An Evaluation of Select Prolactin Antagonists in Human Breast Cancer Cells

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THE POTENTIAL ROLE OF POTENT PROLACTIN ANTAGONISTS AS CHEMOTHERAPEUTICS FOR HUMAN CANCERS: AN EVALUATION OF SELECT PROLACTIN ANTAGONISTS IN HUMAN BREAST CANCER CELLS

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the Graduate

School of The Ohio State University

Colleen Marie Almgren, B.S., D.V.M.

* * * * *

The Ohio State University

2005

Dissertation Committee: Approved by Professor Charles L. Brooks, Adviser

Professor Donna F. Kusewitt ______Adviser Professor Steven E. Weisbrode Department of Veterinary Biosciences

ABSTRACT

Prolactin stimulates growth and lactation in mammary epithelial cells. Recent evidence shows most human breast tumors produce prolactin and express prolactin receptors, suggesting a local autocrine/paracrine system. Existing prolactin antagonists (G129R human prolactin) block prolactin receptor binding sites, interrupting the lactogenic autocrine system and slow human breast tumor cell growth.

Unfortunately, the retention of substantial agonist activity renders these antagonists ineffective in investigating the role of prolactin in vivo.

We have designed a new and effective category of prolactin receptor antagonist. A lead compound, Delta41-52 human prolactin, has 12 deleted residues and retains 100-fold less agonist activity than earlier compounds. The Ohio State

University has sought patent protection for the unique design of this new class of prolactin antagonists.

The work presented in this dissertation tests and compared the activity of

Delta41-52 with wild-type and G129R human prolactins using standard bioassays.

These studies have shown that prolactin acted not as a mitogen in human breast cancer cells as previously thought, but functioned as a survival factor. Using techniques, including microarrays, morphology and caspace assays, I have shown Delta41-52 - ii - human prolactin induced apoptosis in cell lines from both a human breast tumor

(T47D) and a murine lymphoma (FDC-P1). In both cell lines, Delta41-52 was more effective than G129R human prolactin in decreasing the survival of cells in vitro.

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Dedicated to my family and friends, “our gang”, whose unending love, support and encouragement made this work possible With my love always

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ACKNOWLEDGMENTS

A career in science and medicine is a lifelong journey of learning which cannot be achieved in solitude, but requires extensive and continuous interchange of knowledge, experience and ideas. And so, to the many educators and colleagues who have enriched and enlightened my life with their knowledge, assistance and friendship over the years, I offer my deepest and heartfelt gratitude. I wish to thank my adviser, Charles L. Brooks, for his guidance, encouragement, support and patience in all aspects of my graduate program. He is a scientist whose research ethics are beyond reproach and a “true educator” in every sense, taking as much pride and effort in his teaching as his research. He always has the best interest of his students in mind and always has time for any student, no matter how busy he is at the time. He has taught me many valuable lessons, not only about science, but about life in general. I thank Lynne Olson and Diane McClure for providing a solid initial foundation during the early years of my research career and my current committee members, Donna Kusewitt and Steven Weisbrode, for their guidance and support during the final stages of my doctoral project. Numerous people have assisted with various aspects of this work. I especially thank Samar Al Maalouf, Scott McCardle, Kyong Lee and Mark Troyer for may hours of hard work and dedication, Kate Hayes not only for her expertise in QRT-PCR but

- v - also for her encouragement and perpetual optimism, Richard Meister for flow cytometry analysis, Gorden Renkes for training in circular dicroism spectroscopy, Kari Green-Church and staff at the Campus Chemical Instrumentation Center (CCIC) for performing mass spectrometry and Karl Kornacker for his statistical expertise and analysis of the microarray data. To Joan Wicks, Francis Peterson, Emanuel Schenck, Jeff Voorhees, Michelle Corliss and Laura DePalatis for their friendship, antics and making the lab a fun place to work. To Danielle Driscoll, Louise Douce and Patti Carlton, many thanks and much gratitude for helping me realize that seemingly insurmountable obstacles can be overcome with persistence, support and a positive attitude. I am deeply indebted to them for supporting and guiding me through a difficult life transition. I thank Karen Duda, Uma Sivaprasad, Daphne Vasconcelos, Laurie Dickow Fomby, Wayne Buck, Rani Sellers, Julie Hutt, Melinda Butsch Kovacic and Sue Wojick not only for their intellectual and scientific contributions, but also for graciously supporting and assisting me in a time of need despite their busy schedules and for their continued friendship. I would like to thank the faculty of The Ohio State University Department of Veterinary Biosciences for outstanding training in Veterinary Pathology and the support staff including Sherry Frisch, Elaine Bletz, Lisa Wilcoz and Georgia Porcelli for their hard work, attention to detail and willingness to help. This research was supported by N.I.H. grant (R01 DK56117/DK56117-02S1) and The Ohio State University Fellowship Funds (Presidential, Herschel T. Meredith and Glenn Barber).

