Mediated Multidrug Resistance (MDR) in Cancer

Home , H19 (gene), Receptor antagonist, Rhodamine 123

A Thesis

Entitled:

Differential Effects of Dopamine D3 Receptor Antagonists in Modulating ABCG2 -

Mediated Multidrug Resistance (MDR) in Cancer

Noor A. Hussein

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the

Master of Science in Pharmaceutical Sciences Degree in

Pharmacology and Toxicology

______Dr. Amit K. Tiwari, Committee Chair

______Dr. Frank Hall , Committee Member

______Dr. Zahoor Shah, Committee Member

______Dr. Caren Steinmiller, Committee Member

______Dr. Amanda Bryant-Friedrich, Dean College of Graduate Studies

The University of Toledo

May 2017

This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author.

An Abstract of

Differential Effects of Dopamine D3 Receptor Antagonists in Modulating ABCG2 - Mediated Multidrug Resistance (MDR)

Noor A. Hussein

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science in Pharmaceutical Sciences Degree in Pharmacology and Toxicology

The University of Toledo

May 2017

The G2 subfamily of the ATP-binding cassette transporters (ABCG2), also known as the breast cancer resistance protein (BRCP), is an efflux transporter that plays an important role in protecting the cells against endogenous and exogenous toxic substances.

The ABCG2 transporters are also highly expressed in the blood brain barrier (BBB), providing protection against specific toxic compounds. Unfortunately, their overexpression in cancer cells results in the development of multi-drug resistance

(MDR), and thus, chemotherapy failure. Dopamine3 receptor (D3R) antagonists were shown to have excellent anti-addiction properties in preclinical animal models but produced limited clinical success with the lead molecule. Thus, other more potent D3R antagonists, notably NGB2904, SB-277011A, and U99194, and PG01037 were dropped from further studies. Whether ABCG2 transporters limited D3R antagonists’ efficacy or whether these D3R antagonists could modulate ABCG2-mediated MDR has not been evaluated before. The present study was designed a) in a quest to understand whether

ABCG2 transporters might be a limiting factor in D3R antagonists’ accumulation in the brain; b) if these D3R antagonists could be repurposed as anticancer chemo adjuvants to iii

reverse MDR mediated by ABCG2 transporters. Interestingly, the structure of various

D3R antagonists is similar to that of substrates for the ABCG2 transporter. We found that the D3R antagonists (PG01037, NGB2904, SB-277011A, and U99194), alone up to

50µM, do not produce significant toxicity towards normal or cancer cells. In contrast, the

D3R antagonists (PG010037, NGB2904, SB-277011A, and U99194) significantly sensitized ABCG2 overexpressing HEK293/ABCG2; H460/MX-20, S1-M1-80 and

A549-MX-10 cells to well-known anticancer agent’s mitoxantrone (MX) and doxorubicin (DOX) that are substrates of ABCG2 transporters. As shown by accumulation and efflux assay D3R antagonists combination enhanced accumulation of in

MX in ABCG2 overexpressing H460-MX20 cells. Additionally, D3R antagonists

(PG01037 and NGB2904) at a concentration of only 5µM significantly downregulated the expression of ABCG2 when incubated for 24 and 48 hours with ABCG2 overexpressing cells, suggesting that D3R antagonists reverse ABCG2 mediated drug resistance by not only inhibiting its function but also downregulating its expression.

Furthermore, D3R antagonists were found to produce synergistic anticancer activity when combined with MX and DOX. In conclusion, this is the first study to show interaction of

D3R antagonists with ABCG2 transporters suggesting that D3R antagonists might be

ABCG2 substrates, and combining D3R antagonists with certain anticancer agents that are substrates of ABCG2 transporters (i.e. MX and DOX) could produce beneficial results in ABCG2 overexpressing MDR cancer cells.

I would like to dedicate my thesis to my dearest friend Qaswaa who passed away last year. She was a source of inspiration throughout all the way back since my undergraduate years, where we did thesis project together. I am sure that she would be very proud of my success and me reaching a higher degree.

Acknowledgements

I would like to express my sincere gratitude to my advisor and mentor Dr. Tiwari for his tremendous support during my master’s journey. Truly, without his guidance, I could not have successfully completed my scientific research and discovered this new finding. Also, I thank, from the bottom of my heart, my beloved husband Abdullah, who has not only supported me in the difficult times, but also, always motivated me to give the best I can do to complete my mission and achieve my dreams. There are not enough words to describe how grateful I am to have my lovely family: mother, father, brothers and sister in my life. Their endless love and encouragement motivated me from early childhood to explore and excel in science. While I was on this journey to accomplish my master’s thesis, my little baby boy, Yamin, arrived, motivating me even more to accept the challenge of being a successful mother and researcher. Thus, I dedicate my success to my lovely family and to the souls of my lovely grandmother (Sabeha), who passed away few months before my thesis defense. Also, I thank Dr. Ashby (St. John’s University, NY) for his tremendous efforts guiding me and revising my thesis. Furthermore, I thank Dr. Liu for introducing me to the basics of scientific research. Also, I would like to thank my committee members Dr. Hall, Dr. Shah, and Dr. Steinmiller. Lastly, I thank the Higher

Committee for Education Development in Iraq (HCED) for their financial support and for giving me the opportunity to complete my higher education path abroad. v

Table of Contents

Abstract ...... iii

Acknowledgements ...... v

Table of Contents ...... vi

List of Tables……………………………………………………………………………. ix

List of Figures ...... x

List of Abbreviations ...... xii

List of Symbols ...... xv

1. Introduction

1.1 Multi Drug Resistance (MDR) in Cancer ...... 1

1.2 Adenosine Tri-Phosphate Binding Cassette (ABC) Transporters ...... 3

1.3 The Role of ABC Transporters in Cancer Chemotherapy Resistance ...... 10

1.3.1 The Role of ABCB1 Transporter in Producing MDR …………….11

1.3.2 The Role of ABCC1 Transporter in Producing MDR …………...12

1.3.3 The Role of ABCG2 Transporter in Producing MDR……………..13

1.4 Strategies to Surmount ABC- Mediated MDR……………………………14

1.4.1 Generations of MDR Modulators…………………………………14

1.4.2 Natural MDR Modulators…………………………………………18 vi

1.4.3 Miscellaneous MDR Modulators………………………………. ...18

1.4.4 Compounds Known to Modulate ABCG2 Transporter-Mediated

MDR………………………………………………………………………19

1.5 Dopamine D3 Receptor Antagonists………….……….…………………….21

1.6 Objective and Aims………………………………………………………….25

2. Materials and Methods ...... 26

2.1 Materials……………………………………………………………………. 26

2.2 Cell lines and Cell Culture…………………………………………………. .27

2.3 Determination of Cell Cytotoxicity by MTT Assay………………………. ..28

2.4 Cell Morphological Analysis………………………………………………..29

2.5 Protein Estimation: Cell lysate Preparation and Bicinchoninic acid (BCA)

Analysis…………………………………………………………………………....29

2.6 Western Blot Analysis……………………………………………………... 30

2.7 Immunocytochemistry…………………………………………………….. .31

2.8 Rhodamine 123 Accumulation and Efflux Assay…………………………..32

2.9 The Effect of D3 Receptor Antagonists on the Efficacy of Mitoxantrone and

Doxorubicin……………………………………………………………………….33

2.10 Molecular Docking Studies…………………………………………………..33

2.10.1 Ligand Structure Preparation…………………………………… 33

2.10.2 Protein Structure Preparation……………………………………..34

vii

2.10.3 Docking Protocol………………………………………………… ...35

2.11 Statistical Analysis…………………………………………………………. .35

3. Results…………………………………………………………………… ...... 36

3.1 The Effect of D3R Antagonists on the Efficacy of Mitoxantrone and Doxorubicin

in Cell Lines Overexpressing ABCG2 Transporters………………………………...36

3.2 D3 Receptor Antagonists Synergistically Increase the Efficacy of Mitoxantrone

and Doxorubicin ……………………………………………...... 38

3.3 PG01037 and NGB2904 Significantly Decrease the Protein Expression levels of

the ABCG2 Transporter ………...... 40

3.4 PG01037 and NGB2904 Significantly Inhibit the Efflux Function of the

ABCG2 Transporter ………………………………………………………………...41

3.5 Molecular Docking of SB277011A, NGB2904, PG01037, and U99194A as

Determined Using a Homology Model of the ABCG2 Transporter…………………42

4. Tables and Figures……………………………………………………………...... 45

5. Discussion ……………………………………………………………………………69

References……………………………………………………………………………….76

viii

List of Tables

1. Select ABCG2 modulators ...... 46

2. The effect of NGB2904, PG01037, SB-277011A, U99194A, and nilotinib on the cytotoxicity of mitoxantrone in ABCG2-overexpressing H460-MX20 cells ...... 47

3. The effect of NGB2904, PG01037, SB-277011A, U99194A, and nilotinib on the cytotoxicity of mitoxantrone in ABCG2-overexpressing A549-MX10 cells ...... 48

4. The effect of NGB2904, PG01037, SB-277011A, U99194A, and nilotinib on the cytotoxicity of mitoxantrone in ABCG2-overexpressing S1M1-80 cells………………..49

5. The effect of 5 µM of U99194A, NGB2904, SB-277011A, PG01037 and nilotinib on the cytotoxicity of mitoxantrone in ABCG2- transfected HEK293-R2 cells………...50

6. The effect of 5 µM of U99194A, NGB2904, SB-277011A, PG01037 and nilotinib on the cytotoxicity of doxorubicin in ABCG2 overexpressing H460-MX20 cells……...50

7. Characterization of CI range values based on Chou-Talalay method……………..51

8. Combination index (CI) values resulting from the combination of mitoxantrone and with PG01037, NGB2904, SB-277011A, and U99194………………………………….52

9. Combination index (CI) values resulting from the combination of doxorubicin and with PG01037, NGB2904, SB-277011A, and U9914…………………………………...52

List of Figures

1. The structural scheme of ABCB1 and ABCG2 transporters in Chapter 1 ...... 5

2. An ATP-switch mechanism of action of ABC transporters in Chapter 1 ...... 7

3 A constant contact model depicting mechanism of action of ABC transporters in Chapter 1…………………………………………………………………………………..8

4. The three major ABC transporters that are involved in mediating MDR in cancer in Chapter 1………………………………………………………………………………10

5. Major Anti-cancer drugs, which are ABCG2 substrates in Chapter 1………...... 14

6. Chemical structures of D3 receptor antagonists in Chapter 1……………………24

7. The effect of NGB2904, PG01037, SB-277011A, U99194 and nilotinib on the survival of parental H460 and ABCG2 overexpressing H460-MX20 cells in Chapter 4..53

8. The ABCG2 mediated mitoxantrone-MDR reversal potential of PG01037 is shown in ABCG2 overexpressing lung cancer resistant H460-MX20, A549-MX10, and colon cancer resistant S1M1-80 cells in Chapter 4……………………………...... 54

9. The effect of NGB2904 on ABCG2-mediated resistance to mitoxantrone in H460- MX20, A549-MX10, and S1M1-80 cell lines in Chapter 4……………………………..56

10. The effect of SB-277011A and nilotinib on the efficacy of mitoxantrone (MX) in H460-MX20, A549-MX10and S1M1-80 cells in Chapter 4……………………………58

11. The effect of U99194A and nilotinib on the efficacy of mitoxantrone (MX) in H460-MX20, A549-MX10 and S1M1-80 cells in Chapter 4……………………………60

12. The effect of NGB2904, PG01037, SB-277011A, or U99194 on the survival curve and the IC50 values of doxorubicin in ABCG2 overexpressing H460-MX20 cells in Chapter 4…………………………………………………………………………………62

13. The effect of NGB2904, PG01037, SB-277011A, or U99194on the survival curve and the IC50 values of mitoxantrone in ABCG2 transfected HEK293-R2 cells in Chapter 4 ………………………………………………………………………………………….63

14. The effects of PG01037 and NGB2904 on protein expression of ABCG2 transporter in Chapter 4………………………………………………………………….64

15. The effect of PG01037, NGB2904, and nilotinib on the accumulation and efflux of intracellular rhodamine 123 in ABCG2 overexpressing H460-MX20 cells in Chapter 4………………………………………………………………………………………….65

16. The combination index values resulting from combining PG01037, NGB2904, SB-277011A, and U99194A with mitoxantrone and doxorubicin in Chapter 4…………66

17. Model for the binding of PG01037, NGB2904 and SB-277011A, U99194 with the ABCG2 transporter in Chapter 4………………………………………………………...68

List of Abbreviations

ABC: Adenosine triphosphate (ATP) binding cassette

ABCB1: ATP-binding cassette subfamily B1

ABL: Abelson

ABCC1: ATP-binding cassette subfamily C1

ABCG2: ATP-binding cassette subfamily G2

ADME: Absorption, Distribution, Metabolism, Excretion

AGA: Argosterol-A

ALL: Acute lymphoblastic leukemia

AML: Acute myelogenous leukemia

ATP: Adenosine triphosphate

BP: Blood pressure

BBB: Blood - Brain Barrier

BCA: Bicinchoninic acid

BCR: Break point cluster region

BCRP: Breast cancer resistance protein

CML: Chronic myelogenous leukemia

CSA: Cyclosporine A xii

D3R: Dopamine 3 receptors

DAPI: 4’,6-Diamidino-2-phenylindole, dihydrochloride

DMEM: Dulbecco’s modified eagle’s medium

DMSO: Dimethyl sulfoxide

DOX: Doxorubicin

DTT: Dithiothreitol

EGFR: Epidermal growth factor receptor

ErbB1: Erythroblastic leukemia viral oncogene

FBS: Fetal bovine serum

FTC: Fumitremorgin C

GAPDH: Glyceraldehyde 3-Phosphate dehydrogenase

HEK293: Human embryonic kidney 293 cells

HRP: Horseradish peroxide

MDR: Multi drug resistance

MDR1: Multi drug resistance protein

MRP1: Multi drug resistance protein 1

MTT: 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenylterzolium bromide

MTX: Methotrexate

MW: Molecular weight

MX: Mitoxantrone

xiii

MXR: Mitoxantrone resistant protein

NCB: Neochamaejasmin B

NBDs: Nucleotide binding domains

NG: NGB2904

NSCLC: Non small-cell lung cancer

P-gp: P-glycoprotein

PBS: Phosphate buffer saline

PDE-5: Phosphodiesterase-5

PG: PG01037

PI: Propidium iodide

PMSF: Phenylmethylsulfounyl fluoride

PVDF: Polyvinylidene difluoride

QSAR: Quantitative structure activity relationship

TBS: Tris buffer saline

TKIs: Tyrosine kinase inhibitors

TMDs: Trans-membrane domains

SB: SB-277011A

SCLC: Small cell lung cancer

U99: U99194

VEGR: Vascular endothelial growth factor receptor

xiv

List of Symbols

CI...... Combination Index: a quantitative representation of the synergistic effect due to the drug combination, where CI< 1, synergism, CI=1, additive effect, and CI> 1, antagonism.

IC50 ...... Concentration required to inhibit the cell growth by 50%.

Fa...... Fraction affected (percent of cell survival when it converted to the following manner; Fa=0 when the % cell survival = 100 and Fa =1 when % cell survival =0.

FR ...... Fold resistance (the value of IC50 for the substrate in the resistant cell line with or without the presence of reversal compound divided by the IC50 value of the substrate in the parental cell line without the presence of the reversal compound.)

Chapter 1

Introduction

1.1 Multi Drug Resistance (MDR) in Cancer

Since the 1940s, chemotherapy has been one of the major therapeutic modalities for the treatment of cancer [1]. Initial data from clinical studies indicated that when patients were treated with a single drug, chemotherapy fails and tumors relapse, perhaps due to the development of acquired resistance in the cancer cells [2]. Subsequently, in the

1960s-70s, combinatorial regimens were introduced for the treatment of cancer as it was postulated that this would attenuate the development of resistance [3]. However, even the use of combinatorial therapy was not efficacious in treating certain types of cancer, on the contrary, it often had deleterious side-effects. It was first reported in 1976 [4] that cancer cells can become resistant to anticancer drugs by expressing proteins that efflux or remove anticancer drugs, thereby attenuating or even negating their efficacy.

The development of drug resistance poses a continual clinical problem in cancer chemotherapy [5]. In oncology clinics, specialists recognize a phenomenon called Multi

Drug Resistance (MDR), which means that cancer patients may develop resistance to several unrelated classes of anti-cancer drugs without prior exposure [6]. MDR is defined as a significant decrease in the efficacy of structurally and mechanistically unrelated 1

compounds in cancer cells and microorganisms. The acquired MDR rendered a wide variety of anti-cancer agents ineffective. Therefore, using a combination of drugs with different targets was also not always effective [5]. MDR is considered one of the most limiting factors to the success of the chemotherapy. Therefore, the elucidation of the role of cellular drug resistance pushes the progress in eliminating the causes of chemotherapeutic failure, providing better treatment for cancer patients [7]. The cellular drug resistance to the antineoplastic agents could be either primary (intrinsic) or secondary

(acquired) resistance. Intrinsic resistance occurs in the absence of prior exposure to the anti-cancer agents, resulting from genetic or epigenetic reasons. While acquired resistance occurs due to overexpression of specific efflux transporters, apoptosis reduction, advanced DNA damage repair mechanism, autophagy induction, cancer stem cell dysregulation, miRNA and other epigenetic abnormalities and/or hypoxia induction among others [7,8]. The majority of cellular and molecular studies indicate the involvement of three major MDR mechanisms in resistant cancer cells: (1) decreased uptake of hydrophilic drugs or increased active efflux of amphipathic drugs, resulting in reduced accumulation of drugs inside the cells through triggering transporter protein or detoxification mechanisms; (2) host factors and specific genetic and epigenetic alterations that limit drug-target interaction including: poor absorption or penetration to the active site of drug action and increased the metabolism and elimination of the drugs; and (3) various factors and changes that affect the cell survival, like optimized DNA repair mechanism, enhanced survival rate under oxidative stress conditions, and circumvention of apoptotic pathways [9,10].

The energy-depended efflux of a wide variety of amphipathic anti-cancer agents by ATP-binding cassette (ABC) transporters is one of the most important mechanisms conferring an acquired drug resistance. The ABC transporters are one of the largest trans- membranous superfamily of proteins encoded in the human genome [8,11]. Following their recognition 35 years ago, ABC transporters are also called MDR transporters due to their implication in eliciting cancer drug resistance [12]. It is now well established that the over expression of several of these ABC transporters is the main mechanism of MDR (i.e., produces resistance to structurally and mechanistically unrelated compounds) [6,4]. For example, the optimum drug delivery of many chemotherapeutic drugs like vinca alkaloids, taxanes, epipodophyllotoxins, anthracyclines and even the newer class of tyrosine kinase inhibitors could be limited by the overexpression of specific ABC transporters [5].

1.2 Adenosine Tri-Phosphate Binding Cassette (ABC) Transporters

The ABC transporter super family encompasses a wide variety of membrane- associated proteins that are present in all organisms from prokaryotes to eukaryotes [5].

Numerous studies indicate that ABC transporters, by utilizing ATP, actively transport or efflux, a wide variety of substrates, including ions, as well as macro-molecules [5].

In eukaryotes, ABC transporters are located in both plasma membranes and intracellular membranes, including the endoplasmic reticulum, mitochondria, and peroxisome. ABC transporters are present in numerous tissues and organs, including 3

liver, intestine, kidney, lung, and the blood-brain barrier (BBB), where they provide protection against the accumulation of toxic compounds [5]. These transporters are composed of transmembrane domains (TMDs) and distinctive nucleotide-binding domains (NBDs) [8], and the latter is also known as ATP-binding domains, where ATP binds and is hydrolyzed by the ATPase enzyme. The transporters act either as importers, enabling nutrients and other molecules to enter the cells, or as exporters, pumping across the cellular membrane toxic substances, drugs, and lipids, while the exporter ones exist in both prokaryotes and eukaryotes, the importers are only present in prokaryotes [8,13,14]. In eukaryotes, ABC transporter proteins share the same characteristic motifs, which are known as Walker A and B motifs, that are separated by ˷90-120 amino acids [15].

Additionally, there is a unique linker called the C region, which is located upstream of the Walker B site and it makes the ABC transporter proteins distinguishable from other

ATP-binding proteins [15,16,17]. Typically, the so-called functional ABC transporter proteins have two NBDs and two TMDs [18]. The TMDS have 9-11 membrane-spanning

α helices, which play a key role in substrate specificity [17]. NBDs are located in the cytoplasm and they mediate the hydrolysis of ATP and the energy obtained from this process is used to transport the substrate across the membrane (Figure 1) [18,17].

Figure1. The structural scheme of ABCB1 and ABCG2 transporters (A): ABCB1 is a full transporter that has two NBDs and two TMDs that facilitate energy-driven transport through ATP hydrolysis; while (B): ABCG2 is known as half transporter encompassing only one NBD containing ABC and a six membrane-spanning domain. Adapted from “ABC transporters, neural stem cells and neurogenesis–a different perspective.” By T. Lin et al.,2006, Cell Research, 16(11):857-871.Copyright 2006 by T. Lin.

Eukaryotic ABC transporters can be classified as 1) full transporters (i.e. ABCB1), which combine four domains (2 NBDs and 2 TMDs) in a single polypeptide (Figure1); or 2) half transporters (i.e. ABCG2) that are composed of only two domains (one NBD and one

TMD) (Figure 1) [19,20]. It is the general consensus that the half-transporters need to either

homo- or heterodimerize in order to be a functional pump [19]. There are 48 known human

ABC transporter genes [21,22]. The ABC transporter superfamily encompasses 7 subfamilies from ABC- A to G based on amino-acid sequence [23]. The subfamilies are further subdivided in to sub-subfamilies, except for the ABCE/OABP family transporters, which depends on the number, combination, and structural domain similarity or differences in TMDs and NBDs [11,17].

