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Altered metabolism of daunorubicin and doxorubicin by genetic variants of human aldo-keto and carbonyl… Bains, Onkar Singh 2010

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  ALTERED METABOLISM OF DAUNORUBICIN AND DOXORUBICIN BY GENETIC VARIANTS OF HUMAN ALDO-KETO AND CARBONYL REDUCTASES   by   Onkar Singh Bains   M.E.T., Simon Fraser University, 2004 B.Sc. (Biology), Simon Fraser University, 2001     A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF   DOCTOR OF PHILOSOPHY   in   The Faculty of Graduate Studies  (Pharmaceutical Sciences)   THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   October 2010    © Onkar Singh Bains, 2010     ii ABSTRACT  The anthracyclines, doxorubicin (DOX) and daunorubicin (DAUN) are commonly used to treat a variety of cancers.  Their use is associated with life-threatening adverse events, especially chronic cardiotoxicity, in some patients.  There may be a genetic basis for this variation, arising from altered metabolism by non-synonymous single nucleotide polymorphisms (ns-SNPs) in genes encoding for the aldo-keto reductase (AKR) and carbonyl reductase (CBR) enzymes, which are responsible for the biotransformation of these two drugs. The first two studies (Chapters 2 and 3) of this thesis examined the effect of ns- SNPs in 8 AKR and 3 CBR genes on the in vitro metabolism of both anthracyclines to their major metabolites, doxorubicinol (DOXol) and daunorubicinol (DAUNol) using purified, human wild-type and genetic variant enzymes.  Michaelis-Menten kinetic curves were plotted and the metabolic capacities of the wild-type and variant enzymes were compared using catalytic efficiency (kcat/Km).  In the presence of DAUN, 7 AKR and 5 CBR variants exhibited significantly reduced metabolic activity while 3 AKR and 5 CBR variants demonstrated significantly reduced activity with DOX as substrate.  These findings suggest that genetic variants of human AKRs and CBRs are capable of decreasing the in vitro metabolism of DOX and DAUN. There is considerable controversy in the literature on how DAUN and DOX contribute to the variable adverse events seen in patients treated with these drugs.  Some studies suggest that the toxic species are the major metabolites, DAUNol and DOXol, while others suggest the parent drug is more toxic.  To study this, I examined whether a strong and consistent association exists between metabolic activity and drug toxicity among nine cell lines from different tissues (Chapter 4).  My findings indicated that there  iii is a strong, and inversely proportional, association between cytotoxicity and DAUN or DOX metabolism.  Furthermore, the cell lines that were resistant to the toxic effects of these drugs had significantly greater expression of the AKRs and CBRs. Overall, these data provide a foundation of biochemical evidence to design in vivo studies that will elucidate the role of altered metabolism by genetic variants of human AKRs and CBRs in the development of anthracycline-induced cardiotoxicity.                                     iv TABLE OF CONTENTS  ABSTRACT........................................................................................................................ ii TABLE OF CONTENTS................................................................................................... iv LIST OF TABLES............................................................................................................ vii LIST OF FIGURES ........................................................................................................... ix LIST OF ABBREVIATIONS.......................................................................................... xiii ACKNOWLEDGEMENTS............................................................................................. xvi DEDICATION............................................................................................................... xviii PREFACE........................................................................................................................ xix Co-authorship............................................................................................................... xix Publications arising from work presented in this thesis................................................ xx  CHAPTER 1: Overview ..................................................................................................... 1 1.1 Anthracyclines—chemical structure and mechanism of action.......................... 2 1.2 DAUN and DOX—their use in cancer treatment and cardiac side effects......... 4 1.3 Proposed mechanisms of DAUN/DOX-induced cardiotoxicity......................... 9 1.4 The phases of biotransformation and DOX/DAUN metabolism...................... 13 1.5 Aldo-keto reductases and carbonyl reductases ................................................. 20 1.6 Genetic polymorphisms in genes producing drug metabolizing enzymes........ 24 1.7 Rationale ........................................................................................................... 34 1.8 Research hypotheses and predictions................................................................ 35  CHAPTER 2: Altered metabolism of daunorubicin and doxorubicin by allelic variants of human aldo-keto reductases.............................................................................................. 38 2.1 Preface............................................................................................................... 38 2.2 Materials and Methods...................................................................................... 42 2.2.1 Chemicals and enzymes............................................................................ 42 2.2.2 Molecular cloning of human AKR genes and creation of allelic variants 43 2.2.3 Expression and purification of recombinant human AKR wild-type and variant enzymes ........................................................................................ 47 2.2.4 Rate of enzymatic activity of AKRs in presence of test substrates .......... 50 2.2.5 Kinetic activity of AKR enzymes in the presence of anthracyclines........ 51 2.2.6 Statistical analysis..................................................................................... 53 2.3 Results............................................................................................................... 53 2.3.1 Expression and purification of the AKR enzymes.................................... 53 2.3.2 Enzyme activities of AKR wild-type and variant enzymes using test substrates................................................................................................... 55 2.3.3 Kinetic characterization of wild-type and variant enzymatic activities with DOX and DAUN as substrates ................................................................. 59 2.4 Discussion ......................................................................................................... 68  CHAPTER 3: Allelic variants of human carbonyl reductases demonstrate reduced in vitro metabolism of daunorubicin and doxorubicin .................................................................. 76 3.1 Preface............................................................................................................... 76 3.2 Methods............................................................................................................. 79 3.2.1 Chemicals and enzymes............................................................................ 79  v 3.2.2 Molecular cloning of human CBR genes and creation of the genetic variants...................................................................................................... 80 3.2.3 Expression and purification of recombinant human CBR wild-type and variant enzymes ........................................................................................ 82 3.2.4 Kinetic analysis of CBR wild-type and variant enzymes ......................... 84 3.2.5 Statistical analysis..................................................................................... 85 3.3 Results............................................................................................................... 86 3.3.1 Expression and purification of the human CBRs...................................... 86 3.3.2 Kinetic characterization of CBR wild-type and variant enzymatic activities with menadione......................................................................................... 87 3.3.3 Kinetic characterization of wild-type and variant enzymatic activities with DOX and DAUN....................................................................................... 91 3.4 Discussion ......................................................................................................... 96  CHAPTER 4: Ex vivo and in vitro studies suggest a negative association between cytotoxicity and metabolism of the anthracyclines daunorubicin and doxorubicin by aldo- keto and carbonyl reductases .......................................................................................... 103 4.1 Preface............................................................................................................. 103 4.2 Methods........................................................................................................... 106 4.2.1 Chemicals and enzymes.......................................................................... 106 4.2.2 Cell culture.............................................................................................. 106 4.2.3 MTT cell viability assay to measure cytotoxicity................................... 107 4.2.4 DAUN and DOX metabolic assays with cytosolic fractions derived from cell lines .................................................................................................. 108 4.2.5 Instrumentation and experimental conditions for UPLC-MS/MS.......... 109 4.2.6 Western blotting of cytosols to detect AKRs and CBRs ........................ 111 4.2.7 Statistical analysis................................................................................... 112 4.3 Results............................................................................................................. 113 4.3.1 Cytotoxicity of cells following exposure to anthracyclines.................... 113 4.3.2 Metabolism of the anthracyclines using cell line cytosols...................... 116 4.3.3 Expression of cytosolic AKRs and CBRs in cell lines ........................... 118 4.3.4 Increase in DAUN/DOX metabolism and induction of AKR and CBR gene expression are responses in cell lines following exposure to anthracycline drugs ................................................................................. 121 4.3.5 Association between cytotoxicity and DOX/DAUN metabolism in cell lines exposed to these anthracyclines ..................................................... 127 4.3.6 UPLC-MS/MS method validation .......................................................... 127 4.4 Discussion ....................................................................................................... 131  CHAPTER 5: Overall summary and conclusions........................................................... 137 5.1 Novel findings................................................................................................. 137 5.2 Implications of findings .................................................................................. 139 5.3 Potential limitations of research...................................................................... 141 5.3.1 The use of a bacterial expression system for the in vitro studies............ 141 5.3.2 Focusing solely on the polymorphisms in the coding regions of the AKR and CBR genes........................................................................................ 145  vi 5.3.3 Allele frequencies for two variants are not reported in the NCBI database .  ................................................................................................................. 146 5.4 Suggested future research directions .............................................................. 146 5.4.1 Biochemical investigations ..................................................................... 147 5.4.2 Cancer patient correlation studies to determine if AKR and CBR variant alleles are genetic biomarkers of cardiotoxicity arising from DAUN/DOX therapy..................................................................................................... 153  REFERENCES ............................................................................................................... 157 APPENDICES ................................................................................................................ 180                                       vii LIST OF TABLES  Table 1—The human AKR proteins within the AKR1, AKR6, and AKR7 families identified in the AKR Superfamily website along with the location of the gene in the chromosome...................................................................................................................... 21  Table 2—The human CBR proteins along with the location of the gene in the chromosome...................................................................................................................... 23  Table 3—A summary of studies that looked at the effect of ns-SNPs in genes for different drug metabolizing enzymes. ............................................................................................. 31  Table 4—Allele frequencies of the non-synonymous single nucleotide polymorphic variants of human AKR enzymes from different ethnic groups. ...................................... 40  Table 5—Enzymatic rates for reported test substrates by recombinant 6x-His tagged AKR wild-type and variant allele enzymes. ..................................................................... 56  Table 6—Kinetic constants for DAUN metabolism by recombinant 6x-His tagged AKR wild-type and variant enzymes. ........................................................................................ 64  Table 7—Kinetic constants for DOX metabolism by recombinant 6x-His tagged AKR wild-type and variant enzymes. ........................................................................................ 67  Table 8—Allele frequencies of the non-synonymous single nucleotide polymorphic variants of human CBR enzymes from different ethnic groups. ...................................... 78  Table 9—Michaelis-Menten kinetic parameters for test substrate menadione by recombinant 6x-His tagged CBR wild-type and variant allele enzymes. ......................... 89  Table 10—Kinetic constants for DAUN metabolism by recombinant 6x-His tagged CBR wild-type and variant enzymes. ........................................................................................ 94  Table 11—Kinetic constants for DOX metabolism by recombinant 6x-His tagged CBR wild-type and variant enzymes. ........................................................................................ 95  Table 12—Mean LC50 values of DAUN and DAUNol for cell lines at specified time intervals following exposure to the drug. ....................................................................... 115  Table 13—Mean LC50 values of DOX and DOXol for cell lines at specified time intervals following exposure to the drug. ...................................................................................... 116  Table 14—Results for accuracy and precision (intra-day and inter-day) for the UPLC- MS/MS determinations of DOXol and DAUNol in pooled matrix of nine cell lines (days 1 to 3).. ............................................................................................................................ 130   viii Table 15—Enzymatic rates for reported test substrates by recombinant 6x-His tagged AKR wild-type along with kinetic parameters for CBR1 wild-type in the presence of menadione. ...................................................................................................................... 145  Table 16—Allele frequencies of the non-synonymous single nucleotide polymorphic variants of human AKR enzymes from different ethnic groups. .................................... 147                                           ix LIST OF FIGURES  Figure 1—Chemical structure of an anthracycline illustrating the fused tetracycline ring (denoted by A, B, C, and D) as as well the daunosamine sugar. ........................................ 2  Figure 2—Chemical structures of (A) DOX and (B) DAUN. ............................................ 5  Figure 3—Chemical structures of anthracycline analogs epirubicin, idarubicin, and aclarubicin........................................................................................................................... 8  Figure 4—DOX-related redox cycling generation of ROS and reactive nitrogen species (RNS) by cellular enzymatic mechanisms........................................................................ 12  Figure 5—A simplified overview illustrating Phase I, II, and III metabolism of aspirin occurring in a cell.............................................................................................................. 14  Figure 6—Schematic representative of DOX metabolism.. ............................................. 17  Figure 7—The location of AKRs and CBRs within all existing categories of metabolic enzymes............................................................................................................................. 19  Figure 8—Schematic representations of the different human genetic polymorphisms: missense, nonsense, insertion, deletion, duplication and frameshift. ............................... 26  Figure 9—A schematic representation of a gene comprised of exons and introns, as well as other regulatory regions of DNA that control gene expression (promoter, silencer and enhancer)........................................................................................................................... 28  Figure 10—(Top) Michaelis-Menten kinetic curve plotting metabolic reaction activity rate against substrate concentration.  (Bottom) Kinetic parameter values and how they are affected with low and high metabolizing enzymes........................................................... 30  Figure 11—A translated product of the pET28a-AKR1A1 construct with modifications to the amino terminus of AKR1A1: a 6x-His-tag followed by an amino acid linker and a Factor Xa (FXa) recognition site. ..................................................................................... 43  Figure 12—Interaction between neighboring histidine residues in the 6x-His tag and the nickel-nitrilotriacetic acid (Ni-NTA) matrix .................................................................... 49  Figure 13—Purification of human recombinant 6x-His-tagged wild-type enzymes: (A) AKRA1, (B) AKR1B1, (C) AKR1B10, (D) AKR1C1, (E) AKR1C2, (F) AKR1C3, (G) AKR1C4, and (H) AKR7A2............................................................................................. 54  Figure 14—Representative Western blot detection of purified 6x-His tagged AKR proteins [(A) AKR1C3, (B) AKR1C4, and (C) AKR7A2 wild-type enzymes; lane 2; 3 µg] and native AKR proteins. ........................................................................................... 58   x Figure 15—Generation of DAUNol and DOXol in vitro by purified AKR incubated with DOX (top panel) and DAUN (bottom panel).. ................................................................. 61  Figure 16—In vitro enzymatic activities for the purified 6x-His tagged (A) AKR1A1, (B) AKR1B1, (C) AKR1B10, (D) AKR1C1, (E) AKR1C2, (F) AKR1C3, (G) AKR1C4, and (H) AKR7A2 wild-type and variant enzymes with daunorubicin. ................................... 63  Figure 17—In vitro enzymatic activities for the purified 6x-His tagged (A) AKR1A1, (B) AKR1B1, (C) AKR1B10, (D) AKR1C1, (E) AKR1C2, (F) AKR1C3, (G) AKR1C4, and (H) AKR7A2 wild-type and variant enzymes with doxorubicin ...................................... 66  Figure 18—Three-dimensional molecular structures of human (A) AKR1A1, (B) AKR1C3, (C) AKR1C4, and (D) AKR7A2 wild-type enzymes.. .................................... 71  Figure 19—Proposed catalytic mechanism for AKR-mediated reduction reaction [modified based on the scheme provided by Barski et al. (2008)] ................................... 72  Figure 20—A translated product of the pET28a-CBR1 construct with modifications to the amino terminus of AKR1A1: a 6x-His-tag followed by an amino acid linker and a Factor Xa (FXa) recognition site ...................................................................................... 81  Figure 21—Purification of human recombinant 6x-His-tagged wild-type enzymes: (A) CBR1, (B) CBR3, and (C) CBR4. .................................................................................... 87  Figure 22—Representative Western blot detection of purified 6x-His tagged CBR proteins [(A) CBR1, (B) CBR4, and (C) CBR4 wild-type enzymes] and native AKR proteins.............................................................................................................................. 91  Figure 23—Generation of DOXol and DAUNol in vitro by purified CBR3 incubated with DOX (top panel), and purified CBR1 incubated with DAUN (bottom panel). ................ 92  Figure 24—In vitro enzymatic activities for the purified 6x-His tagged (A) CBR1, (B) CBR3, and (C) CBR4 wild-type and variant enzymes with daunorubicin ....................... 93  Figure 25—In vitro enzymatic activities for the purified 6x-His tagged (A) CBR1, (B) CBR3, and (C) CBR4 wild-type and variant enzymes with with doxorubicin................. 95  Figure 26—Three-dimensional molecular structure of human (A) CBR1 and (B) CBR3 wild-type enzymes complexed with the cofactor, NADP+ (green) [Protein Data Bank ID: 3BHI (CBR1) and 2HRB (CBR3)]. .................................................................................. 99  Figure 27—A proposed catalytic mechanism for CBR-mediated reduction reaction (see text for details) ................................................................................................................ 100  Figure 28—Representative UPLC-MS/MS chromatogram of doxorubicin, doxorubicinol, daunorubicin, daunorubicinol, and idarubicin. ............................................................... 111   xi Figure 29—Sample dose-response curves of (A) H9c2 rat heart cell line and (B) HepG2 liver cell line in the presence of varying concentrations of daunorubicin (DAUN), doxorubicin (DOX), daunorubicinol (DAUNol), and doxorubicinol (DOXol) following a 48 hr incubation. ............................................................................................................. 114  Figure 30—Enzymatic activities for rat and human cell line cytosols incubated with 10 µM of daunorubicin (A) and doxorubicin (B). ............................................................... 117  Figure 31—Western blot detection of the sensitive cell line cytosols (lane 1: heart, lane 2: prostate, lane 3: ovary, lane 4: pancreas, and lane 5: breast) as well as the resistant cell line cytosols (lane 6: liver, lane 7: colon, lane 8: lung, lane 9: kidney) confirms expression of the desired AKR and CBR proteins.......................................................... 119  Figure 32—Relative expression ratio levels of AKR and CBR proteins in the sensitive (heart, prostate, ovary, pancreas, and breast) as well as the resistant cell line cytosols (liver,colon, lung, and kidney). ....................................................................................... 120  Figure 33—The metabolic activity rates (measured as pmol DAUNol or DOXol/minute•mg total protein) of cytosols that were extracted from cell lines treated with 100 nM DAUN (A) and DOX (B) after 0, 6, 24, and 48 hr exposure time periods.. ......................................................................................................................................... 123  Figure 34—Sample Western blot analyses (A) of cytosols from H9c2 rat heart and HCT- 15 human colon carcinoma cell lines for purposes of assessing induction of AKR1C3 and CBR1 after 0, 6, 24, and 48 hr exposure to either 100 nM DAUN or DOX.  Densitometry was performed on the immunoreactive bands and normalized against β-tubulin (loading control) in order to calculate relative expression ratios.  With the DOX-treated cell lines, the relative expression ratios for AKR1C3 (B) and CBR1 (C) indicate significant induction (*, p<0.05) in cytosols treated for 24 and 48 hrs.  These results were similar for the DAUN-treated cell lines............................................................................................ 126  Figure 35—Scatterplot of cytotoxicity (LC50 values) and metabolic activity following DAUN (A) and DOX (B) treatment in the nine cell lines for the purposes of seeing if there is an association between these two variables for 6, 24, and 48 hr incubations. ... 127  Figure 36—Bar graphs illustrating the relative abundance of the cytosolic AKRs and CBRs in human heart lysate (H) and pooled human liver lysate (L).  The relative abundance values of the individual reductases are ordered from highest to lowest kcat/Km values towards DAUN (A) and DOX (B), which were determined from the in vitro studies with the recombinant enzymes.  The reductase enzymes in boxes represent those with variants that significantly reduce DAUN or DOX metabolism compared to their respective wild-type enzymes.  (Below bar graphs) Lysates (20 µg total protein) were run on 18% SDS-PAGE gels and subjected to Western blotting for detection of AKR1A1, AKR1B1, AKR1B10, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR7A2, CBR1, and CBR3 proteins................................................................................................................. 133    xii Figure 37—Purification of human recombinant 6x-His-tagged wild-type enzymes for Sf9 insect cells: (1) AKRA1, (2) AKR1B1, (3) AKR1B10, (4) AKR1C2, (5) AKR1C4, (6) AKR7A2, and (7) CBR1................................................................................................. 144  Figure 38—A spin trapping chemical reaction in which 5-Diethoxyphosphoryl-5-methyl- 1-pyrroline N-oxide (DEPMPO), the spin trapping agent, reacts with a free radical to form a radical adduct that is more stable than the initial radical (Swartz et al., 2007)... 150  Figure 39—EPR spectra of the positive and negative controls assays using DEPMPO. For the positive control assay (xanthine/xanthine oxidase), the spectra representing the DEPMPO-superoxide spin adduct is given in red while the negative control (no DEPMPO) is represented in blue.................................................................................... 151                                     xiii LIST OF ABBREVIATIONS  6x-His  Six histidine oC  Degree Celsius xg  Times gravity (centrifugal force) α  Alpha β  Beta µg  Microgram µl  Microlitre µM  Micromolar A  Adenine ABC   ATP-binding cassette ACN  Acetonitrile AKR  Aldo-keto reductase ANOVA Analysis of variance C  Cytosine CBR  Carbonyl reductase CE  Collision energy C.I.  Confidence interval C.V.  Coefficient of variation CYP  Cytochrome-P450 DAUN  Daunorubicin DAUNol Daunorubicinol dB  Decibel DEPMPO 5-Diethoxyphosphoryl-5-methyl-1-pyrroline N-oxide DMSO  Dimethyl sulfoxide DNA  Deoxyribonucleic acid DOX  Doxorubicin DOXol Doxorubicinol E. coli  Escherichia coli EPR Electrón paramagnetic resonance g   Gram G  Guanine GHz  Gigahertz H2O2  Hydrogen peroxide HPLC  High performance liquid chromatography hr   Hour Hz  Hertz i.d.  Internal diameter IPTG  Isopropyl β-D-thiogalactopyranoside k  Kilo kDa  Kilodalton kcat  Substrate turnover rate kcat/Km  Catalytic efficiency Km Substrate affinity – the substrate concentration at which the reaction rate reaches half of its maximum value kHz  Kilohertz  xiv kV  Kilovolt KH2PO4 Potassium dihydrogen phosphate LC50  Lethal Concentration 50—the concentration which causes 50% death LOQ  Limit of quantitation m   Metre M  Molar (mole/litre) ml   Millilitre mM  Millimolar min  Minute MRM  Multiple reaction monitoring MS/MS Tandem mass spectrometry msec  Millisecond MTT  3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide m/z  Mass to charge ratio n  Number of subjects or samples N/A  Not available NADP+ β-Nicotinamide adenine dinucleotide phosphate NADPH β-Nicotinamide adenine dinucleotide phosphate, reduced form NaH2PO4 Sodium dihydrogen phosphate NCBI  National Centre for Biotechnology Information nM  Nanomolar nmol  Nanomole ns-SNP Non-synonymous single nucleotide polymorphism ·O2-  Superoxide anion ·OH   Hydroxyl radical p  Statistical probability (of obtaining a result at least as extreme as the one that was observed) PBS  Phosphate-buffered saline PCR  Polymerase chain reaction pH  Negative logarithm of hydrogen ion concentration pmol  Picomole POR  Cytochrome P450 reductase QC  Quality control r  Corelation coefficient r 2   Coefficient of determination ROS  Reactive oxygen species s  second S.D.  Standard deviation SDR  Short-chain dehydrogenases/reductase SDS-PAGE Sodium dodecyl sulphate polyacrylamide gel electrophoresis sec  Second SNP  Single nucleotide polymorphism T  Thymine TIC  Total ion current U  Uracil UPLC  Ultra-high performance liquid chromatography V  Volt  xv v/v  Volume to volume ratio Vmax  Maximal rate of velocity W  Watt  Amino acid one letter abbreviations  A  Alanine (Ala) C  Cysteine (Cys) D  Aspartic acid (Asp) E  Glutamic acid (Glu) F  Phenylalanine (Phe) G  Glycine (Gly) H  Histidine (His) I   Isoleucine (Ile) K  Lysine (Lys) L  Leucine (Leu) M  Methionine (Met) N  Asparagine (Asn) P   Proline (Pro) Q  Glutamine (Gln) R  Arginine (Arg) S  Serine (Ser) T  Threonine (Thr) V   Valine (Val) W  Tryptophan (Trp) Y  Tyrosine (Tyr)  Variant nomenclature (using two variants of AKR1A1 as an example) N52S  A change from asparagine to serine at amino acid position 52 E55D  A change from glutamic acid to aspartic acid at amino acid position 55  NCBI population groups  CEU   Utah residents with ancestry from northern and western Europe, collected by Centre d'Etude du Polymorphisme Humain (CEPH) CHB   Han Chinese in Beijing, China JPT   Japanese in Tokyo, Japan YRI   Yoruba in Ibadan, Nigeria HSP  Hispanic PRH   Pacific Rim Heritage UFV   Combination of residents from Utah, as well as French and Venezuelan X   Combined population from Michigan along with UFV MITO  MITOGPOP6: combination of Caucasian, Japanese, Chinese, Amerindian, Pygmy, Russian, etc.  xvi ACKNOWLEDGEMENTS  First of all, I owe my deepest gratitude to my principal supervisor, Dr. K. Wayne Riggs, for accepting me as his graduate student in this project, which focused on an area that was vastly different from my background in biology and environmental toxicology.  I will never forget the encouragement and support he provided during my tenure as a Ph.D. student.  Thank you to my co-supervisor, Dr. Ronald E. Reid, and Dr. Thomas A. Grigliatti for their constructive feedback during lab meetings, professional attitude, and guiding me to becoming a better critical thinker in science.  In addition, this thesis would not have been possible without the expert advice and amazing support by my supervisory committee members, Dr. Judy Wong, Dr. Pierre Kennepohl, and Dr. Stelvio Bandiera. I am forever grateful to Dr. Tom Pfeifer, Dr. Ryan H. Takahashi, Dr. Joanna M. Lubieniecka, and Dr. Randy Mottus for their valuable advice on ways to strengthen my research project and teaching me scientific techniques in molecular biology. Furthermore, it is an honor for me to have worked with Dr. Andras Szeitz for his technical assistance with HPLC and UPLC/MS/MS, as well as our entertaining conversations we had about our favorite NHL hockey team, the Vancouver Canucks.  I would like to show my gratitude to the past members of the Grigliatti lab for their technical assistance and advice on the project, as well as their support during the lab meetings: Omid Toub, Dr. Pamela Kalas, Dr. Greg Doheny, and Madalene Earp.  In addition, I thank Dr. Vlad-Martin Diaconescu for assisting with the electron paramagnetic resonance (EPR) part of my studies. I express many thanks to my colleagues and friends in the Faculty of Pharmaceutical Sciences for making my five years unforgettable.  Also, thank you to the incredible and hardworking staff that made my journey in completing this thesis much  xvii easier: Suzana Topic, Barb Conway, Jamal Kurtu, Joan Cosar, Wes Wong, Violet Yuen, Marie Langton, Josie Lim, Arti Maharaj, Sandra Stallberg, and June Chow. I am deeply grateful for having family and friends that supported me in completing this project.  Thank you to my parents (Mr. Gian Singh Bains and Mrs. Joginder Kaur Bains), brothers (Sukhjit and Sunny), sister-in-law (Mandeep), grandparents, and all of my uncles and aunts that encouraged me to work hard and focus on finishing my Ph.D. degree.  Also, thank you to my friends for your heartfelt encouragement and positivity, especially when times were tough. Personal financial support was gratefully accepted from the Canadian Institutes of Health Research (CIHR) and the Faculty of Graduate Studies at the University of British Columbia.  Project funding for the project was received from CIHR.                          xviii DEDICATION              To my parents                                 xix PREFACE  Co-authorship  This thesis includes five manuscripts (four published, one submitted) for which I am co-first author for one and first author for the rest.  In relation to the findings with AKR1A1 (Chapter 2), equal work was performed by Dr. Ryan Takahashi and myself towards the research and preparation of the manuscript.  Dr. Takahashi had established the HPLC-fluorescence detection assay method of detecting the doxorubicinol (DOXol) and daunorubicinol (DAUNol) metabolites before I started my Ph.D. research project. For the studies involving the carbonyl reductases (CBRs) in Chapter 3, I was assisted by a summer research student, Miss. Morgan J. Karkling.  I had created the prokaryotic expression constructs of the wild-type and variant CBR1 and CBR3 enzymes, and we were both responsible for purification of the CBR enzymes from bacteria and enzyme kinetic analyses using daunorubicin (DAUN) and doxorubicin (DOX).  I analyzed the data arising from the CBR1 and CBR3 studies and prepared the manuscripts, which have been published. In the last study in Chapter 4, Dr. Joanna M. Lubieniecka taught me proper techniques for using mammalian cell lines and we both participated in the experimental design.  Also, Dr. András Szeitz and I developed the UPLC-MS/MS analytical method to measure the concentrations of DAUNol and DOXol in the metabolic assays. In recognition of the significant contributions of the aforementioned individuals in my studies, they will be co-authors in future manuscripts, which are ready for submission.  Other than the exceptions provided above, the contributions of the co- authors in all the manuscripts were through their involvement in intellectual discussion regarding research design and manuscript preparation.  xx  Publications arising from work presented in this thesis  1. Bains OS, Takahashi RH, Pfeifer TA, Grigliatti TA, Reid RE, and Riggs KW (2008) Two allelic variants of aldo-keto reductase 1A1 exhibit reduced in vitro metabolism of daunorubicin.  Drug Metab Dispos 36(5): 904-910.  2. Bains OS, Karkling MJ, Grigliatti TA, Reid RE, and Riggs KW (2009) Two non- synonymous single nucleotide polymorphisms of carbonyl reductase 1 demonstrate reduced in vitro metabolism of daunorubicin and doxorubicin. Drug Metab Dispos 37: 1107-1114.  3. Bains OS, Karkling MJ, Grigliatti TA, Reid RE, and Riggs KW (2010) Naturally occurring variants of human CBR3 alter anthracycline in vitro metabolism. J Pharmacol Exp Ther 332(3): 755-763.  4. Bains OS, Grigliatti TA, Reid RE, and Riggs KW (2010) Naturally occurring variants of human aldo-keto reductases with reduced in vitro metabolism of daunorubicin and doxorubicin. J Pharmacol Exp Ther. (accepted Sept 13th, 2010, doi:10.1124/jpet.110.173179)  The first and fourth publications are used in Chapter 2 while the second and third publications are mentioned in Chapter 3, along with the findings for CBR4 in the fourth publication.  