whether these findings refer to the same transporter or multiple possibly related transporters of an emerging class. A host of potentially harmful transporter-based clinical DDIs could result from a number of combinations, thus further research into proton-coupled/organic cation transporters is urgently needed. Greater understanding of these transporters could improve the clinical safety and efficacy of the many possible substrates, and even possibly aid in the development of new CNS acting drugs and anti- addiction therapies (Cisternino et al., 2013; Shimomura et al., 2013).

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A.4 Emerging transporters

In vivo data has suggested the GLUT-1 transporter is involved in the BBB transport of M6G (Polt et al., 1994; Bourasset et al., 2003). GLUTs have established roles as glucose and/or fructose transporters, but their other major substrates have likely not yet been identified, making predicting potential transporter-mediated DDIs difficult (Mueckler and Thorens, 2013). Further research into the role of GLUT transporters in the BBB transport of other medications may potentially unveil transporter-based DDIs as well as provide a new target for CNS acting drugs.

There also appear to be unidentified active transporters involved in the BBB transport of oxymorphone (Sadiq et al., 2013) and fentanyl (Henthorn et al., 1999), in addition to the aforementioned proton-coupled antiporters of morphine, codeine, diacetylmorphine, and oxycodone. Other active transporters which have yet to be fully elucidated include the probenecid- like transporter of M6G (putative OAT)(Tunblad et al., 2005), the digoxin-sensitive BBB transporter (putative OATP1B1) (Bourasset et al., 2003) of morphine, and pyrilamine BBB transporter of oxycodone (putative OCT) (Okura et al., 2008). Identifying these putative transporters are important steps towards mechanistically understanding the pharmacokinetics of opioids, particularly their BBB transport, as well as developing a platform for predicting transporter-based DDIs.

Although there does not currently appear any literature regarding interactions between multidrug and toxic compound extrusions transporters (MATEs) and opioids, they are emerging transporters of increasing interest. Both MATE1 and MATE2 appear to play particularly important roles in secreting organic cations into the urine. MATE1 is a proton-coupled organic cation antiporter that is mainly expressed in the kidney and liver where it is localized to the luminal membranes of renal

181 tubules and bile canaliculi (Motohashi and Inui, 2013). MATE2 is only expressed in the kidney and is localized at the brush-border membrane of proximal tubules (Motohashi and Inui, 2013).

Established MATE1 and MATE2 substrates include cimetidine, metformin, guanidine, procainamide and cephalexin (Motohashi and Inui, 2013).

There presently does not appear to be any drug transporter information available for hydrocodone or hydromorphone. This is particularly surprising considering hydrocodone is the most commonly dispensed and abused opioid, and was recently designated as a Schedule II medication in a new monotherapy formulation. Hydromorphone has also shown an increasing trend in prescription numbers and abuse reports. This absence of information highlights the great need for future research into their transport mechanisms to help in elucidating their pharmacokinetic mechanisms and potentially identify dangerous DDIs.

A.5 Transporter Polymorphisms

Pharmacogenomics appears to be playing an increasingly important role in transporter research and drug development. A host of genetic polymorphisms in a number of drug transporters have previously been linked to certain diseases, chemotherapy resistance, and immune deficiencies (Ho and Kim, 2005). There have also been a number of preclinical and clinical investigations into drug transporter polymorphisms and opioids.

The role of ABCB1 polymorphisms in the PK and PD of morphine remains currently unclear though despite a number of clinical investigations (Coulbault et al., 2006; Campa et al., 2008;

Fujita et al., 2010). However, there does appear to be a present consensus that OCT1 loss-of-

182 function polymorphisms have significant impacts on morphine PK, elevating morphineAUC

(Tzvetkov et al., 2013) and decreasing its clearance (Fukuda et al., 2013). OCT1 loss-of-function variants were also found to significantly affect the PK and PD of O-desmethyltramadol (Tzvetkov et al., 2011).

As with morphine, there does not appear to be a clear consensus on the role of ABCB1 polymorphisms in the PK and PD of oxycodone (Zwisler et al., 2010; Naito et al., 2011; Lam et al., 2013), fentanyl (Park et al., 2007; Kesimci et al., 2012; Skrobik et al., 2013), or methadone

(Coller et al., 2006; Crettol et al., 2006; Uehlinger et al., 2007; Crettol et al., 2008; Levran et al.,

2008; Buchard et al., 2010; Fonseca et al., 2011; Hung et al., 2011; Barratt et al., 2012; Lee et al.,

2013). The reasons behind this apparent lack of clarity may be complex, and possibly involve the geographic distribution of patients enrolled as well as the polymorphisms selected for investigation. A more standardized approach including more transporters of interest may help in elucidating the impact these polymorphisms have on the PK and PD of opioids. These findings could potentially provide a platform towards personalized opioid pain-management in the future.

A.6 Other contributors to opioid disposition and addiction

A.6.1 Drug Metabolizing Enzymes While transporter proteins play an important role in the PK/PD of many drugs of abuse, they are not the only constituents which may lead to clinical DDIs. Metabolizing enzymes in the intestines and liver are also key regulators of the disposition of these opioid medications and their interactions may alter the expression or activity of enzymes or systemic exposure to certain compounds. In addition to these DDIs, polymorphisms in the genes encoding for these

183 metabolizing enzymes can result in phenotypes which have significantly augmented or hindered metabolic activity.

Of particular importance to the abused drugs listed in this review are cytochrome P450 (CYP) enzymes 3A4 and 2D6. Codeine, a prodrug, is metabolized to its active form, morphine, by

CYP2D6 in the liver (Thorn Caroline F, Klein Teri E, Altman Russ B. "Codeine and morphine pathway" Pharmacogenetics and genomics (2009).). CYP2D6 is additionally responsible for the metabolism of oxycodone, hydrocodone, and tramadol to their active metabolites, oxymorphone, hydromorphone, and O-desmethyltramadol, respectively (Thorn Caroline F, Klein Teri E,

Altman Russ B. "Codeine and morphine pathway" Pharmacogenetics and genomics (2009)., and

Gong Li, Stamer Ulrike M, Tzvetkov Mladen V, Altman Russ B, Klein Teri E. "PharmGKB summary: tramadol pathway"Pharmacogenetics and genomics (2014).). These drugs are also oxidized by CYP3A4 to less potent metabolites

(http://dmd.aspetjournals.org/content/32/4/447.long). CYP3A4 has been shown to oxidize oxymorphone and hydromorphone to less potent metabolites, and along with CYP2B6 can catalyze the N-desmethylation of tramadol, designating it for conjugation and elimination(Thorn

Caroline F, Klein Teri E, Altman Russ B. "Codeine and morphine pathway" Pharmacogenetics and genomics (2009)., and Gong Li, Stamer Ulrike M, Tzvetkov Mladen V, Altman Russ B,

Klein Teri E. "PharmGKB summary: tramadol pathway"Pharmacogenetics and genomics (2014).).

It has been demonstrated that CYP3A4 is the major enzyme responsible for methadone metabolism in the liver with less significant contributions from CYP2D6 and CYP1A2

(http://www.ncbi.nlm.nih.gov/pubmed/15501692). CYP3A4 is also a key player in the metabolism of fentanyl in both the intestine and the liver

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(http://www.ncbi.nlm.nih.gov/pubmed/9311623). Buprenorphine interacts with many metabolizing enzymes following its administration. Major contributions are made to its metabolism and elimination by CYP3A4, CYP3A5, CYP3A7, and CYP2C8

(http://dmd.aspetjournals.org/content/34/3/440.full). Diacetylmorphine is the only drug of abuse focused on in this article which is not metabolized by cytochrome P450 enzymes. Instead, human carboxylesterases 1 and 2 are responsible for its metabolism, as well as the metabolism of cocaine (http://www.ncbi.nlm.nih.gov/pubmed/8930175).

The expression and activity of these metabolizing enzymes, and others, may be altered both genetically and chemically. It has been shown that methadone is a potent activator of nuclear receptors CAR and PXR. These receptors are key regulators of the expression of several drug metabolizing enzymes and transporters including CYP3A4, CYP2B6, and

MDR1(http://www.ncbi.nlm.nih.gov/pubmed/19520773). Alterations in the expression levels of these proteins can significantly alter the metabolism and disposition of their substrates which may have severe clinical ramifications. While an increase in drug metabolism is most often associated with increased elimination of the drug and decreased efficacy, in the case of pro-drugs or drugs which are metabolized to active forms like several of these drugs of abuse, increases in metabolism may increase risk of toxicity or adverse event.

A.6.2 Metabolizing Enzyme Polymorphisms Genetic polymorphisms in drug metabolizing enzymes can have drastic effects on the metabolism of drugs and the resultant concentration of drug in circulation. CYP2D6 is a highly polymorphic enzyme with some polymorphisms resulting in decreased metabolic activity while others encode an ultra-rapid metabolizer phenotype

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(http://www.ncbi.nlm.nih.gov/pubmed/15492763). These differences in metabolism can result in significantly different clinical outcomes following administration of drugs which are substrates of CYP2D6. Of particular interest here are codeine, oxycodone, and hydrocodone, which are predominantly metabolized in the liver by CYP2D6.

A.6.3 Opioid Receptor Polymorphisms The primary site of action of the opioid analgesic drugs is the mu-opioid receptor in the brain

(http://www.ncbi.nlm.nih.gov/pubmed/15694871). Genetic variations in this receptor have been identified and have been shown to require varying levels of morphine to achieve pain relief

(http://www.ncbi.nlm.nih.gov/pubmed/15694871). Studies have shown that variations of

OPRM1, the gene encoding the mu-opioid receptor, may interact with polymorphisms of

ABCB1, encoding P-gp, in opposite ways, requiring different amounts of morphine or methadone, in different studies, to provide analgesia (http://www.dovepress.com/abcb1- haplotype-and-oprm1-118a-gt-g-genotype-interaction-in-methadone--peer-reviewed-article-

PGPM).

Conversely, Smith et. al. provided evidence that genetic polymorphisms in OPRM1 do not alter individuals’ susceptibility to developing dependence on opioid analgesics. In this study, 170 severe opioid-dependent individuals were screened alongside 128 control subjects and there were no significant genetic differences identified between these test groups

(http://www.ncbi.nlm.nih.gov/pubmed/15558714). As a result of an overall lack of research into the subject, there have yet to be any definitive conclusions drawn regarding the implications of genetic polymorphisms of the mu-opioid receptor in opioid addiction.

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A.7 Implications for cancer therapy

Drug transporters such as P-gp, BCRP, and a number of MRPs have been linked to chemotherapy resistance in a number of different cancers, in some cases even serving as indicators of poor prognosis and survival (Filipits et al., 1999; Zochbauer-Muller et al., 2001; Munoz et al., 2007;

Natarajan et al., 2012). These transporters also appear to be involved in the disposition of a number of opioids which are often first-line treatment options in cancer pain management. Given the apparent prominent role of drug transporters in chemotherapy resistance and the common use of opioids in cancer-pain management, there is an increased likelihood of transporter-mediated DDIs between the two.

Although it appears unclear based on clinical evidence, preclinical evidence strongly suggests that morphine is a P-gp substrate. The concomitant administration of morphine with the apparent P-gp substrate paclitaxel may result in a transported-mediated DDI with unpredictable consequences

(Crowe, 2002). In vivo results have demonstrated that co-administration of oral morphine with the

P-gp substrate etoposide resulted in significantly increased acute morphine-induced analgesia, likely as a result of impaired P-gp-mediated efflux at the intestinal epithelium (Fujita-Hamabe et al., 2012). In addition, patients with P-gp+ tumors (≥10% IHC staining) were found to have significantly decreased morphine-induced analgesia, requiring higher doses (Wang et al., 2012).

The morphine phase II metabolite M6G may also be a weak OATP1B1 substrate at the BBB based on in vivo evidence (Bourasset et al., 2003), indicating potential transporter-mediated DDIs with other substrates which may include docetaxel (Malingre et al., 2001) and paclitaxel (Meerum

Terwogt et al., 1999). Morphine also appears to be a likely OCT1 substrate or inhibitor, potentially

187 inhibiting the hepatic clearance of other substrates that may include oxaliplatin (Zhang et al., 2006) and imatinib (White et al., 2006), consequently increasing their already significant toxicities.

Preclinical evidence has suggested M3G and M6G are likely MRP2 and MRP3 substrates (Zelcer et al., 2005; van de Wetering et al., 2007), potentially causing transporter-based DDIs with other substrates or inhibitors during hepatic clearance. Therefore, concomitant administration of morphine with other potential MRP2 substrates such as etoposide (Guo et al., 2002), irinotecan

(Chu et al., 1998), methotrexate (El-Sheikh et al., 2007), vinblastine (Tang et al., 2002), or inhibitors such as daunorubicin, etoposide, vincristine (Tang et al., 2002), and possible MRP3 substrates such as methotrexate, folic acid, and leucovorin (Zeng et al., 2001) could result in adverse clinical DDIs.

Tournier et al. suggested that buprenorphine and its metabolite norbuprenorphine may inhibit the activity of BCRP. If clinically accurate, this could imply the dual benefit of buprenorphine treatment in the pain management of cancer patients, providing pain relief while also reducing the efflux of BCRP substrate chemotherapies from cancerous cells. Wang et al., also demonstrated that buprenorphine-induced analgesia was unaffected by the P-gp status of patients tumors (Wang et al., 2012). Although preliminary, these findings may suggest that buprenorphine is a preferred opioid in cancer-pain management due to its favorable transporter interactions.

Conversely, Hassan et al. demonstrated in vivo evidence that oxycodone is a BCRP inducer, increasing the efflux of mitoxantrone from tissues. This finding may also apply to other BCRP substrates such as daunorubicin and doxorubicin(Hassan et al., 2010). Oxycodone was also shown to induce P-gp expression in rats, corresponding with decreased tissue concentrations of paclitaxel

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(Hassan et al., 2007). Together these preclinical results suggest that the concomitant use of oxycodone in cancer patients may incur adverse transporter-based DDIs that should be avoided.

Other studies have also shown that methadone increases the accumulation of vinblastine in multidrug resistant cells while also inhibiting P-gp mediated uptake of paclitaxel in placental inside-out cells (Callaghan and Riordan, 1993; Hemauer et al., 2009). Together, there potentially appears to be both positive and adverse transporter-based DDIs that may result from concomitant use of opioids with anti-cancer therapies. A greater understanding of the drug transporters of opioids and anti-cancer therapies will help towards optimizing cancer-pain management.

A.8 Conclusions

The U.S. is currently facing a severe epidemic in opioid-related deaths as well as dramatic increases in reports of opioid abuse and adverse events. Despite these alarming trends, relatively little is known about major components of opioid pharmacokinetics – membrane drug transporters.

A lack of clarity and even controversy exists regarding the role certain drug transporters play in the disposition of particular opioids, while a complete absence of information exists for others.

There also appears to be an emergence of yet fully identified transporters such as the proton- coupled organic cation antiporters which may play important roles in the BBB transport of opioids and a number of other drugs of abuse unknown. Drug transporter genomics is also emerging as an area of interest in predicting individualized patient responses to various opioids. This review predicts a number of opioid transporter-mediated DDIs as well as highlights both the potential adverse and beneficial effects these interactions may have in cancer pain management. To conclude, there presently appears to be a general lack of information and clarity on the role of drug transporters in the disposition of opioids, highlighting the need for further research. However, there

189 also appears promising potential that increased drug transporter knowledge may improve opioid safety and efficacy as well provide insight into the development of new anti-addiction therapies.

190

Figure A.1 Distribution of key opioid transporters. This figure illustrates the location and function of the key transporters responsible for the disposition of many drug substrates. The central compartment with red blood cells is representative of systemic circulation throughout the body. Each surrounding compartment is representative of a single cell of its respective tissue type with specific transporters located at the apical or basolateral membranes of each, as well as, in the case of hepatocytes, at the canalicular membrane. Green arrows indicate that a protein functions as an uptake transporter from circulation into the cell while red arrows represent efflux from the cell either back into circulation or to the bile. The few transporters with bidirectional arrows have been shown to function as shuttles for drug both into and out of cells. Figure used with permission of the copyright holder, Springer Publishing Group.

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Table A1: Summary of opioid-drug transporter interactions and their potential implications

Drug Name Transporter Evidence Clinical implications Morphine P-gp In vitro: The role of P-gp in the Morphine is a substrate (Callaghan disposition of morphine and Riordan, 1993; Schinkel et al., and its glucuronidated 1995; Letrent et al., 1999; Crowe, metabolites is unclear. 2002; Wandel et al., 2002) Morphine is not a substrate (Tournier et al., 2010) M6G is a substrate (Huwyler et al., 1996) M3G and M6G are not a substrates (Wandel et al., 2002) In vivo: Morphine is a substrate (Schinkel et al., 1995; Letrent et al., 1998; Xie et al., 1999; Aquilante et al., 2000; Thompson et al., 2000; Zong and Pollack, 2000; Dagenais et al., 2001; King et al., 2001; Hamabe et al., 2007; Fujita-Hamabe et al., 2012) M6G is a substrate (Lotsch et al., 2002) M6G is not a substrate (Bourasset et al., 2003) Clinical: Morphine is a substrate (Fudin et al., 2012; Wang et al., 2012; Meissner et al., 2013) Morphine and M6G are not substrates, while M3G is a possible substrate (Drewe et al., 2000) ABCB1 polymorphisms impact morphine PK/PD (Campa et al., 2008; Fujita et al., 2010) ABCB1 polymorphisms have no impact on morphine PK/PD (Coulbault et al., 2006) BCRP In vitro: Limited evidence Morphine is not a substrate (Tournier suggests morphine may et al., 2010) not be a BCRP substrate

192

Table A.1 continued

OCT1 In vitro: Morphine appears to be Morphine is an inhibitor (Ahlin et al., a likely OCT1 2008) substrate/inhibitor, Morphine is a substrate (Tzvetkov et inferring potential al., 2013) clinical DDIs with other Clinical: OCT1 substrates which OCT1 polymorphisms impact PK of may include acyclovir morphine (Fukuda et al., 2013; (Takeda et al., 2002), Tzvetkov et al., 2013) metformin (Wang et al., 2002; Wang et al., 2003a; Shu et al., 2007; Shu et al., 2008; Nies et al., 2009; Ahlin et al., 2011), imatinib (White et al., 2006), oxaliplatin (Zhang et al., 2006), ranitidine, (Bourdet et al., 2005) and inhibitors such as quinidine (Bourdet et al., 2005), atropine, diphenhydramine (Muller et al., 2005), amitriptyline (Ahlin et al., 2011), memantine, cocaine (Amphoux et al., 2006), prazosin (Minematsu et al., 2010), rosiglitazone (Bachmakov et al., 2008), pioglitazone (Ahlin et al., 2011), verapamil (Minematsu et al., 2010), and tramadol(Tzvetkov et al., 2011) OCT3 In vitro: Limited evidence Morphine is not a substrate suggests morphine is not (Tzvetkov et al., 2013) an OCT3 substrate.

GLUT-1 In vivo: Heroin and morphine M6G is a substrate at the BBB (Polt may affect glucose et al., 1994; Bourasset et al., 2003) transport at the BBB

193

Table A.1 continued

MRP1 In vivo: MRP2 and MRP3 M6G is not a substrate (Bourasset et appear to be involved in al., 2003) hepatic excretion of morphine glucuronidated MRP2 In vitro & in vivo: metabolites. This could M3G is a substrate (Zelcer et al., transporter-based DDIs 2005; van de Wetering et al., 2007) with other MRP2 and MRP3 In vitro: MRP3 substrates and M6G is a substrate (Zelcer et al., inhibitors. 2005; van de Wetering et al., 2007) In vivo: Some possible MRP2 M3G is a substrate (Zelcer et al., substrates include 2005; van de Wetering et al., 2007) olmesartan (Yamada et al., 2007), valsartan (Yamashiro et al., 2006), etoposide (Guo et al., 2002), irinotecan (Chu et al., 1998), methotrexate (El-Sheikh et al., 2007), vinblastine (Tang et al., 2002), and inhibitors include cyclosporine A, daunorubicin, etoposide, vincristine (Tang et al., 2002), efavirenz, emtricitabine, delavirdine (Weiss et al., 2007), indomethacin, ketoprofen (El-Sheikh et al., 2007).

