Inhibitors of glucose and hydroperoxide metabolism potentiate 17AAG-induced cancer cell killing via metabolic oxidative stress

Transcription

1 University of Iowa Iowa Research Online Theses and Dissertations 2011 Inhibitors of glucose and hydroperoxide metabolism potentiate 17AAG-induced cancer cell killing via metabolic oxidative stress Peter Marcus Scarbrough University of Iowa Copyright 2011 Peter Marcus Scarbrough This dissertation is available at Iowa Research Online: Recommended Citation Scarbrough, Peter Marcus. "Inhibitors of glucose and hydroperoxide metabolism potentiate 17AAG-induced cancer cell killing via metabolic oxidative stress." PhD (Doctor of Philosophy) thesis, University of Iowa, Follow this and additional works at: Part of the Other Biochemistry, Biophysics, and Structural Biology Commons

2 INHIBITORS OF GLUCOSE AND HYDROPEROXIDE METABOLISM POTENTIATE 17AAG-INDUCED CANCER CELL KILLING VIA METABOLIC OXIDATIVE STRESS by Peter Marcus Scarbrough An Abstract Of a thesis submitted in partial fulfillment of the requirements for the Doctor of Philosophy degree in Free Radical and Radiation Biology in the Graduate College of The University of Iowa May 2011 Thesis Supervisor: Professor Douglas R. Spitz

3 1 ABSTRACT 17-Allylamino-17-demethoxygeldanamycin (17AAG) is an experimental chemotherapeutic agent, believed to form free radicals in vivo, and cancer cell resistance to 17AAG is believed to be a thiol-dependent process. Inhibitors of thiol-dependent hydroperoxide metabolism [L-buthionine-S,R-sulfoximine (BSO) and auranofin (AUR)] were combined with the inhibitor of glucose metabolism [2-deoxy-D-glucose (2DG)] to determine if 17AAG-mediated cancer cell killing could be enhanced. When 2DG (20 mm, 24 h), BSO (1 mm, 24 h), and auranofin (500 nm, 3 h) were combined with 17AAG, they significantly increased cell killing in three human cancer cell lines (PC-3, SUM159, MDA-MB-231), relative to 17AAG alone. Increases in toxicity seen with this drug combination also correlated with increased glutathione (GSH) and thioredoxin (Trx) oxidation and depletion. Furthermore, treatment with the thiol antioxidant, N-acetyl cysetine (NAC, 15 mm, 24 h), was able to significantly protect from drug-induced toxicity and ameliorate GSH oxidation, Trx oxidation, and Trx depletion. These data strongly support the hypothesis that simultaneous inhibition of GSH and Trx dependent metabolism is necessary to sensitize human cancer cells to 2DG + 17AAG-mediated cancer cell killing by enhancing thiol-dependent oxidative stress and suggest that simultaneous targeting of both GSH and Trx metabolism could represent an effective strategy for chemo-sensitization in human cancer cells. Abstract Approved: Thesis Supervisor Title and Department Date

4 INHIBITORS OF GLUCOSE AND HYDROPEROXIDE METABOLISM POTENTIATE 17AAG-INDUCED CANCER CELL KILLING VIA METABOLIC OXIDATIVE STRESS by Peter Marcus Scarbrough A thesis submitted in partial fulfillment of the requirements for the Doctor of Philosophy degree in Free Radical and Radiation Biology in the Graduate College of The University of Iowa May 2011 Thesis Supervisor: Professor Douglas R. Spitz

5 Graduate College The University of Iowa Iowa City, Iowa CERTIFICATE OF APPROVAL PH.D. THESIS This is to certify that the Ph.D. thesis of Peter Marcus Scarbrough has been approved by the Examining Committee of the thesis requirement for the Doctor of Philosophy degree in Free Radical and Radiation Biology at the May 2011 graduation. Thesis Committee: Douglas R. Spitz, Thesis Supervisor Garry R. Buettner Joseph J. Cullen Prabhat C. Goswami Raymond J. Hohl

6 ACKNOWLEDGEMENTS Special thanks go to my family, friends, and colleagues who helped me throughout my development as a graduate student and, without whom, this project and thesis would not have been possible. My parents, Ken Scarbrough and Carolyn Scarbrough, and my brother, Andrew Scarbrough, deserve special acknowledgement for their unwavering emotional and financial support. If it weren't for this support, I am sure that I would have never found myself in graduate school. My parents also deserve special credit for instilling in me a love for education, regardless of the multitude of flaws that exist in our current educational systems. And, my whole family (immediate and extended) deserve thanks for instilling in me a belief that I can be absolutely anything that I want to be. I would like to thank Dr. Alice Lindgren for running a challenging and classically-driven science program at Bemidji State University, which prepared me greatly for my graduate education and for her support, guidance, and recommendation for me to continue my education in the Free Radical and Radiation Biology Program at The University of Iowa. Dr. Larry W. Oberley also deserves special mention, as his influence during his leadership of the Free Radical and Radiation Biology Program created an environment where students come first, where education is valued, and where good science is valued over money-driven or popular science, without exception. I am very thankful and mindful that I am a beneficiary of the incredible philosophical impact he has had on this program, which I know will be carried on into the foreseeable future. ii

7 I must also thank Dr. Douglas R. Spitz, my Ph.D. advisor, for the incredible and direct influence he has had not only on my graduate school experience but for my maturation as a scientist and as a more independent investigator. Dr. Spitz was always there to discuss science, to help with finding new directions, providing encouragement and praise, or, as the case may be, a healthy dose of constructive criticism. The financial support I received from his grants and the professional support I received from him, as a person, were absolutely invaluable to my progression and success in the Free Radical and Radiation Biology Program. I would also like to thank Dr. Prabhat Goswami for the mentorship and guidance I received from him as well, during my time at Iowa. His calm and measured advice and the clarity with which he illustrated my path to graduation made a seemingly impossible task actually seem easy. While on the topic, I would also like to thank his lab for their pseudo-adoption of me, both as a graduate student and as a friend. They certainly were not required to have provided the professional and emotional support that they did for me, and I would like them to know that this fact was not lost on me. My committee members (Dr. Douglas Spitz, Dr. Garry Buettner, Dr. Joseph Cullen, Dr. Prabhat Goswami, and Dr. Raymond Hohl) also deserve a great deal of thanks, and not just for their impressive commitment of time and energy that they have devoted to developing my thesis project and overseeing my exam. These people also deserve credit for being willing to discuss science, answer any science question I've had, while also providing simultaneous encouragement and challenge during my professional development at Iowa. iii

8 Thanks also to Dr. Michael McCormick for his assistance in helping me run some of my glutathione assays for me when I was especially busy, and for all the help, assistance, and training he provided for me during my time working with him in the Antioxidant Enzyme Core Laboratory. I would also like to thank Dr. Yueming Zhu and Dr. Leena Chaudhuri, who joined the program at the same time that I did. It was a pleasure to be in a graduate program with such good peers and friends, and the support I received from them, whether it was advice concerning my science experiments, or whether it was emotional support, as we suffered through the same classes, was greatly valued and appreciated. Special thanks also go out to Amanda Kalen, Dr. Nükhet Aykin-Burns, and Dr. Tanja Hadzic, and not just because of the role they played in offering advice and corrections on my thesis, but also because of the incredible amount of friendship and professional support I received through them, over my years at Iowa. Very similar and special thanks also go out to Laura Hefley, a great friend, who I must also thank for helping me to navigate the administrative mazes that are sometimes found at the University of Iowa. Dr. David Gius, Dr. David Mattson, and Dr. Walter Watson, also deserve thanks for the critical role they played in the development of my project, especially to Drs. Gius and Mattson for their inspiration concerning the idea for this project and to Dr. Watson for the crucial role he played in allowing us to develop and run our thioredoxin redox Westerns properly. Finally, I would like to thank my entire lab and the entire Free Radical and Radiation Biology Program for their professional and administrative support as well as the National Institutes of Health for their past and continued financial support for my iv

9 career and for continuing to generously support cancer research at academic institutions all across the country (supported by R01CA133114, R01CA100045, and T32 CA078586). v

10 TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS viii ix xi CHAPTER I. INTRODUCTION AND BACKGROUND Introduction Background Sources of Metabolic Oxidative Stress Hydroperoxide Metabolic Pathway Metabolic Redox Cancer Biology Utilizing Disruptions to Thiol-Based Hydroperoxide Metabolism to Sensitize to 17-Allylamino-17- Demethoxygeldanamycin Treatment 2-Deoxy-D-Glucose: Inhibitor of Glucose Metabolism L-Buthionine Sulfoximine and Auranofin: Inhibitors of Thiol-Based Hydroperoxide Metabolism Summary and Goals II. INHIBITORS OF GLUCOSE AND HYDROPEROXIDE METABOLISM POTENTIATE 17AAG-INDUCED CANCER CELL KILLING VIA METABOLIC OXIDATIVE STRESS. Abstract Introduction Materials and Methods Cell Lines, Media, and Culture Conditions Drug Treatment Clonogenic Survival Assay Glutathione Assay Bicinchoninic Acid Protein Assay Thioredoxin Reductase Assay Thioredoxin-1 Immunoblotting Semi-quantitative Image Analysis Coomassie Blue Gel Staining and Imaging Results Discussion vi

11 III. STUDIES OF THE MECHANISM OF TOXICITY FOLLOWING 2DG, BSO, AURANOFIN, AND 17AAG-MEDIATED CYTOTOXICITY Abstract Introduction Materials and Methods Cell Lines, Media, and Culture Conditions Drug Treatment Clonogenic Survival Assay Superoxide Dismutase Activity Assay Catalase Activity Assay Lowry Protein Assay DHE and CDCFH 2 : Probe Labeling Transfection of sirna ASK-1 Protein Detection Results Discussion IV. DISCUSSION AND FUTURE DIRECTIONS REFERENCES Research Design and Methods General Cell Culture and Design Considerations Aim 1 Rationale Experimental Design Anticipated Results UnanticipatedResults/Alternative Approaches Aim 2 Rationale Experimental Design Anticipated Results Unanticipated Results/Alternative Approaches Aim 3 Rationale Experimental Design Anticipated Results Unanticipated Results/AlternativeApproaches vii

12 LIST OF TABLES Table 1. Genotype and phenotypic characteristics by cell line. 48 viii

13 LIST OF FIGURES Figure 1. Proposed model of how 2DG, BSO, and auranofin may sensitize to 17AAG-mediated cell killing by disrupting three nodes of hydroperoxide metabolism: glucose, glutathione, and thioredoxin metabolism. 2. Hypothesized mechanism by which thioredoxin catalyzes the reduction of protein disulfide bonds. 3. Chemical structure of 17-allylamino-17- demehtoxygeldanamycin. 4. Chemical structure of D-glucose and 2-deoxy-D-glucose. 5. Three human cancer cell lines show different sensitivities to 2DG and 17AAG. 6. BSO and AUR were incapable of enhancing 2DG and 17AAGmediated cell killing when acting as independent agents. 7. The combination of BSO and AUR sensitized to 2DG and 17AAG-mediated clonogenic cell killing and cancer cells were rescued by NAC treatment. 8. 2DG, 17AAG, BSO, and AUR decreased total glutathione levels but NAC was not effective in reversing this trend. 9. Increases in %GSSG caused by 2DG, 17-AAG, BSO, and Auranofin treatment were suppressed by NAC DG, 17AAG, BSO, and AUR treatment significantly increased the ratio of oxidized to total thioredoxin, which is reversed by NAC. 11. Incubation with dithiothreitol prior to iodoacetic acid derivitization restores reduced/total levels of thioredoxin-1 after 2DG, 17AAG, BSO, and auranofin treatment. 12. CDCFH 2 and DHE oxidation in response to drug treatment ix

14 13. AdMnSOD, AdMitoCat, and PEG-Catalase were ineffective at protecting MDA-MB-231 cells from 2DG and 17AAG toxicity. 14. PEG-SOD and PEG-catalase treatments are unable to protect SUM159 cells from 2DG, 17AAG, BSO, and AUR induced cytotoxicity. 15. Pharmacological inhibitors of Akt and JNK signaling were ineffective at modifying cytotoxic response to 2DG and 17AAG treatment. 16. Treatment with ASK-1 sirna did not change clonogenic survival plating efficiency. 17. ASK-1 sirna treatment knocked down ASK-1 protein expression but failed to sensitize cancer cells to 2DG and 17AAG treatment in the presence or absence of BSO and AUR x

15 LIST OF ABBREVIATIONS %GSSG: 17AAG: 2DG: AdMnSOD: AdMitoCat: AdBgII: ANOVA: Percent glutathione disulfide 17-allylamino-17-demethoxygeldanamycin 2-Deoxy-D-glucose Adenovirus containing manganese superoxide dismutase Adenovirus containing mitochondrially-targetted catalase Adenovirus containing BgII (empty vector) Analysis of variance AP-1: Activator protein 1 ATCC: ATP: American Tissue Culture Collection Adenosine triphosphate ASK1: Apoptotic signaling kinase 1 AUR: BCA: BSA: BSO: CDCFH 2 : CO 2 : Cys: DHE: DNA: DMEM: DTNB: Auranofin Bicinchoninic acid Bovine serum albumin L-Buthionine-S,R-sulfoximine Dichlorodihydrofluorescein Carbon dioxide Cysteine Dihydroethidium Deoxyribonucleic acid Dulbecco s Modified Eagle Medium 5,5 -dithio-bis-2-nitrobenzoic acid xi

16 DTT: EDTA: EGTA: ETC: FACSCAN: FADH: FBS: FDG: GCL: GSH: GSSG: GPx: GR: Grx: GST: H + : H 2 O: H 2 O 2 : HCl: HEPES: HIF: HO : HRP: Dithiothreitol Ethylenediaminetetraacetic acid Ethylene glycol tetraacetic acid Electron transport chain Fluorescently activated cell sorter scan Flavin adenine dinucleotide (reduced form) Fetal bovine serum 18-fluoro-deoxy-D-glucose positron emission tomography Glutamate cysteine ligase Glutathione Glutathione disulfide Glutathione peroxidase Glutathione disulfide reductase Glutaredoxin Glutathione-S-transferase Hydrogen ion Water Hydrogen peroxide Hydrochloric acid 4-(2-Hydroxyethyl)-1-piperazineethanesulfonic acid Hypoxia inducible factor Hydroxyl radical Horseradish peroxidase xii