The manuscript with the findings for the cell line study in Chapter 4 looking at the association between cytotoxicity and DOX/DAUN metabolism has been submitted for publication.                1 CHAPTER 1: OVERVIEW   Cancer is one of the most common causes of death, accounting for nearly 1 of every 4 deaths in the US and Canada (Marrett et al., 2008; American Cancer Society, 2010).  One common method of treating cancer is through the use of chemotherapy, which involves the administration of anti-cancer drugs to slow or stop cancer cells from growing, multiplying or spreading to other parts of the body.  In the past several decades, these drugs have prolonged the lives of countless cancer patients; however, the effectiveness of many anti-cancer drugs is limited by their toxicity to normal rapidly dividing cells.  This is the case with one group of anti-cancer drugs known as the anthracyclines, in particular, daunorubicin (DAUN) and doxorubicin (DOX).  There is considerable inter-patient variability in the onset of serious life-threatening adverse effects associated with anthracyclines, such as chronic cardiotoxicity.  A possible reason for this variability is altered metabolism due to genetic polymorphisms in the genes encoding the metabolic enzymes for these drugs.  The enzymes of interest are the aldo- keto reductases (AKRs) and carbonyl reductases (CBRs) since previous studies have demonstrated that they are capable of metabolizing DAUN and/or DOX.  This thesis describes the detailed studies conducted to examine the role of genetic variants in the AKRs and CBRs on the metabolism and cytotoxicity of DOX and DAUN: • Chapter 1 provides the general background in support of the studies; • Chapters 2 and 3 examine the role of genetic variation in AKRs and CBRs using bacterially-expressed human recombinant enzymes and comparing DAUN and DOX metabolism between the wild-type and variants;  2 • Chapter 4 assesses the association between cytotoxicity and altered metabolism of DAUN and DOX mediated by AKRs/CBRs using a variety of cell lines; and • Chapter 5 provides a global summary of the studies with some suggestions for future directions of this work.  1.1 Anthracyclines—chemical structure and mechanism of action  Anthracyclines are a class of anti-cancer drugs used in clinical practice for the treatment of carcinomas (invasive malignant tumors derived from epithelial tissue), leukemias (cancer of the bone marrow), lymphomas (cancer of the lymph nodes or lymphoid tissue), and sarcomas (cancer of the body’s connective tissues such as bone, muscle, and cartilage) (Wojtacki et al., 2000; Danesi et al., 2002).  The chemical structure of anthracyclines consist of a fused tetracycline ring containing (i) hydroquinone and quinone structures found adjacent to each other in rings B and C, respectively, which gives the ring system both electron-donating and -accepting properties, (ii) a methoxy group at the carbon-4 position on ring D, and (iii) a short carbonyl-containing side chain at carbon-9 and glycosidic linkage to a daunosamine sugar at carbon-7 (Figure 1).   Figure 1—Chemical structure of an anthracycline illustrating the fused tetracycline ring (denoted by A, B, C, and D) as as well the daunosamine sugar.  3  The introduction of anthracyclines to cancer chemotherapy has been one of the major successes of oncology.  For example, in pediatric oncology, the 5-year survival rate for childhood cancer has increased from approximately 30% in the 1960s to 70–80% today (Gatta et al., 2002; Jemal et al., 2006) with more than 50% of cancer survivors receiving anthracycline treatment (Krischer et al., 1997). Notwithstanding the widespread use of anthracyclines in patient care and experimental studies, the exact mechanisms by which these drugs exert their cytotoxic actions are not certain (Gewirtz, 1999; Minotti et al., 2004).  The most commonly described mechanisms of action are DNA intercalation (Sinha et al., 1984; Gerwitz, 1999) and inhibition of topoisomerase II (Mordente et al., 2001; Binaschi et al., 2001). The intercalation of the anthracyclines into the DNA structure inhibits replication of cancer cells since enzymes required for DNA replication (i.e., DNA polymerases, helicases, and primases) are unable to interact with the anthracycline-DNA complex. Likewise, DNA repair enzymes, such as the DNA glycosylases (enzymes involved in base excision repair), would not be able to bind to the anthracycline-DNA complex. Without proper repair of DNA, cancer cells will eventually die through the activation of apoptotic response systems (Goto et al., 2001). Inhibition of topoisomerase II is another mechanism that is believed to play a significant role in anthracycline-induced cytotoxicity (Minotti et al., 2004).  Its role in DNA replication and cell division is vital, since it catalyzes several reactions, including catenation–decatenation of sister chromosomes, DNA knotting–unknotting, and removal of supercoils, by making transient double stranded nicks in the DNA strand, all of which reduce the topological complexity of DNA (Tewey et al., 1984; Wilstermann and  4 Osheroff, 2003; Roca, 2009).  Anthracyclines act as “topoisomerase poisons” by stabilizing the DNA-topoisomerase II covalent adduct, thus preventing re-ligation of the DNA strands (Guano et al., 1999; Maxwell et al., 2005).  DNA damage due to topoisomerase poisoning by anthracyclines can overwhelm the cell leading to growth arrest in the G1 and G2 phases of the cell division cycle, ultimately triggering cancer cell apoptosis via the p53-dependent pathway (Ruiz-Ruiz et al., 2003; Minotti et al., 2004; Simunek et al., 2009).  In addition to these proposed mechanisms, some studies have suggested that the production of reactive oxygen species (ROS), direct damage to cell membranes (Vichi and Tritton 1992; Binaschi et al., 2001), and lipid peroxidation participate in the anti-cancer effects of anthracyclines (Muindi et al., 1984).  However, these suggested mechansisms are ascertained from in vitro studies; hence, it remains unclear to what extent they contribute to the cytotoxicity of cancer cells, since the drug concentrations or experimental conditions for these studies often do not reflect the in vivo situation (Gewirtz, 1999).   1.2 DAUN and DOX—their use in cancer treatment and cardiac side effects  Many of the anthracyclines continue to undergo clinical trials for cancer therapy. Two of these anthracyclines, DAUN and DOX, are commonly used in cancer therapy. The chemical structures of these two drugs differ solely by the presence of a hydroxyl group at the carbon-14 position (Figure 2).  DAUN (otherwise known as daunomycin and rubidomycin) and DOX (also referred to as adriamycin), were isolated in the 1960s from Streptomyces peucetius, a species of actinobacteria (Tan et al., 1967; Gewirtz, 1999; Simunek et al., 2009).  DOX is used in the treatment of a broad spectrum of cancers, including breast cancer, non-Hodgkin’s disease, childhood solid tumors, and soft tissue  5 carcinomas, while DAUN is employed in the treatment of acute myeloid and acute lymphoblastic leukemias (Hunault-Berger et al., 2001; Danesi et al., 2002; Fassas and Anagnostopoulos, 2005; Cortes-Funes and Coronado, 2007).      Figure 2—Chemical structures of (A) DOX and (B) DAUN.  Even though DAUN- and DOX-based chemotherapies have contributed to improved life expectancy in cancer patients, there are common adverse effects, but fortunately they are largely reversible and clinically manageable: myelosuppression (a drop in white blood cell count), stomatitis (inflammation of the mucous lining of any of the structures in the mouth), hair loss, mucositis (inflammation and ulceration of the mucous membranes lining the digestive tract), and gastrointestinal disturbances (nausea and vomiting) (Gianni et al., 1995; Rubin and Hait, 2003; Lang-Bicudo et al., 2008; Simunek et al. 2009; Majem et al., 2009).  On the other hand, there are some adverse effects that require specific attention due to their irreversible, life-threatening nature.  In  6 particular, a major concern is the considerable inter-patient variability seen in the development of chronic cardiotoxicity (Shan et al., 1996; Wojtacki et al., 2000; Mordente et al., 2001; Minotti et al., 2001; Lipshultz et al., 2008; Simunek et al., 2009).  This type of toxicity is severe because it can ultimately lead to decreased left ventricular ejection fractions, cardiomegaly (enlargement of the heart), and eventual congestive heart failure, which accounts for at least 20% of mortalities in patients treated with DOX (Praga et al., 1979; Von Hoff et al., 1979; Shan et al., 1996).  Chronic cardiotoxicity arises through a progressive decrease in ventricular contractile function, normally within the first year after completion of treatment with anthracyclines (Singal and Iliskovic, 1998); however, it also occurs as a delayed form, presenting itself at 4 to 20 years after conclusion of cancer therapy (Steinherz et al., 1991). The incidence of chronic cardiotoxicity and congestive heart failure is dose- dependent, escalating in occurrence with increasing total lifetime dosing of anthracyclines.  In a retrospective study of 399 patient records, congestive heart failure was detected in 4% of cancer patients who received 500 to 550 mg DOX/m2 body surface, 18% in patients given 551 to 600 mg/m2, and 36% in patients given ≥ 601 mg/m2 (Lefrak et al., 1973).  Another retrospective study verified this trend of dose-dependent increase in congestive heart failure with DOX after analysis of 4018 patient records: 3% at a cumulative dose of 400 mg DOX/m2; 7% at 550 mg/m2, and 18% at 700 mg/m2 (Von Hoff et al., 1979).  Dose-dependent increases in congestive heart failure have also been reported for DAUN following the review of 5613 patient records with the incidence rising from 1.5% at a cumulative dose of 600 mg/m2 to 12% at 1000 mg/m2 (Von Hoff et al., 1977).  Despite variations among patients in their tolerance of DOX and DAUN, an empirical cumulative lifetime dose limit of 500 mg/m2 is suggested as a strategy to  7 minimize the risk of chronic cardiotoxicity and congestive heart failure (Gilladoga et al., 1976; Wallace, 2003).  While 500 mg/m2 is the recommended dose, there is considerable inter-patient variation observed with some cancer patients developing congestive heart failure at a cumulative dose of 300 mg DOX/m2; however, other patients exhibited no signs of cardiomyopathy with cumulative doses greater than 1000 mg DOX/m2 (Deng and Wojnowski, 2007).  At this time, there are no biomarkers to determine the risk a cancer patient has for developing chronic cardiotoxicity or other forms of cardiac damage prior to starting anthracycline therapy.  Therefore, cancer patients who can endure doses of anthracyclines higher than the recommended limit will not receive optimal therapy, whereas those patients who are highly susceptible to congestive heart failure are put in a dangerous situation since the recommended dose may prove to be lethal or permanently detrimental. The clinical use of DAUN and DOX spans more than fifty years and an analog that is a potent cancer cell killer with diminished cardiotoxic properties has yet to be made.  Over 2000 synthetic analogs of DAUN and DOX (i.e., aclarubicin, epirubicin, and idarubicin are just to name a few) have been developed with modifications made to the chemical structure in attempts to retain antitumor efficacy while eliminating the incidence of cardiotoxicity (Figure 3).  These modifications involve adding or removing substituents from the tetracycline rings and carbon-9 side chain, as well as adding a longer chain of daunosamine sugars.  Only a few analogs have reached the stage of clinical development and approval; among them, epirubicin and idarubicin enjoy popularity as useful alternatives to DOX or DAUN, respectively. Unfortunately, the major side effect of epirubicin and idarubicin, as well as the other clinically used analogs in cancer therapy, is the development of cardiotoxicity (Dabich et al., 1986; Natale et al.,  8 1993; Anderlini et al., 1995; Dhingra et al., 1995; Ryberg et al., 1998; Minotti et al., 2004).  Figure 3—Chemical structures of anthracycline analogs epirubicin, idarubicin, and aclarubicin.  In addition, the concomitant use of anthracyclines with certain other anti-cancer drugs has resulted in an increased risk of anthracycline-induced chronic cardiotoxicity (Wojtacki et al., 2000; Mordente et al., 2001; Danesi et al., 2002; Floyd et al., 2005; Gianni et al., 2007).  For example, taxanes such as paclitaxel are microtubule inhibitors that induce apoptosis in breast cancer cells and inhibit tumor angiogenesis (Grant et. al., 2003; Minotti et al., 2004).  Therefore, the combination of anthracyclines with taxanes came as a natural step toward an improved treatment of metastatic breast cancer. However, trials incorporating bolus DOX followed by a 3 hr infusion of paclitaxel have  9 resulted in 18% of patients developing congestive heart failure at cumulative doses of 480 mg/m2 (Gianni et al., 1995).  This finding was supported by a previous study, which demonstrated that 50% of breast cancer patients undergoing DOX-paclitaxel treatment had significant reductions in left ventricular ejection fractions, and 20% of these patients developed congestive heart failure (Gehl et al., 1996).  Another anti-cancer drug, Herceptin® (also known as trastuzumab), is a humanized monoclonal antibody that selectively inhibits the growth and proliferation of breast cancer cells overexpressing tyrosine kinase human epidermal growth factor receptor 2 (HER-2) (Feldman et al., 2000; Tan and Swain 2003; Jones and Smith, 2004).  Although Herceptin has been successful in breast cancer chemotherapy, its use with DOX has resulted in cardiotoxic effects.  For example, a study by Seidman et al., (2002) reported that the incidence of cardiac dysfunction in patients receiving Herceptin alone was approximately 3-7%, yet this incidence increased substantially to 27% for patients undergoing treatment with a combination involving DOX and Herceptin.   1.3 Proposed mechanisms of DAUN/DOX-induced cardiotoxicity  There is evidence that the accumulation of DOX in the heart is dangerous due to damage of the cardiac tissue (Menna et al., 2007).  A slow infusion of DOX in patients has led to reductions in cardiotoxicity compared to the administration methods involving bolus dosing and drug encapsulation, both of which prolong drug circulation (Berry et al., 1998; Speyer and Wasserheit, 1998; Minotti et al., 2004; Cortes-Funes and Coronado, 2007).  However, the exact mechanism of anthracycline-induced cardiotoxicity is not certain.  Previous studies have suggested that there are several pathogenic mechanisms involved: (i) cellular toxicity from metabolites (Boucek et al., 1987; Minotti et al., 1995);  10 (ii) selective inhibition of gene expression for proteins associated with contraction of the myocardium (i.e., cardiac troponins, actin thin filaments, myosin light chains, and creatine kinase) (Ito et al., 1990); (iii) excessive calcium overload inside cardiomyocytes due to altered activity of calcium pumps (Mitrius and Vogel, 1990); (iv) intensive release of vasoactive amines in the myocardium and peripheral tissue (Rossi et al., 1994); and (v) inhibition of topoisomerase II activity (Cummings et al., 1991). Although the cause of anthracycline-induced cardiotoxicity is multifactorial, a large body of evidence points to the involvement of reactive oxygen species (ROS) in cardiomyocyte damage (Myers et al., 1977; Doroshow, 1983; Jackson et al., 1984; Rajagopalan et al., 1988; Minotti et al., 2004; Gilleron et al., 2009; Zhang et al., 2009; Menna et al., 2010).  ROS are reactive molecules that include hydrogen peroxide (H2O2) and highly reactive free radicals such as the hydroxyl radical (·OH) and superoxide anion (·O2-), all of which have been documented to be the major perpetrators responsible for DOX-induced chronic cardiotoxicity in cancer patients following anthracycline treatment (Rajagopalan et al., 1988; Minotti et al., 1998; Xu et al., 2001; Tokarska-Schlattner et al., 2006).  ROS are naturally produced in biological systems and are capable of damaging cells through a number of different mechanisms, in particular, oxidation of cell membrane lipids, DNA disintegration, and dysfunction of enzymes containing sulfhydryl groups (Wojtacki et al., 2000).  Another mechanism involves anthracyclines inhibiting the mitochondrial respiratory chain by interacting with mitochondrial DNA or binding to cardiolipin, a polyunsaturated, fatty acid-rich phospholipid with a high affinity for anthracyclines found in elevated concentrations in the inner mitochondrial membrane (Giantris et al., 1998; Herman et al., 1999; Wouters et al., 2005; Simbre et al., 2005; Lipshultz et al., 2008).  On the other hand, it is also important to mention that ROS have  11 beneficial roles such as activating phagocytic cells responsible for killing harmful bacteria and regulating smooth muscle tone in vascular tissue (Horenstein et al., 2000). ROS production in the presence of DOX has been speculated to occur through one or a combination of non-enzymatic and enzymatic processes.  The non-enzymatic process tends to be iron-mediated.  Cells normally contain a small amount of total cellular cytosolic iron, less than 5%, that is either free or loosely bound (Esposito et al., 2002; Xu et al., 2005).  Anthracyclines like DOX can directly bind to Fe3+ in the presence of oxygen, forming a DOX-Fe3+ complex.  This complex can be reduced to DOX-Fe2+ in the presence of glutathione or by intramolecular autooxidation of the hydroquinone moiety in the tetracycline ring.  The DOX-Fe2+ complex can go through either of two reaction pathways: (i) it can react with molecular oxygen (O2) to form ·O2- as one of the products, which may then dismutate to form H2O2; or (ii) the complex can react with H2O2 to generate the extremely reactive ·OH radical.  In both cases, DOX-Fe3+ is regenerated.  This non-enzymatic process is comparable to that of DOX redox cycling with no metabolites being produced and the reaction proceeding indefinitely (Jung and Reszka et al., 2001; Xu et al., 2005).  Studies have demonstrated that the use of dexrazoxane, a prodrug analog of the iron chelator EDTA, has had some success in preventing the cardiotoxicity of anthracycline therapy, therefore providing good clinical evidence for involvement of the iron-mediated non-enzymatic process in ROS formation following anthracycline treatment (Hasinoff et al., 2003; Schroeder and Hasinoff, 2005; Hasinoff and Herman, 2007; Hasinoff, 2008; Sanchez-Medina et al., 2010). The enzymatic process of anthracycline-mediated ROS generation (Figure 4) involves a one electron reduction of the quinone moiety in the tetracycline ring by cellular enzymes (i.e., cytochrome-P450 or cytochrome b5 reductases, mitochondrial  12 NADH dehydrogenases, xanthine dehydrogenases, and endothelial nitric oxide synthases) which results in the formation of a semiquinone radical (Vasquez-Vivar et al., 1997; Minotti et al., 1999; Minotti et al., 2004).  The DOX semiquinone can subsequently transfer an electron to O2 to form ·O2- (Olson and Mushlin, 1990; Singal et al., 1997; Minotti et al., 1998; Wallace and Starkov, 2000; Tokarska-Schlattner et al., 2006), initiating a reaction cascade leading to the formation of other ROS and reactive nitrogen species: superoxide dismutases can convert ·O2- into H2O2; ·O2- and H2O2 can interact with iron or other transition metal ions to create ·OH; ·O2- can also initiate lipid peroxidation forming lipid peroxides and derived alkoxyl and peroxyl radicals (ROOH, RO·, ROO·) or react with nitric oxide (NO·) to form peroxynitrite (ONOO-) (Tokarska- Schlattner et al., 2006).  Figure 4—DOX-related redox cycling generation of ROS and reactive nitrogen species (RNS) by cellular enzymatic mechanisms (explained in the text).  The redox cycling involves a one electron (e-) reduction of the quinone moiety to a semiquinone radical in the tetracycline ring of DOX by cellular enzymes.  The DOX semiquinone transfers an electron to O2 to form ·O2-, which subsequently leads to the formation of other ROS and RNS. The quinone moeity and semiquinone radical within the DOX chemical structure are shown in dashed boxes.  13  However, as oxidation is the primary means by which human get energy and accompanies many metabolic processes, the human body has evolved a natural counterbalance to oxidative cell damage from ROS with the widespread use of antioxidant molecules and the expression of antioxidant enzymes such as superoxide dismutases (responsible for catalyzing the conversion of ·O2- into H2O2 and O2), as well as catalases and glutathione peroxidases (both enzymes convert H2O2 to H2O and O2). Nonetheless, under conditions where ROS production is significantly increased, the antioxidant protective system may be overwhelmed.  This is especially the case with the heart since cardiomyocytes are characterized by a low content of antioxidant enzymes, in particular, glutathione peroxidases and superoxide dismutases (Cummings et al., 1991; Horenstein et al., 2000).  Also, it has been demonstrated that during DOX treatment, concentrations of glutathione peroxidase are decreased, which further enhances sensitivity of the heart to the destructive effects of ROS.   1.4 The phases of biotransformation and DOX/DAUN metabolism  Biotransformation is the process whereby a substance is converted from one chemical to another by an enzyme-catalyzed chemical reaction in the body.  The biotransformation reactions catalyzed by metabolic enzymes are generally divided into, Phase I and Phase II processes.  This may be followed by a Phase III process, which involves the removal of the metabolites from the cell with the aid of efflux transporters (Figure 5).   14  Figure 5—A simplified overview illustrating Phase I, II, and III metabolism of aspirin occurring in a cell. Phase I and II reactions require enzymes (in green; either free in the cytosol or membrane bound) while Phase III focuses on transporters (in red) embedded in the plasma membrane that assist in the removal of Phase I and Phase II metabolites.  Phase I biotransformation normally involves oxidation, reduction, or hydrolysis reactions that lead to the addition or exposure of polar functional groups on the substrate molecule.  This increases the hydrophilicity of the molecule, albeit a small increment which facilitates elimination from the body (Klaasen, 1995; Ioannides and Lewis, 2004). Examples of functional entities added or unmasked are the hydroxyl (-OH), carboxyl (- COOH), sulfhydryl (-SH) and amino (-NH2) groups.  Cytochrome P450s (CYPs) are the major enzymes in Phase I metabolism of exogenous and endogenous compounds, which carry out a number of oxidation and reduction reactions, including aliphatic and aromatic hydroxylation, epoxidation, sulfoxidation, and oxidative dehalogenation.  Other Phase I  15 enzymes consist of flavin-dependent monooxygenases (catalyze N- and S-oxidation), peroxidases (catalyze reduction of hydroperoxides to alcohols), carboxylesterases and peptidases (both catalyze hydrolysis of ester or peptide bonds, respectively), and alcohol dehydrogenases (catalyze oxidation of alcohols to aldehydes (Yin 1994; Krueger et al., 2006; Imai, 2006) Phase II biotransformation generally follows Phase I, and generally introduces a hydrophilic group to the compound through a conjugation reaction with the previously formed functional groups (Klaasen, 1995; Knights, 1998).  This leads to a substantial increase in water solubility of the compound so that it can be easily excreted from the body.  Some of the prominent examples of enzymes (and conjugates) participating in Phase II reactions are: UDP-glucuronosyltransferases (catalyzes the transfer of glucuronic acid to the substrate); sulfotransferases (sulfate group); glutathione S- transferases (glutathione); and amino acid N-acyl transferases (amino acid, such as glycine).  If a compound already has an exposed functional group, it can bypass Phase I and go directly to Phase II. Phase III encompasses the export of conjugated metabolites from Phase II reactions, as well as unconjugated metabolites from Phase I metabolism, across the plasma membrane into the extracellular space via membrane-bound transporter pumps (Homolya et al., 2003; Xu et al., 2005).  Phase III does not chemically change the molecule as seen in Phase I and II; however, it is included in the metabolic process since it prevents the accumulation of conjugated and unconjugated metabolites in the cell, and therefore, is important in the detoxification process.  There are a number of examples of Phase III transporters that exist in humans: P-glycoproteins [also known as multi-drug resistance 1 (MDR1) protein]; multi-drug resistance associated proteins (MRPs), and  16 breast cancer resistance proteins (BCRPs) (Homolya et al., 2003; Haimeur et al., 2004; Okamura et al., 2004).  These three transporters fall under a superfamily of transmembrane proteins referred to as ATP-binding cassette (ABC) transporters, which efflux a broad spectrum of endogenous and exogenous compounds out of the cell, such as chemotherapeutic drugs, peptides, glucocorticoids, steroids, as well as Phase I (unconjugated) and Phase II (conjugated) biotransformation metabolites.  There are also ATP-independent Phase III transporters, such as lung resistance-related proteins (LRPs), which are involved in intracellular redistribution of drugs, thereby, reducing exposure of nuclear targets from cytotoxic agents (Zurita et al., 2003; Perez-Tomas, 2006). DOX is extensively metabolized by Phase I enzymes, such as oxidoreductases (enzymes that catalyze the transfer of electrons from one molecule, the oxidant, to another molecule, the reductant) to yield the alcohol metabolite, doxorubicinol (DOXol), and by cytochrome P450 reductases (POR) that cleave the glycosidic bond and release the aglycones, 7-desoxydoxorubicinon and 7-desoxydoxorubicinol (Figure 6) (Felsted et al., 1977; Oki et al., 1977; Pan et al., 1981; Lown JW, 1993; Robert and Gianni, 1993; Le Guellec et al., 1993; Riddick et al., 2005).  Phase II processes do not appear to be important metabolic routes for DOX; however, 4-demethyl-7-deoxydoxorubicinol aglycone-4-O-β-glucuronide (dA3-4-O-glucuronide) has been identified in urine following DOX therapy (Takanashi and Bachur, 1976) as has the sulfate conjugate, 4- demethyl-7-deoxydoxorubicinol aglycone-4-O-sulfate (dA3-4-O-sulfate) (Takanashi and Bachur, 1976; Andrews et al., 1980)  (Figure 5).  Renal clearance of DOX is low with approximately 12% of the total dose recovered in urine during 6 days of treatment, while hepatic clearance is high with more than half of the total dose excreted in bile within 7 days of treatment (Danesi et al., 2002).  Of the fraction eliminated in bile, approximately  17 50% is the parent drug, 23% is DOXol (the major metabolite), and the remainder consists of other metabolites like the aglycones (Lipp and Bokemeyer, 1999).  DAUN follows a similar metabolic pathway in humans with daunorubicinol (DAUNol) being the major metabolite (Bachur, 1971; Andrews et al., 1980; Akopfure et al., 1982; Pea et al., 2000).  Figure 6—Schematic representative of DOX metabolism.  The parent drug, DOX, is shown in the solid box while the major alcohol metabolite, doxorubicinol (DOXol) is indicated in the dashed box.  AKR, CBR, and POR correspondingly refer to aldo-keto reductase, carbonyl reductase, and cytochrome P-450 reductase.  NADPH (nicotinamide adenine dinucleotide phosphate, reduced form) is the enzyme cofactor involved in the chemical process.   18 The high variability in the response of patients receiving anthracycline treatment is reflected in the various pharmacokinetic parameters for the parent drug as well as the alcohol and aglycone metabolites, which have been extensively reviewed and reported in the literature (Andrews et al., 1980; Balis et al., 1983; Eksborg et al., 1986; Camaggi et al., 1988a; Camaggi et al., 1988b; Mross et al., 1988; Speth et al., 1988; Jacquet et al., 1990;  Launchbury and Habboubi, 1993; Piscitelli et al., 1993; Robert and Gianni, 1993). There is a large variation in the values of the pharmacokinetic parameters compiled for DOX from these references, which include: elimination half life (t1/2), 22 to 74 hrs; volume of distribution (Vd), 21 to 40 L; total body clearance (CL), 24 to 120 ml/min; and area-under-the-curve (AUC), 1000 to 3700 ng•h/ml.  A wide range in t1/2 values (12 to 52 hrs) for DOXol has also been reported (Jacquet et al., 1990).  The considerable inter- patient variation observed in DOX pharmacokinetics, which in turn could explain the variation in chronic cardiotoxicity development in cancer patients, is thought to be related in part to the individual differences in anthracycline metabolism (Cummings et al., 1986). Two groups of oxidoreductase enzymes have been shown to metabolize DAUN and DOX: the aldo-keto reductases (AKRs) and carbonyl reductases (CBRs) (Cummings et al., 1991; Ohara et al., 1995; O’Connor et al., 1999; Forrest and Gonzalez et al., 2000; Gonzalez-Covarrubias et al., 2007; Kassner et al., 2008).  Within the realm of metabolic enzymes, AKRs and CBRs are classified as oxidoreductases [a class of enzymes that catalyze the reversible transfer of electrons from one substance to another (oxidation– reduction, or redox reaction)] (Figure 7).  AKRs are one superfamily of oxidoreductases while CBRs are under the umbrella of another protein superfamily known as the short- chain dehydrogenases/reductases (SDRs).  There are 15 families of AKRs with human AKR enzymes categorized into 3 of these families: AKR1, AKR6, and AKR7.  For the  19 CBRs, there are 3 human families identified: CBR1, CBR3, and CBR4.  A detailed description of the AKRs and CBRs are addressed in the next section.    Figure 7—The location of AKRs and CBRs within all existing categories of metabolic enzymes.  The main AKR and CBR enzymes of interest are the ones found in humans (highlighted in green): AKR1, AKR6, AKR7, CBR1, CBR3, and CBR4.  The categories for metabolic enzymes were derived by the International Union of Biochemistry and Molecular Biology following their numerical classification scheme [the Enzyme Commission (EC) number] of the enzymes based on the chemical reactions they catalyze: oxidoreductases (EC1), transferases (EC2), hydrolases (EC3), lyases (EC4), isomerases (EC5), and ligases (EC6).  20  1.5 Aldo-keto reductases and carbonyl reductases  Aldo-keto reductases (AKRs) are members of a highly divergent superfamily of NAD(P)H-dependent oxidoreductase enzymes with more than 140 members divided into 15 families (AKR1 to AKR15 as seen in Figure 7) (Barski et al., 2008; Mindnich and Penning, 2009).  They are generally described as monomeric proteins with an approximate length of 320 amino acids and are found in all phyla ranging from prokaryotes, protozoans, and yeasts to plants, amphibians, and mammals.  The crystal structures determined for a number of AKRs reveal a general protein structure described as an (α/β)8 barrel motif.  In this motif the α-helix and β-strand alternate eight times, and the β-strands coalesce in the core of the structure to form the staves of a barrel (Penning, 2003; Barski et al., 2008).  A nomenclature system for these enzymes was developed based on amino acid sequence similarity that distinguishes the unique protein isoforms (Jez et al., 1997). Using AKR1A1 as an example, the designation “AKR” identifies the protein as a member of the superfamily; the first numeric figure “1” designates family, defined by 40% shared  amino acid sequence identity; the letter “A” represents the subfamily, defined by 60% shared amino acid sequence identity; and the last numeric figure “1” representing the unique protein sequence.  Proteins that share 97% or greater amino acid sequence identity must be demonstrated to have distinct functions (i.e., different enzymatic activities or distinct 3' untranslated regions) to be considered unique proteins, rather than variant alleles of a single protein isoform. A webpage that is publicly available with current information about AKR proteins is maintained at the University of Pennsylvania by Dr. T. Penning (http://www.med.upenn.edu/akr/).  From this website, human AKR proteins are  21 categorized into 3 of the 15 families: AKR1, AKR6, and AKR7.  There are 10 human AKR proteins identified in the AKR1 family, 3 for the AKR6 family, and 2 for the AKR7 family (Table 1).  The AKR1 proteins are the largest of all the families and include aldose reductases, aldehyde reductases, hydroxysteroid reductases, and steroid 5β- reductases (Jin and Penning, 2007; Penning and Drury, 2007).  The AKR6 and AKR7 proteins are human homologs of potassium channel subunits and aflatoxin aldehyde reductase, respectively.  These AKR enzymes are widely distributed in human tissues, with high levels of expression being notable in the liver, heart, small intestine, kidney, and brain (O’Connor et al., 1999; Jin and Penning, 2007). Table 1—The human AKR proteins within the AKR1, AKR6, and AKR7 families identified in the AKR Superfamily website along with the location of the gene in the chromosome (http://www.med.upenn.edu/akr/).  GENES ALTERNATIVE NAMES CHROMOSOME LOCATIONS AKR1A1  Aldehyde reductase 1p33-p32 AKR1B1 Aldose reductase 7q35 AKR1B10 Aldose reductase-related protein; Small intestine reductase 7q33 AKR1B15 Aldose reductase related protein 7q33 AKR1C1 Trans-1,2-dihydrobenzene-1,2-diol dehydrogenase; 20α- Hydroxysteriod dehydrogense; Dihydrodiol dehydrogenase 1; Indanol dehydrogenase 10p15-p14 AKR1C2 Trans-1,2-dihydrobenzene-1,2-diol dehydrogenase; 3α- Hydroxysteriod dehydrogense type 3; Dihydrodiol dehydrogenase 2; Bile acid binding protein 10p15-p14 AKR1C3 Trans-1,2-dihydrobenzene-1,2-diol dehydrogenase; 3α- Hydroxysteriod dehydrogense type 2; Dihydrodiol dehydrogenase x; 17β-Hydroxysteriod dehydrogenase type 5; Testosterone 17 β-dehydrogenase 5; Indanol dehydrogenase 10p15-p14 AKR1C4 3α-Hydroxysteriod dehydrogense type 1; Dihydrodiol dehydrogenase 4; Chlordecone reductase 10p15-p14 AKR1D1 Steroid 5β-reductase; 3-oxo-5β-steroid 4-dehydrogenase 7q32-q33 AKR1E2 Testis-specific protein 10p15.1  22 GENES ALTERNATIVE NAMES CHROMOSOME LOCATIONS AKR6A3 Potassium voltage-gated channel, shaker-related subfamily, β member 1 3q26.1 AKR6A5 Potassium voltage-gated channel, shaker-related subfamily, β member 2 1p36.3 AKR6A9 Potassium voltage-gated channel, shaker-related subfamily, β member 3 17p13.1 AKR7A2 Aflatoxin aldehyde reductase 1p36.13 AKR7A3 Aflatoxin aldehyde reductase 1p36.13  Carbonyl reductases (CBRs) are members of the short chain dehydrogenase/ reductases (SDRs), a highly divergent superfamily of NADPH-dependent oxidoreductase enzymes that has grown by several orders of magnitude, from 20 in 1991 to over 47,000 today (Persson et al., 1991; Persson et al., 2009; Kallberg et al., 2010).  In phylogenetic comparisons, members of the SDRs show early divergence where the majority have only low pairwise amino acid sequence identity (typically 20–30%), but have several properties in common (Persson et al., 1991; Kavanagh et al., 2008; Persson et al., 2009). These common properties include the presence of a single-domain, cofactor binding Rossmann fold consisting of a β-sheet sandwiched between three α-helices on each side, as well as an active site containing a catalytic tetrad of highly conserved tyrosine, lysine, serine and asparagine residues (Filling et al., 2002; Kavanagh et al., 2008).  SDRs average between 250–350 amino acids in length and exhibit no structural similarities to aldo-keto reductases (AKRs), in spite of the overlapping substrate specificities (Flynn and Green, 1993; Maser, 1995; Hoffmann and Maser, 2007). Currently, there are three isoforms of CBRs found in humans: CBR1, CBR3, and CBR4 (Table 2) (Matsunaga et al., 2006; Hoffman and Maser, 2007; Oppermann, 2007; Endo et al., 2008).  CBRs are ubiquitously expressed in different human tissues, which  23 include the liver, heart, lung, epidermis, kidney, small intestine, and brain (Wirth and Wermuth, 1992; Forrest and Gonzalez, 2000).  