Possible MRP3 substrates include fexofenadine (Matsushima et al., 2008), methotrexate, folic acid, leucovorin (Zeng et al., 2001), and inhibitors efavirenz, emtricitabine, and delavirdine (Weiss et al., 2007)

194

Table A.1 continued

Digoxin- In vivo: The identity of this sensitive M6G is a weak substrate at the BBB transporter has not been transporter (Bourasset et al., 2003) established, but may be OATP1B1. If so this could imply potential DDIs with OATP1B1 substrates such as pitavastatin, rosuvastatin (Busti et al., 2008), simvastatin (Kantola et al., 1998), docetaxel (Malingre et al., 2001), paclitaxel (Meerum Terwogt et al., 1999), fexofenadine (Kharasch et al., 2009), glyburide (Zheng et al., 2009), and digoxin (Ding et al., 2004), as well as likely OATP1B1 inhibitors such as ritonavir (Ding et al., 2004; Annaert et al., 2010), atazanavir, darunavir, indinavir, lopinavir (Annaert et al., 2010), and verapamil (Kantola et al., 1998)

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Table A.1 continued

Probenecid- In vivo: The identity of this sensitive M6G is a possible substrate outside transporter has not been transporter the BBB (Tunblad et al., 2005) established. (OAT) If M6G is an OAT substrate, there may be potential DDIs between morphine and other OATP substrates such as acyclovir (Laskin et al., 1982), cidofovir (Cundy et al., 1995), a number of cephalosporins such as cefaclor (Welling et al., 1979), cefonicid (Pitkin et al., 1981), ceftriaxone (Stoeckel et al., 1988), and cephradine (Welling et al., 1979), ciprofloxacin (Jaehde et al., 1995), dicloxacillin (Liu et al., 2008), famotidine (Inotsume et al., 1990), and furosemide (Vree et al., 1995), as well as with OAT inhibitors such as probenecid (Liu et al., 2008) and sulfamethoxazole- trimethoprim (Shiveley et al., 2008). Proton- In vivo: Possible inhibitor of an coupled Possible inhibitor at BBB (Andre et emerging but not yet antiporter of al., 2009) fully identified clonidine transporter at the BBB. Could be a source of a number of clinical DDIs between oxycodone and other potential substrates/inhibitors including clonidine, tramadol and nicotine, codeine, heroin, cocaine, and MDMA, tramadol (Andre et al., 2009; Cisternino et al., 2013)

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Table A.1 continued

Codeine OCT1 In vitro: Role of OCT1 is not Inhibitor (Ahlin et al., 2008) clear Not a substrate (Tzvetkov et al., 2013) Proton- In vitro: Yet to be fully identified coupled Possible substrate at intestinal transporter at BBB, may antiporter epithelium and BBB (Fischer et al., be similar to the proton- 2010) coupled antiporter of clonidine (Andre et al., 2009) and the pyrilamine transporter (Okura et al., 2008; Nakazawa et al., 2010).

The cellular uptake of codeine was potently inhibited by pyrilamine, clonidine, diphenhydramine, propranolol, verapamil, as well as a numbers of drugs of abuse, including D- and L- amphetamine, cocaine, and methamphetamine (Fischer et al., 2010) Diacetylmorphine Proton- In vivo: Possible inhibitor of an coupled Possible inhibitor at BBB (Andre et emerging but not yet antiporter of al., 2009) fully identified clonidine transporter at the BBB. Could be a source of a number of clinical DDIs.

Could be a source of a number of clinical DDIs between oxycodone and other potential substrates/inhibitors including clonidine, diphenhydramine, tramadol and nicotine, codeine, morphine, cocaine, and MDMA (Andre et al., 2009; Cisternino et al., 2013)

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Table A.1 continued

Oxycodone P-gp In vitro: Role of P-gp is highly Substrate (Hassan et al., 2007) controversial (Olkkola et In vivo: al., 2013) Substrate (Hassan et al., 2007; Hassan et al., 2009) Not a substrate (Bostrom et al., 2006) Clinical: C3435T and G2677T/A ABCB1 polymorphisms linked to less adverse effects of oxycodone (Zwisler et al., 2010) Mothers with at least one 2677 T copy had increased risk of oxycodone-induced sedation (Lam et al., 2013) C3435T polymorphism had no effects on oxycodone PK (Naito et al., 2011) BCRP In vivo: In vivo results have Inducer (Hassan et al., 2010) shown the oxycodone- induced upregulation of BCRP resulted in decreased brain mitoxantrone concentration. Concomitant use of oxycodone with other BCRP substrates could also result in transporter-mediated DDIs. Other BCRP substrates include daunorubicin, doxorubicin, methotrexate, imatinib, lapatanib, irinotecan, and topotecan ((FDA), 2012), as well as non- chemotherapy agents such as nitrofurantoin, prazosin, glyburide (Ni et al., 2010), rosuvastatin, sulfasalazine ((FDA), 2012), and fellow drug of abuse, marijuana (Holland et al., 2007; Tournier et al., 2010; Spiro et al., 2012)

198

Table A.1 continued

Pyrilamine In vitro & in vivo: Putative OCT may be transporter Substrate at the BBB (Okura et al., related to the proton- 2008; Nakazawa et al., 2010) coupled antiporter described by Andre et al., and Fischer et al.

In vitro results suggested significantly inhibited BBB uptake of oxycodone in the presence of pyrilamine, quinidine, verapamil, amantadine (Okura et al., 2008), the antidepressants amitriptyline, imipramine, clomipramine, amoxapine, and fluvoxamine, the antiarrhythmics mexiletine, lidocaine, and flecainide, and ketamine (Nakazawa et al., 2010)

Proton- In vitro: In vivo results suggest coupled Substrate at BBB (Sadiq et al., 2011; oxycodone and antiporter Shimomura et al., 2013) diphenhydramine do not share a common BBB transporter and that a clinical DDI is unlikely (Sadiq et al., 2011)

This transporter may be the same as the proton coupled antiporter described by Andre P et al., Kuwayama et al., Okura et al., Nakazawa et al., and Kitamura et al. Oxymorphone P-gp In vitro: Limited evidence Not a substrate (Hassan et al., 2009) suggests oxymorphone is not a likely P-gp substrate

199

Table A.1 continued

Unidentified In vivo: Further research is BBB Oxymorphone undergoes active needed transporter transport at BBB by a yet identified transporter (Sadiq et al., 2013) Fentanyl P-gp In vitro: Current role of P-gp is Substrate (Henthorn et al., 1999; not clear Hamabe et al., 2006) Not a substrate (Wandel et al., 2002) In vivo: Substrate (Cirella et al., 1987; Mayer et al., 1997; Thompson et al., 2000; Dagenais et al., 2004; Hamabe et al., 2006) Clinical: Intestinal but not BBB substrate (Kharasch et al., 2004a) 1236TT, 2677TT, and 3435TT genotypes linked with increased fentanyl-induced respiratory depression (Park et al., 2007) ABCB1 polymorphisms have no effect on fentanyl-induced sedation or respiratory depression (Kesimci et al., 2012), or coma/delirium (Skrobik et al., 2013) OATP In vitro: Role of OATP is not Not OATP1B1 substrate (Ziesenitz et clear. Fentanyl does not al., 2013) appear to be an In vivo: OATP1B1 substrate Substrate (Elkiweri et al., 2009) Clinical: Not a substrate (Ziesenitz et al., 2013) Yet identified In vitro: More research is needed transporter at Substrate at the BBB (Henthorn et into this transporter BBB al., 1999) which in vitro evidence suggests plays a more prominent role than P- gp in oxycodone disposition at the BBB

200

Table A.1 continued

Methadone P-gp In vitro: In vitro and in vivo Substrate (Callaghan and Riordan, evidence clearly support 1993; Bouer et al., 1999; Stormer et methadone as a P-gp al., 2001; Nanovskaya et al., 2005; substrate, but clinical Nekhayeva et al., 2005; Crettol et al., evidence is conflicting. 2007; Hassan et al., 2009; Hemauer et al., 2009; Beghin et al., 2010; Tournier et al., 2010; Hung et al., 2013; Linardi et al., 2013) The current role of P-gp In vivo: is unclear Substrate (Thompson et al., 2000; Dagenais et al., 2004; Rodriguez et al., 2004; Wang et al., 2004; Ortega et al., 2007; Hassan et al., 2009) Clinical: Substrate (Kreek et al., 1976; Eich- Hochli et al., 2003; Niemi et al., 2003) Possible intestinal, but not BBB substrate (Kharasch et al., 2004a) Unlikely substrate (Kharasch et al., 2008; Kharasch et al., 2009; Kharasch et al., 2012; Kharasch and Stubbert, 2013) ABCB1 polymorphisms influence methadone dosing (Coller et al., 2006; Levran et al., 2008; Hung et al., 2011) and PK (Uehlinger et al., 2007; Lee et al., 2013) ABCB1 polymorphisms have little/no influence methadone dosing (Crettol et al., 2008; Fonseca et al., 2011; Barratt et al., 2012) or PK (Crettol et al., 2006; Lotsch et al., 2006; Buchard et al., 2010)

201

Table A.1 continued

Buprenorphine P-gp In vitro: In vitro and in vivo Inhibitor: buprenorphine and evidence appear to norbuprenorphine (Tournier et al., suggest buprenorphine 2010) is not, while Substrate: norbuprenorphine norbuprenorphine is a P- (Tournier et al., 2010; Brown et al., gp substrate. 2012b) Not a substrate: buprenorphine One clinical study (Nekhayeva et al., 2006; Hassan et available suggests al., 2009; Brown et al., 2012b) buprenorphine is not a In vivo: P-gp substrate (Wang et Substrate: buprenorphine (Suzuki et al., 2012), but this al., 2007) and norbuprenorphine finding has been (Alhaddad et al., 2012; Brown et al., contested by others 2012b) (Megarbane and Not a substrate: buprenorphine Alhaddad, 2013) (Hassan et al., 2009) Clinical: Not a substrate (Wang et al., 2012) BCRP In vitro: Limited evidence Inhibitor: buprenorphine and suggests buprenorphine norbuprenorphine (Tournier et al., and norbuprenorphine 2010) are BCRP inhibitors. This could lead to clinical DDIs with likely BCRP substrates such as the chemotherapy agents mitoxantrone, methotrexate, imatinib, lapatanib, irinotecan, and topotecan ((FDA), 2012), as well as non- chemotherapy agents such as nitrofurantoin, prazosin, glyburide (Ni et al., 2010), rosuvastatin, sulfasalazine ((FDA), 2012), and fellow drug of abuse, marijuana (Holland et al., 2007; Tournier et al., 2010; Spiro et al., 2012)

202

Table A.1 continued

Tramadol P-gp In vitro: (+)-tramadol, (-)-tramadol Tramadol and O- and (+)-O-desmethyltramadol are not desmethyltramadol not substrates (Kanaan et al., 2009) appear to be P-gp In vivo: Tramadol is not a substrate substrates (Sheikholeslami et al., 2012) Clinical: MDR1 C3435Tpolymorphisms influence tramadol Cmax in CYP2D6 poor metabolizers (Slanar et al., 2007) MDR1 C3435T polymorphisms have no influence on tramadol-induced post-operative analgesia (Slanar et al., 2012) P-gp inhibitor verapamil had no influence on the PK of tramadol or its DDI with ticlopadine (Hagelberg et al., 2013) Proton-based In vitro: efflux (+)-tramadol, (-)-tramadol and (+)-O- transporter desmethyltramadol are substrates of a yet identified pH dependent efflux transporter during GI absorption and renal excretion (Kanaan et al., 2009)

Proton- In vitro: In vitro evidence coupled Substrate at the BBB (Kitamura et suggests DDIs at the organic al., 2014) BBB between tramadol antiporter In vivo: and morphine, codeine, Substrate at the BBB (Cisternino et oxycodone, al., 2013) apomorphine, clonidine, pyrilamine, diphenhydramine, amantadine, memantine, verapamil, and quinidine (Kitamura et al., 2014). In vivo evidence suggests DDI at the BBB between tramadol and nicotine or diphenhydramine (Cisternino et al., 2013) These may refer to the same emerging transporters described by Okura et al., Sadiq et al., and Shimomura et al., Tega et al., and Andre et al.

203

Table A.1 continued

OCT1 In vitro & clinical: Tramadol appears to be Substrate (Tzvetkov et al., 2011) a likely OCT1 substrate, inferring potential clinical DDIs with other OCT1 substrates such as acyclovir (Takeda et al., 2002), metformin (Wang et al., 2002; Wang et al., 2003a; Shu et al., 2007; Shu et al., 2008; Nies et al., 2009; Ahlin et al., 2011), imatinib (White et al., 2006), oxaliplatin (Zhang et al., 2006), ranitidine, (Bourdet et al., 2005) and inhibitors such as quinidine (Bourdet et al., 2005), diphenhydramine (Muller et al., 2005), amitriptyline (Ahlin et al., 2011), memantine, cocaine (Amphoux et al., 2006), prazosin (Minematsu et al., 2010), rosiglitazone (Bachmakov et al., 2008), pioglitazone (Ahlin et al., 2011), verapamil (Minematsu et al., 2010), morphine (Tzvetkov et al., 2013), as well as with potential OCT1 inhibitors such as MDMA, amantadine, famotidine (Bourdet et al., 2005), memantine (Amphoux et al., 2006), amitriptyline (Ahlin et al., 2011), cimetidine, ranitidine (Minematsu et al., 2010), clonidine (Zhang et al., 1998; Muller et al., 2005), cocaine, D- amphetamine, ketamine, phencyclidine (Amphoux et al., 2006),

204

Table A.1 continued

Hydrocodone No transporter information Hydromorphone

205

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B.1 Introduction

Cocaine abuse remains a significant public health concern in the United States and in many regions around the world. Globally, cocaine is used by approximately 17 million people

(United Nations Office on Drugs and Crime, 2015). In the United States roughly 900,000

Americans fell under the Diagnostic and Statistical Manual of Mental Disorders criteria for dependence on or abuse of cocaine, in any form, in 2014 (Substance Abuse and Mental Health

Services Administration, 2014). Of this number, only about 600,000 people received any form of treatment for cocaine use disorder (CUD) or cocaine addiction (Substance Abuse and Mental

Health Services Administration, 2014). Current treatments of CUD are largely limited to cognitive or behavioral-based interventions and have demonstrated limited success and there is no available FDA-approved medication for CUD (Penberthy et al., 2010; Shorter and Kosten,

2011; Haile et al., 2012; Mariani and Levin, 2012). Further, in addition to physical detriment to cocaine users and the impact on their families and communities, the socioeconomic cost of cocaine is substantial, with estimated costs in the tens of billions of dollars (Anonymous Office of National Drug Control Policy, 2004). As such, the need for improved anti-addiction therapies for cocaine users is evident.

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levo-Tetrahydropalmatine (l-THP) is a purified compound from Chinese plants Stephania and Corydalis and is clinically approved in China for management of chronic pain (Mantsch et al., 2007; Mantsch et al., 2010; Liu et al., 2012; Wang and Mantsch, 2012; Yue et al., 2012).

This compound is a member of the tetra-hydroprotoberberines (THB) family which has been identified as having anti-drug addiction properties (Chu et al., 2008). In recent years, l-THP specifically has displayed utility in attenuating drug-seeking behavior in animals as well as humans. This utility has been demonstrated pre-clinically in studies with cocaine, heroin, and methamphetamine behavioral models of addiction (Mantsch et al., 2007; Mantsch et al., 2010;

Yue et al., 2012; Su et al., 2013). Further, in humans, l-THP has displayed utility in increasing abstinence from heroin use following detoxification (Yang et al., 2008). However, the mechanisms by which l-THP exhibits its therapeutic effects have yet to be definitively elucidated. It is believed that l-THP acts as a post-synaptic D1 receptor antagonist disrupting signaling in the mesolimbic dopamine system to diminish the psychological rewards from drugs of abuse (Marcenac et al., 1986; Xi et al., 2007). Still, the antagonistic activity of l-THP at D2 autoreceptors can alter DA signaling of reward resulting in efficacy in the treatment of addiction.

Beyond these interactions with DA receptors and signaling, l-THP is known to act at serotonin 5- hydroxytryptamine (5-HT), gamma amino butyric acid (GABA), and alpha 1-adrenergic receptors, which may facilitate its therapeutic actions concerning drug addiction, while diminishing common side effects seen in traditional DA antagonists such as haloperidol (Wang and Mantsch, 2012). Given that l-THP is garnering an increase in attention as a potential drug abuse cessation treatment, it is critical to fully characterize this compound to ensure that l-THP is safe for administration in humans and will not contribute to adverse drug-drug interactions

(DDI).

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Clinical trials designed to examine the potential utility of l-THP for cocaine addiction and for efficacy in heroin-dependent individuals have yielded promising results. An initial study examining the impact of l-THP towards heroin addiction indicated that individuals receiving l-

THP treatment reported significantly lower post-acute withdrawal syndrome (PAWS) scores as well as decreases in somatic symptoms, insomnia, and craving, which all coincided with an overall increased abstinence rate as compared to the placebo group. In a recent trial with humans receiving oral l-THP and nasally-administered cocaine, it was concluded that l-THP is well tolerated and does not affect the overall PK of cocaine in man (Hassan et al., 2017).

Many studies have been conducted to characterize the pharmacokinetics and toxicity of racemic

THP and the parent class of THB compounds (Hong et al., 2005a; Hong et al., 2005b; Hong et al., 2006; Li et al., 2006; Ou et al., 2006; Hong et al., 2008; Hong et al., 2010b; Kovtun et al.,

2010; Wang et al., 2010; Wang et al., 2013b). Still, few studies have been conducted on the purified l-THP form, and even fewer studies exist investigating the pharmacokinetics of l-THP and its potential for interactions with drugs of abuse in pre-clinical models. This paucity of research leaves a void in the knowledge of how the PK of abused drugs are altered in the presence of l-THP. As l-THP is intended to treat CUD, it is necessary to investigate potential drug-drug interactions between l-THP and cocaine especially in pre-clinical models that would be used to evaluate the pharmacological activity of l-THP. In the present study, we sought to provide a comprehensive analysis of the pharmacokinetics of l-THP alone and in combination with cocaine to begin to fill this knowledge gap.

B.2 Methods and Materials

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B.2.1 Culture of HepG2 and H9c2 cells HepG2 cells were cultured in DMEM supplemented with 10% fetal bovine serum as well as penicillin and streptomycin. Cells were kept in T-75 flasks at 37°C and 5% CO2. H9c2 rat cardiomyoblast cells were cultured in DMEM supplemented with 10% fetal bovine serum in T-

75 flasks at 37°C and 10% CO2. All cells were passaged when confluence reached ~90% and kept for less than 40 passages.

B.2.2 MTT assays with HepG2/H9c2 cells HepG2 and H9c2 cells were seeded at a density of 7.5 x 104 cells/well in 96-well plates and incubated for 24 hours at 37°C and 5% CO2. Following incubation, wells were treated in triplicate with l-THP over a range of concentrations for 24 hours with 0.1% Triton-X100 as a positive control for cell toxicity. 20 µL of MTT solution (5.0 mg/mL) was added to each well followed by a 3 hour incubation period under the same conditions. Following removal of the

MTT solution, 150 µL of DMSO was added to each well to dissolve the resultant crystals.

Absorbance was determined at 570 nm on a SpectraMax 384 Plus plate reader (Molecular

Devices).

B.2.3 Rat subjects Male Sprague-Dawley rats (250-275 g) were purchased from Harlan Laboratories (Indianapolis,

IN). Since estrogen and progesterone have been shown to alter the PK of cocaine, only male rats were utilized for the present study (Niyomchai et al., 2006). Rats were housed in the animal facility of the University of Maryland School of Medicine and were maintained on a 12-hour light/dark cycle at a temperature of 72 ± 2°F. Food (Purina 5001 Rodent Chow, Purina, St.

Louis, MO) and water were available ad libitum. The animal study protocol was approved by the Institutional Animal Care and Use Committee of the School of Pharmacy, University of

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Maryland. Animal facilities were accredited by the American Association of Laboratory Animal

Care and all experiments were conducted in accordance with the National Institutes of Health

Guide for the Care and Use of Laboratory Animals.