17 Hsp90: Heat shock protein 90 htrx-1: Human thioredoxin-1 hask-1: Human apoptotic signaling kinase 1 IAA: JNK: LSD: Me: MnSOD: MOI: NAC: NADH: NADP + : NADPH: NEM: NF-κB: O 2 : O - 2 : PBS: PBST: PEG: PEG-Cat: PEG-SOD: PMSF: Iodoacetic acid Jun-N-terminal kinase Least significant difference Methyl Manganese superoxide dismutase Multiplicity of infection N-acetyl-L-cysteine Nicotinamide adenine dinucleotide (reduced form) Nicotinamide adenine dinucleotide phosphate (oxidized form) Nicotinamide adenine dinucleotide phosphate (reduced form) N-ethylmaleimide Nuclear factor-κb Molecular oxygen Superoxide Phosphate buffered saline Phosphate buffered saline with 0.1% tween Polyethylene glycol Polyethylene glycol-conjugated catalase Polyethylene glycol-conjugated superoxide dismutase Phenylmethanesulfonylfluoride xiii

18 Prx: PSH: PSSG: R : RH: ROH: ROO : ROOH: ROS: RNS: RPMI: Rxn: Sc sirna: SD: SDS: Peroxiredoxin Protein sulfhydral Protein-glutathione disulfide Alkyl radical (carbon-centered radical) Hydrocarbon Alcohol Organic peroxyl radical Alkyl hydroperoxide Reactive oxygen species Reactive nitrogen species Roswell Park Memorial Institute Reaction Scrambeled sirna Standard deviation Sodium dodecyl sulfate SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis SE: Se: SiRNA: SSA: Trx: Trx-1: TR: Standard error Selenium Silencing ribonucleic acid Sulfosalicylic acid Thioredoxin Thioredoxin-1 Thioredoxin Reductase xiv

19 SOD: UV: Superoxide dismutase Ultraviolet xv

20 1 CHAPTER I: INTRODUCTION AND BACKGROUND Introduction It has been projected that there were 1.5 million new cancer cases and 500,000 cancer deaths in the United States in 2010 [1]. Although the number of deaths is staggering, there has been a noticeable decline in yearly cancer deaths from , amounting to a 21.0% decrease for men and a 12.3% decrease for women. However, despite this small amount of progress, in 2010 the number of deaths caused by cancer is expected to surpass heart disease, as the leading cause of death for those under the age of 85 [1]. Therefore, cancer still represents a major public health concern. However, it is also important to note that while the yearly cancer death rate has declined over the last two decades, this decrease is probably due to earlier detection and prevention. Sadly, when it comes to treating advanced cancer disease stages, little progress has been made in this same time period. For example, in 1996 the 5-year survival rate for stage IV breast cancer was below 20% [2]. According to the National Breast Cancer Foundation, as of 2010, this number has not improved, and is currently measured at approximately 16% [3]. Because of this, it is very important to try to develop novel therapies and targets in cancer research in an attempt to improve patient outcomes and quality of life. One promising target in cancer therapy is glucose and hydroperoxide metabolism. In particular, cancer cells commonly appear to have increased metabolic oxidative stress, while also having considerable capacity to cope with this oxidative stress, via glucose metabolism and glutathione- and thioredoxin-dependent antioxidant pathways [4]. Cancer cells exhibit altered mitochondria metabolism (a source for ROS), higher glucose

21 2 consumption, and higher levels of glutathione and thioredoxin metabolism, compared to normal cells [5-9]. The current study investigates whether decreasing the ability of cancer cells to cope with oxidative stress through glutathione and thioredoxin pathways can sensitize cancer cells to chemotherapies via the enhancement of cellular oxidative stress. In particular, this study shows how inhibitors of glucose and hydroperoxide metabolism can be combined in human cancer cells to overcome chemotherapy resistance and enhance 17AAG-mediated cell killing. It is hoped that this work has potential future applications in cancer therapy by illustrating how simultaneous inhibition of glucose and hydroperoxide metabolism may play a central role for improving outcomes in patients treated with chemotherapeutic agents in a clinical setting. Background Sources of Metabolic Oxidative Stress During cellular metabolism, reactive chemical species are produced as normal byproducts of oxidative metabolism. A prime example of this is found within the mitochondrial electron transport chain (ETC) [10]. Mitochondrial electron transport chains use electrons from reducing co-factors (NADH, succinate/fadh) to reduce oxygen to water in a process to generate energy via a process termed oxidative phosphorylation [43]. This process creates a large amount of potential chemical energy which is eventually used for the generation of chemical energy, in the form of ATP. However, there is a finite probability this process will also produce the one-electron reduction product of O 2, superoxide (O - 2 ), contributing to the production of cellular reactive oxygen species (ROS).

22 3 Most of the O - 2 generation in normal cells is thought to occur from Complex I and Complex III of the mitochondrial ETC [12, 17]. However, dysfunction at other sites may also be important to cancer, since defects in Complex II, are known to be strongly associated with the genesis of paragangliomas and pheochromocytomas in humans [16, 62]. It has been estimated that the endogenous rate of O - 2 production in normal cells is approximately 1-2 molecules of O - 2 produced for every 100 molecules of O 2 that are converted to water by oxidative phosphorylation [13, 14]. However, mitochondria are not the only source of O - 2 in the cell. Other notable sources for O - 2 include NAD(P)H oxidases, xanthine oxidase, the membrane of the endoplasmic reticulum, and cytochome p450 enzymes [15, 18-20]. However, in many cell types, the mitochondria are responsible for as much as three-quarters of the all O - 2 production. This is not always the case though. For example, in mitochondrially-dense liver cells, mitochondrial - sources for O 2 are probably more important, whereas they are less important in red blood cells, which lack mitochondria. Conversely, NADPH oxidases may play more a larger role in total prooxidant generation in specific cell types, such as white blood cells, where ROS play prominent roles in inflammatory responses. Superoxide does not generally cause direct chemical damage to DNA or proteins. However, one of the reasons O - 2 is important to redox biology is because O - 2 plays a central role in the generation of extremely reactive chemical species. One of the most important ways that O - 2 can do this is through the formation of hydrogen peroxide (H- 2O 2 ), which is accomplished either through the spontaneous or enzymatic dismutation of O - 2 (Rxn 1) [21, 22]. At ph 7.4, the rate constant for the spontaneous dismutation is k s1

23 4 = 2.4 x 10 5 M -1 s -1, whereas the rate constant for the enzymatic reaction (by superoxide dismutase) is k s2 = 2 x 10 9 M -1 s O H + H 2 O 2 + O 2 (1) Hydrogen peroxide is of great importance to redox biology for its ability to break down into the most strongly oxidizing species that can be produced by any biological system, the hydroxyl radical (HO ) [23]. The production of HO by H 2 O 2 occurs through a number of different pathways, all of which work by cleaving H 2 O 2 into two chemical species, HO and HO -. UV light (260 nm) and O - 2 are capable of reacting with H 2 O 2 to form HO [24, 25]. But, in a biological system, it has been suggested that the most relevant pathway for generating the HO species is through an iron- or copper-catalyzed Fenton reaction, as it is by far the most kinetically favorable reaction of those mentioned (Rxn 2) [25]. Anything capable of reducing ferric iron (Fe 3+ ) to ferrous iron (Fe 2+ ) is therefore capable of driving Rxn 2, which is known as Fenton chemistry. Fenton chemistry can also be catalyzed by Cu +2 and Cu +1 cations. Superoxide, itself, may act as a reductant, in which case Rxns 2-3 represents the overall reaction known as ironcatalyzed Haber-Weis chemistry [25-29]. H 2 O 2 + Fe 2+ OH + HO + Fe 3+ (2) O Fe 2+ O 2 + Fe 3+ (3) This chemistry implies that O - 2 may play a role in both the production of hydrogen peroxide and HO. However, evidence suggests that superoxide does not directly donate its electrons to either iron or hydrogen peroxide in order to generate the hydroxyl radical. It actually appears that superoxide plays its most significant role in reacting with 4Fe-4S heme clusters, liberating Fe, which is then able to go on to be

24 5 reduced by other cellular factors, before participating in Fenton chemistry [147, 148]. In either case, this magnifies the importance of O - 2, and also of mitochondrial dysfunction to redox biology. Secondly, it may be inferred that any chemical species that is capable of reducing Fe 3+ or Cu +2 may then also promote the generation of hydroxyl radicals. This last point is notable as it suggests the importance of adventitious metals in redox biology. The hydroxyl radical plays a crucial role in redox biology because its high reactivity means that it can chemically react with and damage essentially any cellular macromolecule to which it comes in contact [23]. This may include damage to proteins, lipids, and, most importantly, to DNA. In fact, due to the net negative charge of DNA, and the positive charge of iron, it has been observed and hypothesized that HO formation and damage may occur preferentially near the cell s genetic material, which could then invoke consequences ranging from mutagenesis to the induction of cell death [30-32]. Additionally, as free radical damage occurs to hydrocarbons (e.g. proteins, lipids, DNA) this can result in the formation of a carbon-centered radical (R ), depicted in Rxn 4 [23, 33]. HO + RH R + H 2 O (4) The carbon centered radical is important because it has a number of fates which have significant consequences for the cell. What is worth particular consideration is the organic radical's reaction with molecular oxygen, as this is a favorable reaction, based on the bioavailability of oxygen and a high rate constant for the reaction. For example, the reaction of oxygen with a carbon centered radical on a lipid molecular is estimated to be so favorable as to be limited only by diffusion and the local availability of oxygen (k 5 = 10 9 M -1 s -1 ) (Rxn 5) [34]. The resulting organic hydroperoxide (ROOH) can then react

25 6 with transition metals to form toxic aldehydes, ketones, and other reactive oxygen species, such as peroxyl or alkoxyl radicals (which are similar to HO in their reactivity) [35]. In many cases, this causes additional hydrogen extractions from organic molecules, which results in a propagation of the chemical damage. An example of this is found in the free radical propagation reactions in lipid peroxidation [36]. However, there are ways to repair the organic hydroperoxides before these subsequent damaging reactions occur. R + H + + O 2 ROOH (5) Antioxidants such as ascorbate and catalase are capable of removing hydroperoxides directly, before they cause additional chemical damage. However, there is also another arm of hydroperoxide metabolism, based on thiol-chemistry, which plays a crucial role in cellular detoxification of hydroperoxides. This involves glutathione (GSH) and glutathione peroxidases as well as thioredoxin (Trx) and thioredoxin peroxidases (also known as peroxiredoxins). Glutathione and Trx act as cofactors, donating reducing equivalents to the peroxidase enzymes that catalytically decompose hydroperoxides. Hydroperoxide Metabolic Pathways Hydroperoxides formed in biology are either hydrogen peroxide (H 2 O 2 ) or organic hydroperoxides (ROOH). In either case, these peroxides are important to redox biology because of their ability to generate reactive by-products, such as HO or ROO, which themselves may go on to cause a significant amounts of biological damage or act as signaling molecules. Cells have evolved several different metabolic pathways which allow for the elimination of cellular hydroperoxides. The major detoxification pathways

26 7 that will be considered here are catalase-based metabolism, glucose metabolism, and thiol-based metabolism. Catalase metabolism is perhaps the simplest form of enzymatically catalyzed hydroperoxide metabolism, breaking down hydrogen peroxide to produce water and oxygen (Rxn 6) [37]. 2H 2 O 2 O 2 + 2H 2 O (6) Unlike other hydroperoxide metabolizing pathways, catalase does not require energy to initiate this reaction. Catalase is a heme-containing protein that typically cycles between resting (Fe(III)) and compound I (Fe(IV)) states during its catabolism of hydrogen peroxide [38]. Each step breaks down one molecule of hydrogen peroxide, finally recycling the enzyme back to its active state, and both of these reactions happen rapidly, k c1 = 1.7 x 10 7 M -1 s -1 for the first step and k c2 = 2.6 x 10 7 M -1 s -1 for the second step [39]. Because of the high activity of the enzyme, and the need for it to switch effectively between resting and compound I states, catalase is typically most active and biologically relevant at higher H 2 O 2 concentrations. However, it can be inactivated by extremely high amounts of H 2 O 2, which convert the active site into Compound II [Fe(V)] or Compound III [Fe(VI)] [42]. This system also has other limitations. For example, catalase is localized primarily in the peroxisomes, and so may be of lesser importance to hydroperoxide metabolism everywhere else in the cell [40]. Also, catalase is less efficient at removing H 2 O 2 in the cell at low H 2 O 2 concentration, and it shows limited activity with organic peroxides [14]. Alternatively, hydrogen peroxide may be eliminated through glucose metabolism. It has been speculated that this pathway may represent the most primordial and basic

27 8 form of hydrogen peroxide metabolism. Here, pyruvate, the end-product of glycolysis may react directly with hydrogen peroxide, detoxifying it to acetic acid, carbon dioxide, and water (Rxn 7) [41]. Pyruvate + H 2 O 2 Acetic Acid + H 2 O + CO 2 (7) This pathway has a limitation in that, unlike the other pathways that will be discussed, this reaction is non-enzymatic. Glucose consumption also leads to the detoxification of hydroperoxides through pentose phosphate pathway metabolism, leading to the reduction of nicotinamide adenine dinucleotide phosphate (oxidized) (NADP+) to nicotinamide adenine dinucleotide phosphate (reduced) (NADPH), a critical co-factor needed in glutathione- and thioredoxin-mediated hydroperoxide metabolism. Unlike the other pathways discussed so far, glutathione (GSH) metabolism can act effectively to metabolize H 2 O 2 as well as other organic hydroperoxides. Glutathione metabolism involves enzymatic processes and also requires NADPH as a co-factor, for the proper recycling of the oxidized thiol components that the system produces [43, 45]. Glutathione-mediated hydroperoxide metabolism essentially occurs in two phases. In the first phase, glutathione peroxidase (GPx) utilizes glutathione to detoxify hydroperoxides [44]. This reaction converts two molecules of GSH into glutathione disulfide (GSSG), which reduces the hydroperoxide moiety to a water molecule, with either an additional H 2 O molecule (from H 2 O 2 ) or an ROH (from ROOH) as additional products (Rxn 8). ROOH + 2GSH ROH + H 2 O + GSSG (8) This reaction (Rxn 8) catabolizes hydroperoxides, and along with glutathione reductase (GR, Rxn 9), allows GSSG (oxidized form) to be recycled back to GSH (reduced form), using NADPH as the source of electrons.