CBR1 and CBR3 are considered to be of clinical importance since they play a major role in metabolism of the anthracycline drugs, daunorubicin (DAUN) and doxorubicin (DOX) (Licata et al., 2000; Lakhman et al., 2005; Gonzalez-Covarrubias et al., 2007; Blanco et al., 2008).  There are no published studies on the ability of CBR4 to metabolize these drugs; however, this enzyme was included in our studies along with CBR1 and CBR3 for the sake of completeness.  Table 2—The human CBR proteins along with the location of the gene in the chromosome (Matsunaga et al., 2006; Hoffman and Maser, 2007; Oppermann, 2007; Endo et al., 2008). GENES ALTERNATIVE NAMES CHROMOSOME LOCATIONS CBR1  Prostaglandin-E(2) 9-reductase; Prostaglandin 9-ketoreductase; 15-hydroxyprostaglandin dehydrogenase 21q22.12 CBR3 Short chain dehydrogenase/reductase family 21C, member 2 21q22.2 CBR4 Short chain dehydrogenase/reductase family 45C, member 1; Carbonic reductase 4; 3-oxoacyl-[acyl-carrier- protein] reductase 4q32.3   AKRs and CBRs are classified as Phase I biotransformation enzymes, which play an essential role in converting a broad spectrum of endogenous and exogenous compounds containing reactive aldehyde and ketone functional groups to their corresponding hydroxy metabolites (Matsunaga et al., 2006; Jin and Penning, 2007; Hoffman and Maser, 2007; Oppermann, 2007).  This metabolic conversion increases the water solubility of the metabolites and facilitates their elimination from the body directly or via Phase II conjugation reactions.  Some examples of compounds that are metabolized  24 by AKRs are steroid hormones, aflatoxins, sugar/lipid aldehydes, polycyclic aromatic hydrocarbons and prostaglandins (Matsunaga et al., 2006; Jin and Penning, 2007; Penning and Drury, 2007).  The detoxification and activation of many of these substrates are necessary for complex processes such as drug metabolism, toxicant elimination, or carcinogenesis (Jin and Penning, 2007). As stated previously (on page 18 of section 1.4), AKRs and CBRs are of particular interest clinically since they play a major role in the metabolism of anthracycline drugs DAUN and DOX, which rank among the most effective antineoplastic agents ever developed in cancer therapy (Licata et al., 2000; Jin and Penning, 2007).  It is possible that altered metabolic activity of AKRs and CBRs resulting from genetic polymorphisms in the genes producing the AKR and CBR enzymes may be one factor contributing to the considerable inter-patient variability in DAUN and DOX pharmacokinetics and occurrence of chronic cardiotoxicity.   1.6 Genetic polymorphisms in genes producing drug metabolizing enzymes  Genetic and non-genetic factors are determinants of the inter-individual and inter- ethnic variability in drug disposition (absorption, distribution, metabolism, and excretion of an administered drug).  Non-genetic risk factors include age, sex, diet, concomitant therapy, drug interactions, organ function, and disease states (i.e., chronic liver disease or human immunodeficiency virus infection), all of which can influence the therapeutic effects of drugs, as well as the onset of adverse drug reactions (Jackson, 2004; Shah, 2005).  For this thesis, the focus is on genetic factors, more specifically, the genetic polymorphisms associated with the drug metabolizing enzymes, that could alter the metabolism of the anthracyclines DAUN and DOX, and therefore play a role in the inter-  25 patient variability associated with the development of serious adverse effects such as chronic cardiotoxicity. Genetic polymorphisms refer to variations in the DNA sequence among individuals; they may, or may not, affect the physical or biochemical phenotype (collective characteristics) of an organism.  Some examples of genetic polymorphisms are illustrated in Figure 8, and include: • silent  mutations–a change in one DNA base pair that does not the change the amino acid in the protein made by the gene; • missense mutations–a change in one DNA base pair that results in a change in amino acid in the protein made by the gene; • nonsense mutations–similar to a missense mutation, except that the DNA base pair change gives rise to one of three stop codons, UAA, UAG, or UGA, which prematurely signals the cell to stop building the protein and generally leads to production of a truncated protein; • insertions–changes the number of DNA base pairs in a gene by adding a piece of DNA; • deletions–changes the number of DNA base pairs by removing a piece of DNA; small deletions involve the removal of one of a few base pairs of DNA; and larger deletions remove an entire gene or segments of a chromosome; • duplications–a segment of DNA, usually comprising one or more genes, is present in one or more extra copies one or more times; and • frameshift mutations–the addition or loss of a DNA base pair that shifts the reading frame of the gene; the consequence of altering the reading frame is that the sequence of amino acids added from the point of the mutation onward is altered.  26   Figure 8—Schematic representations of the different human genetic polymorphisms: missense, nonsense, insertion, deletion, duplication and frameshift. The silent mutation is not shown, but it involves a single base pair change leading to the same encoded amino acid.  Images were obtained from “Genetics Home Reference” website (http://ghr.nlm.nih.gov/)    27 All of these polymorphisms can ultimately affect the levels of protein expression for a particular enzyme as well as its functionality.  For example, a missense mutation that alters the three-dimensional structure of either the substrate or cofactor binding sites may produce an enzyme with either a lowered or even non-functional metabolic capability. Single nucleotide polymorphisms (SNPs) involve a solitary base pair change in the DNA sequence and are the most common genetic variations in humans (Shastry, 2002).  Within the human genome, which is comprised of 3 billion base pairs of DNA, SNPs occur on the average of one in every 300 to 400 base pairs (Kruglyak and Nickerson, 2001), and can occur in the protein coding regions of genes known as exons (Figure 9).  Within exons, SNPs that are silent mutations are termed synonymous since they do not lead to a replacement of one amino acid with another, that is, they do not alter the amino acid sequence of the protein. Missense or nonsense mutations alter the amino acid sequence of the protein; hence, these changes are referred to as non-synonymous mutations.  SNPs that are not in protein-coding regions may still have consequences on protein expression and function (Figure 9).  For example, SNPs in the promoter site (a region of DNA that facilitates the transcription of a particular gene), may alter the binding of the transcription initiation complex which is comprised of many proteins and recruits RNA polymerase II, an enzyme required for transcription of DNA to messenger RNA.  Also, SNPs at the junction between exons and introns (non-coding region of DNA) may affect splicing during pre-messenger RNA processing.  Splicing is important in removing introns (non-coding regions regions in the gene and primary transcript) and joining exons (coding regions) before producing the correct protein through translation. Furthermore, SNPs in introns can potentially affect gene expression since some of these  28 non-protein coding regions are known to increase expression of genes that they are located in by a process identified as intron-mediated enhancement (Buchman and Berg, 1988; Mascarenhas et al., 1990).  The mechanism by which this occurs is still unknown.  Figure 9—A schematic representation of a gene comprised of exons and introns, as well as other regulatory regions of DNA that control gene expression (promoter, silencer and enhancer).  Exons are protein coding regions of the gene while introns are the non-coding regions. Promoters are segments of DNA usually occurring upstream from the introns and act as a controlling element in the expression of that gene.  They are an important site where RNA polymerase binds and signals where RNA synthesis (transcription) should begin.  Enhancers are control regions of DNA that can turn on promoters with the help of activator proteins (in blue), thereby increasing the rate of transcription of a gene.  Silencers are control regions of DNA that, upon binding with repressor proteins, can halt the expression of the gene. SNPs that occur at any of the regions (designated by yellow lightning bolt icons) can potentially alter enzyme expression and activity.  Other important proteins of note are: (i) the TATA binding protein (in red), a transcription factor that binds specifically to a DNA sequence within the promoter called the TATA box, and initiates the recruitment of other proteins that are required for RNA polymerase to begin transcription, such as coactivators and basal transcription factors; (ii) coactivators (in purple), which are “adapter” molecules that integrate signals from activators; and (iii) basal transcription factors (in green), which position RNA polymerase at the start of transcription and initiate the transcription process.  This figure is adapted from Griffiths et al., (2000).   There are bioinformatics databases for SNPs such as the “Database for single nucleotide polymorphisms” (dbSNP) from the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/snp).  This database is an annotated collection of all publicly available nucleotide sequences and their protein translations, which was produced by NCBI as part of an international collaboration with the European Molecular Biology Laboratory (EMBL) Data Library from the European Bioinformatics Institute (EBI) and the DNA Data Bank of Japan (DDBJ).  This is the database used in  29 identifying the polymorphisms that occur naturally within the human population, for the various AKR and CBR genes and enzymes that were studied.  The focus of this research is on the naturally-occurring ns-SNPs in the coding sequence of the human AKR and CBR genes.  This type of polymorphism, as previously described, has the potential to alter the function of the enzymes.  However, the extent of altered function depends on the type of amino acid replacement that occurs and can vary from reducing activity by a few percent, perhaps a physiologically insignificant amount, to a complete null allele (no detectable enzyme activity).  The activity of the non-synonymous polymorphic enzymes (i.e., allelic variants) can be ascertained by simply creating the appropriate base pair change, via site-directed mutagensis, in the DNA sequence coding for the AKR/CBR wild-type enzymes (wild-type refers to the ‘normal’ and usually most predominant sequence in the human population based on the NCBI database), transforming the modified genes into a host cell for expression, purifying the expressed enzyme from other endogenous proteins of the host cell, and performing in vitro assays with purified enzyme and a substrate of interest.  These methods are addressed in greater detail in Chapters 2 and 3 of my thesis in relation to the AKR and CBR genes and their enzymes. In vitro assays are carried out to compare metabolic rates of wild-type with that of variant enzymes at specific substrate concentrations, or through Michaelis-Menten studies to determine rates for a range of substrate concentrations.  These rates are plotted against the substrate concentrations to compare the values of the enzyme kinetic parameters of the wild-type and allelic variants (Figure 10).  The parameters looked at in this study are: the maximum rate at which the enzyme can perform (Vmax), the affinity or strength of binding between the enzyme and its substrate (Km), the rate at which the substrate is converted into the product (kcat), and catalytic efficiency (kcat/Km).   In order  30 for a variant enzyme to exhibit reduced activity, there will be an increase in Km and decreases in Vmax, kcat, and kcat/Km, compared to the wild-type enzyme, while the reverse is true for increased activity.  These kinetic parameter values will assist in understanding the results from the upcoming examples of studies provided in this Chapter that looked at the metabolic effect of variant enzymes arising from ns-SNPs, and they are defined and described more extensively below.  Figure 10—(Top) Michaelis-Menten kinetic curve plotting metabolic reaction activity rate against substrate concentration.  (Bottom) Kinetic parameter values and how they are affected with low and high metabolizing enzymes.  31 Previous studies have demonstrated that ns-SNPs are capable of modifying the activity of an enzyme (Table 3).  This is especially the case with certain variants of the human AKRs and CBRs.  For example, a recent study by Takahashi et al. (2009) revealed that each of the two naturally occurring allelic variants of human AKR1C2, F46Y and L172Q, have significantly reduced ability to metabolize the androgen 5α- dihydrotestosterone (DHT), which is the most potent natural ligand for the human androgen receptor to its metabolite, 5α-androstane-3α,17β-diol (3α-diol), a less potent receptor ligand.  This finding suggests that these variants may have a pivotal role in modulating DHT levels and, consequently, in regulating receptor signalling in the androgen-dependent tissues such as the prostate (Ji et al., 2003; Ji et al., 2007; Penning et al., 2008).  In addition, in vitro studies by Gonzalez-Covarrubias et al. (2000) and Blanco et al. (2008) have demonstrated that ns-SNPs in genes encoding human CBRs (V88I and V244M) reduce metabolism of the anthracycline based drugs, DAUN and DOX, repectively.  The CBR1 V88I variant had a 47% lower production of DAUNol, while the CBR3 V244M variant exhibited a 2.6-fold decrease in DOXol production, compared to their respective wild-type CBR enzymes.  Table 3—A summary of studies that looked at the effect of ns-SNPs in genes for different drug metabolizing enzymes.  STUDIES ENZYMES METABOLIC PATHWAY OR ROLE OF ENZYME VARIANT(S) VARIANT EFFECT COMPARED TO WILD-TYPE Takahashi et al., 2009 AKR1C2 (aldo- keto reductase 1C2) Reduction of dihydrotestosterone to 3α-diol F46Y, L172Q Lower activity (decrease of ~40% in Vmax for both variants) Blanco et al., 2008 CBR3 (carbonyl reductase 3) Converting carbonyl group of DOX to a hydroxyl (DOXol) at the carbon-13 position V244M 2.6-fold decrease in DOXol production in relation to the wild- type human CBR3 enzyme  32 STUDIES ENZYMES METABOLIC PATHWAY OR ROLE OF ENZYME VARIANT(S) VARIANT EFFECT COMPARED TO WILD-TYPE Gonzalez- Covarrubius et al., 2007 CBR1 (carbonyl reductase 1) Converting carbonyl group of DAUN to a hydroxyl (DAUNol) at the carbon-13 position V88I 47% less DAUNol production compared to wild-type human CBR1 enzyme Lee et al., 2002 CYP2C9 (cytochrome P450 2C9) (S)-warfarin 7'- hydroxylation, phenytoin 4'- hydroxylation, tolbutamide methylhydroxylation, diclofenac 4'-hydroxylation, fluriprofen 4'-hydroxylation R144C, I359L Both lower activity (Vmax of R144C lowered by 47 to 86% for all substrates; Km of I359L increased by 3.2-11.5 fold) Hanioka et al., 2010 CYP2C8 (cytochrome P450 2C8) 6α-hydroxylation of paclitaxel A238P Lowers activity (Km value 2.9-fold higher than wild-type) Sutton et al., 2005; Shimoda- Matsubayashi et al., 1996; Rosenblum et al., 1996 MnSOD (manganese superoxide dismutase) Catalyzes the conversion of superoxide radicals to hydrogen peroxide  A-9V 30–40% less activity; affects localization and transport of the enzyme into mitochondria Zhu and Hein, 2008 NAT1 (N- acetyltransferase 1) N-OH-PhIP) O- acetyltransferase activity R33stop, R187stop, R64W, D251V Decreased enzyme expression and activity for all variants  In addition to the AKR and CBR enzymes, there are extensive studies on the effect of ns-NSPs in genes encoding for cytochrome P450 enzymes (CYPs), see Table 3 for some examples.  CYPs represent the most important Phase I drug-metabolizing enzymes that oxidize a broad spectrum of endogenous substances and xenobiotics, including more than 90% of all drugs, into more hydrophilic compounds (Nebert and Russell, 2002).  Kinetic studies using a number of different pharmaceutical compounds e.g., warfarin (an anticoagulant), phenytoin (an antieplipetic), tolbutamide (potassium- channel blocker), diclofenac, and fluriprofen (both non-steroidal anti-inflammatory drugs) have demonstrated that mutations in the CYP2C9 gene, and hence its protein  33 product, significantly reduces the rate of hydroxylation of each of these drugs compared to the wild-type enzyme.  For example, the R144C variant has shown to lower Vmax of the enzyme product by 47 to 86% of that of the wild-type (Lee et al., 2002).  Also, the catalytic activity of the I359L variant enzyme is significantly reduced for most CYP2C9 substrates due to an increase in Km (3.2 to 11.5-fold) and a reduction in Vmax (50-92%) (Lee et al., 2002).  One variant of the CYP2C8 gene, specifically the A238P substitution, has been associated with reduced 6α-hydroxylation activity in the presence of the anti- cancer drug, paclitaxel (a 2.9-fold decrease in Km compared to wild-type) (Hanioka et al., 2010).  These findings with the different variants suggest the amino acid substitutions may influence the clinical response to drugs that are metabolized mainly by CYP2C8 and CYP2C9 enzymes. Studies looking at the effect of ns-SNPs on enzyme function have also encompassed other metabolic enzymes that are not involved in Phase I reactions.  For instance, an alanine to valine substitution at position -9 (A-9V) in the mitochondrial targeting signal peptide of human manganese superoxide dismutase (Mn-SOD) has been shown to change the structural conformation of this targeting sequence, which affects transport and localization of this enzyme into the mitochondria (Shimoda-Matsubayashi et al., 1996; Rosenblum et al., 1996; Sutton et al., 2003).  Furthermore, the alanine substitution by valine has been demonstrated to reduce activity of MnSOD by 30–40% compared to the alanine-containing wild-type counterpart (Rosenblum et al., 1996). MnSOD is vital for catalyzing the conversion of superoxide radicals (liberated as a by- product of the mitochondrial electron transport chain) to hydrogen peroxide. Also, four ns-SNPs in the gene coding for human arylamine N-acetyltransferase 1 (NAT1), a Phase II enzyme responsible for N-acetylation of arylamines and hydrazine,  34 have demonstrated effects on both protein expression and function.  The N-acetylation mechanism requires cysteine at amino acid at position 68 (C68), in the active site, to accept an acetyl group from acetyl-CoA, and then subsequently transfer this group to the substrate.  Two of the ns-SNPs in the NAT1 gene are nonsense mutations that lead to truncated enzymes (R33Stop and R187Stop) while two others are missense mutations, R64W and D251V.  When the nonsense allele was expressed in transfected monkey kidney COS-1 cells, no protein was detected. When the R64W and D251V missense alleles were expressed in the same in vitro system, the amount of protein they produced was 50- and 40-fold, respectively, lower than the amount produced by the wild-type NAT1 allele (Zhu and Hein, 2008).  Furthermore, the activity of all these variants, as determined by the reduction of N-hydroxy-2-amino-1-methyl-6-phenylimidazo[4,5- b]pyridine (N-OH-PhIP), were below the limit of detection (Zhu and Hein, 2008).   1.7 Rationale  It is well documented that some patients develop significant cardiac adverse effects following treatment with the anthracycline-based drugs DAUN or DOX, and the likelihood of developing these adverse effects is directly correlated with the life-time cumulative dose of the drug treatment.  The inter-patient variability in relation to adverse effects associated with DAUN and DOX treatment cannot be explained by known clinical parameters.  It is likely that a significant proportion of this variability may be due to the differences between patients in the activity among enzymes that metabolize these anthracyclines, in particular, the AKRs and CBRs.  The AKR and CBR families of interest in this thesis are the ones found in humans: AKR1, AKR6, AKR7, CBR1, CBR3 and CBR4.  These families will be further addressed in Chapters 2 and 3.  35 It has been documented in previous studies that human AKR and CBR enzymes play a vital role in the bioactivation and detoxification of a broad spectrum of anthropogenic and natural chemical species, which also includes the anthracycline anti- cancer drugs, DAUN and DOX.  The lack of understanding of factors that modulate the function of these oxidoreductase enzymes makes it important to characterize these factors for the purposes of relating their contributions to the inter-patient variability seen in anthracycline metabolism and, potentially, as determinants of the development of chronic cardiotoxicity.   1.8 Research hypotheses and predictions  HYPOTHESIS #1: The cause of the inter-patient variation in DAUN- or DOX- induced adverse effects is unknown; however, allelic variation in the genes expressing enzymes that metabolize these anthracyclines may be one factor contributing to this inter-patient variable toxicity.  PREDICTION:  Naturally occurring genetic polymorphisms in one or more of these genes will significantly reduce the activity of its protein product.  As previously mentioned, the enzymes that metabolize DAUN and DOX belong to the aldo-keto-reductase (AKR) and carbonyl reductase (CBR) families of genes/proteins.  Therefore, to test the validity of our overall hypothesis, we examined whether naturally occurring ns-SNPs in the coding regions of the human AKR and CBR genes produce enzymes with altered capacity for the in vitro metabolism of DAUN and/or DOX.  This study compares the wild-type and allelic variants of the selected human AKRs and CBRs with the in vitro metabolism of DAUN and DOX to the  36 corresponding carbon-13 alcohol metabolites, DAUNol and DOXol.  Using purified, bacterially-expressed, human AKR enzymes, we demonstrate that, of the 29 allelic variants that were examined in this thesis, 7 resulted in significantly reduced catalytic efficiencies (kcat/Km) of DAUN compared to the wild-type enzyme, while 3 variants reduced the kcat/Km of DOX.  The analyses for the AKR genes and their enzymes are described in Chapter 2.  A similar set of analyses were completed for the CBR genes, and are presented in Chapter 3.  Of the 10 CBR allelic variants, 5 were found to significantly reduce the kcat/Km of DAUN and DOX.   HYPOTHESIS #2:  There is a strong and consistent association between DAUN/DOX metabolic activity and drug toxicity.  PREDICTION:  Alterations in DAUN and DOX metabolism are associated with the development of cytotoxic effects induced by these drugs.  Using nine cell lines from different tissues, cytotoxicity studies were conducted by incubating cell lines with different concentrations of DAUN or DOX (0 to 150 µM) for specified time periods (0, 6, 24, or 48 hr) and determining LC50 values (the concentration attributing to 50% cell death) using cell viability assays.  Metabolic studies were measured by treating cell lines with 100 nM DAUN or DOX for the same time periods, extracting the cytosols, introducing 10 µM of DAUN or DOX to the each cytosolic extracts, and measuring production of the carbon-13 metabolites.  The findings from this study indicate that there is a negative relationship between cytotoxicity and DAUN or DOX metabolism.  In addition, we looked at the expression of AKRs and CBRs in the cell line cytosols, and discovered that cells that are susceptible to toxic  37 effects by DAUN or DOX are the ones with the lowest expression of these enzymes, while the reverse is true for the cells that are resistant to DAUN/DOX toxicity.  These analyses are addressed in greater detail in Chapter 4.                                          38 CHAPTER 2: ALTERED METABOLISM OF DAUNORUBICIN AND DOXORUBICIN BY ALLELIC VARIANTS OF HUMAN ALDO-KETO REDUCTASES 1,2   2.1 Preface  Aldo-keto reductases (AKRs) are members of a highly divergent superfamily of NAD(P)H-dependent oxidoreductase enzymes that have been shown to metabolize a broad range of endogenous and exogenous carbonyl-containing compounds, including steroid hormones, aflatoxins, sugar/lipid aldehydes, and prostaglandins (Matsunaga et al., 2006; Hoffmann and Maser, 2007; Jin and Penning, 2007; Penning and Drury, 2007). AKRs and CBRs are categorized as Phase I metabolizing enzymes responsible for converting compounds containing reactive aldehyde and ketone functional groups to their corresponding hydroxy metabolites.  This metabolic conversion increases the water solubility of the metabolites, and facilitates their elimination from the body directly or via Phase II conjugation reactions. In addition to the aforementioned compounds, AKRs and CBRs have also been implicated in the metabolism of the anthracycline antibiotics, daunorubicin (DAUN) and doxorubicin (DOX) (Cummings et al., 1991; Jin and Penning, 2007).  As stated in Chapter 1, DAUN is extensively used in the treatment of acute myeloid and  1  A version of this chapter has been published:  Bains OS, Takahashi RH, Pfeifer TA, Grigliatti TA, Reid RE, and Riggs KW (2008) Two allelic variants of aldo-keto reductase 1A1 exhibit reduced in vitro metabolism of daunorubicin. Drug Metab Dispos 36: 904- 910.  Bains OS, Grigliatti TA, Reid RE, and Riggs KW (2010) Naturally occurring variants of human aldo-keto reductases with reduced in vitro metabolism of daunorubicin and doxorubicin. J Pharmacol Exp Ther. (accepted Sept 13th, 2010, doi:10.1124/jpet.110.173179  2  See Co-authorship statement for details of contribution of this manuscript.  39 lymphoblastic leukemias while DOX is employed against numerous cancers, such as breast cancer, childhood solid tumors, non-Hodgkin’s lymphoma, and soft tissue carcinomas (Hunault-Berger et al., 2001; Fassas and Anagnostopoulos, 2005; Cortes- Funes et al., 2007; Deng and Wojnowski et al., 2007).  Even though cancer treatments involving these drugs have resulted in greater life expectancy, both anthracyclines have been associated with variation in the onset of life-threatening adverse events, such as chronic cardiotoxicity (Minotti et al., 1995; Barry et al., 2007; Deng and Wojnowski, 2007; Menna et al., 2007).  Both the frequency of chronic cardiotoxicity and mortality rate are correlated with the lifetime cumulative dose of either drug.  Moreover, the risk of chronic cardiotoxicity increases when DOX and DAUN are used in combination with other anticancer drugs, such as herceptin, paclitaxel, docetaxel, vincristine, and cyclophosphamide (Mordente et al., 2001; Danesi et al., 2002; Floyd et al., 2005; Gianni et al., 2007). The cause of the inter-patient variation in DAUN- or DOX- induced adverse effects is unknown; however, allelic variation in the genes expressing enzymes that metabolize these anthracyclines may be one factor contributing to this interpatient variable toxicity.  To test this hypothesis, we examined whether naturally occurring non- synonymous single nucleotide polymorphisms (ns-SNPs) in the coding regions of human AKR genes produce enzymes with altered capacity for in vitro metabolism of DAUN and/or DOX.  Ns-SNPs are single base pair changes that may either produce a missense or nonsense mutation: a missense mutation results in a different amino acid, while a nonsense mutation results in a premature stop codon.  This thesis will focus on the ns- SNPs of a select group of human AKRs, for which the wild-type enzymes have been demonstrated to metabolize DAUN and/or DOX: AKR1A1, AKR1B1, AKR1B10,  40 AKR1C1, AKR1C2, AKR1C3, AKR1C4, and AKR7A2 (Ohara et al., 1995; O’Connor et al., 1999; Martin et al., 2006; Kassner et al., 2008).  There are 29 documented ns-SNPs in these human genes listed in the National Centre for Biotechnology Information Database with allele frequencies ranging from 0.8 to 94.3% (Table 4).  Presently, there is no information on the catalytic properties of the remaining enzyme variants in the presence of either anthracycline.  The other remaining AKRs from Table 1 (page 21 of thesis) were excluded from this study since they either (i) have no documented ns-SNPs (i.e., AKR1D1), or (ii) have not been reported in literature to be capable of metabolizing DAUN and/or DOX. Table 4—Allele frequencies of the non-synonymous single nucleotide polymorphic variants of human AKR enzymes from different ethnic groups.  ENZYMES a VARIANTS NCBI rs- number ALLELE FREQUENCIES b  N52S rs2229540 CEU=2.5% (n=120); HCB=5.6% (n=90); JPT=3.3% (n=90); YRI=1.7% (n=120) AKR1A1  (EC 1.1.1.2) E55D rs6690497 Not available I15F rs5054 UFV=1.0% (n=184); X=10.0% (n=68) H42L rs5056 YRI=5.0% (n=80); UFV=1.0% (n=184); JPT=1.1% (n=88) L73V rs5057 X=5.0% (n=68) K90E rs2229542 Multiple (CEU, HCB, JPT, etc)=4.7% (n=64) G204S rs5061 X=5.0% (n=68) AKR1B1  (EC 1.1.1.21) T288I rs5062 YRI=5.0% (n=80) P87S rs2303312 CEU=1.7% (n=118); HCB=24.4% (n=90); JPT=23.3% (n=90) M286T rs3735042 HCB=6.0% (n=84); JPT=4.7% (n=86) AKR1B10  (EC 1.1.1.-) N313D rs4728329 CEU=9.2% (n=120) R170H rs17295755 UFV=52.0% (n=184) AKR1C1  (EC 1.1.1.-, EC 1.1.1.149, EC 1.3.1.20, EC 1.1.1.112) Q172L rs1735444 UFV=32.0% (n=184)  41 ENZYMES a VARIANTS NCBI rs- number ALLELE FREQUENCIES b  AKR1C2  (EC 1.-.-.-, EC 1.3.1.20, EC 1.1.1.213) F46Y rs2854482 CEU=5.8% (n=120); YRI=14.2% (n=120) R66Q rs35961894 CEU=1.3% (n=76); HSP=1.4% (n=76); JPT=3.9% (n=76); YRI=6.6% (n=76) R170C rs35575889 CEU=1.4% (n=76) P180S rs34186955 CEU=8.1% (n=76) A106T rs4987102 PRH=2.1% (n=76) E36Term rs1804062 UFV=14.0% (n=48)  AKR1C3   (EC 1.-.-.-, EC 1.3.1.20, EC 1.1.1.213, EC 1.1.1.63, EC 1.1.1.64, EC 1.1.1.188, EC 1.1.1.112) H5Q rs12529 CEU=40.0% (n=120); HCB=82.2% (n=90); JPT=94.3% (n=88); YRI=48.3% (n=76) G135E rs11253043 YRI=2.1% (n=48); HSP=2.2% (n=46) S145C rs3829125 CEU=38.3% (n=120); HCB=34.4% (n=90); JPT=41.1% (n=90); YRI=50.8% (n=120) AKR1C4  (EC 1.1.1.-, EC 1.1.1.225, EC 1.1.1.50) L311V rs17134592 CEU=15.8% (n=120); HCB=15.6% (n=90); JPT=8.9% (n=90) V135M rs6670759 YRI=0.9% (n=116) S255N rs2231203 YRI= 2.1% (n=116) G198S rs2231200 CEU=0.9% (n=116) A142T rs1043657 CEU=5.0% (n=120); HCB=1.1% (n=90); YRI=0.8% (n=120) E180K rs859210 UFV=5.0% (n=184) AKR7A2  (EC 1.1.1.n11) Q157H rs859208 CEU=0.8% (n=120); HCB=13.6% (n=88); JPT=3.4% (n=88); YRI=28.0% (n=118)  a  Below the name of the enzyme are the Enzyme Commission (EC) numerical classification numbers, which were obtained from the Universal Protein (UniProt) database (http://www.uniprot.org/).  Based on the chemical reactions they catalyze, some of the enzymes have more than one EC number.  b  Allele frequencies were obtained from The National Center for Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov/).  The ethnic groups are designated as follows: YRI (African), CEU (European), HCB (Chinese), HSP (Hispanic), JPT (Japanese), PRH (Pacific Rim Heritage), and UFV (Utah, French and Venezuelan).  X refers to a combined population from Michigan along with UFV.  The chromosome sample counts (n) for each variant are also given.  Note that the amino acid location numbers for all the AKR7A2 variants in the NCBI SNP database are 29 residues greater than their location within the protein coding sequence from the NCBI Protein database.  An explanation for this discrepancy can be found in Kelly et al., (2002) with numbering of amino acid residues on the amino terminus starting from a methionine located 29 residues ahead of the methionine used as the start site in AKR7A2 coding sequence. b   42  The purpose of this study is to improve our understanding of the effect of genetic variation in the human AKR genes on the in vitro metabolism of DAUN and DOX to the corresponding carbon-13 alcohol metabolites, daunorubicinol (DAUNol) and doxorubicinol (DOXol).  Using purified, bacterially-expressed, human AKR enzymes, we demonstrate that 7 AKR variants resulted in significantly reduced catalytic efficiencies (kcat/Km) of DAUN compared to the wild-type enzyme, while 3 variants reduced kcat/Km of DOX.  Furthermore, we observed that DAUN is generally a better substrate than DOX for the AKR wild-type and variant isoforms, as shown by the significant increases in kcat/Km.  2.2 Materials and Methods  2.2.1 Chemicals and enzymes  Agarose, ampicillin (sodium salt), chloramphenicol, daunorubicin, DL- glyceraldehyde, DNAseI, doxorubicin, idarubicin, kanamycin, (S)-1-indanol, lysozyme, methanol, potassium phosphate (KH2PO4), N,N,N’,N’ tetramethylethylenediamine, NADP+, NADPH, RNAseI, 1-acenaphthenol, and 9,10-phenanthrenequinone were supplied by Sigma-Aldrich (St. Louis, MO).  High performance liquid chromatography (HPLC)-grade acetonitrile, agar, ammonium persulfate, formic acid, ethanol, glycine, glycerol, glacial acetic acid, imidazole, and Tris were purchased from Thermo Fisher Scientific (Waltham, MA).  NaCl and yeast extract were ordered from EMD Chemicals Inc. (Darmstadt, Germany).  Bacto tryptone and pooled human liver cytosol were obtained from BD Biosciences (Franklin Lakes, NJ) while isopropyl β-D-1- thiogalactopyranoside (IPTG) was supplied by Fermentas (Hanover, MD), respectively. Tween 20 was purchased from EMD Biosciences (San Diego, CA).  Klenow fragment,  43 T4 ligase, Factor Xa, and restriction enzymes were purchased from New England Biolabs (Ipswich, MA).  Doxorubicinol was obtained from Qventas Inc. (Branford, CT).  2.2.2 Molecular cloning of human AKR genes and creation of allelic variants  The AKR1A1 and AKR1C2 genes were excised from insect cell expression vector constructs (p2Z0p2N-AKR1A1 and p2Z0p2N-AKR1C2) available in Dr. T. Grigliatti’s lab oratory (Department of Zoology, University of British Columbia) using DraI and NotI, and subcloned into the NheI (blunt end with Klenow fragment)-NotI sites of the prokaryotic expression vector, pET28a (Novagen, San Diego, CA) with T4 DNA ligase. These constructs encoded the AKR with a six histidine purification affinity tag (6x-His) separated by a 17-amino acid residue linker and a Factor Xa (FXa) recognition site [isoleucine (I), glutamic acid (E), glycine (G), and arginine (R)] on the amino terminus (Figure 11).  The FXa cleavage site is located after the FXa recognition site and before the AKR gene.  Figure 11—A translated product of the pET28a-AKR1A1 construct with modifications to the amino terminus of AKR1A1: a 6x-His-tag followed by an amino acid linker and a Factor Xa (FXa) recognition site.  The translated product of the pET28a-AKR1C2 (not shown) has the same amino terminus modifications.  The purpose of the 6x-His affinity tag is to allow for efficient purification of the recombinant protein from the endogenous bacterial proteins using nickel-nitrilotriacetic  44 acid (Ni-NTA) affinity chromatography, which will be discussed in the purification protocol on pages 12 and 13 (Gaberc-Porekar and Menart, 2001; Waugh 2005; Arnau et al., 2006).  The amino acid linker allowed the 6x-His tag to be exposed for Ni-NTA affinity chromatography so that more purified protein could be obtained for the enzymatic activity assays.  In addition, the FXa cleavage site permitted removal of the tag and linker from the enzyme in order to see if these amino terminus modifications affected enzyme activity.  This is addressed further in the Results section of this chapter on pages 20 to 21.  The translated products for the remaining AKR constructs were set up in a similar manner. The human AKR1C3 wild-type coding region was excised from a pOTB7 recombinant plasmid (Invitrogen, Carlsbad, CA) using XmnI and DdeI (blunt end with Klenow fragment) and subcloned into HindIII (blunt end)-XhoI (blunt end) sites of the pET28a prokaryotic expression vector (EMD, Novagen, San Diego, CA) with T4 ligase. This construct gave rise to a human AKR1C3 enzyme with an amino terminal 6x-His tag separated from the enzyme by a 32-amino acid residue linker.  A FXa cleavage site and methionine start site were inserted at the amino terminus between the linker and AKR1C3 gene using the QuikChange® Site-Directed Mutaganesis Kit (Stratagene, La Jolla, CA) with the 5' – CTCCGTCGACAAGCTATAGAAGGAAGAATGGATTCCAAACACCAG – 3' (forward) and 5' – CTGGTGTTTGGAATCCATTCTTCCTTCTATAGCTTGTCGACGGAG – 3' (reverse) primers (the FXa and methionine sites are underlined in the primer sequences).  