The proposed mechanism for the transport of substrates by ABC-MDR transporters involves number of conformational changes. First, a conformational change in the NBDs is induced when the ligand or substrate enters the cell membrane and binds to a large hydrophobic and high-affinity pocket formed by the TMDs. Second, this ligand-induced conformational change allows for the binding of two ATP molecules to the NBDs. Third, these ATP molecules are hydrolyzed by an ATPase, generating energy that is used in combination with energy released by the formation of the closed NBD dimer to expel or efflux substrates bound in the hydrophobic pocket. Fourth, once the substrate is pumped out of the cell, ADP and inorganic phosphate (Pi), the products of

ATP hydrolysis, are released from the NBD and this leads to the open dimer conformation, thereby allowing the ABC transporter cycle to continue. (Figure 2)

[18,24,25,26,14].

Figure 2. An ATP-switch mechanism of action of ABC transporters The ATP-switch mechanism involves the induction of a conformational change in the NBDs, when the ligand enters the cell membrane and binds to a large hydrophobic, high-affinity pocket is formed by the TMDs. The conformational change will lead to attracting two molecules of ATP to bind to NBDs. Adapted from” Structure and Function of ABC Transporters.” By Kenneth J. Linton, 2007, Physiology,22(2):122- 130.Copyright 2007 by Kenneth J. Linton.

There is an alternative theory known as the constant contact model, which also describes the mechanism by which ABC transporters function [27]. The constant contact model is based on the early alternating site model that proposes an alternating ATP hydrolysis in each NBD, with one site opening and the second site remaining closed with

ATP bound and occluded [28,29]. According to the constant contact model, one site opens adequately, allowing nucleotide release without the full separation of the NBD monomers. Subsequently, when this site is closed with the new ATP molecule, the opposite site will be ready for hydrolysis and the cycle is repeated on an alternating basis

[30]. The modular organization of ABC transporters in a constant contact model is shown in Figure 3 [14].

Figure 3. A constant contact model depicting mechanism of action of ABC transporters The standard composition of ABC transporter is represented by an illustrative cartoon. The ABC transporter encompasses two transmembrane domains, and two nucleotide binding domains. Two conformational states of ABC transporters are revealed: 1) outward facing, where the substrate binding site oriented extracellularly; and 2) inward facing, where the substrate binding site oriented toward the cytoplasm, depicting the alternating access mechanism of transport. Adapted from” ABC transporters: the power to change.” By D C. Rees et.al., 2009, Nature Reviews Molecular Cell Biology, 10(3):218-227. Copyright 2009 by D C. Rees et.al.

According to the ABC transporter function, the ABC superfamily comprises of two groups [31]. The first group consists of the primary active transporter that uses energy generated by ATP hydrolysis to translocate the various substrates across the cellular membrane. The second group encompasses the non-transporter ABC proteins that are localized in the nucleus or cytosol and are used for the maintenance and repair of the

DNA and gene regulation [30]. The ABC transporters have been shown to play a crucial role in most physiological, pharmacological, and pharmacokinetic processes. Also, they are involved in the drug-drug interactions, adverse effects, and therapeutic efficacy of over 50% of clinically prescribed drugs, indicating their economical and clinical importance [18]. The ABC transporters are ubiquitously expressed in a variety of normal 8

cells throughout the human body, where their primary role is to protect the body by extruding a wide variety of endogenous and exogenous xenobiotic compounds or their metabolites, whose accumulation could produce cell damage or dysfunction [32].

Additionally, the ABC transporters are also involved in translocating useful endogenous substrates, including amino acids, peptides, vitamins, lipids, cholesterol and its derivatives, saccharides and many hydrophobic agents [32,12,33,10]. Furthermore, the expression of key ABC transporters particularly, the Multidrug resistance 1 transporter

(MDR1; P-gp - P-glycoprotein or ABCB1), Multi-Drug Resistance Protein1 (MRP1 or

ABCC1), and Breast Cancer Resistance Protein (BCRP; MXR - Mitoxantrone Resistance

Protein or ABCG2) in certain drug disposing organs (i.e. liver, kidneys and intestines) significantly alters the pharmacokinetic [PK] (i.e. absorption, distribution, metabolism and elimination [ADME]) properties, and subsequently, the bioavailability, of several clinical drugs [34,33, 35,6,36].

It should be also noted that mutations in at least 14 ABC genes can produce diseases such as familial high density lipoprotein deficiency and Tangier disease

(ABCA1), Stargard disease (ABCA4), Dubin-Johnson syndrome (ABCC2), Pseudo- xanthoma elasticum (ABCC6), cysticfibrosis (ABCC7), adrenoleukodystrophy

(ABCD1), and sitosterolemia (ABCG5/ABCG8) [37,32,33,12,38,39].

It goes without saying that ABC transporters have an important role in the efflux of various types of endogenous substances and xenobiotics. They are involved in not only producing disease but also altering important PK. Yet, in our study, we focused on the reversal of MDR mediated by ATP transporters and emphasized their crucial role in

MDR to various antineoplastic agents leading to the reduction of intracellular drug

concentration and failure of chemotherapy.

1.3 The Role of ABC Transporters in Cancer Chemotherapy Resistance

As mentioned before, cross-resistance to a wide variety of structurally and

biochemically diverse drugs can result from the over expression of certain ABC

transporters in tumor cells [37]. Numerous studies indicate that specific ABC transporters,

including particularly ABCB1, ABCG2 and ABCC1-5, are involved in mediating MDR

in cancer cells [10,32,40]. Over the past 30 years, the role of those transporters in

chemotherapeutic resistance has been identified. The three major ABC transporters

involved in MDR are shown in Figure 4.

ABCB1 (MDR1) ABCG2 ABCC1 (BCRP) (MRP1)

MDR

Figure 4. The three major ABC transporters that are involved in mediating MDR in cancer

1.3.1 The Role of ABCB1 Transporter in Producing MDR

Human MDR1, also called ABCB1, was the first identified ABC transporter in

1970[4]. Subsequently, the cloning and the identification of the gene that contains the multi-drug resistance phenotype as MDR1 (P-gp or ABCB1) were cloned and identified[41]. ABCB1 is a 170 kDa, membrane-bound glycoprotein and its DNA sequence is located on chromosome 7p21 [42]. The ABCB1 transporter is widely distributed and present in the kidney, liver, intestines, placenta, adrenal gland, choroid plexus, astrocytes, microglia, and the blood capillaries in the brain [32,33,43]. Generally,

ABCB1 transporters extrude or efflux various xenobiotics, thereby protecting cells from cytotoxicity [44]. Indeed, a study has revealed, through using X-ray crystallography, that the ABCB1 transporter can bind and pump various substrates outside the cells due to the presence of multiple binding sites [45].

According to numerous in vitro studies, the accumulation of a broad range of neutral and cationic hydrophobic chemotherapeutic substrates are significantly reduced due to the overexpression of ABCB1 in tumor cells [32,46]. ABCB1 substrates include taxanes (e.g. paclitaxel, docetaxel, etc.), epipodophyllotoxins (e.g. etoposide, teniposide, etc.), vinca alkaloids (e.g. vinblastine, vincristine, etc.), anthracycline (e.g. doxorubicin, daunorubicin, etc.), antibiotics (e.g. dactinomycin, actinomycin D, etc.), and tyrosine kinase inhibitors (TKIs), such as the break point cluster region-abelson BCR-ABL TKIs nilotinib, imatinib and ponatinib; epidermal growth factor receptor (EGFR) TKIs such as gefitinib, erlotinib and osimertinib [9,10,40,47,48,49] and others. 11

1.3.2 The Role of ABCC1 Transporter in Producing MDR

The ABCC1 or MRP1 transporter is a 190-kDa protein that is encoded by the

ABCC1 gene located on chromosome 16p13.1. In 1992, the ABCC1 gene was first cloned from a human lung carcinoma cell line in the laboratory of Cole and Deeley [50,51]. MRP1 is located on the basolateral surface of the epithelium membrane [52,53,54].

The physiological role of the MRP1 has been elucidated using Mrp1 (-/-) knockout mice [55], and Mdr1a/1b (-/-) and Mrp1 (-/-) triple knock-out mice [56,57]. In these mice, it was reported that the efflux of glutathione conjugates, leukotriene C4, and antineoplastic drugs were significantly reduced [58]. The ABCC1 mediates MDR in several types of cancer, including lung, childhood neuroblastoma, ovary, prostate, and breast cancer [59]. ABCC1 has a high affinity for negatively charged lipophilic compounds, in contrast to ABCB1 transporters which have a high affinity for hydrophobic compounds [54].

Although there is only a 15% overlap in the amino acids sequence between

ABCB1 and ABCC1, their substrate profiles overlap to a significant extent [60,59]. They both transport a wide range of compounds, including anthracyclines, vinca alkaloids, antimetabolites, numerous glutathione and glucuronide conjugates of those compounds, and various organic anions [61,62,59].

1.3.3 The Role of ABCG2 Transporter in Producing MDR

The ATP-binding cassette sub-family G (ABCG) encompasses five members including: ABCG1, ABCG2, ABCG4, ABCG5, and ABCG8 [63]. The ABCG2 or BCRP is a 72 kDa half transporter (Figure 1) that is encoded by the human ABCG2 gene localized on chromosome 4q22 [64]. Simultaneously, three independent research groups isolated and identified the ABCG2 gene from both drug-selected model cell lines and a cDNA library [65,66,64]. It is well established that the ABCG2 transporter plays a major role in mediating MDR in many types of cancers [67]. In order to function as a transporter and actively efflux substrates, ABCG2 has to either homo-dimerize or tetramerize

[68,69,70]. In most cases, it has been suggested that ABCG2 tends to form homo-dimers in order to function as active transporters [71]. ABCG2 transporters are expressed in numerous organs and tissues, such as breast, placenta, colon, small and large intestine, alveoli, islets and acinar cells of the pancreas, canalicular membrane of the liver and bile, venous endothelium and in capillaries, adrenal glands, cortical tubules of the kidney and prostate epithelium, and on the luminal surface of the endothelial cells of human brain micro vessels [72,73]. Numerous studies have shown that overexpression of ABCG2 transporters mediates the development of MDR to many anti-cancer drugs in both solid tumors (like small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), colon carcinoma, breast cancer, and hepatic cancer) and hematological malignancies (like acute myelogenous leukemia (AML), acute lymphoblastic leukemia (ALL), and chronic myelogenous leukemia (CML)) [67].

MTX nilotinib etoposide

topotecan sunitinib

doxorubicin lapatinib

mitoxantrone ABCG2 flavopridol

Figure 5. Major anti-cancer drugs, which are substrates of ABCG2 transporter

The ABCG2 transporters have been reported to produce significant resistance to several anticancer agents, for example nucleoside analogs, tyrosine kinase inhibitors, anthracyclines (like doxorubicin and mitoxantrone), topoisomerase inhibitors (like topotecan and SN-38), methotrexate (MTX), and flavopiridol [74,46,75]. Figure 5 illustrates the anticancer drugs that are substrates for ABCG2.

1.4 Strategies to Surmount ABC-mediated MDR

1.4.1 Generations of MDR Modulators

Since the role of ABC transporter-mediated MDR is known to produce chemotherapy failure, research has led to the discovery and testing of compounds in cellular and clinical settings to surmount transporter mediated MDR by modulating their function. These compounds were categorized or classified as first, second or third

generation inhibitors for ABC transporters [76]. Currently, research related to fourth- generation compounds is still in its infancy. These above mentioned classes of compounds have been designated MDR modulators, inhibitors, or chemo sensitizers [76].

By inhibiting the transport function of certain ABC transporters, they can increase the intracellular levels of specific anticancer drugs, thereby increasing their cytotoxic efficacy [77]. The ideal MDR modulator is thought to possess high potency, affinity, and specificity to the specific ABC transporter, without inducing toxic effects in normal cells or tissues [77,78]. During the past two decades, the major challenge in the generation of

ABC modulators resides in difficulties in developing effective, potent, selective, and nontoxic MDR reversal compounds. Several modulators of the oldest discovered ABCB1 transporters have been reported and tested in preclinical and clinical trials [79,80,81,78,8,82].

In 1981, the first generations of MDR inhibitors were discovered. It was shown that the calcium channel blocker verapamil could re-sensitize vincristine-resistant p-388 leukemia cells to vincristine and vinblastine [83]. The first generation of MDR modulators were compounds that were used for other indications such as verapamil

(antihypertensive), quinine (antimalarial), and cyclosporine A (CSA, immuno- suppressant) [84,85,86]. Although some of these compounds had efficacy in preclinical models, they did not produce any beneficial effects in human MDR cancer patients [77].

For example, in phase-III clinical trials in patients with refractory multiple myeloma, the combination of cyclosporine-A (CSA) with vincristine, doxorubicin or dexamethasone failed to achieve significant clinical outcomes. Besides, the unpredictable pharmacokinetic results posed a limitation for the first-generation modulators.

Furthermore, the doses of these compounds required to produce acceptable efficacy in 15

humans resulted in severe or significant toxic effects [87]. Additionally, toxicity from the modulators itself limited their use as MDR modulators. For example, the administration of verapamil, at doses required to overcome the MDR, produced cardiac toxicity [88].

Thus, the use of first generation MDR modulators was discontinued due to lack of efficacy and production of toxic effects [87].

The second generations of MDR-modulators were synthesized to target specific

MDR transporters to circumvent the problems that were inherent to the first-generation modulators. Second generation compounds, such as valspodar (PSC833, a CSA analogue) and biricodar (VX-710), were reported to have lower toxicity and greater efficacy compared to the first-generation compounds [89,90,91]. However, the compounds tested in clinical trials increased the incidence of significant toxic effects when used in combination with standard anticancer drugs due to their inhibition/activation of intestinal and hepatic cytochrome P450s [92,76]. Furthermore, the second-generation MDR modulators lacked significant efficacy when given in combination with clinically approved anti-cancer drugs [89,93].

The third generation of MDR modulators were developed using combinational chemistry and quantitative structure activity relationship (QSAR) with the notion that they would not produce the unwanted pharmacokinetic outcomes associated with the second generation modulators [94,95]. The third generation MDR modulators, such as elacridar (GF120918), laniquidar (R101933), zosuquidar (LY335979) and tariquidar

(XR9576), were reported to inhibit ABCB1 efflux function at nanomolar concentrations

[96,97,98]. Furthermore, the third-generation modulators, such as elacridar, laniquidar, zosuquidar and tariquidar, also selectively inhibited ABCB1, ABCC1, and ABCG2 [97,9]. 16

Thus, based on their specificity and potency it was believed that they would be highly effective in overcoming MDR due to the overexpression of certain ABC transporters.

Currently, a number of third-generation MDR modulators have reached phase I and phase

II clinical trials [99-101]; such as tariquidar [102], zosuquidar [103], laniquidar [104], elacridar

[105]. Recent data indicated that zosuquidar had significant efficacy in restoring chemotherapy sensitivity in AML in phase III clinical trials [106,107]. The use of 3D QSAR pharmacophore modeling has provided promising information on whether or not a specific compound will be effective in inhibiting the activity of specific ABC transporters

[108]. For example, the interaction of tariquidar with the so-called hydrophobic domain is required for inhibition. It has a dimethoxytetrahydroisoquinoline sub-structure and must have a second amide group. The hydrophobic domain is necessary for the inhibitory function of tariquidar. In order to increase the stability of tariquidar as MDR modulator, several analogs were designed using 3D QSAR modeling and contour map analysis [109].

These studies have shown that the presence of a hydrogen bond donor increases the activity of tariquidar analogues by favoring the binding of the modulator to the ABCC1 transporter [109]. It has been reported that tariquidar is a substrate, as well as an inhibitor, for ABCG2 transporter [110]. It is widely known that most of the MDR modulators are

ABCB1 inhibitors. However, ABCC1- and ABCC2- mediated MDR could be reversed by MDR modulators such as argosterol-A (AGA), CSA, biricodar, leukotriene C4, the leukotriene D4-receptor antagonist (MK571) and raloxifene analogues [100,111,112]. In vitro studies indicate that the function of ABCC3 is blocked by sulfinpyrazone, probenecid, and indomethacin [113]. Conversely, there is sparse information regarding compounds that

inhibit ABCA2, ABCB4, ABCB5, ABCB11, ABCC4, ABCC5, ABCC6, ABCC10, and

ABC11[114].

1.4.2 Natural MDR Modulators

Numerous studies over the last decade have reported that natural compounds, such as epigallocatechin [115], curcumin [116,117], capsacin, gingerol [116], citrus phytochemicals [118], rosemary phytochemicals [119], polyphenolic compounds (e.g. flavonoids or stilbenes) [120], and neochamaejasmin B (NCB) [121] inhibit ABCB1, ABCC1, or

ABCG2 transporters in vitro, with low toxicity. However, poor oral bioavailability (due to ineffective delivery and/or metabolic unstability) of the majority of these compounds poses limitations for their clinical use [122]. However, it should be noted that curcumin, if given intravenously in a liposomal form to mice, had acceptable toxicity and bioavailability [122]. Also, compounds from natural sources; such as cytarabine, trabectidine, and Halaven are clinically approved and have been shown to have MDR reversal efficacy [123-126]. However, numerous limitations are associated with many of these natural modulators including unpredictable pharmacokinetic interactions, poor absorption, delivery or stability after administration, low bioavailability, and variation in expression of drug transporter in targeted cells among different individuals [8].

1.4.3 Miscellaneous MDR Modulators

Many classes of compounds have been reported to antagonize MDR-mediated resistance due to ABC transporters such as breakpoint cluster region-abelson (BCR-ABL) tyrosine kinase inhibitors (TKI) including imatinib [127], nilotinib [128], and ponatinib [129], 18

epidermal growth factor receptor (EGFR) TKI including icotinib [130], erlotinib [131],

AST1306 [132] , gefitinib [133], WHI-P154 [134], afatinib [135], lapatinib [136], and canertinib

[137], vascular endothelial growth factor receptor (VEGFR)TKIs including vandetanib

[138], sunitinib [139], sorafenib [140], motesanib[141], and telatinib[142], and phosphodiesterase-

5(PDE-5) inhibitors including sildenafil [143] and vardenafil [144]. All of the aforementioned groups of compounds reverse ABC transporter-mediated MDR either through blocking the efflux function or by reducing the expression level of the ABC transporters [76]. There are many other novel strategies to surmount MDR, including small molecules obtained from versatile scaffolds [145], nanotechnology [146,147,148,149], microRNA and synthetic RNA (siRNAs) that inactivate MDR genes [150,151], and ‘Omics’ technology, which identifies MDR biomarkers [152,153].

1.4.4 Compounds Known to Modulate ABCG2 Transporter-Mediated MDR

Since its discovery in 1998, it has been known that the ABCG2 transporter plays a role in producing MDR in certain types of cancer. Poor clinical outcomes in various cancer types; including breast, non-small lung cancer, and ovarian cancer; have been linked to ABCG2 transporter expression [154]. Therefore, the outcomes of the use of chemotherapeutics can be improved through discovering novel ABCG2 inhibitors that reverse MDR [155]. However, the number and structural variety of ABCG2 inhibitors is still way less investigated as compared with the number of the ABCB1 inhibitors. Indeed, success of the few ABCG2 modulators that have reached clinical trials is limited. One of the first compounds reported to potently and specifically inhibit the ABCG2 transporter was fumitremorgin C (FTC), a neurotoxic mycotoxin [156,157,158]. Actually, FTC was 19

discovered even before the discovery of ABCG2 transporter [157]. It was shown that FTC re-sensitized, or significantly restored, anticancer efficacy when used in combination with mitoxantrone to re-sensitize (ABCG2 overexpressing) mitoxantrone -resistant colon cancer cells [157]. Indeed, in vitro studies showed that 5 µM of FTC increased the efficacy of mitoxantrone, doxorubicin and topotecan by 93-, 26- and 24-fold, respectively. In contrast, 5 µM of FTC did not significantly reverse ABCB1- or ABCC1-mediated MDR

[157]. Unfortunately, in vivo studies revealed that FTC is extremely toxic, thus precluding its clinical use [156]. To increase the potency of FTC and reduce the toxicity of FTC, SAR studies were conducted and this lead to the synthesis of the tetracyclic FTC analogue,

Ko143. Subsequent studies indicated that Ko143 was more potent and selective for

ABCG2 transporters and less toxic than FTC [156,159]. However, its specificity for ABCG2 transporters in both in vivo and clinical studies was challenged by other studies [160].

Numerous compounds have been reported to reverse MDR mediated by ABCG2 transporters in various types of cancer cells and in xenograft tumor mouse models.

Novobiocin was shown to be a specific reversal agent for ABCG2 transporter [161,162,163].

GF120918 (elacridar) is also known to be a potent inhibitor and not a substrate for

ABCG2 transporter [164,165]. There are many other BCRP modulators such as

Erythroblastic leukemia viral oncogene (ErbB1) inhibitors [132,137], pheophorbide [166],

ARRY-334543 [167], acridonederivatives [168], tariquidar [166,110], geftinib [169], erlotinib [131]

,tariquidar analogue [170], substituted chromones [171], estrogen agonists and antagonists

[172], diethylstilbestrol [172], sunitinib [173], artesunat [174], OSI-930 analogues [155], pheophorbide [166], imatinib [175], and novel plant derived synthetic analogue IND [176].