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VITA

February 24, 1960 ...... Born – Chicago, Illinois

1982...... B.S., Biology College of Liberal Arts and Sciences University of Illinois Urbana, Illinois

1985...... B.S., Veterinary Medicine College of Veterinary Medicine University of Illinois Urbana, Illinois

1987 ...... Doctor of Veterinary Medicine College of Veterinary Medicine University of Illinois Urbana, Illinois

1995- 1996 ...... Veterinary Anatomic Pathology Resident Department of Veterinary Pathobiology The Ohio State University Columbus, Ohio

1996- Present ...... Graduate Research Associate Department of Veterinary Biosciences The Ohio State University Columbus, Ohio

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PUBLICATIONS

Research Publication:

1. Almgren CM, Olson LE (1999) “Moderate Hypoxia Increases HSP90 Expression in Excised Rat Aorta.” Journal of Vascular Research, 36: 363-371.

Pathology Publication:

1. Almgren CM, McClure DE (2000) “Granulomatous Pneumonia in the Opossum (Didelphis virginiana) associated with an intracellular fungal agent.” Comparative Medicine, 50(3): 323-328

FIELDS OF STUDY

Major Field: Veterinary Biosciences

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TABLE OF CONTENTS

Page Abstract ...... ii

Dedication ...... iv

Acknowledgments...... v

Vita...... vii

List of Tables ...... xiii

List of Figures ...... xiv

List of Abbreviations ...... xvii

Chapters:

1. Introduction...... 1 1.1 Project overview...... 1 1.2 Background and significance ...... 5 1.3 Prolactin and human breast cancer...... 5 1.4 The physiology, structure and functions of human prolactin...... 7 1.4.1 General overview of human prolactin and related proteins ...... 7 1.4.2 The human prolactin gene and pituitary versus extrapituitary prolactin synthesis and secretion...... 11 1.4.3 Human prolactin protein and posttranslational modifications ...... 13 1.5 The structure of human prolactin...... 14 1.6 Binding of prolactin to the prolactin receptor...... 19 1.6.1 Structural and functional binding epitopes ...... 20 1.7 Structure of the human prolactin receptor...... 22 1.7.1 The human prolactin receptor binding protein...... 26 1.7.2 Intracellular signal transduction pathways activated by prolactin receptor binding ...... 26 - ix - 1.8 Rationale associated with the design of human prolactin antagonists ...... 27 1.9 Apoptosis overview...... 31 1.9.1 General mechanisms of apoptosis ...... 31 1.9.2 Physiologic apoptosis ...... 33 1.9.3 Pathologic apoptosis ...... 33

2. Materials and Methods...... 35 2.1 Amino acid substitution within human prolactin by DNA mutagenesis...... 35 2.1.1 The pT7-7 (f-) phagemid...... 35 2.1.2 Production of single strand (ss) DNA ...... 40 2.1.3 Mutagenic primer design...... 40 2.1.4 Site-directed mutagenesis...... 41 2.1.5 Production of the Delta41-52/G129R Double Mutant (DM) hPRL ...... 44 2.2 Production of full-length recombinant human prolactin proteins...... 44 2.2.1 Protein expression...... 44 2.2.2 Cell lysis, inclusion body collection, solubilization and protein refolding ...... 44 2.2.3 Purification of recombinant human prolactin proteins...... 45 2.3 Characterization of recombinant full-length human prolactins ...... 46 2.3.1 Protein concentration...... 46 2.3.2 SDS polyacrylamide gel electrophoresis ...... 46 2.3.3 Ultraviolet (absorbance) spectroscopy...... 47 2.3.4 Fluorescent spectroscopy...... 48 2.3.5 Circular dichroism spectroscopy...... 48 2.3.6 Mass spectrometry ...... 49 2.4 General cell culture reagents ...... 50 2.4.1 Sera for cell culture ...... 50 2.4.2 General cell culture media and reagents ...... 51 2.4.3 Cell culture environment...... 53 2.5 Experimental assessment of function and relative biological activity of recombinant human prolactins ...... 53 2.5.1 FDC-P1 hPRLR cell line...... 53 2.5.1.1 Maintenance of the FDC-P1 hPRLR cell line...... 53 2.5.1.2 FDC-P1 hPRLR Cell Bioassays...... 54 2.5.2 Nb2-11C cell Line...... 55 2.5.2.1 Maintenance of the Nb2-11C cell line ...... 55 2.5.2.2 The Nb2-11C cell bioassays ...... 56 2.5.3 The human Jurkat cell line ...... 57 2.6 Analysis of recombinant human prolactins in breast cancer cells ...... 57 2.6.1 The T47D and T47Dco human breast cancer cell lines ...... 58

- x - 2.6.1.1 Maintenance of the T47D and T47Dco human breast cancer cell lines ...... 59 2.6.1.2 T47D/T47Dco breast cancer cell bioassays ...... 59 2.6.2 The MCF7 Human Breast Cancer Cell Line...... 60 2.6.2.1 Maintenance of the MCF7 Human Breast Cancer Cell Line ...... 60 2.6.2.2 MCF7 Breast Cancer Cell Bioassays ...... 61 2.6.3 Rationale for selection of human breast cancer cell types ...... 62 2.7 Total RNA extraction for microarray and QRT-PCR experiments ...... 63 2.8 Microarray (genechip) experiments ...... 65 2.9 Quantitative real-time RT-PCR ...... 68 2.9.1 Primer selection ...... 68 2.9.2 Primer design ...... 68 2.9.3 QRT-PCR standard controls ...... 71 2.9.4 Experimental conditions...... 72 2.10 ATP assays...... 72 2.11 AKT kinase assay...... 73 2.12 Western blot...... 74 2.13 Cell morphology and Oil Red O lipid staining ...... 75 2.14 Flow cytometric analysis for mitochondrial transmembrane potential...... 76