The QuikChange® polymerase chain reaction (PCR) amplification protocol for site directed mutagenesis was modified as follows: two separate 50 µl reactions (one for each primer)  45 were subjected to 10 cycles of denaturation at 95oC for 1 min, annealing at 60oC for 1.5 min, and elongation at 68oC for 6.5 min.  A 25 µl aliquot of each PCR amplification reaction was combined with 0.75 µl PfuTurbo® DNA polymerase (Stratagene).  This reaction was subjected to 18 cycles of the same PCR protocol above. The human AKR1B10 wild-type coding region was PCR amplified from a pOTB7 (Invitrogen) recombinant plasmid using the following primers, which contained an EcoRI adapter in the forward primers and a XhoI adapter in the reverse primers (adapters are underlined): 5' – GTACCGCTCGAATTCATGGCCACGTTTGTGG – 3' (forward) and 5' – GTCTGCTACCTCGAGTCAATATTCTGCATCG – 3' (reverse).  The PCR was performed in a 50 µl reaction buffer containing 100 ng of template, 200 ng of each primer, 0.2 mM dNTPs, and 1.25 units of PfuTurbo® DNA polymerase.  The amplifying conditions for PCR involved an initial denaturation step at 95oC for 1 min, followed by 35 cycles of denaturation at 95oC for 30 sec, annealing at 55oC for 1 min, and extension at 68oC for 10 min.  Subsequently, a final extension reaction was performed at 68oC for 10 min.  The AKR1B10 PCR product was cut with EcoRI and XhoI, then subcloned into pET28a.  This construct gave rise to a human AKR1B10 enzyme with an amino terminal 6x-His tag as well as a 26-amino acid residue linker between the tag and enzyme.  A FXa cleavage site was inserted at the amino terminus between the linker and gene via site directed mutagenesis with the subsequent primers:  5' – GGATCCGAATTCATAGAAGGAAGAATGGCCACGTTTGTGG – 3' (forward) and 5' – CCACAAACGTGGCCATTCTTCCTTCTATGAATTCGGATCC– 3' (reverse) (the FXa sites are underlined in the primer sequences). The pET15b constructs containing the human AKR1B1, AKR1C1, AKR1C4, and AKR7A2 genes were generously provided by Dr. C.R. Wolf (Biomedical Research  46 Centre, Ninewells Hospital and Medical School, University of Dundee, Scotland, U.K.). These constructs gave rise to their respective AKR genes with a 10-amino acid residue linker between the 6x-His tag and gene.  A FXa cleavage site was inserted at the amino terminus between the linker and gene using site directed mutagenesis with the following primers (the FXa site is underlined in the primer sequences) [AKR1B1: 5' – CGCGGCAGCCATATAGAAGGAAGAATGGCAAGCCGTCTCC – 3' (forward) and 5' – GGAGACGGCTTGCCATTCTTCCTTCTATATGGCTGCCGCG – 3' (reverse); AKR1C1: 5' – CGCGGCAGCCATATAGAAGGAAGAATGGATTCGAAATATC– 3' (forward) and 5' –GATATTTCGAATCCATTCTTCCTTCTATATGGCTGCCGCG– 3' (reverse); AKR1C4:  5' – GCGGCAGCCATATAGAAGGAAGAATGGATCCCAAATATC – 3' (forward) and 5' – GATATTTGGGATCCATTCTTCCTTCTATATGGCTGCCGC – 3' (reverse); AKR7A2: 5' – GCGGCAGCCATATAGAAGGAAGAATGGATCCCAAATATC – 3' (forward) and 5' – GATATTTGGGATCCATTCTTCCTTCTATATGGCTGCCGC – 3' (reverse)].  In the case of the construct with the AKR1C4 gene, a ns-SNP resulting in a change from cysteine to tyrosine at position 170 was detected after sequencing. Therefore, we performed site directed mutagenesis as described above with the following primers (ns-SNP is underlined in the primer sequences) to generate the wild-type AKR1C4 gene: 5' – GTCAACTTCAACTGCAGGCAGCTGGAG – 3' (forward) and 5' – CTCCAGCTGCCTGCAGTTGAAGTTTGAC – 3' (reverse).  The construct with the AKR7A2 gene included a ns-SNP at position 142 resulting in a change from alanine to threonine, which turned out to be one of the variants that we used in this study. Therefore, we performed site directed mutagenesis as described above with the following primers to generate the wild-type gene: 5' – CTTCTACCTACACGCACCTGACCACG –  47 3' (forward) and 5' – CGTGGTCAGGTGCGTGTAGGTAGAAG – 3' (reverse).  This construct gave rise to a wild-type AKR7A2 enzyme with a 10-amino acid residue linker between the 6x-His tag and gene. The pET28a- and pET15b-variant constructs were created by site directed mutagenesis using the QIAGEN (Mississauga, Ontario) protocol with primers listed in Supplemental Table 1 (see Appendices, pages 180 to 181).  However, p2Z0pie2N laboratory vectors containing the variant genes for AKR1A1 had been created previously and did not require site-directed mutagenesis.  As a result, these genes were sub-cloned into the pET28a in the same manner as the wild-type AKR1A1 gene, which was described earlier on page 7.  All constructs were verified by dideoxy sequencing at the University of British Columbia Nucleic Acid Protein Service unit.  The truncated variant for AKR1C3 (E36Term) was not created since the translated protein is devoid of the important amino acid residues required for catalysis (aspartic acid-50, tyrosine-55, lysine- 84, and histidine-117) (Schlegel et al., 1998; Di Luccio et al., 2006; Jin and Penning, 2007).  Therefore, it was assumed that the protein would be inactive.  2.2.3 Expression and purification of recombinant human AKR wild-type and variant enzymes  The pET constructs of the AKR wild-type and variants were heat-shock transformed into Escherichia coli BL21 (DE3) pLysS competent cells and expressed under the control of an IPTG-inducible T7 polymerase.  Cells were plated on Luria- Bertani broth agar (1% bacto-tryptone, 0.5% yeast extract, 0.5% NaCl) supplemented with antibiotics (25 µg/ml chloramphenicol and 50 µg/ml kanamycin sulphate for the pET28a constructs or 100 µg/ml ampicillin for the pET15b constructs).  Colonies were  48 randomly picked and cultured overnight at 37oC in 3 ml of Luria-Bertani broth with kanamycin and chloramphenicol at the same concentrations stated previously.  Cultures were expanded to 800 ml and grown at 37°C until an OD600 of 0.5 was reached.  IPTG was added to a final concentration of 1 mM and cells were allowed to grow for an additional 5 hrs, after which the cultures were harvested by centrifugation (4000xg for 20 min at 4oC). The supernatant was removed and the cells containing the recombinant 6x-His tagged AKR enzymes resuspended at 5 ml per gram wet weight with Buffer A (300 mM NaCl, 50 mM NaH2PO4, pH 8.0).  The cell suspensions were then lysed with lysozyme (final concentration of 1 mg/ml, incubated on ice for 30 min) and the cells disrupted using six 10-sec burst (with a 10 sec cooling period between each burst) from a sonic dismembranator with a microtip set at 200-300 W.   This was followed by incubation with DNaseI and RNAseI (5 and 10 µg/ml, respectively) for 15 min on ice and then centrifugation (10,000xg, 20 min, 4oC).  The cell lysate was subjected to Ni-NTA affinity chromatography, with the recombinant protein being isolated according to the manufacturer’s instructions (QIAGEN, Mississauga, Ontario).  Briefly, the supernatant was incubated with Ni-NTA agarose beads for 1.5 hrs at 4oC to allow for the 6x-His tagged AKR proteins to interact with the Ni-NTA.  Ni-NTA occupies four of the six ligand binding sites in the coordination sphere of the nickel ion, leaving two sites free to interact with the 6x-His tag (Figure 12).  The supernatant mixture was then transferred to a gravity-flow polypropylene column, after which the 6x-His-tagged AKRs bound to the agarose beads were washed with Buffer A containing 20 mM imidazole to remove non- specific endogenous bacterial proteins bound to the beads.  AKRs were further eluted  49 with multiple fractions of Buffer A with increasing concentrations of imidazole (30, 50, 100 and 250 mM).  Figure 12—Interaction between neighboring histidine residues in the 6x-His tag and the nickel- nitrilotriacetic acid (Ni-NTA) matrix.  This figure is modified from The QIAexpressionistTM: A handbook for high-level expression and purification of 6x-His tagged proteins (QIAGEN; June 2003, 5th edition).  Protein purity was assessed by running elution fractions on 18% SDS- polyacrylamide gels, which were stained with SYPRO® Ruby (Invitrogen Canada, Inc., Burlington, Ontario) overnight (16 hrs).  After staining, the protein was detected using a Storm 840 Molecular Dynamics Imager (GE Healthcare, Piscataway, NJ) at excitation and emission wavelengths of 450 and 520 nm, respectively. Western blot analyses of the purified fractions were conducted according to the procedure described by OdysseyTM (LI-COR Biosciences, Lincoln, NE).  Following 18% SDS-polyacrylamide gel electrophoresis, proteins were transferred at 20 V in Towbin's buffer (25 mM Tris, 192 mM glycine, and 20% v/v methanol) overnight (at 4oC) to a Hybond-C Extra nitrocellulose membrane (GE Healthcare, Piscataway, NJ).  The membranes were blocked in Odyssey blocking buffer, and the enzyme detected using  50 either a MaxPab polyclonal mouse anti-human AKR1A1, AKR1B1, AKR1B10, AKR1C1, AKR1C2, AKR1C3, AKR1C4, or AKR7A2 antibody (Abnova® Corporation, Taipei City, Taiwan) (diluted 1:2500) as the primary antibodies and IRDye 800CW goat anti-mouse IgG as the secondary antibody (diluted 1:5000) (LI-COR).  Both primary and secondary antibodies were in blocking buffer containing 0.1% Tween 20.  The bound secondary antibody was detected using the OdysseyTM Infrared Imaging system (LI- COR).  2.2.4 Rate of enzymatic activity of AKRs in presence of test substrates  The rate of enzyme activities of the purified 6x-His tagged AKR wild-type and variant enzymes were measured using a Fluoroskan Ascent FL (Thermo Fisher Scientific, Waltham, MA) by following the initial rate of either NADPH oxidation or NADP+ reduction (depending on the test substrate) at excitation and emission wavelengths of 355 and 460 nm, respectively.  The assays were conducted using 1-acenaphthenol (for AKR1C isoforms), DL-glyceraldehyde (for AKR1A1 and AKR1B1), (S)-1-indanol (AKR1B10), and 9,10-phenanthrenequinone (for AKR7A2) as test substrates (Burczynski et al., 1998; O’Connor et al., 1999; Martin et al., 2006; Takahashi et al., 2008; Byrns et al., 2008).  NADPH oxidation was measured with DL-glyceraldehyde, 9,10-phenanthrenequinone, and (S)-1-indanol, while NADP+ reduction was measured with 1-acenapthenol.  In brief, 3 µg purified protein was incubated with 2.3 mM NADP+ or 0.2 mM NADPH and test substrate (1 mM acenapthenol and DL-glyceraldehyde, 0.5 mM (S)-1-indanol, and 0.05 mM 9,10-phenanthrenquinone) in a reaction mixture of 150 µl of 100 mM KH2PO4, pH 7.4.  Assays involving AKR1A1, AKR1B1, AKR1C1, AKR1C2, AKR1C3, and AKR7A2 were performed at 25oC while assays with AKR1B10  51 and AKR1C4 were conducted at 37oC (these were the temperatures in which the assays were performed in the published literature).  In these assays, the concentration of DMSO- methanol (4:1 mixture) required to dissolve the substrates (except for DL-glyceraldehyde for which water was used) was below 4% (v/v) in the final reaction mixture.  Readings were collected at 20-sec intervals for 1.5 hrs with shaking between each reading. Maximal rates were calculated from the Ascent software version 2.6 computer program (Thermo Fisher Scientific) using a 5-min interval (15 total readings) with the steepest slope.  The rate of enzymatic activity was calculated from the maximal rates using a standard curve constructed from the fluorescence measurements of solutions of known NADPH concentrations.  Enzyme activity rates in the presence of 1-acenapthenol and (S)-1-indanol were measured as nanomoles of NADP+ reduced per minute per milligram of purified protein while activity rates for the other substrates was measured as nanomoles NADPH oxidized per minute per milligram of purified protein.  Activity rates were ascertained and compared with published rates to determine if the purified enzymes were functional.  2.2.5 Kinetic activity of AKR enzymes in the presence of anthracyclines  Activity measurements for the reduction of the anthracyclines were performed by incubating either DOX or DAUN (10-700 µM; in some cases up to 1000 µM) with 3 µg purified AKR enzyme in a total volume of 150 µl containing 100 mM potassium phosphate, pH 7.4, and 1 mM NADPH at 37°C.  Protein concentrations were based on the Bradford protein assay using bovine serum albumin as a standard.  The reaction was stopped by adding 300 µl of ice-cold acetonitrile, which contained idarubicin as an internal standard, followed by vortex mixing and centrifugation at 10,000g for 10 min at  52 4°C to pellet the protein.  The supernatant was removed for high performance liquid chromatography (HPLC) analysis.  HPLC separation was performed using a Waters Alliance 2695 system (Waters Corporation, Milford, MA) with a C18, 75 x 4.6 mm i.d., 3 µm analytical column (Waters Symmetry) and a C18, 40 x 4.6 mm i.d. guard column (Phenomenex SecurityGuard; Phenomenex, Torrance, CA).  HPLC conditions were as follows: mobile phase A, 0.1% formic acid and B, acetonitrile; gradient elution, 0 to 1 min, 15% B; 1 to 8 min, 15% B to 35% B; 8 to 10 min, 35% B; 10 to 10.1 min, 35% B to 15% B; column re-equilibration for 2 min at a constant flow rate of 1 ml/min.  The column was heated to 30°C and the autosampler temperature was set to 10°C with 5 µl of sample injected onto the column.  Fluorescence detection of DOX and DAUN and their carbon-13 hydroxy major metabolites, DOXol and DAUNol, was performed with excitation and emission wavelengths of 460 and 550 nm, respectively (Waters 2475 Multi Wavelength Detector). Quantitation of DOXol and DAUNol was performed using a weighted (1/x2) linear regression determined from solutions of known concentrations of an authentic chemical standard for DOXol.  Since a chemical standard for DAUNol could not be obtained, its concentrations were calculated as DOXol equivalents using a response ratio of 1.0.  All HPLC data processes, including chromatogram integration, calibration, and quantitative calculations, were performed with Waters Empower software (version 2.0). Maximal reaction velocity (Vmax) and substrate affinity (Km) were determined by fitting the rate measurement data using nonlinear least-squares fitting to a Michaelis- Menten hyperbola (GraphPad Prism version 4.0; GraphPad Software Inc., San Diego, CA).  Values for substrate turnover rate (kcat) were calculated from Vmax values using the apparent molecular weight for the 6x-His tagged AKRs.  The kcat/Km values for the wild-  53 type and variant enzymes were also calculated.  Following Michaelis-Menten data analysis, Eadie-Hofstee plots were constructed (a graphical representation of enzyme kinetics in which reaction velocity is plotted as a function of the velocity vs. substrate concentration ratio) in order to check for deviation from linearity with changing substrate concentrations.  2.2.6 Statistical analysis  Statistical analyses were performed by GraphPad Instat® (version 3.6; GraphPad Software Inc., San Diego, CA).  Results were expressed as means ± S.D.  Enzyme activities were compared using a one-way analysis of variance followed by Tukey- Kramer multiple comparisons tests.  Differences were considered significant at p<0.05. Sample sizes (n) for the following experiments with the AKR wild-type isoforms and variants were as follows: enzymatic activity rates using appropriate test substrates (n=9), determination of Michaelis-Menten kinetic parameters using DAUN as substrate (n=9), and determination of kinetic parameters using DOX as substrate (n=9).   2.3 Results  2.3.1 Expression and purification of the AKR enzymes  The expression of the 6x-His tagged recombinant human AKR wild-type enzyme was confirmed by Western blot analysis, which showed a band with mobility corresponding to the calculated molecular mass of the tagged AKR or CBR (41 kDa for AKR1A1, 38.5 kDa for AKR1B1, 40.3 kDa for AKR1B10, 39.4 kDa for AKR1C1, 40.2 kDa for AKR1C2, 41.9 kDa for AKR1C3, 39.7 kDa for AKR1C4, and 39.3 kDa for AKR7A2) (Figure 13).  Total protein staining of the SDS-PAGE gel demonstrated that  54 the wild-type fraction was purified from its transformed bacterial lysate, since no other proteins were detected (Figure 13).  For the AKR wild-type and variant enzymes, the majority of the pure enzyme was recovered in the 250 mM imidazole elution fractions; no further protein was eluted with higher imidazole concentrations.  The results for the expression and purification of the variant forms of each enzyme paralleled that of the corresponding wild-type enzyme (Supplemental Figures 1 to 4; see Appendices, pages 182 to 185).   Figure 13—Purification of human recombinant 6x-His-tagged wild-type enzymes: (A) AKRA1, (B) AKR1B1, (C) AKR1B10, (D) AKR1C1, (E) AKR1C2, (F) AKR1C3, (G) AKR1C4, and (H) AKR7A2. (Left) Gel stained with SYPRO® Ruby following SDS-PAGE showing purified protein fraction (lane 3; 2 µg), free of contaminating proteins from the bacterial lysate (lane 1; 10 µg total protein). Removal of contaminating proteins is observed in flow through fraction from Qiagen purification procedures [Ni-NTA column flow through (lane 2; 10 µg total protein)].  (Right) Western blot detection of transformed lysate (lane 6) and purified protein fractions (lane 8), confirms expression of the desired AKR protein.  Little immunoreactivity was detected in the flow through fraction (lane 7) suggesting that majority of the enzyme was bound to the Ni-NTA resin prior to its elution.  GST-tagged full recombinant proteins (Abnova® Corporation, Taipei City, Taiwan; lane 5; 2 µg total protein) were used as positive controls for antibody immunoreactivity for all enzymes.  No antibody immunoreactivity was observed for untransformed bacterial lysate (lane 4; 10 µg total protein).  M refers to the molecular weight markers.  55  2.3.2 Enzyme activities of AKR wild-type and variant enzymes using test substrates  First, we examined whether the purified human 6x-His tagged AKR proteins were active and how the mutations affected enzyme activity compared to the wild-type using published test substrates (Table 5).  As mentioned previously, enzymatic rates for the AKR1C isoforms were determined using 1-acenaphthenol while the rates for AKR1A1 and AKR1B1 were ascertained using DL-glyceraldehyde.  The test substrates, 9,10- phenanthrenequinone and (S)-1-indanol, were introduced in metabolic assays to analyze AKR7A2 and AKR1B10 activity, respectively.  In the presence of the test substrates, the 6x-His tagged wild-type AKR isoforms were found to have rates in accordance with the reported values in previous literature (these values are given in Table 5 along with the references from which they were obtained).  The reported rate values for AKR1B10, AKR1C1, AKR1C2, and AKR1C3 were from assays using native (untagged) proteins, while the remaining four AKR isoforms were 6x-His tagged. A total of eight 6x-His tagged variants exhibited significantly reduced activity rates compared to their corresponding AKR wild-type enzymes:  a 29 to 42% decrease in activity for three variants of AKR1C3 (A106T, R170C and P180S; n=9), one variant of AKR1C2 (F46Y; n=9), one variant of AKR1C4 (L311V; n=9), two variants of AKR1A1 (E55D and N52S; n=9), and one variant of AKR7A2 (A142T; n=9).  None of the allelic variants of AKR1B1, AKR1B10, and AKR1C1 were shown to have significantly altered activity compared to their respective wild-type enzymes.  56 Table 5—Enzymatic rates for reported test substrates by recombinant 6x-His tagged AKR wild-type and variant allele enzymes.  ENZYMES VARIANTS SUBSTRATES RATES (nmol/min ● mg protein) REPORTED RATES (nmol/min ● mg protein) a AKR1A1  DL-glyceraldehyde 1240±170 1263±56   [1] N52S  850±170*  E55D  520±170* AKR1B1  DL-glyceraldehyde 354±48 441±14 [1] I15F  287±36 H42L  347±42 L73V  342±25 K90E  336±51 G204S  327±45  T288I  313±45 AKR1B10  (S)-1-indanol 980±80 1000 [2] P87S  870±90 M286T  820±90 D313N  900±50 AKR1C1  1-acenaphthenol 2050±200 1800 [3]; 2100 [4] R170H  1891±164  Q172L  1870±149 AKR1C2  1-acenaphthenol 2980±151 2400 [3]; 2500 [4]; 2230±80 [5]  F46Y  2075±170* AKR1C3 R66Q 1-acenaphthenol 3370±160 2800 [4] H5Q  3380±53 R66Q  3078±276 A106T  2060±81* R170C  2298±115*  P180S  2410±165* AKR1C4  1-acenaphthenol 1660±190 1951±49 [1] G135E  1484±181 S145C  1820±121 L311V  958±132* AKR7A2  9,10-phenanthrenequinone 2553±229 3100±107 [1]  V135M  2385±295  57 ENZYMES VARIANTS SUBSTRATES RATES (nmol/min ● mg protein) REPORTED RATES (nmol/min ● mg protein) a A142T  1660±130* Q157H  2425±237 E180K  2303±247 G198S  2483±271 S255N  2450±230  Values correspond to the mean ± S.D obtained from three experiments performed with three independent enzyme preparations (n=9) for each isoform.  Reported rates for the wild-type enzymes are also provided for comparison purposes. * Variants significantly different from their respective wild-type enzymes (p<0.05) a   [1]=O’Connor et al., 1999; [2]=Martin et al., 2006; [3]=Byrns et al., 2008 ; [4]=Burczynski et al., 1998; [5] Takahashi et al., 2008   Following the studies with the test substrates, we wanted to see if there was a significant difference in activity between the tagged and untagged enzymes.  The untagged enzymes were generated by incubating the tagged wild-type AKR proteins with Factor Xa (FXa) for 6 hrs at 23oC.  FXa cleaves the 6x His tag linker sequence after the arginine residue in the isoleucine-glutamic acid-glycine-arginine recognition sequence, thereby creating the native AKR enzyme. Subsequently, the reaction was mixed with Ni- NTA resin and run through a column to separate the 6x-His tag and amino acid linker from the native enzyme.   Western blot analysis demonstrated this treatment completely removed the tag and linker from the wild-type enzymes (Figure 14).  58  Figure 14—Representative Western blot detection of purified 6x-His tagged AKR proteins [(A) AKR1C3, (B) AKR1C4, and (C) AKR7A2 wild-type enzymes; lane 2; 3 µg] and native AKR proteins (lane 3; 3 µg). The 6x-His tagged proteins were incubated with Factor Xa for 6 hrs at 23oC to allow for removal of the tag and linker from the amino terminus.  GST-tagged AKR recombinant proteins (Abnova Corporation) were used as a positive controls for antibody immunoreactivity (lane 1; 1 µg).  M refers to the molecular weight markers.  In the case of the 6x-His tagged human AKR1A1 enzyme, there was unsuccessful cleavage of the tag and linker from the native enzyme, which was likely due to the FXa recognition site being hidden within the protein structure, thereby making it inaccessible to the enzyme.  The following attempts were undertaken in hopes of removing the tag and linker by FXa cleavage: (i) altering concentrations of the reaction buffer components, Tris-HCl, CaCl2 and NaCl; (ii) using different ranges of pH (6 to 9) and temperature (4 to 37oC) to increase FXa specificity; (iii) increasing FXa enzyme concentration; (iv) incubating the 6x-His tagged protein with thrombin to cleave the tag and a portion of the linker at the thrombin recognition site (leucine-valine-proline-arginine-glycine-serine) which may alter the folding of AKR1A1 and expose the primary cleavage site for FXa, and (v) performing FXa incubation while the enzyme was bound to the Ni-NTA resin to aid in exposing the recognition site.  Although these attempts were unsuccessful, the  59 activities of the 6x-His tagged AKR1A1 enzyme were in accordance to activity values of native human AKR1A1 as reported in literature using comparable assays (Table 4).  As a result, we deemed it unnecessary to cleave the tag and linker from AKR1A1 as they did not appear to alter enzyme activity. For the other AKR enzymes, the enzymatic rates of tagged and native (untagged) enzymes were compared.  Using 1-acenaphthenol, there were no significant differences in enzymatic activity between the tagged and native AKR1C isoforms [rates of the native enzymes were 1800±130, 2710±140, 3060±210, and 1500±210 nmol/min●mg for AKR1C1, AKR1C2, AKR1C3, and AKR1C4, respectively; n=9], suggesting that the amino acid linker and 6x-His tag engineered on the amino terminus of the wild-type gene products has no effect on enzyme activity.  Likewise, we found similar results between the tagged and native AKR1B isoforms and AKR7A2 [rates of the native enzyme were 300±50 (AKR1B1), 910±40 (AKR1B10), and 2550±250 (AKR7A2) nmol/min●mg; n=9].  Although we did not cleave off the tag and linker for the variants, we assumed that there would be no significant difference between the rates of the tagged and untagged variant enzymes.  Keeping these results and assumptions in mind, the uncleaved wild- type and variant enzymes were used for subsequent activity assays using the anthracyclines as substrates.  2.3.3 Kinetic characterization of wild-type and variant enzymatic activities with DOX and DAUN as substrates  To evaluate the impact of the single amino acid substitutions in the human AKR enzymes on the reduction of anthracycline drugs, we measured the in vitro formation of the major alcohol metabolites.  A 50 min incubation period was found to be in the linear range of enzymatic activity for each of the concentrations of DOX and DAUN used to  60 conduct the enzymatic assays (3 µg purified protein).  In addition, the concentration of cofactor (1 mM NADPH) was sufficient for maximal enzymatic activity during this 50 min incubation period.  Higher concentrations of cofactor were also examined (1.5 mM and 2 mM); however, the enzymatic rates associated with these concentrations did not differ from that of 1 mM. Full chromatographic resolution of DAUNol, DOXol, DAUN, DOX, and idarubicin (internal standard) was achieved for all chemical standards and in vitro samples (Bains et al., 2008).  DOXol, DOX, DAUNol, DAUN, and idarubicin were observed to elute at 4.6, 5.5, 6.1, 6.9, and 7.4 min, respectively (Figure 15).   Incubation of the 6x-His tagged AKR wild-type and variant enzymes with DOX generated a single new chromatographic peak that was identified as DOXol.  Similarly, incubation with DAUN generated a single new chromatographic peak that was identified as DAUNol.  The identification of the metabolite peaks was confirmed by incubation of DOX and DAUN with human liver cytosol and the generation of compounds that had identical chromatographic behaviors.  There were no detectable peaks at the DAUNol or DOXol retention time in the absence of the AKR proteins.  In addition to the enzymatic assays performed in this study, we incubated enzyme only as well as enzyme and substrate without the addition of cofactor, as controls.  The production of DOXol and DAUNol from these controls was below the limit of detection (25 nM) using HPLC-fluorescence. Therefore, we conclude the production of the metabolites is due to enzymatic processes.  61   Figure 15—Generation of DAUNol and DOXol in vitro by purified AKR incubated with DOX (top panel) and DAUN (bottom panel).  Measurement of DOXol and DAUNol was performed using HPLC- fluorescence.  Representative chromatograms show clear resolution of DOXol and DAUNol from DOX, DAUN, and idarubicin (IDA, internal standard).  Retention times observed for DOXol, DOX, DAUNol, DAUN, and IDA are 4.6, 5.5, 6.1, 6.9, and 7.4 minutes, respectively.  62    Michaelis-Menten kinetic curves were constructed for the AKR wild-type (Figure 16) and each of the variant enzymes in the presence of differing concentrations of DAUN, and the kinetic parameter values determined (Table 6).  A total of 7 allelic variants of AKR1A1, AKR1C3, AKR1C4, and AKR7A2 exhibited significant reductions in enzymatic activity with DAUN compared to their respective wild-type enzymes: a 29 and 46% reduction in kcat/Km for both the E55D and N52S variants of AKR1A1, respectively [this reduction is due to corresponding increases in  Km (30 and 79%); n=9]; a 28 to 40% reduction in kcat/Km for the A106T, R170C, and P180S variants of AKR1C3 [this reduction is due to corresponding decreases in Vmax (23-47%)  and kcat (22-47%); n=9]; a 45% reduction in kcat/Km for the L311V variant of AKR1C4 [this reduction is due to corresponding decreases in Vmax (47% lower) as well as kcat and kcat/Km (43% lower); n=9]; and a 85% reduction in kcat/Km for the A142T variant of AKR7A2 [this reduction is due to corresponding decreases in Vmax and kcat (both 61%) and an increase in Km (156%); n=9]. With DOX as a substrate (Figure 17; Table 7), 3 allelic variants of AKR1C3 and one for AKR7A2 demonstrated significant reductions in enzymatic activity with respect to the wild-type enzymes: a 52 and 69% reduction in kcat/Km for both the R170C and P180S variants of AKR1C3, respectively [this reduction is due to corresponding decreases in Vmax (41 and 44%) and kcat (39 and 45% decrease); n=9]; and a 60% reduction in kcat/Km for the A142T variant of AR7A2 [this reduction is due to corresponding decreases in Vmax (41%) and kcat (44%) and an increase in Km (47%); n=9].  63   Figure 16—In vitro enzymatic activities for the purified 6x-His tagged (A) AKR1A1, (B) AKR1B1, (C) AKR1B10, (D) AKR1C1, (E) AKR1C2, (F) AKR1C3, (G) AKR1C4, and (H) AKR7A2 wild-type and variant enzymes with daunorubicin.  Activities were measured by following the rate of daunorubicinol production.  Three independent batches of each enzyme were purified and assays were performed in triplicate with each batch.  Enzymatic activities are reported as mean ± S.D. (n=9).  Dotted lines refer to variants that have significant differences in kcat/Km parameter values compared to the wild-type.   64 Table 6—Kinetic constants for DAUN metabolism by recombinant 6x-His tagged AKR wild-type and variant enzymes.  ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km            (s-1 M-1) AKR1A1  4042±233 737±39 2.76±0.10 3750±210 N52S 3714±156 957±59*  2.54±0.11 2650±183*  E55D 3910±260 1321±135* 2.67±0.16 2020±194* AKR1B1  427±16 897±51 0.27±0.01 329±14 I15F 405±12 939±50 0.25±0.01 277±15 H42L 414±56 781±91 0.27±0.04 343±60 L73V 382±38 775±85 0.25±0.02 320±48 K90E 389±61 725±65 0.25±0.04 348±66 G204S 456±51 790±78 0.29±0.03 375±68  T288I 440±37 839±88 0.29±0.02 339±47 AKR1B10  1829±77 447±37 1.23±0.06 2752±382 P87S 1700±91 404±30 1.14±0.07 2822±360 M286T 1654±98 452±28 1.11±0.07 2453±287 D313N 1790±84 410±32 1.20±0.06 2927±391 AKR1C1  87±9 551±41 0.057±0.006 103±19 R170H 77±7 585±57 0.051±0.006 87±16  Q172L 72±10 534±39 0.047±0.006 88±17 AKR1C2  114±17 1236±168 0.076±0.01 62±7  F46Y 120±19 1322±152 0.080±0.02 61±10 AKR1C3  1570±37 122±16 1.09±0.03 8937±701 H5Q 1640±76 114±9 1.15±0.04 10066±770 R66Q 1534±28 122±14 1.07±0.02 8854±844 A106T 1082±103* 118±19 0.76±0.07* 6440±740* R170C 837±53* 108±21 0.58±0.05* 5348±676*  P180S 1211±46* 134±21 0.85±0.03* 6432±584* AKR1C4  377±28 1096±78 0.23±0.02 228±21 G135E 340±25 1156±64 0.22±0.02 194±25 S145C 356±22 1122±89 0.23±0.02 210±19 L311V 199±24* 1060±91 0.13±0.02* 125±18* AKR7A2  3659±294 329±33 2.39±0.19 7369±858 V135M 3883±240 411±62 2.54±0.16 6322±661 A142T 1418±83* 842±77* 0.93±0.05* 1109±117*  Q157H 3363±163 379±26 2.24±0.15 5836±510  65 ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km            (s-1 M-1) E180K 3204±159 366±20 2.10±0.10 5750±412 G198S 3557±174 353±37 2.33±0.11 6652±638 S255N 3274±294 339±21 2.14±0.19 6354±718  Values correspond to the mean ± S.D obtained from three experiments performed with three independent enzyme preparations (n=9) for each isoform. * Variants significantly different from their respective wild-type enzymes (p<0.05) a    kcat calculated from Mr 41000 (AKR1A1), 38500 (AKR1B1), 40300 (AKR1B10), 39400 (AKR1C1), 40200 (AKR1C2), 41900 (AKR1C3), 39700 (AKR1C4), and 39300 (AKR7A2)                                    66   Figure 17—In vitro enzymatic activities for the purified 6x-His tagged (A) AKR1A1, (B) AKR1B1, (C) AKR1B10, (D) AKR1C1, (E) AKR1C2, (F) AKR1C3, (G) AKR1C4, and (H) AKR7A2 wild-type and variant enzymes with doxorubicin.  Activities were measured by following the rate of doxorubicinol production.  Three independent batches of each enzyme were purified and assays were performed in triplicate with each batch.  Enzymatic activities are reported as mean ± S.D. (n=9).  Dotted lines refer to variants that have significant differences in kcat/Km parameter values compared to the wild-type.   67 Table 7—Kinetic constants for DOX metabolism by recombinant 6x-His tagged AKR wild-type and variant enzymes.  ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km            (s-1 M-1) AKR1A1  75±10 540±124 0.051±0.006 95±11 N52S 72±10 605±150 0.049±0.007 82±19  E55D 54±10 479±102 0.037±0.004 77±12 AKR1B1  193±12 813±17 0.12±0.01 153±10 I15F 191±23 851±16 0.12±0.01 144±18 H42L 167±8 840±11 0.11±0.01 127±10 L73V 167±19 829±19 0.11±0.01 129±14 K90E 168±19 854±23 0.11±0.01 126±12 G204S 160±15 844±17 0.10±0.01 123±21  T288I 160±17 805±26 0.10±0.01 128±16 AKR1B10  11±1 508±64 0.007±0.001 14±3 P87S 9±1 530±48 0.006±0.001 11±3 M286T 15±2 521±34 0.010±0.002 19±4 D313N 12±2 489±40 0.008±0.001 16±3 AKR1C1  17±2 643±52 0.011±0.002 17±4 R170H 14±1 670±48 0.009±0.001 13±3  Q172L 19±1 651±34 0.012±0.001 18±3 AKR1C2  56±11 780±67 0.038±0.007 49±12  F46Y 63±16 708±104 0.043±0.011 62±21 AKR1C3  546±27 142±29 0.38±0.02 2514±268 H5Q 570±18 161±12 0.40±0.01 2485±241 R66Q 509±14 158±14 0.36±0.01 2266±194 A106T 527±16 138±13 0.37±0.01 2692±297 R170C 323±23* 188±17 0.23±0.02* 1208±115*  P180S 306±27* 273±20* 0.21±0.02* 786±95* AKR1C4  73±13 962±64 0.049±0.008 51±9 G135E 70±12 974±37 0.047±0.008 48±8 S145C 71±11 992±63 0.047±0.007 48±9 L311V 69±12 935±41 0.046±0.008 49±8 AKR7A2  237±15 340±25 0.16±0.01 457±17  V135M 215±24 361±20 0.14±0.02 393±56  68 ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km            (s-1 M-1) A142T 141±19* 501±23* 0.09±0.01* 184±24* Q157H 214±16 362±20 0.14±0.01 385±26 E180K 226±28 367±19 0.15±0.02 404±52 G198S 222±19 374±17 0.15±0.01 389±33 S255N 220±13 377±18 0.14±0.01 383±38  Values correspond to the mean ± S.D obtained from three experiments performed with three independent enzyme preparations (n=9) for each isoform. * Variants significantly different from their respective wild-type enzymes (p<0.05) a    kcat calculated from Mr 41000 (AKR1A1), 38500 (AKR1B1), 40300 (AKR1B10), 39400 (AKR1C1), 40200 (AKR1C2), 41900 (AKR1C3), 39700 (AKR1C4), and 39300 (AKR7A2)   Eadie-Hofstee plots for the AKR wild-type and variant enzymes verified linearity at the same concentrations of DAUN and DOX used to conduct the assays (r2 > 0.84 for all plots).  Furthermore, by comparing kcat/Km values, we observed that DAUN is a better substrate for the AKR wild-type and variant enzymes compared to DOX (26.2 to 39.5- fold higher for AKR1A1, 1.9 to 3-fold higher for AKR1B1, 129.1 to 256.5-fold higher for AKR1B10, 4.9 to 6.7-fold higher for AKR1C1, 2.4-8.2 fold higher for AKR1C3, 2.5- 4.5 fold higher for AKR1C4, and 6.0-17.1 fold higher for AKR7A2).  Only the AKR1C2 enzyme (wild-type and variant) exhibited no significant difference in kcat/Km values between DAUN and DOX; thereby, suggesting that both drugs are equally good substrates for this enzyme.   2.4 Discussion  The central focus of this in vitro study was to examine the effect of ns-SNPs on the metabolic activity of human AKRs using test substrates, as well as DAUN and DOX as substrates.  The wild-type and naturally occurring variant alleles of the human AKR genes were cloned into an E. coli expression vector with a 6x-His tag added to the amino  69 terminus of the expressed protein.  The respective wild-type and variant proteins for each gene were purified and purity assessed by electrophoretic and Western blot analyses.  To determine whether the 6x-His tag influenced enzyme activity, the tag was removed by incubation with FXa and the enzyme repurified.  Using the test substrates, the activity of the tagged enzyme did not significantly differ from its native counterpart.  As a result, we were able to assess the impact of the single amino acid substitutions on the activity of each enzyme, without cleaving the tag in the subsequent assays involving DAUN and DOX. In these assays, the carbon-13 alcohol metabolites of DOX and DAUN, DOXol and DAUNol, respectively, were quantified since previous published studies demonstrated that they are the major metabolites in cancer patients receiving treatment with either of these anthracycline anti-cancer drugs (Lipp and Bokemeyer, 1999; Plebuch et al., 2007).  Our assays show that both DOX and DAUN are able to be converted to their respective major metabolites by the wild-type and variants enzymes for the AKRs examined in this study. Out of the 28 allelic variants that were studied (excluding the E36Term truncated variant), 7 were found to significantly decrease metabolism of DAUN compared to their respective wild-type enzymes: the E55D and N52S variants forms of AKR1A1; the A106T, R170C, and P180S variant forms of AKR1C3; the L311V variant of AKR1C4; and the A142T variant of AKR7A2.  