28 9 GSSG + H + + NADPH 2GSH + NADP + (9) Glutathione can be present in up to millimolar amounts in cells and plays a very significant role in the total cellular detoxification of hydroperoxides [40, 45]. However, glutathione may play other roles in cells besides the ones strictly related to hydroperoxide metabolism. For example, glutathione can form mixed protein disulfides (PSSG), to either repair oxidative protein damage or perhaps even to alter the metabolic, regulatory, and structural events of a cell (Rxn 10) [46, 47,142]. These reactions can then be catalytically reversed by a class of thiol-disulfide oxidoreductases, known as glutaredoxins (Grx) (Rxn 11) [48]. PSH + GSSG PSSG + GSH (10) PSSG + HS-Grx-SH HS-Grx-SSG + PSH (11) Glutathione also plays an important role in the liver, as part of phase II metabolism. Here, glutathione is conjugated to various compounds, by the action of a class of enzymes known as glutathione-s-transferases (GST), to assist in the neutralization, solubilization, and elimination of potentially toxic xenobiotics [45]. Certain classes of glutathione transferases (μgsts and αgsts) are also known to be able to decompose organic hydroperoxides in a reaction similar to GPx, and are thought to also contribute to non-se-dependent GPx activity in some cells [128]. Thioredoxins (Trx) are kda proteins which represent another thiol-based hydroperoxide metabolizing system in the cell. In mammalian cells, there are three forms of thioredoxins. Thioredoxin-1 is predominantly located in the cytosol, thioredoxin-2 is predominantly found in the mitochondria, whereas thioredoxin-3 is only expressed in human spermatozoa, and it is so far only known to play a poorly understood role in

29 10 spermatogenesis [50, 56-58]. Thioredoxin metabolism has many similarities to glutathione metabolism, one of which is the ability to catalyze dithiol-disulfide oxidoreductions [50]. Trx does this by first coordinating with a disulfide-containing protein. The catalytic cysteines of Trx then each transfer a hydrogen atom to the oxidized protein. This reaction oxidizes Trx, generating an intramolecular disulfide bond, and reduces the target protein (Fig. 2) [50]. Thioredoxin is also capable of donating its electrons to peroxiredoxins. In so doing, thioredoxin forms a disulfide bond. Peroxiredoxins are a family of proteins which contains six isoforms (in mammalian cells) and, in their reduced form are capable of metabolizing hydrogen peroxide as well as organic hydroperoxides directly [55]. Once in its disulfide form, thioredoxin lacks antioxidant activity. Therefore, in order to be recycled, thioredoxin needs to be reduced by the enzyme thioredoxin reductase (TR) and the cofactor NADPH [49, 50]. For this recycling reaction, TR binds NADPH and Trx. In the ensuing catalytic reaction, two hydrogen atoms are transferred to thioredoxin disulfide, reducing it back to the active form of thioredoxin. Trx can then reduce another disulfide protein (such as peroxiredoxin), and this cycle can continue. In this way, Trx, TR, peroxiredoxins and NADPH represent another key system by which hydroperoxides can be metabolized by cells [51]. Recent research is beginning to show that Trx-1 can also have other effects in a cell that stand apart from its electron donating abilities. These include the ability of Trx- 1 to be able to interact with numerous signaling molecules and transcription factors in the cell, which may cause significant cellular effects, especially with regard to the induction of protective responses associated with drug resistance in cancer cells.

30 11 Thioredoxin-1 is thought to interact with the signaling molecule ASK1 by being able to bind to its N-terminal region when Trx1 is in its reduced form [53]. Interestingly, Grx is able to bind to the C-terminus of ASK1, when Grx is in its reduced form, and also controls the activity of ASK1, similar to Trx1. Either Trx or Grx binding to ASK1 is thought to be inhibitory to ASK1 activity. However, it has been shown that, when ROS oxidize Grx and Trx, this will cause them to disassociate with ASK1 [54,144]. ASK1 is then free to participate in cell signaling events, with notable effects with regards to inducing apoptosis in some cell lines [53]. Thioredoxin-1 is also capable of binding to and affecting the activity of protein kinase C and NF-κB [52]. However, Trx-1 has even more notable and seemingly paradoxical effects on the transcription factor NF-κB that are seemingly not related to its protein binding activity. Reduced Trx-1 can reduce cysteine 62 of the p50 subunit for NF-κB, thereby allowing it to bind to the DNA. However, at the same time, Trx-1 can also prevent the NF-κB inhibitor, IκB, from disassociating. In other cases, the effects that Trx-1 can have on cellular proteins can be more indirect. For example, Trx-1 can reduce the cysteine residues of Ref-1, which can then reduce the cysteine residues of fos and jun -- subunits of the important transcription factor, AP-1 [52]. This reduction reaction will then promote AP-1 s competency for DNA binding. This pathway has been shown to be activated by such stressors as ionizing radiation [129]. Here, ionizing radiation is thought to enhance AP-1 activity by causing oxidative stress which leads to an increase in pentose phosphate activity. The increase in pentose phosphate activity is then thought to lead to the increased production of NADPH,

31 12 which is then thought to lead to increasing the ratio of reduced to oxidized thioredoxin, which would then favor AP-1 activation. In summary, the cellular capacity and redox state of Trx-1 can create significant effects in the cell through its interaction with various chemical intermediaries, leading to detoxification of hydroperoxides and/or activation of signaling and gene expression pathways. Cells have numerous pathways to metabolize cellular hydroperoxides. Having multiple pathways available gives the cell flexibility and versatility, making it able to respond rapidly and efficiently to different levels of hydroperoxide stress, in different cellular compartments. There also appears to be evolutionary advantages to having redundancies built into these systems, as one system could then compensate for the loss of the other. These pathways are also of particular importance, as they may govern the responses of cancer cells to oxidative stress. Metabolic Redox Cancer Biology Cancer is a very heterogeneous disease, varying from patient to patient, tissue to tissue, and even between the cells of a single metastatic lesion [59]. Growth rates, nutrient needs, genetic mutation, and epigenetic modifications all abound in cancer and are highly variable. This represents a fundamental problem in cancer therapy, making target identification for eradicating cancer cells difficult. However, alterations to cancer cell oxidative metabolism seem to be found in nearly all cancer cells and may represent a valid target for designing novel and effective clinical therapies. At first glance, it would seem as if the metabolic patterns of cancer cells are as variable from cell to cell as their highly mutable genomes [7, 60, 61]. However, there are

32 13 several consistent oxidative metabolic alterations, which seem to be constant in the majority of cancer cells tested. One of these observations is that cancer cell mitochondria have an unusually high number of genetic mutations compared to normal cells, and even compared to the cancer cell nuclear DNA, and cancer cells have historically been observed as having diminished rates of aerobic respiration, compared to normal cells [5, 6, 8-10]. Cancer cell mitochondria have also been shown to demonstrate morphological alterations compared to normal cell mitochondria, including mitochondrial hypertrophy, fragmentation, and unusual arrangements of mitochondrial cristae [63]. Given the severe alterations in cancer cell mitochondrial morphology, it is expected that this creates an area of critical dysfunction in cancer cells, where mutations to mitochondria ETC proteins accumulate, allowing for increased ROS production and, thus, even more mutation potential. This hypothesis has been supported by data showing that, under glucose deprivation, a panel of several different human cancer cell lines (PC-3, DU145, MDA-MB-231, and HT29) showed evidence of increased oxidative stress (as measured by CDCFH 2 fluorescence and increased glutathione oxidation). Normal cells show no such sensitivity to glucose deprivation [4]. Importantly, Rho0 cells (which lack mitochondrial DNA) were resistant to the induction of oxidative stress and toxicity caused by glucose deprivation, strongly implying that the source of toxicity caused by glucose deprivation in these cancer cells was through mitochondrially generated ROS [68]. The significance of mitochondrial DNA mutations in cancer cells was also highlighted by work which showed that mutations to the succinate dehydrogenase complex subunits C and D (components of Complex II of the mitochondrial ETC)

33 14 increase oxidative stress and genomic instability in Chinese hamster lung fibroblast cells [130, and Data in Submission, Owens et al.]. These data imply and potentially explain how high levels of mitochondrial DNA damage, observed in cancer cells, may directly lead to increased steady-state amounts of ROS in cancer cells, relative to normal cells, as these mitochondrial DNA mutations lead to dysfunctional mitochondrial ETC proteins, which then have been shown to be capable of enhancing cellular oxidative stress and genomic instability. In agreement with this model, every cancer cell line tested thus far has shown increased levels of oxidative stress compared to their normal cells counterparts, as shown by increased levels of DHE and CDCFH 2 oxidation [4]. This is a critical point, as it suggests a fundamental difference between cancer cells and normal cells, which may have far reaching implications to designing effective cancer therapies. However, while defective mitochondria may play a significant role as a source for increased oxidative stress in cancer cells, there are also other general changes to cancer cells' redox biology that are worth noting as well. It has been known for decades that cancer cells consume more glucose than their normal cell counterparts [5]. Increased glucose consumption in cancer cells is actually such a common feature that it has been used for decades, in 18-fluoro-deoxy-D-glucose positron emission tomography (FDG-PET), to image neoplastic tissues in cancer patients. Cancer cells also tend to overexpress glutathione transferases, which play an important role in drug detoxification and in decreasing cellular oxidative stress [64]. Oberley et al. also showed that cancer cells tend to have lower activity levels of manganese superoxide dismutase (SOD), particularly with respect to the mitochondrially located form of SOD,

34 15 manganese superoxide dismutase (MnSOD) [65]. The consequences of this decrease in MnSOD activity also appeared to be particularly profound in cancer cells. For example, overexpressing MnSOD in melanoma cells profoundly altered the phenotype of these cells, including inhibition of colony formation in soft agar as well as the ability to form tumors in mice [69]. These data strongly implied that alterations to SOD activity in cancer may not just be an indirect event but somehow were causally related to the evolution of the cancer phenotype as well. Oberley et al. also showed that, while there were no other alterations to antioxidant activity that were as consistent as those found with MnSOD activity, it was found that some antioxidant activities were, at least in general, very low in cancer cells, relative to normal cells [66]. This demonstrates a common trend in cancer cells, of having decreases in some antioxidant enzyme expression and higher levels of oxidative stress, relative to normal cells. Glucose consumption has also been implicated as playing a part in hydroperoxide metabolism, as pyruvate may be used to detoxify hydrogen peroxide directly, and glucose can also be metabolized through the pentose phosphate pathway to produce NADPH, an essential co-factor for GSH and Trx metabolism. In fact, to date, there is no evidence that increased glucose consumption in cancer cells is necessary for ATP production [67]. Meanwhile there is much evidence accumulating to suggest that glucose metabolism is upregulated in cancer for the specific purpose of combating oxidative stress (via hydroperoxide metabolism) in cancer cells. For example, Lee et al. showed that glucose deprivation was toxic to MCF-7 adriamycin-resistant breast cancer epithelial cells, and that this toxicity could be reversed by treatment with N-acteyl cysteine (NAC), a small molecule thiol-antioxidant [68]. These data were further supported by work which later

35 16 showed that glucose deprivation was selectively toxic to cancer cells versus their normal cell counterparts, in every cell line tested, and that these toxicities could also be reversed by treatment with adenovirus-transduced catalase (mitochondrially targeted) and MnSOD over-expression [4]. Data from the NAC rescue of glucose-deprivation-induced cytotoxicity also implicates thiol-mediated chemistry in the cell as playing some important role in cancer cell survival. Since glucose metabolism also fuels glutathione and thioredoxin metabolism, it is thought that the impairment of these processes may actually be a primary cause for the cancer cell toxicity caused by glucose deprivation, by sensitizing to endogenous oxidative stress. This is also supported by observations that glutathione and glutathione-s-transferases are often upregulated in cancer cells resistant to drugs such as adriamycin, relative to normal cells [64, 76]. Also, glutathione levels have been shown to correlate to chemotherapy resistance in a variety of cancer cell lines, models, and among a wide variety of chemotherapy agents tested [70-75]. Additionally, higher levels of glutathione and thioredoxin can protect against mutagenic events and apoptosis, which would be expected to assist in driving the process of carcinogenesis forward and contribute to chemotherapy resistance in cancer cells [54, 70, 77]. All of these data support the hypothesis that cancer cells are under increased oxidative stress, from a variety of potential sources, as compared to normal cells. Also, it appears that cancer cells may be defective in certain antioxidant activities, such as SOD activity, while being more reliant on other forms of antioxidant protection than normal cells (such as glutathione, thioredoxin, and glucose metabolism). These observations lead to the hypothesis that by inhibiting thiol-based hydroperoxide metabolism and

36 17 glucose metabolism in cancer cells, effective oxidative stress-induced cell killing could be achieved in cancer cells. Therefore, it was the aim of this project to combine inhibitors of thiol-based hydroperoxide metabolism and glucose metabolism to see if they could selectively enhance cell killing and oxidative stress in cancer cells, with the aim of overcoming chemotherapy resistance. Utilizing Disruptions to Thiol-Based Hydroperoxide Metabolism to Sensitize to 17-Allylamino-17-Demethoxygeldanamycin Treatment 17-Allylamino-17-demethoxygeldanamcyin (17AAG) is a derivative of the experimental chemotherapeutic compound, geldanamycin (Fig. 3) [78-81]. Geldanamycin was first discovered in 1970 as an antibiotic in the broth of streptomyces hygroscopicus [82]. In 1977, its potential as an anticancer agent was uncovered [83]. In 1990, it was suggested that its anticancer effects may be related to its ability to inhibit heat shock protein 90 (Hsp90) [84, 85]. This garnered interest in developing this drug for clinical trials, as Hsp90 is a known chaperone protein for p53, HER2-Neu, HIF-1A, Bcr- Abl, and other known and prominently occurring oncogenes, which are thought to help drive the cancerous phenotype as well as carcinogenesis [86]. In the absence of Hsp90 activity, Hsp90 clients are improperly folded and then ubiquitinated for proteosomal degradation [87]. Thus, it was thought that geldanamycin could help to combat multidrug resistance by simultaneously halting the activity of several important oncogenes, and thus help to limit the cancer cells ability to adapt to the therapy, while also having little to no effect on normal cells. Preclinical data was highly supportive of this notion, but subsequent clinical trials and animal models identified that geldanamycin