3. Initial comparison of biological activity of recombinant human prolactins ...... 80 3.1 Introduction...... 80 3.2 Protein characterization and biologic activity...... 80 3.3 Biologic activity of recombinant human prolactins...... 82 3.4 Biologic activity of recombinant human prolactins in human breast cancer cell lines ...... 83 3.5 Cell morphology and evaluation of lipid accumulation by Oil Red O lipid stain ...... 91 3.6 Discussion ...... 97

4. Effect of human prolactin antagonists on apoptosis ...... 100 4.1 Introduction...... 100 4.2 Results...... 104 4.2.1 Caspace western immunoblotting ...... 104 4.2.2 ATP assays...... 105 4.2.3 Flow cytometry ...... 118

5. Recombinant human prolactin and signal transduction pathways in breast cancer cells ...... 131 5.1 Introduction...... 131 5.2 Results...... 132

- xi - 6. Global Analysis of Recombinant Human Prolactin Effects on Human Breast Cancer Cells ...... 135 6.1 Introduction...... 135 6.2 Results...... 138 6.2.1 Microarray experiment #1...... 138 6.2.2 Microarray experiment #2 (time course evaluation)...... 144 6.2.3 Evaluation of the repeatability of microarray data between experiments ...... 145 6.3 Discussion ...... 145

7. Comparison of Quantitative RT-PCR and Microarray Data...... 148 7.1 Introduction...... 148 7.2 Apoptosis inhibitor 5 (API5) results ...... 149 7.3 Aven expression results ...... 154 7.4 Human prolactin (hPRL) expression results ...... 156 7.5 Human prolactin receptor (hPRLR) expression results ...... 158 7.6 NfκβIA expression results...... 160 7.7 Prolactin-inducible protein (PIP) expression results...... 165 7.8 Human growth hormone (hGH) mRNA expression ...... 169 7.9 Discussion...... 171

Appendix A (microarray experiment #1 additional data) ...... 173 A.1 Genes with statistically significant up-regulation by Delta41-52 hPRL (fold change as compared with WT hPRL)...... 174 A.1 Genes with statistically significant down-regulation by Delta41-52 hPRL (fold change as compared with WT hPRL)...... 175 A.3 Gene expression significantly altered by treatment of T47D human breast cancer cells with WT hPRL alone or in combination with Delta41-52 hPRL for 48 hours duration (normalized mean values for each gene)...... 176

List of references and literature cited...... 177

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LIST OF TABLES

Table Page

1.1 Amino acid residues and secondary structure of hPRL and hGH ...... 17

1.2 Tissue specificity of the hPRL receptor promoters ...... 23

2.1 Gibco, Invitrigen Life Technologies cell culture reagents...... 52

2.2 Human breast cancer cell lines...... 58

2.3 Primer sequences for quantitative real-time RT-PCR ...... 70

4.1 Analysis of WT and hPRL antagonists in FDC-P1 cells by flow cytometry ...129

4.2 Analysis of mutant hPRL recombinant proteins in FDC-P1 cells by flow cytometry for evaluation of potential antagonist activity ...... 129

6.1 Genes significantly upregulated by treatment of T47D human breast cancer cells for 48 hours with Delta41-52 hPRL antagonist ...... 142