Besides, many TKIs showed ABCG2 reversal activity like telatinib [142], icotinib [177], 20

lapatinib [178],WHI-P154 [134], nilotinib [128], YHO-13177 [179], and AST1306 [132] (see

Table 1 for a detailed summary).

1.5 Dopamine3 receptor (D3R) antagonists

The topology and physicochemical properties of the protein binding sites determine the structural requirements for binding of ABCG2 modulators to the ABCG2 transporter [108]. Many molecular fields (like steric, electrostatic, hydrophobic, and hydrogen bonding) determine the inhibitory potency of the MDR modulators [108]. For example, tariquidar analogues have a para nitro group or a 3,4-dimethoxyphenyl at substituent position R2 and an amide linker, which have positive effects on ABCG2 inhibition [180]. In a similar fashion, QSAR is an important tool for determining the biological activity for compounds based on molecular features and chemical moieties.

Also, QSAR predicts the ABCG2 substrates or inhibitors prior to in vitro and in vivo studies. The number of H-bond acceptors, molar refractivity, number of rotatable bonds, and total hydrophobic van der Waals surface area are the major descriptors for the

ABCG2 pharmacophore. Nilotinib is a potent ABCG2 inhibitors [128]. According to pharmacophore modelling studies, ABCG2 inhibitors encompass six features: one hydrogen bond acceptor; one hydrogen bond donor; one hydrophobic group; and three aromatic rings[181]. Nilotinib is shown to be perfectly aligned with the previous six features, enabling an optimum binding with the ABCG2 transporters [182]. These features are coupled with the hydrophobic nature of nilotinib due to the chemical structure like the hydrogen bond donor feature mapped onto the amide −NH group [182]. We postulate that the D3R antagonists may interact with the ABCG2 transporter as they appeared to have 21

certain structural feature in common (C=O-NH (carboxamide), a long molecular axis, hydrophobicity) with some TKIs compounds like imatinib, dastinib, and nilotinib.

NGB2904, PG01037, SB-277011A, and U99194 maleate are highly potent and selective dopamine D3/D2 antagonists, except U99194, which is a mixed dopamine3 and dopamine2 antagonist (Figure 6). Both in vitro and in vivo studies have shown their effectiveness in addiction paradigms for nicotine, cocaine, alcohol, heroin, and methamphetamine [183-189] based on the literature and publications of clinicaltrials.gov,

The D3R antagonists lead molecule, GSK598,809, failed in clinical trials prematurely because of the toxicity and poor pharmacokinetic profile [190-194], precluding the role of all other D3R antagonist as a target for the treatment of psychostimulant addictions and limiting the translation of pre-clinical results of the other D3R antagonists into the clinic

[195].

Herein, we will briefly discuss the major limitations of D3R antagonists used in our study, as potential medication for psychostimulant addictions. Owing to their high molecular weights (MWs) and lipophilicities, D3R antagonists share features like lower blood brain barrier (BBB) permeability, and lower solubility [196]. It is well-known that

[197] cocaine has major cardiovascular side effects . Due to the presence of D3R in the kidneys, D3R antagonists appeared to increase the blood pressure (BP), especially if they were co-administered with cocaine [198,199]. Being a non-selective dopamine receptor antagonist, U99194 was not a compound of interest for further research [200,201,202].

GlaxoSmithKline (GSK) found that the limitation for the pursuant of clinical studies of

NGB2904 resides in the poor solubility, low bioavailability and the short half-life [203].

Linking to the fact that SB-277011A is rapidly metabolized by hepatic aldehyde oxidase 22

enzyme, primate in vivo studies have shown poor bioavailability and short half-life properties of SB-277011A [204]. However, other in vivo studies demonstrate good pharmacokinetics properties for this compound. With slight chemical structure modification of NGB2904, PG01037 showed a favorable pharmacokinetics profile like improved water solubility, and D3R antagonists’ selectivity. However, being a substrate for ABCB1 in the BBB limits its clinical success in terms of psychostimulant addiction treatments [205].

ABCG2 and ABCB1 transporters are widely distributed in the BBB, limiting the

[206] access of D3R antagonists and various compounds into the brain . Studies have shown that the active-efflux ABC transporters restrict the brain distribution of the D3R antagonist compound YQA-14, suggesting that D3R antagonists are likely substrates of

ABC transporters [207]. Additional studies have revealed that PG010037 is a substrate for

ABCB1 in the BBB [196,205]. Originally, nilotinib had a major role in overcoming ABCG2 and ABCB1 MDR in cancer [128]. According to bioluminescence imaging-based high- throughput assay, acepromazine, which has a dopamine inhibitory effect in BBB, inhibits

ABCG2 transporter in ABCG2 overexpressed tumors [208]. No previous studies have shown the role of D3R antagonists in overcoming MDR due to ABCG2 transporter in cancer cells. Therefore, in our study, we test D3R antagonists to see their capability of modulating ABCG2-mediated MDR in both lung and colon cancer resistant models.

A. C.

Figure 6. Chemical structures of D3 receptor antagonists A. NGB2904 B. PG01037 C. SB-277011A D. U99194 maleate

1.6 Objectives and Aims

Aim1: In this study, we sought to determine the interactions of certain D3 receptor antagonists (PG01037, NGB2904, SB-277011A, and U99194) with ABCG2 transporters. Our aim was to determine if D3R antagonists (PG01037, NGB2904, SB-

277011A, and U99194) could attenuate ABCG2-mediated resistance to the anticancer drugs mitoxantrone (MX) and doxorubicin (DOX) in well-established drug-selected lung cancer resistance models (H460-MX20, A549-MX10), and colon cancer resistance models (S1-M1-80). In addition, we looked at the reversal potential of these D3R antagonists in an ABCG2 transfected wild type-human embryonic kidney cell line -

HEK293-482R2. To our knowledge, our study is the first to investigate the efficacy of

PG01037, NGB2904, SB277011A and U99194 to surmount ABCG2-mediated resistance.

Aim 2: We aimed to examine the effects of both PG01037 and NGB2904 on

1) efflux function of ABCG2 using the well-established substrate rhodamine 123 accumulation assay; and 2) on the levels of ABCG2 protein expression using western blot analysis and immunocytochemistry; and 3) binding affinity on the ABCG2 binding sites using molecular modelling studies.

Chapter 2

Materials and Methods

2.1 Materials

NGB2904, PG01037, SB277011A dihydrochloride, and U99194 maleate were purchased from Tocris Bioscience (Bristol, UK). Mouse monoclonal antibody (BXP-21) for

ABCG2 was purchased from Novus Biologicals (Littleton, CO, USA). Nilotinib was purchased from Sigma-Aldrich (St. Louis, MO, USA). Mitoxantrone was purchased from

Selleck Chemicals (Houston, TX, USA). Doxorubicin was purchased from Enzo Life

Science, Inc. (Farmingdale, NY, USA). Rhodamine 123 fluorescent dye was purchased from Marker Gene Technologies, Inc. (Eugene, OR, USA). 3-(4,5-dimethylthiazol-2-yl)-

2,5-diphenyltetrazolium bromide (MTT) was purchased from Calbiochem EMD

Millipore (Billerica, MA, USA). Dulbecco’s modification of Eagle’s medium (DMEM) and 0.25% trypsin + 2.2 Mm ethylenediaminetetraacetic acid (EDTA), phosphate buffered saline (PBS without calcium or magnesium), and DMEM (phenol red - free) were purchased from Mediatech, Inc. (Corning subsidiaries, Manassas, VA, USA). Fetal

Bovine Serum (FBS) was purchased from Atlanta Biologicals (Flowery Branch, GA,

USA). Penicillin/streptomycin was purchased from Lonza, Inc. (Allendale NJ, USA).

Propidium Iodide (PI) and 4’,6-diamidino-2-phenylindole, dihydrochloride (DAPI) was purchased from Molecular Probes (Eugene, OR, USA). Dimethyl sulfoxide (DMSO) was purchased from VWR Analytical (Radnor, PA, USA). Monoclonal antibody against glyceraldehyde 3-phosphate dehydrogenase (GAPDH), monoclonal antibody against beta-actin (β-actin), anti-mouse secondary antibody, and anti-mouse Alexa Fluor ® 488 were purchased from Cell Signaling Technology (Danvers, MA, USA). Bovine serum albumin (BSA) standard protein, bicinchoninic acid (BCA) solution, and copper solution were purchased from G-Biosciences (St. Louis, MO, USA). Paraformaldehyde (powder form) was purchased from Fisher Scientific (Hampton, NH, USA). Mini-Protean®

TGX™ precast Gels, Clarity™, and Clarity Max™ Western ECL Blotting Substrates were purchased from BIO-RAD Laboratories (Hercules, CA, USA). Polyvinylidene difluoride (PVDF) membrane was purchased from Thermo Fisher Scientific (Waltham,

MA, USA). Non-fat dry milk was purchased from Cell Signaling (Danvers, MA, USA).

Tween-20 was purchased from Fisher Scientific (Springfield Township, NJ, USA)

2.2 Cell Lines and Cell Culture

The S1, S1M1-80, A549, A549-MX10, H460 and H460-MX20 cell lines were a gift from the late Dr. Gary Kruh (University of Chicago, IL). All the cell lines were grown as adherent monolayers in flasks with DMEM cultured media supplemented with

10% FBS and 1% streptomycin/penicillin in a humidified incubator with 5% CO2 at

37°C. The human embryonic kidney 293 (HEK293)/pcDNA3.1 and wild type HEK293-

R2 (ABCG2-482-R2) cell lines were originally generated by transfecting HEK293 cells with either the empty pcDNA3.1 vector or the pcDNA3.1 vector containing the full 27

length ABCG2 gene, coding for arginine (R) at amino acid 482. The resistant colon cancer cell line, S1M1-80 was originally established by maintaining colon cancer S1 cells in increasing concentrations of mitoxantrone up to 80 µM [209]. The ABCG2 overexpressing, non-small cell lung cancer (NSCLC) cell line, A549-MX10, was established by selecting and maintaining A549 cells with mitoxantrone up to 10µM [210,209-211]. All of the aforementioned cell lines were cultured in media with 2 mg/ml of G418 [212] until 1 week before experimentation.

2.3 Determination of Cell Cytotoxicity by MTT Assay

The MTT colorimetric assay was used to analyze the sensitivity of cells to anticancer drugs, as previously described [213]. Briefly, after harvesting the cells with 0.25% trypsin, both resistant and parental cancer cell lines were re-suspended in DMEM. Cells were seeded evenly (160 µl/well) into 96 well-plates in triplicate at 5000 cells/well and the plates were returned to the incubator, allowing cells to attach to the wells for up to 24 h. For the reversal experiments, various concentrations of NGB2904, PG01037, SB-

277011A dihydrochloride, U99194 maleate, or 5µM nilotinib (20 µL/well) were added during the second day of the experiment, followed by different concentrations of doxorubicin and mitoxantrone (20 µL/well) ranging from 0.1 to 100 µM into the same wells. After 72 h of incubation, 20 µL of the MTT solution (4 mg/ml) was added to each well. Subsequently, the plates were further incubated for 4 h to allow the viable cells to biotransform the yellow-colored MTT into dark-blue formazan crystals. The media was aspirated and 100 µl of DMSO was used to dissolve the formazan crystals. The absorbance was measured using the Synergy H1 Multi-Mode Hybrid Reader from

BioTek (Winooski, VT, USA) at 570 nm. The IC50 was determined using the Bliss 28

method [214], which is based on the change in the percentage of viable cells after the addition of chemotherapeutic drugs, with or without the reversal compounds. Resistance was determined by dividing the IC50 obtained in the resistant cancer cells (with or without the reversal compounds) by the IC50 of the non-resistant, parental cancer cells.

2.4 Cell Morphological Analysis

Cell images were taken using an inverted microscope (Olympus, BX53F) (Center

Valley, PA) with a fluorescent lamp and digital camera. Morphological changes were observed 72 h after incubation with the chemotherapeutic drugs mitoxantrone and doxorubicin alone, or the combination of the chemotherapeutic drugs with the D3 receptor antagonists at different concentrations.

2.5 Protein Estimation: Cell lysate Preparation and Bicinchoninic acid (BCA) Analysis H460-MX20 cells, in T25 flasks, were incubated with 5 µM of either NG2904 or

PG01037 for either 24 or 48 hrs. The media was aspirated and the cells were rinsed with

5 ml of PBS drop by drop, followed by gentle shaking and aspiration of PBS. Two ml of

PBS was added three times to the cells, which were collected for lysis with the use a cell scraper to detach the cells. During the transfer of the cells from flasks to 15 ml tubes, they were kept on ice. The tubes were centrifuged at 1500 rpm for 3 minutes and the supernatant was discarded and the white pellets were kept for the cell lysis step. The cytosolic fraction was extracted by the addition of 400 µL of ice-cold prepared buffer A lysis buffer [1M HEPES-KOH (pH 7.9), 45 mM MgCl2, 300 mM KCL, 50 mM dithiothreitol (DTT), 100 mM phenylmethylsulfounyl fluoride (PMSF), and 3ml of a 29

protease inhibitor cocktail (ThermoScientific)] to each sample. The sample pellets were re-suspended through vortexing and transferred to Eppendorf tubes. The cell homogenates were kept on ice for 15 minutes and 23 µL of NP40 was added to each sample for 2 minutes. The samples were centrifuged at 13,000 rpm for 1 minute and the supernatant layer, which contains membranous proteins, was taken by aspiration with a pipette and kept at – 20° C until analysis. The concentrations of the proteins in the samples were determined using the BCA assay. A standard curve, using 8 different concentrations of bovine serum albumin, was prepared. The working solution used was composed of BCA solution and copper solution in a ratio of 50 parts BCA: 1part copper solution. Two hundred µl of the working solution was added to the samples and standard wells. After incubating the plate at 37 °C, the absorbance was measured at 562 nM using the Synergy H1 Multi-Mode Hybrid plate reader from BioTek (Winooski, VT, USA) with Gen 5 software. The calibration curve was used to determine the concentration of protein samples.

2.6 Western Blot Analysis

Protein samples were analyzed by loading equivalent amounts (20 µg) onto

7.5% SDS-polyacrylamide gels using Mini-PROTEAN® Tetra Cell from Bio-Rad

(Hercules, CA, USA). The proteins were separated based on their molecular weight and then transferred to a PVDF membrane, which was previously activated using methanol.

To prevent non-specific binding, the membrane was incubated for 1 h with 5% non-fat milk in TBS-T (10x tris buffered saline (TBS) [24.2 g Tris base, 80 g NaCl, 1N HCl, 38 ml] containing 0.1% Tween-20) before adding the primary BXP-21 anti-ABCG2 30

antibody (1:1000). The membrane was incubated with the primary antibody overnight at

4 °C with gentle shaking. After overnight incubation, the membrane was washed three times with TBS-T washing buffer. Before adding the horseradish peroxide (HRP)-linked anti-mouse secondary antibody (1:3000; cell signaling), the membrane was incubated with blocking buffer. Subsequently, the membrane was incubated with the secondary antibody for 90 min at room temperature and washed 3 times with TBS-T buffer. The

Western ECL blotting substrates (Western peroxide reagent, and clarity Western luminol enhancer) were added in a 1:1 ratio before reading the blots with a Molecular imager®

ChemiDoc™ XRS+ from BIO RAD (Hercules, CA, USA). Either β-actin or GAPDH was used as a house-keeping control for protein samples. Image quantification analysis of

Western blots was done using either Image Lab (Hercules, CA, USA) or Image J software (NIH, Bethesda, USA).

2.7 Immunocytochemistry

The H460-MX20 cells were seeded at a density of 2X105 per ml on coverslips inside six well plates and left overnight. Coverslips had been sterilized in 1N HCl and washed with distilled water and soaked with 100% ethanol 24 h previously. On the second day, 5 µM of NGB2904 or PG01037 were added for 24 or 48 h, respectively. The cells were fixed with 4% paraformaldehyde for 20 min and then rinsed three times with

PBS. A 7.5% bovine serum albumin (BSA) blocking buffer (Sigma-Aldrich, St. Louis)

(MO, USA) was added to the cells for 1 h at room temperature and the cells were incubated with a monoclonal antibody BXP-21 against ABCG2 (1:200) overnight at 4 ˚C.

The cells were washed three times with PBS and blocked with BSA before incubation 31

with anti-mouse Alexa Fluor fluorescent secondary antibody (1:500) for 1h at room temperature. Coverslips were placed over labeled glass slides and mounted with 1-2 drops of DAPI for staining the nucleus, and were sealed. The slides were allowed to dry for about 1-3 h before taking images. The images were taken using a Nikon TE-2000s fluorescence microscope (Melville, NY, USA). Fluorescein isothiocyanate (FITC) was excited at 488 nm and light emission measured at 558 nm, whereas DAPI was excited at

350 nm and light emission measured at 470 nm. The images were analyzed using the

Nikon NIS Elements microscope imaging software and image J software.

2.8 Rhodamine 123 Accumulation and Efflux Assay

The ABCG2 overexpressing NSCLC H460-MX20 cells were seeded at a density of 5 X105 cells per ml in six-well plates and allowed to attach overnight. Each plate was incubated for 1 h with 5 µM of NGB2904, PG01037, or nilotinib. Thereafter, 5 µM rhodamine 123 was added and the cells further incubated for 1 h. The cells were rinsed twice with ice-cold complete phenol red-free media. The cells were further incubated at

37 °C in a rhodamine-free media in the presence or absence of 5 µM of NGB2904 or

PG01037 for 1 or 2 h, respectively, to allow the efflux of rhodamine. Subsequently, the cells were harvested at the indicated efflux times (0, 1 or 2 h) and centrifuged at 400 g for

5 min, washed twice with ice-cold PBS, and dispersed in 1 ml of PBS. Cellular rhodamine 123 accumulation was analyzed in 10,000 events per 1 ml of the sample using a flow cytometer from Accuri C6 Cytometers, Inc. (Ann Arbor, MI, U.S) and the data was captured using C Flow® Plus software. The data were further analyzed using either FCS

Express 5 Plus (Glendale, CA, U.S) and/or Flow Jo V10 software. 32

2.9 The Effect of the D3 Receptor Antagonists on the Efficacy of Mitoxantrone and Doxorubicin

In order to determine if D3 receptor antagonists can increase the efficacy of anticancer drugs, such as mitoxantrone and doxorubicin, the combination index (CI) was determined based on the Chou and Talalay method [215]. The CI represents a quantitative measure of the magnitude of the additive, synergistic or antagonistic drug effects [215].

The data were analyzed using CompuSyn software (CompuSyn, NJ). The CI values are interpreted as follows: antagonism, CI > 1; addition, CI=1; and synergism, CI< 1. The fraction affected value (Fa) corresponds to the percent of cells that survive: Fa= 0 when the percentage of cells surviving = 100%, Fa =1 when the percentage of cells surviving is equal to 0%.

2.10 Molecular Docking Studies

2.10.1 Ligand Structure Preparation

The structures of the four D3 receptor antagonists were constructed using the builder module of Maestro v 9.3.5 and the energy minimized by Macromodel program v9.9 (Schrödinger, Inc., New York, NY, 2012), using the OPLSAA force ﬁeld with the steepest descent, followed by a truncated Newton conjugate gradient protocol. The low- energy 3D structures of the four D3 receptor antagonists were generated by LigPrep v2.5 and the parameters were deﬁned based on different protonation states at physiological pH

± 2, and all possible conformations were ﬁltered with a maximum relative energy difference of 5 kcal/mol to exclude redundant conformers. The ligand structures obtained from the LigPrep v2.5 run were further used for generating 100 ligand conformations for

each structure using the default parameters of mixed torsional/low-mode sampling. The output conformational search (Csearch) ﬁle containing 100 unique conformers of each D3 receptor antagonist was used as input for docking simulations at the binding site of human ABCG2.

2.10.2 Protein Structure Preparation

A homology model of ABCG2 was constructed as previously reported [216], using mouse apoprotein (PDB ID: 3G5U)[45] as a template for the molecular docking studies.

The homology model of ABCG2 was optimized using the 'Protein Preparation Wizard' workflow implemented in the Schrödinger molecular modeling suite (Schrödinger, Inc.,

New York, NY, 2012). This optimization includes adding hydrogen atoms, assigning correct bond orders and building disulfide bonds. The protonation states of all of the ionizable residues were predicted by PROPKA provided in the protein preparation wizard. An optimized structure model was energy minimized (only hydrogen atoms) using the OPLS2005 force field. The refined protein model was used to generate various grids based on the following residues as centroids: Arg482 (grid 1), Asn629 (grid 2),

Arg383 (grid 3), and Leu241 along with Gly83 (grid 4). The selection of these residues was based on their significant involvement in ABCG2 function as demonstrated in mutational experiments [217,218,219,212]. The grid 2 generated using Asn629 as the centroid was found to have the best docking score; hence, docking analyses were based on binding mode of four D3 receptor antagonists at this site.

2.10.3 Docking Protocol

The diverse conformational library of NGB2904, SB-277011A, PG01037, and

U99194 were docked at the generated grid 2, using the ‘‘Extra Precision’’ (XP)[220] mode of Glide program v5.8[221] (Schrödinger, Inc., New York, NY, 2012), with the default functions. The best docked conformations of the D3 receptor antagonists were established by high XP GScore and used for further analysis.

2.11 Statistical Analysis

At least 2 to 3 independent experiments were done for each of the above- mentioned assays. Data were expressed as the mean ± standard deviation (SD) in cell survival assays and as the mean ± standard error of the mean (SEM) in all other assays.

Statistical analyses were performed using GraphPad prism software 5.04 from GraphPad

Software, Inc. (La Jolla, CA, U.S). The data were analyzed using a one-way analysis of variance (ANOVA). Post hoc analyses were performed using either Dunnett’s test, a test for linear trends to show dose- or time–dependent effects or Tukey’s multiple comparison test. The a priori significance level was set at p < 0.05.