B.2.4 Catheter implantation for IV pharmacokinetics studies Catheter surgeries were performed under aseptic conditions using ketamine (100 mg/kg, i.p.) and xylazine (7.5 mg/kg i.p.). Once completely anesthetized, silastic catheters were implanted into the right jugular vein and secured with silk sutures. Animals were given two days to recuperate and catheters were flushed with saline to maintain patency.

B.2.5 HPLC Quantitation Method for Metabolism Studies Quantitation of l-THP and cocaine was performed as previously described by Yu et al. and

Abdallah et al. with few modifications (Yu et al., 2014; Abdallah et al., 2017). Briefly, a 100 µL aliquot of sample was spiked with internal standard (venlafaxine HCl, 1.25 µg/mL), vortexed, and extracted with 1.5 mL of hexane. The upper organic layer of 1.35 mL was aliquoted into clean tubes and evaporated to dryness under a nitrogen stream at 37°C. The residue was reconstituted with 150 µL of mobile phase and a 25 µL aliquot was injected into an ACQUITY

UPLC H-Class system from Waters (Milford, MA) with a fluorescence detector (excitation 230 nm, emission 315 nm). The separation was performed on an ACQUITY UPLC BEH C-18 column (2.1 x 50 mm, 1.7 µm) with an ACQUITY in-line filter from Waters. The mobile phase was composed of acetonitrile:methanol:0.005M ammonium phosphate buffer (8:8:84, v/v/v) with a flow rate of 0.6 mL/min.

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B.2.6 Quantitation of IV cocaine and l-THP administration using a validated UPLC method A validated ultra-performance liquid chromatography (UPLC) method with fluorescence detector (excitation 230 nm, emission 315 nm) was used to quantify cocaine and l-THP in plasma and brain samples. Brain samples were first homogenized in phosphate-buffered saline using a PowerGen125 from Fisher Scientific (Pittsburgh, PA) and then treated in the same manner as plasma samples. A 200 µL aliquot of sample was spiked with internal standard

(venlafaxine HCl, 1.25 mg/mL), vortexed, and extracted with 1 mL hexane. The upper organic layer of 850 µL was aliquoted into clean tubes and evaporated to dryness under a nitrogen stream. The residue was reconstituted with 150 µL of mobile phase and a 50 µL aliquot was injected into an ACQUITY HPLC H-Class system from Waters (Milford, MA) with an in-line fluorescence detector. The separation was performed on a Waters SYMMETRY C-18 column

(4.6 x 100 mm, 5 µm) with a security guard and filter from Phenomenex (Torrance, CA). The mobile phase was composed of acetonitrile:methanol:0.01M ammonium phosphate buffer

(18:18:64, v/v/v) with a flow rate of 0.8 mL/min. The lower limit of quantification (LLOQ) for both cocaine and l-THP was 0.0025 µg/mL with a linearity range from 0.0025 – 5 µg/mL. Intra- and inter-day validations were conducted, and all CV values were below 15%. Also, both precision and accuracy determinations met the FDA guidelines and the CV were below 15%, including the LLOQ. Cocaine was eluted at 4 minutes, internal standard at 7 minutes, and l-THP at 11 minutes.

B.2.7 Drug-stimulated ATPase assay l-THP-stimulated P-gp ATPase activity was evaluated with the Glo (Promega, Madison, WI) assay system. This assay utilizes the light-generating reaction of firefly luciferase which

228 decreases in luminescence with ATP consumption. In a 96-well plate, recombinant human or rat

P-gp (25 µg) (BD Biosciences, San Jose, CA) was incubated with the Glo assay kit buffer (20

µL) (control, n = 4), verapamil (100 µM), sodium orthovanadate (500 µM) (n = 4), and l-THP (4,

20, 100 µM) (n = 4/concentration). Verapamil served as a positive control for P-gp activity and sodium orthovanadate was utilized as an ATPase inhibitor. The assay reaction is initiated by the addition of MgATP (10 mM) and terminated 40 minutes later by the addition of 50 µL of the firefly luciferase reaction mixture, initiating an ATP-dependent luminescence reaction. After a

60-minute incubation period, luminescence signals were measured for 10 seconds using an

LMax luminometer (Molecular Devices, Sunnvale, CA), and converted to ATP concentrations by interpolation from a luminescent ATP standard curve. Rates of ATP consumption (picomoles of ATP consumed per microgram of P-gp per minute) and –fold stimulation of the basal P-gp activity were calculated as described below in equations 1-3.

Equation 1: Basal P-gp activity (pmol ATP consumed/µg of P-gp/min)

퐴푇푃 − 퐴푇푃 = 푣푎푛푎푑푎푡푒 푐표푛푡푟표푙 25휇푔 푃−푔푝 × 40푚푖푛

Equation 2: Test compound stimulated P-gp activity (pmol ATP consumed/µg of P-gp/min)

퐴푇푃푣푎푛푎푑푎푡푒 − 퐴푇푃푐표푚푝표푢푛푑 = 25휇푔 푃−푔푝 × 40푚푖푛

Equation 3: -Fold stimulation by a test compound

푇푒푠푡 푐표푚푝표푢푛푑 푠푡푖푚푢푙푎푡푒푑 푃 − 푔푝 푎푐푡푖푣푖푡푦 = 퐵푎푠푎푙 푃 − 푔푝 푎푐푡푖푣푖푡푦

229 where ATPvanadate is the number of total (non-consumed) picomoles of ATP in the presence of the

ATPase inhibitor sodium orthovanadate. ATPcontrol is the number of non-consumed ATP picomoles present in only the assay buffer, and ATPcompound is the number of non-consumed picomoles of ATP in the presence of a test compound. ANOVA followed by Dunnett’s post hoc test (GraphPad Prism V5) was used to examine the statistical significance of the difference between treatment groups. Significance was determined at p < 0.05.

B.2.8 Rat liver microsome metabolism studies The time course of metabolism of l-THP (25 µM final concentration; n = 3) was determined using pooled male rat liver microsomes from BD Biosciences. The reaction mixture consisted of a NADPH-regenerating system (1.3 mM NADP+, 3.3 mM glucose-6-phosphate, 0.1 U/mL glucose-6-phosphate dehydrogenase, and 3.3 mM magnesium chloride), 25 µM l-THP in acetonitrile, and 100 mM potassium phosphate buffer pH 7.4, and distilled water. The reaction was initiated by the addition of ice cold microsomes to a pre-warmed mixture of buffer, substrate, and co-factor. The microsomes were used at a final concentration of 0.5 mg/mL. The reaction system was incubated at 37°C and 100 µL samples were collected at 0, 5, 10, 15, 20, 25,

30, 35, 40, 50, and 60 minutes and immediately vortexed with 100 µL of acetonitrile to terminate the reaction. Finally, samples were centrifuged at 10,000 x g for 15 minutes and the supernatants were analyzed by validated HPLC method. Assuming a first-order disappearance rate for the substrate, the disappearance rate constant was calculate from the slope of the log Ct vs time profile based on equation 4:

퐾 log 퐶 = log 퐶 − 푡 푡 0 2.303

230 where Ct is the concentration of substrate at the various time points, C0 is the initial concentration of substrate, and K is the disappearance rate constant. The initial metabolic rate

V0 was calculated via equation 5:

퐶 푉 = 퐾 × 0 0 푒 푃푀푆 where PMS concentration of microsomes (0.5 mg/mL). Intrinsic clearance was calculated with equation 6:

푉0 퐶푙푖푛푡 = 퐶0

Studies investigating the time course metabolism of l-THP in the presence of cocaine were performed as described above in the preliminary l-THP metabolism studies with the addition of

25 µM cocaine to the reaction mixture. All microsome studies were performed in triplicate.

B.2.9 In-vivo pharmacokinetics studies Rats were assigned to one of two groups: vehicle + cocaine (n=7) or l-THP + cocaine (n=8).

Rats were administered 1 mL/kg vehicle or 7.5 mg/kg l-THP i.v. b.i.d. for two and a half days.

This dosing regimen was chosen to ensure that steady-state plasma concentrations of l-THP were achieved. The elimination half-life (t1/2) of l-THP in Sprague-Dawley rats was reported to be 4 hours. As such, b.i.d. administration lead to l-THP accumulation and achievement of l-THP steady-state plasma concentrations before cocaine was introduced to the system. Catheters were flushed with 0.2 mL saline before and after dosing to ensure the maintenance of catheter patency.

On the day of the experiment, rats in each group received i.v. treatment of vehicle or l-THP immediately followed by a single i.v. dose of cocaine HCl (10 mg/kg). One animal was lost

231 from each group after cocaine was infused too quickly through the i.v. catheter. An additional animal was later lost from the vehicle group. Blood samples (400μL) were taken from animals via aspiration of the i.v. catheter at pre-determined time points: pre-dose, 5, 15, 30, 45, 60, 75,

90, 105, 120, 150, 180, 210, 240, 270, 300, 330, 360, 390, and 420 minutes post-dose. Collected blood samples were centrifuged for 10 minutes at 10,000 rpm (Denville Scientific 260D,

Metuchen, NJ), and plasma was stored at -80°C until analysis. Not all animals were able to provide blood samples at each time point. After completion of the time course, animals were sacrificed and brain tissues were collected, blotted dry, weighed, and stored at -80°C until analysis. Following quantitation via UPLC method, non-compartmental and compartmental PK analyses were performed using Phoenix WinNonlin.

B.2.10 Gene induction in treated rat tissue Total RNA from harvested brain from rats utilized in the above pharmacokinetic study treated with l-THP (7.5 mg/kg, i.v.) and cocaine (10 mg/kg, i.v.) (n=8) or control (saline, i.v.) plus cocaine (10 mg/kg, i.v.) (n=7) was isolated with TRIzol Reagent (Life Technologies) and reverse transcribed using a High Capacity cDNA Archive kit (Applied Biosystems) following the manufacturers' instructions. mRNA expression of Cyp1a1, Cyp3a1, Ugt1a1, Sult1a1, Mdr1b, and

Bcrp was normalized against that of Gapdh. Real-time PCR assays were performed in 96-well optical plates on a StepOnePlus Real-Time PCR System with SYBR Green PCR Master Mix

(Applied Biosystems). The primer sequences used for real-time PCR analyses are listed in Table

B.1(Silverman et al., 1991; Caron et al., 2005; Yue et al., 2011; Xu et al., 2012b; Zhou et al.,

2012; Lindblom et al., 2014). Fold induction of genes over control was determined as 2ΔΔCt, where ΔCt is representative of the cycle threshold number difference between the target gene and

232

GAPDH and ΔΔCt represents the relative change in the intergroup variations. Statistical significance was determined at p < 0.05 as outlined under the statistical analysis section.

B.2.11 Statistical analyses All values were presented as mean ± SEM. Student’s t-test, analysis of variance (ANOVA) with repeated measures, or ANOVA followed by either Dunnett’s or Bonferroni’s posthoc tests were used to determine statistical significance between groups. The criterion of significance was set at the 0.05 level of probability.

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Table B.1 Primers utilized for qPCR studies in rat brain tissue.

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B.3 Results

B.3.1 l-THP is non-toxic at pharmacologically-relevant concentrations. The toxicity of l-THP was examined in-vitro via MTT assay in HepG2 and H9c2 cell lines to examine cell viability in both a human- and rat-derived cell line. Further, a cardiomyoblast call line (H9c2) was chosen to confirm that l-THP administration would not exacerbate the known cardiotoxicity associated with cocaine use (Phillips et al., 2009). At pharmacologically-relevant concentrations (1-60 µM). l-THP did not result in any cell death, though it did exhibit modest cytotoxicity in both cell lines at elevated concentrations (Figure B.1A, B). Importantly, l-THP remained non-toxic at pharmacologically-relevant concentrations (1-60 µM).

B.3.2 Metabolic stability of l-THP and cocaine The metabolism of cocaine was examined in rat liver microsomes in the presence and absence of l-THP (Figure B.2A, B). There was no significant difference in the intrinsic clearance of cocaine. In the presence of l-THP the intrinsic clearance of cocaine was calculated to be 77.69 ±

1.32 µL/min/mg of protein and without l-THP the clearance rate was 77.53 ± 2.42 µL/min/mg of protein. The metabolism of l-THP was evaluated using recombinant rat liver microsomes in the presence and absence of cocaine. When administered alone, l-THP followed first-order reaction kinetics with concentrations declining mono-exponentially over time (Figure B.2C, D). The metabolism of l-THP was altered in the presence of cocaine, however. The intrinsic clearance value for l-THP was calculated to be 45.75 ± 12.75 µL/min/mg of protein without cocaine, and

27.18 µL/min/mg of protein in the presence of cocaine.

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Figure B.1 l-THP is non-toxic at pharmacologically-relevant concentrations in human and rat cell lines. Human HepG2 (A) and rat H9c2 cells (B) were treated with a range of l-THP concentrations (1-500 µM) for 24 hours with 0.01% Triton X-100 as a positive control for cell toxicity. At pharmacologically-relevant concentrations (1-60 µM) l-THP remained non-toxic in both cell lines. At elevated concentrations, modest cytotoxicity was observed. *, p < 0.05; ***, p < 0.001.

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Figure B.2 Metabolism of cocaine is not altered by l-THP in microsomes while cocaine changes clearance of l-THP. The metabolism of cocaine was examined in the presence and absence of l-THP in rat liver microsomes over a 1h time course (A). The intrinsic clearance of cocaine, as calculated in the materials and methods, was not altered by l-THP (B). The intrinsic clearance of l-THP was significantly changed with the addition of cocaine in similar metabolism experiments (C, D).

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B.3.3 l-THP does not alter the PK profile of cocaine in rats. Our bioanalytical method was able to quantify cocaine in the isolated plasma samples from both the vehicle and l-THP-treated groups (Figure B.3A). No significant difference was found between the two groups concerning the plasma concentrations at any time point. Non- compartmental and compartmental pharmacokinetic analyses of each group revealed comparable parameter estimates for each group with respect to Cmax, Tmax, Vss, Cl, t1/2, and AUC (Tables B.2 and B.3). l-THP was detectable via our UPLC method throughout the entire 420-minute time course of the study (figure B.3B). Consistent with previous reports, l-THP was cleared more slowly than cocaine (Table B.3). Since animals were sampled serially instead of in a destructive manner, brain samples were only collected at the conclusion of the 420-minute time course.

Analysis of brain homogenate revealed that l-THP-treated rats retained significantly more cocaine within the brain than the rats treated only with vehicle (p<0.0001). There was also a large concentration of l-THP accumulated within the brain tissue at the termination of this study

(Figure B.4).

B.3.4 l-THP does not induce the expression of key drug metabolizing enzymes and transporters in rats. At the conclusion of the serial blood sampling of the rats for PK analysis, the brains of all animals were collected. mRNA was isolated from the harvested tissue and analyzed via RT- qPCR for the induction of key drug metabolizing enzymes and transporters (Figure B.5A). The genes examined included BChE, Cyp1a1, Cyp3a1, Ugt1a1, Sult1a1, Mdr1, and Bcrp. The l-

THP-treated rats exhibited no significant difference in the expression of these genes when compared to vehicle-treated rats.

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Figure B.3 Plasma concentration profile of cocaine is unchanged in the presence of l-THP. Rats were treated i.v. with vehicle (1 mL/kg saline) or l-THP (7.5 mg/kg b.i.d. for two and a half days followed by a single administration of cocaine (10 mg/kg, i.v.). Plasma samples were collected via aspiration of jugular vein catheters at predetermined time points. The cocaine concentration profile of rats pre-treated with l-THP was not significantly different from those pre-treated with vehicle (A). l-THP was readily absorbed following i.v. administration and quantified throughout the entire time course of the study (420 minutes) (B).

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Figure B.4 Brain concentrations of cocaine were elevated with l-THP co-treatment. Following the time course study described in Figure B.3, the brains of all rats were collected and analyzed for cocaine and l-THP concentrations. Rats treated with l-THP had significantly more cocaine present than rats treated with vehicle. l-THP was also present in the collected brain tissue. *, p < 0.05; ***, p < 0.001.

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B.3.5 Activity of P-gp is not altered by l-THP at physiologically-relevant concentrations. The induction of rat and human P-gp by l-THP was further examined in ATPase assays. In these studies, verapamil was used as a positive control (Figure B.6A, B). At pharmacologically- relevant concentrations (4 and 20 μM), l-THP had no effect on the activity of P-gp. It was observed that at an elevated concentration (100 μM) l-THP was able to stimulate the activity of

P-gp, but this concentration is higher than what was achieved in our PK study or has been reported in other animal or human studies.

B.4 Discussion

The use of and addiction to cocaine remain significant public health concerns in the United

States as well as many other countries with an estimated 17 million people using cocaine annually across the globe (American Psychiatric Association, 2013; United Nations Office on

Drugs and Crime, 2015). It was estimated in 2013 that in the United States there were 1.5 million cocaine users and fewer than half received treatment for cocaine use disorder (CUD)

(Substance Abuse and Mental Health Services Administration, 2014). l-THP has shown intriguing characteristics as a candidate for CUD as a modest antagonist of the D1, D2, and D3 receptors, as well as α1 adrenergic receptors and several 5-HT receptors (Liu et al., 2012).

Further, l-THP has been shown to enhance GABAergic transmission (Henkes et al., 2011). It is this unique profile of l-THP activity which makes it particularly appealing for potential treatment of CUD.

In the present study we sought to characterize the metabolism, transport, toxicity, gene expression of l-THP as well as the impact of multiple dose administration of l-THP on the PK of

241

Table B.2 Pharmacokinetic parameters of cocaine in the presence or absence of cocaine in rats.

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Table B.3 Pharmacokinetic parameters of l-THP in rats.

243 cocaine in rats to interrogate l-THP as a safe, therapeutic agent for treating CUD. MTT assays revealed that l-THP is non-toxic at concentrations up to 30 μM in both human and rat cell lines, which is greater than any concentration achieved in our metabolism or pharmacokinetic studies.

Beyond this concentration, cell viability decreased in a concentration-dependent manner.

Consistently, l-THP was well tolerated in vivo for doses as high as 20 mg/kg in rats (Mantsch et al., 2007; Xi et al., 2007) and as high as 55 mg/kg in dogs (data on file). In fact, antagonists of

D3 receptors have previously been shown to decrease the frequency of cocaine self- administration in rats, providing evidence of diminished reward (Galaj et al., 2014; Song et al.,

2014; Galaj et al., 2015).

Extensive safety and functional studies of l-THP have been conducted in China, however l-THP has not gained approval in the United States owing to presumed safety risks. These risks arise from toxicities associated with a Chinese adulterated preparation of l-THP known as Jin Bu

Huan which has been associated with hepatotoxicity and CNS depression (Woolf et al., 1994;

Horowitz et al., 1996). It is likely, however, that these observed toxicities arose from improper preparation and use, a commonly observed trend with herbal therapies (Wang and Mantsch,

2012). The dextro isomer of THP found in racemic preparations is believed to contribute to the toxicological profile of THP, but the levo isomer has demonstrated little-to-no toxicity in preclinical studies (Wang and Mantsch, 2012). Further, l-THP has been safely used clinically in

China within the range of 60-180 mg for over 40 years (Wang and Mantsch, 2012).

Cocaine is extensively metabolized, primarily by hydrolytic ester cleavage mediated by butyrylcholinesterase, with minor metabolic contributions from CYP3A4 (Gorelick, 1997; Zhan and Gao, 2005). In vitro metabolism studies using rat liver microsomes revealed that upon

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Figure B.5: l-THP does not alter the expression of key drug metabolizing enzymes and transporters in rat brains. At the cessation of the in vivo study, rat brains were harvested and mRNA was isolated, reverse transcribed, and examined for the expression of metabolizing enzymes and transporters including Cyp1a1, Cyp3a1, Ugt1a1, Sult1a1, Mdr1b, Bcrp, and BChE with qPCR as described in the materials and methods. Data presented are the mean ± SD of three independent experiments. No significant alterations in the expression of any of the examined genes were observed.

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Figure B.6: l-THP does not alter human or rat P-gp function at pharmacologically-relevant concentrations. Human and rat P-gp ATPase activity was evaluated using the Glo Assay System from Promega as described in the materials and methods. Verapamil (100 µM) was used as a positive control for P-gp activity induction. At pharmacologically-relevant concentrations (4 and 20 µM) l-THP had no impact on either human or rat P-gp activity. At an elevated concentration (100 µM) activity was significantly induced in both human and rat P-gp. Data presented are the mean ± SD of five independent experiments. *, p < 0.05; ** p < 0.01.