37 18 had a problem with dose-limiting liver and kidney toxicity [88]. Thus, interest was then generated on finding a chemical derivative of geldanamycin which could provide the same anticancer activity of geldanamycin but without the dose limiting side effects. 17AAG is one of the compounds that arose from these efforts [81]. With a substitution at the 17-position of the chemical, 17AAG was able to show virtually identical anticancer activity to geldanamycin with a far-reduced ability to cause liver damage, in both rodent models and in humans [80]. So far, 17AAG has been used in several phase I and II clinical trials [78, 79]. It has been applied to a variety of cancers, including prostate and breast cancer models, which will be utilized for this project. 17AAG has also shown some successful instances of enhancing cancer therapy while also being well-tolerated in patients. Thus, 17AAG is attractive compound for further clinical development, particularly with respect to 17AAG s connections to enhancing cellular oxidative stress. While it is true that 17AAG is an inhibitor of Hsp90 and part of its anticancer effects are due to this, it has also been proposed that 17AAG also has several oxidative stress connections, which seem related to 17AAG-induced cancer cell toxicity. For example, 17AAG is known to downregulate the expression of peroxiredoxins 1-4 [89]. Theoretically, this could further increase the levels of oxidative stress in cancer cells, since they are known to already have dysfunctional mitochondria which may overproduce ROS, compared to normal cells. Also, 17AAG contains a quinone structure, which is especially relevant to its redox activity. It had been hypothesized that, under the right conditions, this quinone could undergo redox reactions in the cell, to engage in a process of futile redox cycling [90]. This is a process where cellular reductants are

38 19 consumed to reduce 17AAG's quinone structure into a semiquinone, which would then donate its electron to oxygen, producing O - 2 in a cycle that can be repeated an indeterminate number of times [91]. In accordance with this hypothesis, superoxide production by 17AAG has been detected through EPR analysis in vivo and this has also been associated with 17AAG-toxicity [90]. This supports the hypothesis that 17AAG is capable of redox cycling in the cell and producing O - 2. Additionally, 17AAG toxicity is also thought to be associated with oxidative stress because high cellular glutathione levels are known to be highly correlative to 17AAG resistance [75]. Finally, 17AAG is thought to be related to oxidative stress due to the ability of NAC to act as an antidote to 17AAG toxicity [75]. These data allow for a crucial connection to be made between 17AAG toxicity, the induction of oxidative stress, and the reliance on thiol-based hydroperoxide metabolism for cancer cell survival. Therefore, it was hypothesized that, if hydroperoxide metabolism could be compromised, then cancer cells would be selectively sensitized to 17AAG-mediated cell killing. Thus, this project has the goal of finding pharmacological ways to disrupt hydroperoxide metabolism, so as to sensitize to 17AAGmediated cell killing to potentially enhance the clinical development and utility of this chemotherapy agent. 2-Deoxy-D-Glucose: Inhibitor of Glucose Metabolism Glucose deprivation, while achievable in cell culture, is not achievable in vivo. This is because the liver provides a constant source of glucose to the body through the process of gluconeogenesis [43]. Thus, the only way of mimicking glucose deprivation in vivo is to use a pharmacological agent. For this purpose, the pharmacological agent, 2- deoxy-d-glucose (2DG), was used as a competitive inhibitor of glycolysis (Fig. 4). 2DG

39 20 can be converted by hexokinase into 2-deoxy-glucose-6-phosphate, but this product will go on to inhibit phosphoglucose isomerase and it may also affect other downstream enzymes involved in glycolysis. This causes glycolytic rates to be inhibited when 2DG and glucose are added in equal-molar concentrations to each other in a glycolytic system [92]. 2DG is also known to have inhibitory effects in the pentose phosphate pathways as well. While 2DG is not thought to be able to inhibit the first NADPH producing step of the pentose phosphate pathway (catalyzed by glucose-6-phosphate dehydrogenase), it is thought to be able to inhibit the enzymatic activity of 6-phosphogluconate dehydrogenase. This is thought to reduce the amount of NADPH that can be produced by the pentose phosphate pathway metabolism of glucose by 50%. This theory is also supported, at least in part, by experiments which showed that 20 mm 2DG treatment (1:1 ratio of 2DG:glucose from the media) for 24 h was able to decrease NADPH levels in MDA-MB-231 cells by roughly half of their non-treated values [Unpublished Data, Hadzic et al., 4, 74]. 2DG is already known to be tolerated in humans with only minor side-effects [93]. 2DG has also been shown to be able to enhance chemotherapy agent toxicity in a variety of cell models with a variety of chemotherapy agents [71, 72,74]. Specifically, 2DG was shown to enhance breast, head and neck, and color cancer cell killing in the presence of paclitaxil, cisplatin, andriamycin, and carboplatin [Unpublished Data, Fath et al., 71, 72, 74]. All of this work was performed in cell culture, but selected models have already been transitioned into mouse tumor xenograft studies. In particular, studies using mice bearing human head and neck cancer cell xenografts (FaDu and Cal-27) showed

40 21 that the combined treatment of 2DG and cisplatin was able to significantly increase survival, compared to untreated animals and cisplatin treatment alone [94]. Because of the low normal tissue toxicity seen in these previous studies there is still great interest in pursuing 2DG as a clinical agent. However, it was also found that acquired resistance to 2DG therapy was potentially a problem, and it was not known how cancer cells were becoming resistant to 2DG. This led to the hypothesis that cancer cells were compensating for 2DG treatment by upregulating other antioxidant responses and protective mechanisms. In particular, it was thought that enhancing cellular thiol-based hydroperoxide metabolism would be a logical way to compensate for 2DG-induced oxidative stress. Therefore, efforts were undertaken to explore avenues by which cancer cells could be more effectively sensitized to oxidative stress induced by 2DG, by combining with inhibitors of glucose and thiol-based hydroperoxide metabolism [73]. L-Buthionine Sulfoximine and Auranofin: Inhibitors of Thiol-Based Hydroperoxide Metabolism Glutamate cysteine ligase (GCL) is required for and is the rate limiting enzyme in glutathione synthesis [45]. Its irreversible inhibition with L-buthionine sulfoximine (BSO) treatment (1 mm) has been shown to nearly completely inhibit glutamate cysteine ligase activity and deplete intracellular glutathione levels to 5% or less of their untreated values within 24 h [131, 143]. This is especially important because it has previously been shown that 1 mm BSO is an achievable and safe plasma concentration in both animals and humans [95]. The fact that BSO has already been in clinical trials and found to be well-tolerated in humans makes it an attractive agent for depleting intracellular glutathione for future clinical applications.

41 22 It is thought that BSO s ability to deplete intracellular glutathione is significant enough that it should have a profound ability to sensitize cells to oxidative stressmediated cell death, as long as glutathione metabolism is involved in the process. However, like 2DG, previous researchers, as well as work done within this project (see Chapter 2), have shown that BSO, by itself, is sometimes insufficient to cause cancer cell death [72, 73]. This has led to the proposition that BSO could be combined with other agents that cause oxidative stress and cell death, in order to achieve chemosensitization. However, despite some positive data, BSO treatment has sometimes shown inability to sensitize to 2DG and other chemotherapy agents consistently (see Chapter 2). Therefore, it was hyopthesized that there could be other redundant mechanisms in cancer cells that could compensate for GSH depletion. Thioredoxin metabolism was identified as a likely metabolic pathway that could compensate for GSH depletion, as it could function at the levels of cell signaling and hydroperoxide metabolism to adapt to the loss of glutathione. Whereas glutathione is synthesized from a set of enzymes specific to making glutathione, thioredoxin is a much larger peptide, and is synthesized through the ribosomal machinery, like other cellular proteins. This means that it is difficult to selectively halt the synthesis of thioredoxin without halting general protein synthesis which could cause non-specific cytotoxicity. Therefore, a different strategy was used to inhibit thioredoxin metabolism. Namely, the compound auranofin (AUR) was used to inhibit the activity of thioredoxin reductase, the enzyme responsible for the recycling of thioredoxin, from its oxidized to its reduced state [96]. It was thought that this compound should further sensitize cells to oxidative stress by causing increases in thioredoxin oxidation and subsequent activation of cell death signaling pathways.

42 23 Like BSO, AUR has several advantages that allow it to be used as a potent tool for disrupting thioredoxin metabolism while also allowing it to be developed as a clinical tool. One of these advantages is that it is already known that AUR can be safely administered to people, as it is used in the treatment of rheumatoid arthritis [11]. Furthermore, it is known that the plasma concentrations that are achievable in humans and already shown to be safe (micromolar levels) are also concentrations at which inhibition of thioredoxin reductase activity can be observed (nanomolar levels) [11, 97]. With the addition of 2DG, BSO, and AUR, it was hypothesized that a more complete inhibition of cellular hydroperoxide metabolism could be achieved, as redundancies in hydroperoxide metabolism would each be targeted by a specific drug treatment (Fig. 1). Since each drug was, by itself, relatively non-toxic to normal cells and already shown to be well-tolerated in humans, it was thought that the combination could have the potential to increase cancer cell killing, while having limited normal tissue sideeffects. Furthermore, it was expected that the 2DG, BSO, and AUR combination could also abrogate chemotherapy agent resistance, as is often associated with thiol metabolism in cancer cells. These compounds have also previously been shown to be effective when combined with other agents that cause oxidative stress, to enhance cancer cell killing [71-74]. Therefore, these agents were thought to be attractive candidates for combining with 17AAG to cause effective and consistent cancer cell killing, with the aim of improving the clinical development of 17AAG. Summary and Goals The central hypothesis of this project is that the inhibition of hydroperoxide metabolism, at the levels of glucose-, glutathione-, and thioredoxin-metabolism, could

43 24 represent a means of sensitizing cancer cells to oxidative stress-induced cell killing mediated by 17AAG. Consistent with this hypothesis, it was shown that 2DG, BSO, and AUR treatments were capable of dramatically sensitizing to 17AAG-induced cancer cell killing, in MDA-MB-231 and SUM159 breast cancer epithelial cells and in PC-3 prostate adenocarcinoma cells. Furthermore, these increases in toxicity correlated with depletion and oxidation of both thioredoxin and glutathione. Finally, these increases in parameters indicative of oxidative stress, as well as the observed drug toxicity, were reversed by treatment with the thiol antioxidant, NAC. The goal of this project is to use these data and results to define potential mechanisms for selective cancer cell killing via metabolic oxidative stress, as well as to improve our understanding of how hydroperoxide metabolism contributes to chemotherapy resistance and how inhibition of these metabolic pathways could provide a powerful new tool for the enhancement of future cancer therapy outcomes.

44 25 Figure 1: Proposed model of how 2DG, BSO, and AUR may sensitize to 17AAGmediated cell killing by disrupting three nodes of hydroperoxide metabolism: glucose, glutathione, and thioredoxin metabolism.

45 26

46 27 Figure 2. Hypothesized mechanism by which thioredoxin catalyzes the reduction of protein disulfide bonds [adapted from 50].

47 28

48 29 Figure 3. Chemical structure of 17-allylamino-17-demethoxygeldanamycin [adapted from 81].

49 30

50 Figure 4. Chemical structure of D-glucose and 2-deoxy-D-glucose [adapted from 98]. 31

51 32

52 33 CHAPTER II: INHIBITORS OF GLUCOSE AND HYDROPEROXIDE METABOLISM POTENTIATE 17AAG-INDUCED CANCER CELL KILLING VIA METABOLIC OXIDATIVE STRESS. Abstract 17-Allylamino -17-demethoxygeldanamycin (17AAG) is an experimental chemotherapeutic agent, believed to form free radicals in vivo, and cancer cell resistance to 17-AAG is believed to be a thiol-dependent process. Inhibitors of glucose metabolism [2-deoxy-D-glucose (2DG)] and inhibitors of thiol-dependent hydroperoxide metabolism [L-buthionine-S,R-sulfoximine (BSO) and auranofin (AUR)] were tested to determine if they could enhance 17AAG-mediated cell killing. When 2DG (20 mm, 24 h), BSO (1 mm, 24 h), and AUR (500 nm, 3 h) were combined with 17AAG, they significantly (p < 0.05) increased cell killing, in three human cancer cell lines (PC-3, SUM159, MDA-MB- 231). Increases in toxicity seen with this drug combination also correlated with increased glutathione depletion (all three cell lines), glutathione oxidation (MDA-MB-231, SUM159), Trx oxidation (all three cell lines), and Trx depletion (MDA-MB-231, SUM159). Furthermore, treatment with the thiol antioxidant NAC (15 mm, 24 h) was able to significantly protect from the drugs (2DG, 17-AAG, BSO, and AUR) toxicity as well as reverse drug-induced glutathione oxidation, Trx oxidation, and Trx depletion in every cell line tested. These data strongly support the hypothesis that 2DG, BSO, and AUR sensitized to 17AAG-mediated cell killing by causing thiol-dependent oxidative stress and suggest that these agents could be used in combination to enhance efficacy in human cancer therapy.