In the presence of DOX as a substrate, 3 of the 7 aforementioned variants significantly reduced activity compared to their respective wild- type enzyme:  R170C, P180S and A142T.  To our knowledge, this study is the first demonstration of the effect of these variant enzymes on DAUN and DOX metabolism.  70 We used three-dimensional models of human AKR1A1, AKR1C3, AKR1C4 and AKR7A2 enzymes (Figure 18) to examine the location of the 7 mutations relative to the active and cofactor binding sites.  Reduction of the carbonyl group by AKR enzymes is thought to involve the co-operation of four amino acids (tyrosine, lysine, aspartic acid and histidine) forming a catalytic tetrad, which are positionally conserved in the individual reductases within this superfamily (Jez et al., 1997; Penning 2003; Barski et al., 2008).  The locations of these conserved residues for the 4 aforementioned AKR isoforms are as follows: AKR1A1: aspartic acid-45, tyrosine-50, lysine-80, and histidine- 113; AKR1C3 and 1C4: aspartic acid-50, tyrosine-55, lysine-84, and histidine-117; AKR7A2: aspartic acid-72, tyrosine-77, lysine-105, and histidine-141.  The roles that these residues play in the reduction of carbonyl-containing substrates to their alcohol products are explained in Figure 19 (Schlegel et al. 1998; Di Luccio et al., 2006; Jin and Penning, 2007; Barski et al., 2008; Di Costanzo et al., 2009).  In the case of AKR1A1, the locations of the N52S and E55D mutations occur close to the catalytic tyrosine-50 residue, which can likely hinder the role of tyrosine-50 in the metabolism of the anthracyclines. The R170C and P180S mutations in AKR1C3 are located close to amino acid residues in the cofactor binding site that participate in hydrogen bonding to the nicotinamide ring of NADPH (serine-166 in β-sheet 5, asparagine-167 in loop 5, and glutamine-190 in β-sheet 6), and therefore help anchor the cofactor to the AKR1C3 enzyme (Komoto et al., 2004).  It is possible that these mutations affect the binding of the cofactor, which ultimately reduces the enzymatic conversion of DAUN and DOX to DAUNol and DOXol, respectively.  Currently, there is no data to indicate why or how the A106T polymorphism affects cofactor or substrate binding.  It is likely chemical  71  Figure 18—Three-dimensional molecular structures of human (A) AKR1A1, (B) AKR1C3, (C) AKR1C4, and (D) AKR7A2 wild-type enzymes.  In these structures, the latter three are shown to be complexed with the cofactor, NADP+ (green) [Protein Data Bank ID: 2ALR (AKR1A1), 2FGB (AKR1C3), 2FVL (AKR1C4), and 2BP1 (AKR7A2)].  The mutations that significantly altered enzyme activity are shown (purple) as well as those that did not alter enzyme activity (red).  In addition, the residues comprising the catalytic tetrad are illustrated (blue) [AKR1A1: (1) histidine-113, (2) lysine-80, (3) tyrosine-50, and (4) aspartic acid-45; AKR1C3 and 1C4: (1) histidine-117, (2) lysine-84, (3) tyrosine-55, and (4) aspartic acid- 50; AKR7A2: (1) histidine-141, (2) lysine-105, (3) tyrosine-77, and (4) aspartic acid-72].  Also, provided are three residues of AKR1C3 that participate in cofactor binding: serine-166, asparagine-167, and glutamine-190 (pink).  The molecular graphic images of the AKRs were produced using the UCSF Chimera program (Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA).   72   Figure 19—Proposed catalytic mechanism for AKR-mediated reduction reaction [modified based on the scheme provided by Barski et al. (2008)].  The numbering of the four catalytic residues is illustrated for AKR1A1.  Top panel: In the reduction of the carbonyl-containing substrate, the tyrosine-50 residue is shown to be a proton donor for the carbonyl substrate.  It also forms a hydrogen bond with the substrate, resulting in carbonyl polarization, which accelerates the hydride transfer of the pro-R hydrogen from NADPH to the carbonyl carbon.  The hydrogen-bonding network provided by lysine-80 and aspartic acid- 45 serves to lower the pKa of tyrosine, making the proton transfer from tyrosine to the substrate easier. Bottom panel: The reduced carbonyl (i.e., the alcohol-containing substrate) then dissociates from the active site, and a net charge on the tyrosinate anion is stabilized by the hydrogen bonding network.  Histidine-113 also participates in the catalytic mechanism by donating protons to the tyrosinate anion to restore the conserved tyrosine residue.  73 structural differences between the side chain groups of these amino acids [alanine: -CH3; threonine: -CH(OH)(CH3)] may be enough to alter the conformation of the AKR1C3 protein, thereby changing the structure of the active and/or cofactor binding sites.  Since a significant difference in metabolic capability was detected between this variant and the wild-type in the presence of DAUN, and not DOX, it is possible that the active site is affected. Previous studies have shown the importance of leucine-311 in substrate binding to human AKR1C4.  For example, a study by Matsuura et al. (1998), which used chimeric enzymes produced by switching the C-terminal loop in AKR1C4 with that of AKR1C1, demonstrated that the binding of substrates, inhibitors and activators of AKR1C4 requires that the amino acid residues are located in the C-terminal loop of the wild-type AKR1C4 enzyme.  Furthermore, the authors found that a leucine to valine mutation in amino acid 311 (L311V) decreased the catalytic activity of AKR1C4 for its substrates, but it did not affect the enzyme’s sensitivity to an inhibitor or affect the enzyme’s response to an activator.  Hence, this study suggested that leucine-311 is important in substrate binding to the active site of the AKR1C4 enzyme.  This finding was further substantiated in a study by Kume at al. (1999), which used purified recombinant human AKR1C4 enzymes to show that the L311V polymorphism resulted in a 3- to 5-fold decrease in enzyme activity compared to the wild-type for a variety of xenobiotic and steroidal substrates [e.g., (S)-1-indanol, cholic acid, andosterone, naloxone, naltrexone].  In addition to the effect of the L311V mutation, this study also revealed that the S145C ns-SNP (serine to cysteine mutation at amino acid position 145) had no significant effect on enzyme activity compared to the wild-type for a variety of xenobiotic and steroidal substrates [e.g., (S)-1-indanol, cholic acid, andosterone, naloxone, naltrexone].  As well as the effect  74 of the L311V mutation, this study also revealed that the S145C ns-SNP (serine to cysteine mutation at amino acid position 145) had no significant effect on enzyme activity compared to the wild-type.  Our study demonstrates that the L311V mutation dramatically alters the ability of the enzyme to metabolize DAUN and DOX and, like the previous studies on xenobiotic and steroidal substrates, indicates that the S145C mutation has little affect on the enzymes ability to use DAUN and DOX as substrates. The alanine to threonine mutation at amino acid position 142 in human AKR7A2 (the A142T ns-SNP) is adjacent to the histidine-141 residue, which is one of the four amino acids that forms a catalytic tetrad for reduction of the substrate (others being tyrosine-77, lysine-105, and aspartic acid-72).  Due to this proximity, the A142T polymorphism may hinder the ability of histidine-141 to participate in catalysis of DOX and DAUN, thus, leading to reduced enzymatic activity compared to the wild-type AKR7A2 enzyme. In addition to looking at the differences in enzyme activity between the wild-type and variant enzymes with both anthracyclines, our studies demonstrated that DAUN was generally a better substrate for all wild-type and variant forms of the human AKRs, as shown by 1.9- to 257-fold increases in kcat/Km over DOX.  However, this was not the case for AKR1C2 as both DAUN and DOX are equally good substrates.  Also, we found that the human AKR1C3 wild-type enzyme is the most efficient at metabolizing both DAUN and DOX as demonstrated by having the highest kcat/Km values compared to the remaining 7 wild-type AKR enzymes.  The same could be said for AKR7A2 in the presence of DAUN. Overall, our study demonstrates that AKR enzymes are able to metabolize both DAUN and DOX, with the AKRs having higher specificity for the former anthracycline  75 drug.  Significant reductions in enzyme activity were discovered in 7 of 28 allelic variants of AKRs that we examined.  All of these variants may contribute to the interpatient variability seen with the development of serious cardiac side effects in DAUN- and DOX-treated patients.  If AKRs play a major role in anthracycline-induced cardiotoxicity, we propose that this condition is largely the result of accumulation of the parent drug.  The data collected begs the question of whether individuals with one or more of the aforementioned AKR polymorphisms are at higher risk for developing cardiac side effects after treatment with either DAUN or DOX.  This issue of correlating naturally-occurring allelic variation with cardiotoxicity can be addressed with clinical association studies, which are currently underway in our laboratory.                            76 CHAPTER 3: ALLELIC VARIANTS OF HUMAN CARBONYL REDUCTASES DEMONSTRATE REDUCED IN VITRO METABOLISM OF DAUNORUBICIN AND DOXORUBICIN 1,2   3.1 Preface  Aldehydes and ketones are reactive carbonyl-containing compounds present in a broad range of natural and synthetic compounds to which living organisms are exposed: aflatoxins, food ingredients, pharmaceutical drugs, and environmental pollutants (Matsunaga et al., 2006; Hoffman and Maser, 2007).  The reactive nature of aldehydes and ketones can be detrimental to living organisms.  For example, they can (i) interact directly with proteins and membranes, thereby resulting in loss of function to enzymes, membrane transporters, transcription factors, signaling components, microtubules, and other proteins (Karlhuber et al., 1997; Picklo et al., 2002); (ii) trigger apoptotic pathways ultimately leading to cell death via mechanisms involving the activation of caspases (Kruman et al., 1997; Ji et al., 2001; Li et al., 2006); and (iii) form adducts with DNA (Ellis, 2007).  All of these molecular perturbations can ultimately lead to cell death (Li et al., 1996; Li et al., 2006).  Luckily, organisms have evolved several enzyme systems for detoxifying aldehydes and ketones in order to minimize cellular damage.  Such well established pathways include the oxidation of aldehydes to their corresponding carboxylic acids by aldehyde dehydrogenases and aldehyde oxidases, as well as the 1  A version of this chapter has been published :  Bains OS, Karkling MJ, Grigliatti TA, Reid RE, and Riggs KW.  Two non-synonymous single nucleotide polymorphisms of human carbonyl reductase 1 demonstrate reduced in vitro metabolism of daunorubicin and doxorubicin. Drug Metab Dispos 2009; 37: 1107-1114.  Bains OS, Karkling MJ, Lubieniecka JM, Grigliatti TA, Reid RE, Riggs KW. Naturally occurring variants of human CBR3 alter anthracycline in vitro metabolism. J Pharmacol Exp Ther, 2010; 332(3): 755-763.  2  See Co-authorship statement for details of contribution of this manuscript.  77 reduction of aldehydes and ketones into the corresponding alcohols by NADPH- dependent reductases (Matsunaga et al., 2006). One group of enzymes capable of metabolizing carbonyl-containing compounds is the carbonyl reductases (CBRs).  CBRs are ubiquitously expressed in different human tissues and are considered to be of clinical importance since they play a major role in metabolism of the highly effective anthracycline drugs, daunorubicin (DAUN) and doxorubicin (DOX) (Wirth and Wermuth, 1992; Forrest and Gonzalez, 2000; Licata et al., 2000; Lakhman et al., 2005; Gonzalez-Covarrubias et al., 2007; Blanco et al., 2008). Even though DAUN and DOX are effective cancer therapies, their use is limited due to the onset of adverse side effects which are highly variable from patient to patient.  The most concerning is the development of  life-threatening cardiotoxicity since it can result in irreversible complications such as reduced left ventricular ejection fraction or congestive heart failure (Barry et al., 2007; Deng and Wojnowski, 2007; Menna et al., 2007).  The cause of the interpatient variation in DAUN- or DOX-associated adverse effects is unknown; nonetheless, one contributing factor may be the altered metabolism of these anthracyclines by allelic variants of CBR enzymes.  The variants are those arising from non-synonymous single nucleotide polymorphisms (ns-SNPs) in CBR genes. Therefore, the central focus of this study is to improve our understanding, and compare the function, of the wild-type and variant enzymes on the in vitro metabolism of DOX and DAUN.  There are a total of 10 documented ns-SNPs in the human CBR gene listed in the National Centre for Biotechnology Information Database with allele frequencies ranging from 1.7 to 62.5% in specific ethnic populations (Table 8).  While there are documented studies demonstrating the catalytic properties of the V88I variant enzyme with DAUN and V244M variant with DOX (Lakhman et al., 2005; Gonzalez-  78 Covarrubias et al., 2007; Blanco et al., 2008), none are reported for these variants in the presence of  DOX and DAUN, respectively.  Furthermore, there is no information on the catalytic properties of the 8 remaining enzyme variants with either anthracycline as substrates.  Here we investigate the wild-type and the 10 known variants of human CBR3 for the in vitro metabolism of DAUN and DOX to the corresponding carbon-13 alcohol metabolites, daunorubicinol (DAUNol) and doxorubicinol (DOXol).  Using purified, bacterially-expressed, human histidine-tagged enzymes, we demonstrate that 5 variants (CBR1: V88I and P131S; CBR3: C4Y, V244M, and V93I) had significantly reduced catalytic efficiencies (kcat/Km) compared to their corresponding wild-type enzymes.  No significant differences in kcat/Km were detected for the lone L70M variant of CBR4 with either DAUN or DOX.  In addition, we observed that DAUN is a better substrate than DOX for the wild-type and variant isoforms of CBR1 as seen with a 35 to 46-fold increase in kcat/Km values.  On the other hand, DOX was found to be a better substrate than DAUN for both CBR3 (2.3 to 4.7-fold increase in kcat/Km) and CBR4 (32 to 40-fold increase in kcat/Km). Table 8—Allele frequencies of the non-synonymous single nucleotide polymorphic variants of human CBR enzymes from different ethnic groups.  ENZYMES a VARIANTS NCBI rs- number ALLELE FREQUENCIES b  V88I rs1143663 YRI=2.1% (n=48) CBR1  (EC 1.1.1.184, EC 1.1.1.189, EC 1.1.1.197) P131S rs41557318 CEU=2.2% (n=46) P131S rs16993929 YRI=15.8% (n=120) V244M rs1056892 CEU=30.0% (n=120); HCB=33.3% (n=90); JPT=30.0% (n=90); YRI=52.5% (n=120) C4Y rs8133052 CEU=48.3% (n=120); HCB=53.3% (n=90); JPT=47.7% (n=88); YRI=23.7% (n=118) CBR3  (EC 1.1.1.1849) M235L rs4987121 YRI=2.5% (n=120)  79 L84V rs9282628 CEU=2.2% (n=46); YRI=11.8% (n=34) V93I rs2835285 CEU=1.7% (n=120) D239V rs11701643 Not available CBR4  (EC 1.-.-.-, EC 1.1.1.) L70M rs2877380 CEU=24.2% (n=120); HCB=2.2% (n=90); JPT=3.3% (n=90); YRI=62.5% (n=120)  a  Below the name of the enzyme are the Enzyme Commission (EC) numerical classification numbers, which were obtained from the Universal Protein (UniProt) database (http://www.uniprot.org/).  Based on the chemical reactions they catalyze, some of the enzymes have more than one EC number.  b  Allele frequencies were obtained from The National Center for Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov/).  The ethnic groups are designated as follows: YRI (African), CEU (European), HCB (Chinese), and JPT (Japanese).  The chromosome sample counts (n) for each variant are also given.    3.2 Methods  3.2.1 Chemicals and enzymes  Agarose, chloramphenicol, daunorubicin, doxorubicin, idarubicin, kanamycin sulfate, lysozyme, menadione, methanol, potassium phosphate (KH2PO4), RNaseI, sodium phosphate (NaH2PO4), N,N,N’,N’ tetramethylethylenediamine and NADPH were supplied by Sigma-Aldrich (St. Louis, MO).  HPLC-grade acetonitrile, agar, ammonium persulfate, formic acid, ethanol, glycine, glycerol, glacial acetic acid, imidazole, and Tris were purchased from Fisher Scientific Co. (Fair Lawn, NJ).  NaCl and yeast extract were ordered from EMD Chemicals Inc. (Darmstadt, Germany).  Bacto tryptone and isopropyl β-D-1-thiogalactopyranoside (IPTG) were obtained from BD Biosciences (Franklin Lakes, NJ) and Fermentas Inc. (Hanover, MD), respectively.  Tween 20 was purchased from EMD Biosciences (La Jolla, CA), and DNaseI was provided by Boehringer Manheim GmbH (Manheim, Germany).  Klenow fragment, T4 ligase, Factor Xa, and  80 restriction enzymes were purchased from New England Biolabs (Ipswich, MA). Doxorubicinol was obtained from Qventas Inc. (Branford, CT).  Pooled human liver cytosol was purchased from BD Biosciences (San Jose, CA).  3.2.2 Molecular cloning of human CBR genes and creation of the genetic variants  The human CBR1 wild-type coding region, which was excised from a pOTB7 recombinant plasmid (MGC-1920, American Type Culture Collection (ATCC), Manassas, VA) using BssHII (blunt end with Klenow fragment) and XhoI, was subcloned into NheI (blunt end)-XhoI sites of the pET28a prokaryotic expression vector (EMD, Novagen, San Diego, CA) with T4 ligase.  This construct gave rise to a human CBR1 enzyme with a 6x-His tag separated by an 18-amino acid residue linker on the amino terminus (Figure 20).  A Factor Xa (FXa) site was inserted at the amino terminus between the linker and CBR1 gene using the QuikChange® Site-Directed Mutaganesis Kit (Stratagene, La Jolla, CA) with the 5' - CCCCGTTCAGCCATAGAAGGAAGAATGTCGTCCGGC - 3' (forward) and 5' - GCCGGACGACATTCTTCCTTCTATGGCTGAACGGGG - 3' (reverse) primers (the FXa site is underlined in the primer sequences).  The QuikChange® polymerase chain reaction (PCR) amplification protocol for site directed mutagenesis was modified as follows: two separate 50 µl reactions (one for each primer) were subjected to 10 cycles of denaturation at 95oC for 1 min, annealing at 60oC for 1.5 min, and elongation at 68oC for 6.5 min.  A 25 µl aliquot of each PCR amplification reaction was combined with 0.75 µl PfuTurbo® DNA polymerase (Stratagene).  This reaction was subjected to 18 cycles of the same PCR protocol above.  81  Figure 20—A translated product of the pET28a-CBR1 construct with modifications to the amino terminus of AKR1A1: a 6x-His-tag followed by an amino acid linker and a Factor Xa (FXa) recognition site.  The translated product of the other pET28a-CBRs (not shown) has similar amino terminus modifications.  The human CBR3 wild-type coding region was excised from a pOTB7 recombinant plasmid (MGC-3489, American Type Culture Collection (ATCC), Manassas, VA) using BlpI (blunt end with Klenow fragment) and XhoI and subcloned into NheI (blunt end)-XhoI sites of the pET28a prokaryotic expression vector (EMD, Novagen, San Diego, CA) with T4 ligase.    This construct gave rise to a human CBR3 enzyme with an amino terminal 6x-His tag separated from the enzyme by a 15-amino acid residue linker. A Factor Xa (FXa) cleavage site was inserted at the amino terminus between the linker and CBR3 gene using the same site directed mutagenesis conditions for CBR1 with the 5' – GCTAGCTCAGGCATAGAAGGAAGAATGTCGTCCTGC – 3' (forward) and 5' – CGAGGACGACATTCTTCCTTCTATGGCTGAGCTAGC – 3' (reverse) primers (the FXa site is underlined in the primer sequences). The human CBR4 wild-type coding regions were PCR amplified from a pCMV- SPORT6 recombinant plasmid (Invitrogen) using the following primers, which contained an EcoRI adapter in the forward primers and a XhoI adapter in the reverse primers (adapters are underlined): 5' – GTACCGCTCGAATTCATGGACAAAGTGTGTGCTG – 3' (forward) and 5' – GTCTGCTAACTCGAGGTGCCCTTGATGCTAATC – 3' (reverse) for CBR4.  PCR was performed in a 50 µl reaction buffer containing 100 ng of  82 template, 200 ng of each primer, 0.2 mM dNTPs, and 1.25 units of PfuTurbo® DNA polymerase.  The amplifying conditions for PCR involved an initial denaturation step at 95oC for 1 min, followed by 35 cycles of denaturation at 95oC for 30 sec, annealing at 55oC for 1 min, and extension at 68oC for 10 min.  Subsequently, a final extension reaction was performed at 68oC for 10 min.  The CBR4 PCR product was cut with EcoRI and XhoI, and then subcloned into pET28a.  This gave rise to a human CBR4 enzyme with an amino terminal 6x-His tag as well as a 26-amino acid residue linker between the tag and enzyme.  A FXa cleavage site was inserted at the amino terminus between the linker and gene via site directed mutagenesis with the subsequent primers: 5' – CGGATCCGAATTCATAGAAGGAAGAATGGACAAAGTGTGTGC– 3' (forward) and 5' –GCACACACTTTGTCCATTCTTCCTTCTATGAATTCGGATCCG– 3' (reverse) for CBR4 (the FXa sites are underlined in the primer sequences). The pET28a-variant constructs were created by site directed mutagenesis using the QIAGEN (Mississauga, Ontario) protocol with primers listed in Supplemental Table 2 (see Appendices, page 186).  All constructs were verified by dideoxy sequencing at the University of British Columbia Nucleic Acid Protein Service unit (http://naps.msl.ubc.ca/).  3.2.3 Expression and purification of recombinant human CBR wild-type and variant enzymes  The pET constructs of the AKR wild-type and variants were heat-shock transformed into Escherichia coli BL21 (DE3) pLysS competent cells and expressed under the control of an IPTG-inducible T7 polymerase.  Cells were plated on Luria- Bertani broth agar (1% bacto-tryptone, 0.5% yeast extract, 0.5% NaCl) supplemented  83 with antibiotics (25 µg/ml chloramphenicol and 50 µg/ml kanamycin sulphate for the pET28a constructs or 100 µg/ml ampicillin for the pET15b constructs).  Colonies were randomly picked and cultured overnight at 37oC in 3 ml of Luria-Bertani broth with kanamycin and chloramphenicol at the same concentrations stated previously.  Cultures were expanded to 800 ml and grown at 37°C until an OD600 of 0.5 was reached.  IPTG was added to a final concentration of 1 mM and cells were allowed to grow for an additional 5 hrs, after which the cultures were harvested by centrifugation (4000xg for 20 min at 4oC). Expression and purification of the 6x-His tagged CBR1 and CBR3 enzymes (both wild-type and variants) were performed using the same protocols as described in Chapter 2 with the AKRs.  In the case of CBR4 wild-type and the L70M variant, the expression protocol was similar to that of CBR1 and CBR3 (starting with the heat shock transformation of the pET construct up to the bacterial culture harvestation by centrifugation); however, the purification protocol was different.  The harvested cells were resuspended in Buffer B (100 mM NaH2PO4, 10 mM Tris-Cl, pH 8.0) with 8 M urea for lysis.  The extracted CBR4 and L70M proteins were subjected to purification by Ni-NTA chromatography under denaturing conditions according to the QIAGEN protocol.  In the end, CBR4 and L70M were eluted using multiple fractions of Buffer B with decreasing pH levels (6.3, 5.9 and 4.5).  The eluted fractions were then dialyzed at 4oC to gradually remove the urea (Buffer B with 6 M, 4 M, 2 M and 1 M urea for 2 hrs each followed by 0 M urea overnight). The protocols for protein purity assessment and Western blotting were similar to that of the AKR study (section 2.2.3, pages 47-50 in thesis).  However, for Western blotting, different primary monoclonal antibodies were used: a monoclonal mouse anti-  84 human CBR1 antibody (Abnova® Corporation, Taipei City, Taiwan) (diluted 1:3000), as well as MaxPab polyclonal mouse anti-human CBR3 and CBR 4 antibodies (Abnova®) (diluted 1:2500).  3.2.4 Kinetic analysis of CBR wild-type and variant enzymes  The enzyme activities of the purified 6x-His-tagged CBR wild-type and variant enzymes were measured at 37°C using a Fluoroskan Ascent® FL fluorometer (Thermo Fisher Scientific, Waltham, MA) by following the initial rate of NADPH oxidation at excitation and emission wavelengths of 355 and 460 nm, respectively.  The assays were conducted as described previously using menadione as the test substrate (Lakhman et al., 2005; Gonzalez-Covarrubias et al., 2007; Endo et al., 2008).  In brief, purified protein (3 µg) was incubated with NADPH (1 mM for CBR1 and CBR3; 0.2 mM for CBR4) and menadione (CBR1: ranging from 20 to 150 µM; CBR3: 20-100 µM; CBR4: 5-500 µM) in a reaction mixture of 150 µl of 100 mM potassium phosphate, pH 7.4.  Protein amount and incubation times were selected for each enzyme and substrate concentration to ensure that measured rates were in the linear range of the enzyme kinetic curve.  In these assays, the concentration of 95% ethanol, which was required to dissolve the substrate, was below 4% (v/v) in the final reaction mixture.  Readings were collected at 20-sec intervals for 1.5 hrs with shaking between each reading.  Maximal rates were calculated from the Ascent program (version 2.6) using a 5-min interval (15 total readings) with the steepest slope.  Enzymatic activity (nanomoles of NADPH consumed per minute per milligram of purified protein) was calculated from these rates using a standard curve constructed from the fluorescence measurements of solutions of known NADPH concentrations.  85 Activity measurements for the reduction of the anthracyclines were performed by incubating either DOX or DAUN (CBR1: 10 to 400 µM; CBR3 and CBR4: 10 to 700 µM) with purified enzyme (3 µg) for 30 min in a total volume of 150 µl buffer containing 100 mM potassium phosphate, pH 7.4, and 1 mM NADPH at 37°C.  The samples were mixed at 250 rpm. Protein concentrations were based on the Bradford protein assay using bovine serum albumin as a standard.  The reaction was stopped by adding 300 µl of ice- cold acetonitrile, which contained idarubicin as an internal standard, followed by vortex mixing and centrifugation at 10,000xg for 10 min at 4°C to remove protein.  The supernatant was removed for high performance liquid chromatography (HPLC) analysis. The procedures for HPLC separation and fluorescence detection of DOX and DAUN and their carbon-13 hydroxy metabolites, DOXol and DAUNol, were carried out as previously described (Bains et al., 2008). The kinetic constants of Vmax and Km were determined by fitting the rate measurement data using nonlinear least-squares fitting to a Michaelis-Menten hyperbola (GraphPad Prism version 4.0; GraphPad Software Inc., San Diego, CA).  The turnover values (kcat) were calculated from Vmax values using the apparent molecular weight for the 6x-His-tagged CBR and variant proteins of 34 kDa (CBR1 and CBR3) or 29.6 kDa (CBR4).  The values for kcat/Km were also calculated.  Following Michaelis-Menten data analysis, Eadie-Hofstee plots were generated to check for deviation from linearity with changing substrate concentrations.  3.2.5 Statistical analysis   Statistical analyses were performed using the same protocol as described in the AKR study (section 2.2.6, page 53 of thesis) with results expressed as means ± S.D and  86 enzyme activities compared using a one-way analysis of variance followed by a Tukey- Kramer multiple comparisons test.  Differences were considered significant at p<0.05. Sample sizes (n) for the following experiments with the CBR wild-type isoforms and variants were as follows: determination of Michaelis-Menten kinetic parameters using menadione as substrate (n=9), determination of kinetic parameters using DAUN as substrate (n=9), and determination of kinetic parameters using DOX as substrate (n=9).  3.3 Results  3.3.1 Expression and purification of the human CBRs  The expression of the 6x-His-tagged recombinant human CBR wild-type enzyme was confirmed by Western blot analysis, which showed a band with mobility corresponding to the calculated molecular mass of the tagged CBR (34 kDa for CBR1, 34 kDa for CBR3, and 29.6 kDa for CBR4) (Figure 21).  Total protein staining of the SDS- PAGE gel demonstrated that the wild-type fraction was purified from its transformed bacterial lysate as no other proteins were detected (Figure 21).  For the CBR1, and CBR3 wild-type and variant enzymes, a majority of the pure enzyme was recovered in the 250 mM imidazole elution fractions; no further protein was eluted with higher imidazole concentrations.  For the CBR4 wild-type and variant enzymes, the majority of the pure enzyme was recovered in pH 4.5 elution fractions following protein purification under denaturing conditions with 8 M urea.  The results for the expression and purification of the variant forms of each enzyme paralleled that of the corresponding wild-type enzyme (Supplemental Figure 5; see Appendices, page 187).   87  Figure 21—Purification of human recombinant 6x-His-tagged wild-type enzymes: (A) CBR1, (B) CBR3, and (C) CBR4.  (Left) Gel stained with SYPRO® Ruby following SDS-PAGE showing purified protein fraction (lane 3; 2 µg), free of contaminating proteins from the bacterial lysate (lane 1; 10 µg total protein). Removal of contaminating proteins is observed in flow through fraction from Qiagen purification procedures [Ni-NTA column flow through (lane 2; 10 µg total protein)].  (Right) Western blot detection of transformed lysate (lane 6) and purified protein fractions (lane 8), confirms expression of the desired CBR protein.  Little immunoreactivity was detected in the flow through fraction (lane 7) suggesting that majority of the enzyme was bound to the Ni-NTA resin prior to their elution.  GST-tagged human CBR4 recombinant protein (Abnova® Corporation, Taipei City, Taiwan; lane 5; 2 µg total protein) and human liver cytosol (lane 5; 20 µg total protein; for CBR1 and CBR3) was used as positive controls for antibody immunoreactivity for these enzymes.  No antibody immunoreactivity is observed for untransformed bacterial lysate (lane 4; 10 µg total protein).  M refers to the molecular weight markers.  3.3.2 Kinetic characterization of CBR wild-type and variant enzymatic activities with menadione  Before running the kinetic assays with DAUN and DOX, the human CBR wild- type and variant enzymes were subjected to assays with test substrates in order to confirm that they were active following purification by comparing enzymatic activity values with published studies.  Another reason to perform these assays was to determine which variant enzymes exhibit significantly altered activity compared to the wild-type.  This  88 information is important since we would expect that these variants are capable of altering metabolism of DAUN and DOX. For the CBR wild-type and variant enzymes, menadione was used as the test substrate, and Michaelis-Menten kinetic parameter values [maximal reaction velocity (Vmax), substrate affinity (Km), turnover rate (kcat), and kcat/Km] were determined and compared with published values (Table 9).  The Vmax for the CBR1 wild-type enzyme in this study is approximately two-fold higher than the value in the literature (Gonzalez- Covarrubias et al., 2007) for bacterially expressed recombinant human 6x-His-tagged CBR1.  Reasons for this discrepancy between these two studies include: (i) greater CBR1 protein activity following purification in our study, as well as (ii) the use of a more sensitive method for measuring the rate of NADPH oxidation (fluorescence) in our study versus UV-visible spectrophotometry, which was used in the Gonzalez-Covarrubias study.  In relation to the reported studies for the CBR3 wild-type enzyme, there were discrepancies reported for kinetic parameter values (Vmax, Km, kcat, and kcat/Km) between two studies (Table 9) (Lakhman et al. 2005; Miura et al., 2008).  When comparing the kinetic parameter values in these two studies, menadione is metabolized more readily by CBR3 in the Lakhman study.  The parameter values obtained in our study were consistent with the Miura study, even though both studies used the same assays conditions provided by the Lakhman group.  To test if CBR3 activity would increase, the menadione assays in our study were performed with higher concentrations of cofactor (1.5 mM and 2 mM); however, the kinetic parameter values did not differ from those reported in the study with 1 mM NADPH.  Taken together, menadione is able to be metabolized by CBR3; however, not as efficiently as claimed by the Lakhman group.  With the CBR4 wild-type enzyme, the kinetic parameter values that were obtained in this study for menadione were  89 consistent with those reported in Endo et al. (2008).  Overall, the CBR1 enzyme exhibited the greatest capability of metabolizing menadione (kcat/Km: 17400±2800), followed by CBR4 (kcat/Km: 5670±650), and CBR3 (kcat/Km: 1320±290).  Table 9—Michaelis-Menten kinetic parameters for test substrate menadione by recombinant 6x-His tagged CBR wild-type and variant allele enzymes.    KINETIC PARAMETERS ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km (s-1 M-1) CBR1  582±43 20±6 0.33±0.02 17400±2800 REPORTED:  220±27 [1] c N/A N/A N/A V88I 300±9* 21±2 0.17±0.02* 8090±710*  P131S 561±43 40±5* 0.32±0.06 7950±900* CBR3  170±29 76±23 0.096±0.014 1320±290 REPORTED:  19600±2000 [2] c 25±3 [2] c 9.9 [2] c 402000 [2] c REPORTED:  126 b [3] c 54±10 [3] c 0.071 [3] c 1300 [3] c P131S 145±22 64±10 0.082±0.013 1280±248 V244M 90±10* 134±6* 0.051±0.007* 381±42* C4Y 85±5* 140±7* 0.048±0.004* 343±48* M235L 158±31 65±13 0.090±0.018 1380±371 L84V 164±26 71±14 0.093±0.015 1310±345 V93I 96±9* 142±8* 0.054±0.006* 380±51*  D239V 171±29 80±11 0.097±0.016 1210±253 CBR4  543±41 47±9 0.27±0.02 5670±650 REPORTED:  508 b [4] c 36 [4] c 0.21 [4] c 5833 [4] c  L70M 525±37 49±10 0.26±0.02 5330±543  Values correspond to the mean ± S.D obtained from three experiments performed with three independent enzyme preparations (n=9) for each isoform.  Reported parameter values for the wild-type enzymes are also given for comparison purposes. * Variants significantly different from their respective wild-type enzymes (p<0.05) a    kcat calculated for 6x-His tagged CBRs from Mr 34000 (CBR1), 34000 (CBR3),  and 29600 (CBR4) b   Calculated Vmax based on other parameter values given in study c   [1]=Gonzalez-Covarrubias et al., 2007; [2]=Lakhman et al., 2005; [3]=Miura et al., 2008; [4]=Endo et al., 2008 N/A=No value available from the study   90 Some of the CBR variants were found to decrease activity significantly compared to their respective wild-type enzymes (n=9): a 54% reduction in kcat/Km for both the V88I and P131S variants (CBR1) as well as a 71-74% decrease for the V244M, C4Y, and V93I variants (CBR3).  There was no significant difference in activity between the CBR4 wild- type and the L70M variant (n=9).  The kcat/Km value was primarily used for comparison between the variants and wild-type enzymes since it incorporates Vmax, Km, and kcat; thus, making it a better measure of enzyme activity. The 6x-His tag and amino acid linker were removed with Factor Xa (FXa), as described in Chapter 2, in order to see if this modification on the amino terminus of the enzyme disrupted activity in our preparation (Figure 22).  This was not the case since the kinetic parameters did not differ significantly from the tagged enzyme [untagged CBR1: Vmax (489±38 nmol/min•mg), Km (22±5 µM), kcat (0.28±0.02 s-1), and kcat/Km (12600±2100 s-1M-1); untagged CBR3: Vmax (149±31 nmol/min•mg), Km (60±15 µM), kcat (0.084±0.016 s-1), and kcat/Km (1410±400 s-1M-1); untagged CBR4: Vmax (483±39 nmol/min•mg), Km (58±7 µM), kcat (0.24±0.02 s-1), and kcat/Km (4140±780 s-1M-1)] (all n=9) .  Therefore, we deemed it not necessary to cleave off the tag and linker from the wild-type and variant enzymes for the subsequent assays involving DAUN and DOX.  91  Figure 22—Representative Western blot detection of purified 6x-His tagged CBR proteins [(A) CBR1, (B) CBR4, and (C) CBR4 wild-type enzymes; lane 2; 3 µg] and native AKR proteins (lane 3; 3 µg).  The 6x- His tagged proteins were incubated with Factor Xa for 6 hrs at 23oC to allow for removal of the tag and linker from the amino terminus.  GST-tagged human CBR4 recombinant protein (Abnova® Corporation, Taipei City, Taiwan; lane 1; 2 µg total protein) and human liver cytosol (lane 1; 20 µg total protein; for CBR1 and CBR3) were used as positive controls for antibody immunoreactivity for these enzymes.  M refers to the molecular weight markers.   3.3.3 Kinetic characterization of wild-type and variant enzymatic activities with DOX and DAUN  To evaluate the impact of the single amino acid substitutions in the human CBR enzymes on the reduction of the anthracycline drugs, we measured the formation of the major alcohol metabolites in vitro, as performed in the AKR study (Chapter 2).  