246 concomitant administration, the metabolism of cocaine is unaltered by l-THP. This is an advantage of l-THP for treatment of cocaine as concomitant administration of l-THP and cocaine does not lead to inhibition of cocaine metabolism increasing its toxicity. In rats, the plasma concentrations of cocaine and l-THP were quantified using a validated UPLC method. No statistical differences in plasma concentration of cocaine were observed at any of the recorded time points. Further, noncompartmental and compartmental PK analysis of both cocaine and l-

THP was performed using Phoenix WinNonlin software. Consistent with most previous reports, our cocaine PK data was best fit with a one compartment model, although some groups have proposed a two compartment model for the PK profile of cocaine (Booze et al., 1997; Mendelson et al., 1999; Zheng and Zhan, 2012). In the present study, no differences in any cocaine PK parameters were observed between groups including Cmax, Vss, Cl, t1/2, or AUC. Further, l-THP followed a two-compartment model which is in line with previous reports (Chao-Wu et al.,

2011). Taken together, these results indicate that while l-THP has significant effects brain receptors and cocaine-seeking behavior, it does not alter the pharmacokinetics of concomitantly administered cocaine, alleviating concerns regarding untoward toxicities that may arise from

DDIs.

In examination of brain homogenate following the seven-hour time course, it was observed that rats treated with l-THP retained greater cocaine concentrations in the brain suggesting that l-THP treatment results in longer exposure to cocaine. This accumulation may arise from the inhibition of an efflux transporter other than P-gp for which cocaine is a substrate. However, we postulate that this may be a mechanism of the therapeutic effects of l-THP. If cocaine remains in the brain for a longer time, an individual may not feel compelled to engage in drug-seeking activity as the

“high” achieved from cocaine administration is not short-lived. This mechanism is reminiscent

247 of nicotine replacement therapies which supply long-lasting amounts of nicotine to nicotinic acetylcholinergic receptors, treating withdrawal symptoms and eliminating peak plasma concentrations of nicotine associated with reward (Fant et al., 1999). Further, in line with previous reports, l-THP was able to readily enter the brain and accumulate. Given that l-THP increases extracellular dopamine, an individual pre-treated with l-THP may not experience the hypodopaminergic state associated with withdrawal from drug use. The absence of this state may protect against relapse and drug-seeking behavior due to adequate concentrations of monoamines.

Further, we deemed it fit to examine the induction of important drug metabolizing enzymes and transporters which could contribute to untoward drug-drug interactions by l-THP in treated rats and also to investigate a potential mechanism by which cocaine concentrations are elevated in the brain. Specifically, using RT-qPCR, we examined the inductive expression of BChE,

Cyp1a1, Cyp3a1, Ugt1a1, Sult1a1, Mdr1, and Bcrp in isolated rat brains. We chose these genes as they are known to be expressed in brain tissue, the site of action of cocaine and l-THP, and furthermore, cocaine is known to be a substrate of Mdr1, BChE, and Cyp3a1. qPCR analysis indicated that l-THP did not have any impact on the expression of any of these genes indicating that its administration should not alter the disposition of cocaine as mediated by these genes.

Further, as cocaine is a known P-gp substrate, we investigated the impact of l-THP on P-gp activity in ATPase assays. These studies revealed that l-THP can stimulate P-gp activity at supra- physiological concentrations (100 µM) in ATPase assays, but not at concentrations achieved in our DDI studies. Together these results show that l-THP administration does not alter the expression of key metabolizing enzymes and transporters that would lead to unexpected or untoward DDIs at physiological concentrations.

248

The objective of our study was to examine the potential for untoward toxicities arising from

DDIs between l-THP and cocaine. Our results demonstrated that administration of l-THP in rats does not alter the expression of the genes responsible for cocaine disposition. Further, the concomitant administration of l-THP had no impact on the pharmacokinetics of cocaine in rats.

Taken together, these results provide further evidence for potential safe and non-toxic clinical utilization of l-THP as a novel treatment for cocaine addiction.

249

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Appendix C: Administration of Methadone and Oxycodone Alters the Expression of Drug Metabolizing Enzymes and Transporters Affecting the Disposition of Cocaine in Rats

C1. Introduction

Illicit cocaine use has been a problem in the United States and around the world and it remains a significant public health concern with approximately 17 million people using cocaine across the globe annually(2015.). In 2014, around 900,000 Americans met the criteria outlined in the

Diagnostic and Statistical Manual of Mental Disorders for dependence on or abuse of cocaine in any form(2013.-a). Additionally, we have observed a significant increase in the number of fatalities associated with drug poisonings and opioid overdoses and drug overdose has become the leading cause of accidental death in the United States. In 2015 there were 52,404 reported lethal drug doses in the United States with 20,101 of these related to prescription pain relievers(Rudd et al., 2016).

Of increasing concern is the frequency with which cocaine is used concurrently with other commonly abused drugs. Further, cocaine abuse is known to occur frequently in individuals who are addicted to opioids and in methadone maintenance treatment(Grella et al., 1997; Leri et al.,

2003). In examining the national trend data, scientists at the National Institute on Drug Abuse

(NIDA), the National Center for Injury Prevention and Control (NCIPC) and the U.S.

Department of Health and Human Services observed that heroin and synthetic opioids are

254 driving the recently observed increase in cocaine-related overdose deaths. This report revealed that cocaine-related overdose deaths increased from 2000 to 2006, and declined between 2006 and 2010 which reflected the reduction in supply and increase in street prices of cocaine. Since

2010, however, cocaine-related overdose deaths have increased despite an overall decrease in cocaine use. The scientists involved in this study determined that this recent increase was largely driven by cocaine-related overdose deaths involving opioids, primarily heroin and/or synthetic opioids. This trend follows the recent increasing supply and use of heroin and fentanyl in the

United States(McCall Jones et al., 2017).

It has been reported that individuals with both cocaine and opioid use disorders have more significant drug use and legal problems as well as poorer outcomes regarding substance use treatment compared with individuals with either substance use disorder alone(Kumari et al.,

2016; Rodriguez-Cintas et al., 2016). It has also been shown that heroin use among cocaine users saw a significant increase between 2008 and 2010 as well as between 2011 and 2013. It was concluded in these studies that cocaine use disorder (CUD) was an important risk factor for both heroin and prescription opioid use disorder(Han et al., 2015; Jones et al., 2015).

Oxycodone is one of the most frequently prescribed opioid analgesics in the United States and oral oxycodone is reported as one of the most heavily abused of the commonly prescribed opioids(Wightman et al., 2012),(2014b). In 2013 nearly 60 million oxycodone prescriptions were filled and in 2012 an estimated 16 million Americans used oxycodone for non-medical purposes.

In 2011 oxycodone abuse led to over 150,000 ED visits and 43 deaths due to oxycodone abuse were reported. Of these, about 65,000 ED visits were related to oxycodone-containing products and nearly 14,000 of these ED visits were the result of oxycodone-related suicide attempts(2006;

S.A.M.H.S.A., 2011).

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Mounting preclinical evidence indicates the likelihood of important DDIs between oxycodone and other concomitantly administered drugs. There are conflicting reports in the literature regarding the impact of P-gp expression on the disposition of oxycodone. In rats, pre-treatment with known P-gp inhibitors has been shown to incur no difference in plasma pharmacokinetics or brain concentrations of oxycodone compared with controls indicating that oxycodone is likely not a substrate of P-gp(Bostrom et al., 2006). In a clinical study with 33 participants exposed to experimental pain, carriers of variant alleles C3435T and G2677T/A within the ABCB1 gene experienced fewer adverse drug events following administration of oxycodone administration(Zwisler et al., 2010). However, in an additional study performed in mother-infant breastfeeding pairs, mothers carrying one copy or more of the 2677T polymorphism were at an increased risk of oxycodone-induced sedation(Lam et al., 2013). Further, it was shown that cancer patients with the C3435T variant had little effect on the plasma concentration of oxycodone(Naito et al., 2011). In addition to these controversial results observed in clinical studies, oxycodone has been shown to significantly increase the expression of P-gp in various tissues in rats and this increase in expression has been associated with decreased tissue concentrations of paclitaxel, a known P-gp substrate(Hassan et al., 2007). Thus, existing literature regarding the pharmacokinetics and adverse events of oxycodone monotherapy remains inconsistent, and further inquiry into concomitant administration of oxycodone and other drugs which may be impacted by altered expression of P-gp and other transporters and metabolizing enzymes is warranted.

Methadone is the oldest synthetic opioid drug that is still prescribed and has been used for decades to aid in detoxification and treatment of opioid dependence(Tetrault et al., 2013; 2014a).

Recently, prescription rates for methadone have increased owing to its clinical efficacy in

256 treating moderate-to-severe pain and its cost-effectiveness(Nicholson, 2007; 2014a). Methadone has widely been reported to cause adverse events including QT prolongation and Torsades de

Pointes(Justo, 2006; Ehret et al., 2007). Following a significant increase in methadone-related deaths and adverse reactions the FDA issued a black box warning and public health advisory recommending prescribed methadone doses be carefully chosen and monitored by the prescriber.

In addition to these toxicities and adverse events, methadone has an extensive history of dependence and abuse. In 2012, the National Survey of Drug Use and Health (NSDUH) reported that nearly 2.5 million Americans over the age of 12 had used methadone in their lifetime for a non-medical purpose(2013.-b). In 2011 there were almost 67,000 ED visits related to non-medical methadone use; an increase of over 80% from 2004(S.A.M.H.S.A., 2011). There were 51 reported deaths resulting from methadone abuse in 2012 by the American Association for Poison Control Centers. Methadone is known to have highly variable and unpredictable pharmacokinetics between individual users. To this end, several studies investigating the transport mechanisms of methadone have been published(Callaghan and Riordan, 1993; Bouer et al., 1999; Stormer et al., 2001; Nanovskaya et al., 2005; Nekhayeva et al., 2005; Crettol et al.,

2007; Hemauer et al., 2009; Beghin et al., 2010; Tournier et al., 2010; Linardi et al., 2013).

However, there remains a clear gap in the literature regarding the interactions between methadone and other illicit drugs and their consequences.

With our present studies, we seek to begin filling this literature void by investigating the impact of concomitant administration of methadone or oxycodone on the pharmacokinetics of cocaine in rats. We have developed sensitive and selective HPLC-UV and LC-MS/MS methods for the quantification of cocaine, methadone, and oxycodone in rat serum and brain tissue samples, and further have examined the inductive expression of key drug metabolizing enzymes and

257 transporters in liver, kidney, and brain tissues of treated rats. Our results provide a platform for investigating the significant DDIs that occur between opioids and cocaine and demonstrate the importance of the study of these interactions.

C.2 Materials and Methods

C.2.1 Materials Methadone hydrochloride and cocaine were purchased from Sigma-Aldrich (St. Louis, MO,

USA). Levo-tetrahydropalmatine (l-THP) (internal standard) was acquired from WuxiGorunjie

Technology Co., Ltd. (No. 97, Wuqiao West Road, Wuxi, Jiangsu, 214044CN). Oxycodone was obtained from Normaco, Inc. (Wilmington, DE). Oxycodone-D3 (internal standard) was purchased from Cerilliant Corporation (Round Rock, TX, USA). Solvents used in the HPLC methods were HPLC-grade; acetonitrile and methanol were obtained from Sigma-Aldrich (St.

Louis, MO, USA), and those for the LC-MS/MS method were LC-MS-grade; acetonitrile, methyl-t-butyl ether, formic acid, and water were obtained from Fisher Scientific (Fair Lawn,

NJ, USA). Ammonium hydroxide, potassium phosphate monobasic salt, and hexanes were also purchased from Fisher Scientific. Water was purified with a Milli-Q filtration system (Millipore,

Milford, MA, USA). Blank Sprague-Dawley rat serum was obtained from Valley Biomedical

(Winchester, VA, USA). Blank brain homogenate was prepared by mixing fresh brain tissue obtained from untreated animals with saline (1:2 w/v) obtained from Baxter International Inc.

(Deerfield, IN). The mixture was homogenized using a Fisher Scientific PowerGen Model 125 homogenizer in 5 mL vials. Samples were centrifuged in a temperature-controlled Eppendorf®

5417R centrifuge. Organic solvents were evaporated using a Multi-vap nitrogen evaporator.

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C.2.2 Animal Subjects Adult male Sprague-Dawley rats (250-300g) were purchased from Harlan Laboratories

(Frederick, MD). The rats were housed in the animal facility of the University of Maryland

School of Medicine and were maintained at a temperature of 72 ± 2°F on a light/dark cycle of 12 hours. Food (Purina 5001 Rodent Chow, Purina, St. Louis, MO) and water were available to the rats ad libitum. The protocol for this animal study was approved by the Institutional Animal

Care and Use Committee of the University of Maryland School of Pharmacy. The animal facilities were accredited by the American Association of Laboratory Animal Care are all experiments were conducted in accordance with the National Institutes of Health Guide for the

Care and Use of Laboratory Animals.

C.2.3 Quantification of Cocaine, Methadone, and Oxycodone A sensitive high-performance liquid chromatography (HPLC) assay with dual UV detection was developed and validated for the simultaneous quantification of methadone and cocaine in rat serum and brain tissue samples in our laboratory (Nakhla et al., 2017). Preparation of serum and brain samples involved liquid-liquid extraction methods using hexanes for the extraction of target analytes. Aliquots of 500 µL of serum and brain samples were spiked with the internal standard (15 µg/mL l-THP in methanol). Samples were alkalinized with 100 µL ammonium hydroxide and vortexed slightly. 1 mL of hexanes was added, and the samples were vortexed briefly followed by high speed shaking for 20 minutes and subsequent centrifugation at 14,000 rpm at 4°C. The upper organic layer of 0.8 mL was aliquoted into clean Eppendorf® microcentrifuge tubes and evaporated to dryness under a nitrogen stream. The residue was reconstituted with 50 µL of the mobile phase and a 30 µL aliquot was injected into the HPLC

259 system. The HPLC system consisted of a Waters® (Milford, MA) Alliance 2695 module coupled with a 2487 photodiode array detector. Analytical separation was performed on a

Waters Symmetry C18 analytical column (150 x 4.6 mm, 5 µm) with a C18 guard column (4 x 3 mm, 5 µm) from Phenomenex (Torrance, CA). The mobile phase consisted of a mixture of (A)

5mM potassium phosphate monobasic in water with 0.1% triethylamine (pH 6.5) and (B) acetonitrile (ACN). The initial gradient conditions were 50% (B) for 8 minutes, increased to

90% and maintained at this concentration for an additional 6 minutes. The flow rate throughout was set to 1 mL/min. The total run time was 23 minutes. Detection was carried out at 215 and

235 nm for methadone and cocaine, respectively. The lower limit of quantitation for both methadone and cocaine was 0.05 µg/mL with a linearity range of 0.05 to 10 µg/mL.

An ultra-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the quantification of oxycodone in rat serum and brain tissue samples. A simple liquid-liquid extraction technique using methyl-t-butyl ether was utilized for serum and brain tissue samples. Aliquots of 500 µL of serum and brain samples were spiked with 10 µL of 500 ng/mL oxycodone-D3 (internal standard). 1 mL methyl-t-butyl ether was added, vortexed for 10 seconds, shaken at high speed for 20 minutes, and then centrifuged at

14,000 rpm for 30 minutes at 4°C. 800 µL from the upper organic layer was pipetted into a clean

Eppendorf® microcentrifuge tube and evaporated to dryness under a stream of nitrogen. The residue was then reconstituted in 40 µL of mobile phase and a 10 µL aliquot was injected into the UPLC system. Chromatographic analysis was carried out using a conventional reverse-phase

Waters Symmetry C18 analytical column (100 x 4.6 mm, 5 µm) with a Phenomenex Luna® security guard column (4 x 3 mm, 5 µm). The column temperature was maintained at 60°C.

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Isocratic elution was programmed using ACN:0.1% formic acid in LC-MS-grade water (pH 2.7)

(15:85 v/v) as the mobile phase with a flow rate of 0.4 mL/min. Tandem mass spectrometric analysis was carried out using positive electrospray ionization in MRM mode for the detection of oxycodone and its isotopically-labeled internal standard (oxycodone-D3). The mass spectrometry parameters were optimized for oxycodone and its internal standard to the following protonated ions: m/z 316.10 →198.18 [M + H] + (oxycodone), m/z 319.16 → 301.18 [M + H] +

(oxycodone-D3) to achieve maximum sensitivity. The analysis was performed in five minutes over a concentration range of 10-2000 ng/mL for oxycodone. Both methods were validated according to the FDA guidance for bioanalytical method validation (###) by replicate injection of quality control samples. Accuracy and precision of all compounds were of satisfactory results below 11.89% of CV.

C.2.4 Evaluation of gene induction with RT-qPCR mRNA was isolated from brain, liver, and kidney tissue harvested from rats treated with control

(saline), cocaine (dose), oxycodone plus cocaine (doses), and methadone plus cocaine (doses) with TRIzol Reagent (Life Technologies). Isolated mRNA was reverse-transcribed using a High

Capacity cDNA Archive Kit (Applied Biosystems) following the manufacturer’s instructions. mRNA expression of Cyp3a1, Cyp2b2, Mdr1, Oatp1b, Bcrp, and BChE was normalized against that of Gapdh. Real-time PCR assays were performed on a StepOnePlus Real-Time PCR System with SYBR Green PCR Master Mix (Applied Biosystems). The primer sequences used for these experiments are listed in Table C.1. The fold induction of the genes of interest versus control was determined as 2∆∆Ct where ∆Ct is representative of the cycle threshold number difference between the gene of interest and the Gapdh control, and ∆∆Ct represents the relative changes in the inter-group variations. The statistical significance for these experiments was determined at p

< 0.05 as outlined under the statistical analysis section.

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Table C.1: Primers utilized in qPCR studies in treated rat liver, kidney, and brain tissue.

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C.2.6 Western blotting analysis Homogenate proteins from control and treated rat liver, kidney, and brain tissues were resolved on NuPAGE Bis-Tris 4% to 12% gradient gels (Thermo Fisher Scientific) and electrophoretically transferred onto immobilon-P polyvinylidene difluoride membranes.

Membranes were incubated with specific antibodies against P-gp (ID Laboratory, ON, Canada),

Bcrp (Abcam), Oatp-c (Santa Cruz Biotechnology), Cyp3a1 (Cell Signaling), diluted 1:1000,

1:500, 1:1000, 1:5000, respectively. β-actin (1:50,000 dilution) was used to normalize protein loading. Following incubation with horseradish peroxidase goat anti-mouse or anti-rabbit IgG antibodies, membranes were developed using SuperSignal West Pico or Femto

Chemiluminescent Substrate (Thermo Scientific). Western blot signals were quantified by densitometry using ImageStudio Software. Target protein signal intensity was normalized against that of the loading control, β-actin.

C.2.7 Statistical analyses All values were presented as mean ± SEM. Students t-test, analysis of variance (ANOVA) with repeated measures, or ANOVA followed by either Dunnett’s or Bonferroni’s posthoc tests were used to determine statistical significance between groups. The criterion of significance was set at the 0.05 level of probability.

C.3 Results

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C.3.1 Administration of oxycodone and methadone alters the expression of drug metabolizing enzymes and transporters in rats. The mRNA expression of key drug metabolizing enzymes and transporters including Cyp3a1,

Cyp2b2, Mdr1a, Bcrp, Oat1, Oat3, Oct2, Bsep, Oatp1b1, and Oatp1b3 was examined in liver, kidney, and brain tissues from rats treated with vehicle (saline), cocaine (10 mg/kg i.p.), cocaine and oxycodone (10 mg/kg i.p., 5 mg/kg i.p.), or cocaine and methadone (10 mg/kg i.p., 7 mg/kg i.p.) via RT-qPCR and western blotting, respectively. These genes were selected as they were either implicated in the FDA Guidance on drug interactions or known to have an impact on the disposition of cocaine. Those genes showing differential mRNA expression were carried forward for western blotting analysis of protein expression.