53 34 Introduction Cancer cells are thought to be under increased metabolic oxidative stress compared to their normal cell counterparts [4]. To date, every cancer cell line tested has shown significantly higher levels of CDCFH 2 and DHE oxidation, relative to its normal cell counterpart, which is believed to be indicative of increased steady-state levels of reactive oxygen species (ROS), such as superoxide or hydrogen peroxide in cancer cells [4]. It is thought that these increased levels of ROS are in part due to dysfunctional mitochondrial metabolism which has also been commonly observed in cancer cells [8-10, 63, 99]. Increased levels of ROS are believed to contribute to aberrant redox signaling, genomic instability, cell immortalization, and the inability to differentiate, which are all characteristics of the malignant phenotype. It is thought that cancer cells upregulate several aspects of hydroperoxide metabolism in order to compensate for these higher levels of oxidative stress, relative to normal cells [54, 64, 71, 73-75]. As evidence of this, metabolic pathways involving glutathione, thioredoxin and glucose (both glycolysis and pentose cycle activity) are often elevated in cancer cells relative to normal cells [4, 5, 6, 64, 77]. These pathways are all processes thought to play critical roles in metabolism of cellular hydroperoxides [4]. Glutathione and thioredoxin are used as cofactors (by glutathione peroxidases or thioredoxin peroxidases) to eliminate cellular hydroperoxides. The pentose phosphate pathway (which utilizes glucose as a substrate) provides NADPH, which is a critical cofactor that allows the disulfide forms of glutathione and thioredoxin to be recycled back into their sulfhydral states (through glutathione reductase and thioredoxin reductase) [43]. The hypothesis that glucose metabolism protects cancer cells from endogenous

54 35 oxidative stress is supported by the observation that glucose deprivation has been found to cause selective clonogenic cell killing in cancer cell populations via increases in hydroperoxide and superoxide levels [4,67]. Glucose metabolism via glycolysis may also limit the need to utilize aerobic respiration to provide energy for the cell (a potent source of endogenous ROS). This hypothesis was supported by Ahmad et al., where it was shown that, while glucose deprivation caused cytotoxicity and increases in parameters indicative of oxidative stress (increases in glutathione disulfide (GSSG) and superoxide), Rho0 cells (lacking mitochondrial DNA) were resistant to these affects caused by glucose deprivation [68]. Thus, glucose and hydroperoxide metabolism are thought to work coordinately and play critical roles, during oxidative metabolism, in detoxifying hydroperoxides. Glucose deprivation is not achievable in vivo. This is because liver provides a constant source of glucose to the body through the process of gluconeogenesis [43]. Thus, the only way of mimicing glucose deprivation in vivo is to use a pharmacological agents that inhibit glucose metabolism, such as 2-dexoy-D-glucose (2DG), a competitive inhibitor of glucose metabolism. Previous studies have shown that 2DG induces differential cytotoxicity between cancer cells versus normal cells as well as inducing oxidative stress in cancer cells [4,67,71-74]. There is a significant body of evidence suggesting that agents capable of enhancing oxidative stress, such as 2DG, are capable of selectively increasing cancer cell killing and sensitivity to chemotherapy agents, relative to normal cells [4, 71-74]. Using this biochemical rationale, pharmacological interventions that could effectively inhibit hydroperoxide metabolism in cancer cells, for the purpose of sensitizing cancer cells to

55 36 oxidative stress and chemotherapy-mediated cytotoxicity have been under development, such as the GSH depleting agent, L-buthione-S,R-sulfoximine (BSO) and the thioredoxin reductase (TR) inhibitor, auranofin (AUR). 17AAG is a derivative of geldanamcyin and was chosen for use in this study because of its potential for further clinical development (it is in several phase I and phase II clinical trials) and because of its connections to oxidative stress. [78, 79]. Electron paramagnetic resonance (EPR) analysis has shown that 17AAG can form free radicals in vivo and that these may be at least partially responsible for its toxicity, that 17AAG resistance correlates to high glutathione levels, and that 17AAG may also inhibit peroxiredoxin activity, which could also enhance intracellular oxidative stress in cancer cells [75, 78, 79 89, 90]. When tested in combination, 2DG and 17AAG were shown to sensitize some cancer cell lines (MDA-MB-231 and PC-3) but not others (SUM159) to clonogenic cell killing. However, the combination of GSH synthesis inhibition with BSO and TR inhibition with AUR, consistently sensitized all cell lines tested to 2DG and 17AAG toxicity. Futhermore, this increased toxicity was accompanied by increased thiol oxidation and depletion, and these changes, as well as the cytotoxicity caused by the drug combination, were attenuated by treatment with N-acetyl cysteine (NAC). This increase in tumor cell killing did not occur unless both BSO and AUR were used in combination. These data support the conclusion that simultaneous disruption of both glutathione and thioredoxin metabolism could provide effective and consistent sensitization to 17AAGinduced cancer cell killing. MDA-MB-231, SUM159, and PC-3 cell lines were chosen for use in this study because they represent aggressive, hormone-independent cancers, which tend to be

56 37 difficult to treat, leading to significant mortality in patients with breast and prostate cancer. Breast and prostate cancer models were also utilized for this study to explore the generality of this work to both multiple cell lines and for cancers that arise from different tissues of origin. Additionally, these cell lines express a variety of genotypic and phenotypic traits that also helps to improve the potential generality of the results obtained from these experiments (Table 1). Materials and Methods Cell Lines, media, and culture conditions Hormone-independent human breast cancer epithelial cells (MDA-MB-231) were a kind gift from the lab of Michael Henry from The University of Iowa (Iowa City, IA). Human prostate adenocarcinoma cells (PC-3) were obtained from ATCC, (Manassas, VA). Each of those two cell lines were grown in RPMI 1640 and 10% fetal bovine serum. Human hormone-independent breast cancer SUM159 cells were obtained from Asterand, (Detroit, MI) and were grown in Ham's F12 media, supplemented with 10 mm HEPES, 10 ng/ml insulin, 50 nm hydrocortisone, and 5% FBS. All cells were grown and maintained at 37 o C and 21% oxygen. During clonogenic survival assays, the culture media was supplemented with 0.1% gentamycin sulfate. Drug Treatment Cells were plated and then allowed to grow for 48 h, until they had reached approximately 70% confluence. Following this, the media on each plate was changed and then the cells were treated with 500 nm 17-AAG, 20 mm 2DG, 15 mm NAC, and/or 1 mm BSO for 24 h, in the same media used to grow each cell line. This was done to mimic therapeutically deliverable doses as closely as possible. For experiments in which

57 38 the cells were treated with AUR, the cells were treated as normal, and then in the last 3 h of drug treatment, the cells were treated with 200 nm or 500 nm AUR. The cells were then incubated with AUR until the end of the 24 h drug treatment. Clonogenic Survival Assay Both floating and attached cells from the treated dishes were collected. Attached cells were collected using trypsinization. Trypsin (0.25%) was inactivated with media containing FBS. Cells were then centrifuged, before being resuspended in fresh media. Cell counts were then made with a Coulter Counter (Beckman Coulter, Brea, CA). Cells were then plated at a low density and allowed to grow for 8-14 days in complete media. Cells were then stained with Coomassie Blue dye, and the colonies on each plate were subsequently counted and recorded, and clonogenic cell survival was determined, as described previously [102]. Surviving fraction was determined as the number of colonies per plate divided by the number of cells initially plated. Normalized surviving fraction was determined as the surviving fraction of a clonogenic plate divided by the average surviving fraction of the control (untreated) plates within a single experiment. Glutathione Assay Prior to the GSH/GSSG assay, cells were scraped in 5% 5-sulfosalicylic acid (SSA) and frozen. The 5,5 -dithio-bis-2-nitrobenzoic acid (DTNB) recycling assay was then used to quantify GSH and GSSG levels in the cell supernatants, as described previously by Griffith and Anderson [103, 104]. Sample data was normalized to protein level per sample, as determined by the bicinchoninic acid protein assay.

58 39 Bicinchoninic Acid Protein Assay Bicinchoninic acid protein assay was performed using the BCA TM Protein Assay Kit from Pierce Biotechnology (Rockford, IL). The assay was performed as per manufacturer s instructions, using the Enhanced Protocol. Thioredoxin Reductase Activity Assay 700,000 MDA-MB-231 cells were seeded to each 100 mm tissue cultures plate and allowed to grow for 48 h. Cells were then treated with 500 nm auranofin for 3 h. Treatment plates that were not treated with auranofin received the auranofin vehicle (DMSO, 0.1% final concentration) as a control. After this, cells were scraped and harvested in PBS. Then, cells were assayed for thioredoxin reductase activity by using a Thioredoxin Reductase Activity Kit, purchased from Sigma-Aldrich (St. Louis, MO, Catalog Number: CS0170). The assay was run by following the suggested manufacturer s protocol. Briefly, samples were incubated in approximately 90 mm potassium phosphate, ph 7.0, 9 mm EDTA, 0.24 mm NADPH, and 1.19 mg/ml DTNB. The rate of DTNB reduction was then measured spectrophotometrically by measuring change in absorbance at 412 nm for 3 min. Thioredoxin reductase activity was then estimated by subtracting the rate of DTNB reduction, in the presence of sample, from the rate of DTNB reduction in the presence of sample plus an inhibitor of thioredoxin reductase activity: 1/50 dilution of Thioredoxin Reductase Inhibitor Solution, also provided by Sigma-Aldrich (St. Louis, MO, Catalogue Number: T9199). Thioredoxin activity for each sample was then also normalized to protein, as determined by the Bradford protein assay, as described previously [106].

59 40 Thioredoxin-1 Immunoblotting The thioredoxin-1 immunoblotting procedure was generally performed, as described previously [105]. Approximately three million cells were lysed in G-lysis buffer (50 mm Tris-HCl, ph 8.3, 3 mm EDTA, 6 M guanidine-hcl, 0.5% Triton X-100) containing 50 mm iodoacetic acid (ph 8.3). For each experiment, control plates, for identifying thioredoxin redox state bands in the eventual Western blot, were also incubated with either 2 mm DL-dithiothreitol (DTT) or 2 mm H 2 O 2, for 10 min at RT, prior to the addition of 50 mm iodoacetic acid (IAA). Afterwards, the lysate from all cells was then incubated in the dark for thirty minutes, with the IAA. The lysates were then centrifuged in G-25 microspin columns (GE Healthcare). Protein was then quantified, from the eluent by performing a Bradford protein assay, as previously described [106]. Equal amounts of protein were then added to a 15% acrylamide native gel. The gel was then run at 100 V constant for approximately 2.5 h. The proteins contained in the gel were then transferred to a nitrocellulose membrane (BIORAD Labs), using a semi-dry transfer protocol, as described previously [105, 107]. The nitrocellulose membrane was then washed in PBST (phosphate buffered saline, with 0.1% Tween), blocked in 5% milk with PBST for 1 h, before being incubated at 4 o C overnight with the primary antibody, 1:1000 goat anti-htrx-1 (American Diagnostica, Inc.) in PBST with 2% BSA. The primary antibody was then removed, the blot was washed in PBST for 10 minutes three times, with constant shaking, before being incubated for 1 h with the secondary antibody [Rabbit anti-goat IgG, horseradish-peroxidase- (HRP)-labeled, 1:3000 dilution in PBST (Santa Cruz Biotechnology, cat#sc2020)]. The blot was then washed again for 10 minutes three times in PBST before being treated with ECL

60 41 (electrochemiluminescence) detection reagents (Renaissance, NEN). The protein was then visualized by exposing the blot to X-ray film for 2-5 min in a dark room with a film cassette, before developing the film. In an alternate method of protein visualization, a Typhoon FLA 7000 (GE Healthcare Life Sciences) imaging system was used to directly detect the fluorescent signal from the blot. Semi-quantitative Image Analysis Image files were processed and analyzed using Image J software (1.42q, Wayne Rasband, National Institutes of Health, USA). Briefly, the image was cropped to include only the bands of interest and the immediate surrounding areas of the blot. Background was then subtracted by using a 50-pixel rolling ball algorithm. The integrated density of each band was then measured, and this measurement was subtracted from the measured integrated density of an area of the blot, adjacent to the band of interest, containing no other bands. The result was interpreted to be the true integrated density of the thioredoxin-1 signal. The ratio of oxidized to total thioredoxin was defined as (integrated density of the oxidized thioredoxin band)/(integrated density of the reduced thioredoxin band + integrated density of the oxidized thioredoxin band). Coomassie Blue Gel Staining and Imaging Following the transfer step of a standard western blotting protocol, the acrylamide gel was stained in a Coomassie Blue solution, containing 0.2% Coomassie Blue, 7.5% acetic acid, and 50% ethanol for 15 min, with gentle shaking. The gel was then destained with phosphate buffered saline, containing 0.1% Tween-20, with three washes over two hours. The gel containing the stained protein was imaged using an AlphaImager (Alpha Innotech Corp).

61 42 Results In order to examine whether or not an inhibitor of glucose metabolism (2DG), could effectively enhance 17AAG toxicity, the two drugs were combined together in three different cancer cell lines, and their toxicity was measured via a clonogenic cell survival assay. Since 17AAG has already been used in Phase I and II clinical trials in both breast and prostate cancer models, and because the hormone-independent variants of these cancers have been shown to be resistant to existing therapies, cell lines for use in this study were selected that would address this appropriate clinical need while also maintaining relevance to cancer models where 17AAG has been proposed to be effective. Because of this, breast epithelial cancer cell lines, MDA-MB-231 and SUM159, along with prostate cancer cell line, PC-3, were chosen for these studies. Cells were treated with 20 mm 2DG and 500 nm 17AAG for 24 h. Following drug treatment, cells were trypsinized and assayed for clonogenic cell survival. Interestingly, each cell line tested showed a different response profile to the 2DG and 17AAG drug combination (Fig. 5). In particular, it seemed that MDA-MB-231 cells showed an increase in toxicity that could be additive, compared to the toxicity of each drug alone. PC-3 cells appeared to show a similar increase of toxicity, with the 2DG and 17AAG combination. Conversely, SUM159 appeared to be resistant to the treatment of 2DG and 17AAG, both as single agents and in combination. These results encouraged further exploration into mechanisms that could account for the differential susceptibility between the cell lines. In particular it was hypothesized, since 2DG suppresses hydrogen peroxide metabolism that adding other inhibitors of hydroperoxide metabolism could either further enhance 17AAG toxicity or overcome resistance to 17AAG. Accordingly,

62 43 cells treated with 2DG and 17AAG were treated with BSO (an inhibitor of glutatmate cysteine ligase, a rate limiting enzyme in the synthesis of glutathione) and/or AUR (an inhibitor of thioredoxin reductase), in order to limit hydroperoxide metabolism through the glutathione peroxidase- and peroxiredoxin-pathways. MDA-MB-231 and PC-3 cells were treated with either BSO (1 mm, 24 h) or AUR (500 nm, for the last 3 h of drug treatment) (Fig. 6). The activity of auranofin was confirmed by running a thioredoxin reductase assay on similar treated cells (Fig. 6 C), and the activity of BSO was shown in glutathione assays performed on similarly treated cells (Fig. 8). However, neither BSO or AUR, by themselves, were capable of enhancing 2DG and 17AAG toxicity. In contrast, when BSO and AUR were used in combination, remarkable sensitization to 2DG and 17AAG cell killing was observed, even in the previously drug resistant SUM159 cell line (Fig. 7). Furthermore, when cells were treated with 15 mm N-acetyl-L-cysteine (NAC) for 24 h during drug treatment, the toxicity from the drug combinations was significantly ameliorated. Since NAC is a nonspecific thiol antioxidant, these data suggested that BSO and AUR were enhancing the toxicity of the 2DG and 17AAG combination by causing severe disruptions to critical cellular thiol pools and enhancing cellular oxidative stress. In order to examine this hypothesis further, the glutathione and thioredoxin redox couples were examined to determine how the drug treatments were affecting cellular thiol redox status. In all three cell lines, treatment with 2DG, BSO, AUR, and 17AAG caused significant reduction in total glutathione content (Fig. 8). Interestingly, even though NAC was able to significantly restore cellular viability in cells treated with 2DG, BSO, AUR, and 17AAG, NAC was not capable of restoring total glutathione levels. However,