6.2 Microarray experiment #2 data table ...... 146

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LIST OF FIGURES

Figure Page

1.1 Structure of human prolactin (PDB# 1N9D) ...... 2

1.2 Composite diagram of four α-helical cytokine/hematopoietic proteins...... 9

1.3 Overall structure of human prolactin with labeled helices...... 16

1.4 Comparison of human prolactin and human growth hormone structures...... 19

1.5 Binding of human prolactin to the human prolactin receptor ...... 21

1.6 Human prolactin receptor binding domain (extracellular hPRLR domain) ...... 25

1.7 Human G129R prolactin antagonist (size comparison of aa mutation) ...... 29

1.8 Comparison of hPRL Delta41-52 and hGH(∆32-46) protein structures...... 30

2.1 Illustration of the original PT7-7 phagemid (S. Tabor, Harvard Medical School) ...... 37

2.2 Modified PT7-7(f-) phagemid (F. Peterson, The Ohio State University)...... 38

2.3 Kunkel method of site-directed mutagenesis ...... 43

3.1 Analysis of FBS and CSS in T47D human breast cancer ...... 85

3.2 Evaluation of 5% FBS on T47D cell proliferation ...... 86 - xiv -

3.3 Analysis of low concentrations FBS and CSS in T47D cells ...... 87

3.4 T47Dco human breast cancer cell bioassay ...... 89

3.5 MCF7 human breast cancer cell bioassay...... 90

3.6 Oil red O lipid staining of T47D cells 48 hours post Delta41-52hPRL treatment.95

3.7 Oil red O lipid staining of T47D cells 48 hours post WT and G129R hPRL treatment ...... 96

4.1 Cleaved caspase 7 western immunoblot ...... 105

4.2 ATP standard curve in T47D/T47Dco cell media...... 107

4.3 ATP standard curve in MCF7 cell media...... 108

4.4 Comparison of ATP standard curve in T47D/Dco and MCF7 cell media...... 109

4.5 ATP concentrations in prolactin treated T47D cells...... 112

4.6 ATP concentrations in prolactin treated T47Dco cells ...... 113

4.7 MCF7 human breast cancer cell ATP assay ...... 116

4.8 Diagramatic representation of a flow cytometry histogram of untreated, unstained cells ...... 118

4.9 Lack of autofluorescence in untreated, unstained Jurkat cells...... 119

4.10 Flow cytometry histogram of untreated, unstained FDC-P1 hPRLR cells ...... 120

4.11 Untreated, unstained T47D breast cancer cells...... 121

4.12 Propidium iodide (PI) fluorescence for detection of live/apoptotic versus dead cells by flow cytometry...... 122

4.13 Diagramatic illustration of a cell populations as stained by the fluorochrome DiOC6(3) analyzed by flow cytometry ...... 123

4.14 Normal, live FDC-P1 cell population stained with DiOC6(3) only ...... 124

- xv - 4.15 Carbamoyl cyanide m-chlorophenylhydrazone m-CICCP) disruption of inner mitochondrial membrane potential (∆Ψm) ...... 125

4.16 Diagram illustrating the pattern of cells detected by flow cytometry using dual fluorochrome staining (PI and DiOC6(3))...... 126

4.17 Robust apoptosis and moderate levels of necrosis induced by 4 hours treatment of human Jurkat cells with 100µM Camptothecin ...... 127

5.1 Akt kinase levels in prolactin treated T47D human breast cancer cells ...... 133

6.1 Formaldehyde agarose RNA gel electrophoresis...... 137

6.2 Wt hPRL dependent gene upregulation ...... 140

6.3 Delta41-52 hPRL dependent gene upregulation ...... 141

7.1 Apoptosis inhibitor 5 (API5) gene expression...... 150

7.2 Apoptosis inhibitor 5 (API5) mRNA expression (48 hours) ...... 151

7.3 Apoptosis inhibitor 5 (API5) mRNA expression (0-96 hours) ...... 152

7.4 Aven mRNA expression...... 154

7.5 Human prolactin gene expression levels...... 156

7.6 Prolactin mRNA expression in T47D human breast cancer cells...... 157

7.7 Human prolactin receptor QRT-PCR mRNA expression ...... 159

7.8 Human prolactin receptor gene expression in T47D cells (48 hour) ...... 160

7.9 NfκβIA gene expression (48 hours)...... 163

7.10 NfκβIA mRNA expression levels ...... 164

7.11 Prolactin-inducible protein (PIP) gene expression...... 167

7.12 Prolactin-inducible protein (PIP) mRNA expression by QRT-PCR...... 168

7.13 Human growth hormone (hGH) mRNA expression ...... 170

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LIST OF ABBREVIATIONS

AKT……………………………………….serine/threonine kinase (protein kinase B)

API5……………………………………….apoptosis inhibitor 5

ATTC……………………………………...American Type Culture Collection

AVEN……………………………………..inhibitor of caspace activation BCA……………………………………….bicinchoninic acid/copper sulfate assay bp………………………………………….base pair °C………………………………………… degrees celsius CD…………………………………………circular dichroism cDNA………………………………………complementary dideoxy nucleic acid CSS………………………………………...charcoal dextran stripped fetal bovine serum Cys…………………………………………cysteine Delta……………………………………...... ∆ ∆…………………………………………....delta (deletion of)

DiOC6(3) ……………………………………3,3’-dihexyloxacarbocyanine DNA………………………………………..dideoxy nucleic acid dsDNA……………………………………..double-stranded dideoxy nucleic acid E. coli……………………………………….Escherichia coli bacterial cells

- xvii - FBS………………………………………….fetal bovine serum G…………………………………………….glycine GH…………………………………………..growth hormone GHR………………………………………....growth hormone receptor hGH…………………………………………human growth hormone hGHR………………………………………..human growth hormone receptor hPL…………………………………………..human placental lactogen hPRL………………………………………...human prolactin hPRLR……………………………………….human prolactin receptor hPLRbp……………………………………….human prolactin receptor binding protein JAK…………………………………………..janus kinase kb……………………………………………..kilobase kDa…………………………………………...kilodalton MAPK………………………………………..mitogen-activated protein kinase m-CICCP…………………………………… carbamoyl cyanide m-chlorophenylhydrazone mRNA………………………………………..messenger ribonucleic acid MW…………………………………………..molecular weight NFκβ1A…………………………………….. nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha NHPP………………………………………...National Hormone and Pituitary Program NIH…………………………………………..National Institutes of Health NLP………………………………………….negative log of the p-value - xviii - nm……………………………………………nanometer nM……………………………………………nanomolar O.D.…………………………………………..optical density PBS…………………………………………...phosphate buffered saline PCR…………………………………………...polymerase chain reaction PDB…………………………………………...Protein Data Base Phe…………………………………………….phenylalanine PIP…………………………………………….prolactin-inducible protein PL……………………………………………..placental lactogen PRL…………………………………………....prolactin PRLR………………………………………….prolactin receptor QRT-PCR…………………………………….quantitative (real- time) reverse transcriptase polymerase chain reaction R………………………………………………arginine RNA…………………………………………..ribonucleic acid RT…………………………………………….reverse transcription RT-PCR…………………………...... reverse transcriptase polymerase chain reaction SDS…………………………………………..sodium dodecyl sulfate SDS-PAGE…………………………………..sodium dodecyl sulfate - polyacrylamide gel electrophoresis ssDNA………………………………………..single strand dideoxy nucleic acid STAT……………………………...... signal transducers and activators of transcription Tris………………………………………….tris (hydroxymethyl) aminomethane - xix - Trp…………………………………………..tryptophan Tyr…………………………………………..tyrosine µM…………………………………………...micromolar UV……………………………………………ultraviolet WT……………………………………………wild-type