Full chromatographic resolution of DAUNol and DOXol from DAUN and DOX, respectively, and idarubicin (internal standard) was achieved for all chemical standards and in vitro samples.  DOXol, DOX, DAUNol, DAUN, and idarubicin were observed to elute at 4.6, 5.5, 6.1, 6.9, and 7.4 min, respectively (Figure 23).  There were no detectable peaks at the DAUNol or DOXol retention time in the absence of the CBR proteins.   92  Figure 23—Generation of DOXol and DAUNol in vitro by purified CBR3 incubated with DOX (top panel), and purified CBR1 incubated with DAUN (bottom panel).  Measurement of DOXol and DAUNol was performed using HPLC-fluorescence.  Representative chromatograms show clear resolution of DOXol and DAUNol from DOX, DAUN, and idarubicin (IDA, internal standard).  Retention times observed for DOXol, DOX, DAUNol, DAUN, and IDA are 4.6, 5.5, 6.1, 6.9, and 7.4 minutes, respectively.  93  Michaelis-Menten kinetic curves were generated for the CBR wild-types (Figure 24) and each of the variant enzymes in the presence of differing concentrations of DAUN, ultimately leading to the determination of kinetic parameter values (Table 10).  A total of 5 allelic variants of CBR1 and CBR3 exhibited significant reductions in enzymatic activity with DAUN compared to their respective wild-type enzymes: a 50 and 58% reduction in kcat/Km for the V88I and P131S variants of CBR1, respectively [this reduction is due to a decrease in Vmax and kcat (36% for both parameters) for V88I and an increase in Km (93%) for P131S; n=9]; and a 29 to 43% reduction in kcat/Km for the C4Y, V93I, and V244M variants of CBR3 [this reduction due to corresponding decreases in Vmax (22-43%) and kcat (21-43%) for all variants; n=9].    Figure 24—In vitro enzymatic activities for the purified 6x-His tagged (A) CBR1, (B) CBR3, and (C) CBR4 wild-type and variant enzymes with daunorubicin.  Activities were measured by following the rate of daunorubicinol production.  Three independent batches of each enzyme were purified and assays were performed in triplicate with each batch.  Enzymatic activities are reported as mean ± S.D. (n=9).  Dotted lines refer to variants that have significant differences in kinetic parameter values compared to the wild- type.   94 Table 10—Kinetic constants for DAUN metabolism by recombinant 6x-His tagged CBR wild-type and variant enzymes.  ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km            (s-1 M-1) CBR1  2990±245 57±15 1.69±0.14 31500±3580 V88I 1900±100* 68±8 1.08±0.06* 15600±2800*  P131S 2540±150 110±10* 1.44±0.09 13090±3460* CBR3  166±5 461±25 0.094±0.003 204±13 P131S 157±15 503±88 0.088±0.009 180±24 V244M 130±9* 587±75 0.074±0.005* 128±22* C4Y 95±7* 471±63 0.054±0.004* 116±19* M235L 149±14 524±91 0.084±0.008 165±33 L84V 161±8 499±50 0.091±0.005 185±28 V93I 120±7* 472±47 0.068±0.004* 145±16*  D239V 156±7 454±38 0.088±0.004 197±19 CBR4  9±1 673±94 0.0044±0.0007 7±2  L70M 10±1 664±86 0.0049±0.0007 7±2  Values correspond to the mean ± S.D obtained from three experiments performed with three independent enzyme preparations (n=9) for each isoform. * Variants significantly different from their respective wild-type enzymes (p<0.05) a   kcat calculated from Mr 34000 (CBR1), 34000 (CBR3), and 29600 (CBR4)   With DOX as a substrate (Figure 25; Table 11), the same aforementioned variants of CBR1 and CBR3 demonstrated significant reductions in enzymatic activity with respect to the wild-type enzymes: a 43 and 45% reduction in kcat/Km for both the V88I and P131S variants of CBR1, respectively [this reduction is due to a corresponding decrease in Vmax (32%) for V88I and an increase in Km (54%) for P131S; n=9]; and a 41 to 66% reduction in kcat/Km for the C4Y, V93I, and V244M variants of CBR3 [this reduction is due to corresponding decreases in Vmax and kcat (25-34% for both parameters) for all variants along with an increase in Km (120%) for V93I; n=9].  When compared against the CBR4 wild-type enzyme, there were no significant differences detected in any of the kinetic parameters for the L170M variant with either anthracycline.  95    Figure 25—In vitro enzymatic activities for the purified 6x-His tagged (A) CBR1, (B) CBR3, and (C) CBR4 wild-type and variant enzymes with with doxorubicin.  Activities were measured by following the rate of doxorubicinol production.  Three independent batches of each enzyme were purified and assays were performed in triplicate with each batch.  Enzymatic activities are reported as mean ± S.D. (n=9). Dotted lines refer to variants that have significant differences in kinetic parameter values compared to the wild-type.    Table 11—Kinetic constants for DOX metabolism by recombinant 6x-His tagged CBR wild-type and variant enzymes.  ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km            (s-1 M-1) CBR1  319±29 273±47 0.18±0.02 682±77 V88I 218±19* 310±15 0.12±0.02 390±60*  P131S 280±28 421±28* 0.16±0.02 377±71* CBR3  466±22 278±30 0.264±0.013 965±151 P131S 439±24 317±38 0.249±0.013 797±121 V244M 334±16* 311±33 0.189±0.009* 567±47* C4Y 308±10* 382±25 0.175±0.006* 458±27* M235L 345±23* 270±42 0.196±0.014* 745±151 L84V 452±24 310±36 0.256±0.013 842±130  V93I 352±16* 613±48* 0.199±0.009* 327±24*  96 ENZYMES VARIANTS Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1) a kcat /Km            (s-1 M-1) D239V 432±35 334±46 0.245±0.020 743±116 CBR4  63±8 139±16 0.031±0.005 223±55  L70M 71±9 125±19 0.035±0.004 280±61  Values correspond to the mean ± S.D obtained from three experiments performed with three independent enzyme preparations (n=9) for each isoform. * Variants significantly different from their respective wild-type enzymes (p<0.05) a    kcat calculated from Mr 34000 (CBR1), 34000 (CBR3), and 29600 (CBR4)  3.4 Discussion  The main goal of this in vitro study was to examine the effect of ns-SNPs on the metabolic activities of human CBR1, CBR3, and CBR4 enzymes using menadione as a test substrate, as well as for the anthracyclines DAUN and DOX.  The wild-type and naturally occurring variant alleles of the human CBR genes were expressed in bacteria, and then purified by Ni-NTA affinity chromatography.  As seen in the AKR study, the removal of the 6x-His tag and amino acid linker from the CBR wild-type enzymes did not influence enzyme activity in the presence of menadione.  Therefore, in the ensuing assays with the anthracyclines, the 6x-His tagged enzymes (both wild-type and variants) were used to assess the impact of the single amino acid substitutions on the ability of the enzyme to metabolize DOX and DAUN to their corresponding alcohols DOXol and DAUNol, respectively.  Our assays demonstrated that both DOX and DAUN are readily converted to their respective alcohol metabolites by the wild-type and variants enzyme for the CBRs examined in this study. Out of the 10 allelic variants that were examined in this study, 5 were found to significantly decrease metabolism of both DOX and DAUN compared to their respective wild-type enzymes: the V88I and P131S variant forms of CBR1, and the C4Y, V93I, and V244M variant forms of CBR3.  To our knowledge, this study is the first to (i) look at the  97 effect of the CBR1, CBR3, and CBR4 variant enzymes on DAUN and DOX metabolism [except for V244M since and earlier study by Blanco et al. (2008) demonstrated a significant reduction in DAUNol production compared to the wild-type], and (ii) demonstrate that human CBR3 metabolizes DAUN and CBR4 metabolizes both anthracyclines, in vitro. The finding in this study that DOX is metabolized by the CBR3 wild-type was corroborated by Blanco et al. (2008); however, the metabolic activity of our human CBR3 was considerably higher.  Both studies were in disagreement with an in vitro study by Kassner et al. (2008), which suggested that their histidine-tagged human CBR3 does not metabolize DOX.  The reason for the discrepancy between these results is not known. In relation to the CBR variant, V88I, our enzymatic studies with this enzyme in the presence of DAUN is consistent with the study by Gonzalez-Covarrubias et al. (2007), which used cofactor (NADPH) consumption to demonstrate that the Vmax for DAUN metabolism was significantly decreased in the V88I variant compared to the wild- type enzyme.  While co-factor usage is an indirect test of substrate conversion, they further confirmed this kinetic difference by directly measuring DAUNol levels using HPLC-fluorescence at a single DAUN concentration (500 µM), which showed the variant enzyme produced 47% less metabolite than that of the wild-type.  These authors suggested that the V88I mutation has an impact on NADPH binding affinity due to its close proximity to the cofactor site (Figure 26a).  Their finding demonstrates that the valine to isoleucine substitution leads to a lower affinity for the cofactor.  Since NADPH is a vital cofactor in the metabolic conversion of DOX and DAUN to their major alcohol metabolites, this might be the basis for the significant decrease in the levels of DOXol and DAUNol produced with the V88I variant enzyme.  98 In addition, the P131S mutation (Figure 26a) may alter the structural conformation of the cofactor and/or active site of CBR1, which would explain the significant differences seen in the metabolism of both anthracyclines compared to the wild-type enzyme.  The distinctive cyclic structure of proline's side chain is an important structural property, which contributes to the precise three-dimensional shapes of proteins. Proline's linkage to other amino acids through the amino group contributes to various bends and kinks in the shape of the protein, without which the protein could not function properly (Duclohier, 2004; Fu et al., 2009; Moroder and Budisa, 2010).  Therefore, the substitution of proline with a serine may disrupt the folding of the CBR1 enzyme, ultimately affecting the active and cofactor binding sites. With human CBR3, 3 of the 7 allelic variants (C4Y, V93I, and V244M) were found to have significantly altered DOX and DAUN metabolism in our studies.  The locations of these alleles are shown in a three-dimensional model of the CBR3 enzyme (Figure 26b), along with the residues involved in catalysis: tyrosine-194, serine-140, lysine-198, and asparagine-114 (Jornvall et al., 1995; Filling et al., 2002).  These are the same residues for catalysis with human CBR1.  In the reduction of the carbonyl- containing substrate, the tyrosine-194 residue has two functions: (i) it forms a hydrogen bond with the substrate carbonyl, resulting in carbonyl polarization, which accelerates the hydride transfer of the pro-R hydrogen from the nicotinamide ring of NADPH cofactor to the carbonyl carbon of the substrate, and (ii) it acts as a proton donor for the substrate (Figure 27) (Ghosh et al., 1994; Hoffmann and Maser, 2007).  Serine-140 serves to stabilize the substrate via hydrogen bonding, which facilitates proton and hydride transfer from the conserved tyrosine and cofactor, respectively (Grimm et al., 2000).  In addition, the hydrogen-bonding network provided by lysine-198 and asparagine-114 serves to  99 lower the pKa of tyrosine, making the proton transfer easier. (Ghosh et al., 1994; Auerbach et al., 1997; Benach et al., 1999; Hoffmann and Maser, 2007).  After the proton transfer from tyrosine-194 and hydride transfer from NADPH, the reduced carbonyl substrate then dissociates, and a net charge on the tyrosinate anion is stabilized by the hydrogen bonding network of lysine-198 and asparagine-114.  The conserved tyrosine can be regenerated from the tyrosinate anion through the donation of a hydrogen atom by the surrounding solvent or by serine-140 (Ghosh et al., 1994; Duax et al., 2000; Hoffman and Maser, 2007).    Figure 26—Three-dimensional molecular structure of human (A) CBR1 and (B) CBR3 wild-type enzymes complexed with the cofactor, NADP+ (green) [Protein Data Bank ID: 3BHI (CBR1) and 2HRB (CBR3)]. The mutations that significantly altered enzyme activity are shown (purple) as well as those that did not alter enzyme activity (red).  For CBR3, since the amino acid sequence begins at position 5 with serine, there is no C4Y ns-SNP illustrated.  In addition, the residues comprising the catalytic tetrad are illustrated (blue) [CBR1 and CBR3: (1) tyrosine-194, (2) lysine-198, (3) asparagine-114, and (4) serine-140].  The molecular graphic images of the CBRs were produced using the UCSF Chimera program (Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA).    100   Figure 27—A proposed catalytic mechanism for CBR-mediated reduction reaction (see text on pages 98 to 99 for details).  This figure is modified based on the scheme provided by Hoffmann and Maser (2007).  The numbering of the catalytic residues (tyrosine, lysine, asparagine, and serine) follows that of the human CBR1 and CBR3 wild-type enzymes.   101 Of the mutations significantly affecting DAUN and DOX metabolism, only V93I is physically located in close proximity to the catalytic and cofactor binding sites.  The change from valine to isoleucine at this position has been proposed to disrupt side-chain interactions with asparagine-114 (Pilka et al., 2006).  This disruption to the active site may lead to decreased metabolism of DOX and DAUN.  Further studies are needed to provide a more definitive explanation on how the other variants alter CBR3 activity. Besides looking at the differences in enzyme activity between the wild-type and variant enzymes with either DAUN or DOX, our studies also demonstrated that DOX is a better substrate than DAUN for both the wild-type and variant isoforms of human CBR3 and CBR4, as shown by increases in kcat/Km of 2.3 to 4.7-fold and 32 to 40-fold, respectively.  The reverse is true for human CBR1 with DAUN being the better substrate than DOX (35 to 46-fold increase in kcat/Km for the wild-type and variants). In conclusion, this study demonstrates that the 6x-His tagged CBR enzymes are able to metabolize DAUN and DOX.  Significant reductions in enzyme activity were discovered in five variant isoforms, which may contribute to the inter-patient variability seen with the development of serious cardiac side effects in patients treated with either DOX or DAUN.  If these reductases play a major role in anthracycline-induced cardiotoxicity, we propose that this condition is largely the result of accumulation of the parent drug.  The data collected in this study begs the question of whether individuals bearing one or more of the CBR polymorphisms are at higher risk for developing cardiac side effects after treatment with either of these anthracyclines. This issue can be addressed with clinical association studies, which are currently underway in our laboratory to determine whether there is a correlation with chronic cardiotoxicity.  We realize that there are single nucleotide polymorphisms (SNPs) in the non-coding regions  102 of the human CBR genes, including untranslated regions, introns, and promoter regions, which may influence the amount of protein produced.  Even though a study by Zhang and Blanco (2009) found that two common SNPs in the CBR3 promoter [-725 T>C (rs2239566, q=12.7-22.5%) and -326 T>A (rs8132243, q=2.4-17.5%)] did not modify gene promoter activity or significantly alter hepatic CBR3 mRNA levels compared to the wild-type, there are a number of common SNPs in the non-coding regions that remain to be investigated.  The clinical association studies will examine these SNPs as well as the ns-SNPs in the human CBR enzymes to see if there is a correlation with chronic cardiotoxicity.                               103 CHAPTER 4: EX VIVO AND IN VITRO STUDIES SUGGEST A NEGATIVE ASSOCIATION BETWEEN CYTOTOXICITY AND METABOLISM OF THE ANTHRACYLINES DAUNORUBICIN AND DOXORUBICIN BY ALDO-KETO AND CARBONYL REDUCTASES   4.1 Preface  Daunorubicin (DAUN) and doxorubicin (DOX) are two of the most effective antineoplastic agents ever developed (Licata et al., 2000; Lakhman et al., 2005; Blanco et al., 2008).  Conversely, their usage is often associated with considerable inter-patient variability in the onset of life-threatening adverse cardiotoxic events (Wojtacki et al., 2000; Mordente et al., 2001; Danesi et al., 2002; Barry et al., 2007; Deng and Wojnowski, 2007; Menna et al., 2007).  One possible cause of this variation could be disparity in the rate at which these drugs are metabolized, among patients subjected to them.  Two groups of enzymes that have been implicated in the metabolism of DAUN and DOX are the aldo-keto reductases (AKRs) and carbonyl reductases (CBRs) (Cummings et al., 1991; Jin and Penning, 2007). Currently, there is disagreement on the role that drug metabolism plays in generating the DAUN- and DOX-associated toxicity.  Some studies suggest that the major metabolites, daunorubicinol (DAUNol) and doxorubicinol (DOXol), are responsible for the adverse effects.  For example, Olson et al. (2003) observed that inhibition of CBR1 blocks DOX-induced cardiotoxicity in mice.  Similarly, a study by Forrest et al. (2000) demonstrated that transgenic mice, in which human CBR1 had been overexpressed in the heart, exhibited high levels of intracardiac DOXol and increased signs of myocardial damage after DOX administration.  Furthermore, Behnia and Boroujerdi (1999) reported that when DOX was administered to rats, those pre-treated  104 with an AKR inhibitor showed no signs of cardiotoxicity, while the ones that received no pre-treatement exhibited some forms of cardiotoxicity. On the other hand, there are studies suggesting the parent drug is more toxic.  For example, Veitch et al. (2009) showed that a DOX-resistant MCF-7 breast cancer cell line had a 2.17-fold higher DOXol production than wild-type cells.  Furthermore, the introduction of an AKR1C inhibitor dramatically altered the DOX-associated toxicity in this resistant cell line, reducing it to a level that was comparable to that of the wild- type.  A study by Ax et al. (2000) revealed an 8-fold increase in LC50 values of DAUN in DAUN-resistant human stomach carcinoma cells compared to wild-type cells.  DAUNol production in the resistant cell line was 6-fold higher and, based on finding significantly elevated levels of CBR1, AKR1B1, and AKR1C2 mRNAs in the resistant cell line, the authors suggested that resistance may be associated with increased DAUN metabolism. Furthermore, in human erythroleukemia CBR1 transfected cells that were subsequently treated with DAUN, CBR1 activity (conversion of DAUN to DAUNol) increased 83-fold and was associated with a 2- to 3-fold reduction in cytotoxicity compared to non- transfected cells (Gonzalez et al., 1995). This controversy prompted us to determine whether there is a consistent association between DAUN/DOX metabolism, by AKRs and CBRs, and cellular toxicity.  Eight human carcinoma cell lines and one rat embryonic cardiac cell line were chosen for this study.  Ex vivo cytotoxicity studies demonstrated that all cell lines were 100% viable to begin with (0 hr incubation time period).  In the presence of DAUN or DOX for 6, 24, and 48 hrs, four of the cell lines [HepG2 (liver), NCI-H460 (lung), HCT- 15 (colon) and A-498 (kidney)] were more tolerant of the toxic effects of these drugs, based on their significantly higher LC50 values, than the five remaining cell lines [H9c2  105 (heart), PC-3 (prostate), PANC-1 (pancreas), OVCAR-4 (ovary), and MCF-7 (breast)], which were categorized as the sensitive cell lines.  These studies were repeated using DAUNol and DOXol at the 48 hr incubation time period, and LC50 values for these compounds were found to be significantly higher than those for the parent drugs, thus suggesting that the metabolites are less toxic. In vitro metabolic studies were performed with extracted cytosolic fractions of the cell lines following pre-treatment with 100 nM DAUN and DOX separately for 0, 6, 24, and 48 hrs.  These studies revealed the following: (i) at 0 hrs, the tolerant cell lines metabolized DAUN and DOX to their major metabolites more efficiently compared to the sensitive cell lines, and (ii) there were similar incremental increases in enzyme activity for all the cell lines following 6, 24, and 48 hrs incubation with either anthracycline.  One likely hypothesis for these findings is that the tolerant cell lines have a greater abundance of one or more of the cytosolic AKR and CBR enzymes.  Previous in vitro studies suggest that the following enzymes are able to metabolize DAUN and/or DOX: AKR1A1, AKR1B1, AKR1B10, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR7A2, CBR1, and CBR3 (Ohara et al., 1995; O’Connor et al., 1999; Martin et al., 2006; Kassner et al., 2008; Bains et al., 2008; Bains et al., 2009; Bains et al., 2010a; Bains et al., 2010b).  To begin, at the 0 hr incubation time period, the cytosolic expression levels of these enzymes in the tolerant cell lines were significantly greater in abundance compared to the sensitive group.  Next, DAUN and DOX were found to induce the expression of the enzymes (focus on AKR1C3 and CBR1) by similar increments in all the cell lines treated for 6, 24, and 48 hrs.  The induction of the reductases in response to DAUN/DOX exposure at 6, 24, and 48 hrs correlated with the increases in enzyme activity seen for all the cell lines.  Overall, there was a negative  106 relationship between DAUN/DOX-induced cytotoxicity and AKR/CBR-mediated metabolism of DAUN/DOX to DAUNol/DOXol.  4.2 Methods  4.2.1 Chemicals and enzymes  Daunorubicin, doxorubicin, dimethyl sulfoxide (DMSO), 100X antibiotic/antimycotic, potassium phosphate (KH2PO4), 3-(4,5-dimethythiazol-2-yl)-2,5- diphenyl tetrazolium bromide (MTT), N,N,N',N'-tetramethylethylenediamine, sodium chloride (NaCl), sodium monobasic phosphate (NaH2PO4), Tween® 20, and β- Nicotinamide adenine dinucleotide 2′-phosphate reduced tetrasodium salt (NADPH) were provided by Sigma-Aldrich (St. Louis, MO).  Doxorubicinol and daunorubicinol were obtained from SynFine Research (Richmond Hill, Ontario).  High performance liquid chromatography (HPLC)-grade acetonitrile, ammonium persulfate, tetramethylethylenediamine, formic acid, glycine, glycerol, and Tris were purchased from Thermo Fisher Scientific (Waltham, MA).  Phosphate-buffered saline (PBS, pH 7.4) was ordered from InvitrogenTM Corporation (Carlsbad, CA).  Fetal bovine serum albumin was supplied by the American Type Culture Collection (Manassas, VA).  4.2.2 Cell culture OVCAR-4 (ovarian), NCI-H460 (lung), and PANC-1 (pancreas) human carcinoma cell lines were kindly provided Dr. Thomas Hamilton (Fox Chase Cancer Center, Jenkintown, PA), Dr. Urs Häfeli’s laboratory (Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia), and Dr. Sylvia Ng’s laboratory (Faculty of Pharmaceutical Sciences, University of British Columbia),  107 respectively.  The H9c2 rat heart embryonic cell line, as well as HepG2 (liver), A-498 (kidney), MCF-7 (breast), PC-3 (prostate), and HCT-15 (colon) human carcinoma cell lines were obtained from the American Type Culture Collection.  HepG2, A-498 and MCF-7 cells were cultured in Eagle's minimum essential medium.  H9c2 and PANC-1 cells were maintained in Dulbecco’s modified Eagle’s medium, while the PC-3 cells were cultured with F-12K medium.  OVCAR-4, NCI-H460, and HCT-15 cells were maintained in RPMI-1640 medium.  All cells were supplemented with 10% fetal bovine serum and 1X antibiotic/antimycotic.  Cells were grown on BD Falcon™ cell culture dishes (100 mm x 20 mm; BD Biosciences, Mississauga, Ontario) and maintained in a humidified incubator with 5% CO2 at 37°C. 4.2.3 MTT cell viability assay to measure cytotoxicity  Cells were seeded at densities of approximately 50-70% in NunclonTM 48-well cell culture plates (Thermo Fisher Scientfic) and were allowed to attach overnight in a humidified incubator with 5% CO2 at 37°C.  The next day, cells were treated with varying concentrations of DAUN or DOX (0, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1, 2, 5, 10, 25, 50, 100, and 150 µM) for specified time periods (6, 24, and 48 hrs post-incubation). After treatment for each of the time periods, MTT solution [3-(4,5-dimethythiazol-2-yl)- 2,5-diphenyl tetrazolium bromide; 5 mg/mL in PBS, pH 7.4] was added (62.5 µl/well), and the plates were incubated for another 4 hrs at 37oC.  This assay measures the ability of live cells to reduce MTT to an insoluble, colored (dark purple) formazan product by mitochondrial succinate dehydrogenase.  Following the 4 hr incubation period, cells were solubilized by DMSO and absorbance values of the formazan product were measured at 570 nm (and 37°C) using a monochromator-based SynergyTM Mx multi-mode microplate  108 reader with Ultra Fine-TunedTM performance.  Absorbance values were recorded using the Gen5TM version 1.08.4 software program (BioTek Instruments, Inc., Winooski, VT). Cells without drug exposure were used as controls.  For each cell line exposed to DAUN or DOX at each time interval, MTT assays were performed in three independent experiments and repeated in triplicate.  The percentage of live cells was calculated relative to the control wells using the following equation: [(Absorbance value of experimental well)/(Absorbance value of control well)] x 100.  These percentage values were used to construct lethal concentration (LC50) dose-response curves with the GraphPad Prism version 4.0 program (GraphPad Software Inc., San Diego, CA).  LC50 values for each cell line were determined following DAUN and DOX exposure at the aforementioned time intervals.  MTT assays were repeated again to determine LC50 values in all cell lines for the 48 hr exposure period with the major metabolites, DAUNol and DOXol (0, 0.5, 1, 5, 10, 25, 50, 100, 250, 500, 1000, 1500, 2000, and 3000 µM).  4.2.4 DAUN and DOX metabolic assays with cytosolic fractions derived from cell lines  Cytosolic fractions derived from the rat heart and human carcinoma cell lines were extracted according to the protocol provided for mammalian cells by QIAGEN Inc. (Mississauga, Ontario).  Cells were washed in PBS (pH 7.4), collected for 5 min at 1000xg, resuspended in lysis buffer (50 mM NaH2PO4, 300 mM NaCl, pH 8.0) with 0.05% Tween® 20, and lysed by sonication.  The lysate was centrifuged at 10,000xg for 10 min at 4oC to pellet cellular debris and DNA.  The supernatant was stored in 20% glycerol at -20oC and saved for metabolic assays.  109 The enzymatic conversion of DAUN and DOX to their respective major metabolites, DAUNol and DOXol, were measured in cell cytosols.  Assays were performed similar to the Kassner et al. (2008) study: 20 µg total cytosolic protein, 10 µM DAUN or DOX substrate, 2 mM NADPH, 100 mM KH2PO4, pH 7.4 at 37oC, 30 min. Cytosolic protein concentrations were determined using the Bradford protein assay with bovine serum albumin as a standard.  The enzymatic reaction was stopped by adding 300 µl of ice-cold acetonitrile, which contained idarubicin as an internal standard, followed by vortex mixing and centrifuging at 10,000xg for 10 min at 4°C to remove protein.  The supernatant was removed for detection and quantification of the DAUNol and DOXol metabolites by an ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method.  4.2.5 Instrumentation and experimental conditions for UPLC-MS/MS  The UPLC/MS/MS system consisted of a Waters Acquity ultra performance liquid chromatograph connected to a Waters Quattro Premier XE triple quadrupole mass spectrometer equipped with an electrospray ionization source (Waters® Corporation, Milford, MA).  Chromatographic separation of DOX, DOXol, DAUN, DAUNol and idarubicin (internal standard) was achieved using a Waters Acquity UPLCTM bridged ethyl hydrid (BEH) C18 column (100 mm x 2.1 mm i.d., 1.7 µm particle size) with the following mobile phase composition and gradient programming: water with 0.1% formic acid (A), acetonitrile with 0.1% formic acid (B); 0 min, 5% B; 1 min, 5% B; 2 min, 98% B; 4 min 98% B; 4.1 min, 5% B; and 6 min, 5% B.  The flow rate was maintained at 0.2 ml/min with a total run time of 6 mins. The mobile phase flow was diverted to the waste before 2.5 mins and after 3.5 mins during the chromatographic run.  The mass  110 spectrometer was operated in positive electrospray ionization mode with a capillary voltage of 3.5 kV, cone voltage of 40 V, and desolvation temperature of 300 ºC.  The analytes were detected in multiple reaction monitoring (MRM) mode using the total ion current (TIC) of the following ion transitions (m/z), and collision energy (CE, eV) values: for DOX—m/z 544.1  361.2 (CE 20),  m/z 544.1  379.0 (CE 20), and m/z 544.1  397.2 (CE 10); for DOXol—m/z 546.0  345.0 (CE 35), m/z 546.0  363.1 (CE 20), and m/z 546.0  398.9 (CE 10); for DAUN—m/z 527.9  321.0 (CE 20), m/z 527.9  363.2 (CE 20), and m/z 527.9  381.0 (CE 10), for DAUNol—m/z 530.1  306.2 (CE 35), m/z 530.1  321.2 (CE 30), and m/z 530.1  383.1 (CE 10); and for IDA—m/z 497.9  291.2 (CE 25), m/z 497.9  333.0 (CE 25).  Data were acquired and processed using MassLynxTM version 4.1 software (Waters® Corporation).  A representative UPLC- MS/MS chromatogram of DOX, DOXol, DAUN, DAUNol, and IDA is presented in Figure 28.  111   Figure 28—Representative UPLC-MS/MS chromatogram of doxorubicin, doxorubicinol, daunorubicin, daunorubicinol, and idarubicin.  These analytes were monitored using the total ion current (TIC) of three multiple reaction monitoring (MRM) signals for doxorubicin, doxorubicinol, daunorubicin, daunoribicinol, and two MRM signals for idarubicin.  The retention time (in minutes) for each of these analytes are labelled on top of the peaks.  The peaks in the chromatogram appear broad since this is a close up a 1 min time interval (from 2.5 to 3.5 mins).   4.2.6 Western blotting of cytosols to detect AKRs and CBRs  Western blot analyses of the cytosols extracted from each cell line were conducted according to the procedure described by OdysseyTM (LI-COR Biosciences, Lincoln, NE).  Following 18% SDS-polyacrylamide gel electrophoresis, cytosolic proteins were transferred at 20 V in Towbin's buffer (25 mM Tris, 192 mM glycine, and 20% v/v methanol) overnight (at 4oC) to a Hybond-C Extra nitrocellulose membrane (GE Healthcare, Piscataway, NJ).  The membranes were blocked in Odyssey blocking buffer, and the enzyme was detected using either a MaxPab polyclonal mouse anti-human  112 AKR1A1, AKR1B1, AKR1B10, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR7A2, CBR1 or CBR3 antibody (Abnova® Corporation, Taipei City, Taiwan) (diluted 1:2500) as the primary antibodies and IRDye 800CW goat anti-mouse IgG as the secondary antibody (diluted 1:5000) (LI-COR).  Both primary and secondary antibodies were in blocking buffer containing 0.1% Tween 20.  The bound secondary antibody was detected using the OdysseyTM Infrared Imaging system (LI-COR).  β-tubulin served as a loading control and was detected using the same aforementioned Western protocol, except that a mouse monoclonal anti- β-tubulin primary antibody (Abcam® Inc., Cambridge, MA) was used (diluted 1:1000).  Band intensities for AKR or CBR proteins were determined using OdysseyTM densitometry software, and were normalized to band intensities of β-tubulin in order to quantify the relative expression of the individual reductases in each cytosolic extract.  4.2.7 Statistical analysis  Statistical analyses were performed by GraphPad Instat® (version 3.6; GraphPad Software Inc., San Diego, CA).  Percent viabilities to create dose-response curves from the cytotoxicity assays were expressed as means ± S.D while LC50 values were provided along with the 95% confidence intervals.  Results from the expression and metabolic assays were reported as means ± S.D. and compared using one-way analysis of variance followed by Tukey-Kramer multiple comparisons tests.  Differences were considered significant at p<0.05.  Sample sizes (n) for the experiments performed in this study are as follows:  determination of LC50 values with the 9 cell lines in presence of either DAUN, DOX, DAUNol or DOXol (n=3 at each exposure time period), determination of DAUNol/DOXol levels after performing metabolic assays with the cell line cytosolic  113 extracts (n=12), and determination of the relative expression ratios of the reductase enzymes in the individual cell lines after Western blotting and densitometry analyses (n=3).  4.3 Results  4.3.1 Cytotoxicity of cells following exposure to anthracyclines  The cytotoxicities of the anticancer drugs DAUN, DOX, and their metabolites (DAUNol and DOXol) were determined in the cell lines using the MTT assay.  Cell viability was measured after incubating each cell line with various concentrations of the anthracycline parent drug or its major alcohol metabolite for 0 (100% viable), 6, 24, or 48 hrs.  Dose-response curves were plotted for all 9 cell lines; two representative plots are presented in Figure 29 (n=3).  The LC50 values were calculated from these curves, and the LC50 values for each of the cell lines were compared to see which compounds were more toxic.  Cell lines with lower LC50 values are more sensitive to the drug, while cell lines with higher LC50 values are less sensitive (more resistant).  The LC50 values for all nine cell lines are provided in Tables 12 (for DAUN and DAUNol) and 13 (for DOX and DOXol).  Four observations are worth mentioning from these data sets.  First, four cell lines, HepG2 (liver), HCT-15 (colon), NCI-H460 (lung), and A-498 (kidney), were found to be significantly more resistant to DAUN and DOX compared to the five remaining cell lines, H9c2 (heart),  PC-3 (prostate), OVCAR-4 (ovary), PANC-1 (pancreas), and MCF-7 (breast), which I have called the sensitive group of cell lines.  This finding was consistent for all time points examined.  Second, DOX was more toxic than DAUN and, again, this was consistent for all of the cell lines.  Third, LC50 values for DAUNol and DOXol were significantly higher (i.e., less toxic) than the LC50 values of their respective parent drug  114 and this was consistently observed for all cell lines tested.  Indeed, the DAUNol LC50 values were 30- to 108-fold greater than those for DAUN; the DOXol LC50 values were 59- to 162-fold greater than those for DOX.  Taken together, these findings strongly suggest that the parent drugs, DAUN or DOX, are far more toxic to these cells than are their metabolites, DAUNol and DOXol, respectively.       Figure 29—Sample dose-response curves of (A) H9c2 rat heart cell line and (B) HepG2 liver cell line in the presence of varying concentrations of daunorubicin (DAUN), doxorubicin (DOX), daunorubicinol (DAUNol), and doxorubicinol (DOXol) following a 48 hr incubation.  Three independent batches of cells for each cell line were grown and subjected to MTT viability assays.  The % viability values are reported as the mean ± S.D. (n=3).                115 Table 12—Mean LC50 values of DAUN and DAUNol for cell lines at specified time intervals following exposure to the drug.   MEAN LC50 (µM) a (95% C.I.) DAUN DAUN DAUN DAUNol CELL LINES 6 hrs 24 hrs 48 hrs 48 hrs H9c2 (heart) 12.6      (11.2-14.1) 3.2 (3.0-3.5) 0.4 (0.3-0.5) 42.7 (37.6-48.5) PC-3 (prostate) 10.2       (9.2-11.4) 3.2 (2.9-3.6) 0.4 (0.3-0.5) 43.2 (38.1-49.1) OVCAR-4 (ovary) 11.1       (9.8-12.5) 3.1 (2.8-3.4) 0.7 (0.6-0.8) 41.6 (35.5-48.9) PANC-1 (pancreas) 11.4 (10.1-13.0) 3.6 (3.2-4.0) 0.6 (0.5-0.7) 45.0 (39.5-51.4) MCF-7 (breast) 14.1     (11.9-16.6) 4.2 (3.8-4.6) 0.6 (0.5-0.7) 48.7 (42.6-55.7) Hep G2 (liver) 21.5     (18.4-25.1) 9.5 (8.3-10.9) 1.5 (1.3-1.9) 54.5 (47.8-62.0) HCT-15 (colon) 19.7     (17.0-22.7) 9.9 (8.7-11.3) 1.4 (1.2-1.7) 54.0 (47.7-61.1) NCI-H460 (lung) 21.0     (18.1-24.3) 10.3 (9.3-11.5) 1.7 (1.4-2.0) 55.0 (48.8-62.0) A-498 (kidney) 22.9     (20.5-25.6) 13.7 (12.4-15.0) 1.7 (1.5-1.9) 51.7 (45.3-59.2)  a   LC50 values were calculated from dose-response curves generated from MTT viability experiments.  95% confidence intervals (C.I.s) are provided in brackets below the mean LC50 values.  The dark grey shaded section of the table refers to the sensitive cell lines while the unshaded section refers to the resistant cell lines.                    116 Table 13—Mean LC50 values of DOX and DOXol for cell lines at specified time intervals following exposure to the drug.   