63 44 in cells treated with 2DG, BSO, AUR, and 17AAG, NAC was able to significantly suppress the percent of GSSG, as a proportion to total cellular glutathione, in SUM159 cells (Fig. 9). Similar results were obtained in MDA-MB-231, but did not reach statistical significance. (GSSG was not-detectable in PC-3 cells.) The ability of NAC treatment to suppress %GSSG as well as suppressing clonogenic cell killing (Fig. 7) suggests that the oxidation of cellular thiol pools may be casually related to cell killing. Further confirmation for this conclusion was obtained when all three cell lines treated with 2DG, BSO, AUR, and 17AAG demonstrated significant increases in the oxidation of thioredoxin that were nearly completely suppressed by NAC treatment (Fig. 10). In addition, the drug-induced increases in the ratio of oxidized to total thioredoxin were 3-4-fold higher, versus control, ratios in every cell line tested. In certain western blots, some drug treated conditions appeared to show changes to either the total or the redox state of cellular thioredoxin-1 (i.e. Fig. 10B, Lane 2 vs. Lane 6; Fig 10C Lane 1 vs. Lane 3), but these changes were not seen to be statistically significant upon further experimental replication. These results, combined with the glutathione data, clearly showed that the combination of 2DG, BSO, AUR, and 17AAG caused oxidative stress, as measured by changes to glutathione and thioredoxin metabolism. A closer analysis of thioredoxin redox Western blots from MDA-MB-231 (10A, Lane 4), SUM159 (Fig. 10B, Lane 4), and PC-3 (Fig. 10C, Lane 4) also showed what appears to be a decrease in total thioredoxin levels in the 2DG, BSO, AUR, and 17AAG treatment condition. Coomassie-stained gels suggested that this difference in total amounts of thioredoxin was not due to differences in protein loading. It was therefore hypothesized that the thioredoxin may be either degraded or that the thioredoxin was

64 45 forming mixed protein disulfide complexes with larger proteins that may not be able to enter the 15% acrylamide native gel. To determine if larger mixed protein disulfide complexes of thioredoxin could be forming during drug treatment, samples from cells treated with 2DG, BSO, AUR, and 17AAG were lysed and then treated with DTT to reduce mixed protein disulfides, before then being dervatized with IAA and processed for a thioredoxin redox Western blot (Fig. 11). The results showed that DTT completely reduced the oxidized thioredoxin in the higher molecular weight bands and restored the drug treated cells (Fig. 11, Lane 2) to control levels of thioredoxin-1 immunoreactive protein. These data strongly support the hypothesis that the disappearance in total thioredoxin in the 2DG, BSO, AUR, and 17AAG treated cells was caused by an increase in the formation of mixed protein disulfides containing thioredoxin-1. Taken together, the thioredoxin and glutathione data (Fig. 8-11) strongly suggest that 2DG, BSO, AUR, and 17AAG were effectively causing oxidative stress in cellular thiol pools engaged in hydroperoxide metabolism, that this may be casually related to the toxicity caused by the 2DG, BSO, AUR, and 17AAG treatments, and that NAC is able to reduce both the toxicity and oxidative stress caused by these agents. Discussion The data presented in the current study support the hypothesis that human cancer cells demonstrate a variety of different basal sensitivities to inhibitors of glucose metabolism (2DG) combined with 17AAG. The combination of inhibitors of glutathione and thioredoxin metabolism (BSO and AUR), as single agents, were relatively non-toxic in all cancer cell lines. However, when BSO and AUR were combined, highly significant sensitization to 2DG and 17AAG-mediated clonogenic cell killing was achieved in all

65 46 cells tested. It is note worthy that both thioredoxin as well as glutathione metabolism needed to be compromised before cancer cells were effectively sensitized to cytotoxicity caused by the drug combination. This finding suggests that both major intracellular thiol pools involved in hydroperoxide metabolism must be compromised before maximum drug sensitization is observed. This also supports the hypothesis that if either GSH or Trx metabolic is inhibited, one pathway may be able to compensate for the loss of the other. Interestingly, the use of AUR (a thioredoxin reductase inhibitor) was not sufficient to cause an alteration in the cellular redox state of thioredoxin. This was interpreted as suggesting that a decrease in thioredoxin reductase activity is unable to effect thioredoxin levels, as long as the cells are not under significant stress, as, in combination with other agents (BSO, 2DG, and 17AAG), thioredoxin redox state was then shown to be profoundly affected in all of the tested cell lines. The combination of 2DG, BSO, AUR, and 17AAG was observed to be very capable at depleting intracellular glutathione and thioredoxin, while also dramatically increasing the oxidation of both glutathione and thioredoxin-1 thiol pools. These changes correlated to the increases in clonogenic cell killing, which were observed in the three human cancer cell lines tested. In a direct test of causality, the drug-induced changes to these thiol pools, as well as the cytotoxicity caused by these drug treatments, were either partially or completely inhibited in every cell line tested by treatment with the thiol antioxidant N-acetyl-L-cysteine. These data strongly support a causal connection between disruptions to thiol-mediated hydroperoxide metabolism and cancer cell killing by these drug combinations.

66 47 The finding that inhibition of both GSH and Trx-1 metabolism is required for maximal sensitization is significant because many times cancer cell heterogeneity and their ability to adapt is responsible for treatment failure. The identification of relatively non-toxic and well-tolerated adjuvants for enhancing cancer cell killing is also highly desirable in the case of advanced, hormone-independent cancers. The results show that BSO and AUR, which have been shown to be well-tolerated in humans as single agents, dramatically enhance cancer cell chemosensitivity. Therefore, this suggests an important and underexplored biochemical rationale for enhancing the efficacy of anticancer therapy.

67 48 Table 1: Genotype and phenotypic characteristics by cell line. Information with respect to p53, Rb, p16, hormone receptor status, and aldehyde dehydrogenase positivity are shown for MDA-MB-231, SUM159, and PC-3 cells. Data obtained through literature review. References used are noted within the table. ER = estrogen receptor, PR = progesterone receptor, HER2 = HER2Neu receptor, AR = Androgen receptor measured inhibition of growth by androgen treatment, and ALDH+ = Percent of aldehyde dehydrogenase expressing cells.

68 49 Figure 5: Three human cancer cell lines show different sensitivities to 2DG and 17AAG. MDA-MB-231 (A), SUM159 (B), and PC-3 (C) cancer cells were treated with 20 mm 2DG and 500 nm 17AAG for 24 h before being assayed for clonogenic cell survival. Each panel represents data from at least three experiments. Data shown represent mean normalized surviving fraction + SD. * = p < 0.05 versus control treatment, # = p < 0.05 versus any other treatment condition within the cell line, as determined by One-way ANOVA, using Tukey s post-hoc test.

69 50

70 51 Figure 6: BSO and AUR were incapable of enhancing 2DG and 17AAG-mediated cell killing when acting as independent agents. MDA-MB-231 (A) and PC-3 cells (B) were treated with 20 mm 2DG, 500 nm 17AAG, and 1 mm BSO for 24 h and 500 nm AUR for the last 3 h of drug treatment, before being assayed for clonogenic cell survival. Panels (A) and (B) represent data from at least three experiments each. Panel (C) represents data from MDA-MB-231 cells, collected from at least 4 independent treatment plates. Data shown in (A) and (B) represent mean normalized surviving fraction + SD. Data shown in (C) represents mean normalized thioredoxin reductase activity + SD. One-way ANOVA, using Tukey s post-hoc analysis determined that BSO and AUR treatment did not significantly alter response in cells treated with or without 2DG + 17AAG. * = p < 0.05 versus the same treatment without 2DG + 17AAG. # = p < 0.05 versus control.

71 52

72 53 Figure 7: The combination of BSO and AUR sensitized to 2DG and 17AAGmediated clonogenic cell killing and cancer cells were rescued by NAC treatment. MDA-MB-231 (A), SUM159 (B), and PC-3 (C) cells were treated with 20 mm 2DG, 500 nm 17AAG, and 1 mm BSO for 24 h and 500 nm AUR for the last 3 h of drug treatment, before being assayed for clonogenic survival. Data shown represent mean normalized surviving fraction + SD. * = p < 0.05 versus control and # = p < 0.05 versus the same drug treatment plus NAC, as determined by One-way ANOVA, using Tukey s post-hoc test to test for significance. Data are from (MDA-MB-231, PC-3) three experiments each or (SUM159) two experiments.

73 54

74 55 Figure 8: 2DG, 17AAG, BSO, and AUR decreased total glutathione levels but NAC was not effective in reversing this trend. MDA-MB-231 (A), SUM159 (B), and PC-3 (C) cells were treated with 20 mm 2DG, 500 nm 17AAG, and 1 mm BSO for 24 h and 500 nm AUR for the last 3 h of drug treatment, then assayed for total glutathione, using a spectrophotometric GR/NADPH/DTNB-based recycling assay, as described previously [16, 17]. Data shown represent mean fold change in total glutathione, relative to nontreated cells, + SE. Each panel represents data from at least three experiments each. * = p < 0.05 versus control treatment and # = p < 0.05 versus the same treatment group without NAC, as determined by One-way ANOVA, using Tukey s post-hoc test for significance.

75 56

76 57 Figure 9: Increases in %GSSG caused by 2DG, 17-AAG, BSO, and AUR treatment were suppressed by NAC. MDA-MB-231 (A) and SUM159 (B) cells were treated with 20 mm 2DG, 500 nm 17-AAG, and 1 mm BSO for 24 h and 500 nm AUR for the last 3 h of drug treatment, then assayed for total glutathione and GSSG (in GSH equivalents), using a spectrophotometric GR/NADPH/DTNB-based recycling assay. Bars represent GSSG/(Total Glutathione)x100% + SE. * = p < 0.05 versus control, # = p < 0.05 versus the same treatment without NAC, as determined by One-way ANOVA, using Tukey s post-hoc test. Each panel represents data from at least three experiments.

77 58

78 59 Figure 10: 2DG, 17AAG, BSO, and AUR treatment significantly increased the ratio of oxidized to total thioredoxin, which is reversed by NAC. Semi-quantitative analysis of thioredoxin redox Westerns and representative Western blots for Trx-1 are shown for MDA-MB-231 (A), SUM159 (B), and PC-3 (C) cells were treated with 20 mm 2DG, 500 nm 17AAG, and 1 mm BSO for 24 h and 500 nm AUR for the last 3 h of drug treatment, prior to being assayed for Trx-1 by Western blotting. Following drug treatment, cells were scraped directly into G-lysis buffer (50 mm Tris-HCl, ph 8.3, 3 mm EDTA, 6 M guanidine-hcl, 0.5% Triton X-100) and then derivatized in 50 mm iodoacetic acid (IAA), as described previously [17]. 2 mm DTT and 2 mm H 2 O 2, for 15 minutes, prior to cell harvest, were used as positive controls for thioredoxin reduction or oxidation, respectively. If DTT or H 2 O 2 was used, cells were incubated in G-lysis buffer with 2 mm of one of the respective compounds for 15 minutes, before derivatization with IAA was then allowed to proceed for 30 min. Data shown represent mean (integrated density of oxidized band(s))/(integrated density of reduced band + integrated density of oxidized band(s)), normalized to control. * = p < 0.05 versus control, as determined by One-way ANOVA, using Tukey s post-hoc test to test for significance. Each panel is representative of data from at least three experiments.

79 60

80 61 Figure 11: Incubation with dithiothreitol prior to iodoacetic acid derivitization restores reduced/total levels of thioredoxin-1 after 2DG, 17AAG, BSO, and AUR treatment. SUM159 cells were treated with 20 mm 2DG, 500 nm 17AAG, and 1 mm BSO for 24 h and 500 nm AUR for the last 3 h of drug treatment. Following drug treatment, cells were scraped directly into G-lysis buffer (50 mm Tris-HCl, ph 8.3, 3 mm EDTA, 6 M guanidine-hcl, 0.5% Triton X-100) and then derivatized in 50 mm iodoacetic acid (IAA). If DTT or H 2 O 2 was used, cells were incubated in G-lysis buffer with 2 mm of one of the respective compounds for 15 minutes, before derivatization with IAA was then allowed to proceed for 30 min. Figure is representative of data from three experiments.

81 62

82 63 CHAPTER III: STUDIES OF THE MECHANISM OF TOXICITY FOLLOWING 2DG, BSO, AURANOFIN, AND 17AAG-MEDIATED CYTOTOXICITY Abstract In combination with inhibitors of glucose and hydroperoxide metabolism (2DG, BSO, and AUR), 17AAG toxicity is significantly enhanced in cancer cell lines, via a mechanism that involves disruptions to thiol-mediated hydroperoxide metabolism. However, the exact mechanism leading to clonogenic cell death has not been completely elucidated. Additional experiments were done with 2DG, 17AAG, BSO, and AUR compounds in order to better delineate a mechanism of action. In particular, JNK, Akt, and ASK-1 signaling were investigated in MDA-MB-231 cells, following 2DG, 17AAG, BSO, or AUR treatment. Also, the role of specific free radical mediators, such as superoxide and hydrogen peroxide were investigated by measuring DHE and CDCFH 2 oxidation in treated cells or by pretreating cells with strategies to increase SOD or catalase activity prior to drug exposure. Data obtained suggest that these cell signaling mechanisms and specific free radical mediators may not play a significant role in 2DG, 17AAG, BSO, and AUR-mediated oxidative stress and cytotoxicity. Introduction It has already been shown in chapter 2 that, in combination with 2DG, BSO, and AUR, 17AAG-mediated cytotoxicity, along with other indicators of increased cellular oxidative stress, were dramatically increased. A precise mechanism by how this ocurred though was not delineated. Therefore, additional experiments were performed in order to delineate such a mechanism, to improve our understanding of the biological principles underlying these effects in cancer cells.