Chapter 3

Results

3.1 The Effect of D3R antagonists on the Efficacy of Mitoxantrone and Doxorubicin in Cell Lines Overexpressing ABCG2 Transporters

There are two critical aspects to interpreting MDR reversal: the choice of comparison cell lines, and determination if cell viability is generally affected by the drugs being studied. First, using the appropriate pairs of MDR-ABC transporter overexpressing cell lines (resistant cells) and non-resistant cell lines is crucial. Therefore, we chose both drug selected cell line pairs, including H460, H460-MX20, A549, A549-MX10, S1, and

S1M1-80, as well as and transfected ABCG2 cell lines, including HEK293 and HEK293-

R2 as shown in Figures 8, 9, 10, 11, 12, and 13. Second, we determined the effect of the

D3 receptor antagonists on cells viability. The IC50 values of U99194, NGB2904,

PG01037, and SB-277011A alone in H460 cells were 87, 70, 63, 73 µM, respectively. In contrast, the IC50 values of U99194, NGB2904, PG01037, and SB-277011A alone in

ABCG2-overexpressing cells H460-MX20 were 133, 159, 122, and 130 µM, respectively as shown in Figure 7.

The aforementioned IC50 values suggest that quite high concentrations of the D3 receptor antagonists are required to significantly decrease cell viability when 36

administered alone. Based on the above data, we used concentrations from 0.1 to 10 µM for each D3 receptor antagonist to determine their efficacy for sensitizing ABCG2- mediated MDR using mitoxantrone and doxorubicin, which are ABCG2 transporter substrates [222]. PG01037, at concentrations of 0.1, 0.5, 1, 2.5, 5, and 10 µM, significantly reduced the IC50 of mitoxantrone in both the H460-MX20 and A549-MX10 cell lines

(Table 1, Table 2, and Figure 8). Additionally, PG01037 significantly reduced the IC50 of mitoxantrone in S1-M180 cells at concentrations of 1, 2.5, 5, and 10 µM (Table 3,

Figure 8). Similarly, 5 µM nilotinib (an inhibitor of ABCB1 and ABCG2 [128]) significantly reduced the IC50 of mitoxantrone in H460-MX20, A549-MX10 and S1M1-

80 cell lines (Tables 1-3 and Figure 8). However, neither NGB2904 nor PG01037 significantly altered the cytotoxicity of mitoxantrone in the parental H460, A549, or S1 cell lines (Tables 1- 3).

NGB2904, at concentrations of 0.01, 0.1, 0.5, 1, 2.5, 5, or 10 µM, significantly reduced the IC50 of mitoxantrone in H460-MX20 cells (Table 1 and Figure 9).

Furthermore, NGB2904 significantly reduced the IC50 of mitoxantrone in A549-MX10

(0.1, 0.5, 1, 2.5, 5, or 10 µM) and S1-M180 (1, 0.5, 1, 2.5, 5, or 10 µM) cell lines (Tables

2 and 3, and Figure 9). SB-277011A, at concentrations of 1, 2.5, 5, and 10 µM, significantly reduced the IC50 of mitoxantrone in both H460-MX20 and A549-MX10 cells (Tables 1 and 2, and Figure 10). SB-277011A also significantly reduced mitoxantrone’s IC50 in H460-MX20, A549-MX10, and S1-M180 cell lines, in a concentration–dependent manner, at concentrations of 2.5, 5, and 10 µM (Tables 1-3, and Figure 10). U99194, at concentrations of 1, 2.5, 5, and 10 µM, significantly reduced the IC50 of mitoxantrone in both H460-MX20 and A549-MX10 cells (Tables 1 and 2, 37

and figure 11). U99194A significantly reduced the IC50 of mitoxantrone in S1-M180 cells at concentrations of 2.5, 5, and 10 µM (Table 3 and Figure 11). Also, U99194, in a concentration-dependent manner significantly reduced the IC50 of mitoxantrone in H460-

MX20, A549-MX10, and S1-M180 at 2.5, 5, and 10 µM (Tables 1- 3 and Figure 11). At concentrations, up to 5 µM, NGB2904, PGO1037, and SB-277011A produced a significant reduction in the IC50 of mitoxantrone in ABCG2 overexpressing transfected wild-type (HEK293-R2) cells (Table 4 and Figure 13). However, U99194 did not produce a significant change in the IC50 of mitoxantrone. Furthermore, U99194, at a concentration of 5µM, significantly reduced the IC50 of doxorubicin. (Table 5 and

Figure 12). The combination of 5µM of PG01037 or NGB2904 with mitoxantrone produces cell morphological changes exemplified by a significant reduction in the number of living cells and the shifting of the IC50 for mitoxantrone in H460-MX20

ABCG2 overexpressing cells, corroborating the synergistic effects of D3 receptor antagonists (Figures 16 I).

3.2 D3 Receptor Antagonists Synergistically Increase the Efficacy of Mitoxantrone and Doxorubicin

Achieving a synergistic therapeutic effect and reducing the onset of drug resistance are the main goals of drug combinations in cancer treatment [223]. Thus, we determined if 5 or 10 µM NGB2904, PG01037, SB-277011A, or U99194 produced synergistic effects in combination with mitoxantrone or doxorubicin, in H460-MX20 cells. The CI values were determined using the CI ranges values table (Table 7)[224,225] with an Fa range from 0 to 1. The combination of 10 µM PG 01037 and 0.1-100 µM mitoxantrone produced a strong synergistic effect (CI = 0.1-0.3; Figure 16A) and the 38

combination of 1 µM of mitoxantrone and 10 µM of PG 01037 produced a very strong synergistic effect (CI<0.1; Figure 16A). Similarly, the combination of 10 µM NGB2904 and 1-30 µM mitoxantrone produced a very strong synergistic effect (CI <0.1; Figure

16B). 10 µM NGB2904 combined with 0.1 µM mitoxantrone, as well as 100 µM mitoxantrone combined with 10 µM NGB2904, produced synergism, albeit to a lesser extent (CI = 0.3-0.7; Figure 16B). However, the combination of 0.3 µM mitoxantrone and 10 µM NGB2904 produced a strong synergism (CI value = 0.1-0.3; Figure 16B).

The combination of 10 µM SB-277011A with 0.3-100µM mitoxantrone produced a strong synergistic effect (CI value=0.1-0.3; Figure 16C). However, the combination of

10 µM SB-277011A and 0.1 µM mitoxantrone showed synergism (CI value=0.3-0.7;

Figure 16 C). Finally, the combination of 10 µM U99194 and 0.3-100 µM mitoxantrone produced a strong synergistic effect (CI 0.1-0.3; Figure 16D), although 10 µM U99194 and 0.1 µM mitoxantrone elicited only moderate synergism (CI = 0.7-0.85; Figure 16D).

The combination of 5 µM PG01037 and 0.03-1 µM doxorubicin produced a strong synergism (CI value=0.1-0.3; Figure 16E), whereas 3 µM doxorubicin and 5 µM

PG01037 produced synergism (CI value=0.3-0.75; Figure 16E). In contrast, 5 µM

PG01037 and 10 µM doxorubicin produced an antagonistic effect (CI = 1.45-3.3; Figure

16E).

The combination of 5 µM NGB2904 and 0.1-3 µM doxorubicin produced synergism (CI value = 0.3-0.75; Figure 16F). However, 5 µM NGB2904 and 0.03 µM doxorubicin and 5 µM NGB2904 and 10 µM doxorubicin produced antagonism (CI

=1.45-3.3; Figure 16F). The combination of 5 µM SB-277011A and 0.03-10 µM doxorubicin produced synergism (CI=0.3-0.75, Figure 16G). However, 10 µM 39

doxorubicin and 5 µM SB-277011A produced a moderate antagonism (CI value=1.2-1.5;

Figure 16G). The combination of 5 µM U99194 and 0.3-3 µM doxorubicin produced synergism (CI=0.3-0.75; Figure 16H). Similarly, 0.03 µM doxorubicin and 5 µM

U99194, as well as 0.1 µM doxorubicin and 5 µM U99194 produced moderate synergism

(CI=0.7-0.85, Figure 16H). However, 10 µM doxorubicin and 5 µM U99194 produced moderate antagonism (CI=1.2-1.45; Figure 16H). (Tables 8 and 9 summarize the CI values for the combinations of D3 receptor antagonists and mitoxantrone or doxorubicin).

3.3 PG01037 and NGB2904 Significantly Decrease the Protein Expression levels of the ABCG2 Transporter

NGB2904 and PG01037-induced increases in the efficacy of mitoxantrone and doxorubicin in cells overexpressing ABCG2 transporters could result from: 1) inhibiting the efflux function of ABCG2 transporter; 2) a reduction in the ABCG2 protein level; or

3) a decrease in the number of ABCG2 transporters present in the cell membrane. Based on cell viability results, PG01037 and NGB2904 were the most efficacious compounds for reversing ABCG2-mediated MDR. Therefore, we tested the in vitro effects of

NGB2904 and PG01037 on the expression of ABCG2 protein levels. The incubation of

H460-MX20 cells (which overexpress ABCG2 transporters) with 5 µM of PG01037 for

24 or 48 h significantly reduced the protein expression levels of the ABCG2 transporter

(Figure 14 B). Additionally, the incubation of cells with 5 µM of NGB2904 for 48 h significantly reduced the protein expression levels of ABCG2 transporter (Figure 14B).

The above results were further corroborated by immunocytochemistry assays, which 40

showed a significant down-regulation of the ABCG2 transporter after 48 h of incubation of cells with 5 µM PG01037 or 5 µM NGB2904 (Figure 14C). The fluorescence- integrated density of cells incubated with either PG01037 or NGB2904 was significantly reduced compared with the control cells (Figure 14C). Thus, NGB2904 and PG01037 significantly reverse ABCG2-mediated MDR through the down-regulation of the ABCG2 protein. However, these compounds may also attenuate ABCG2-mediated MDR via additional mechanisms (see below).

3.4 PG01037 and NGB2904 Significantly Inhibit the Efflux Flunction of the ABCG2

Transporter

To further elucidate the mechanisms by which PG01037 and NGB2904 attenuate

ABCG2-mediated MDR, we determined their effect on the cellular accumulation of the fluorescent dye rhodamine 123, a substrate for ABC transporters [226,227]. Based on cell viability results, PG01037 and NGB2904 were the most potent compounds for reversing

ABCG2-mediated MDR. Therefore, we tested the in vitro effect of NGB2904 and

PG01037 on ABCG2 efflux. The intracellular levels of rhodamine 123, which correspond to the fluorescence intensity, were measured in the presence or absence of NGB2904,

PG01037, or nilotinib (used as a positive control) in H460-MX20 cells. The intracellular accumulation of rhodamine in H460-MX20 cells incubated with 5µM of PG01037,

NGB2904 or nilotinib was significantly greater than in the control (i.e. no treatment)

H460-MX20 cells (Figure 15). This occurred because the rhodamine 123 fluorescence intensity in control H460-MX20 cells was substantially and significantly reduced over time at the 1 and 2 h time-points, reflecting the continuous efflux, as compared with the 0 41

h time-point. By contrast, no reductions were observed in either the PG01037- or

NGB2904-treated cells.

3.5 Molecular Docking of SB277011A, NGB2904, PG01037, and U99194A as Determined Using a Homology Model of the ABCG2 Transporter

Molecular docking studies were performed for the four D3 receptor antagonists using a homology model of ABCG2 following a previously reported protocol[142]. The docking models predicted by Glide indicated that all the D3 receptor antagonists bind at the substrate binding site of the ABCG2 transporter, predominantly through hydrophobic interactions. The binding conformation of PG01037 is similar to NGB2904, whereas SB-

277011A and U99194 exhibit a different binding pattern compared to PG01037 and

NGB2904.

As shown in Figure 17A, the piperazinyl ring, with an attached 2,3 dichlorophenyl moiety in PG01037, is positioned in a hydrophobic pocket of the ABCG2 transporter formed by Tyr464, Phe489, Phe511, Ile573, Tyr576, and Leu581, thereby enabling hydrophobic interactions. This placement is further stabilized by an electrostatic interaction between the 3-Cl atom in the phenyl ring and the -OH group of Tyr576. The

4-(pyridin-2-yl) benzamide of PG01037 also binds favorably in another hydrophobic pocket formed by the side chains of Leu626, Trp627, and His630, along with Val631.

The orientation of the 2-pyridinyl ring in the hydrophobic pocket also facilitates a polar interaction with Arg465. The benzamido -NH group forms a hydrogen bond with the imidazole ring nitrogen of His630 (NH•••N-His630, 2.1 Å). This interaction is significant

as it had been demonstrated previously that His630 from each monomer plays a critical role in the function of ABCG2 [228].

The compound with the next highest docking score, NGB2904, adopts a similar binding conformation to that of PG01037, differing only in the orientation of 9H- fluorenyl ring in the hydrophobic pocket formed by the side chains of Leu626, Trp627, and His630, along with Val631. This is mainly due to steric hindrance caused by the increased planarity of 9H-fluorenyl ring compared to the 2-phenylpyridine ring in

PG01037 (Figure 17 B).

The glide predicted docking models for SB-277011A and U99194 (Figure 17 C, and D) revealed differences in the binding mode compared to PG01037 and NGB2904 at the Asn629 centroid-based grid of ABCG2. This is not surprising given the polyspecificity associated with substrates for ABCG2. For SB-277011A, the quinoline ring is stabilized by hydrophobic contacts with amino acid residues Ile573, Tyr464,

Phe489, Tyr570, Ile573, Pro574, and Leu581. Furthermore, the quinoline ring nitrogen atom also forms a hydrogen bond with the hydroxyl group of Tyr464 (N•••HO-Tyr464,

2.13 Å). The cyclohexyl ethyl linker between the quinolinyl-4-carboxamide and 5,6,7,8- tetrahydronaphthalene-2-carbonitrile moieties are involved in extensive hydrophobic interactions with Ala580, Leu581, Phe511, Trp627, and His630. The orientation of the

5,6,7,8-tetrahydronaphthalene-2-carbonitrile moiety is stabilized through hydrophobic contacts with side chains of Phe507, Val508, and Leu633. In addition, the nitrile group present in the 5,6,7,8-tetrahydronaphthalene ring is also involved in electrostatic interactions with the basic amino group of Lys628.

U99194, the least ranked molecule in our docking analysis, adopts a binding conformation that positions the 5,6-dimethoxy-2,3-dihydro-1H-indene ring in the hydrophobic pocket lined by side chains of amino acid residues Phe511, Ala580, His630,

Leu633, and Trp627. The oxygen atom in the methoxy group attached to the indene ring forms a hydrogen bond with the caboxamido -NH2 group of Asn629 (O•••HN-Asn629,

2.1 Å). The n-propyl side chains of the 2- dipropylamino group attached to C2 of the 2,3- dihydro-1H-indene ring were stabilized through hydrophobic contacts with the side chains of Ile412, Phe489, Gly577, Leu581, Pro574, and Trp627. The XP GScores for

PG01037, NGB2904, SB-277011A, and U99194 were -9.704, -9.299, -9.068, and -6.525, respectively.

Chapter 4

Tables & Figures

Table 1: Select ABCG2 modulators

Effect on ABCG2 compound Concentration Challenges Substrate Accumulation Efflux Expression Selectivity FTC 1,5 µM ⁺ ↑ N/A N/A Specific inhibitor neurotoxicity of ABCG2

(FTC analouges) 0.25,0.2,0.1µM ⁺ ↑ ↓ N/A Specific inhibitors rapid metabolisim Ko143,Ko123,k0134 of ABCG2 in rat plasma & selectivity Novobiocin 300 µM ⁺ ↑ ↓ N/A Specific inhibitor of ABCG2 potency

Pheophorbide 10 µM ⁺ ↑ ↓ N/A Specific inhibitor N/A of ABCG2

Elacridar 0.25,1,10 µM ⁺ ↑ ↓ N/A Dual Inhibitor of selectivity ABCB1 &ABCG2

Tariquidar 1 µM ⁺ ↑ ↓ N/A Dual Inhibitor of selectivity ABCB1 &ABCG2

Tariquidar analouge 10 µM ⁺ ↑ ↓ N/A Specific inhibitor lack of in vivo of ABCG2 studies

Diethylstilbestrol 30 µM ⁺ ↑ ↓ N/A N/A potency and lack of in vivo studies

Imatinib 1 µM ⁺ ↑ ↓ N/A N/A selectivity& lack of mechanistic clarity

Geftinib 0.5,1,10 µM ⁺ ↑ ↓ N/A Dual Inhibitor of selcectivity ABCB1 &ABCG2

Erlotinib 10 µM ⁺ ↑ ↓ ↔ Dual Inhibitor of selcectivity ABCB1 &ABCG2

Lapatinib 1& 2.5 µM ⁺ ↑ ↓ ↔ Dual Inhibitor of selcectivity ABCB1 &ABCG2

Artesunate 100µM ⁺ N/A N/A ↓ N/A Selectivity

WHI-P154 4µM ⁺ ↑ ↓ ↔ N/A Selectivity

AST1306 1µM ⁺ ↑ ↓ ↔ N/A Selectivity

Sunitinib 0.62, 1.25,&2.5µM ⁺ ↑ ↓ ↔ N/A Selectivity

Nilotinib 2.5,5,10 µM ⁺ ↑ ↓ ↔ Dual Inhibitor of Selectivity ABCB1 &ABCG2

Telatinib 1µM ⁺ ↑ ↓ ↔ N/A Selectivity

YHO-13177 0.5µM ⁺ ↑ ↓ ↓ Specific inhibitor N/A of ABCG2

OSI-930 10µM ⁺ ↑ ↓ ↔ Specific inhibitor N/A of ABCG2 IND 7 & IND8 10µM ⁺ ↑ ↓ N/A N/A N/A

The symbols depict the activity of above listed compounds on ABCG2 transporters. For example, (+): reverse the ABCG2 mediated MDR; (-) has no reversal activity on ABCG2;(↑): increase or up-regulate; (↓): decrease or down-regulate; (↔):no significant changes; (N/A): not applicable.

Table 2: The effect of NGB2904, PG01037, SB-277011A, U99194A, and nilotinib on the cytotoxicity of mitoxantrone in ABCG2-overexpressing H460-MX20 cells

IC ± SD (µM)a Treatment 50 H460 FRb H460-MX20 FRb Mitoxantrone 0.25 ± 0.01 1 6.26 ± 0.03 25 + NGB2904 - 0.01 µM 0.27 ± 0.02 1 0.6 ± 0.05*** 2.4 + NGB2904- 0.1 µM 0.14 ± 0 0.6 0.44 ± 0.02*** 1.8 + NGB2904 - 0.5 µM 0.15 ± 0 0.6 0.5 ± 0.02*** 1.8 + NGB2904- 1 µM 0.13 ± 0.02 0.5 0.47 ± 0.01*** 1.8 + NGB2904- 2.5 µM 0.11 ± 0 0.4 0.45 ± 0*** 1.7 + NGB2904- 5 µM 0.18 ± 0 0.7 0.44 ± 0.09*** 1.7 + NGB2904- 10 µM 0.16 ± 0.05 0.6 0.45 ± 0*** 1.7 + Nilotinib - 5 µM 0.16 ± 0.04 0.6 0.4 ± 0*** 1.5

+ PG01037 - 0.1 µM 0.2 ± 0.01 0.8 2.2 ± 0.08*** 8.5 + PG01037 - 0.5 µM 0.14 ± 0.01 0.6 2 ± 0.05*** 8 + PG01037 - 1 µM 0.13 ± 0.01 0.5 0.46 ± 0.05*** 1.8 + PG01037 - 2.5 µM 0.17 ± 0 0.6 0.46 ± 0*** 1.8 + PG01037 - 5 µM 0.14 ± 0 0.6 0.4 ± 0.04*** 1.6 + PG01037 - 10 µM 0.18 ± 0.02 0.7 0.4 ± 0.05*** 1.6 + Nilotinib - 5 µM 0.16 ± 0.04 0.6 0.4 ± 0*** 1.5

+ SB-277011A - 1 µM 0.14 ± 0.1 0.5 3.75 ± 0.05*** 15 + SB-277011A - 2.5 µM 0.18 ± 0 0.7 3.6 ± 0*** 14 + SB-277011A - 5 µM 0.21 ± 0.04 0.8 1.8 ± 0.1*** 7 + SB-277011A - 10 µM 0.17 ± 0 0.66 0.84 ± 0.04*** 3.32 + Nilotinib - 5 µM 0.16 ± 0.04 0.6 0.4 ± 0*** 1.5

+ U99194 - 1 µM 0.23 ± 0 0.9 5 ± 0.05*** 20 + U99194 - 2.5 µM 0.16 ± 0.06 0.6 4.2 ± 0.2*** 16.6 + U99194 - 5 µM 0.26 ± 0.05 0.9 3.5 ± 0.08*** 14 + U99194 - 10 µM 0.13 ± 0.02 0.5 0.8 ± 0.02*** 3 + Nilotinib - 5 µM 0.16 ± 0.04 0.6 0.4 ± 0*** 1.5

a IC50 data is presented in the two columns H460 and H460-MX20 for the two cell lines as mean ± SD (standard deviation) of at least three experiments conducted in triplicate. b Fold resistance (FR) is presented in the adjacent columns, calculated as described in the materials and methods. The percentage of surviving cells was determined using the MTT assay. Statistical significance was determined in comparison to the control condition (mitoxantrone alone) *P<0.05; **P<0.01; ***P<0.001.