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CHAPTER 1 INTRODUCTION

1.1 Project Overview Based on critical evaluation of the structure and function of prolactin (PRL) and the corresponding prolactin receptor (PRLR) from various species, our lab and others have rationally designed and produced prolactin antagonists. Preliminary studies have shown that one of our antagonists Delta41-52 hPRL, a structurally correct sequence- modified hPRL with a deletion of 12 amino acid residues within the loop between helix 1 and helix 2 (1) (Figure 1.1), is significantly more effective in decreasing the growth and survival of human breast cancer cells in vitro than the most potent prolactin antagonist, G129R human prolactin (hPRL), currently described in the literature (2, 3). Delta41-52 hPRL is a strong prolactin receptor antagonist retaining minimal agonist activity. In the past, there has been much difficultly comparing the efficacy of prolactin antagonists produced by different laboratories. Standard growth bioassays performed poorly for evaluation of these compounds in prolactin-sensitive cell lines and human breast cancer cells.

Figure 1.1: Structure of Human Prolactin (PDB#1N9D)(4) illustrating the four α- helical structures (helix 1-red, helix 2-green, helix 3-blue, helix 4-purple), the single mini-helix (MH-black) and the 12 amino acid region deleted in the Delta41-52 human prolactin antagonist (yellow). The N-terminus (N) and C-terminus (C) are labeled for orientation.

2 This work characterizes Delta41-52 human prolactin and tests this compound in various biological assays (NB-2 cells, FDC-P1 cells transfected with the hPRLR and cell lines derived from human breast tumors) and determined that hPRL acts not as a significant mitogen in these cells as was previously thought, but instead as a breast cancer cell survival factor. Designing appropriate assays and conditions to test prolactin antagonists became of utmost importance if the in vitro activity and efficacy of these prolactin antagonists were to be compared prior to in vivo experiments. Various techniques including microarray technology, morphological studies and caspace assays are utilized to describe decreased survival and the induction of apoptosis in human breast tumor cells produced by Delta41-52hPRL antagonist treatment. Comparisons of the activity of Delta41-52hPRL to wild-type (WT hPRL) and other known prolactin antagonists have shown that Delta41-52 hPRL is significantly more effective in decreasing the survival of human breast cancer cells in vitro than the most potent prolactin antagonist described in the current literature. This potent prolactin antagonist (Delta41-52hPRL) designed, developed and produced by our laboratory was evaluated as a potential chemotherapeutic for human breast cancer and used as a model to evaluate the sequence modifications capable of altering prolactin-induced receptor dimerization and activation of signal transduction without causing global changes in the folding (tertiary structure) of the protein, with the eventual goal of creating even more potent hPRL antagonists. These modifications have produced prolactin proteins (receptor antagonists) which are: fully recognizable by the cell surface prolactin receptors due to unaltered structure; are capable of binding the prolactin receptor without activating cell signal transduction; and block the prolactin receptor thereby preventing stimulation of the cells by endogenous prolactin.

3 These sequence modified proteins can be easily produced using recombinant protein expression methods ensuring a readily obtainable and sufficient supply of these compounds without the concerns of transmitting human disease as was noted with early crude preparations of human growth hormone (5), are recognized and can bind cell surface prolactin receptors, and can be manipulated to act as potent antagonists with minimal to no agonist activity thereby inducing apoptosis and/or necrosis and decreasing the survival of breast cancer cells in vitro. These studies will better our understanding of the role of prolactin in the survival of human breast cancer cells and the progression of breast neoplasms. These studies have already revealed significant differences in the response of breast cancer cells to wild-type hPRL and hPRL antagonist treatment when compared with other cell lines commonly utilized in lactogenic bioassays (such as the NB2 rat lymphoid and FDC-P1 mouse myeloid cells transfected with the human prolactin receptor). These studies help define the role of PRL antagonists in human breast cancer therapy, especially for those cases considered refractory to treatment with current hormone-based chemotherapeutics, and provide knowledge essential for the future design of improved significantly more potent prolactin antagonists. A better understanding of both the time-course and varying effects of prolactin antagonists on different breast cancer cell lines is needed to bridge the gap in our knowledge of the mechanisms of hPRL’s biologic activity and to design improved therapeutics for human breast cancer. Others in the lab are currently using knowledge gained from this work with breast cancer cells to evaluate prolactin antagonists in human prostate and immune system cancer cell lines.