83 64 While Hsp90 inhibition is thought to play some role in 17AAG-mediated cytotoxicity, it is known that increased oxidative stress is also involved. For example, it has previously been reported that 17AAG can form superoxide in vivo and that the formation of these radicals is at least partially responsible for its toxicity [90]. This increase in superoxide levels is thought to be due to 17AAG's quinone structure, and ability to redox cycle [91]. However, 17AAG may have other ways of increasing cellular oxidative stress as well. For example, the expression of peroxiredoxins 1, 2, 3, and 4 were all found to be decreased in retinal pigment epithelial cells treated with 17AAG [89]. High glutathione levels are also known to correlate to 17AAG resistance [75]. Taken together, these data suggest that 17AAG toxicity may be strongly influenced by oxidative stress, perhaps explaining why 2DG was able to cause increased cell killing in certain cancer cell lines (i.e. MDA-MB-231 and PC-3). Because of these data regarding 17AAG, it was hypothesized that superoxide or hydrogen peroxide may directly mediate the disruptions that were caused to thiol metabolism, following 2DG, BSO, AUR, and 17AAG treatment. This was suggested because of 17AAG's ability to produce superoxide and superoxide's ability to dismute to hydrogen peroxide, which could then directly cause thiol oxidation. However, specific free radicals species were not the only mediators which could theoretically be involved in the drugs' toxicity. Potential cell signaling responses to 2DG, BSO, AUR, and 17AAG treatment were also considered. 17AAG-toxicity also has several connections to certain cell signaling pathways. For example, it is known that Hsp90-inhibition can inhibit Akt, causing the activation of apoptotic signaling kinase-1 (ASK-1), which has been previously shown to be involved

84 65 in 17AAG-mediated cytotoxicity [108, 109]. Importantly, these pathways were also thought to be relevant to this study because they contain several connections to increased cellular oxidative stress. ASK-1 activity is tightly regulated by a thiol-mediated mechanism, having its N- terminal side bound by thioredoxin and its C-terminal side bound by glutaredoxin [110]. Under conditions of oxidative stress, these thiol proteins will become oxidized and will release ASK-1, allowing for its further activation and activity. ASK-1 activity is also known to increase the activity of JNK, which itself has redox connections. In particular, JNK is known to be activated by a number of oxidative stress events, including UV radiation, X-ray radiation, serum deprivation, and heat shock [ ]. JNK activation has also previously been shown to be a mechanism of toxicity associated with glucose deprivation, which could explain why 2DG was able to enhance 17AAG-mediated cell killing in certain cell lines [67, 115]. Furthermore, since ASK-1 activity is controlled by thioredoxin and glutaredoxin, it was thought that this also may explain why BSO and AUR could dramatically enhance 2DG and 17AAG-mediated cell killing, by causing the oxidation of thioredoxin and glutaredoxin, enhancing ASK-1 activation. Therefore, these signaling pathways were also seen as potentially relevant to the mechanisms of 2DG, BSO, AUR, and 17-AAG-mediated cytotoxicity. In general, data obtained so far from CDCFH 2, DHE, and clonogenic assays found that superoxide, hydrogen peroxide, ASK-1 activation, JNK activation, or Akt inhibition do not appear to play a significant role in the toxic interaction caused by 2DG, 17AAG, BSO, and AUR treatment. These data suggest that some other, as of yet undiscovered mechanism involving thiol oxidation, must be involved.

85 66 Materials and Methods Cell Lines, media, and culture conditions Human hormone-independent breast cancer cells (MDA-MB-231) were obtained from the lab of Michael Henry from the University of Iowa (Iowa City, IA). Human prostate cancer adenocarcinoma cells (PC-3) were obtained from ATCC, (Manassas, VA). Each of those cell lines were grown in RPMI 1640 and 10% fetal bovine serum. Human hormone-independent breast cancer SUM159 cells were obtained from Asterand, (Detroit, MI) and were grown in Ham's F12 media, supplemented with 10 mm HEPES, 10 ng/ml insulin, 50 nm hydrocortisone, and 5% FBS. All cells were grown and maintained at 37 o C and 21% oxygen. During clonogenic survival assays, the culture media was supplemented with 0.1% gentamycin sulfate. Drug Treatment Cells were plated and then allowed to grow for 48 h, until they had reached approximately 70% confluence. Following this, the media on each plate was changed and then the cells were treated with 500 nm 17-AAG, 20 mm 2DG, 15 mm NAC, and/or 1 mm BSO for 24 h, in the same media used to grow each cell line. For experiments in which cells were treated with AUR, cells were treated as described above, and then in the last 3 h of drug treatment, cells were treated with 200 nm or 500 nm AUR. Cells were then incubated with AUR until the end of the 24 h drug treatment. For cell signaling studies, cells were incubated with either (1 or 10 µm) SP or 25 µm LY for 24 h (during 2DG, BSO, and 17AAG treatment), as these concentrations have previously been reported to be capable of inhibiting JNK or Akt activity, respectively [116, 117]. For antioxidant studies, cells were either incubated with 100 U/mL Polyethylene glycol-

86 67 conjugated superoxide dismutase (PEG-SOD), 100 U/mL PEG-catalase, and/or 18 μm PEG (negative control) for 24 h (during 2DG, BSO, and 17AAG treatment). Alternatively, cells were transduced with adenovirus constructs, containing 100 multiplicity of infection (MOI), containing either no target gene (AdEmpty) or containing MnSOD gene and containing mitochondrially-targetted catalase gene (50 MOI AdMnSOD + 50 MOI AdMitoCat). Following transduction, cells would be incubated with virus for an additional 24 h, before drug treatment then proceeded as normal. Clonogenic Survival Assay Both floating and attached cells from the treated dishes were collected. Attached cells were collected by using 0.25% trypsinization. Trypsin was inactivated with media containing 10% FBS. Cells were then centrifuged, before being resuspended in fresh media. Cell counts were then made with a Coulter Counter. Cells were then plated at a low density and allowed to grow for 14 days in complete media. Cells were then stained with Coomassie Blue dye, and the colonies on each plate were subsequently counted and recorded, and clonogenic cell survival was determined, as described previously [102]. Surviving fraction was determined as the number of colonies per plate divided by the number of cells initially plated to that plate. Normalized surviving fraction was determined as the surviving fraction of a plate normalized to the average surviving fraction for control (sham treatment) plates within an experiment. Superoxide Dismutase Activity Assay Following clonogenic survival, the excess trypsinized cells were washed in ice cold PBS, centrifuged, excess PBS removed, and cell pellets frozen at -20 o C. On the day of the assay, cell pellets were then resuspended in DETAPAC buffer (0.05 M phosphate

87 68 buffer, ph 7.8, 1.34 mm DETAPAC). Protein concentration for each sample was then determined by using the method of Lowry [146]. Samples were then assayed for superoxide dismutase activity, as described previously [145]. Briefly, samples were placed in a reaction buffer containing 0.05 M potassium phosphate, ph 7.8, 1.34 mm DETAPAC, 0.13 mg/ml BSA, 1 U catalase, 56 μm NBT, 100 μm Xanthine, and 50 μm bathocuproine disulfonic acid. Xanthine oxidase (approximately 0.01 U/mL in 1.34 mm DETAPAC) was then added to the reaction buffer. The superoxide-mediated reduction of NBT was then assessed spectrophotometrically by reading the change in absorbance at 560 nm in the sample tube, and the rate of NBT reduction (over 3 min) in the sample buffer was then calculated. Sample was then added in progressively higher amounts, and the change in the rate of NBT reduction was calculated as percent inhibition (a function of µg of protein added), relative to the rate of NBT reduction in the absence of sample. Percent inhibition was assumed to be proportional to the amount of SOD activity in the sample added to the reaction tube. Percent inhibition was then plotted versus protein concentration, for each sample, and the resulting curve was assumed to follow Michaelis- Menton kinetics, from which the SOD activity for each sample was calculated in terms of U per mg protein. Catalase Activity Assay Following clonogenic survival, the excess trypsinized cells were washed in ice cold PBS, centrifuged, excess PBS removed, and cell pellets were frozen at -20 o C. On the day of the assay, cell pellets were then resuspended in DETAPAC buffer (0.05 M phosphate buffer, ph 7.8, 1.34 mm DETAPAC). Protein concentration for each sample was then determined by using the method of Lowry [146]. Sample protein (2-5 mg) was

88 69 then added to 0.05 M potassium phosphate buffer, ph 7.8, and this solution was then blanked at 240 nm. Then, the same concentration of sample protein was used in a solution containing 0.05 M potassium phosphate buffer and 10 mm H 2 O 2. The disappearance of H 2 O 2 was then immediately assayed spectrophotometrically, by measuring the change in sample absorbance at 240 nm for 2 min. The activity of catalase in the reaction tube was then calculated as k = 1/60 * ln(abs 0 sec /Abs 60 sec ). The activity was then normalized to mg protein for each sample, and activity was then reported as k/mg protein. Lowry Protein Assay Cell pellets were resuspended in DETAPAC buffer (0.05 M phosphate buffer, ph 7.8, 1.34 mm DETAPAC). Protein concentration for each sample was then determined by using the method of Lowry [146]. Briefly, a solution containing 0.01% cupric sulfate, 0.01% NaK Tartarate, 2% sodium carbonate, and 0.1 N sodium hydroxide was added to each sample and to each tube containing BSA and water (for the standard curve of the assay). Samples were vortexed and then allowed to incubate for 10 min at RT. Then, Folin-Ciocalten Phenol Reagent was added to each reaction tube to a final concentration of 0.1 N. Samples were vortexed and then allowed to incubate for 30 min at RT. The absorbance of each sample tube was then read at 500 nm. A standard curve was constructed and each sample protein concentration was then calculated by interpolating within the range of values provided by the standard curve. All Lowry protein assay reagents were obtained from Sigma-Aldrich (St. Louis, MO).

89 70 DHE and CDCFH 2 Probe Labeling Media was aspirated off plates and cells were washed with PBS and then 2 ml of PBS was added to each dish. 10 μg/ml of oxidation sensitive 5-(and-6)-carboxy-2,7 - dichlorodihydrofluorescein diacetate (CDCFH 2 ) probe, or 10 μg/ml DHE were added to each treatment plate. All treatment plates were done in triplicate for each experiment. Vehicle control using 0.1% DMSO by volume (no CDCFH 2 or DHE) and positive control using 0.1% Antamycin A by volume were also included in all experiments. Cells were then incubated with either CDCFH 2 for 15 min or DHE for 60 min, before the probe was washed off. The cells were then trypsinized on ice with 10x trypsin, which was inactivated 15 min later by MEM phenol-free media containing 10% FBS. Cells were then centrifuged at 4 o C before being collected in tubes which were then run through FACScan flowcytometer (Becton Dickinson Immunocytometry System, INC., Mountain View, CA) (excitation 488 nm, emission 585 nm band-pass filter for DHE studies and exciting 488 nm, emission 530 nm band-pass filter for CDCFH 2 studies). Roughly 10,000 counts were made per sample, and the mean of three samples was calculated for each condition. The negative control (background fluorescence) was subtracted from each of the sample averages and then each sample was normalized to the control probe labeled sample, to yield the mean fluorescent intensity (MFI) measurement per cell, for each sample. Transfection of sirna Scambled sirna (sc-37007), ASK-1-specific sirna (sc-29748), and transfection reagent (TR) (sc-29528) were obtained from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA). Eight µl of each sirna construct (initial concentration: 10 μm) were added to two

90 71 separate vials, containing 100 µl of serum-free RPMI 1640 media (Reagent A1 and Reagent A2). Eight µl of TR was then added to two separate vials, containing 100 µl of serum-free RPMI 1640 media (Reagent B1 and B2). 100 µl of Regent A1 was then carefully added to Reagent B1 (ASK-1 specific sirna mixture), and likewise with Reagents A2 to Reagent B2 (scrambeled sirna mixture). The reagents were then incubated at room temperature in the dark for 30 min. After this, 800 µl of serum free media was added to each of the combined reagent mixtures (A1 + B1 and A2 + B2). After this time, MDA-MB231 cells that were approximately 70% confluent on a 60 mm tissue culture dish, had their media aspirated off. They were washed once with serumfree media. One ml of serum-free media was then added to a control plate. Two other plates were incubated with 1 ml each of either scrambled or ASK-1 specific sirna solution. The plates were then incubated in the dark at 37 o C for 5 h. After this time, 1 ml of RPMI 1640 media, containing 20% FBS was added to each plate. Cells were then incubated for 72 h at 37 o C, 5% CO 2, and 21% O 2. Subsequent to this, cells were then either treated with 2DG, BSO, AUR, and 17AAG (as previously described) to assay for clonogenic survival, or cells were scraped in PBS, to determine ASK-1 content in the cells, following sirna transfection. ASK-1 Protein Detection Protein was determined using a Bradford protein assay, as previously described [17]. Equal protein was then loaded to an 8% SDS gel, and PAGE was performed at a constant 100 V, for approximately 3 h. The gel was then transferred to a nitrocellulose membrane, using a semi-dry transfer protocol, as previously described [105, 107]. The blot was then blocked in milk, and hask-1 was then detected using the antibodies and

91 72 methods provided by Santa Cruz Biotechnology, Inc. (Santa Cruz, CA). For the primary antibody incubation, the western blot was incubated in (1:100 dilution) mouse monoclonal IgG 1, anti-human ASK-1 (F-9) antibody (Santa Cruz, CA, product: sc-5294) in 2% BSA, overnight at 4 o C. Cells were then washed in PBST for 10 min, three times, before being incubated with the secondary antibody. The secondary antibody was goat anti-mouse IgG-HRP-linked (Santa Cruz, CA, product: sc-2005) and was made up as a 1:1000 dilution in PBST with 5% non-fat dry milk. Western blots were incubated with the secondary antibody for 1 h at room temperature, before then being washed in PBST for 10 min three times. After this wash, protein was then detecting using ECL detection and imaging methods, as described previously (see Chapter 2). Results In order to investigate the role that superoxide or hydrogen peroxide may play in the toxicity of the 2DG and 17AAG treatments, MDA-MB-231 cells were treated with 20 mm 2DG and 500 nm 17AAG for 24 h, before being labeled with either DHE or CDCFH 2 probes (Fig. 12). The fluorescent signal emitted by oxidized DHE or oxidized CDCFH 2 were interpreted as indirect indications of the steady-state levels of either cellular superoxide or hydrogen peroxide, respectively. Data from the DHE studies did not show an significant increase in DHE oxidation in any of the drug treated conditions (2DG and 17AAG) (Fig. 12B). However, data from the CDCFH 2 studies showed statistically significant increases in probe oxidation in both the 17AAG condition, as well as the 2DG + 17AAG condition (Fig. 12A). While these results suggested that the cells may be under some increased steady-state level of prooxidants, the lack of specificity of the CDCFH2 probe for specific prooxidants, leaves doubt as to the actual oxidant being