Table 3: The effect of NGB2904, PG01037, SB-277011A, U99194A, and nilotinib on the cytotoxicity of mitoxantrone in ABCG2-overexpressing A549-MX10 cells

IC ± SD (µM)a Treatment 50 A549 FRb A549-MX10 FRb Mitoxantrone 0.26 ± 0.02 1 1.51 ± 0.05 6 + NGB2904- 0.1 µM 0.27 ± 0 1 0.5 ± 0*** 1.7 + NGB2904 - 0.5 µM 0.22 ± 0.02 0.9 0.27 ± 0.01*** 0.9 + NGB2904- 1 µM 0.18 ± 0.07 0.7 0.24 ± 0.05*** 0.9 + NGB2904- 2.5 µM 0.21 ± 0.05 0.8 0.24 ± 0*** 0.9 + NGB2904- 5 µM 0.2 ± 0 0.7 0.25 ± 0.02*** 0.9 + NGB2904- 10 µM 0.22 ± 0.01 0.9 0.22 ± 0.02*** 0.9 + Nilotinib - 5 µM 0.23 ± 0.01 0.9 0.27 ± 0.01*** 1

+ PG01037 - 0.1 µM 0.25 ± 0.03 1 0.5 ± 0.06*** 1.8 + PG01037 - 0.5 µM 0.21 ± 0.02 0.8 0.24 ± 0.04*** 0.9 + PG01037 - 1 µM 0.18 ± 0.03 0.7 0.24 ± 0.06*** 0.9 + PG01037 - 2.5 µM 0.2 ± 0 0.8 0.25 ± 0.03*** 0.9 + PG01037 - 5 µM 0.23 ± 0.03 0.9 0.27 ± 0.01*** 0.9 + PG01037 - 10 µM 0.12 ± 0.01 0.44 0.24 ± 0.02*** 0.9 + Nilotinib - 5 µM 0.23 ± 0.01 0.9 0.27 ± 0.01*** 1

+ SB-277011A - 1 µM 0.24 ± 0.03 0.9 0.7 ± 0.1*** 2.6 + SB-277011A - 2.5 µM 0.24 ± 0.04 0.9 0.5 ± 0.03*** 1.9 + SB-277011A - 5 µM 0.25 ± 0.04 0.9 0.43 ± 0.07*** 1.6 + SB-277011A - 10 µM 0.23 ± 0.03 0.9 0.21 ± 0.03*** 0.9 + Nilotinib - 5 µM 0.23 ± 0.01 0.9 0.27 ± 0.01*** 1

+ U99194 - 1 µM 0.17 ± 0.01 0.7 0.4 ± 0.06*** 1.6 + U99194 - 2.5 µM 0.2 ± 0.07 0.8 0.4 ± 0.05*** 1.5 + U99194 - 5 µM 0.25 ± 0.02 1 0.26 ± 0.02*** 1 + U99194 - 10 µM 0.23 ± 0.01 0.9 0.23 ± 0.01*** 0.9 + Nilotinib - 5 µM 0.23 ± 0.01 0.9 0.27 ± 0.01*** 1

a IC50 data is presented in the two columns A549 and A549-MX10 for the two cell lines as mean ± SD (standard deviation) of at least three experiments conducted in triplicate. b Fold resistance (FR) is presented in the adjacent columns, calculated as described in the materials and methods. The percentage of surviving cells was determined using the MTT assay. Statistical significance was determined in comparison to the control condition (mitoxantrone alone) *P<0.05; **P<0.01; ***P<0.001.

Table 4: The effect of NGB2904, PG01037, SB-277011A, U99194A, and nilotinib on the cytotoxicity of mitoxantrone in ABCG2-overexpressing S1M1-80 cells

a IC50 ± SD (µM) Treatment b S1 FR S1M1-80 FRb Mitoxantrone 0.9 ± 0.08 1 80 ± 0.08*** 88 + NGB2904- 1 µM 0.8 ± 0.06 0.9 23 ± 0.01*** 25 + NGB2904- 2.5 µM 0.42 ± 0.05 0.5 10 ± 0.1*** 11 + NGB2904- 5 µM 0.6 ± 0.03 0.7 6 ± 0.08*** 6 + NGB2904- 10 µM 0.8 ± 0.1 0.83 6 ± 0.02*** 6 + Nilotinib - 5 µM 0.14 ± 0.03 0.15 0.81 ± 0.02*** 0.9

+ PG01037 - 1 µM 0.74 ± 0.03 0.8 27 ± 0*** 29 + PG01037 - 2.5 µM 0.8 ± 0.06 0.9 9 ± 0.01*** 10 + PG01037 - 5 µM 0.74 ± 0.01 0.8 6 ± 0.01*** 6.6 + PG01037 - 10 µM 0.74 ± 0.07 0.8 6 ± 0.09*** 6.6 + Nilotinib - 5 µM 0.14 ± 0.03 0.15 0.81 ± 0.02*** 0.9

+ SB-277011A - 2.5 µM 0.8 ± 0.1 0.9 27 ± 0*** 30 + SB-277011A - 5 µM 0.83 ± 0 0.9 20 ± 0.1*** 21.4 + SB-277011A - 10 µM 0.83 ± 0.07 0.9 8 ± 0.09*** 8 + Nilotinib - 5 µM 0.14 ± 0.03 0.15 0.81 ± 0.02*** 0.9

+ U99194 - 2.5 µM 0.9 ± 0 1 24 ± 0.09*** 26 + U99194 - 5 µM 0.9 ± 0.03 1 23 ± 0.07*** 25 + U99194 - 10 µM 0.7 ± 0 0.8 16 ± 0.1*** 17 + Nilotinib - 5 µM 0.14 ± 0.03 0.15 0.81 ± 0.02*** 0.9 a IC50 data is presented in the two columns S1 and S1M180 for the two cell lines as mean ± SD (standard deviation) of at least three experiments conducted in triplicate. b Fold resistance (FR) is presented in the adjacent columns, calculated as described in the materials and methods. The percentage of surviving cells was determined using the MTT assay. Statistical significance was determined in comparison to the control condition (mitoxantrone alone) *P<0.05; **P<0.01; ***P<0.001.

Table 5: The effect of 5 µM of U99194A, NGB2904, SB-277011A, PG01037 and nilotinib on the cytotoxicity of mitoxantrone in ABCG2- transfected HEK293-R2 cells

IC ± SD (µM)a Treatment 50 HEK293 FRb HEK293-R2 FRb Mitoxantrone 0.08 ± 0.02 1 0.2 ± 0.01 2.5 + U99194 - 5 µM 0.02 ± 0.3 0.25 0.18 ± 0.01 2.25 + NGB2904 - 5 µM 0.08 ± 0.01 1 0.09 ± 0.01*** 1.125 + SB-277011A- 5 µM 0.06 ± 0.01 0.75 0.08 ± 0.03*** 1 + PG01037 - 5 µM 0.008 ± 0.01 0.1 0.01 ± 0.01*** 0.1 + Nilotinib - 5 µM 0.008 ± 0.03 0.1 0.04 ± 0.01*** 0.5 a represents the mean ± SD (standard deviation) of the IC50 value changes for mitoxantrone alone (the control group) or in combination with 5 µM of NGB2904, PG01037, SB-277011A, or U99194 in at least three in depended experiments conducted in triplicate. b Represents the fold resistance(FR), which was calculated as described in the Material and Methods. The magnitude of cell survival was determined using the MTT assay, as previously described in the Materials and Methods. ***P< 0.001 against the value of IC50 in the presence of mitoxantrone alone and the absence of NGB2904, PG01037, SB-277011A, U99194, or nilotinib.

Table 6: The effect of 5 µM of U99194A, NGB2904, SB-277011A, PG01037 and nilotinib on the cytotoxicity of doxorubicin in ABCG2 overexpressing H460-MX20 cells

IC ± SD (µM)a Treatment 50 H460 FRb H460-MX20 FRb Doxorubicin 0.14 ± 0.07 1 0.4 ± 0.05 3 + U99194 - 5 µM 0.13 ± 0.06 0.9 0.3 ± 0.08*** 1.9 + NGB2904 - 5 µM 0.16 ± 0.04 1 0.2 ± 0.04*** 1.5 + SB-277011A- 5 µM 0.12 ± 0.04 0.9 0.2 ± 0.02*** 1 + PG01037 - 5 µM 0.12 ± 0.03 1 0.1 ± 0.01*** 1 + Nilotinib - 5 µM 0.16 ± 0.07 1 0.2 ± 0.07*** 1 a represents the mean ± SD (standard deviation) of of the IC50 value changes for doxorubicin alone (the control group) or in combination with 5 µM of NGB2904, PG01037, SB-277011A, or U99194 in at least three in depended experiments conducted in triplicate. b Represents the fold resistance (FR), which was calculated as described in the Material and Methods. The magnitude of cell survival was determined using the MTT assay, as previously described in the Materials and Methods”. ***P< 0.001 against the value of

IC50 in the presence of doxorubicin alone and the absence of NGB2904, PG01037, SB-277011A, U99194, or nilotinib.

Table 7: Characterization of CI range values based on Chou-Talalay method[224,225].

Combination Interpretation Index (CI)

<0.1 Very strong synergism 0.1–0.3 Strong synergism 0.3–0.7 Synergism 0.7-0.85 Moderate synergism 0.85-0.9 Slight

synergism 0.9-1.1 Nearly additive 1.1-1.2 Slight antagonism 1.2-1.45 Moderate antagonism 1.45-3.3 Antagonism 3.3-10 Strong antagonism >10 Very strong antagonism

Table 8: Combination index (CI) values resulting from the combination of MX with PG01037, NGB2904, SB-277011A, and U99194 MXa PG01037 CIb NGB2904 CIb SB-277011A CIb U99194 CIb dose (µM) dose(µM) dose(µM) dose(µM) dose(µM) 0.1 10 0.24 10 0.61 10 0.36 10 0.82 0.3 10 0.11 10 0.15 10 0.16 10 0.16 1 10 0.09 10 0.03 10 0.19 10 0.13 3 10 0.13 10 0.02 10 0.16 10 0.19 10 10 0.1 10 0.03 10 0.04 10 0.18 30 10 0.27 10 0.08 10 0.11 10 0.14 100 10 0.2 10 0.13 10 0.2 10 0.2

a MX: mitoxantrone, b CI: combination index.

Table 9: Combination index (CI) values resulting from the combination of Dox with PG01037, NGB2904, SB-277011A, and U9914

DOXa PG01037 CIb NGB2904 CIb SB-277011A CIb U99194 CIb dose (µM) dose(µM) dose(µM) dose(µM) dose(µM) 0.03 5 0.31 5 1.52 5 0.62 5 0.78 0.1 5 0.25 5 0.46 5 0.28 5 0.85 0.3 5 0.27 5 0.47 5 0.41 5 0.54 1 5 0.23 5 0.26 5 0.19 5 0.23 3 5 0.51 5 0.57 5 0.51 5 0.64 10 5 1.63 5 1.8 5 1.58 5 1.52 30 5 4.78 5 4 5 4.67 5 4

aDox: doxorubicin, bCI: combination index.

Figure 7. The effect of NGB2904, PG01037, SB-277011A, U99194 and nilotinib on the survival of parental H460 and ABCG2 overexpressing H460-MX20 cells. The MTT cytotoxicity assay survival rates are shown for H460 and H460-MX20 cells incubated with A:

NGB2904, B: PG01037, C: SB-277011A, and D: U99194. E: the IC50 values of the D3 receptor antagonists for H460 and H460-MX20 cells. Data points represent the mean ± SD of at least three independent experiments repeated in triplicate.

Figure 8. The ABCG2 mediated mitoxantrone-MDR reversal potential of PG01037 is shown in ABCG2 overexpressing lung cancer resistant H460-MX20, A549-MX10, and colon cancer resistant S1M1-80 cells.

MTT cytotoxicity expressed as IC50 values for mitoxantrone alone (control) or in combination with different concentrations of PG01037 or with 5 µM nilotinib (a known inhibitor of the ABCG2 transporter) in H460-MX20 cells (A), A549-MX10 cells (C), and S1M1-80 cells (E). The results also show the changes in cell survival percentages in H460 and H460-MX20 cells (B), A549 and A549-MX10 cells (D), and S1 and S1M1-80 cells (F). Data points represent the means ± SD of at least three independent experiments, each with triplicate determinations. The data were analyzed using a one-way ANOVA with Dunnett’s post hoc to compare the IC50 of mitoxantrone in combination with different concentrations of PG01037 or with 5 µM nilotinib (a known inhibitor of the ABCG2 transporter) in H460-MX20 cells (*** P<0.001) vs. control cells treated with mitoxantrone alone.

Figure 9. The effect of NGB2904 on ABCG2-mediated resistance to mitoxantrone in H460-MX20, A549-MX10, and S1M1-80 cell lines

MTT cytotoxicity expressed as IC50 values for mitoxantrone alone (control) or in combination with different concentrations of NGB2904 or with 5 µM nilotinib (a known inhibitor of the ABCG2 transporter) in H460-MX20 cells (A), A549-MX10 cells (C), and S1M1-80 cells (E). The results also show the changes in the percentage of surviving cells in H460 and H460-MX20 cells (B), A549 and A549-MX10 cells (D), and S1 and S1M1-80 cells (F). Data points represent the means ± SD of at least three independent experiments, each with triplicate determinations. The data were analyzed using a one-way ANOVA with Dunnett’s post hoc comparisons of IC50 values of mitoxantrone in combination with different concentrations of NGB2904 or with 5 µM nilotinib (a known inhibitor of the ABCG2 transporter) in H460- MX20 cells (*** P<0.001) vs. control cells treated with mitoxantrone alone.

Figure 10. The effect of SB-277011A and nilotinib on the efficacy of mitoxantrone (MX) in H460-MX20, A549-MX10and S1M1-80 cells.

The IC50 values for mitoxantrone alone (the control group) or in combination with different concentrations of SB-277011A or with 5 µM of nilotinib in A: H460-MX20 cells C: A549-MX10 cells E: S1M1-80 cells. The changes in cell survival percentages in B: H460 and H460-MX20 cells D: A549 and A549-MX10 cells F: S1 and S1M1-80 cells. Data points represent the mean ± SD of at least three independent experiments done in triplicate. The data were analyzed using a one-way ANOVA with Dunnett’s post hoc test (***

P<0.001), where the IC50 values for cells that are incubated with combination of MX+SB were compared with MX alone (control). Also, a post-test for a linear trend showed a concentration-dependent reduction in the IC50 values of MX in combination group as compared to the IC50 values of MX alone (control).

Figure 11. The effect of U99194A and nilotinib on the efficacy of mitoxantrone (MX) in H460-MX20, A549-MX10 and S1M1-80 cells.

The IC50 values for mitoxantrone alone (the control group) or in combination with different concentrations of U99194A or with 5µM nilotinib (a known inhibitor of ABCG2 transporter) in A: H460-MX20 cells C: A549-MX10 cells E: S1M1-80 cells. The changes in cell survival percentages in B: H460 and H460-MX20 cells D: A549 and A549-MX10 cells F: S1 and S1M1-80 cells. Data points represent the means ± SD of at least three independent experiments done in triplicate. The data were analyzed using a one-way ANOVA with Dunnett’s post hoc test (*** P<0.001), where the IC50 values for cells that are incubated with combination of MX+SB were compared with MX alone (control). Also, a post-test for a linear trend showed a concentration-dependent reduction in the IC50 values of MX in combination group as compared to the IC50 values of MX alone (control).

Figure12: The effect of NGB2904, PG01037, SB-277011A, or U99194 on the survival curve and the IC50 values of doxorubicin in ABCG2 overexpressing H460-MX20 cells.

A. Percentage cell survival changes and B. the IC50 value changes for doxorubicin alone (the control group) or in combination with 5 µM of NGB2904, PG01037, SB-277011A, or U99194. Data points represent the mean ± SD of at least three independent experiments done in triplicate. ***P< 0.001 against the value of IC50 in the presence of doxorubicin alone and the absence of NGB2904, PG01037, SB-277011A, U99194, or nilotinib.

Figure13. The effect of NGB2904, PG01037, SB-277011A, or U99194on the survival curve and the IC50 values of mitoxantrone in ABCG2 transfected HEK293-R2 cells.

A. Percentage cell survival changes and B. the IC50 value changes for mitoxantrone alone (the control group) or in combination with 5 µM of NGB2904, PG01037, SB-277011A, or U99194. Data points represent the mean ± SD of at least three independent experiments done in triplicate. ***P< 0.001 against the value of IC50 in the presence of mitoxantrone alone and the absence of NGB2904, PG01037, SB- 277011A, U99194, or nilotinib.

Figure 14. The effects of PG01037 and NGB2904 on the protein expression of ABCG2 transporter. A: The baseline expression of the ABCG2 protein in H460 and H460-MX20 cell lines. B. H460-MX20 cells incubated with both 5 µM NGB2904 and 5 µM PG01037 for 24 and 48 h, respectively. Columns in the lower lanes represent the mean of the Western blot quantification values. The error bars represent the SEM. At least two other trials showed a similar result to the representative figure results. The data were analyzed using a one-way ANOVA and Dunnett’s post hoc comparisons (*P<0.05 vs. control group). C: Immuno-cytochemical analysis of H460-MX20 cells after incubation with 5 µM of both NGB2904 and PG01037 for 48 h is shown. In the immunofluorescence image, the ABCG2-specific antibody is shown in green and the nuclear staining with DAPI is shown in blue. In addition to the representative figure, at least three independent experiments were performed using different batches of cells at different times. The fluorescence integrated density was quantified and is represented by the lower lane bar graph. The data were analyzed using a one-way ANOVA, followed by Dunnett’s post hoc comparisons (*** P<0.001 vs. control group).

A. B.

Figure 15. The effect of PG01037, NGB2904, and nilotinib on the the accumulation and efflux of intracellular rhodamine 123 in ABCG2 overexpressing H460-MX20 cells. A: Rhodamine efflux at 0, 1, and 2 h is shown. The treatment groups were: black: control untreated H460- MX20 cells; red: 5 µM NGB2904; blue, 5 µM PG01037; green: 5 µM nilotinib. Rhodamine efflux is determined by comparing treated and untreated groups in H460-MX20 cells, using a one-way ANOVA, followed by a post hoc test for linear trends. B: The intracellular rhodamine accumulation was expressed as the units of mean fluorescent intensity. The data represent the mean ± SEM of triplicate determinations. The data for the efflux experiments at 0, 1, and 2 h was analyzed using a one-way ANOVA, followed by Tukey’s multiple comparison post hoc test (#, P<0.05 and ##, P< 0.01 vs. control 1 h; ***, P<0.001 vs control 2 h).

Figure 16. The combination index values resulting from combining PG01037, NGB2904, SB-277011A, and U99194A with mitoxantrone and doxorubicin

CI values for 10µM PG01037 (A), 10µM NGB2904 (B), 10µM SB-277011A (C), and 10µM U99194 (D) in combination with 0.1, 0.3, 1, 3, 10, 30, 100 µM of mitoxantrone; CI values for 5µM PG01037 (E), 5µM NGB2904 (F), 5µM SB-277011A (G), and 5µM U99194 (H) in combination with 0.1, 0.3, 1,3,10, 30 µM of doxorubicin for Fa range from 0 to1. CI< 1, synergism; CI=1, additive effect; CI>1, antagonism. Data represent the mean ± SD of three independent experiments, each in triplicate. (I): Microscopic images illustrating the synergistic effects of PG01037 and NGB2904 on the potentiation of MX cytotoxicity at different concentrations.

Figure 17. Model for the binding of PG01037, NGB2904 and SB-277011A, U99194 with the ABCG2 transporter. XP-Glide predicted binding mode of PG01037 (A), NGB2904 (B), SB-227011A (C), and U99194 (D) with homology modeled ABCG2. Important amino acids are depicted as sticks with the atoms colored as: carbon = green; hydrogen = white; nitrogen = blue; oxygen = red; and sulfur = yellow. The ligand PG01037 is shown with the same color scheme except for the carbon atoms, which are represented by yellow and chlorine atoms are represented by dark green. The red dotted lines represent hydrogen bonding. (A schematic diagram of the protein–ligand interaction is shown for PG01037 (E), NGB2904 (F), SB- 227011A (G) and U99194 (H). Blue circles represent polar amino acids; green circles represent hydrophobic amino acids and purple arrows represent side chain donor/acceptor interactions.

Chapter 5

Discussion

This study is the first to report that D3 receptor antagonists increase the efficacy of ABCG2 substrate cancer therapeutics. Specifically, the D3 receptor antagonists

PG01037, NGB2904, SB-277011A, and U99194 significantly increase the efficacy of mitoxantrone and doxorubicin (ABCG2 substrates) in the ABCG2 overexpressing cancer cell lines H460-MX20, A549-MX10, and S1M1-80. Furthermore, at 5 µM, PG01037,

NGB2904, SB-277011A, and U99194 significantly enhanced the efficacy of mitoxantrone in a transfected wild-type ABCG2 overexpressing cell line, HEK293-R2.

By contrast, the above listed D3 receptor antagonists did not significantly sensitize the parental cell lines H460, A549, S1, or HEK293, which do not overexpress ABCG2 transporters, to mitoxantrone or doxorubicin. This finding suggests that the D3 receptor antagonists selectively reverse ABCG2-mediated MDR. It is unlikely that the D3 receptor antagonists used in this study were producing toxicity alone as the concentrations used

(0.1-10 μM) were well below concentrations that decreased cell viability.