4 1.2 Background and Significance Breast cancer is a significant health risk for women affecting approximately one out of eight women in their lifetime. Breast cancer is the leading cause of death in women over 40. Only 10% of human breast cancers are considered to be the result of inherited mutations of the BRCA1 and BRCA2 genes, while the remaining 90% of cases are related to disruption of biochemical pathways involving growth factors and hormones and their receptors, including but not limited to the estrogen receptor, progesterone receptor and more recently the c-ErbB-2 receptor (6). Recent enhancements in diagnosis and treatment have significantly improved chances of breast cancer survival, but mortality rates of advanced-stage and hormone receptor negative (ER-/PR-) breast cancers have not significantly deceased due to the lack of effective therapies for these cancers. The development of chemotherapeutics for breast cancers unresponsive to current treatments, such as Tamoxifen, is currently of critical importance and of significant interest to the medical and breast cancer patient communities. 1.3 Prolactin and Human Breast Cancer Prolactin, a protein hormone and member of the cytokine/hematopoietic family of growth factors, has been thought to be a mitogen for mammary epithelial cells and is thought to play a role in human breast cancer (7-9). Prolactin receptors are present, often in significant numbers, and have been found to be biologically active in human breast cancer cells. Prolactin receptors are found in higher numbers in cancerous breast tissue compared with adjacent normal breast tissue from the same individual (10). Breast cancer cells have been shown to produce hPRL, forming a local autocrine/paracrine prolactin loop within breast tissue (11, 12).

5 Previous studies blocking pituitary-produced prolactin, with the centrally acting dopamine agonist bromocriptine, were deemed minimally effective or ineffective in treating breast cancer thus causing hPRL to be disregarded as a major contributing factor in breast cancer progression (13-15). Failure of treatments blocking pituitary hPRL production, are now thought to be due to extrapituitary hPRL production by many tissues throughout the body, including local production of hPRL within the mammary gland. More recent identification and investigation of local autocrine/paracrine hPRL stimulation within the breast has spurred an increased awareness of the significance of hPRL in breast cancer and stimulated a renewed interest in developing potent hPRL antagonists capable of blocking or inactivating the hPRLR locally at the level of the breast cancer cell (8, 16-18). Recent research in the breast cancer arena is defining large gaps in our knowledge and identifying many significant differences between cell lines derived from different breast tumors. These breast cancer cell lines have recently been found to differ not only in their response to treatment, but also in the signal transduction pathways utilized by the cells upon receptor dimerization. Breast cancer cell lines have recently been found to vary greatly in their utilization of different death/survival pathways and even in the caspace isoforms these cells express. Researchers are also uncovering crosstalk between various cell surface receptor pathways, and discoveries such as the interaction between hPRL and the ErbB-2 receptor (an indicator of poor prognosis for breast cancer patients) (6), underscores the importance expanding our knowledge and better defining the role of prolactin in human breast cancer.

6 1.4 The Physiology, Structure and Functions of Human Prolactin 1.4.1 General Overview of Human Prolactin and Related Proteins Human prolactin is a 23,000 dalton (23kDa) polypeptide hormone, a member of the growth hormone/prolactin/placental lactogen family of the group 1 helix bundle protein hormones (19-22). Based on their structural, functional and binding properties, this group of protein hormones is thought to have arisen from a common gene by gene duplication with the divergence of the human growth hormone (hGH) and hPRL genes occurring approximately 400 million years ago (22-29) and the human placental lactogen (hPL) line diverging later from either the hGH gene (in primates) or hPRL gene (in nonprimates)(27, 30-32). Placental lactogen has GH-like biologic actions in primates, in which the PL gene descended from the ancestral GH gene, and has PRL- like biological activities in nonprimates, in which the PL gene diverged from the PRL gene. Recently, the GH/PRL/PL protein family has been included in the larger family of hematopoietic cytokines, based on similarities in structural, genomic, biologic and immunologic functions of these molecules (17, 21, 33). This group of hematopoietic cytokines all share the same four helix bundle (Figure 1.2) and include GH, PRL, several interleukins (34) (35), leukemia inhibitory factor (LIF) (36), granulocyte- macrophage colony stimulating factor (GM-CSF) and may others (37). In addition to PRL’s actions as a neuroendocrine and polypeptide hormone, PRL has recently been classified as a cytokine (17, 21, 33). Human PRL acts as both a hormone and a cytokine. It is secreted by the anterior pituitary and released into the bloodstream, as for other hormones, where it travels to distant sites to exert its direct effects on lactation and reproduction. Extrapituitary hPRL acts more like a cytokine, being produced locally in many tissues,

7 and acting as an immunomodulator and an autocrine/paracrine growth or survival factor for many cell types including neoplastic cells of the breast, female reproductive tract and prostate (4).

Figure 1.2: Composite diagram showing the typical four α–helical bundles characteristic of the PRL/GH/PL protein family and also of the larger cytokine/hematopoietic superfamily. Shown (in clockwise order) are hPRL (PDB#1N9D)(4), hGH (PBD#1HGU)(38), Leukemia Inhibitory Factor (LIF)(PDB#1LKI)(39, 40) and Erythropoietin (EPO)(PDB#1BUY)(39-41).