In liver tissue treatment with oxycodone increased the mRNA expression of Mdr1a, Bcrp,

Oatp1b, Cyp2b2, and Cyp3a1 9-. 15-, 4-, 6-, and 9-fold, respectively, corresponding with respective increases in protein expression of 4-. 12-, 4-, 2- and 3-fold (Fig. C.1A, B). Methadone induced the mRNA expression of Mdr1a, Bcrp, Oatp1b, Cyp2b2, and Cyp3a1 by 8-, 6-. 8-, 10-, and 16-fold (Fig. C.1C, D). The expression of these proteins was induced by methadone by 3-, 7-

. 5-. 4-, and 8-fold, respectively. No differences were observed in the expression of these genes or proteins in the group treated with only cocaine.

Oxycodone treatment increased the mRNA expression of Mdr1a, Bcrp, Oatp1b, and Cyp3a1 in kidney tissue by 7-, 12-. 5-, and 2-fold, respectively. The expression of P-gp, Bcrp, Oatp-c, and

Cyp3a1 protein was increased by 2-, 3-, 4-fold by oxycodone, respectively, but no change was observed in the expression of Cyp3a1 following oxycodone treatment (Fig. C.2A, B). Methadone treatment induced the mRNA expression of Mdr1a, Bcrp, Oatp1b, and Cyp3a1 6-, 13-, 9-, and 4-

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Figure C.1: Repeated administration of oxycodone and methadone alters the expression of drug metabolizing enzymes and transporters in rat liver. Expression of key drug metabolizing enzymes and transporters was examined in treated rat liver tissue. mRNA of P-gp, Abcg2, Oatp1b2, Cyp3a1, and Cyp2b2 was significantly induced by oxycodone and methadone (A). These genes were carried forward for protein expression analysis via western blotting (B). Western blot images are representative of 3 separate individuals. Western blot results were quantified with ImageStudio Software. Data represent mean ± SD (n = 6 for qPCR, n=3 for western blot); *: p < 0.05; **: p < 0.01; ***: p < 0.001.

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Figure C.2: Oxycodone and methadone treatment changes the mRNA and protein expression of important drug transporters and metabolizing enzymes in rat kidney. qPCR analysis and western blotting were carried out to examine the mRNA (A) and protein (B) expression of several important drug metabolizing enzymes and transporters of rats treated with oxycodone or methadone prior to cocaine challenge. Significant induction of mRNA and (protein) was observed in Mdr1a (P-gp), Abcg2 (Bcrp), Slco1b2 (Oatp1b2), and Cyp3a1 (Cyp3a1) in treated rat kidneys. Western blot images are representative of 3 separate individuals. Western blot results were quantified with ImageStudio Software. Data represent mean ± SD (n = 6 for qPCR, n=3 for western blot); *: p < 0.05; **: p < 0.01; ***: p < 0.001.

266 fold, respectively which corresponded with increases in protein expression of P-gp, Bcrp, and

Cyp3a1 of 3-, 7-, 5-, and 2-fold, respectively (Fig. C.2C, D). Cocaine alone did not lead to any changes in the expression of these genes or proteins. Modest induction of P-gp, Bcrp, and

Oatp1b mRNA and protein was observed in isolated brain tissue following treatment with oxycodone and methadone. With oxycodone treatment, the mRNA of Mdr1a, Bcrp, and Oatp1b was induced 6-, 12-, and 4-fold, respectively, and the 6-, 8-, and 4-fold, respectively, corresponding with increases in P-gp, Bcrp, and Oatp-c protein of 2-, 4-, and 2-fold (Fig. C.3C,

D).

C.3.2 Quantification of cocaine, oxycodone, and methadone in rat serum and brain tissue homogenate With our analytical methods we were able to quantify cocaine, methadone, and oxycodone in serum and brain. We were able to successfully quantify baseline cocaine parameters over a 120- minute time course in both serum and brain tissue homogenate (Fig. C.4A, B). In serum, oxycodone and methadone were able to be quantified out to 120 and 360 minutes, respectively

(Fig. C.4C, D), and in brain tissue they were quantified over 240 and 360-minute experiments, respectively (Fig. C.4E, F). In the presence of oxycodone, cocaine was quantifiable in serum and brain tissue homogenate 60 and 120 minutes, respectively (Fig. C.5A,B). When cocaine was co- administered with methadone, cocaine was able to be quantified over 120 minutes in both rat serum and brain tissue (Fig. C.5C, D).

C.3.3 Changes in expression of drug metabolizing enzymes and transporters by oxycodone and methadone alters the PK of cocaine in rats Noncompartmental pharmacokinetic analysis was performed for oxycodone, methadone, cocaine without co-treatment, cocaine in the presence of oxycodone, and cocaine in the presence of

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Figure C.3: Expression of drug metabolizing enzymes and transporters in rat brain is altered by repeated administration of methadone and oxycodone. Following pre-treatment with oxycodone or methadone and cocaine challenge, the expression of key drug metabolizing enzymes and transporters including Mdr1a (P-gp), Abcg2 (Bcrp), and Slco1b2 (Oatp1b2), was examined in brain tissue. Western blot images are representative of 3 individual experiments and results were quantified using ImageStudio Software. Data represent mean ± SD (n = 6 for qPCR, n=3 for western blot); *: p < 0.05; **: p < 0.01; ***: p < 0.001.

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Figure C.4: Baseline plasma and brain concentration profiles of cocaine, oxycodone, and methadone in rats. Using our validated UPLC and LC-MS/MS methods, we were able to establish baseline plasma and brain concentration profiles of cocaine (A, B), oxycodone (C, D), and methadone (E, F) in rats. Cocaine was able to be quantified in both serum and brain tissue for 120 minutes, oxycodone was quantifiable in serum over 120 minutes and brain tissue for a 240-minute time course, and methadone could be quantified over 360 minutes post-dose.

269 methadone in serum and brain tissue (Table C.2). In the presence of oxycodone the serum half life (t1/2) of cocaine was decreased from 63 to 19 min while methadone co-treatment reduced the serum t1/2 of cocaine to 33 min. The brain t1/2 of cocaine was reduced by oxycodone and methadone treatment from 88 min in the control group to 20 and 26 minutes, respectively. The observed maximum concentration (Cmax) of cocaine in serum in the control group was 2655 ng/mL. In the oxycodone- and methadone-treated groups the Cmax of cocaine was 2009 and 3296 ng/mL, respectively. In brain, the Cmax of cocaine in the control group was 1982 ng/g and the observed Cmax of cocaine in brain tissue in the oxycodone- and methadone-treated groups was unchanged at 1950 and 2160 ng/g, respectively. The time at which Cmax was observed (Tmax) for cocaine in serum for all groups was 5 minutes. In brain however, the Tmax was 10 minutes in the control and methadone-treated groups, but in the oxycodone-treated group, Tmax was 5 minutes.

The overall serum exposure to cocaine as determined by the area under the curve (AUC) was

47,726 min*ng/mL in the control group. This was reduced to 29,075 and 37,493 min*ng/mL in the oxycodone-, and methadone-treated groups, respectively. In the brain, the AUC of cocaine in the control group was 85,794 min*ng/g which was remained unaltered in the treatment groups with AUC measurements of 91,380 and 99,844 min*ng/g respectively in the oxycodone- and methadone-treated groups. The AUCbrain/AUCserum ratio was increased by co-treatment with oxycodone and methadone from 1.8 to 3.1 and 2.7, respectively. The clearance of cocaine was significantly increased with the co-administration of oxycodone to 316 mL/(min/kg) from 173 mL/(min/kg) in the control group while this parameter was unchanged by the co-treatment with methadone at 193 mL/(min/kg).

270

Figure C.5: Altered expression of drug metabolizing enzymes and transporters by oxycodone and cocaine alters the pharmacokinetics of cocaine. Following concomitant administration of either oxycodone (A, B) or methadone (C, D) with cocaine, the concentration profiles of cocaine in both serum and brain tissue was significant altered. In the presence of oxycodone, cocaine was only quantifiable in serum for 60 minutes, while it remained able to be quantified for 120 minutes in brain tissue. Following co-treatment with methadone, cocaine was quantifiable in serum for only 60 minutes in both serum and brain tissue.

271

Table C.2: PK parameters of oxycodone, methadone, and cocaine alone or with oxycodone or methadone.

272

C.4 Discussion

The use and abuse of cocaine as well as prescription opioid pain relievers remain a significant public health concern both in the United States and globally. It has also been shown that cocaine use occurs frequently in people who are addicted to opioids and those who are undergoing methadone maintenance therapy. Further, despite an overall decrease in cocaine use nationally, over the past several years officials have reported an increase in mortality rates arising from cocaine-related overdoses. This rate is being driven by the recent increase observed in cocaine- related overdose deaths involving concomitant use of opioids including synthetic opioids and heroin.

Opioids have been utilized extensively for the management of pain for decades. However, there remains a lack of studies examining their ability to modulate the expression of drug transporters and/or metabolizing enzymes. Previous reports have indicated that methadone is a strong activator of both CAR and PXR in human primary hepatocytes resulting in the potent induction of P-gp, CYP3A4, CYP2B6 and UGT1A1(Tolson et al., 2009). Further, oxycodone has been demonstrated to regulate the expression of many DMEs and transporters including P-gp, Bcrp, and glutathione-S-transferase in multiple tissues in rats(Hassan et al., 2007; Myers et al., 2010;

Hassan et al., 2013).

It is important to understand potential changes in the expression of transporters and DMEs mediated by opioids as they can result in significant pharmacokinetic and pharmacokinetic DDIs.

Our group previously demonstrated that oxycodone induces Abcb1 in liver, kidney, brain, and intestinal tissue limiting the accumulation of paclitaxel, a known P-gp substrate, in these tissues

(Hassan et al., 2007). Further, we have demonstrated that Bcrp is significant upregulated in rat brain tissue by oxycodone which restricts the uptake of known Bcrp substrate

273 mitoxantrone(Hassan et al., 2010). However, the impact of concomitant administration of oxycodone or methadone on the disposition of cocaine has never been investigated, and due to the increasing rate of cocaine use-related ED visits and deaths is of high importance.

In the present study we examined the impact of concomitant administration of oxycodone and methadone on the expression of key drug metabolizing enzymes and transporters and the resulting difference in cocaine pharmacokinetics. Pre-treatment of rats with methadone or cocaine significant altered the expression of several drug metabolizing enzymes and transporters frequently implicated in drug-drug interactions including Cyp2b2, Cyp3a1, P-gp, Bcrp, Oatp1b.

The modulated expression of these genes and proteins resulted in significant alterations in the pharmacokinetics of cocaine. Notably, in the presence of oxycodone, the clearance of cocaine was significantly increased from 173 mL/(min/kg) to 316 mL/(min/kg). Further, the

AUCbrain/AUCserum ratio was significantly increased in both co-treatment groups over the control.

While the AUCbrain in each group remained unchanged, the AUCserum was significantly reduced in the methadone- and oxycodone-treated groups to 29,075 and 37,493 min*ng/mL, respectively, from 47,726 min*ng/mL in the control group.

In conclusion, this is the first report, to our knowledge, to examine the in vivo DDI between cocaine and frequently abuse opioid pain medications oxycodone and methadone. Our results, in line with previous studies, demonstrate that repeated administration of oxycodone or methadone alter the expression of several important drug transporters and metabolizing enzymes in multiple tissues in rats. These changes in expression result in significant changes in the pharmacokinetics of cocaine in the treated rats. This research will begin to fill the current void in literature regarding the pharmacokinetic impact of concomitant administration of opioid pain relievers with cocaine which is necessary as despite a decrease in overall cocaine use, cocaine-related ED

274 visits and deaths have increased owing to co-use with other medications. We acknowledge that significant species differences exist between rats and humans and this the translation of these in vivo finding to humans should be done cautiously.

275

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278

Appendix D: Antibody-Drug Conjugates: PK/PD modeling, preclinical characterization, clinical studies, and lessons learned

D.1 Introduction

Despite significant improvements in therapeutic agents and surgical techniques, cancer remains the second leading cause of death in the United States (Global Burden of Disease Cancer et al.,

2015). Chemical-based treatment of cancer gained significant interest in the early 1900s. Paul

Ehrlich, the esteemed German chemist, first sought to treat infectious diseases with chemical agents, coining the term “chemotherapy”. Ehrlich was also interested in using chemical drugs to treat cancers, though his success was limited (DeVita and Chu, 2008). In his career, Ehrlich described his vision of a “magic bullet” therapy which would be utilized to target and kill diseased tissues while leaving healthy tissues intact (Schwartz, 2004). Until the 1960s conventional treatment of cancer employed surgical and radiotherapeutic approaches, until it was realized that the addition of drugs to these therapies could allow practitioners to optimize tumor treatment while limiting unwanted toxicities (DeVita, 1978; DeVita and Chu, 2008). Since then, countless chemotherapeutic agents have been designed, tested, and marketed for many diseases.

However, curative rates of treatment leave room for improvement for a number of reasons including acquired multidrug resistance, insufficient target specificity, and intolerable toxicities

(Plenderleith, 1990). There remains an unmet need to develop new therapeutic modalities that specifically target cancer cells and exhibit relatively minimal side effects. As a result,

279 immunotherapy was explored as a new modality that carries a great potential for treatment of cancer mainly due to its target specificity (Schietinger et al., 2008).

Immunotherapy dates back to the 1970s and the development of hybridoma technology allowing for the reliable production of antibodies first by Kohler and Mistein (Kohler and Milstein, 1975).

In 1980, the first patient with relapsed lymphoma was treated with therapeutic antibodies after in vitro screening showed promising anti-tumor activity. While this initial trial proved unsuccessful due to a lack of prolonged efficacy in patients, the development of these biological agents continued as they were generally well tolerated and today over 60 monoclonal antibodies have been approved for treatment of various health conditions (Figure D.1), most prevalently in the field of oncology (Nadler et al., 1980; Ritz and Schlossman, 1982).

Monoclonal antibodies are highly specific and can bind to the same antigenic epitope due to the fact that they are secreted from identical immune cells that are all clones of a unique parent cell.

This makes monoclonal antibodies attractive therapeutic tools for targeted therapeutic approaches. In addition to treating cancer, monoclonal antibodies can be used to treat certain forms of arthritis, systemic lupus erythematosus (SLE), multiple sclerosis (MS), inflammatory bowel disease (IBD), and other autoimmune diseases (Berger et al., 2002). Four major antibody types have been developed: murine, chimeric, humanized, and human. The guiding principle was to develop antibodies that can escape immunological rejection by the host while still maintaining their bioactive properties (Liu, 2014). Murine antibodies, denoted with the suffix ‘-omab’, were the first to be developed into therapeutics. The major drawback to these therapeutics was the recognition by the host as foreign proteins and the development of vigorous immune responses resulting in adverse events, increased drug clearance (Cl), and reduced efficacy (Courtenay-Luck et al., 1986). This led to the idea of the development of chimeric antibodies (suffix, ‘-ximab’)

280

Figure D.1: Timeline of the US Food and Drug Administration approval of monoclonal antibody therapeutics and antibody–drug conjugates. Antibody–drug conjugates discussed in this review are highlighted with a yellow star. The color of each block denotes the type of antibody: blue, murine; red, chimeric; orange, humanized; green, human. *This timeline only includes therapeutics approved at the time of writing this review (2017). The number of approvals between 2015 and 2017 is in line with the increasing trend in approved biologic therapeutics. Figure used with permission of the copyright holder, Springer Publishing Group.

281 made by fusing varying ratios of murine antigen-binding domains with human effector domains.

The human sequences usually represent about 70% of the whole protein. Due to the incorporation of more human proteins, these antibodies were not as foreign to the immune system as murine antibodies and thus exhibited decreased immunogenicity and increased serum half-life (t1/2) (Zuckier et al., 1998). The most successful chimeric monoclonal antibody to date is rituximab, an anti-CD20 antibody utilized in the treatment of B-cell lymphomas (Edwards et al.,

2004). It has also proven effective in the treatment of autoimmune diseases such as rheumatoid arthritis and MS (Edwards et al., 2004; Hauser et al., 2008). Most antibodies being developed today are either humanized (suffix, ‘-zumab’) generated by combining mouse hypervariable regions with human constant domains, or fully human (suffix, ‘-umab’) produced in transgenic mice or by using phage display technology. The humanized antibodies boast over 90 percent human sequences and are thus less foreign to the immune system than chimeric antibodies. The main difference between humanized and human antibodies is that humanized antibodies have non-human origins. Trastuzumab and adalimumab represent two of the most successful humanized and human antibodies on the market today, respectively (Furst et al., 2003; Piccart-

Gebhart et al., 2005).

Antibody drug conjugates (ADCs) are an emerging class of biopharmaceutical agents designed for targeted treatment primarily for cancer patients. These conjugate drugs closely resemble the

“magic bullet” vision of Paul Ehrlich. By conjugating active drug moieties to targeted antibodies, ADCs are designed to attack only cancerous cells while remaining non-toxic to healthy tissue (Kovtun et al., 2006; Kovtun and Goldmacher, 2007; Ducry and Stump, 2010).

This targeted delivery of antineoplastic agents is designed to enhance the potency of antibody therapeutics while widening the often-narrow therapeutic index of chemotherapeutic drugs

282

Figure D.2: Antibody–drug conjugate (ADC) assembly and interaction with target cells. (A) Assembly of an ADC. (B) Typical mechanism of action of an ADC. The administered ADC binds to antigens expressed on the surface of target tumor cells. Following binding, the ADC is internalized. Some of the ADC is recycled back to circulation by the neonatal Fc receptor (FcRn). The remainder of the ADC is trafficked from the late endosome to the lysosome where the antibody is degraded and the linked drug is released. The free drug enters the nucleus of the cell and damages DNA leading to cell death. Figure used with permission of the copyright holder, Springer Publishing Group.

283

(Kovtun et al., 2010). The process of ADC binding, internalization, cleavage, and cytotoxicity is described in Figure D.2. Briefly, the monoclonal antibody moiety of the ADC will bind to the target antigen on the surface of cells. The entire ADC complex is then internalized, the conjugated drug is released, and the cell is killed by the cytotoxic effect of the conjugated drug.

This strategy has also been employed for overcoming multidrug-resistance in target cells

(Loganzo et al., 2016).

To date, only 4 ADCs have received FDA approval. The first of which, gemtuzumab ozogamicin (Mylotarg®), was approved in 2001 for the treatment of acute myelogenous leukemia (AML). It was withdrawn from the market in June 2010 as it was linked to a serious and potentially fatal liver condition known as veno-occlusive disease. Gemtuzumab ozogamicin was resubmitted for approval with a fractionated dosing regimen and was recently (September

2017) approved by the FDA for the treatment of adults with newly diagnosed CD33+ AML and adults and children 2 years and older with relapsed or refractory CD33+ AML. 3 other FDA- approved ADCs remain on the market including brentuximab vedotin (Adcetris®) for treatment of CD30+ Hodgkin lymphoma (HL) and systemic anaplastic large cell lymphoma (sALCL), trastuzumab emtansine (Kadcyla®) for treating human epidermal growth factor 2 (HER2)- positive metastatic breast cancer, and inotuzumab ozogamicin (Besponsa ®) which targets

CD22+ non-Hodgkin lymphoma (NHL) and was recently approved for use. The structure and targets of these ADCs are listed in Table D.1 (Diamantis and Banerji, 2016; FDA News Release,

2017).

There are several factors contributing to the overall efficacy of ADC therapies including tumor penetration and accumulation, target binding and cellular uptake, release of active catabolic products within the target cells and the potency of these products, as well as the PK profile of the

284

ADC Name Antibody Target Linker Payload Origin Gemtuzumab Humanized CD33 4-(4-acetylphenoxy)butanoic NAC ozogamicin acid Brentuximab Chimeric CD30 valine-citrulline MMAE vedotin Trastuzumab Humanized HER2 MCC DM1 emtansine Inotuzumab Humanized CD22 4-(4-acetylphenoxy)butanoic NAC ozogamicin acid Abbreviations: CD20/22/30, B-cell receptor CD20/22/30; DM1, emtansine; HER2, human epidermal growth factor receptor 2; MMAE, monomethyl aurostatin E; NAC, N-acetyl-γ- calicheamicin

Table D.1: Structure and targets of clinically approved ADCs.