PG01037 and NGB2904, at a concentration of 0.1 µM, significantly reduced fold- resistance (e.g. the sensitized cell line compared to the non-sensitized cell line) in A549-

MX10 cells from 6 to 1.8 and from 6 to 1.7, respectively. Both SB-277011A and

U99194, in a concentration-dependent manner, significantly reduced fold-resistance and restored sensitivity in H460-MX20, S1M1-80, and A549-MX10 cell lines to

mitoxantrone. However, SB-277011A and U99194 were not as potent as PG01037 and

NGB2904 in decreasing the resistance fold of mitoxantrone in the same cell lines.

Although it is unknown why NGB2904 and PG01037 are more efficacious than

SB277011A and U99194A, these findings do appear to follow a similar pattern to aspects of the molecular docking analyses. Although U99194 has a significantly lower docking score than NGB2904 and PG01037, the docking score for SB277011A was not significantly different from NGB2904 and PG01037. Thus, factors other than the affinity for the ABCG2 transporter may explain the differences in efficacy. The mode of binding was most similar between NGB2904 and PG01037, compared to SB277011A and

U99194A. As previously reported, nilotinib significantly increased the efficacy of mitoxantrone and doxorubicin [128]. Nilotinib, at a concentration of 1, and 2.5 µM, significantly reduces the fold-resistance of HEK293-R2 cells to mitoxantrone and doxorubicin as compared with the FTC [128].

Previous studies have identified selective and efficacious ABCG2 modulators, but these compounds produced significant toxicity and/or drug-drug interactions, thereby preventing their use in the clinic [156]. For example, in vitro studies show that 5 µM FTC augments the efficacy of mitoxantrone, doxorubicin and topotecan by 93-, 26- and 24- fold, respectively [157]. However, in vivo studies indicate that FTC is extremely toxic, thus precluding its clinical use [156]. Other studies have shown that nilotinib is an ABCG2 substrate and inhibitor [229,128]. Nilotinib binds and interacts with the ABCG2 transporter substrate binding sites and inhibits the efflux function of the ABCG2 transporter [229]. We postulated that D3 receptor antagonists could inhibit the ABCG2 transporter and/or be a substrate, based on structural homology to TKIs. However, MTT results alone cannot 70

determine if a compound is an ABCG2 substrate. Mechanistic assays, such as the

ATPase assay, photo-affinity labeling, and membrane vesicle uptake assays are necessary to ascertain if D3 receptor antagonists bind to the ABCG2 substrate sites.

Many previous studies have reported that using drug combinations in cancer treatment has many advantages compared to use of a single drug [230,231,225]. The combination treatment data from the present studies presented here corroborate previous

MTT results, where the most potent compounds in term of reversing ABCG2-mediated

MDR were NGB2904 and PG01037, which produced strong and very strong synergism, respectively. The combination of 10 µM PG01037 and 0.1-100 µM mitoxantrone produces strong to very strong synergism. Similarly, the combination of 10 µM

NGB2904 with 1-30 µM mitoxantrone produces strong to very strong synergism. The combination effects of both SB-277011A and U99194 ranged from synergism to strong synergism as well. However, the results obtained with combinations of 0.03-30 µM doxorubicin and 5 μM of the D3 receptor antagonists were more variable, producing effects ranging from synergism to antagonism. It is possible that using lower concentrations of the D3 receptor antagonists, which significantly augmented mitoxantrone efficacy, may produce less variable results (i.e. synergism only).

Another major finding of this study was that PG01037 and NGB2904 maintained concentrations of rhodamine123, an ABCG2 substrate, in H460-MX20 cells by preventing drug efflux. In addition, as previously reported [176], 5 µM nilotinib also maintained intracellular levels of rhodamine123. Moreover, the magnitude of the effects of NGB2904 and PG01037 on the maintenance of intracellular rhodamine levels was similar to what was observed with nilotinib treatment. These results, in combination with 71

the docking analyses for NGB2904 and PG01037, suggest that these compounds surmount ABCG2-mediated resistance to doxorubicin and mitoxantrone by inhibiting the efflux function of the ABCG2 transporter. However, additional studies must be conducted to determine if the D3 receptor antagonists are binding directly to the efflux site of ABCG2 transporters or act through another mechanism. Our results with the D3 receptor antagonists are consistent with those reported for other compounds, such as

Ko143[232], novobiocin[162], elacridar[233], tariquidar analogue [170], imatinib[175], lapatinib[178], and nilotinib[128], which have been shown to inhibit ABCG2 efflux function in cell lines overexpressing ABCG2 transporters.

The D3 receptor antagonists used in this study countered ABCG2-mediated resistance by downregulating the levels of the ABCG2 protein. PG01037 and NGB2904 were the most efficacious drugs at reversing ABCG2-mediated resistance to mitoxantrone and doxorubicin. Our results indicated that the incubation of H460-MX20 cells for 24 or

48 hours with 5 µM PG01037 or 5 µM NGB2904 significantly decreased levels of the

ABCG2 protein. Our results indicated that the incubation of H460-MX20 cells for 24 or

48 hours with 5 µM of either PG01037 or NGB2904 significantly decreased the levels of the ABCG2 protein. Previous studies showed that one of the mechanisms responsible for reversing ABCG2 mediated MDR is the down regulation of the ABCG2 transporter[234,235,179]. For example, artesunate and YHO-13177 were shown to reverse

ABCG2 mediated MDR through downregulation of ABCG2 [174,179]. Data in other studies suggest that c-jun N-terminal kinase, mitogen-activated protein kinases, phosphate and tensin homolog, epidermal growth factor receptor and human epidermal growth factor

(EGFR), among others, mediate the expression of ABCG2 in various cancer cell lines 72

[236]. PD153035 (an EGFR antagonists) could significantly decrease the expression level of ABCG2 at the transcription[237], as well as post-translational level, but further study is needed to determine how PD153035 downregulates ABCG2 expression.

Perhaps PG01037 and NGB2904 decrease ABCG2 protein levels by inducing rapid internalization and degradation via lysosomes[238] and/or proteasomes[238]. Finally,

PG01037 and NGB2904 may decrease protein expression levels by lowering ABCG2 gene transcription or decreasing mRNA stability. Clearly, future studies must be conducted to delineate the mechanism(s) by which PG01037 and NGB2904 downregulate ABCG2 protein expression. Immunocytochemistry studies support these western blot findings. ABCG2 fluorescence integrated intensity is significantly reduced in H460-MX20 cells treated with 5 µM of both NGB2904 and PG01037 for 48 h as compared to untreated cells. Data indicate that depending on the context, autophagy can increase tumor growth [239]. Interestingly, a recent study has shown that autophagy elicited by certain stressors is augmented in cancer cell sublines that overexpress ABCG2 transporters [240]. In addition, in HeLa cells, ammonia increases autophagy via activation

[241] of dopamine D3 receptors and inhibition of mTOR . Therefore, it is possible that the efficacy of the D3 antagonists, in part, may result from a decrease in autophagy, which can contribute to a decrease in cancer cell survival. However, experiments must be conducted to verify the hypothesis.

One of the important structural aspects determining drug interactions with the

ABCG2 transporter is the presence of an amine group bonded to one carbon of a heterocyclic ring[242]. Thus, the presence of the carboxamide group in these drugs was 73

one of the main criteria suggesting that D3 receptor antagonists might have a high binding affinity for ABCG2 transporters. The docking scores obtained from our docking analysis corroborates this hypothesis as PG01037 and NGB2904 have high binding affinities for the ABCG2 transporter, with values of -9.704, and -9.299, respectively. SB-277011A has an XP GScore of -9.068, while U99104 had the lowest XP GScore, which was -6.525.

U99194’s low docking score may result from its smaller size (Molecular Weight 277.4) compared to the other ligands (Molecular Weight >430) that permit only limited interaction with the amino acids in the binding site of ABCG2.

Modulation of the ABCG2 transporter by these D3 receptor antagonist drugs has several potential implications beyond cancer treatment. D3 receptor antagonist drugs have been proposed to be potential addiction therapeutics [243], based on the effects of these drugs in animal models of the reinforcing and addictive effects of drugs of abuse

[244,245]. The present findings suggest that effects upon ABCG2 (or other transporters) by these drugs might influence responses to drugs of abuse. This might be especially true for drugs of abuse that are themselves substrates, or otherwise active, at ABC transporters.

Some drugs of abuse (primarily opiates and cannabinoids) are known to inhibit ABCG2

[246,247], and to regulate the function of these transporters at the blood-brain barrier [248].

Thus, either illicit or licit use of these drugs, many of which are opiate analgesics as well as addictive, may affect cancer treatment, but conversely differences in ABC transporter expression may influence responses to drugs of abuse and play a role in addiction. Not much work has explored this possibility, although ABCC4 was repeatedly found to be associated with drug dependence in genome-wide association studies [249]. The influence of differences in ABC transporter function need not be genetic in basis however. ABCG1 74

knockout mice are also more sensitive to the effects of Δ-9-tetrahydrocannabinol [250], demonstrating that differences in transporter levels can affect the behavioral effects of drugs of abuse.

In conclusion, returning to the primary concern of this report, the results presented here indicate that the D3 receptor antagonists PG01037, NGB2904, SB-277011A, and

U99194 significantly reversed ABCG2-mediated MDR in both lung and colon cancer cell lines overexpressing ABCG2 transporters. This reversal effect occurred at in vitro concentrations significantly below those that decreased cell viability. PG01037 and

NGB2904 were the most potent in reversing ABCG2-mediated MDR. In addition,

NGB2904 and PG01037 significantly inhibited the intracellular ABCG2 efflux function.

Furthermore, both compounds significantly decreased the expression of ABCG2 protein levels. A synergistic response was obtained with the combination of the D3 receptor antagonists and the ABCG2 transporter substrates, mitoxantrone and doxorubicin.

Tentatively, our results, if replicated in vivo, suggest that D3 receptor antagonists could be used as adjuvant therapeutic compounds with traditional chemotherapeutics to improve the clinical response. However, for various reasons, none of the D3 receptor antagonists in this study could be used in humans. Finally, further studies, such as photo affinity labelling and ATPase assay, are needed to elucidate the interaction of D3 receptor antagonists with the ABCG2 transporter.

References

1. DeVita VT, Chu E. A history of cancer chemotherapy. Cancer research. 2008;68(21):8643-8653.

2. Boesen JJ, Niericker MJ, Dieteren N, Simons JW. How variable is an spontaneous mutation rate in cultured mammalian cells? Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis. 1994;307(1):121-129.

3. Mo W, Zhang J-T. Human ABCG2: structure, function, and its role in multidrug resistance. International Journal of Biochemistry and Molecular Biology. 2012;3(1):1-27.

4. Juliano RL, Ling V. A surface glycoprotein modulating drug permeability in Chinese hamster ovary cell mutants. Biochimica et Biophysica Acta (BBA)- Biomembranes. 1976;455(1):152-162.

5. Gottesman MM, Fojo T, Bates SE. Multidrug resistance in cancer: role of ATP– dependent transporters. Nature Reviews Cancer. 2002;2(1):48-58.

6. Ambudkar SV, Dey S, Hrycyna CA, Ramachandra M, Pastan I, Gottesman MM. Biochemical, cellular, and pharmacological aspects of the multidrug transporter 1. Annual review of pharmacology and toxicology. 1999;39(1):361-398.

7. Wu Q, Yang Z, Nie Y, Shi Y, Fan D. Multi-drug resistance in cancer chemotherapeutics: mechanisms and lab approaches. Cancer letters. 2014;347(2):159-166.

8. Wu C-P, Calcagno AM, Ambudkar SV. Reversal of ABC drug transporter- mediated multidrug resistance in cancer cells: evaluation of current strategies. Current molecular pharmacology. 2008;1(2):93-105.

9. Szakacs G, Paterson JK, Ludwig JA, Booth-Genthe C, Gottesman MM. Targeting multidrug resistance in cancer. Nat Rev Drug Discov. 2006;5(3):219-234.

10. Gottesman MM. Mechanisms of cancer drug resistance. Annual review of medicine. 2002;53(1):615-627. 76

11. Dean M, Annilo T, R A, R T. EVOLUTION OF THE ATP-BINDING CASSETTE (ABC) TRANSPORTER SUPERFAMILY IN VERTEBRATES The ABCs of immunology: structure and function of TAP, the transporter associated with antigen processing. Annual Review of Genomics and Human Genetics. 2005;6(1):123-142.

12. Szakács G, Varadi A, Özvegy-Laczka C, Sarkadi B. The role of ABC transporters in drug absorption, distribution, metabolism, excretion and toxicity (ADME– Tox). Drug discovery today. 2008;13(9):379-393.

13. CF H. ABC transporters: from micro-organisms to man. Annu. Rev. Cell. Biol. 1992;8:67.

14. Rees DC, Johnson E, Lewinson O. ABC transporters: the power to change. Nature reviews Molecular cell biology. 2009;10(3):218-227.

15. Walker JE, Saraste M, Runswick MJ, Gay NJ. Distantly related sequences in the alpha-and beta-subunits of ATP synthase, myosin, kinases and other ATP- requiring enzymes and a common nucleotide binding fold. The EMBO journal. 1982;1(8):945.

16. Hyde SC, Emsley P, Hartshorn MJ, et al. Structural model of ATP-binding proteing associated with cystic fibrosis, multidrug resistance and bacterial transport. 1990.

17. Dean M, Hamon Y, Chimini G. The human ATP-binding cassette (ABC) transporter superfamily. Journal of lipid research. 2001;42(7):1007-1017.

18. Linton KJ. Structure and function of ABC transporters. Physiology. 2007;22(2):122-130. 19. Broehan G, Kroeger T, Lorenzen M, Merzendorfer H. Functional analysis of the ATP-binding cassette (ABC) transporter gene family of Tribolium castaneum. BMC genomics. 2013;14(1):1.

20. Lin T, Islam O, Heese K. ABC transporters, neural stem cells and neurogenesis–a different perspective. Cell research. 2006;16(11):857-871.

21. Venter JC, Adams MD, Myers EW, et al. The sequence of the human genome. Science. 2001;291(5507):1304-1351.

22. Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome. Nature. 2001;409(6822):860-921.

23. Dean M, Annilo T. Evolution of the Atp-Binding Cassette (Abc) transporter superfamily in vertebrates*. Annu. Rev. Genomics Hum. Genet. 2005;6:123-142.

24. Zaitseva J, Oswald C, Jumpertz T, et al. A structural analysis of asymmetry required for catalytic activity of an ABC‐ATPase domain dimer. The EMBO journal. 2006;25(14):3432-3443.

25. Schaffitzel C, Oswald M, Berger I, et al. Structure of the E. coli signal recognition particle bound to a translating ribosome. Nature. 2006;444(7118):503-506.

26. Higgins CF, Linton KJ. The ATP switch model for ABC transporters. Nature structural & molecular biology. 2004;11(10):918-926.

27. Jones PM, George AM. Opening of the ADP‐bound active site in the ABC transporter ATPase dimer: Evidence for a constant contact, alternating sites model for the catalytic cycle. Proteins: Structure, Function, and Bioinformatics. 2009;75(2):387-396.

28. Senior AE, Al-Shawi MK, Urbatsch IL. The catalytic cycle of P-glycoprotein. FEBS letters. 1995;377(3):285-289.

29. Senior AE, Bhagat S. P-glycoprotein shows strong catalytic cooperativity between the two nucleotide sites. Biochemistry. 1998;37(3):831-836.

30. George AM, Jones PM. Perspectives on the structure–function of ABC transporters: The Switch and Constant Contact Models. Progress in biophysics and molecular biology. 2012;109(3):95-107. 31. Holland IB, Blight MA. ABC-ATPases, adaptable energy generators fuelling transmembrane movement of a variety of molecules in organisms from bacteria to humans. Journal of molecular biology. 1999;293(2):381-399.

32. Borst P, Elferink RO. Mammalian ABC transporters in health and disease. Annual review of biochemistry. 2002;71(1):537-592.

33. Schinkel AH, Jonker JW. Mammalian drug efflux transporters of the ATP binding cassette (ABC) family: an overview. Advanced drug delivery reviews. 2003;55(1):3-29.

34. Glavinas H, Krajcsi P, Cserepes J, Sarkadi B. The role of ABC transporters in drug resistance, metabolism and toxicity. Current drug delivery. 2004;1(1):27-42. 35. Borst P, Evers R, Kool M, Wijnholds J. A family of drug transporters: the multidrug resistance-associated proteins. Journal of the National Cancer Institute. 2000;92(16):1295-1302.

36. Senior AE, Gadsby DC. ATP hydrolysis cycles and mechanism inP-glycoprotein and CFTR. Paper presented at: Seminars in cancer biology1997.

37. Gottesman MM, Ambudkar SV. Overview: ABC transporters and human disease. Journal of bioenergetics and biomembranes. 2001;33(6):453-458.

38. Vasiliou V, Vasiliou K, Nebert DW. Human ATP-binding cassette (ABC) transporter family. Human genomics. 2009;3(3):1.

39. Klein I, Sarkadi B, Váradi A. An inventory of the human ABC proteins. Biochimica et Biophysica Acta (BBA)-Biomembranes. 1999;1461(2):237-262.

40. Gillet J-P, Efferth T, Remacle J. Chemotherapy-induced resistance by ATP- binding cassette transporter genes. Biochimica et Biophysica Acta (BBA)-Reviews on Cancer. 2007;1775(2):237-262.

41. Chen G, Durán GE, Steger KA, et al. Multidrug-resistant human sarcoma cells with a mutant P-glycoprotein, altered phenotype, and resistance to cyclosporins. Journal of Biological Chemistry. 1997;272(9):5974-5982.

42. Borst P, Schinkel AH. Genetic dissection of the function of mammalian P- glycoproteins. Trends in Genetics. 1997;13(6):217-222. 43. Fricker G, Miller DS. Modulation of drug transporters at the blood-brain barrier. Pharmacology. 2004;70(4):169-176.

44. Ambudkar SV, Kim I-W, Sauna ZE. The power of the pump: mechanisms of action of P-glycoprotein (ABCB1). european journal of pharmaceutical sciences. 2006;27(5):392-400.

45. Aller SG, Yu J, Ward A, et al. Structure of P-glycoprotein reveals a molecular basis for poly-specific drug binding. Science. 2009;323(5922):1718-1722.

46. Deeley RG, Westlake C, Cole SP. Transmembrane transport of endo-and xenobiotics by mammalian ATP-binding cassette multidrug resistance proteins. Physiological reviews. 2006;86(3):849-899.

47. He M, Wei M-J. Reversing multidrug resistance by tyrosine kinase inhibitors. Chinese journal of cancer. 2012;31(3):126.

48. Zhang X-Y, Zhang Y-K, Wang Y-J, et al. Osimertinib (AZD9291), a Mutant- Selective EGFR Inhibitor, Reverses ABCB1-Mediated Drug Resistance in Cancer Cells. Molecules. 2016;21(9):1236.

49. Noguchi K, Kawahara H, Kaji A, Katayama K, Mitsuhashi J, Sugimoto Y. Substrate‐dependent bidirectional modulation of P‐glycoprotein‐mediated drug resistance by erlotinib. Cancer science. 2009;100(9):1701-1707.

50. Cole S, Bhardwaj G, Gerlach J, et al. Overexpression of a transporter gene in a multidrug-resistant human lung cancer cell line. SCIENCE-NEW YORK THEN WASHINGTON-. 1992;258:1650-1650.

51. Cole SP, Sparks KE, Fraser K, et al. Pharmacological characterization of multidrug resistant MRP-transfected human tumor cells. Cancer research. 1994;54(22):5902-5910.

52. Bakos E, Evers R, Szakács G, et al. Functional multidrug resistance protein (MRP1) lacking the N-terminal transmembrane domain. Journal of Biological Chemistry. 1998;273(48):32167-32175.

53. Deeley RG, Cole SP. Function, evolution and structure of multidrug resistance protein (MRP). Paper presented at: Seminars in cancer biology1997. 54. Kruh GD, Belinsky MG. The MRP family of drug efflux pumps. Oncogene. 2003;22(47):7537-7552.

55. Rappa G, Finch RA, Sartorelli AC, Lorico A. New insights into the biology and pharmacology of the multidrug resistance protein (MRP) from gene knockout models. Biochem Pharmacol. 1999;58(4):557-562.

56. Robbiani DF, Finch RA, Jäger D, Muller WA, Sartorelli AC, Randolph GJ. The Leukotriene C 4 Transporter MRP1 Regulates CCL19 (MIP-3β, ELC)–Dependent Mobilization of Dendritic Cells to Lymph Nodes. Cell. 2000;103(5):757-768.

57. Johnson DR, Finch RA, Lin ZP, Zeiss CJ, Sartorelli AC. The pharmacological phenotype of combined multidrug-resistance mdr1a/1b-and mrp1-deficient mice. Cancer research. 2001;61(4):1469-1476.

58. Szakács G, Paterson JK, Ludwig JA, Booth-Genthe C, Gottesman MM. Targeting multidrug resistance in cancer. Nature reviews Drug discovery. 2006;5(3):219- 234. 59. Munoz M, Henderson M, Haber M, Norris M. Role of the MRP1/ABCC1 multidrug transporter protein in cancer. IUBMB life. 2007;59(12):752-757.

60. Lautier D, Canitrot Y, Deeley RG, Cole SP. Multidrug resistance mediated by the multidrug resistance protein (MRP) gene. Biochemical pharmacology. 1996;52(7):967-977.

61. Lorico A, Rappa G, Srimatkandada S, et al. Increased rate of adenosine triphosphate-dependent etoposide (VP-16) efflux in a murine leukemia cell line 80

overexpressing the multidrug resistance-associated protein (MRP) gene. Cancer research. 1995;55(19):4352-4360.