9 Prolactin was initially named due to its ability to stimulate lactation in rabbits in response to suckling and to stimulate growth of the crop sac and production of crop milk in pigeons (29, 42). Today, more than 300 biological activities are attributed to the actions of PRL (43) including effects on: reproduction, maintenance of the corpus luteum in some species, lactation – both initiation of milk synthesis (lactogenesis) and maintenance of milk production (galactopoiesis), mammary gland lobuloalveolar growth and development (mammogenesis), testosterone regulation, maturation of the neonatal immune and neuroendocrine systems, maternal behavior, osmoregulation, immune system regulation, angiogenesis, bone formation and maintenance through direct effect on osteoblasts, male lacrimal gland sexual dimorphism in rodents, harderian gland porphyrin secretion and carbohydrate metabolism primarily in females

(17, 29). Due to PRL’s many biological actions, it has been proposed that PRL be renamed “versatilin” or “omnipotin”(29, 44).

The major source of both hPRL and hGH is acidophilic cells within the anterior pituitary gland. The lactotrophic (PRL-producing, mammotrophic), somatotrophic

(GH-producing) and thyrotrophic (thyrotropin-producing) cells are thought to have descended from the pituitary transcription factor–1 (Pit-1)-dependent pituitary cell line

(45-48). Human PRL is secreted primarily by lactotrophs (mammotrophs), which comprise up to 20-50% of the anterior pituitary cells (29, 49-51). GH is secreted by somatotrophs. An intermediate population of bifunctional anterior pituitary cells, the mammosomatotrophs (52-55) can secrete either PRL or GH depending on the type of signal or hormonal stimulus applied to these cells (56, 57). Estrogen causes the mammosomatotrophs to differentiate into lactotrophs (57). Human placental lactogen 10 (PL) or Prolactin-like proteins (PLP’s) are produced by syncytiotrophoblastic cells of the mammalian placenta (22, 29, 58-60).

Sequence homology varies between species, with primate PRL’s showing 97% sequence homology, but homology between rodent and primate PRL’s is only about

56% (61). Human GH and hPL share approximately 85% sequence homology. It is interesting to note, that although hGH and hPRL share only about 23% sequence homology, they are similar in structure, share many of the same binding epitopes and both have the ability to bind to and activate the PRLR.

Primate growth hormone is species specific (62-65), whereas GH in other species does not show such strict specificity. Primate GH and PL can interact with and activate both the GH (somatotrophic) receptor and the PRL (lactogenic) receptor (66,

67). Human PRL has been show to bind only to the PRL receptor.

1.4.2 The Human Prolactin Gene and Pituitary versus Extrapituitary Prolactin

Synthesis and Secretion

The hPRL gene consists of a single gene located on chromosome 6 (68) which is composed of 6 exons and 5 introns, is greater than 15kb in length (24, 25, 68, 69) and has been identified in all vertebrate species. Transcription of pituitary and extrapituitary PRL are directed by two separate promoters. Pituitary expression of PRL is directed by the 5,000bp proximal region and begins within exon 1b (70), while extrapituitary PRL secretion is regulated by an independent more upstream promotor in exon 1a (71). The prolactin messenger RNA (mRNA) from these two different promoters differs by 134bp, but they both produce an identical mature PRL protein. It has recently been shown that the human breast cancer cell line SK-BR-3, even though it 11 lacks Pit-1, uses the pituitary promoter and that some human breast cancer cell lines and cells from breast cancer biopsies can use either promoter (17, 72).

Pituitary produced hPRL is transported to the trans-face of the Golgi apparatus where it accumulates as large aggregates and forms secretory granules, a storage form of PRL, which is released by calcium stimulated exocytosis upon appropriate stimulatory signals from the hypothalamus. Pituitary PRL is secreted in a pulsatile manner and exhibits daily variations, circadian cycles of secretion and is increased during stress in humans. Pituitary secretion of PRL is inhibited primarily by negative feedback from dopamine secreted by the hypothalamus and interacting with D2 dopamine receptors on lactrophic cells within the anterior pituitary. Recently, many other substances have been found to either inhibit or stimulate (estrogen, TRH) pituitary

PRL secretion including neuropeptides, neurotransmitters and other hormones

(reviewed in (17, 29)). Prolactin also exerts a negative feedback upon itself, by acting indirectly upon PRLR containing dopaminergic neurons or directly upon lactotrophs

(17).

In contrast to pituitary produced PRL, extrapituitary PRL is secreted immediately from the cells and does not exhibit an aggregated or granular storage form and is not regulated by either the Pit-1 promoter or dopamine. Extrapituitary prolactin is produced by many tissues throughout the body including, but not limited to, cells of the breast, uterus, placenta, prostate, immune system, central nervous system, skin and vascular endothelium (73-75).

12 1.4.3 Human Prolactin Protein and Posttranslational Modifications

The hPRL gene encodes the sequence for a 227 amino acid (aa) PRL prohormone with a 28aa signal peptide. The signal peptide is cleaved within the endoplasmic reticulum leaving a mature hPRL protein 199aa’s in length (61). In most species, full-length PRL consists of 199aa’s (76-79), but pituitary PRL from mice (80) and rats (26) is only 197aa’s in length.