285

ADC. The significant majority (~98%) of the total ADC is comprised by the antibody component and the PK of the ADCs are influenced greatly by the properties of the antibody backbone. Antibody properties governing ADC PK include target specific binding, neonatal Fc receptor (FcRn)-dependent recycling, and Fc (Fragment, Crystallizable) effector functions, and

ADCs exhibit the same ADME properties associated with unconjugated antibodies including low volume of distribution, slow Cl, long t1/2, and proteolysis-mediated catabolism (Lobo et al.,

2004; Lin et al., 2013). Applications and recommended PK considerations of various ADCs have been the subject of numerous review articles (Lin and Tibbitts, 2012; Bornstein, 2015; Kamath and Iyer, 2015). In addition to PK challenges, ADCs come with risks of toxicity and immunogenicity which can be mediated by any of the components of the ADC complex.

Expression of a target antigen on normal cells can lead to toxicity in healthy tissue and early cleavage of the linker leading to drug release can result in more systemic toxicities. The majority of the reported toxicity from ADCs, including those discussed in this article, arises from the payload drug. Monomethyl aurostatin E

(MMAE) has been associated with peripheral neurpathy and neutropenia while emtansine (DM1) is known to cause thrombocytopenia and elevated liver enzymes (Donaghy, 2016). In the cases of brentuximab vedotin and gemtuzumab ozogamicin, ADC immunogenicity has been reported manifesting as infusion reactions and transient shortness of breath, respectively (Hanbali et al.,

2007; Baxley et al., 2013) . Immunological rejection is another caveat and is often associated with negative impacts on the pharmacokinetic properties of the drug such as increased drug Cl.

Impacts of these risks on efficacy and safety of the drug formulations need to be carefully assessed.

286

Table D.2: Clinical studies performed with approved ADCs.

Antibody-Drug Year Study Design Major Findings Reference

Conjugate

gemtuzumab 2001 PK study in 59 AML patients Determined Cmax, t1/2, (Dowell et

ozogamicin in first relapse given single- AUC, Cl al., 2001)

agent (9 mg/m2), 2 doses 2

weeks apart Observed elevated plasma

levels following second

administration

2001 29 male and 29 female Age has no impact (i.e., (Korth-

patients of mean age 53 ± 16 non-significant covariate) Bradley et

years given 2 h IV infusion on PK of gemtuzumab al., 2001)

(9 mg/m2), single 2-hour ozogamicin

infusion

2004 29 pediatric AML patients Mean PK values in (Buckwalte

given 6, 7.5, or 9 mg/m2 pediatric patients similar r et al.,

gemtuzumab ozogamicin, 2 to those reported in adult 2004)

doses, 14-28 days apart populations

Adult and pediatric

patients exhibit large

inter-individual PK

variability

287

Table D.2 continued

2009 PK study in 40 Japanese Japanese patients (Kobayashi

patients with demonstrated a similar et al., 2009)

relapsed/refractory AML, 2 toxicity profile as other

doses (9 mg/m2) 2 weeks ethnicities

apart. Japanese patients

remained in remission

longer than previous

reports in other ethnic

groups

brentuximab 2011 Dose-escalation (0.4-1.4 MTD determined to be (Fanale et

vedotin mg/kg days 1, 8, 15) study to 1.2 mg/kg in this al., 2012)

determine MTD in patients population

with relapsed/refractory

CD30+ hematologic

malignancies, dosed weekly

2014 Combination of brentuximab 88% objective response (Fanale et

vedotin with rituximab, 2 rate when brentuximab al., 2014)

cycles of brentuximab vedotin was administered

vedotin (1.8 mg/kg) followed simultaneously with

by 6 cycles of CHOP or rituximab, while 85%

brentuximab plus CHOP objective response rate

once every 3 weeks when adminiswtered in

succession with rituximab

288

Table D.2 continued

trastuzumab 2010 Dose escalation study in 24 MTD determined to be (Krop et

emtansine patients. Dose range 0.3-4.8 4.8 mg/kg al., 2010)

mg/kg every 3 weeks

t1/2 = 3.5 days

Cl greater at doses less

than 1.2 mg/kg

2011 Administered at 3.6 mg/kg in Strong anticancer activity (Burris et

112 patients once every 3 and well tolerated as a al., 2011)

weeks as a single agent single agent at this dose

2012 PK study in HER2+ breast PK of single agent (Girish et

cancer patients given at 3.6 trastuzumab emtansine al., 2012)

mg/kg as a single agent once was well characterized

every 3 weeks and consistent with

previous reports

Exposure to trastuzumab

emtansine does not

correlate with clinical

response or adverse

events

289

Table D.2 continued

2012 Dose escalation (1.2-2.4 MTD when administered (Beeram et

mg/kg) with weekly dosing weekly determined to be al., 2012)

in 28 patients to determine 2.4 mg/kg

MTD, safety, tolerability, and

PK at this dosing frequency Exposure to drug in

patients is dose-

proportional at doses less

than 1.2 mg/kg

2015 PK, toxicity, MTD examined MTD in Japanese patients (Yamamoto

in 10 Japanese patients with matched other ethnic et al., 2015)

HER2+ breast cancer. Dose groups, 3.6 mg/kg

escalation study from 1.8 to

3.6 mg/kg every 3 weeks

2016 73 Japanese patients with Safety and efficacy (Kashiwaba

previously treated HER2+ profile of trastuzumab et al., 2016)

breast cancer given 3.6 emtansine in Japanese

mg/kg trastuzumab populations closely

emtansine every 3 weeks matches other

investigated ethnic

populations

290

Table D.2 continued

inotuzumab 2006 Dose escalation study (0.4- Determined MTD of (Advani et

ozogamicin 2.4 mg/m2) at 14 European inotuzumab ozogamicin al., 2005;

and US sites with 36 patients to be 1.8 mg/m2 every 4 Fayad et

followed by expanded trial of weeks with a manageable al., 2006)

clinical activity at MTD (1.8 overall safety profile

mg/m2 every 4 weeks)

2008 Fixed dose of rituximab (375 This combination (Fayad et

mg/m2) day one followed by provides efficacy in this al., 2008)

inotuzumab ozogamicin (0.8- patient population with a

1.8 mg/m2) day 2 in patients manageable safety profile

with CD22+ B-cell NHL similar to that of

inotozumab ozogamicin

monotherapy

2010 13 Japanese patients with Confirmed previously- (Ogura et

relapsed/refractory CD22+ reported MTD of al., 2010)

NHL previously treated with inotuzumab ozogamicin

R-CHOP, dose escalation 1.3 of 1.8 mg/kg in Japanese

mg/m2 to 1.8 mg/m2 petients

administered once every 28

days

291

Table D.2 continued

2012 Inotozumab ozogamicin PK profile of inotuzumab (Ogura et

administered in combination ozogamicin closely al., 2012)

with rituximab in patients resembled that of single-

with relapsed/refractory B- agent inotuzumab

cell NHL, administered once ozogamicin

every 28 days up to 8 cycles

(1.8 mg/m2)

2013 Dose escalation study in Single agent inotuzumab (Kantarjian

patients with ozogamicin is highly et al., 2013)

relapsed/refractory ALL. active and safe in this

First 49 patients received 1.3 patient population

to 1.8 mg/m2 single agent

inotuzumab ozogamicin once

every 3 to 4 weeks, next 41

patients received 0.8 mg/m2

on day 1, 0.5 mg/m2 on days

8 and 15, and every 3 to 4

weeks thereafter

292

Table D.2 continued

2013 Escalating doses of This combination has (Fayad et

inotuzumab ozogamicin (0.8- strong response rates and al., 2013)

1.8 mg/m2) with fixed dose long-term progression-

of rituximab (375 mg/m2) to free survival with a

determine MTD manageable toxicity

profile

Combination of inotuzumab

ozogamicin and rituximab

administered at MTD (375

mg/m2 rituximab day 1, 1.8

mg/m2 inotuzumab

ozogamicin every 4 weeks

for up to 8 cycles) in patients

with CD20/22+ NHL

Abbreviations: ALL, acute lymphoblastic leukemia; AML, acute myelogenous leukemia; AUC, area under the curve; CD20/22/30, B-cell receptor CD20/22/30; Cl, clearance; Cmax, maximum observed concentration; HER2, human epidermal growth factor receptor 2; IV, intravenous; MTD, maximum tolerated dose; NHL, non-Hodgkin lymphoma; PK, pharmacokinetics; R- CHOP, rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone; t1/2, half-life.

293

Until recently, the development of ADCs has been carried out empirically, without significant understanding of the correlation between in vitro, preclinical, in vivo, and clinical results. Here, we explore the progression of ADCs, challenges in their development, and some early mechanistic and quantitative pharmacology models which have been developed from previously conducted preclinical studies and clinical trials with the intention of creating better predictive models for accelerating ADC candidate selection and development. We will also discuss the results of clinical studies carried out with clinically advanced ADCs. The overall results of these clinical studies are summarized in Table D.2.

D.2 Gemtuzumab ozogamicin

Gemtuzumab ozogamicin (Mylotarg®) received accelerated approval from the FDA in 2000 for the treatment of acute myelogenous leukemia (AML). Gemzuzumab ozogamicin is a humanized anti-CD33 monoclonal antibody covalently linked to the antitumor antibiotic N-acetyl-γ- calicheamicin (NAC) by a bifunctional linker, (4-(4-acetylphenoxy) butanoic acid). It is indicated for the treatment of patients with CD33+ AML in first relapse who are 60 years of age or older and who are not candidates for other cytotoxic chemotherapeutic interventions.

Gemtuzumab ozogamicin binds to the CD33 antigen expressed on the surface of leukemic blasts, normal myeloid cells, and leukemic clonogenic precursors (Bross et al., 2001). The fact that

CD33 is not expressed on pluripotent hematopoietic stem cells is a big advantage as it allows for gemtuzumab ozogamicin-induced myelosuppression reversal (Walter et al., 2012). The binding of gemtuzumab ozogamicin to CD33 results in the formation of a complex that is internalized

294 followed by the release of the antitumor antibiotic inside the lysosome of the cell. The antibiotic binds to DNA which leads to DNA double strand breaks and cell death (Bross et al., 2001).

In accordance with the FDA Accelerated Approval Program, a randomized phase 3 control trial

(SWOG S0106) was initiated in 2004. This trial was terminated early due to observed fatal toxicities in the gemtuzumab ozogamicin treatment group as compared with the control group that received a standard chemotherapeutic treatment (Petersdorf et al., 2009; Petersdorf et al.,

2013). In the ADC-treated group, the overall mortality rate was 5.7% (16/283 patients) as compared to 1.4% (4/281 patients) in the standard-of-care therapy group. This toxicity was attributed to veno-occlusive disease (VOD), a condition in which blood flow within small blood vessels of the liver is obstructed (Tack et al., 2001). After ten years, per the request of the FDA, this ADC was withdrawn from the US market in 2010, as it showed no improvement in patient survival in addition to increased risk of mortality (Petersdorf et al., 2013). Although this drug was absent from the US market, it remained available in Japan and was recently approved by the

FDA with a modified dosing regimen (Kell, 2016). Despite the limited success off gemtuzumab ozogamicin to date, valuable lessons were learned from its development process, clinical studies, and PK/PD data.

D.2.1 Clinical studies with gemtuzumab ozogamicin In 2001, Dowell et al. examined the PK of gemtuzumab ozogamicin in AML patients in first

2 relapse. In this study 59 patients received a single dose (9 mg/m , IV infusion) of gemtuzumab ozogamicin and plasma samples were collected at specified time points. The PK parameters of gemtuzumab ozogamicin in this population were estimated to be: maximum observed concentration (Cmax), 2.86 ± 1.35 mg/L; area under the curve (AUC), 123 ± 105 mg∙h/L; t1/2, 72.4

295

± 42.0 hours; and Cl, 0.265 ± 0.229 L/h. The authors also observed elevated plasma concentrations following a second dose of the ADC and speculated that this increase may have arisen from a decrease in Cl by CD33+ blast cells resulting from decreased tumor burden

(Dowell et al., 2001).

D.2.2 Impact of age, ethnicity, and gender on gemtuzumab ozogamicin PK/PD In 2001, Korth-Bradley et al. examined the impact of age and gender of individuals on the PK of gemtuzumab ozogamicin. In a 58-patient gender-balanced study with a mean age of 53 ± 16 years, the authors determined that no differences in PK of the antibody or drug component of gemtuzumab ozogamicin were based on age or gender (i.e., age and gender were not significant covariates) (Korth-Bradley et al., 2001).

As gemtuzumab ozogamicin was initially approved for treatment of patients over 60 years old, there was a great interest in expanding its usage to other populations. As such, in 2004,

Buckwalter et al. sought to characterize the PK of gemtuzumab ozogamicin in pediatrics. 29 pediatric patients with refractory or relapsed AML received dosages of 6, 7.5, and 9 mg/m2. The mean PK parameters of gemtuzumab ozogamicin were similar to those in adult populations with both populations demonstrating large inter-individual variability. The authors concluded that treatment with gemtuzumab ozogamicin could be equally efficacious in pediatric patients as in adults at a 9 mg/m2 dose (Buckwalter et al., 2004).

In 2009, Kobayashi et al. sought to examine the PK of gemtuzumab ozogamicin in patients with relapsed or refractory CD33-positive AML. The dose-limiting toxicities associated with gemtuzumab ozogamicin were determined in a phase I study. Consistent with previous reports, the major toxicities associated with this ADC were hepatotoxicities and the optimum dose was

296 determined to be 9 mg/m2. In a phase II study, 5 patients achieved complete remission and another achieved remission without platelet recovery. Interestingly, the authors reported that the

Japanese patients included in the study remained in remission longer than non-Japanese patients from previous studies (Kobayashi et al., 2009).

D.2.3 Lessons learned from gemtuzumab ozogamicin Although the commercial life of gemtuzumab ozogamicin was limited to only ten years (2000-

2010), it provided very useful information regarding this developing class of therapeutics.

Importantly, it demonstrated the need for controlled clinical trials to confirm the benefits of ADC therapy over traditional therapy as well as post-marketing surveillance to monitor toxicity. It is noteworthy that this ADC remained available for ten years while providing minimal clinical benefit over conventional chemotherapy and causing untoward hepatotoxicity. This liver toxicity may have arisen from the ADC binding to healthy sinusoidal cells in the liver expressing

CD33 on their surface, demonstrating the need to better understand the target expression, an issue that was addressed while developing the ADCs that followed (Rajvanshi et al., 2002).

Another important lesson learned from the development and clinical lifetime of gemtuzumab ozogamicin was the investigation of fractionated doses of the ADC allowing for the safe administration of greater cumulative doses. This dosing strategy was investigated in the Acute

Leukemia French Association trial ALFA-0701 in which patients received 3 mg/m2 of gemtuzumab ozogamicin on days 1, 4, and 7 in conjunction with standard front-line chemotherapy which yielded significantly improved patient outcomes (Castaigne et al., 2012;

Hills et al., 2014). These efforts indicate the importance of investigating various dosing

297 regimens of ADCs early in the clinical development process. In fact, gemtuzumab ozogamicin was recently re-approval using an altered dosing regimen.

D.3 Brentuximab vedotin

Brentuximab vedotin (Adcetris®) was approved for treatment of CD30-positive HL and sALCL.

Brentixumab vedotin is composed of brentuximab, a chimeric monoclonal antibody which targets CD30 conjugated to the antimitotic chemotherapeutic agent, MMAE, via a cathepsin cleavable linker (valine-citrulline). Currently, several phase III trials involving brentuximab vedotin are underway assessing its utility in lymphoma patients as compared to other biological therapies and combination chemotherapies.

D.3.1 Early clinical studies with brentuximab vedotin

In 2011, a dose escalation study was conducted by Fanale et al. to examine the safety, maximum tolerated dose (MTD), and activity of brentixumab vedotin dosed weekly in patients with relapsed or refractory CD30+ hematologic malignancies. Brentixumab vedotin was given intravenously on days 1, 8, and 15 of each 28-day cycle at doses that ranged from 0.4 to 1.4 mg/kg. Doses were increased by 0.2 mg/kg weekly until dose-limiting toxicity (DLT) was observed. The results of this study indicated that the MTD of brentuximab vedotin was 1.2 mg/kg administered weekly with the most common side effects presenting as peripheral sensory neuropathy, fatigue, nausea, diarrhea, arthralgia, and pyrexia. Tumor regression was achieved in

85% of patients and the overall objective response rate was 59% with 34% of patients achieving complete remission. This trial demonstrated that weekly administration of brentuximab vedotin

298 results in tumor regression and lengthy remissions in patients with CD30+ malignancies with manageable toxicities (Fanale et al., 2012).

D.3.2 PK/PD modeling of brentuximab vedotin

Shah, et al. sought to develop a PK/PD model of ADCs using brentixumab vedotin as an example to better understand and predict preclinical to clinical translation of ADC efficacy (Shah and Betts, 2012; Shah et al., 2012). The authors utilized data from various reports to develop and validate the model based on in vitro and in vivo PK data for ADC and unconjugated drug

(Hamblett et al., 2004; Sanderson et al., 2005; Okeley et al., 2010), drug concentrations in tumors (Thurber et al., 2008a; Thurber et al., 2008b; Schmidt and Wittrup, 2009), preclinical tumor growth inhibition data (Francisco et al., 2003; Hamblett et al., 2004), ADC and drug PK in patients (Younes et al., 2010), and prediction of clinical responses utilizing the developed PK/PD model (Zhao et al., 2009; Younes et al., 2010; Fanale et al., 2012; Shah et al., 2012). The authors were able to successfully predict xenograft tumor and plasma drug concentrations, and predicted complete response and progression-free survival rates that closely matched results from clinical studies (Shah et al., 2012). The success of this model may be due to notable submodels included within the overall PK/PD model. These submodels included an in vivo intracellular ADC kinetic model which allowed for extrapolation to humans using species- specific target densities as well as a tumor disposition model based on drug molecular weight and tumor size which provided a valuable platform to extrapolate this model to other drugs (Shah et al., 2012; Wada et al., 2014).

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In 2014, Chen et al. developed the first physiologically-based pharmacokinetic (PBPK) model to predict potential enzyme-mediated drug-drug interactions (DDIs) resulting from MMAE release from an ADC complex, acknowledging this important aspect of developing ADCs as therapeutics. In this study, a minimal PBPK model was developed to link antibody-conjugated

MMAE to unconjugated MMAE using valine-citrulline-MMAE ADCs and validated using clinical PK data from brentixumab vedotin. This model sought to overcome the challenge of determining the PK of unconjugated MMAE formed via cleavage of the linker of ADCs as the mechanisms and kinetics of this process are yet to be fully characterized (Lin and Tibbitts, 2012;

Lu et al., 2013a). The constructed model by Chen et al utilized both “bottom-up” and “top- down” approaches combining existing preclinical and clinical data in addition to a PBPK distribution model. The authors estimated total Cl of MMAE to be 8 L/h scaled from a metabolic Cl of ~4 L/h using in vitro in vivo extrapolation (IVIVE). Using this model the authors were able to successfully demonstrate that these MMAE conjugates have limited risk of enzyme-mediated DDIs (Chen et al., 2015).

In 2016, Flerlage et al. examined the PK and safety of brentixumab vedotin dosed weekly in pediatric HL patients. The observed AUC and Cmax were lower in pediatric patients than previously reported in adult studies by 25 and 11%, respectively while other factors, including toxicity, remained consistent. The authors concluded that patient body weight was a significant covariate explaining the intersubject variability in Cl of brentuximab vedotin in pediatric patients and that weekly dosing of brentuximab vedotin is safe in these patients (Flerlage et al., 2016).

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Further, in 2016, Zhao et al. investigated the impact of renal and hepatic impairment on exposure to brentuximab vedotin. Exposure to MMAE was increased by 2.3-fold in patients with severe hepatic impairment and 1.9-fold in those with severe renal impairment. Further, exposure to the intact ADC decreased in both of these patient groups. The authors proposed that poor outcomes and adverse events following treatment with brentuximab vedotin were attributable to poor baseline attributes resulting from co-morbid conditions (Zhao et al., 2016).

D.3.3 Lessons learned from brentuximab vedotin The results from these clinical studies have indicated that weekly administration of brentuximab vedotin at a relatively low dose leads to tumor regression and manageable toxicities, indicating the benefit of optimizing dose and frequency as mentioned above regarding gemtuzumab ozogamicin. This is the first example of a minimal PBPK model utilized to predict potential

DDIs resulting from drug release from an ADC. This model demonstrated that there is little risk of enzyme-mediated DDIs for this ADC. Several groups reported that impaired hepatic and renal function can significantly impact exposure to both intact ADC and released drug. While the authors of these studies did not report additional adverse events in patients with altered renal and hepatic function, increased exposure to drug could lead to unwanted toxicity. Further development of predictive models of the disposition of ADCs in patients with co-morbid conditions is warranted as it may influence patient treatment.