62. Breuninger LM, Paul S, Gaughan K, et al. Expression of multidrug resistance- associated protein in NIH/3T3 cells confers multidrug resistance associated with increased drug efflux and altered intracellular drug distribution. Cancer research. 1995;55(22):5342-5347.

63. Woodward OM, Köttgen A, Köttgen M. ABCG transporters and disease. Febs Journal. 2011;278(18):3215-3225.

64. Miyake K, Mickley L, Litman T, et al. Molecular Cloning of cDNAs Which Are Highly Overexpressed in Mitoxantrone-resistant Cells Demonstration of Homology to ABC Transport Genes. Cancer research. 1999;59(1):8-13.

65. M ARaD. cloning of novel ABC transporter genes. Methods in enzymology. 1998;929:116-130.

66. Doyle LA, Yang W, Abruzzo LV, et al. A multidrug resistance transporter from human MCF-7 breast cancer cells. Proceedings of the National Academy of Sciences. 1998;95(26):15665-15670.

67. Natarajan K, Xie Y, Baer MR, Ross DD. Role of breast cancer resistance protein (BCRP/ABCG2) in cancer drug resistance. Biochemical pharmacology. 2012;83(8):1084-1103.

68. CD XZaS. efficient syntheis of a flourescent farnesylated Ras peptide. J org Chem. 2001;66:5241-5244.

69. Kage K, Tsukahara S, Sugiyama T, et al. Dominant‐negative inhibition of breast cancer resistance protein as drug efflux pump through the inhibition of S‐S dependent homodimerization. International journal of cancer. 2002;97(5):626- 630. 70. Xu D, Kang H, Fisher M, Juliano RL. Strategies for inhibition of MDR1 gene expression. Molecular pharmacology. 2004;66(2):268-275.

71. Krishnamurthy P, Schuetz J. Role of ABCG2/BCRP in biology and medicine. Annu. Rev. Pharmacol. Toxicol. 2006;46:381-410.

72. Maliepaard M, Scheffer GL, Faneyte IF, et al. Subcellular localization and distribution of the breast cancer resistance protein transporter in normal human tissues. Cancer research. 2001;61(8):3458-3464.

73. Fetsch PA, Abati A, Litman T, et al. Localization of the ABCG2 mitoxantrone resistance-associated protein in normal tissues. Cancer letters. 2006;235(1):84-92. 81

74. Mao Q. Role of the breast cancer resistance protein (ABCG2) in drug transport. The AAPS journal. 2005;7(1):E118-E133.

75. Polgar O, Robey RW, Bates SE. ABCG2: structure, function and role in drug response. Expert opinion on drug metabolism & toxicology. 2008;4(1):1-15. 76. Kathawala RJ, Gupta P, Ashby CR, Chen Z-S. The modulation of ABC transporter-mediated multidrug resistance in cancer: A review of the past decade. Drug Resistance Updates. 2015;18:1-17.

77. Li W, Zhang H, Assaraf YG, et al. Overcoming ABC transporter-mediated multidrug resistance: Molecular mechanisms and novel therapeutic drug strategies. Drug Resistance Updates. 2016;27:14-29.

78. Ullah MF. Cancer multidrug resistance (MDR): a major impediment to effective chemotherapy. Asian Pac J Cancer Prev. 2008;9(1):1-6.

79. Kellen JA. The reversal of multidrug resistance: an update. Journal of Experimental Therapeutics and Oncology. 2003;3(1):5-13.

80. Falasca M, Linton KJ. Investigational ABC transporter inhibitors. Expert opinion on investigational drugs. 2012;21(5):657-666.

81. Sharom FJ. ABC multidrug transporters: structure, function and role in chemoresistance. 2008.

82. McDevitt CA, Callaghan R. How can we best use structural information on P- glycoprotein to design inhibitors? Pharmacology & therapeutics. 2007;113(2):429-441.

83. Tsuruo T, Iida H, Tsukagoshi S, Sakurai Y. Overcoming of vincristine resistance in P388 leukemia in vivo and in vitro through enhanced cytotoxicity of vincristine and vinblastine by verapamil. Cancer research. 1981;41(5):1967-1972.

84. Slater LM, Murray SL, Wetzel MW, Sweet P, Stupecky M. Verapamil potentiation of VP-16-213 in acute lymphatic leukemia and reversal of pleiotropic drug resistance. Cancer chemotherapy and pharmacology. 1986;16(1):50-54.

85. Slater LM SP, Stupecky M and Gupta S Cyclosporin A reverse vincristine and daunorubicin resistance in acute lymphatic leukemia in vitro. J clin INVEST. 1986;77:1405-1408.

86. Leonard GD, Fojo T, Bates SE. The role of ABC transporters in clinical practice. The oncologist. 2003;8(5):411-424.

87. Thomas H, Coley HM. Overcoming multidrug resistance in cancer: an update on the clinical strategy of inhibiting p-glycoprotein. Cancer control. 2003;10(2):159- 159.

88. Dalton WS, Crowley JJ, Salmon SS, et al. A phase III randomized study of oral verapamil as a chemosensitizer to reverse drug resistance in patients with refractory myeloma. A Southwest Oncology Group study. Cancer. 1995;75(3):815-820.

89. Nobili S, Landini I, Giglioni B, Mini E. Pharmacological strategies for overcoming multidrug resistance. Current drug targets. 2006;7(7):861-879.

90. Nobili S, Landini I, Mazzei T, Mini E. Overcoming tumor multidrug resistance using drugs able to evade P‐glycoprotein or to exploit its expression. Medicinal research reviews. 2012;32(6):1220-1262.

91. Goldman B. Multidrug resistance: can new drugs help chemotherapy score against cancer? Journal of the National Cancer Institute. 2003;95(4):255-257.

92. Lum BL, Gosland MP. MDR expression in normal tissues. Pharmacologic implications for the clinical use of P-glycoprotein inhibitors. Hematology/oncology clinics of North America. 1995;9(2):319-336.

93. Friedenberg WR, Spencer SK, Musser C, et al. Multi-drug resistance in chronic lymphocytic leukemia. Leukemia & lymphoma. 1999;34(1-2):171-178.

94. Hyafil F, Vergely C, Du Vignaud P, Grand-Perret T. In vitro and in vivo reversal of multidrug resistance by GF120918, an acridonecarboxamide derivative. Cancer research. 1993;53(19):4595-4602.

95. Roe M, Folkes A, Ashworth P, et al. Reversal of P-glycoprotein mediated multidrug resistance by novel anthranilamide derivatives. Bioorganic & medicinal chemistry letters. 1999;9(4):595-600.

96. Martin C, Berridge G, Mistry P, Higgins C, Charlton P, Callaghan R. The molecular interaction of the high affinity reversal agent XR9576 with P‐ glycoprotein. British journal of pharmacology. 1999;128(2):403-411.

97. Dantzig A, Shepard R, Law K, et al. Selectivity of the multidrug resistance modulator, LY335979, for P-glycoprotein and effect on cytochrome P-450 activities. Journal of Pharmacology and Experimental Therapeutics. 1999;290(2):854-862.

98. Mistry P, Stewart AJ, Dangerfield W, et al. In vitro and in vivo reversal of P- glycoprotein-mediated multidrug resistance by a novel potent modulator, XR9576. Cancer research. 2001;61(2):749-758.

99. Kuppens IE, Witteveen EO, Jewell RC, et al. A phase I, randomized, open-label, parallel-cohort, dose-finding study of elacridar (GF120918) and oral topotecan in cancer patients. Clinical Cancer Research. 2007;13(11):3276-3285.

100. Morschhauser F, Zinzani PL, Burgess M, Sloots L, Bouafia F, Dumontet C. Phase I/II trial of a P-glycoprotein inhibitor, Zosuquidar. 3HCl trihydrochloride (LY335979), given orally in combination with the CHOP regimen in patients with non-Hodgkin's lymphoma. Leukemia & lymphoma. 2007;48(4):708-715.

101. Pusztai L, Wagner P, Ibrahim N, et al. Phase II study of tariquidar, a selective P‐ glycoprotein inhibitor, in patients with chemotherapy‐resistant, advanced breast carcinoma. Cancer. 2005;104(4):682-691.

102. Fox E, Bates SE. Tariquidar (XR9576): a P-glycoprotein drug efflux pump inhibitor. Expert review of anticancer therapy. 2007;7(4):447-459.

103. Kemper EM, Cleypool C, Boogerd W, Beijnen JH, van Tellingen O. The influence of the P-glycoprotein inhibitor zosuquidar trihydrochloride (LY335979) on the brain penetration of paclitaxel in mice. Cancer chemotherapy and pharmacology. 2004;53(2):173-178.

104. Luurtsema G, Schuit RC, Klok RP, et al. Evaluation of [11 C] laniquidar as a tracer of P-glycoprotein: radiosynthesis and biodistribution in rats. Nuclear medicine and biology. 2009;36(6):643-649.

105. Dö rner B, Kuntner C, Bankstahl JP, et al. Synthesis and small-animal positron emission tomography evaluation of [11C]-elacridar as a radiotracer to assess the distribution of P-glycoprotein at the blood− brain barrier. Journal of medicinal chemistry. 2009;52(19):6073-6082.

106. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Thun MJ. Cancer statistics, 2009. CA: a cancer journal for clinicians. 2009;59(4):225-249. 107. Tang R, Faussat A-M, Perrot J-Y, et al. Zosuquidar restores drug sensitivity in P- glycoprotein expressing acute myeloid leukemia (AML). BMC cancer. 2008;8(1):1.

108. Pajeva IK, Wiese M. Structure–activity relationships of tariquidar analogs as multidrug resistance modulators. The AAPS journal. 2009;11(3):435-444.

109. Kakarla P, Inupakutika M, Devireddy AR, et al. 3D-QSAR and contour map analysis of tariquidar analogues as multidrug resistance protein-1 (MRP1) 84

inhibitors. International journal of pharmaceutical sciences and research. 2016;7(2):554.

110. Kannan P, Telu S, Shukla S, et al. The “specific” P-glycoprotein inhibitor tariquidar is also a substrate and an inhibitor for breast cancer resistance protein (BCRP/ABCG2). ACS chemical neuroscience. 2010;2(2):82-89.

111. Qadir M, O'Loughlin KL, Fricke SM, et al. Cyclosporin A is a broad-spectrum multidrug resistance modulator. Clinical Cancer Research. 2005;11(6):2320- 2326.

112. Sumizawa T, Chen Z-S, Chuman Y, et al. Reversal of multidrug resistance- associated protein-mediated drug resistance by the pyridine analog PAK-104P. Molecular pharmacology. 1997;51(3):399-405.

113. Zelcer N, Saeki T, Reid G, Beijnen JH, Borst P. Characterization of drug transport by the human multidrug resistance protein 3 (ABCC3). Journal of Biological Chemistry. 2001;276(49):46400-46407.

114. K Tiwari A, Sodani K, Dai C-L, R Ashby C, Chen Z-S. Revisiting the ABCs of multidrug resistance in cancer chemotherapy. Current pharmaceutical biotechnology. 2011;12(4):570-594.

115. Kim J, Zhang X, Rieger-Christ KM, et al. Suppression of Wnt signaling by the green tea compound (–)-epigallocatechin 3-gallate (EGCG) in invasive breast cancer cells requirement of the transcriptional repressor HBP1. Journal of Biological Chemistry. 2006;281(16):10865-10875.

116. Nabekura T, Kamiyama S, Kitagawa S. Effects of dietary chemopreventive phytochemicals on P-glycoprotein function. Biochemical and biophysical research communications. 2005;327(3):866-870. 117. Chearwae W, Shukla S, Limtrakul P, Ambudkar SV. Modulation of the function of the multidrug resistance–linked ATP-binding cassette transporter ABCG2 by the cancer chemopreventive agent curcumin. Molecular cancer therapeutics. 2006;5(8):1995-2006.

118. Nabekura T, Yamaki T, Kitagawa S. Effects of chemopreventive citrus phytochemicals on human P-glycoprotein and multidrug resistance protein 1. European journal of pharmacology. 2008;600(1):45-49.

119. Nabekura T, Yamaki T, Hiroi T, Ueno K, Kitagawa S. Inhibition of anticancer drug efflux transporter P-glycoprotein by rosemary phytochemicals. Pharmacological research. 2010;61(3):259-263.

120. Michalak K, Wesolowska O. Polyphenols counteract tumor cell chemoresistance conferred by multidrug resistance proteins. Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry-Anti-Cancer Agents). 2012;12(8):880-890.

121. Pan L, Hu H, Wang X, et al. Inhibitory effects of neochamaejasmin B on P- glycoprotein in MDCK-hMDR1 cells and molecular docking of NCB binding in P-glycoprotein. Molecules. 2015;20(2):2931-2948.

122. Shukla S, Wu C-P, Ambudkar SV. Development of inhibitors of ATP-binding cassette drug transporters–present status and challenges. Expert opinion on drug metabolism & toxicology. 2008;4(2):205-223.

123. Lopez D, Martinez-Luis S. Marine natural products with P-glycoprotein inhibitor properties. Marine drugs. 2014;12(1):525-546.

124. Huang X-C, Xiao X, Zhang Y-K, et al. Lamellarin O, a pyrrole alkaloid from an Australian marine sponge, Ianthella sp., reverses BCRP mediated drug resistance in cancer cells. Marine drugs. 2014;12(7):3818-3837.

125. Abraham I, Jain S, Wu C-P, et al. Marine sponge-derived sipholane triterpenoids reverse P-glycoprotein (ABCB1)-mediated multidrug resistance in cancer cells. Biochemical pharmacology. 2010;80(10):1497-1506.

126. Shi Z, Jain S, Kim IW, et al. Sipholenol A, a marine‐derived sipholane triterpene, potently reverses P‐glycoprotein (ABCB1)‐mediated multidrug resistance in cancer cells. Cancer science. 2007;98(9):1373-1380. 127. Gao L, Chen L, Fei X-H, Qiu H-Y, Zhou H, Wang J-M. STI571 combined with vincristine greatly suppressed the tumor formation of multidrug-resistant K562 cells in a human-nude mice xenograft model. Chinese medical journal. 2006;119(11):911-918.

128. Tiwari AK, Sodani K, Wang S-R, et al. Nilotinib (AMN107, Tasigna®) reverses multidrug resistance by inhibiting the activity of the ABCB1/Pgp and ABCG2/BCRP/MXR transporters. Biochemical pharmacology. 2009;78(2):153- 161.

129. Sen R, Natarajan K, Bhullar J, et al. The novel BCR-ABL and FLT3 inhibitor ponatinib is a potent inhibitor of the MDR-associated ATP-binding cassette transporter ABCG2. Molecular cancer therapeutics. 2012;11(9):2033-2044.

130. Liang W, Wu X, Fang W, et al. Network meta-analysis of erlotinib, gefitinib, afatinib and icotinib in patients with advanced non-small-cell lung cancer harboring EGFR mutations. PloS one. 2014;9(2):e85245.

131. Shi Z, Peng X-X, Kim I-W, et al. Erlotinib (Tarceva, OSI-774) antagonizes ATP- binding cassette subfamily B member 1 and ATP-binding cassette subfamily G member 2–mediated drug resistance. Cancer research. 2007;67(22):11012-11020.

132. Zhang H, Wang Y-J, Zhang Y-K, et al. AST1306, a potent EGFR inhibitor, antagonizes ATP-binding cassette subfamily G member 2-mediated multidrug resistance. Cancer letters. 2014;350(1):61-68.

133. Kitazaki T, Oka M, Nakamura Y, et al. Gefitinib, an EGFR tyrosine kinase inhibitor, directly inhibits the function of P-glycoprotein in multidrug resistant cancer cells. Lung Cancer. 2005;49(3):337-343.

134. Zhang H, Zhang YK, Wang YJ, et al. WHI‐P154 enhances the chemotherapeutic effect of anticancer agents in ABCG2‐overexpressing cells. Cancer science. 2014;105(8):1071-1078.

135. Sequist LV, Yang JC-H, Yamamoto N, et al. Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. Journal of Clinical Oncology. 2013;31(27):3327-3334.

136. Kuang Y-H, Shen T, Chen X, et al. Lapatinib and erlotinib are potent reversal agents for MRP7 (ABCC10)-mediated multidrug resistance. Biochemical pharmacology. 2010;79(2):154-161.

137. Erlichman C, Boerner SA, Hallgren CG, et al. The HER tyrosine kinase inhibitor CI1033 enhances cytotoxicity of 7-ethyl-10-hydroxycamptothecin and topotecan by inhibiting breast cancer resistance protein-mediated drug efflux. Cancer research. 2001;61(2):739-748.

138. Zheng L-s, Wang F, Li Y-h, et al. Vandetanib (Zactima, ZD6474) antagonizes ABCC1-and ABCG2-mediated multidrug resistance by inhibition of their transport function. PloS one. 2009;4(4):e5172.

139. Shukla S, Robey RW, Bates SE, Ambudkar SV. Sunitinib (Sutent, SU11248), a small-molecule receptor tyrosine kinase inhibitor, blocks function of the ATP- binding cassette (ABC) transporters P-glycoprotein (ABCB1) and ABCG2. Drug Metabolism and Disposition. 2009;37(2):359-365.

140. Hu S, Chen Z, Franke R, et al. Interaction of the multikinase inhibitors sorafenib and sunitinib with solute carriers and ATP-binding cassette transporters. Clinical Cancer Research. 2009;15(19):6062-6069.

141. Wang Y-J, Kathawala RJ, Zhang Y-K, et al. Motesanib (AMG706), a potent multikinase inhibitor, antagonizes multidrug resistance by inhibiting the efflux activity of the ABCB1. Biochemical pharmacology. 2014;90(4):367-378. 87

142. Sodani K, Patel A, Anreddy N, et al. Telatinib reverses chemotherapeutic multidrug resistance mediated by ABCG2 efflux transporter in vitro and in vivo. Biochemical pharmacology. 2014;89(1):52-61.

143. Shi Z, Tiwari AK, Shukla S, et al. Sildenafil reverses ABCB1-and ABCG2- mediated chemotherapeutic drug resistance. Cancer research. 2011;71(8):3029- 3041.

144. Chen JJ, Sun YL, Tiwari AK, et al. PDE5 inhibitors, sildenafil and vardenafil, reverse multidrug resistance by inhibiting the efflux function of multidrug resistance protein 7 (ATP‐binding Cassette C10) transporter. Cancer science. 2012;103(8):1531-1537.

145. Zinzi L, Capparelli E, Cantore M, Contino M, Leopoldo M, Colabufo NA. Small and innovative molecules as new strategy to revert MDR. Multidrug Resistance in Cancer: Pharmacological Strategies from Basic Research to Clinical Issues. 2015:48.

146. Tiram G, Segal E, Krivitsky A, et al. Identification of dormancy-associated MicroRNAs for the design of osteosarcoma-targeted dendritic polyglycerol nanopolyplexes. ACS nano. 2016;10(2):2028-2045.

147. Bar-Zeev M, Assaraf YG, Livney YD. β-casein nanovehicles for oral delivery of chemotherapeutic drug combinations overcoming P-glycoprotein-mediated multidrug resistance in human gastric cancer cells. Oncotarget. 2016.

148. Zhang T-T, Li W, Meng G, Wang P, Liao W. Strategies for transporting nanoparticles across the blood–brain barrier. Biomaterials science. 2016;4(2):219- 229.

149. Kang L, Gao Z, Huang W, Jin M, Wang Q. Nanocarrier-mediated co-delivery of chemotherapeutic drugs and gene agents for cancer treatment. Acta Pharmaceutica Sinica B. 2015;5(3):169-175.

150. Dong W-H, Li Q, Zhang X-Y, Guo Q, Li H, Wang T-Y. Deep sequencing identifies deregulation of microRNAs involved with vincristine drug-resistance of colon cancer cells. International journal of clinical and experimental pathology. 2015;8(9):11524.

151. Fisher M, Abramov M, Van Aerschot A, Xu D, Juliano RL, Herdewijn P. Inhibition of MDR1 expression with altritol-modified siRNAs. Nucleic acids research. 2007;35(4):1064-1074.

152. Liu S, Wang H, Zhang L, et al. Rapid detection of genetic mutations in individual breast cancer patients by next-generation DNA sequencing. Human genomics. 2015;9(1):1.

153. Morrison CD, Liu P, Woloszynska-Read A, et al. Whole-genome sequencing identifies genomic heterogeneity at a nucleotide and chromosomal level in bladder cancer. Proceedings of the National Academy of Sciences. 2014;111(6):E672-E681.

154. Ricci J, Lovato D, Larson R. ABCG2 inhibitors: will they find clinical relevance. J. Dev. Drugs. 2015;4:138.

155. Kuang Y-H, Patel JP, Sodani K, et al. OSI-930 analogues as novel reversal agents for ABCG2-mediated multidrug resistance. Biochemical pharmacology. 2012;84(6):766-774.

156. Allen JD, van Loevezijn A, Lakhai JM, et al. Potent and Specific Inhibition of the Breast Cancer Resistance Protein Multidrug Transporter in Vitro and in Mouse Intestine by a Novel Analogue of Fumitremorgin C 1 This work was supported in part by grant NKI 97-1433 from the Dutch Cancer Society (to AHS). Synthesis investigations by A. v. L. and GJ. K. were supported by the Netherlands Research Council for Chemical Sciences (NWO/CW) and the Netherlands Technology Foundation (STW). 1. Molecular Cancer Therapeutics. 2002;1(6):417-425.

157. Rabindran SK, He H, Singh M, et al. Reversal of a novel multidrug resistance mechanism in human colon carcinoma cells by fumitremorgin C. Cancer research. 1998;58(24):5850-5858.