MEAN LC50 (µM) a (95% C.I.) DOX DOX DOX DOXol CELL LINES 6 hrs 24 hrs 48 hrs 48 hrs H9c2 (heart) 5.1         (4.4-5.8) 1.1 (1.0-1.3) 0.2 (0.1-0.3) 25.8 (22.5-29.5) PC-3 (prostate) 5.1         (4.6-5.7) 0.9 (0.8-1.1) 0.2 (0.1-0.3) 27.0 (23.2-31.5) OVCAR-4 (ovary) 6.6         (5.9-7.5) 1.1 (0.9-1.2) 0.2 (0.1-0.3) 27.2 (24.0-30.7) PANC-1 (pancreas) 7.4         (6.3-8.6) 1.3 (1.1-1.5) 0.2 (0.1-0.3) 29.6 (25.6-34.1) MCF-7 (breast) 7.3         (6.4-8.3) 1.3 (1.1-1.5) 0.2 (0.1-0.3) 32.4 (28.2-37.1) Hep G2 (liver) 11.9     (10.1-13.8) 3.4 (3.0-3.9) 0.5 (0.4-0.6) 37.2 (30.2-45.6) HCT-15 (colon) 10.1       (9.1-11.1) 2.4 (2.2-2.6) 0.5 (0.4-0.6) 38.8 (34.8-43.3) NCI-H460 (lung) 10.9       (9.8-12.0) 3.0 (2.6-3.4) 0.6 (0.5-0.7) 35.5 (30.7-41.0) A-498 (kidney) 12.2     (10.6-14.0) 4.1 (3.7-4.6) 0.5 (0.4-0.6) 38.9 (34.4-44.0)  a   LC50 values were calculated from dose-response curves generated from MTT viability experiments.  95% confidence intervals (C.I.s) are provided in brackets below the mean LC50 values.  The dark grey shaded section of the table refers to the sensitive cell lines while the unshaded section refers to the resistant cell lines.   4.3.2 Metabolism of the anthracyclines using cell line cytosols  Since the liver, colon, lung, and kidney derived cell lines seemed to be considerably less sensitive to DAUN or DOX than the remaining five cell lines, we wished to ascertain the basis for this difference.  More specifically, we wanted to determine whether this difference was associated with differences among the cell types in the rate at which they were able to metabolize the drugs or were based on some other physiological property, perhaps transport into or out of the cell, as an example.  Hence,  117 we measured the rate of enzymatic conversion of DAUN and DOX to their respective major metabolites, DAUNol and DOXol, in cytosolic extracts from each of the nine cell lines.  Among the five cell lines that were more sensitive to the drugs (heart, prostate, ovary, pancreas, and breast), the rates of conversion of DAUN to DAUNol ranged from 17.6±1.0 to 27.3±1.9 pmol DAUNol/min•mg cytosolic protein and the rate of conversion of DOX to DOXol ranged from 3.6±1.0 to 5.0±0.8 pmol DOXol/min•mg cytosolic protein (Figure 30) (all n=12).  The four tolerant (less sensitive) cell lines (liver, colon, lung, and kidney) had significantly higher metabolic rates ranging from 50.0±3.2 to 80.7±9.7 pmol DAUNol/min•mg and 9.3±0.8 to 10.5±1.1 pmol DOXol/min•mg (Figure 30) (all n=12).  As a result, the five sensitive cell lines were classified as the low metabolizers of these anthracycline drugs and the four tolerant cell lines as the high metabolizers.  Furthermore, all cell lines were shown to metabolize DAUN more rapidly (a 3.3- to 7.8-fold higher rate) than DOX.   Figure 30—Enzymatic activities for rat and human cell line cytosols incubated with 10 µM of daunorubicin (A) and doxorubicin (B).  Activities were measured by following the rate of daunorubicinol and doxorubicinol production.  Three independent batches of cells for each cell line were grown and cytosols extracted.  Assays were performed in quadruplicate with each batch.  Enzymatic activities are reported as mean ± S.D. (n=12).  Cell lines to the left of the vertical dashed line are sensitive to DAUN and DOX while the cell lines to the right are the resistant ones.   118   4.3.3 Expression of cytosolic AKRs and CBRs in cell lines  Next, we wanted to determine whether the difference in metabolic activity between the tolerant and sensitive cell lines resulted from a difference in the relative abundance of specific AKR and/or CBR enzymes, or was due to other physiological factors that might differentiate the cell types.  Western blot analysis for each of eight AKR (AKR1A1, 1B1, 1B10, 1C1, 1C2, 1C3, 1C4, and 7A2) and two CBR enzymes (CBR1 and CBR3) was performed on cytosolic extracts from each of the nine cell lines. Distinct bands with mobilities corresponding to the calculated molecular mass for each of the enzymes, 35-38 kDa for the AKRs and 30 kDa for the CBRs, were detected in each extract (Figure 31).  Expression levels of the reductases for each cell line were ascertained by densitometry analysis and normalized against the expression levels of β- tubulin (as an internal standard) in order to obtain the relative abundance of each enzyme in each cell type.  Comparing these values between cell lines, each of the cell types in the tolerant group (liver, colon, lung, and kidney) express AKRs and CBRs at significantly higher levels than any of the five cell types that comprise the sensitive group (Figure 32) (all n=3).  Therefore, it appears that the higher expression of the reductase genes contributes to the ability of the tolerant cell lines to metabolize DAUN and DOX more efficiently than the sensitive cell lines.         119  Figure 31—Western blot detection of the sensitive cell line cytosols (lane 1: heart, lane 2: prostate, lane 3: ovary, lane 4: pancreas, and lane 5: breast; all at 15 µg total protein) as well as the resistant cell line cytosols (lane 6: liver, lane 7: colon, lane 8: lung, lane 9: kidney; all at 15 µg total protein) confirms expression of the desired AKR and CBR proteins.  β-tubulin (~55 kDa) was used as an internal loading control.  6x-His tagged AKR and CBR recombinant proteins were used as positive controls for antibody immunoreactivity (~1 µg).  Cell lines to the left of the vertical dashed line are sensitive to DAUN and DOX while the cell lines to the right are the resistant ones.  120   Figure 32—Relative expression ratio levels of AKR and CBR proteins in the sensitive (heart, prostate, ovary, pancreas, and breast; all at 15 µg total protein) as well as the resistant cell line cytosols (liver,colon, lung, and kidney; all at 15 µg total protein).  Densitometry was used to determine expression values of reductases in each cell line following Western blotting.  These individual reductase expression values were then divided by the expression values of β-tubulin with the purpose of calculating relative expression ratios. Three independent batches of cells for each cell line were grown and subjected to Western blotting and densitometry analyses.  Relative expression values are reported as mean ± S.D. (n=3). Cell lines to the left of the vertical dashed line are sensitive to DAUN and DOX while the cell lines to the right are the resistant ones.  121  4.3.4 Increase in DAUN/DOX metabolism and induction of AKR and CBR gene expression are responses in cell lines following exposure to anthracycline drugs  If there is a connection between the AKR and/or CBR enzymes and detoxification or protection against these drugs, then either the expression of the AKR and/or CBR may be induced in response to exposure to either drug.  Therefore, it was necessary to ask whether exposure to either DAUN or DOX elicited any response in one or more of the nine cell lines.  If a response was elicited by the cell lines following anthracyline exposure, then the next step was to determine if the resistant cell lines (liver, colon, lung, and kidney) respond differently than the sensitive cell lines (heart, prostate, ovary, pancreas, and breast).  Finally, it was important to see if any increase from the metabolism of the drugs was correlated with gene expression rather than some post- translational alteration in enzyme activity or some other physiological event.  Hence, the relative abundance of each enzyme in the cell lines was measured following exposure to the drug at each of the aforementioned time periods. To begin, all the cell lines were exposed to 100 nM of either DAUN or DOX for 6, 24, or 48 hrs.  This drug concentration was selected since cell viability was 75% or greater based on the dose-response curves generated from the cytotoxicity study; therefore, the cells would have a chance to respond to the drug, if they could.  At each time interval, the cells were washed three times with PBS, immediately thereafter cytosolic extracts were made from each cell line, and their ability to metabolize DAUN or DOX was tested.  The metabolic assays were conducted for 30 min as described above; 10 µM of DAUN was used as the substrate for the DAUN-treated cell lines and 10 µM DOX was used as the substrate for the DOX-treated cell lines.  Metabolic activity  122 rates of all the treated cell lines were measured by the production of the major metabolites DAUNol and DOXol, and compared to rates of their respective non-treated (0 hr) cell lines.  The results are shown in Figure 33 (all n=12); three observations are noteworthy.  First, while there was no significant difference in metabolic activity between the non-treated and 6 hr DAUN- or DOX-treated cell lines, there was a clear upward trend in the measured activity of nearly all cell lines.  The single exception, among the 18 experiments, is the lung cells exposed to DAUN where there was no detectable change after 6 hrs.  Hence, while the increase in metabolic activity after a 6 hr exposure is not statistically significant, the trend is clear.  Second, after a 24 hr exposure, all 9 cell lines showed a statistically significant increase in their ability to metabolize DAUN or DOX, and after exposure to the drug for 48 hrs, all 9 cell lines showed an even greater increase in their ability to metabolize the drug.  In the case of those cells exposed to DAUN for 24 and 48 hrs, there was a 1.4- to 2.5-fold respective increase in DAUNol production versus the untreated cells.  Likewise, the metabolic activity of cells exposed to DOX for 24 and 48 hrs was 1.6- to 2.6-fold higher than their untreated counterparts.  Lastly, the four cell lines defined previously as high metabolizers (liver, colon, lung, and kidney) did not differ from the low metabolizing group (heart, prostate, ovary, pancreas, and breast) in their ability to respond to exposure to either drug, that is, the induction was similar in all cell lines.   123  Figure 33—The metabolic activity rates (measured as pmol DAUNol or DOXol/minute•mg total protein) of cytosols that were extracted from cell lines treated with 100 nM DAUN (A) and DOX (B) after 0, 6, 24, and 48 hr exposure time periods.  Significant increases (*, p<0.05) in activity rates are seen for the cytosols treated for 24 and 48 hrs.  Metabolic activity rates on the left side of the dashed vertical line represent the sensitive cell lines while activities to the right are the resistant cell lines.  Three independent batches of cells for each cell line were grown and cytosols extracted.  Assays were performed in quadruplicate with each batch.  Enzymatic activities are reported as mean ± S.D. (n=12).    124 Although observable at 6 hrs, the increase in enzyme activity of all nine cell lines was not statistically significant compared to the untreated control until the 24 hr exposure period; this data suggests that the induction by either DAUN or DOX was not immediate, but rather it took some time.  This delay may be consistent with the time needed for induction of transcription and subsequent translation processes.  Hence, it is reasonable to predict that the increase in metabolic activity in response to exposure to DAUN or DOX was linked to an increase in the amount of the various AKR and/or CBR enzymes produced in each cell line.  To test this, Western blotting was used to examine the relative abundance (i.e., expression) of two enzymes (AKR1C3 and CBR1) in each of the 9 cell lines exposed to DAUN and, separately, DOX for either 0, 6, 24, or 48 hrs.  Rather than perform Western blot analyses for the cytosolic expression of all ten of the aforementioned enzymes in each of the 9 different cell lines, the focus turned towards the AKR1C3 and CBR1 enzymes because the in vitro enzymatic assays from Chapters 2 and 3 have shown that these two enzymes have the highest catalytic efficiency (kcat/Km) towards DOX and DAUN, respectively, compared to the eight remaining AKR and CBR enzymes.  Western blots of AKR1C3 and CBR1 are shown in Figure 34A.  The quantitative analyses of these Western blots are illustrated for AKR1C3 and CBR1 enzymes from DAUN- or DOX-treated cells in Figures 34B to 34E (all n=3).  These analyses demonstrated that the relative abundance of each of these AKR and CBR enzymes increased over time in all 9 cell lines exposed to either these anthracyclines. The increase was detectable after a 6 hr exposure, although not statistically significant compared to the non-treated cells (0 hr exposure), while the expression levels continued to increase with statistically significant differences detected after 24 and 48 hrs of exposure.  For AKR1C3, significant increases in expression were detected in both the 24  125 and 48 hr DAUN-treated (1.2 to 2.3-fold increase compared to non-treated cell lines) and DOX-treated (1.2 to 2.7-fold increase) cell lines.  A similar trend was found for CBR1 expression for the cells exposed for 24 and 48 hr to either DAUN (1.3 to 2.8-fold increase) or DOX (1.5 to 2.4-fold increase).  Therefore, the induction in AKR and CBR gene expression, which leads to an increase in abundance of these enzymes, is a contributing factor to the increase in DAUN and DOX metabolism seen with the treated cell lines over their respective untreated counterparts.  Previous studies have demonstrated signficiant induction of AKRs and CBRs in the presence of DOX.  For example, exposure of MCF-7 breast tumor cells to low (nanomolar) concentrations of DOX resulted in a significant increase in CBR1 protein levels (Gavelova et al., 2008), as well as AKR1C2 and AKR1C3 (Veitch et al., 2009).   In relation to DAUN, the current study was the first to demonstrate that exposure to this anthracycline can lead to significant induction of CBR1 and AKR1C3 enzymes.          126  Figure 34—Sample Western blot analyses (A) of cytosols from H9c2 rat heart and HCT-15 human colon carcinoma cell lines for purposes of assessing induction of AKR1C3 and CBR1 after 0, 6, 24, and 48 hr exposure to either 100 nM DAUN or DOX.  Densitometry was performed on the immunoreactive bands and normalized against β-tubulin (loading control) in order to calculate relative expression ratios.  With the treated cell lines, the relative expression ratios for AKR1C3 (B: DAUN-treated; C: DOX-treated) and CBR1 (D: DAUN-treated; E: DOX-treated) indicate significant induction (*, p<0.05) in cytosols treated for 24 and 48 hrs.  Expression levels on the left side of the dashed vertical line represent the sensitive cell lines while expression levels to the right are the resistant cell lines.  Three independent batches of cells for each cell line were grown and subjected to Western blotting and densitometry analyses.  Relative expression values are reported as mean ± S.D. (n=3).  127  4.3.5 Association between cytotoxicity and DOX/DAUN metabolism in cell lines exposed to these anthracyclines  For each of the incubation time periods, the LC50 values (DAUN and DOX) from the cytotoxicity studies as well as metabolic activity rates from the DAUN and DOX- treated cell lines were plotted against each other to see if an association exists between these two variables (Figure 35).  The high values obtained for correlation coefficients (r) and coefficients of determination (r2) suggest that cytotoxicity and metabolism are strongly related to each other with these two variables being negatively correlated.  Figure 35—Scatterplot of cytotoxicity (LC50 values) and metabolic activity following DAUN (A) and DOX (B) treatment in the nine cell lines for the purposes of seeing if there is an association between these two variables for 6, 24, and 48 hr incubations.  Low LC50 values are synonymous with higher cytotoxicity while the reverse is true for high LC50 values.  The high correlation coefficient (r) and coefficient of determination (r2) values provided for each of the exposure time periods suggest a strong correlation between cytotoxicity and metabolism.  4.3.6 UPLC-MS/MS method validation  The UPLC/MS/MS method was validated for accuracy, precision, linearity, range, limit of quantitation (LOQ), and selectivity.  The validation was performed in spiked samples of a pooled blank cytosol matrix, which was prepared from nine separate cancer cell lines.  Accuracy was expressed as the percentage deviation (% Deviation) between  128 the measured and nominal concentrations of six replicate samples separately spiked at three concentration levels (QC-Low, QC- Mid, and QC-High).  Precision was expressed as the coefficient of variation (% CV) of the measured concentrations of six replicate samples obtained from a single spiked sample of the QC-Low, QC- Mid, and QC-High samples.  Six replicate samples were analyzed at the three QC levels.  For DOXol and DAUNol, the results for accuracy and precision are presented in Table 14.  For DOXol, intra-day and inter-day accuracy ranged from -4.90% to 10.2% and 3.21% to 9.53%, respectively, while intra-day and inter-day precision ranged from 1.77% to 10.5% and 3.43% to 10.4%, respectively.  For DAUNol, intra-day and inter-day accuracy ranged from -6.84% to 11.4% and 3.67% to 8.90%, respectively, while intra-day and inter-day precision ranged from 1.33% to 10.9% and 3.43% to 9.31%, repectively.  Accuracy and precision met the suitability criteria of less than 15% CV for calculated concentrations and less than 15% bias from expected concentration with six replicate samples prepared at three QC levels within the range of the method.  With respect to linearity, the calibration curves for the metabolites were weighted (1/X2, n=3) and were linear with coefficient of determination (r2) values for DOXol ≥ 0.994 and for DAUNol ≥ 0.988. The range of the method was 2.50 to 500 ng/ml for DOXol and DAUNol requiring 150 µl of sample.  The LOQ for DOXol was 2.50 ng/ml (i.e., 4.58 nM) with an accuracy of - 0.552%±3.63% (mean±SD, n=6), and precision of 3.65% (n=6).  The LOQ for DAUNol was 2.50 ng/ml (4.42 nM) with the accuracy of 0.885%±12.3% (mean±SD, n=6), and precision 12.2% (n=6).  The method was selective with no interference at the retention times of DOXol and DAUNol when the blank matrix pooled from the nine cell line cytosols were spiked at LOQ level (n=6).  The criteria used to assess the suitability of the  129 method were based on the best practices developed for bioanalytical method validation that fulfill the current regulatory guidance (Shah et al., 2000; Nowatzke and Woolf, 2007).  130 Table 14—Results for accuracy and precision (intra-day and inter-day) for the UPLC-MS/MS determinations of DOXol and DAUNol in pooled matrix of nine cell lines (days 1 to 3).  Acceptance criteria for the method was set at less than 15% CV (precision) and less than 15% bias at all QC levels.  Each determination was based on six replicate samples.  DOXol DAUNol Intra-day Inter-Day Intra-day Inter-Day Accuracy Day 1 (n=6) Day 2 (n=6) Day 3 (n=6) Days 1-3 (n=18) Accuracy Day 1 (n=6) Day 2 (n=6) Day 3 (n=6) Days 1-3 (n=18) QC-Low (7.5 ng/ml)     QC-Low (7.5 ng/ml) Mean (ng/ml) 7.13 7.17 7.58 7.29 Mean (ng/ml) 6.99 7.54 7.71 7.4 SD (ng/ml) 0.992 0.343 0.627 0.695 SD (ng/ml) 0.90 0.50 0.27 0.66 % Deviation -4.90 -4.40 1.09 9.53 % Deviation -6.84 0.55 2.78 8.90 QC-Mid (80 ng/ml)     QC-Mid (80 ng/ml)   Mean (ng/ml) 81.2 77.9 84.8 81.3 Mean (ng/ml) 80.1 83.7 87.1 83.7 SD (ng/ml) 3.25 4.89 1.50 4.39 SD (ng/ml) 4.36 2.31 1.66 4.08 % Deviation 1.44 -2.67 5.95 5.40 % Deviation 0.149 4.65 8.94 4.88 QC-High (400 ng/ml)     QC-High (400 ng/ml) Mean (ng/ml) 439 427 441 436 Mean (ng/ml) 412 432 446 430 SD (ng/ml) 10.3 14.2 15.1 14.0 SD (ng/ml) 8.86 5.76 7.34 15.8 % Deviation 9.73 6.80 10.2 3.21 % Deviation 3.04 8.08 11.4 3.67     Intra-day Inter-Day Intra-day Inter-Day Precision Day 1 (n=6) Day 2 (n=6) Day 3 (n=6) Days 1-3 (n=18) Precision Day 1 (n=6) Day 2 (n=6) Day 3 (n=6) Days 1-3 (n=18) QC-Low (7.5 ng/ml)     QC-Low (7.5 ng/ml) Mean (ng/ml) 6.4 7.2 7.6 7.1 Mean (ng/ml) 6.68 7.54 7.71 7.31 SD (ng/ml) 0.67 0.34 0.63 0.73 SD (ng/ml) 0.726 0.495 0.273 0.680 % CV 10.5 4.79 8.27 10.4 % CV 10.9 6.57 3.54 9.31 QC-Mid (80 ng/ml)     QC-Mid (80 ng/ml) Mean (ng/ml) 81.0 77.9 84.8 81.2 Mean (ng/ml) 79.2 83.7 87.1 83.4 SD (ng/ml) 2.97 4.89 1.50 4.33 SD (ng/ml) 2.64 2.31 1.66 3.94 % CV 3.67 6.28 1.77 5.33 % CV 3.33 2.76 1.91 4.72 QC-High (400 ng/ml)     QC-High (400 ng/ml) Mean (ng/ml) 432 427 441 433 Mean (ng/ml) 415 432 446 431 SD (ng/ml) 14.4 14 15.1 15 SD (ng/ml) 9.50 5.76 7.34 14.8 % CV 3.34 3.32 3.43 3.43 % CV 2.29 1.33 1.65 3.43  131  4.4 Discussion  DAUN and DOX are among the most commonly used and most successful drugs to treat a variety of leukemias, carninomas, and lymphomas.  However, a considerable number of patients treated with either of these drugs develop serious chronic cardiomyopathies.  While the likelihood of developing some form of cardiotoxicity is directly linked to the cumulative dose of the drug that each patient receives, the underlying cause of the cellular toxicity remains largely unknown.  One hypothesis for the inter-patient variability of these toxic effects is that the patients differ in their metabolic efficiency of removing either the parent drug or its down stream metabolites. However, there is no conclusive evidence in the literature that links altered DAUN or DOX metabolism to toxicity.  The attractiveness of this hypothesis is weakened further by conflicting assertions of whether the cytotoxicity is caused by the parent drug (DAUN or DOX) or its primary metabolite (DAUNol or DOXol, respectively).  To address these issues, we performed ex vivo and in vitro studies on nine different cell lines to determine: (i) whether the parent drugs, DAUN or DOX, or their metabolites, DAUNol and DOXol respectively, were more toxic, (ii) the metabolic efficiency of each cell type, that is, the efficiency with which each cell type converted the parent drug to its primary metabolite, (iii) whether the metabolic efficiency of each cell line correlated with the relative abundance of one or more of the selected AKRs and CBRs, (iv) whether one or more cell types responded to the presence of DAUN or DOX by increasing their capacity to metabolize the drug, and if so, (v) if the increase in the ability to metabolize the drug correlated with an increase in the relative abundance of the DAUN or DOX metabolizing enzymes or resulted from some other physiological event, that is yet to be determined.  132 The cytotoxicity studies revealed that the LC50 values for the metabolites DAUNol and DOXol were far greater (30- to 108-fold and 59- to 162-fold, respectively) than those for the parent drugs, DAUN and DOX respectively, and thus clearly demonstrated that the parent drugs were far more toxic to the cells than were their primary metabolites.  This was true for all nine cell-types that were examined.  Hence, it appears that the parent drugs are physiologically more detrimental to cells, regardless of their tissue of origin.  While all nine cell-types responded similarly, they did not respond equally.  The nine different cell lines could be divided into two different groups based on their sensitivity (LC50 values) to either the parent drugs or their metabolites.  Four cell types (liver, colon, lung, and heart) were less sensitive to DAUN and DOX; while the remaining five cell types (heart, prostate, ovary, pancreas, and breast) were more sensitive, and the differences were statistically significant.  Although we could also divide the nine cell types into two groups based on their response to either DAUNol or DOXol, these differences were not statistically significant. Since previous studies, performed on cancer patients receiving treatment with either DAUN or DOX, demonstrated that DAUNol and DOXol are the major metabolites of these anti-cancer drugs (Lipp and Bokemeyer, 1999; Plebuch et al., 2007), we assessed the efficiency with which the various cell lines metabolized DAUN and DOX by quantifying the rate at which the carbon-13 alcohol metabolites were produced.  Once again, all nine cell lines were able to metabolize either DAUN or DOX, but they differed in the rate at which they converted the parent drug to its metabolite.  Four cell lines (liver, colon, lung, and heart) metabolized DAUN or DOX faster than the remaining five cell lines (heart, prostate, ovary, pancreas, and breast).  The assemblage of the two groups of  133 cell-types based on metabolic efficiency parallels that found for the cytotoxicity studies. Thus, there is an association between these two physiological phenomena, with high metabolizing cell lines exhibiting elevated LC50 values (greater resistance) and conversely, the low metabolizing cell lines having decreased LC50 values (greater sensitivity) for the parent drugs or their metabolites.  Lastly, the relative abundance of the eight AKR and two CBR enzymes in each cell type correlated with the relative efficiency with which the cell types metabolized DAUN or DOX.  The high metabolizing cell lines had considerably more of each AKR and CBR enzyme in their cytosol (often 2 to 3-fold greater) than the amount present in the cell lines comprising the low metabolizing group. Therefore, there is a striking parallel between the efficiency with which each cell type metabolizes DAUN or DOX and the relative abundance (expression level) of the anthracycline metabolizing enzymes.  Our results indicate a negative relationship between toxicity following DOX or DAUN exposure and both metabolism by, and relative abundance of, the eight AKR and two CBR enzymes.  The high metabolizing cell lines are less sensitive to DAUN or DOX and produce more of each type of enzyme, while the low metabolizing enzymes are more sensitive to these drugs and produce less of each enzyme. Some caveats should, however, be stated.  First, the cell lines used are permanent cell lines derived from human tissues, and one from rat, which were established some time ago.  As immortalized cells, their growth properties have, no doubt, been altered; however, we believe that these cell lines do retain much of the biochemical distinctiveness of their parent cell types.  Second, although there is a striking negative relationship between the relative abundance of all eight AKR and both CBR enzymes and  134 the sensitivity of each of the cell-lines to DAUN/DOX-induced cytotoxicity, the findings do not establish a direct involvement of any of these reductases with drug sensitivity. Nevertheless, we believe the results provide a compelling reason for additional studies to determine the basis for the correlation between AKR and CBR abundance and cytotoxicity following exposure to these anthracycline drugs.  These future studies should include (i) inhibiting/reducing the metabolic activity of the individual AKRs/CBRs (i.e., via knockdown/knockout procedures or the use of specific inhibitors) in cell lines with high levels of reductase expression and DAUN/DOX metabolic activity to see if cell toxicity is increased, and (ii) over-expressing individual AKRs and CBRs (i.e., via transfection with vectors containing the reductase gene of interest) in cell lines with low levels of reductase expression/metabolic activity to see if cell toxicity is decreased.  A detail description of these proposed studies is addressed in the “Suggested future research directions” section of Chapter 5. Overall, this study demonstrated a negative association between metabolic activity by AKRs/CBRs and cytotoxicity using nine cell lines.  If cytotoxicity observed in the cell lines, which appears to be correlated with the level of DAUN/DOX metabolism, is mechanistically similar to the toxicity observed following anthracycline therapy in cancer patients, then one would expect that the relative toxicities observed among the nine cell lines would parallel the relative sensitivity of normal cells from which these cell lines were derived.  This may be true in relation to cardiotoxicity, since the AKRs and CBRs are found in human heart tissue, but are in lower abundance than in the liver (Figure 36) (all n=3).  A study by O’Connor et al. (1999) also demonstrated that AKR7A2 and AKR1B1 are expressed in the human heart using Western blot analyses,  135 however, the expression of these two enzymes were not quantified.  Given the correlation between the relative abundance of these enzymes, the relative efficiency with which each cell type metabolizes DAUN or DOX, and their relative sensitivity to the cytotoxic effects of these drugs, one can predict that cancer patients with mutant alleles of the AKR and CBR genes that encode these enzymes are more likely to develop adverse effects (i.e., cardiotoxicity) following DAUN or DOX therapy.  Indeed, if metabolism of DAUN and DOX are associated with sensitivity to the cytotoxic effects of these drugs then, those individuals with the more severe mutant alleles should be at the greatest risk, while those with mutations that have rather minor affects on enzyme function should be a far lower risk.  The next step is to perform clinical studies to see if there are strong associations between frequency of one or more of these reductase variants and the susceptibility of DAUN/DOX-treated cancer patients to the development of serious life-threatening adverse effects such as cardiotoxicity.  This would help determine if these variants are clinically relevant genetic biomarkers for guiding anthracycline therapy.  We have initiated these clinical studies.   136  Figure 36—Bar graph illustrating the relative expression ratios of the cytosolic AKRs and CBRs in human heart lysate (H; single donor, a 38 year old female; ProSci Incorporated, Poway, CA) and pooled human liver lysate (L; 50 donors; BD Biosciences, San Jose, CA).  Densitometry was used to determine expression values of reductases in each cell line following Western blotting.  These individual reductase expression values were then divided by the expression values of β-tubulin with the purpose of calculating relative expression ratios. Western blotting was repeated three times to determine relative expression values of the reductases, which are reported as mean ± S.D. (n=3). (Below the bar graphs) Human heart (H) and liver (L) lysates (~20 µg total protein) were run on 18% SDS-PAGE gels and subjected to Western blotting for detection of AKR1A1, AKR1B1, AKR1B10, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR7A2, CBR1, and CBR3 proteins (ranging from 30 to 38 kDa).  In addition to the reductase enzymes, β-tubulin band was also detected using Western blotting (~55 kDa).  The 6x-His tagged purified proteins were used as positive controls (PCs) for antibody immunoreactivity for these enzymes.  M refers to the molecular weight markers.  137 CHAPTER 5: OVERALL SUMMARY AND CONCLUSIONS   5.1 Novel findings  There are two novel findings that I observed after analyzing the results from the in vitro and ex vivo experiments performed in this thesis.  The first of these findings is that:  1. A total of 12 variant alleles (7 for the AKRs and 5 for the CBRs) were associated with significantly reduced in vitro metabolic activities of DAUN and/or DOX compared to their respective wild-type counterparts (Chapters 2 and 3).  To date, this thesis offers the most comprehensive set of data on the impact that naturally-occurring allelic variants of human AKRs and CBRs, in the form of ns-SNPs, have on the functional activities of these reductase enzymes.  Out of the 38 variants that were examined in the in vitro studies, 12 resulted in significantly decreased enzymatic activities in the metabolic conversion of these drugs to their corresponding major alcohol metabolites, DAUNol and DOXol.  This number can be increased to 13 if one includes the truncated enzyme (E36Term) of AKR1C3. As stated in Chapter 2, this variant cannot metabolize either DAUN or DOX, since it is missing critical residues that are involved in catalysis and cofactor binding.  As stated previously, the in vitro studies involved a series of experiments comprised of cloning the wild-type AKR and CBR genes into pET vectors, creating the variants by site-directed mutagenesis, transforming the wild-type and variant constructs into E.coli for expression, purifying the wild-type and variant enzymes using Ni-NTA affinity chromatography, and finally performing in vitro enzymatic assays with DAUN and DOX for the purposes of comparing kinetic parameter values between the wild-type and variant enzymes.  138   The second novel finding, which was ascertained from the cell line study, is as follows:  2. A reduction in AKR and CBR-mediated metabolism of DAUN and DOX in cell lines is associated with increased cytotoxicity following exposure with either of these anthracyclines (Chapter 4).  The rationale for these experiments was based on previous literature suggesting that metabolism plays a major role in anthracycline-induced cardiotoxicity; however, there is disagreement on whether the alcohol metabolites, DAUNol and DOXol, or the parent drugs are the toxic species (Behenia and Boroujerdi, 1999; Ax et al., 2000; Olson et al. 2003; Veitch et al., 2009).  To recap, nine cell lines, representing tissues from different organs (heart, prostate, ovary, pancreas, breast, liver, colon, lung, and kidney), were subjected to varying concentrations of either DAUN or DOX at specified time periods ranging from 6 to 48 hrs and cell viability (cytotoxicity) was measured.  Cell viability, as a consequence of exposure to various concentrations of either the parent drug or its metabolite was determined using MTT assays, from which LC50 values were determined.  Four of the cell lines (liver, colon, lung, and kidney) were found to be more resistant to DAUN and DOX while the five remaining cell lines (heart, prostate, ovary, pancreas, and breast) were more sensitive.  For the metabolic studies, the resistant and sensitive cells lines were treated with a specific concentration of either DAUN or DOX for the same time periods as in the cytotoxicity studies.  The cytosolic extract derived from each cell line were prepared and subjected to in vitro assays to measure the rate of  139 conversion of DAUN/DOX to DAUNol/DOXol.  The resistant cell lines had significantly higher rates of conversion of the parent drug to its metabolite than did the sensitive cells lines.  In addition to the in vitro assays, the cytosols from the DAUN- and DOX-treated cell lines were subjected to Western blot analyses, and the relative abundance of each of the AKRs and CBRs, in each cell line, were measured.  The levels of the AKR and CBR enzymes were significantly higher in the resistant cell lines than those of the sensitive cell lines.  Finally, the association between cytotoxicity and AKR-/CBR-mediated metabolism of DAUN and DOX at each exposure time period was assessed using correlation analyses.  5.2 Implications of findings  If a reduction in DAUN/DOX metabolism, perhaps caused by variants of AKRs and CBRs, plays a major role in the onset and progression of cardiotoxicity and other toxic adverse effects, then one strategy to reduce these effects is to lower the dose of the drug to be administered.  Ultimately, the dosage should be lowered so that it is sufficient to kill cancer cells while, at the same time prevent damage to the normal cells.  Indeed, this strategy has also been shown to result in a lower incidence of cardiotoxicity compared with that seen in standard dosing controls (Safra 2003).  A recent study has demonstrated the lowering dosage of anthracyclines prevented cardiac side effects, yet the dosage was still high enough to successfully treat the cancer.  The study by Brouwer et al. (2007) found no clinically relevant deterioration of cardiac function in survivors of acute lymphoblastic leukemia treated with a lower dosage of DAUN (cumulative dose of 100 mg/m2), even after a follow-up of 20 years post-treatment.  140 If the ideal therapeutic response is not attainable following low dosage infusion, another alternative is to use liposome-encapsulated formulations of anthracyclines (Vergely et al., 2007).  Liposomes easily accumulate at tumor sites by exiting the bloodstream at sites of leaky vasculature; however, they do not readily exit the circulation in healthy tissues, such as the heart, due to ‘tight’ endothelial capillary junctions (Outomuro et al., 2007; Leonard et al., 2009).  Thus, they may represent a more targeted delivery system, and this may lead to a reduction in toxicity compared with the conventional delivery (i.e., non-encapsulated infusion) these anthracyclines.  