D.4 Trastuzumab emtansine

Trastuzumab emtansine (Kadcyla®) was approved for the treatment of HER2+ breast cancers in

2009. It consists of a humanized HER2-targeted monoclonal antibody, trastuzumab, linked to a

301 cytotoxic agent, DM1, a maytansinoid conjugate, via a stable thioether linker, MCC.

Trastuzumab emtansine exhibits favorable PK and minimal-to-no systemic accumulation of the antibody or drug following multiple doses administered once every 3 weeks (Girish et al., 2012;

Lu et al., 2014). These PK findings have been used to develop mechanistic models of antibody- maytansinoid conjugates to predict the disposition of the conjugated entity as well as the catabolites, and the resulting antitumor activity.

D.4.1 Preclinical characterization and modeling of trastuzumab emtansine Several groups have been interested in the mechanisms of internalization of trastuzumab maytansinoid conjugates and their translocation in cells. In 2015, Hamblett et al. established solute carrier family 46 member A3 (SLC46A3) as a direct transporter of maytansine-based catabolites from the lysosome to the cytoplasm of cells; silencing the expression of SLC46A3 resulted in increased concentrations of the catabolites within the lysosomes (Hamblett et al.,

2015).

Moving beyond in vitro cell-based assays, many groups have investigated the PK and PD of trastuzumab emtansine in mouse models. In 2010, Jumbe et al. developed a PK/PD model of trastuzumab emtansine in mice (Jumbe et al., 2010). The PK of trastuzumab emtansine fits a two-compartment model based on data obtained from single- and multiple-dose studies, as well as time-dose-fractionation studies in animal models and HER2-expressing cells. Subsequently, a population-based PK/PD model was developed to examine the antineoplastic activity of trastuzumab emtansine. Specifically, the authors were able to develop a cell-cycle-phase non- specific tumor cell kill model which included transit compartments of the ADC and offered an

302 accurate representation of the tumor growth inhibition achieved by trastuzumab emtansine

(Jumbe et al., 2010).

Beyond this initial PK investigation in mice, Cilliers et al. sought to examine the tissue and cellular distribution of trastuzumab emtansine and thus developed a multiscale PBPK model coupling the systemic and organ-level distributions of drug with the tissue-level detail of a tumor penetration model. Using this model, the authors were able to examine the impact of drug- antibody ratio (DAR) on tumor penetration, the net result of drug deconjugation, and the impact of utilizing unconjugated antibody to assist the ADC in further penetrating the tumor tissue.

Overall, this model, which is based on in vivo mouse tumor xenograft studies, offers quantitative, mechanistic support to experimental studies working to elucidate the complex mechanisms of action of these drug conjugate therapies (Cilliers et al., 2016).

D.4.2 Clinical studies of trastuzumab emtansine Many phase I studies with trastuzumab emtansine have been conducted. In 2010 a clinical study enrolled 24 patients who had received, on average, 4 prior chemotherapeutic treatments. They received increasing doses of trastuzumab emtansine from 0.3 to 4.8 mg/kg on an every-3-weeks treatment schedule. The MTD of trastuzumab emtansine was determined to be 4.8 mg/kg owing to transient thrombocytopenia. The t1/2 of this ADC was estimated to be 3.5 days with peak DM1 levels below 10 ng/mL. The Cl of the drug was found to be greater at lower doses (less than 1.2 mg/kg) than at greater doses perhaps due to saturation of HER2-binding sites at increased doses

(Krop et al., 2010). Similar dosage-based variability in trastuzumab Cl estimates has been previously reported (Bruno et al., 2005).

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In early 2012, Girish et al. characterized the PK of trastuzumab emtansine in patients with

HER2-positive metastatic breast cancer by assessing the data from 4 studies in which patients received trastuzumab emtansine as a single agent every 3 weeks at a 3.6 mg/kg dose. In this report, the PK parameters for the conjugated ADC trastuzumab emtansine, the drug alone, and the antibody alone, remained consistent across all studies. Trastuzumab emtansine PK was not altered by residual trastuzumab in circulation from prior therapy or by the circulating extracellular domain of HER2. The authors concluded that the PK of single agent trastuzumab emtansine (3.6 mg/kg dosed once every 3 weeks) is well characterized and that the exposure to trastuzumab emtansine is not altered by liver or kidney function (e.g. aspartate aminotransferase

(AST), alanine aminotransferase (ALT), total bilirubin, and albumin) and does not correlate with adverse events including thrombocytopenia or increased concentrations of transaminases (Girish et al., 2012).

Later in 2012, a clinical study investigating weekly dosing of trastuzumab emtansine in patients with advanced HER2-positive breast cancer was conducted by Beeram et al. The aim of this multi-center, open-label, dose-escalation study, was to examine the safety, tolerability, and PK of trastuzumab emtansine administered weekly in breast cancer patients. In this trial, twenty-eight patients received weekly doses of trastuzumab emtansine. The treatment was well tolerated and the MTD was determined to be 2.4 mg/kg administered weekly and the exposure was dose- proportional. This is in contrast with other clinical studies which reported an MTD of 3.6 mg/kg administered once every 3 weeks (Krop et al., 2010; Burris et al., 2011; Beeram et al., 2012;

Yamamoto et al., 2015). In 13 patients, partial tumor growth inhibitory responses were reported with a median tumor inhibition duration of 18.6 months. A weekly dose of trastuzumab

304 emtansine at 2.4 mg/kg had effective antitumor activity and was well tolerated in patients with

HER2-positive breast cancers (Beeram et al., 2012).

More recently, Yamamoto et al. examined the PK, toxicity, and MTD of trastuzumab emtansine in Japanese patients. Patients with HER2-positive metastatic breast cancer received trastuzumab emtansine intravenously at doses of 1.8, 2.4, or 3.6 mg/kg every 3 weeks for a median of 7 cycles. The dose-limiting toxicity was reported as grade-3 elevation of AST/ALT at the 2.4 mg/kg dose. Trastuzumab emtansine administration of up to 3.6 mg/kg was generally well tolerated by Japanese breast cancer patients with toxicities that tended to be more severe than was previously reported (Krop et al., 2010; Beeram et al., 2012; Yamamoto et al., 2015).

Moving beyond these phase 1 trials, several phase 2 investigations have been performed to further examine the safety and efficacy of trastuzumab emtansine in HER2-positive breast cancer patients. In 2011, Burris et al. conducted a phase 2 study in this patient population with individuals who had already received some form of HER2-directed therapy but had subsequent tumor progression. In this study, 112 patients received 3.6 mg/kg trastuzumab emtansine once every 3 weeks. At this dose, the ADC showed strong anticancer activity when administered as a single agent and was well tolerated at the recommended dose (Burris et al., 2011).

In a phase 3 study (MARIANNE), patients with advanced HER2+ breast cancer with no previous therapy for advanced disease received trastuzumab plus taxane, trastuzumab emtansine plus placebo, or trastuzumab emtansine plus pertuzumab at standard doses. The primary endpoint of the study was progression-free survival of patients. In this study, none of the groups receiving trastuzumab emtansine showed superior progression-free survival compared to trastuzumab plus taxane, though fewer patients discontinued treatment due to adverse events in the trastuzumab emtansine arms. Overall it was concluded that trastuzumab showed noninferior, but not superior,

305 efficacy and better tolerability than taxane plus trastuzumab for first-line treatment of advanced

HER2+ breast cancer (Perez et al., 2017).

D.4.3 PK/PD modeling of trastuzumab emtansine Li et al. compiled the results of 8 clinical studies to assess the ethnic sensitivity of trastuzumab emtansine in order to assess whether the clinically recommended dose (3.6 mg/kg) is sufficient and appropriate across ethnicities. The authors utilized four approaches to analyze the data including: noncompartmental analysis (NCA), population pharmacokinetic (popPK) analysis, comparative PK of trastuzumab emtansine in Japanese patients compared with the global population, and exposure-response analyses to examine the impact of ethnicity on PK. The NCA parameters reported were consistent across different ethnic groups; the reported AUCs were 475,

442, and 518 day∙µg/mL for white (n= 461), Asian (n = 68), and others (n = 57), respectively.

The popPK analysis of these 3 groups indicated that ethnicity was not a significant covariate that can affect the PK of trastuzumab emtansine. The exposure-response analyses indicated that ethnicity played no role in efficacy or hepatotoxicity risk, but individuals from Asian populations demonstrated a trend toward greater thrombocytopenia risk. Most Asians exhibiting thrombocytopenia were able to continue receiving treatment following dose-adjustment consistent with the recommendations made for the global population (Li et al., 2016a).

Thrombocytopenia is a frequently noted side effect of treatment with trastuzumab emtansine in breast cancer patients (Krop et al., 2010; Beeram et al., 2012; Yamamoto et al., 2015). As such, several investigators have found it pertinent to develop PK/PD models to characterize the effects of this treatment on patient platelet counts. In 2012, Bender et al. reported a semi-mechanistic population PK/PD model with transit compartments to mimic platelet development and circulation which was fit to platelet concentration-time course data from 2 trastuzumab

306 emtansine single agent studies (Burris et al., 2011; Beeram et al., 2012). This model predicted that with trastuzumab emtansine administration of 3.6 mg/kg once every three weeks, the lowest platelet nadir would be observed following the first administered dose. It was also able to predict a subgroup of patients with variable downward drifting platelet concentration-time profiles, predicted to stabilize by the 8th treatment cycle. However, the authors note that baseline characteristics were not significant covariates in this model (Bender et al., 2012).

Chudasama et al. described a semi-mechanistic popPK model of multivalent trastuzumab emtansine. The authors utilized preclinical data of trastuzumab emtansine to develop a PK model of the intact ADC and the trastuzumab monoclonal antibody alone. In this model, a series of transit compartments with the same disposition parameters was used to represent the deconjugation process from greater to lesser DARs. The authors postulated that this model could be utilized to examine inter-individual variability in ADC PK and that these variabilities could further be correlated to clinical outcomes (Chudasama et al., 2012).

In 2014, Wada et al. sought to employ PK/PD modeling to gain insight into the complex behavior and disposition of antibody-maytansinoid conjugates. To this end, the authors applied mechanistic PK/PD modeling to simulate the processes of ADC tumor uptake, catabolism, and response. Much like the models utilized by Shah et al. describing brentuximab vedotin, the models described by Wada et al. used a comprehensive multi-scale mechanism-based PK/PD approach to translate the ADC PK/PD data from preclinical to clinical which may provide a better understanding of ADC disposition and improved ADC design (Shah et al., 2012; Wada et al., 2014).

In their studies, Wada and colleagues postulated that tumor catabolite concentrations would more closely correlate to efficacy than to other measured concentrations such as plasma ADC

307 concentration and tumor total maytansinoid concentration. As such, the driver of tumor response in their developed model was the catabolite concentration at the tumor site. Using their model, they were able to demonstrate that for trastuzumab emtansine, the catabolite concentrations achieved in tumor cells were highly sensitive to catabolite efflux rate, but less sensitive to the rate of catabolism, which takes place outside of tumor cells. Further, they were able to demonstrate that changing the catabolism rate of the ADC, for example, by changing a more or less stable linker, may have a lesser impact on efficacy than altering the ability of the ADC to exit the tumor (Wada et al., 2014).

In 2014, Lu et al. described the popPK of trastuzumab emtansine with a linear two-compartment model with first-order elimination from the central compartment. The Cl of trastuzumab emtansine was 0.7 L/day, volume of distribution was 3.1 L, and terminal t1/2 was 3.9 days. The authors examined the impact of age, race, geographic region, and renal function and concluded that these covariates are not significant in describing the PK of trastuzumab emtansine (Lu et al.,

2014). Further, they state that refinements in dose based on baseline covariates other than body weight would not explain the inter-individual variability in trastuzumab emtansine PK in this population (Lu et al., 2014).

In a 2016 publication Singh et al. described a cellular disposition model which built upon previously published models by including greater intracellular detail including ADC degradation and passive diffusion of unconjugated drug across tumor cells. Further, different bio- and chemo- measures for trastuzumab emtansine were incorporated into the model to characterize the PK of this ADC in vitro in 3 HER2+ cell lines. Upon combining this cellular disposition model with the tumor disposition model the authors were able to a priori predict tumor DM1 concentrations in xenograft mice. Their analysis indicated that non-specific deconjugation of drug and its passive

308 diffusion across the tumor cell membrane were key parameters for cellular drug exposure (Singh et al., 2016).

In 2017, these authors validated this modeling and simulation (M&S)-based strategy for ADC disposition using trastuzumab emtansine as a case study. Using their model, they developed a

PK/PD model able to characterize in vivo efficacy of trastuzumab emtansine in preclinical tumor models. Parameter estimates for trastuzumab emtansine were taken from preclinical data while the human PK of the ADC was predicted a priori using allometric scaling from PK parameters in monkeys. The predicted human PK, estimated efficacy data from preclinical results, and clinically observed breast tumor volume and growth parameters were combined to develop the full PK/PD model for trastuzumab emtansine. The authors state that this model suggested that a fractionated dosing regimen may provide improved efficacy with trastuzumab emtansine. It was concluded that this M&S strategy for ADC PK/PD was capable of predicting the clinical efficacy of ADCs a priori and the authors were able to retrospectively validate this strategy for all clinically approved ADCs (Singh and Shah, 2017).

D.4.4 Lessons learned from trastuzumab emtansine In contrast to previous attempts to correlate preclinical PK/PD data to clinical application, the predictive model from Singh et al. represents the first generalized PK/PD M&S-based strategy for the bench-to-bedside translation of ADCs and is an exciting new tool in ADC development.

Utilizing preclinical efficacy data, predicted PK data, and estimated PK parameters from monkeys, the authors were able to accurately evaluate the efficacy of various dosing regimens with trastuzumab emtansine and also apply this strategy to the other clinically approved ADCs.

309

This model provides a key mechanism for evaluating ADCs which will be useful both in the development process as well as clinical study design.

D.5 Inotuzumab Ozogamicin

Inotuzumab ozogamicin is an ADC which was recently approved in the UK and US for the treatment of relapsed or refractory B-cell precursor acute lymphocytic leukemia (ALL).This conjugate is made up of inotuzumab, a humanized anti-CD22 monoclonal antibody linked to an anticancer agent from the calicheamicin class, NAC via an acid-labile 4-(4- acetylphenoxy)butanoic acid linker. (Yilmaz et al., 2015). This ADC has been the subject of many clinical trials including two phase II trials for the treatment of NHL. A recent phase 3 study concluded that treatment with single agent inotuzumab was associated with significantly increased remission rates than standard chemotherapy approaches in adults with relapsed or refractory B-cell ALL (Kantarjian et al., 2016).

D.5.1 Preclinical characterization of inotuzumab ozogamicin In 2007, Dijoseph et al. employed an ALL xenograft tumor study to investigate the anti-tumor activity of inotuzumab ozogamicin in mice. Administration of inotuzumab ozogamicin resulted in dose-dependent inhibition of tumor growth of the xenografted leukemia cells producing complete tumor regression at the greatest administered dose (160 µg/kg). At the conclusion of the study, significantly fewer ALL cells were isolated from bone marrow of mice treated with inotuzumab ozogamicin compared with the placebo group. These results provided a solid foundation for the treatment of CD22+ leukemias with inotuzumab ozogamicin (Dijoseph et al.,

2007).

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D.5.2 Clinical studies with inotuzumab ozogamicin In 2006, Fayad et al. reported a dose escalation study performed across 14 European and US sites to determine the MTD of inotuzumab ozogamicin in CD22+ B-cell NHL patients. In this study, the MTD of inotuzuomab ozogamicin was observed to be 1.8 mg/m2 administered once every 4 weeks. This dosing scheme was carried forward in a further clinical study examining the safety of inotuzumab ozogamicin in this patient population which concluded that the toxicity was clinically manageable with the most prominent side effect being thrombocytopenia (Fayad et al.,

2006).

This study was advanced further by this group in 2008 by exploring the combination of inotozumab ozogamicin with rituximab. In this study, a fixed dose of rituximab (375 mg/m2) was administered on day 1 followed by inotuzumab ozogamicin (0.8-1.8 mg/m2) on day 2 of each 28-day cycle for a maximum of 8 cycles. Anti-tumor responses were seen in all patients in the study and the safety profile of this combination closely resembled that of inotuzumab ozogamicin monotherapy (Fayad et al., 2008).

Another early study characterizing the safety, PK, and preliminary clinical activity of inotuzumab ozogamicin was performed in 2010 by Advani et al. In this clinical study on patients with relapsed or refractory CD22+ B-cell NHL, the authors sought to determine the

MTD, safety, and efficacy of inotuzumab ozogamicin. Patients were administered inotuzumab ozogamicin intravenously as a single agent at a dose ranging from 0.4 to 2.4 mg/m2 once every 3 or 4 weeks. The MTD was determined to be 1.8 mg/m2. Frequently reported adverse events at this dose included thrombocytopenia (90%), asthenia (67%), nausea (51%), and neutropenia

(51%). The objective response rate among patients at the cessation of treatment was 39% for all

79 enrolled patients, 68% for patients with follicular NHL treated at the MTD, and 15% for all

311 patients with diffuse large B-cell lymphoma (DLBCL) treated at the MTD. In the enrolled patients, the median progression-free survival was 317 days for patients with follicular NHL and

49 days for patients with DLBCL. Inotuzumab ozogamicin exhibited potent antitumor activity against CD22+ B-cell lymphoma with reversible thrombocytopenia as the most frequently observed toxicity (Advani et al., 2010).

In 2013, Kantarjian et al. reported a clinical study in which patients with refractory/relapsed ALL received either single-dose inotuzumab ozogamicin intravenously at increasing doses from 1.3 to

1.8 mg/m2 every 3 to 4 weeks, or a lower 0.8 mg/m2 dose on day 1, followed by 0.5 mg/m2 on days 8 and 15, repeating every 3 to 4 weeks (Kantarjian et al., 2013). Response rates between these two treatment groups were similar (57% and 59%, respectively), while the median survival for the first group was reported to be 5 months, versus 7.1 months in the latter group. Side effects, including reversible bilirubin elevation, fever, and hypotension were observed less frequently in the weekly treated group as well. The authors concluded that inotuzumab ozogamicin single agent treatment was highly active and safe in patients with refractory-relapsed

ALL and that frequent administration at lower doses appeared to be equally effective and less toxic than elevated single-dose therapy (Kantarjian et al., 2013).

In a clinical study in 2010, Ogura et al. examined the safety, efficacy, tolerability, and PK of inotuzumab ozogamicin in Japanese patients with relapsed or refractory CD22+ B-cell-derived

NHL. All 13 patients included in this trial had follicular lymphoma, were previously treated with rituximab alone or a rituximab-containing chemotherapy-regimen (e.g. R-CHOP), and were enrolled into 2 dose cohorts (1.3 mg/m2, 3 patients; 1.8 mg/m2, 10 patients). None of the 13 patients had dose-limiting toxicities, and the previously reported MTD of 1.8 mg/m2 in Japanese patients was confirmed. Adverse events reported in this trial included thrombocytopenia

312

(100%), leukopenia (92%), lymphopenia (85%), neutropenia (85%), elevated AST (85%), anorexia (85%), and nausea (77%). There were several reported cases of grade 3/4 adverse events in these patients as well, including thrombocytopenia (54%), lymphopenia (31%), neutropenia (31%), and leukopenia (15%). The AUC and Cmax estimates of inotuzumab ozogamicin increased linearly in a dose-dependent manner. Moreover, the PK parameters estimates in Japanese patients were comparable to those in non-Japanese patients. Within this particular study, 7 patients achieved complete response (54%), 4 patients had partial response

(31%) and 2 patients had stable disease (15%), yielding an overall response rate of 85%. This

ADC was well tolerated in these patients at doses up to the MTD of 1.8 mg/m2 and showed efficacy in relapsed or refractory follicular lymphomas following treatment with a rituximab- containing regimen (Ogura et al., 2010).