158. Rabindran SK, Ross DD, Doyle LA, Yang W, Greenberger LM. Fumitremorgin C reverses multidrug resistance in cells transfected with the breast cancer resistance protein. Cancer research. 2000;60(1):47-50.

159. Minderman H, Suvannasankha A, O'Loughlin KL, et al. Flow cytometric analysis of breast cancer resistance protein expression and function. Cytometry. 2002;48(2):59-65.

160. Weidner LD, Zoghbi SS, Lu S, et al. The inhibitor Ko143 is not specific for ABCG2. Journal of Pharmacology and Experimental Therapeutics. 2015;354(3):384-393.

161. Doyle LA, Yang W, Rishi AK, Gao Y, Ross DD. H19 gene overexpression in atypical multidrug-resistant cells associated with expression of a 95-kilodalton membrane glycoprotein. Cancer research. 1996;56(13):2904-2907.

162. Shiozawa K, Oka M, Soda H, et al. Reversal of breast cancer resistance protein (BCRP/ABCG2)‐mediated drug resistance by novobiocin, a coumermycin antibiotic. International journal of cancer. 2004;108(1):146-151.

163. Su Y, Hu P, Lee S-H, Sinko PJ. Using novobiocin as a specific inhibitor of breast cancer resistant protein to assess the role of transporter in the absorption and disposition of topotecan. Journal of Pharmacy & Pharmaceutical Sciences. 2007;10(4):519-536.

164. Maliepaard M, van Gastelen MA, Tohgo A, et al. Circumvention of breast cancer resistance protein (BCRP)-mediated resistance to camptothecins in vitro using non-substrate drugs or the BCRP inhibitor GF120918. Clinical Cancer Research. 2001;7(4):935-941.

165. de Bruin M, Miyake K, Litman T, Robey R, Bates SE. Reversal of resistance by GF120918 in cell lines expressing the ABC half-transporter, MXR. Cancer letters. 1999;146(2):117-126.

166. Robey RW, Steadman K, Polgar O, et al. Pheophorbide a is a specific probe for ABCG2 function and inhibition. Cancer research. 2004;64(4):1242-1246.

167. Wang DS, Patel A, Sim HM, et al. ARRY‐334543 Reverses Multidrug Resistance by Antagonizing the Activity of ATP‐Binding Cassette Subfamily G Member 2. Journal of cellular biochemistry. 2014;115(8):1381-1391.

168. Boumendjel A, Macalou S, Ahmed-Belkacem A, Blanc M, Di Pietro A. Acridone derivatives: design, synthesis, and inhibition of breast cancer resistance protein ABCG2. Bioorganic & medicinal chemistry. 2007;15(8):2892-2897.

169. Nakamura Y, Oka M, Soda H, et al. Gefitinib (“Iressa”, ZD1839), an epidermal growth factor receptor tyrosine kinase inhibitor, reverses breast cancer resistance protein/ABCG2–mediated drug resistance. Cancer research. 2005;65(4):1541- 1546.

170. Kü hnle M, Egger M, Mü ller C, et al. Potent and selective inhibitors of breast cancer resistance protein (ABCG2) derived from the p-glycoprotein (ABCB1) modulator tariquidar. Journal of medicinal chemistry. 2009;52(4):1190-1197.

171. Valdameri G, Genoux-Bastide E, Peres B, et al. Substituted chromones as highly potent nontoxic inhibitors, specific for the breast cancer resistance protein. Journal of medicinal chemistry. 2012;55(2):966-970.

172. Sugimoto Y, Tsukahara S, Imai Y, Ueda K, Tsuruo T. Reversal of breast cancer resistance protein-mediated drug resistance by estrogen antagonists and agonists1. Molecular cancer therapeutics. 2003;2(1):105-112. 90

173. Dai C-l, Liang Y-j, Wang Y-s, et al. Sensitization of ABCG2-overexpressing cells to conventional chemotherapeutic agent by sunitinib was associated with inhibiting the function of ABCG2. Cancer letters. 2009;279(1):74-83.

174. Ma H, Yao Q, Zhang A-M, et al. The effects of artesunate on the expression of EGFR and ABCG2 in A549 human lung cancer cells and a xenograft model. Molecules. 2011;16(12):10556-10569.

175. Houghton PJ, Germain GS, Harwood FC, et al. Imatinib mesylate is a potent inhibitor of the ABCG2 (BCRP) transporter and reverses resistance to topotecan and SN-38 in vitro. Cancer research. 2004;64(7):2333-2337.

176. Karthikeyan C, Malla R, Ashby CR, et al. Pyrimido [1 ″, 2 ″: 1, 5] pyrazolo [3, 4- b] quinolines: Novel compounds that reverse ABCG2-mediated resistance in cancer cells. Cancer letters. 2016;376(1):118-126.

177. Wang D-S, Patel A, Shukla S, et al. Icotinib antagonizes ABCG2-mediated multidrug resistance, but not the pemetrexed resistance mediated by thymidylate synthase and ABCG2. Oncotarget. 2014;5(12):4529-4542.

178. Dai C-l, Tiwari AK, Wu C-P, et al. Lapatinib (Tykerb, GW572016) reverses multidrug resistance in cancer cells by inhibiting the activity of ATP-binding cassette subfamily B member 1 and G member 2. Cancer research. 2008;68(19):7905-7914.

179. Yamazaki R, Nishiyama Y, Furuta T, et al. Novel acrylonitrile derivatives, YHO- 13177 and YHO-13351, reverse BCRP/ABCG2-mediated drug resistance in vitro and in vivo. Molecular cancer therapeutics. 2011;10(7):1252-1263.

180. Gandhi YA, Morris ME. Structure–activity relationships and quantitative structure–activity relationships for breast cancer resistance protein (ABCG2). The AAPS journal. 2009;11(3):541-552.

181. Matsson P, Englund G, Ahlin G, Bergström CA, Norinder U, Artursson P. A global drug inhibition pattern for the human ATP-binding cassette transporter breast cancer resistance protein (ABCG2). Journal of Pharmacology and Experimental Therapeutics. 2007;323(1):19-30. 182. Shukla S, Kouanda A, Silverton L, Talele TT, Ambudkar SV. Pharmacophore Modeling of Nilotinib as an Inhibitor of ATP-Binding Cassette Drug Transporters and BCR-ABL Kinase Using a Three-Dimensional Quantitative Structure– Activity Relationship Approach. Molecular pharmaceutics. 2014;11(7):2313- 2322.

183. Heidbreder CA, Newman AH. Current perspectives on selective dopamine D3 receptor antagonists as pharmacotherapeutics for addictions and related disorders. Annals of the New York Academy of Sciences. 2010;1187(1):4-34.

184. Higley AE, Spiller K, Grundt P, et al. PG01037, a novel dopamine D3 receptor antagonist, inhibits the effects of methamphetamine in rats. Journal of psychopharmacology. 2011;25(2):263-273.

185. Xi Z-X, Newman AH, Gilbert JG, et al. The novel dopamine D3 receptor antagonist NGB 2904 inhibits cocaine's rewarding effects and cocaine-induced reinstatement of drug-seeking behavior in rats. Neuropsychopharmacology. 2006;31(7):1393-1405.

186. Higley AE, Kiefer SW, Li X, Gaál J, Xi Z-X, Gardner EL. Dopamine D 3 receptor antagonist SB-277011A inhibits methamphetamine self-administration and methamphetamine-induced reinstatement of drug-seeking in rats. European journal of pharmacology. 2011;659(2):187-192.

187. John WS, Newman AH, Nader MA. Differential effects of the dopamine D 3 receptor antagonist PG01037 on cocaine and methamphetamine self- administration in rhesus monkeys. Neuropharmacology. 2015;92:34-43.

188. Manzanedo C, Aguilar M, Minarro J. The effects of dopamine D2 and D3 antagonists on spontaneous motor activity and morphine-induced hyperactivity in male mice. Psychopharmacology. 1999;143(1):82-88.

189. Vorel SR, Ashby CR, Paul M, et al. Dopamine D3 receptor antagonism inhibits cocaine-seeking and cocaine-enhanced brain reward in rats. The Journal of neuroscience. 2002;22(21):9595-9603.

190. Keck TM, John WS, Czoty PW, Nader MA, Newman AH. Identifying medication targets for psychostimulant addiction: unraveling the dopamine D3 receptor hypothesis. Journal of medicinal chemistry. 2015;58(14):5361-5380.

191. Dodds CM, O’Neill B, Beaver J, et al. Effect of the dopamine D 3 receptor antagonist GSK598809 on brain responses to rewarding food images in overweight and obese binge eaters. Appetite. 2012;59(1):27-33.

192. Nathan PJ, O'Neill BV, Mogg K, et al. The effects of the dopamine D3 receptor antagonist GSK598809 on attentional bias to palatable food cues in overweight and obese subjects. International Journal of Neuropsychopharmacology. 2012;15(2):149-161.

193. Mugnaini M, Iavarone L, Cavallini P, et al. Occupancy of brain dopamine D3 receptors and drug craving: a translational approach. Neuropsychopharmacology. 2013;38(2):302-312.

194. Le Foll B, Wilson AA, Graff A, Boileau I, Di Ciano P. Recent methods for measuring dopamine D3 receptor occupancy in vivo: importance for drug development. New frontiers in the neuropsychopharmacology of mental illness. 2015:227.

195. Newman AH, Blaylock BL, Nader MA, Bergman J, Sibley DR, Skolnick P. Medication discovery for addiction: translating the dopamine D3 receptor hypothesis. Biochemical pharmacology. 2012;84(7):882-890.

196. Keck TM, Burzynski C, Shi L, Newman AH. Beyond small-molecule SAR: using the dopamine D3 receptor crystal structure to guide drug design. Adv. Pharmacol. 2014;69:267-300.

197. Schindler C. Cocaine and cardiovascular toxicity. Addiction biology. 1996;1(1):31-47.

198. O’Connell DP, Vaughan CJ, Aherne AM, et al. Expression of the dopamine D3 receptor protein in the rat kidney. Hypertension. 1998;32(5):886-895.

199. Zeng C, Jose PA. Dopamine Receptors Important Antihypertensive Counterbalance Against Hypertensive Factors. Hypertension. 2011;57(1):11-17.

200. Levant B. The D3 dopamine receptor: neurobiology and potential clinical relevance. Pharmacological Reviews. 1997;49(3):231-252.

201. Waters N, Svensson K, Haadsma-Svensson S, Smith M, Carlsson A. The dopamine D3-receptor: a postsynaptic receptor inhibitory on rat locomotor activity. Journal of Neural Transmission/General Section JNT. 1993;94(1):11-19.

202. Wustrow DJ, Wise LD. Progress in developing dopamine D3 ligands as potential antipsychotic agents. ChemInform. 1997;28(52).

203. Xi ZX, Gardner EL. Pharmacological actions of NGB 2904, a selective dopamine D3 receptor antagonist, in animal models of drug addiction. CNS drug reviews. 2007;13(2):240-259.

204. Austin N, Baldwin S, Cutler L, et al. Pharmacokinetics of the novel, high-affinity and selective dopamine D3 receptor antagonist SB-277011 in rat, dog and monkey: in vitro/in vivo correlation and the role of aldehyde oxidase. Xenobiotica. 2001;31(8-9):677-686.

205. Mason CW, Hassan HE, Kim K-P, et al. Characterization of the transport, metabolism, and pharmacokinetics of the dopamine D3 receptor-selective fluorenyl-and 2-pyridylphenyl amides developed for treatment of psychostimulant abuse. Journal of Pharmacology and Experimental Therapeutics. 2010;333(3):854-864.

206. Vautier S, Milane A, Fernandez C, Chacun H, Lacomblez L, Farinotti R. Role of two efflux proteins, ABCB1 and ABCG2 in blood-brain barrier transport of bromocriptine in a murine model of MPTP-induced dopaminergic degeneration. Journal of Pharmacy & Pharmaceutical Sciences. 2009;12(2):199-208.

207. Liu F, Wang X, Li Z, Li J, Zhuang X, Zhang Z. P-Glycoprotein (ABCB1) Limits the Brain Distribution of YQA-14, a Novel Dopamine D 3 Receptor Antagonist. Chemical and Pharmaceutical Bulletin. 2015;63(7):512-518.

208. Zhang Y, Byun Y, Ren YR, Liu JO, Laterra J, Pomper MG. Identification of Inhibitors of ABCG2 by a Bioluminescence Imaging–Based High-Throughput Assay. Cancer research. 2009;69(14):5867-5875.

209. Honjo Y, Hrycyna CA, Yan Q-W, et al. Acquired mutations in the MXR/BCRP/ABCP gene alter substrate specificity in MXR/BCRP/ABCP- overexpressing cells. Cancer research. 2001;61(18):6635-6639.

210. Robey RW, Honjo Y, van de Laar A, et al. A functional assay for detection of the mitoxantrone resistance protein, MXR (ABCG2). Biochimica et Biophysica Acta (BBA)-Biomembranes. 2001;1512(2):171-182.

211. Tiwari AK, Sodani K, Dai C-l, et al. Nilotinib potentiates anticancer drug sensitivity in murine ABCB1-, ABCG2-, and ABCC10-multidrug resistance xenograft models. Cancer letters. 2013;328(2):307-317.

212. Robey R, Honjo Y, Morisaki K, et al. Mutations at amino-acid 482 in the ABCG2 gene affect substrate and antagonist specificity. British journal of cancer. 2003;89(10):1971-1978.

213. Carmichael J, DeGraff WG, Gazdar AF, Minna JD, Mitchell JB. Evaluation of a tetrazolium-based semiautomated colorimetric assay: assessment of chemosensitivity testing. Cancer research. 1987;47(4):936-942.

214. Shi Z, Liang Y-j, Chen Z-s, et al. Reversal of MDR1/P-glycoprotein-mediated multidrug resistance by vector-based RNA interference in vitro and in vivo. Cancer biology & therapy. 2006;5(1):39-47.

215. Chou T-C. Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacological reviews. 2006;58(3):621-681.

216. Rosenberg MF, Bikadi Z, Chan J, et al. The human breast cancer resistance protein (BCRP/ABCG2) shows conformational changes with mitoxantrone. Structure. 2010;18(4):482-493.

217. Alqawi O, Bates S, Georges E. Arginine482 to threonine mutation in the breast cancer resistance protein ABCG2 inhibits rhodamine 123 transport while increasing binding. Biochemical Journal. 2004;382(2):711-716.

218. Mitomo H, Ryo K, Akiko I, et al. A functional study on polymorphism of the ATP-binding cassette transporter ABCG2: critical role of arginine-482 in methotrexate transport. Biochemical Journal. 2003;373(3):767-774. 219. Miwa M, Tsukahara S, Ishikawa E, Asada S, Imai Y, Sugimoto Y. Single amino acid substitutions in the transmembrane domains of breast cancer resistance protein (BCRP) alter cross resistance patterns in transfectants. International journal of cancer. 2003;107(5):757-763.

220. Friesner RA, Murphy RB, Repasky MP, et al. Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. Journal of medicinal chemistry. 2006;49(21):6177-6196.

221. Friesner RA, Banks JL, Murphy RB, et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. Journal of medicinal chemistry. 2004;47(7):1739-1749.

222. Doyle LA, Ross DD. Multidrug resistance mediated by the breast cancer resistance protein BCRP (ABCG2). Oncogene. 2003;22(47):7340-7358.

223. Montgomery A, Adeyeni T, San K, Heuertz RM, Ezekiel UR. Curcumin sensitizes Silymarin to exert synergistic anticancer activity in colon cancer cells. Journal of Cancer. 2016;7(10):1250.

224. Chou T-C. Drug combination studies and their synergy quantification using the Chou-Talalay method. Cancer research. 2010;70(2):440-446.

225. McKeon AM, Egan A, Chandanshive J, McMahon H, Griffith DM. Novel Improved Synthesis of HSP70 Inhibitor, Pifithrin-μ. In Vitro Synergy Quantification of Pifithrin-μ Combined with Pt Drugs in Prostate and Colorectal Cancer Cells. Molecules. 2016;21(7):949.

226. Allikmets R, Schriml LM, Hutchinson A, Romano-Spica V, Dean M. A human placenta-specific ATP-binding cassette gene (ABCP) on chromosome 4q22 that is involved in multidrug resistance. Cancer research. 1998;58(23):5337-5339.

227. K M, L M, T L, Z Z, R R. Molecular cloning of cDNAs which are highly overexpressed in mitoxantrone-resistant cells: demonstration of homology to ABC transport genes. Cancer Res. 1999;59:8.

228. Ni Z, Bikadi Z, Cai X, Rosenberg MF, Mao Q. Transmembrane helices 1 and 6 of the human breast cancer resistance protein (BCRP/ABCG2): identification of polar residues important for drug transport. American Journal of Physiology-Cell Physiology. 2010;299(5):C1100-C1109. 229. Shukla S, Skoumbourdis AP, Walsh MJ, et al. Synthesis and characterization of a BODIPY conjugate of the BCR-ABL kinase inhibitor Tasigna (nilotinib): evidence for transport of Tasigna and its fluorescent derivative by ABC drug transporters. Molecular pharmaceutics. 2011;8(4):1292-1302.

230. Jung HJ, Chen Z, McCarty N. Synergistic anticancer effects of arsenic trioxide with bortezomib in mantle cell lymphoma. American journal of hematology. 2012;87(12):1057-1064.

231. Kim MK, James J, Annunziata CM. Topotecan synergizes with CHEK1 (CHK1) inhibitor to induce apoptosis in ovarian cancer cells. BMC cancer. 2015;15(1):1.

232. van Loevezijn A, Allen JD, Schinkel AH, Koomen G-J. Inhibition of BCRP- mediated drug efflux by fumitremorgin-type indolyl diketopiperazines. Bioorganic & medicinal chemistry letters. 2001;11(1):29-32.

233. Lagas JS, van Waterschoot RA, van Tilburg VA, et al. Brain accumulation of dasatinib is restricted by P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2) and can be enhanced by elacridar treatment. Clinical Cancer Research. 2009;15(7):2344-2351.

234. Natarajan K, Bhullar J, Shukla S, et al. The Pim kinase inhibitor SGI-1776 decreases cell surface expression of P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2) and drug transport by Pim-1-dependent and- independent mechanisms. Biochemical pharmacology. 2013;85(4):514-524.

235. Cuestas ML, Castillo AI, Sosnik A, Mathet VL. Downregulation of mdr1 and abcg2 genes is a mechanism of inhibition of efflux pumps mediated by polymeric amphiphiles. Bioorganic & medicinal chemistry letters. 2012;22(21):6577-6579.

236. Zhang Z, Stiegler AL, Boggon TJ, Kobayashi S, Halmos B. EGFR-mutated lung cancer: a paradigm of molecular oncology. Oncotarget. 2010;1(7):497-514.

237. Antczak C, Wee B, Radu C, Bhinder B, Holland EC, Djaballah H. A high-content assay strategy for the identification and profiling of ABCG2 modulators in live cells. Assay and drug development technologies. 2014;12(1):28-42.

238. Ding R, Shi J, Pabon K, Scotto KW. Xanthines down-regulate the drug transporter ABCG2 and reverse multidrug resistance. Molecular pharmacology. 2012;81(3):328-337. 239. White E. Deconvoluting the context-dependent role for autophagy in cancer. Nat Rev Cancer. 2012;12(6):401-410.

240. Ding R, Jin S, Pabon K, Scotto KW. A role for ABCG2 beyond drug transport: Regulation of autophagy. Autophagy. 2016;12(5):737-751.

241. Li Z, Ji X, Wang W, et al. Ammonia Induces Autophagy through Dopamine Receptor D3 and MTOR. PLoS One. 2016;11(4):e0153526.

242. Giacomini KM, Huang S-M, Tweedie DJ, et al. Membrane transporters in drug development. Nature reviews Drug discovery. 2010;9(3):215-236.

243. Paterson NE, Vocci F, Sevak RJ, Wagreich E, London ED. Dopamine D3 receptors as a therapeutic target for methamphetamine dependence. Am J Drug Alcohol Abuse. 2014;40(1):1-9.

244. Xi ZX, Gardner EL. Pharmacological actions of NGB 2904, a selective dopamine D3 receptor antagonist, in animal models of drug addiction. CNS Drug Rev. 2007;13(2):240-259.

245. John WS, Newman AH, Nader MA. Differential effects of the dopamine D3 receptor antagonist PG01037 on cocaine and methamphetamine self- administration in rhesus monkeys. Neuropharmacology. 2015;92:34-43.

246. Tournier N, Chevillard L, Megarbane B, Pirnay S, Scherrmann JM, Decleves X. Interaction of drugs of abuse and maintenance treatments with human P- glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2). Int J Neuropsychopharmacol. 2010;13(7):905-915.

247. Holland ML, Lau DT, Allen JD, Arnold JC. The multidrug transporter ABCG2 (BCRP) is inhibited by plant-derived cannabinoids. Br J Pharmacol. 2007;152(5):815-824.

248. Tournier N, Decleves X, Saubamea B, Scherrmann JM, Cisternino S. Opioid transport by ATP-binding cassette transporters at the blood-brain barrier: implications for neuropsychopharmacology. Curr Pharm Des. 2011;17(26):2829- 2842.

249. Uhl GR, Drgon T, Johnson C, et al. Molecular genetics of addiction and related heritable phenotypes: genome-wide association approaches identify "connectivity constellation" and drug target genes with pleiotropic effects. Ann N Y Acad Sci. 2008;1141:318-381.

250. Spiro AS, Wong A, Boucher AA, Arnold JC. Enhanced brain disposition and effects of Delta9-tetrahydrocannabinol in P-glycoprotein and breast cancer resistance protein knockout mice. PLoS One. 2012;7(4):e35937.