92 73 measured. Interestingly, there was no increase in probe oxidation with respect to the 17AAG-alone treatment versus the 2DG + 17AAG, indicating that these increases in probe oxidation were only the result of 17AAG treatment. These data by themselves do not logically account for the increased toxicity observed by the 2DG + 17AAG combination, versus 17AAG alone. However, these data do not rule out a potential role for either superoxide or hydrogen peroxide, as the data merely reflect the steady-state levels of each chemical species, and they give no indication of their potential flux in the system before or after the labeling interval. Therefore, the roles of superoxide and hydrogen peroxide were interrogated more specifically by antioxidant treatment, in an attempt to protect from the drug toxicity. If superoxide or hydrogen peroxide were somehow causal to the toxicity of the 2DG and 17AAG combination, then it stood to reason that enzymatic scavengers of these compounds should then be able to rescue from the toxicity of 2DG and 17AAG, when given simultaneously with drug treatment. Thus, MDA-MB-231 cells were then treated with 20 mm 2DG and 500 nm 17AAG and then either 100 U/mL PEG-catalase or 18 μm PEG (Fig. 13). Alternatively to treatment with PEG compounds, cells were transduced via adenoviral vector with 50 MOI AdMnSOD + 50 MOI AdMitoCat or 100 MOI AdEmpty, prior to 2DG and 17AAG treatment (Fig. 13, see Materials and Methods). Following drug treatment, cells were then assayed for clonogenic cell survival. Neither PEG-Catalse, or adenovirus-catalase or adenovirus-sod were capable of protecting against 2DG and 17AAG induced cytotoxicity in these experiments. Attempts to further delineate the role of ROS metabolism in the drug interaction were accomplished by treating SUM159 cells with 20 mm 2DG, 100 μm BSO, and 500

93 74 nm 17AAG for 24 h and then 100 nm AUR for the last 15 minutes of drug treatment. Drug treated cells were then supplemented with either 100 U/mL PEG-SOD and 100 U/mL PEG-catalase, vehicle control (36 μm PEG), 15 mm NAC, or vehicle control during the 24 h drug treatment (Fig. 14) and analyzed for clonogenic cell survival following drug treatment. Results showed that treatment with PEG SOD and PEG Catalase were not able to significantly increase SUM159 cell survival after BSO and AUR treatment nor after 2DG, BSO, AUR, and 17AAG treatment. It is important to note though that the absence of an effect by PEG-SOD and PEG-catalase may be attributed to the fact that, when later assayed for activity, SUM159 cells treated with PEG-SOD and PEG-Catalase showed no statistically significant increase in intracellular SOD or catalase activity, compared to SUM159 cells treated with only PEG alone (Data not shown). Therefore, the absence of an effect by PEG-SOD and PEG-catalase may be most easily explained by PEG-SOD and PEG-catalase not being able to get inside the cell. In order to investigate what role cell signaling may play in the drug interactions, MDA-MB-231 cells were treated 20 mm 2DG and 500 nm 17AAG and then either (1 or 10 μm) SP or 25 μm LY for 24 h, prior to being assayed for clonogenic cell survival (Fig. 15). Treatment with SP and LY appeared to be ineffective at changing cell survival in response to 2DG and 17AAG treatment. Compounds were dosed at levels previously shown to cause inhibition of JNK and Akt activity; however, specific knockdown of kinase activity was not assayed, following treatment with the kinase inhibitors. Therefore, these data must be interpreted cautiously, as it is possible that JNK and Akt activity were not affected by either of these pharmacological manipulations. Additionally, pharmacological kinase inhibitors are

94 75 known to have off-target effects, non-specificity, and suffer from the potential for drug inactivation. Regardless, the lack of effect on cell survival, following treatment with 2DG, 17AAG, and SP or LY was interpreted as suggesting that JNK and Akt may not be involved in the 2DG and 17AAG drug toxicity interaction. Because of the inherent difficulty and uncertainty that come from using pharmacological inhibitors, the work in this study was not followed-up, and was instead shifted toward ASK-1, which would be targeted using a more sophisticated molecular biology approach, using sirna. It was hypothesized that if ASK-1 activation was causal to the drug toxicity then its knockdown or inactivation should ameliorate the toxic effects caused by 2DG and 17AAG treatment. To test this hypothesis, ASK-1 was then knocked down in MDA-MB- 231 cells using sirna technology (see Materials and Methods). Cells were then treated with 20 mm 2DG and 500 nm 17AAG for 24 h and then assayed for their clonogenic cell survival. Data from Western blotting suggested that ASK-1 knockdown was achieved in the transfected cells without causing toxicity (Fig. 16). However, survival data (Fig. 17) suggested that ASK-1 knockdown enhances cell killing in response to the 2DG and 17AAG combination -- a result which was at odds with the initial hypothesis leading into the experiment (Fig. 17). This result will be discussed in further detail in the following section. Discussion DHE oxidation was not significantly enhanced following 2DG and 17AAG treatment in MDA-MB-231 cells, and, although CDCFH 2 oxidation was increased following either treatment with 17AAG or the 2DG and 17AAG combination, this increased level of CDFCH 2 oxidation did not appear to correlate to the observed

95 76 increases in toxicity caused by the 2DG and 17AAG combination in MDA-MB-231 cells, but the oxidant responsible for changes in oxidation was not identified. Additionally, PEG-catalase did not rescue from 2DG and 17AAG-induced toxicity and neither PEG- SOD or PEG-catalase treatment appeared to be capable of rescuing cells from 2DG, BSO, AUR, and 17AAG-induced cytotoxicity. The lack of rescue of clonogenic survival in the PEG-SOD and PEG-catalase conditions in SUM159 cells could be explained by these compounds not being capable of entering the cell in the compartments where superoxide or hydrogen peroxide were being produced. Therefore, the role of superoxide or hydrogen peroxide, though less likely for the 2DG + 17AAG combination, remains an open question for the BSO + AUR treatment combinations. Data from the cell signaling studies suggested that JNK, Akt, and ASK-1 did not appear to play a direct role in 2DG and 17AAG-mediated cytoxicity in MDA-MB-231 cells. Both pharmacological inhibitors of JNK and Akt were shown to be unable to alter clonogenic survival following 2DG and 17AAG treatment. This implies that either the pharmacological agents were unable to alter JNK or Akt activity or that these cell signaling kinases were simply uninvolved or unaffected by these drugs in this system. Data from the ASK-1 knockdown studies suggested that ASK-1 may be related to 2DG and 17AAG toxicity, but this relationship is still unclear. It was hypothesized that knockdown of the ASK-1 protein should have protected the cells from death, by inhibiting the pro-apoptotic functions of ASK-1. However, clonogenic cell death actually appeared to be increased in the 2DG and 17AAG combination treatment following ASK- 1 knockdown. This result has several interpretations. One hypothesis is that the cells undergoing 2DG and 17AAG treatment may enter apoptosis, shrink, therefore not not be

96 77 counted in the clonogenic cell survival assay. Thus, it is possible that cells (destined to die from 2DG and 17AAG treatment) could be protected from an apoptotic death, via the knockdown of ASK-1, counted and plated for clonogenic cell survival and then die a reproductive, mitotic, or necrotic death, which would conflate the cell death numbers produced by a clonogenic cell survival assay which is normalized to cell size particles. In agreement with this hypothesis, cell number per plate did appear to be higher, following 2DG and 17AAG treatment, in cells treated with ASK-1 sirna versus cells treated with scrambeled sirna; however, because this experiment was performed only once, and cannot be statistically validated. Further studies will be necessary to resolve these issues to fully understand the role of ASK-1 in the observed effects. As an alternative hypothesis, it has also been suggested that, in certain situations, ASK-1 can have pro-survival effects [141]. In particular, it is thought that early and transient activation of JNK may correlate with survival, whereas late and prolonged activation of JNK may correlate with increased apoptosis. Also, it is thought that if ASK-1 is activating p38, with little to no activation of JNK, this signal can induce differentiation, and potentially survival. This could explain why increased cell killing was observed, following ASK-1 knockdown in this cell line. In the event that ASK-1 to p38 signaling was more dominant in MDA-MB-231 cells, than ASK-1 activation of JNK, then the activity of ASK-1 could contribute to pro-survival signaling. Whether or not these signaling scenarios are present in MDA-MB-231 cells, however, is currently unknown. In conclusion, the collective results of this study suggest that superoxide or hydrogen peroxide are less likely to play a role in the 2DG + 17AAG combination, but

97 78 their role in the 2DG + BSO + AUR + 17AAG, combination is still uncertain. Additionally, this study found that neither JNK signaling, Akt signaling, nor ASK-1 signaling were casual to the drug toxicity induced by 2DG, BSO, AUR, and 17AAG treatment in MDA-MB-231 or SUM159 cells. Data from previous studies supports the notion that disruptions to glutathione and thioredoxin metabolism were casual to 2DG, BSO, AUR, and 17AAG toxicity, but data from this study add to this model only by suggesting that the ASK-1 cell signaling pathways does not appear to add to the chemotherapy-mediated cancer cell killing caused by 2DG, BSO, AUR, and 17AAG combination. The mechanism of toxicity, induced by these drug treatments as far as cell signaling is cocerned, therefore remains largely unknown. These results could suggest that other, more non-specific disruptions to thiol metabolism may be involved in the 2DG, BSO, AUR, and 17AAG drug interaction, and that other thiol systems (such as peroxiredoxin metabolism) be investigated in the future, in order to delineate a more concrete mechanism for the toxicity caused by the 2DG, BSO, AUR, and 17AAG treatments.

98 79 Figure 12: CDCFH 2 and DHE oxidation in response to drug treatment. CDCFH2 (A) and DHE (B) fluorescence was measured via flow cytometry in MDA-MB-231 cells following treatment with 20 mm 2DG and 500 nm 17AAG for 24 h. The data represent mean fluorescent intensity (MFI), per cell, normalized to control cells + SD. * = p < 0.05 versus control cells, as determined by One-way ANOVA, using Tukey s post-hoc test.

99 80

100 81 Figure 13: AdMnSOD, AdMitoCat, and PEG-Catalase were ineffective at protecting MDA-MB-231 cells from 2DG and 17AAG toxicity. (A) Cells were plated and allowed to grow for 24 h, and then treated with 100 MOI of adenovirus empty vector or 50 MOI of adenovirus-mnsod and 50 MOI of adenovirus-mitochondrially targeted catalase. Cells were then allowed to grow for 24 h, reaching exponential growth, and were then treated with 20 mm 2DG and 500 nm 17AAG for 24 h. (B) Cells were plated and allowed to grow for 48 h, reaching exponential growth, and were then treated with 20 mm 2DG, 500 nm 17AAG, and 100 U/mL PEG-catalase or 18 µm PEG alone for 24 h. In both cases, following 2DG and 17AAG treatment, cells were then assayed for clonogenic cell survival. Data shown represent normalized surviving fraction (relative to non-transduced control (A) or untreated control (B)) + SD. * = p < 0.05 versus the same treatment without 2DG or 17AAG added, as determined by One-way ANOVA, using Tukey s post-hoc test for significance. One-way ANOVA, using Fisher s LSD post-hoc test for significance, did not find any other differences between groups that were statistically significant.

101 82

102 83 Figure 14: PEG-SOD and PEG-catalase treatments are unable to protect SUM159 cells from 2DG, 17AAG, BSO, and AUR induced cytotoxicity. SUM159 cells were treated with 20 mm 2DG, 500 nm 17AAG, and 100 µm BSO for 24 h and then 100 nm AUR for the last 15 min of drug treatment. During the 24 h drug treatment cells were also incubated with either 100 U/mL PEG SOD and 100 U/mL PEG Catalase (PEG CAT), vehicle control (36 µm PEG Alone), 15 mm NAC, or no vehicle control (No PEG, data not shown) for 24 h. Following drug treatment, cells were then assayed for clonogenic survival. Normalized surviving fraction, as determined by a clonogenic cell survival assay, was determined, and average normalized surviving fraction + SD is shown for each group. Data are from two independent experiments, containing three clonogenic survival plates per treatment condition per experiment. * = p < 0.05, as determined by One-way ANOVA, using Tukey s post-hoc test.

103 84

104 85 Figure 15: Pharmacological inhibitors of Akt and JNK signaling were ineffective at modifying cytotoxic responses to 2DG and 17AAG treatment. MDA-MB-231 cells were treated with 20 mm 2DG and 500 nm 17AAG and then either 100 μm LY (PI3K/Akt Inhibitor) or 1 or 10 μm SP (JNK Inhibitor) for 24 h. Following drug treatment, cells were then assayed for clonogenic survival. Data shown represent normalized surviving fraction + SD. One-way ANOVA, using Fisher s LSD post-hoc analysis did not find any significant difference between any treatment condition, with or without cell signaling inhibitors. Data in panel A are from one experiment; data from panel B are from two experiments.

105 86

106 87 Figure 16: Treatment with ASK-1 sirna did not change clonogenic survival plating efficiency. MDA-MB-231 cells were plated and allowed to grow for 48 h, reaching exponential growth. Cells were then treated with either scrambled or ASK-1 sirna (see Materials and Methods). Cells were then allowed to grow for 72 h. Cells were then either trypsinized and assayed for clonogenic survival or scraped and harvested for a western blot against ASK-1 protein levels. Clonogenic survival data from one experiment, containing three clonogenic survival plates per treatment condition, 72 h after sirna exposure is shown. Data shown represent normalized surviving fraction + SD. A plate from each treatment group was used to assay for sirna knockdown of ASK-1 via immunoblot. This data is shown in Fig. 17D.

107 88

108 89 Figure 17: ASK-1 sirna treatment knocked down ASK-1 protein expression but failed to sensitize cancer cells to 2DG and 17AAG treatment in the presence or absence of BSO and AUR. MDA-MB-231 cells were plated and grown for 48 h, until reaching exponential growth, and then were treated with sirna constructs (see Materials and Methods). Cells were either treated with scrambled sirna (Sc sirna) or sirna specific to ASK-1 (ASK-1 sirna). Cells were allowed to incubate for 72 h, then MDA- MB-231 cells were treated with (A) 20 mm 2DG and 500 nm 17AAG for 24 h or (B) 1 mm BSO for 24 h and either 500 nm or 100 nm AUR for the last 3 h of drug treatment, prior to all cells then being assayed for clonogenic cells survival. Data shown represent normalized surviving fraction + SD. No treatment condition was significantly different with respect to the Sc sirna versus ASK-1 sirna treatment. Control plates from each sirna transfection condition were obtained for each experiment and samples were processed for immunoblotting against ASK-1 protein expression, shown in (C) and (D). (C) was performed using samples from experiment (A) and (D) was performed using samples from experiment (B). Each panel is representative of data from one experiment each, with three clonogenic plates per treatment condition.

109 90