In 2012, this group investigated the combination of inotuzumab ozogamicin and rituximab in patients with relapsed or refractory B-cell NHL. This clinical study examined the tolerability, efficacy, safety, and PK of intravenously administered inotuzumab ozogamicin alongside rituximab in Japanese patients. 10 patients received a 375 mg/m2 dose of rituximab followed by inotuzumab ozogamicin administered at the previously determined MTD of 1.8 mg/m2. These doses were repeated every 28 days for up to eight cycles or until disease progression or intolerable toxicity. The safety profile of this combination was similar to that of singly- administered inotuzumab ozogamicin; the most common grade 3 or greater adverse events were thrombocytopenia (70%), neutropenia (50%), leukopenia (30%), and lymphopenia (30%). The reported overall response rate with this combination was 80% (8/10 patients). Exposure to the conjugated drug increased with successive doses, similar to the observed PK profiles observed in

313 preliminary studies with inotuzumab ozogamicin monotherapy (Ogura et al., 2010; Ogura et al.,

2012).

In 2013, Fayad et al. performed a clinical trial of inotuzumab ozogamicin plus rituximab (R-

INO) for the treatment of CD20/CD22+ B-cell NHL. The first phase of this study was a dose- escalation phase to determine the MTD of the combination with inotuzumab ozogamicin doses ranging from 0.8-1.8 mg/m2 combined with a fixed 375 mg/m2 dose of rituxumab. In phase 2, an expanded cohort of patients were treated to further examine the safety and efficacy of R-INO at the previously determined MTD. Patients with relapsed follicular lymphoma, relapsed DLBCL, or refractory aggressive NHL received R-INO at the MTD every 4 weeks for up to eight cycles.

Between the 2 phases of this study, 118 patients received at least 1 cycle of R-INO (median, four cycles). Similarly, the most commonly reported grade 3/4 adverse events were thrombocytopenia (31%) and neutropenia (22%). Other common toxicities resulting from this combination included hyperbilirubinemia (25%) and increased AST (36%). As reported previously by Ogura et al. in Japanese patients, the MTD of inotuzumab ozogamicin with co- administered rituximab at 375 mg/m2 was consistent with the MTD of single-agent inotuzumab ozogamicin at 1.8 mg/m2 (Ogura et al., 2010; Ogura et al., 2012). Treatment at this dose achieved overall response rates of 87%, 74%, and 20% for follicular lymphoma, DLBCL, and

NHL, respectively. The 2-year progression-free survival rates in these patient groups were 68% for follicular lymphoma and 42% for DLBCL, indicating that R-INO had strong response rates and long-term progression-free survival in these patients with a manageable toxicity profile

(Fayad et al., 2013).

314

D.5.3 PK/PD modeling of inotuzumab ozogamicin In 2016, Betts et al. performed a retrospective analysis of inotuzumab ozogamicin to develop a model correlating preclinical with clinical PK/PD data. The authors integrated preclinical data into a mechanistic PK/PD model which included: a plasma PK model describing the disposition and Cl of inotuzumab ozogamicin and its released drug (NAC), a tumor disposition model describing diffusion of the ADC into the extracellular environment of target tumors, a cellular model describing binding of the ADC to CD22 and its subsequent internalization, release of drug, and drug binding to DNA and/or efflux from the cell, and tumor growth and inhibition in mouse xenograft models. The authors were able to correlate preclinical data with applicable clinical situations by incorporating human PK data for inotuzumab ozogamicin and clinically relevant tumor volumes, growth rates, and values for CD22 expression in patient populations.

The authors were able to predict progression-free survival rates for treatment with inotuzumab ozogamicin in patients with B-cell malignancies which were comparable to those observed in the clinic. Moreover, they demonstrate that a fractionated dosing regimen was more effective in patients being treated for ALL but not in those receiving treatment for NHL. Further, simulations using this model indicated that growth of tumors is a highly sensitive parameter and correlates well with predictive outcomes of treatment (Betts et al., 2016).

D.5.4 Lessons learned from inotuzumab ozogamicin The story of inotuzumab ozogamicin stresses the need to pay particular attention to the dose and dose frequency of ADCs. In the clinic, patients who received lower doses more frequently achieved comparable tumor regression while reporting fewer untoward effects of their treatment.

Through modeling, one group has been able to correlate preclinical efficacy data with clinical

315

PK/PD data to effectively predict progression-free survival, and to demonstrate that a fractionated dosing regimen is advantageous.

D.6 Conclusions

ADC development and approval has changed the landscape of targeted therapy, in particular, cancer therapy. Indeed, there is a staggering number of ADC development programs supported by industry, academia, and regulatory agencies and certainly new ADCs are expected to be introduced as new therapeutic modalities in the next few years. PK/PD models are indispensable for successful and efficient development programs of ADCs. However, PK/PD modeling of these conjugates represents a unique challenge because of the myriad dynamic and complex processes which follow their administration. These processes include disposition and Cl of the

ADC and the de-conjugated moieties, site-specific binding, and small molecule translocation inside cancer cells. All these processes must be taken into account for better development of mechanistic PK/PD models. In this report, we discussed several cases where advanced unique mechanistic models of ADCs and their constituents were reported. Many of these models employed state-of-the art quantitative pharmacology approaches and were able to combine the disposition of the ADC, antibody and drug while factoring in biological parameters such as tumor volume as well as drug tumor and plasma concentration data for predicting exposure and efficacy. Improved models combined with improved therapeutic and post-marketing surveillance can prevent ineffective or toxic agents from entering or remaining in the market as was seen with gemtuzumab ozogamicin. These approaches improved our understanding of ADCs and their

316 utilization in targeted therapy and undoubtedly they will aid in the discovery and development of

Paul Ehrlich’s famed “magic bullet” chemotherapy.

317

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Appendix E: Bringing Interprofessional Faculty Together for an Innovative Elective in Pharmacogenomics: Genotyping your own DNA

E.1 Background and Purpose

Personalized medicine through the customizing of treatments based on patients’ genetic makeup improves therapeutic outcomes and has become increasingly utilized clinically in recent years

(Wilson and Nicholls, 2015). The overarching goal of pharmacogenomics is to identify individuals among a large population who exhibit different pharmacological responses to drugs despite similar diagnoses due to underlying genetic variations, and to apply this information to improve therapy by altering drug dose or drug choice in these individuals (Shastry, 2006; Ma and

Lu, 2011; Wilson and Nicholls, 2015).

In practice, a conventional pharmacologic treatment plan typically follows a rigid pattern of making a diagnosis and treating patients with drugs shown in clinical trials to be efficacious for treatment of that disease. This approach, however, does not take into consideration of vast interindividual genetic differences in important drug-metabolizing enzymes and transporters, which may lead to significantly varied pharmacological responses and clinical outcomes (Franke et al.,

2010; Sim et al., 2013). A more personalized treatment approach involves implementing pharmacogenomic information into the treatment decision to achieve more individualized and effective therapy. The U.S. Food and Drug Administration (FDA) recognizes the importance of pharmacogenomic differences in patient drug response and outcomes and has included in more

326 than 130 drug labels this information with the goal of improving safety and/or efficacy. For instance, genetic testing is either required or recommended before the prescription of medications such as abacavir, clopidogrel, letrozole, maraviroc, nilotinib, thiopurines, and warfarin (Beitelshees and McLeod, 2006; Kantarjian et al., 2007; Yin and Miyata, 2007; Loi et al., 2013; Dean and Kendal, 2015).

Pharmacists are trained to be medication experts and therefore play an important role in the healthcare team, particularly with respect to choosing appropriate medications, making dosage recommendations, and helping patients navigate complex instructions to ensure compliance with their treatment plan. Given that pharmacogenomics represents a relatively new field, many practicing pharmacists are not yet confident with interpreting pharmacogenomic data; a study in

2012 revealed that only approximately 20% of pharmacists believed that they had an adequate understanding of pharmacogenomic testing (Kisor, 2016). Pharmacogenomics is now included in

Accreditation Council for Pharmacy Education (ACPE) Standards 2016 as a required element of the didactic PharmD curriculum in the areas of pharmaceutical and clinical sciences to assure that students will be “practice ready” (2016). A survey in 2010 indicated that although the pharmacogenomics education provided in U.S. pharmacy schools increased from 39% in 2005 to more than 89% in 2010, the scope and depth of pharmacogenomics information offered by these schools appeared to be limited and the majority schools did not have plans for faculty development in the area of pharmacogenomics (Murphy et al., 2010). Further, medical schools have begun incorporating innovative teaching strategies into their curricula to accommodate the rapid advancement of personalized medicine (Salari et al., 2011; Walt et al., 2011; Sanderson et al., 2013; Garber et al., 2016; Perry et al., 2016). Thus, there is an apparent need to improve

327 pharmacogenomics education in pharmacy schools to enable those entering clinical practice to effectively utilize pharmacogenomics information in patient care.

In order to fully realize the potential benefits of pharmacogenomics in clinical practice, teams of physicians, nurses, genetic counselors, and pharmacists must work together to insure the most benefit from pharmacogenomics in the clinic. Thus, an interprofessional education (IPE) approach is most appropriate to facilitate the clinical implementation of pharmacogenomics- based personalized medicine, although logistical barriers such as curricular requirements and professional cultures often challenge that ideal (Lawlis et al., 2014). At the University of

Maryland School of Pharmacy we have offered an Advanced Pharmacogenomics elective course to pharmacy students since 2008. We recruited diverse faculty including pharmacists, physicians, and regulatory scientists from the FDA to participate in the course, so that pharmacy students can appreciate the clinical, research, and regulatory perspectives of personalized medicine. To further strengthen students’ learning experiences in this class, we developed a hands-on pharmacogenomics exercise using the Affymetrix DMET assay (Burmester et al., 2010). Upon acquiring a pharmacogenomic dataset, students interpret the data according to the Clinical

Pharmacogenetics Implementation Consortium (CPIC) guidelines. Instructors from both pharmacy and medicine offered scientific feedback on the interpretation. The overall objective of this exercise is to enhance interprofessional pharmacogenomics education and communication, and to provide hands-on experience of pharmacogenomic testing to pharmacy students in order to improve the confidence of these future healthcare practitioners in applying genetic-based personalized medicine.

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E.2 Educational Activity and Setting

The Advanced Pharmacogenomics course at University of Maryland School of Pharmacy is offered to third-year PharmD students and pharmaceutical sciences graduate students as a seven- week elective in the fall semester. The main goals of this course are: to increase knowledge of basic pharmacogenomics principles, to recognize the benefits/risks of pharmacogenomic testing, to learn how to interpret pharmacogenomic results, and to understand the clinical utility of pharmacogenomic information to improve the safety and efficacy of drug therapy. The collective knowledge from this course will equip students so they are poised to effectively discuss findings with patients as part of a health care team.

To attain these goals, the format of the Advanced Pharmacogenomics class includes lectures, discussions, and student presentations. The lectures cover topics including background on the initial discovery of the genetic influence on inter-individual variability on drug response, variant frequencies in particular populations, metabolizer categories, the consequences of decreasing or increasing gene expression and/or function, discovery science in the field of pharmacogenomics, and recent advancements in personalized medicine strategies relative to traditional treatment approaches. Through interactive discussions of specific clinical scenarios with pharmacy and medical faculty, students learn how genomic information may be utilized in drug choice or dosing recommendations. Students are introduced to resources such as the CPIC guidelines for incorporating pharmacogenomic information into clinical care and online resources such as www.warfarindosing.com to demonstrate how dosing recommendations may be altered once genetic information is included in a drug dosing algorithm.

The pharmacogenomics exercise is a core in-class activity to implement personal pharmacogenomic testing as an educational tool for all students. Studying the effectiveness of

329 this hands-on educational activity was deemed non-human subjects research by the Institutional

Review Board at the University of Maryland, Baltimore. Students were required to attend an information session about the activity given by a certified genetic counselor who explained the test itself, possible outcomes, benefits and limitations of using one’s own DNA sample, and processes to maintain privacy and confidentiality. The genetic counselor emphasized that the test is not validated under Clinical Laboratory Improvement Amendments (CLIA) regulations, and therefore results should not be used for clinical purposes. Students had the opportunity to meet individually with the genetic counselor if they had additional concerns. Following the information session, students choosing to receive a personal dataset signed an information sheet and submitted a buccal sample labeled with a unique identification number; no identifiable information was included on the label. Students who opted not to submit a DNA sample received data from an anonymous sample. The genetic counselor was the only person with access to the list linking individual student names with identification numbers; faculty assigning grades for the course were unaware if a student chose to use his/her own sample for the activity. DNA isolation and pharmacogenomic testing via the Affymetrix DMET chip was performed on the research side of the Genomics Core within University of Maryland School of Medicine. The genetic counselor distributed two files to each student: a comprehensive dataset containing 959 variants in 79 genes and a phenotype dataset containing the drug metabolism phenotypes of 20 pharmacogenetic genes with strong evidence of clinical utility. Students in Advanced

Pharmacogenomics formed groups and presented a drug-gene pair to their classmates and a multi-disciplinary panel of expert faculty members. The presentations contained background on the drug-gene pair, the group’s results of DMET testing including metabolizer status, and implications for pharmacologically significant diplotypes according to the CPIC guidelines.

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Pharmacy and medical faculty engaged students in lively discussion regarding each group’s findings.

Surveys were designed in Qualtrics (Provo, UT) online platform and delivered to pharmacy students before and after the activity. The pre-activity survey included five questions reflecting students’ current level of understanding of the following pharmacogenomics concepts (thorough understanding, above average understanding, average understanding, little understanding, no understanding):

1. The process of pharmacogenomic testing

2. How to interpret pharmacogenomic test results

3. How pharmacogenomic test results are used in clinical practice

4. The risks of pharmacogenomic testing

5. The benefits of pharmacogenomic testing

Other questions included whether students would use their own genetic samples for the activity, and if they would make the same decision if the results would become part of their medical history. Students were also asked how useful they feel pharmacogenomic testing will be in the clinical setting, how confident they feel in their ability to explain results of pharmacogenomic testing to a patient, and how likely they would be to use their own DNA if this activity also offered DNA analysis to determine a predisposition to a variety of common diseases (e.g. diabetes, heart attack).

The post-activity survey included five statements for students to rate their level of agreement

(strongly agree, agree, neither agree nor disagree, disagree, strongly disagree) regarding comfort level and belief:

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Table E.1: Student responses to survey questions prior to genotyping activity.

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1. I feel comfortable ordering pharmacogenomic testing

2. I feel comfortable explaining the process of pharmacogenomic testing to patients

3. I feel comfortable discussing pharmacogenomic test results with patients

4. I believe pharmacogenomic testing is critical for determining appropriate health care

5. I feel comfortable discussing genetics in general with patients

Other questions asked whether students regretted using or not using their own sample, and whether they felt there was an educational benefit or disadvantage to using their own sample.

Shortly before the onset of our educational activity, a handful of other academic institutions had introduced personal genome testing into their medical school curricula that included the disclosure of results on disease susceptibility and carrier status (along with pharmacogenomic results in some cases) (Salari et al., 2011; Walt et al., 2011; Sanderson et al., 2013). Given the ethical, legal and social issues surrounding genetic testing, we chose to only offer research-grade testing for pharmacogenomics, but in our survey asked students a series of questions on the likelihood of them using their own sample for a test that may diagnose a highly penetrant, adult- onset monogenic disease that they do not yet express that is preventable or treatable (e.g., hereditary breast and ovarian cancer (HBOC), Lynch syndrome); a test that may diagnose a highly penetrant, adult-onset monogenic disease that they do not yet express for which there is currently no treatment or cure (e.g., Huntington’s disease); a test that may identify them as being a carrier of a highly penetrant /recessive monogenic disease that is preventable or treatable (e.g., cystic fibrosis); and a test that gives information on their risk for common disease (e.g., diabetes, cardiovascular disease) (Salari et al., 2011; Walt et al., 2011; Sanderson et al., 2013; Garber et al., 2016). To determine if the decision to submit a sample for testing would be influenced by the

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Table E.2: Student responses to survey questions following participation in the genotyping activity.

334 option to receive a clinical result, as was done at other institutions, we framed questions in terms of if a result would and would not go into the medical record.

E.3 Findings

Student surveys completed before and after this educational activity revealed improvements in the students’ knowledge of and confidence in pharmacogenomic testing and its clinical applications, as shown in Tables E.1 and E.2. Prior to the genotyping activity students reported a mean of 3.47 on a scale of 1 (no understanding) to 5 (thorough understanding) that they understood the process of pharmacogenomics testing; 16% (nine students) responded as having little or no understanding. After the activity students reported a mean of 3.82 on a 5-point Likert scale (strongly agree, agree, neither agree or disagree, disagree, strongly disagree) that they would feel comfortable explaining the process of pharmacogenomic testing to patients; only 10%

(five students) disagreed or strongly disagreed with the statement. In the pre-activity survey students reported a mean understanding of how to interpret pharmacogenomics test results of

2.97 with 36% (21 students) reporting little or no understanding, while in the post-activity survey students reported a mean of 3.78 that they would feel comfortable discussing pharmacogenomic test results with patients; only 8% (four students) disagreed with the statement. It is worth noting that although the questions from the pre- and post- activity surveys were not constructed exactly the same, questions can be classified into examining students’ understanding of pharmacogenomics testing (pre-test questions 1, 4, 5, and post-test questions 1, 2); and their confidence in interpretation of pharmacogenomic test results (pre-test questions 2, 3, and post-

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Figure E.1: Understanding of pharmacogenomics testing and confidence in implementing pharmacogenomics in practice. Students were surveyed regarding their knowledge of pharmacogenomic testing and its application in the clinic. Questions 1, 4 and 5 from the pre- activity survey and questions 1 and 2 from the post-activity survey reflect students’ understanding of pharmacogenomics testing; while questions 2 and 3 from the pre-activity survey and questions 3-5 from the post-activity survey represent their confidence in interpreting pharmacogenomics test results. Each bar represents the mean ± SD of the average Likert scores from related questions. *** P < 0.001.

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Table E.3: Student willingness to include pharmacogenomics data in their own medical records.

337 test questions 3, 4, 5). As demonstrated in Figure D.1, students’ responses in these two major areas are significantly improved upon completion of the in-class genotyping exercise.

Our post-activity survey results also indicated that 54-70% students were likely or extremely likely to use their own sample for a test which may reveal genetic diseases that are currently treatable or non-treatable, as well as whether the information will be included in their medical record or not (Table E.3). These findings are in line with the survey results from University of

Maryland School of Medicine, where 25-78% medical students reported being likely or extremely likely to use their own DNA samples for disease or carrier testing (Perry et al., 2016).

E.4 Discussion

In this report, we describe a hands-on student exercise utilizing the DMET pharmacogenomic assay and an interprofessional educational approach. The activity was offered to third-year

Pharmacy students in the Advanced Pharmacogenomics elective. The course challenged students to discuss recent advancements in pharmacogenomics and its implementation into routine clinical care with medical and pharmacy faculty. A total of 71 pharmacy and pharmaceutical science graduate students enrolled in the Advanced Pharmacogenomics course. Among them, 50 used their own DNA samples for the DMET analysis, while the rest opted to receive data from an anonymous sample. There were 58 and 50 students who completed the pre- and post-activity surveys, respectively.

Student presentations were reviewed positively by the faculty panel and students were able to successfully demonstrate their overall knowledge of pharmacogenomics and the relevant clinical applications. Of particular interest were CYP2D6 variants and their impact on codeine

338 metabolism, CYP2C19 variants on clopidogrel response, and the variability in warfarin pharmacology as a result of CYP2C9/VKORC1 variants. The impact of gain-, decrease-, and loss-of-function variants was analyzed and discussed. Presenting students were challenged with questions from an interprofessional panel of experts, including a basic scientist, clinical pharmacist, genetic counselor and physician-scientist, regarding the impact of these variants on the pharmacokinetics and pharmacodynamics of these drugs, as well as on recommendations that would be made for dosing and patient monitoring.

Given the observed improvement in students’ understanding of pharmacogenomic testing and confidence in its application, integration of a personal pharmacogenomic testing exercise into the core pharmacy curriculum may prove beneficial. Furthermore, with the active interprofessional engagement between pharmacy and medical faculty, the course could be improved by teaching pharmacy and medical students together to promote interdisciplinary interactions and by opening the course to other schools on campus (medical, nursing, and dental) to further expand the demographics of students enrolled in the course.

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E.5 References

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