In addition, liposomes should allow a slow release anthracyclines - over several days, thereby lowering the concentration of free drug in the bloodstream and limiting exposure to the heart and other non-targeted tissues (Vaage et al., 1994; Hobbs et al., 1998; Allen and Martin 2004; Vail et al., 2004).  This enhanced cardio-sparing effect has been reported in two studies, which required endomyocardial biopsy in order to detect anthracycline- induced cardiac damage (Berry et al., 1998; Safra et al., 2000).  Currently, three formulations of liposomal anthracyclines are approved for clinical use: non-pegylated liposomal DOX (MyocetTM), pegylated liposomal DOX (Caelyx®, Doxil®), and liposomal DAUN (DaunoXome®; mainly used for treatment of advanced AIDS-related Kaposi’s sarcoma). In addition to the aforementioned strategies to reduce potential deleterious effects associated with these anthraycline drugs, other considerations might include the implementation of antioxidants and antioxidant enzymes in DAUN/DOX-based chemotherapies, which have been shown to protect against cardiotoxicity in several experimental models.  For example, the use of flavonoids has been linked to cardio-  141 protection due to their iron chelating and antioxidant properties (Bast et al., 2007; Mojzisova et al., 2009; Li et al., 2009).  Furthermore, the administration of coenzyme Q10, an essential component of the electron transport system and a potent intracellular antioxidant, appears to prevent damage to the mitochondria of the heart, thus preventing the development of anthraycline-induced cardiomyopathy (Conklin, 2005).  Finally, previous studies have demonstrated that the use of antioxidant vitamins (i.e., vitamins C and E) has led to a significant reduction of anthracycline-induced cardiotoxicity in rat models and isolated ventricular myocytes (Kalender et al., 2002; Wold et al., 2005), and therefore should be taken into account as part of treatment in cancer patients undergoing DAUN/DOX therapy.  5.3 Potential limitations of this research  5.3.1 The use of a bacterial expression system for the in vitro studies  A bacterial expression system was used to express the human genes and produce the human AKR and CBR enzymes for the enzymology studies.  In the last two decades or so, E. coli based expression systems have been exploited for the production of a variety of therapeutic proteins (Sahdev et al., 2008).  This expression system provides many benefits for in vitro applications, for example, E. coli are (i) inexpensive to culture, (ii) can be grown quickly to high cell densities, and (iii) can be scaled up for high yield production of the recombinant protein of interest (Crespi and Miller, 1999; Terpe, 2006; Zerbs et al., 2009).  However, bacterial hosts generally lack the enzymes and cellular machinery that is required to generate the post-translational modifications often associated with the final, functional form of mammalian proteins.  These modifications  142 play a significant role in many proteins, including proper folding into three-dimensional structures, localization to the correct intracellular compartments, enzyme activation/deactivation, and enhanced stability (Seo and Lee, 2004; Diella et al., 2004; Lee at al., 2006).  Some examples of post-translational modifications consist of: • Glycosylation: the addition of oligosaccharide (complex sugar) chains to either asparagine, hydroxyllysine, serine, or threonine; • Acetylation: the addition of an acetyl group, usually at the N-terminus of the protein; • Methylation: a type of alkylation that involves the addition of a methyl group, usually at lysine or arginine residues; • Phosphorylation: the addition of a phosphate group, usually to serine, tyrosine, threonine or histidine; and • Sulfation: the addition of a sulfate group to a tyrosine. Most of the post-translational modifications documented for AKRs and CBRs involve N-acetylalanines, N-acetyllysines, phosphoserines, and phosphotyrosines [Universal Protein database (http://www.uniprot.org/)].  These modifications are associated with AKR1A1, AKR1B1, AKR1B10, AKR1C2, AKR1C4, AKR7A2, and CBR1.  To determine whether post-translational modifications affected enzymatic activity of these reductases,  I excised the histidine-tagged wild-type coding regions of the AKRs and CBR1 from the pET vectors and cloned the coding regions of each gene into an insect cell expression vector, p2ZOpie2F (Hegedus et al., 1998).  These constructs were then transfected into Sf9 insect cells (cell lines isolated from ovarian tissue of the fall army worm, Spodoptera frugiperda) using the cationic-lipid formulation, Cellfectin® (Invitrogen), and expression of the reductases were verified by Western blotting with  143 specific antibodies (those used in Chapters 2 and 3).  Insect expression systems are known to provide virtually all of the post-translation modifications that occur in mammalian cells, with the exception of sylation (Altmann et al., 1999; Hollister et al., 2002; Harrison and Jarvis 2006).  These InsectSelect™ produced “human” reductases were purified using Ni-NTA affinity chromatography (Figure 37) and the purified enzymes were subjected to metabolic assays using appropriate test substrates.  The results from these assays are provided in Table 15.  No significant differences in activity were detected between the enzymes expressed and purified from the insect-cell expression system and those obtained from the bacterial expression system (all n=9).  Therefore, I proceeded to use the bacterial system for my detailed in vitro enzymology studies with the test substrates as well as DAUN and DOX.  No post-translational modifications were noted in the database for the remaining enzymes: AKR1C1, AKR1C3, CBR3, and CBR4.             144      Figure 37—Purification of human recombinant 6x-His-tagged wild-type enzymes for Sf9 insect cells: (1) AKRA1, (2) AKR1B1, (3) AKR1B10, (4) AKR1C2, (5) AKR1C4, (6) AKR7A2, and (7) CBR1.  (Top) Gel stained with SYPRO® Ruby following SDS-PAGE showing purified protein fractions (1 µg).  (Bottom) Western blot detection of purified protein fractions confirms expression of the desired AKR and CBR proteins.  GST-tagged full recombinant proteins (Abnova® Corporation, Taipei City, Taiwan; 2 µg total protein) and human liver cytosol (20 µg total protein) were used as positive controls (P) for antibody immunoreactivity for the AKRs and CBR1, respectively.  M refers to the molecular weight markers.        145 Table 15—Enzymatic rates for reported test substrates by recombinant 6x-His tagged AKR wild-type along with kinetic parameters for CBR1 wild-type in the presence of menadione.  ENZYMES SUBSTRATES RATES (nmol/min ● mg protein) for insect cell expressed recombinant RATES (nmol/min ● mg protein) for bacterial expressed recombinant AKR1A1 DL-glyceraldehyde 1430±210 1240±170 AKR1B1 DL-glyceraldehyde 410±37 354±48 AKR1B10 (S)-1-indanol 1070±90 980±80 AKR1C2 1-acenaphthenol 3120±190 2980±151 AKR1C4 1-acenaphthenol 1450±135 1660±190 AKR7A2 9,10-phenanthrenequinone 2800±260 2553±229   CBR 1 KINETIC PARAMETERS using menadione  Vmax (nmol/min ● mg protein) Km (µM) kcat (s -1)a kcat /Km (s-1 M-1) Insect cell expressed recombinant 654±31 19±3 0.37±0.02 19500±2100 Bacterial expressed recombinant 582±43 20±6 0.33±0.02 17400±2800  The rates for both the insect cell and bacterial expressed recombinants are provided for comparison purposes.  Values correspond to mean ± S.D obtained from three experiments performed with three independent enzyme preparations (n=9) for each isoform.  Reported rates for the wild-type enzymes are also provided for comparison purposes a kcat calculated for 6x-His tagged CBR1 from Mr 34000.  5.3.2 Focusing solely on the polymorphisms in the coding regions of the AKR and CBR genes  The polymorphisms selected for this thesis were the ns-SNPs in the AKR and CBR genes.  Synonymous SNPs were excluded since these base pair changes do not result in a change from one amino acid to another in the polypeptide sequence, which means that the activity should be identical to that of the wild-type enzymes.  Also, the polymorphisms associated with the non-coding regions (i.e., introns and promoters) were not included since there was already a tremendous amount of work required to determine the level to which each of the 38 ns-SNPs (excluding the E36Term variant of AKR1C3)  146 affected enzyme activity in comparison to their respect wild-type counterparts.  More importantly, there is a lack of information on the impact that genetic polymorphisms in non-coding regions of human AKRs and CBRs may have on enzyme amounts or function.  In addition, the regulatory regions of these genes, such as enhancers, silencers, and response elements, are not well defined.  Clearly, more studies need to be performed on these genes to define the important regulatory regions.  5.3.3 Allele frequencies for two variants are not reported in the NCBI database  For two of the variants (E55D: significantly altered metabolic activity compared to the AKR1A1 wild-type enzyme; and D239V: did not significantly alter activity of the CBR3 wild-type enzyme), there is no frequency data reported in the NCBI database. Therefore, studies on the clinical relevance of these allelic variants may be somewhat premature.  Clearly, if the E55D and D239V alleles do not occur with any significant frequency in the human population, they will have little or no physiological meaning in determining patient variability when it comes to metabolism of DAUN and DOX. Nevertheless, the data for these two variants do provide new protein structure-function information that identifies important residues for function of their respective enzyme (E55D), or residues that are not critical for function (D239V).   5.4 Suggested future research directions  Recommendations for future research directions focus on two areas: (i) biochemical investigations and (ii) cancer patient correlation studies.   147 5.4.1 Biochemical investigations  The studies in this thesis focused on AKR enzymes that have been reported to be involved in the metabolism of DOX and DAUN.  A new direction would be to repeat these in vitro studies with other AKRs for which ns-SNP frequencies have been reported, namely: AKR1E2, AKR6A5, and AKR7A3 (Table 16).  This would increase the breadth of knowledge pertaining to anthracycline metabolism since these enzymes may potentially be added to the list of those that have been demonstrated to metabolize DAUN and/or DOX to their corresponding alcohols.  Such data may also suggest that these variants could also be involved in the dose-dependent cardiotoxicity and/or other side effects seen in cancer patients during and following DAUN/DOX therapy.   Table 16—Allele frequencies of the non-synonymous single nucleotide polymorphic variants of human AKR enzymes from different ethnic groups.  ENZYMES VARIANTS NCBI rs- number ALLELE FREQUENCIES  a  D35N rs61745201 CEU=2.8% (n=72) C52G rs35429729 YRI=2.5% (n=120) K86R rs17133693 CEU=5.8% (n=120); CHB=12.2% (n=90); JPT=7.8% (n=90) L186W rs76596595 CEU=1.4% (n=72) AKR1E2 R301Term rs12240276 CEU=10.8% (n=120); YRI=12.5% (n=120) AKR6A5 E74K rs2229003 MITO=47.7% (n=38) T323A rs1738025 CEU=83.3% (n=120); CHB=80.0% (n=90); JPT=79.5% (n=88) AKR7A3 N215D rs1738023 CEU=84.2% (n=120); CHB=80.0% (n=90); JPT=78.9% (n=90); YRI=65.8% (n=120)  a  Allele frequencies are obtained from The National Center for Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov/).  The ethnic groups are designated as follows: YRI (African), CHB (Chinese), CEU (European), JPT (Japanese), and MITO (MITOGPOP6: combination of Caucasian, Japanese, Chinese, Amerindian, Pygmy, Russian, etc.).  The chromosome sample counts (n) for each variant are also given.  148  Future investigations can also be undertaken in relation to the findings in Chapter 4.  Even though an association between AKR/CBR metabolism and DAUN/DOX- induced cytotoxicity was established in this study, these findings do not confirm a direct relationship between the reductases and cytotoxicity.  Nevertheless, the results provide good reason to look into performing future experiments in order to determine the degree to which AKRs and CBRs are linked to toxicity following exposure to the anthracyclines. These experiments would include:  • Taking cell lines with high expression of AKRs and CBRs (i.e., liver, colon, lung, and kidney) and inhibiting/knocking out or knocking down (reducing) the metabolic ability of the individual reductase enzymes and determining whether sensitivity to DAUN and/or DOX is increased.  Expression of AKRs and CBRs can be decreased or eliminated using gene-silencing systems such as RNA interference (RNAi).  The basic mechanism of RNAi-mediated gene silencing involves delivering small interfering RNAs (siRNAs), which are double-stranded and about 21 to 28 nucleotides in length, into a cell where they associate with specific proteins to form a ribonucleoprotein complex (Bonetta, 2004).  This complex then scans the mRNA to degrade the corresponding mRNA target in a highly specific manner; the net effect is that the protein in question is not made.  However, RNAi is not always specific and can affect the expression of a number of off-target products (Jackson and Linsley, 2004).  Alternately metabolic inhibition experiments can be performed through the use of specific chemical agents or antibodies specific to the AKR and CBR isoforms to reduce or eliminate activity of these enzymes (Coleman, 2005; Gelboin and Krausz  149 2006).  Like RNAi, there are challenges with using inhibitors and antibodies, namely, that they may cross-react with other enzymes, thereby, confounding the findings regarding the contribution of the enzyme of interest to the observed toxicity. • Taking cell lines with low expression of AKRs and CBRs (i.e., heart, prostate, ovary, pancreas, and breast) and increasing the expression of the individual AKR and CBR enzymes to determine whether the increase in enzymatic activity correlates with a decrease in sensitivity to the drugs.  The increase in reductase expression can be attained by transfecting these cell lines with expression vectors containing the AKR or CBR gene of interest.  For each cell line, enhanced expression of the individual reductases in the transfected cells would be assessed by Western blotting and measured against untransfected cells.  Once this is established, the cytotoxicity experiments of the transfected and untransfected cells could be performed in the presence of DAUN and DOX to evaluate and compare LC50 values. Another set of future experiments would involve an extension of the cell toxicity study with the focus on measuring reactive oxygen species (ROS) levels in the resistant and sensitive cell lines during DAUN and DOX exposure.  It would be intriguing to see if an association exists between the amount of ROS generated and the sensitivity of the cell line to each drug.  If significant increases in ROS levels are detected with the sensitive cell lines, then these reactive molecules likely contribute to DAUN/DOX-induced cytotoxicity.  Also, since the sensitive cell lines exhibited lower metabolic activity towards these anthracyclines, then it is possible decreased metabolism is linked to an increase in ROS production.  One technique that allows for identification and quantitation of different ROS species is electron paramagnetic resonance (EPR) spin trapping, which  150 is of particular interest since it allows direct detection of free radicals in intact biological systems (Berliner and Fujii et al., 2004).  The detection of ROS, such as ·O2- and ·OH, is difficult to attain since these free radicals are short lived species; however, the introduction of spin trapping agents have alleviated this problem since they are able to react with free radicals to form another free radical product that is considerably more stable (Figure 38) (Khan and Swartz, 2002; Swartz et al., 2007).    Figure 38—A spin trapping chemical reaction in which 5-Diethoxyphosphoryl-5-methyl-1-pyrroline N- oxide (DEPMPO), the spin trapping agent, reacts with a free radical to form a radical adduct that is more stable than the initial radical (Swartz et al., 2007).   I have performed some preliminary studies using EPR to see if: (i) ROS are generated in the in vitro metabolic assays with the AKRs and CBRs in the presence of either DAUN or DOX, and (ii) ROS levels are altered in metabolic assays with the variants exhibiting significantly reduced activity towards DAUN or DOX compared to their respective wild-type enzyme.  As a starting point, I compared the following wild- type and variant enzymes for the EPR experiments: (i) CBR1 and V88I; (ii) CBR3 and C4Y; (iii) AKR7A2 and A142T; as well as (iv) AKR1C3 and R170C.  The metabolic assays for the EPR experiments were performed using identical conditions to the assays used in determining DAUNol/DOXol levels (Chapters 2 and 3), except for the reaction time being reduced to 30 min, as well as the addition of the DEPMPO spin-trapping agent  151 (20 mM) and the chelating agent, diethylenetriaminepentaacetic acid (DTPA) (1 mM). DTPA sequesters any transition metal ions in the reaction medium since they can induce ROS by Fenton reactions, an oxidation process in which reaction of H2O2 with iron generates ·O2- and ·OH (Anipsitakis and Dionysiou, 2004; Valko et al., 2005; Valko et al., 2006).  This alleviates any potential background ROS signal contribution from the medium.  An in vitro positive control [xanthine (0.25 mM), xanthine oxidase (0.08 U/ml), DEPMPO (20 mM) and DTPA (1 mM) in PBS, pH 7.4 at 37oC for 30 min (Dambrova et al., 2000)] as well as a negative control (without the addition of DEPMPO) were performed concurrently.   Following completion of the assays, aliquots of the reaction medium were dispensed into quartz EPR tubes, frozen in liquid nitrogen, and subjected to EPR analysis.  An example of the EPR spectra generated from the positive and negative control assays is illustrated in Figure 39.  Figure 39—EPR spectra of the positive and negative controls assays using DEPMPO.  For the positive control assay (xanthine/xanthine oxidase), the spectra representing the DEPMPO-superoxide spin adduct is given in red while the negative control (no DEPMPO) is represented in blue.  Recordings shown were performed on samples withdrawn 15 min after the start of the incubation. The EPR spectrometer settings were as follows: microwave frequency, 9.41 GHz; microwave power, 0.6339 mW; modulation frequency, 100 kHz; modulation amplitude, 1 Gauss; receiver gain, 60 dB; and  time constant, 1.28 msec.  152  For the in vitro assays involving the AKRs and CBRs, no ROS levels were detected.  Based on the expert advice given by Dr. Pierre Kennepohl (Department of Chemistry, UBC) as well as Mr. Vlad Martin-Diaconescu (a recent Ph.D. alumnus from Dr. Kennepohl’s laboratory), modifications were made to the assay conditions for the purposes of increasing ROS detection.  These modifications included (i) increasing the concentration of DEPMPO in the assays to 100 mM, (ii) dispensing the assay media into EPR tubes that hold larger volumes, and (iii) repeating the assays using another spin trapping agent, N-tert-butyl-α-phenylnitrone (PBN) at 20 and 100 mM.  Again, no ROS levels were detected using any of the aforementioned assay modifications.  Since the techniques employed in these EPR studies with DEPMPO are sensitive enough to detect ROS at the levels typically found in cells (Liu et al., 1999; Valgimigli et al., 2001; Mojovic et al., 2005; Hardy et al., 2007; Bacic et al., 2008), I conclude that no significant amount of ROS are produced by these enzymatic reactions.  Due to these findings, I did not proceed further with looking at ROS in my research project. Even though the in vitro assays did not generate detectable levels of ROS, these preliminary findings do not rule out the contribution of ROS to anthracycline-induced cardiotoxicity.  Future studies could be performed ex vivo by comparing ROS levels following either DAUN or DOX exposure between non-transfected H9c2 heart cell lines and those that are transfected with the wild-type AKR or CBR based on other studies. L'Ecuyer et al. (2001) demonstrated that H9c2 cells can be used to study free radical production, and can be engineered to express foreign genes at controllable levels, making them a suitable system to study molecular responses to oxidative damage.  Previous  153 works in this area include studies of oxidative cell damage caused by DOX (L’Ecuyer et al., 2001; Filigheddu et al., 2001; Spallarossa et al., 2004).  Successful transfection can be verified by Western blotting with AKR or CBR specific antibodies, and these cell lines should have a greater ability to metabolize DAUN and DOX.  If the findings from this set of future studies demonstrate that non-transfected H9c2 cell lines generate ROS at significantly greater levels than the transfected H9c2 cell lines, then it is likely that decreased metabolism (i.e., more of the parent drug present), which is inversely related to cytotoxicity from my findings in Chapter 4, is also inversely related to ROS generation.  5.4.2 Cancer patient correlation studies to determine if AKR and CBR variant alleles may serve as genetic biomarkers of cardiotoxicity arising from DAUN/DOX therapy  Since the studies performed in this thesis reveal that the parent drug is more cytotoxic than its primary metabolite, it is possible that those individuals who have an ns- SNP in the appropriate gene or combination of genes (which includes one or more of the AKRs and/or CBRs) could be at higher risk for developing cardiotoxicity following exposure to DAUN or DOX.  This leads into the following hypothesis and prediction:  HYPOTHESIS: Individuals with ns-SNPs in genes encoding AKR and CBR enzymes are at greater risk for the development of cardiotoxicity if they receive DAUN or DOX treatment.  PREDICTION:  If ns-SNPs in one or more of the AKR or CBR genes contribute to, and thus are mechanistically associated with, the likelihood of developing cardiotoxicity  154 following drug treatment, then this hypothesis makes the prediction that those ns-SNPs that have the strongest effect on enzyme activity are more likely to be found among patients who develop cardiotoxicity.  At the same time, those variants that have a lesser affect on enzyme activity would be found at slightly lower levels among cardiotoxic patients, or at approximately the same levels as found in the normal population.  Genotyping analyses are now quite easy to do, although they are not routinely done.  The testing of the hypothesis requires genotyping a relatively large number (several hundred) cardiotoxic patients along with a control population, and performing association studies between each genotype (the individual ns-SNPs and haplotype combinations) and (i) cardiotoxicity, as well as (ii) no affect on the heart (control).  The measurement of a cardiotoxicity is a reduction in left ventricular ejection fraction (LVEF; the fraction of blood pumped out of the left ventricle with each heart beat) drop by more than 10% after the start of treatment, or an LVEF of less than 50% (Schwartz et al., 1987; Nousiainen et al., 2002; Daugaard et al., 2005; Belham et al., 2007). Whether a correlation exists between the individual ns-SNPs or haplotype combinations and the development of cardiotoxicity, the next question becomes whether the mutation is a simple biomarker or does it play a mechanistic role in the likelihood of developing cardiotoxicity following drug treatment.  If the mutation has a mechanistic role, rather than being a simple biomarker, then there should be a strong correlation between strong mutant alleles and cardiotoxicity and a lesser correlation with the weaker alleles. The establishment of AKR and CBR genetic biomarkers would allow clinicians to  155 identify individuals at high risk for developing cardiotoxicity by simply collecting blood samples from patients prior to DAUN or DOX therapy and extracting DNA for purposes of genotyping for the presence of the high risk variant allele(s).  This would allow patients and clinicians to choose alternate therapies that will minimize their risk.  For patients that are at low risk of developing cardiotoxic effects, dosage regimens of DAUN and DOX could be increased to treat cancers effectively. If AKRs and CBRs are solely responsible for DAUN/DOX metabolism, then one would expect that cancer patients carrying alleles leading to the expression of AKR/CBR enzyme variants with significantly reduced metabolic activity will be likely to have lower rates for metabolizing these anthracyclines.  However, AKR/CBR-mediated metabolism is likely a single aspect of what is highly complex patient phenotype when it comes to cardiotoxicity.  The likelihood that a single variant allele in one enzyme will be the lone determinant of an individual’s susceptibility to this adverse effect is low.  Therefore, genotyping studies should include looking at other enzymes capable of metabolizing DAUN and DOX, such as the cytochrome P450 enzymes (CYPs), for which there are variant alleles in the human population (Goeptar et al., 1993; Zhang et al., 2009). However, CYPs (i.e., CYP2D6) are apparently involved to a minor extent in the metabolism of anthracyclines (Le Guellec et al., 1993).  Like the AKRs and CBRs, it is possible that some of the CYP variants may significantly reduce metabolism of these anthracyclines compared to their wild-type counterparts.  In addition to looking at drug metabolizing enzymes, genotyping studies look at the frequency of genes representing efflux transporters since they may alter DOX/DAUN pharmacokinetics to the point of developing anthracycline-induced cardiotoxicity.  For example, one study suggested that  156 cardiotoxicity was associated with the G671V variant of the DOX efflux transporter multidrug resistance associated protein 1 (MRP1) and with the V1188E-C1515Y haplotype (i.e., set of alleles of closely linked loci on a chromosome that tend to be inherited together) of the functionally similar efflux transporter multidrug resistance associated protein 2 (MRP2) (Deng and Wojnowski et al., 2007).  Overall, genetic biomarkers in the form of SNPs in genes encoding drug metabolizing enzymes and transporters could be successfully used to identify patients at high risk of cardiotoxicity prior to therapy.  This would facilitate early diagnosis of susceptibility to cardiotoxicity and improve DAUN and DOX therapy.  On the other hand, if the metabolite, or a down stream product of the drug metabolism, is the primary cause of the damage to the heart, then those individuals that have an ns-SNP in the appropriate AKR or CBR gene, or combination of genes, would be more resistant to the development of cardiotoxicity.  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GENES VARIANTSa FORWARD PRIMER (5'3') REVERSE PRIMER (5'3') I15F [AT] CAAGATGCCCTTCCTGGGGTTGG CCAACCCCAGGAAGGGCATCTTG H42L [AT] CGGGTACCGCCTCATCGACTGTGC CC GGGCACAGTCGATGAGGCGGTA CCCG L73V [CG] GCGTGAGGAGGTCTTCATCGTCAG C GCTGACGATGAAGACCTCCTCAC GC K90E [AG] GGGCCTGGTGGAAGGAGCCTGCC GGCAGGCTCCTTCCACCAGGCCC G204S [GA] GCCAGTCCAAAAGCATCGTGGTGA C GTCACCACGATGCTTTTGGACTG GC AKR1B1 T288I [CT] CCAGGATATGACCATCTTACTCAGC TAC GTAGCTGAGTAAGATGGTCATAT CCTGG P87S [CT] CACTTTCTTTGAGAGATCCCTTGTG AGGAAAG CTTTCCTCACAAGGGATCTCTCA AAGAAAGTG M286T [TC] GTGATGAGGAGACGGCAACCATAC TC GAGTATGGTTGCCGTCTCCTCAT CAC AKR1B10 N313D [AG] GACTATCCCTTCGATGCAGAATATT G CAATATTCTGCATCGAAGGGATA GTC R170H [GA] CCAACTTCAACCACAGGCAGCTGG AG CTCCAGCTGCCTGTGGTTGAAGT TGG AKR1C1 Q172L [AT] CTTCAACCGCAGGCTGCTGGAGAT GATCC GGATCATCTCCAGCAGCCTGCGG TTGAAG AKR1C2 F46Y     [TA] CAATAGAAGCCGGGTACCACCATA TTTGATTC GAATCAATATGGTGGTACCCGGC TTCTATTG H5Q [CG] GGAAGAATGGATTCCAAACAGCAG TGTGTAAAGCTAAATG CATTTAGCTTTACACACTGCTGTT TGGAATCCATTCTTCC R66Q [GA] GGTTGGACTGGCCATCCAAAGCAA GATTGCAGATG CATCTGCAATCTTGCTTTGGATG GCCAGTCCAACC A106T [GA] GGAAAACTCACTGAAAAAAACTCA ATTGGACTATGTTGAC GTCAACATAGTCCAATTGAGTTT TTTTCAGTGAGTTTTCC R170C [CT] GGGTGTCAAACTTCAACTGCAGGC AGCTGGAGATG CATCTCCAGCTGCCTGCAGTTGA AGTTTGACACCC AKR1C3 P180S [CT] GAGATGATCCTCAACAAGTCAGGA CTTAAGTACAAGC GCTTGTACTTAAGTCCTGACTTGT TGAGGATCATCTC G135E [GA] GCCACTACCAAAAGATGAAAATGA AAAAGTAATATTCGACACAGTGG CCACTGTGTCGAATATTACTTTTT CATTTTCATCTTTTGGTAGTGGC AKR1C4 S145C [CG] CAGTGGATCTCTGTGCCACATGGG AG CTCCCATGTGGCACAGAGATCCA CTG  181 GENES VARIANTSa FORWARD PRIMER (5'3') REVERSE PRIMER (5'3') L311V [CG] GATATGTTGTCATGGATTTTGTTAT GGACCATCCTGATTATC GATAATCAGGATGGTCCATAACA AAATCCATGACAACATATC V135M [GA] CTGCAGTGTCCCCAAATGGACCTCT TCTACC GGTAGAAGAGGTCCATTTGGGGA CACTGCAG Q157H [GC] GCATGCCTGCCACCGGCTGCACCA G CTGGTGCAGCCGGTGGCAGGCAT GC E180K [GA] GCTGGGAAGTGGCCAAGATCTGTA CCCTC GAGGGTACAGATCTTGGCCACTT CCCAGC G198S [GA] CCACTGTGTACCAGAGCATGTACA ACGCC GGCGTTGTACATGCTCTGGTACA CAGTGG AKR7A2 S255N [GA] CGCTTCTTTGGGAATAACTGGGCTG AGACCTAC GTAGGTCTCAGCCCAGTTATTCC CAAAGAAGCG  a   The base pair mutation is given beneath each variant [in square brackets].  Also, the mutated base pair is underlined in the forward and reverse primer sequences.                                182   Supplemental Figure 1—Purification of human recombinant 6x-His-tagged AKR1A1 variant (E55D and N52S) and AKR1B1 variant enzymes (I15F, H42L, L73V, K90E, G204S, and T288I).  (Left) Gel stained with SYPRO® Ruby following SDS-PAGE showing purified protein fraction (lane 3; 2 µg), free of contaminating proteins from the bacterial lysate (lane 1; 10 µg total protein). Removal of contaminating proteins is observed in flow through fraction from Qiagen purification procedures [Ni-NTA column flow through (lane 2; 10 µg total protein)].  (Right) Western blot detection of transformed lysate (lane 6) and purified protein fractions (lane 8), confirms expression of the desired AKR protein.  Little immunoreactivity was detected in the flow through fraction (lane 7) suggesting that majority of the enzyme was bound to the Ni-NTA resin prior to its elution.  GST-tagged full recombinant proteins (Abnova® Corporation, Taipei City, Taiwan; lane 5; 2 µg total protein) were used as positive controls for antibody immunoreactivity for all enzymes.  No antibody immunoreactivity was observed for untransformed bacterial lysate (lane 4; 10 µg total protein).  M refers to the molecular weight markers.  183   Supplemental Figure 2—Purification of human recombinant 6x-His-tagged AKR1C4 variant (G135E, S145C, and L311V), AKR1C2 variant (F46Y), and AKR1C1 variant enzymes (R170C and Q172L).  (Left) Gel stained with SYPRO® Ruby following SDS-PAGE showing purified protein fraction (lane 3; 2 µg), free of contaminating proteins from the bacterial lysate (lane 1; 10 µg total protein). Removal of contaminating proteins is observed in flow through fraction from Qiagen purification procedures [Ni-NTA column flow through (lane 2; 10 µg total protein)].  (Right) Western blot detection of transformed lysate (lane 6) and purified protein fractions (lane 8), confirms expression of the desired AKR protein.  Little immunoreactivity was detected in the flow through fraction (lane 7) suggesting that majority of the enzyme was bound to the Ni-NTA resin prior to its elution.  GST-tagged full recombinant proteins (Abnova® Corporation, Taipei City, Taiwan; lane 5; 2 µg total protein) were used as positive controls for antibody immunoreactivity for all enzymes.  No antibody immunoreactivity was observed for untransformed bacterial lysate (lane 4; 10 µg total protein).  M refers to the molecular weight markers.   184   Supplemental Figure 3—Purification of human recombinant 6x-His-tagged AKR1C3 variant (H5Q, R66Q, A106T, R170C, and P180S) and AKR1B10 variant enzymes (P87S, M286T, and N313D).  (Left) Gel stained with SYPRO® Ruby following SDS-PAGE showing purified protein fraction (lane 3; 2 µg), free of contaminating proteins from the bacterial lysate (lane 1; 10 µg total protein). Removal of contaminating proteins is observed in flow through fraction from Qiagen purification procedures [Ni-NTA column flow through (lane 2; 10 µg total protein)].  (Right) Western blot detection of transformed lysate (lane 6) and purified protein fractions (lane 8), confirms expression of the desired AKR protein.  Little immunoreactivity was detected in the flow through fraction (lane 7) suggesting that majority of the enzyme was bound to the Ni-NTA resin prior to its elution.  GST-tagged full recombinant proteins (Abnova® Corporation, Taipei City, Taiwan; lane 5; 2 µg total protein) were used as positive controls for antibody immunoreactivity for all enzymes.  No antibody immunoreactivity was observed for untransformed bacterial lysate (lane 4; 10 µg total protein).  M refers to the molecular weight markers.  185   Supplemental Figure 4—Purification of human recombinant 6x-His-tagged AKR7A2 variant enzymes (V135M, A142T, Q157H, E180K, G198S, S255N).  (Left) Gel stained with SYPRO® Ruby following SDS- PAGE showing purified protein fraction (lane 3; 2 µg), free of contaminating proteins from the bacterial lysate (lane 1; 10 µg total protein). Removal of contaminating proteins is observed in flow through fraction from Qiagen purification procedures [Ni-NTA column flow through (lane 2; 10 µg total protein)].  (Right) Western blot detection of transformed lysate (lane 6) and purified protein fractions (lane 8), confirms expression of the desired AKR protein.  Little immunoreactivity was detected in the flow through fraction (lane 7) suggesting that majority of the enzyme was bound to the Ni-NTA resin prior to its elution.  GST- tagged full recombinant proteins (Abnova® Corporation, Taipei City, Taiwan; lane 5; 2 µg total protein) were used as positive controls for antibody immunoreactivity for all enzymes.  No antibody immunoreactivity was observed for untransformed bacterial lysate (lane 4; 10 µg total protein).  M refers to the molecular weight markers.   186 Supplemental Table 2—Primers for creating non-synonymous single nucleotide polymorphic variants of human CBRs using site-directed mutagenesis.  GENES VARIANTS a FORWARD PRIMER (5'3') REVERSE PRIMER (5'3') V88I [GA] CTGGACGTGCTGATCAACAACGC GG CCGCGTTGTTGATCAGCACGTCC AG CBR1 P131S [CT] CTCCCTCTAATAAAATCCCAAGG GAGAGTGG CCACTCTCCCTTGGGATTTTATTA GAGGGAG P131S [CT] CTGCCGATAATGAAATCTCATGG GAGAGTGG CCACTCTCCCATGAGATTTCATTA TCGGCAG V244M [GA] GAAAGACAGCATCAGGACTATG GAGGAGGGGGCTGAGAC GTCTCAGCCCCCTCCTCCATAGTC CTGATGCTGTCTTTC C4Y [GA] GAATGTCGTCCTACAGCCGCGTG GCG CGCCACGCGGCTGTAGGACGACA TTC M235L [AT] GACCAGTGAAGACAGACTTGGAT GGGAAAGACAG CTGTCTTTCCCATCCAAGTCTGTC TTCACTGGTC L84V [CG] CAAGGAGTACGGGGGGGTCAAT GTACTGGTCAAC GTTGACCAGTACATTGACCCCCC CGTACTCCTTG V93I [GA] CAACAACGCGGCCATCGCCTTCA AGAG CTCTTGAAGGCGATGGCCGCGTT GTTG CBR3 D239V [AT] GACATGGATGGGAAAGTCAGCAT CAGGACTGTG CACAGTCCTGATGCTGACTTTCC CATCCATGTC CBR4 L70M     [CA] CATTTGAAGAGATGGAGAAACAT TTAGGTCGAG CTCGACCTAAATGTTTCTCCATCT CTTCAAATG  a   The base pair mutation is given beneath each variant [in square brackets].  Also, the mutated base pair is underlined in the forward and reverse primer sequences.    187    Supplemental Figure 5—Purification of human recombinant 6x-His-tagged CBR variant enzymes.  The top two panels represent variants of CBR1 (V88I and P131S) followed by the CBR4 variant (L70M) and the CBR3 variants (C4Y, L84V, V93I, P131S, M235L, D239V, and V244M).  (Left) Gel stained with SYPRO® Ruby following SDS-PAGE showing purified protein fraction (lane 3; 2 µg), free of contaminating proteins from the bacterial lysate (lane 1; 10 µg total protein). Removal of contaminating proteins is observed in flow through fraction from Qiagen purification procedures [Ni-NTA column flow through (lane 2; 10 µg total protein)].  (Right) Western blot detection of transformed lysate (lane 6) and purified protein fractions (lane 8), confirms expression of the desired CBR protein.  Little immunoreactivity was detected in the flow through fraction (lane 7) suggesting that majority of the enzyme was bound to the Ni-NTA resin prior to their elution.  GST-tagged human CBR4 recombinant protein (Abnova® Corporation, Taipei City, Taiwan; lane 5; 2 µg total protein) and human liver cytosol (lane 5; 20 µg total protein; for CBR1 and CBR3) was used as positive controls for antibody immunoreactivity for these enzymes.  No antibody immunoreactivity is observed for untransformed bacterial lysate (lane 4; 10 µg total protein).  M refers to the molecular weight markers.

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