There are numerous variants of PRL which are thought to occur primarily through posttranslational modifications and proteolytic cleavage, but may also occur due to alternative splicing as described for the rat 137aa variant (81, 82).

Posttranslational modifications may involve phosphorylation, deamidation (removal of ammonia from asparagine and glutamine residues), glycosylation (N or O-linked; varies from 1-60% among species), sulfation, dimerization, oligerimazation and aggregation with other proteins, for example immunoglobulins (reviewed in (29) and references therein).

Several protease cleaved forms of PRL have been described including the

14kDa, 16kDa (residues 1-148) variant produced by the estrogen-induced trypsin-like serine protease kallikrein and 22kDa (residues 1-173) variant produced by carboxypeptidase B (reviewed in (29)). In general, the posttranslationally modified and cleaved forms of PRL have reduced biologic activity and/or receptor binding, with the exception of the 14kDa and 16kDa variants which have been shown to have potent antiangiogenic properties and bind not to the PRLR, but to a unique receptor (74, 75,

83-86).

13 1.5 The Structure of Human Prolactin

For many years, the structure of PRL had to be deduced based on sequence similarities and homology modeling of growth hormone and other helix bundle proteins whose structure was known (33, 38, 87-90). Porcine GH was the first member of this class of proteins for which the structure was identified (90). Based on these structures, over 50% of the residues in PRL were predicted to form four long α-helices, with the remainder of the residues residing within unstructured loops (91). The protein was predicted to be a left-handed, antiparallel four helix bundle with an up-up-down-down helix configuration and unstructured loops bridging the space between the four helices.

In 2003, the structure of hPRL was finally elucidated (4). The NMR spectroscopy structure of hPRL closely matches the earlier models proposed by sequence alignment and comparison with the structure of other known hematopoietic cytokines. Human PRL indeed, consists of four α-helices, 25-32 residues in length, with the characteristic up-up-down-down configuration (4). The helices are rigid with mobility occurring primarily within the unstructured loop regions between the helices.

As expected, the structure of hPRL is very similar to hGH, but some surprising differences were noted. The location of the four α-helices is conserved between hGH and hPRL and helices 1 and 4 overlap and are similar in length, but helices 2 and 3 are longer in hPRL than in hGH. Also conserved are the two loops, the first between helices 1 and 2 and the second between helices 3 and 4. Other differences noted between the structures of hGH and hPRL, were that hPRL is missing mini-helix 1 in the connecting loop between helices 1 and 2, but mini-helix 2 is retained by hPRL (Figure

1.3). Human PRL has a shorter connecting loop between helices 2 and 3 and the N- 14 terminal region of hPRL forms a structured loop with helix 1. Kinks are present in the hPRL molecule at the middle of helix 1 and within helix 3. The kink in helix 1, is not present in hGH, but has been noted in other hematopoietic cytokines including LIF, oncostatin M and ciliary neurotrophic factor (4). The residues of hPRL, based on the

NMR structure, are arranged as follows (Table 1.1 and Figure 1.4).

Figure 1.3: Overall structure of human prolactin illustrating the four α-helices and the single mini-helix (black)(PDB#1N9D)(4)

16 hPRL Type of Structure Color hGH Type of Residue (as displayed Residue Structure #’s in Fig 1.4) #’s 1-14 Structured N-terminal 1-7 Unstructured N- disulfide loop, contacts Gray terminal Helix 1 loop 15-42 α- helix 1 Red 8-35 α- helix 1 43-68 Unstructured loop Gray 36-37 Unstructured 38-47 MH1 Black (mini-helix 1) Gray 48-63 69-75 Mini-helix (similar Black 64-70 MH2 position to MH2 of (mini-helix 2) hGH) 76 Gray 71 77-102 α - helix 2 Green 72-92 α - helix 2 93 Black 94-100 mini-helix 103-110 Unstructured loop Gray 101-105 Unstructured loop 111-135 α - helix 3 Blue 106-128 α - helix 3 136-160 Unstructured loop Gray 129-160 Unstructured loop 161-189 α - helix 4 Purple 161-189 α - helix 4 190-199 C-terminus Gray 190-191 C-terminus Cys4- N-terminus disulfide Cys11 loop Cys58- Central disulfide bond Cys53- Central disulfide Cys174 Cys165 bond Cys191- Cys182- C-terminus, Cys199 C-terminus, disulfide Cys189 disulfide loop loop

Table 1.1: Amino acid residues of hPRL and hGH with types of secondary structures formed. Colors indicated correspond with the structural illustrations of hPRL and hGH in Figure 1.4

Figure 1.4: Overview of the hPRL (PDB#1N9D)(4) and hGH (PDB#1HGU)(38) protein molecules showing the location of the four α-helices and the mini-helical (MH) structures. Note that the single mini-helix in hPRL is analogous to mini-helix 2 (MH2) in hGH.

18 Human PRL has six cysteines, which form 3 disulfide bonds between Cys4 –

Cys11, Cys58 – Cys174, Cys191 – Cys199. These disulfide bonds result in one large central loop and two small loops, one at the N-terminus and one at the C-terminus of the PRL molecule, respectively.

1.6 Binding of Prolactin to the Prolactin Receptor

For many years, it has been known that enzymes (92) and receptors often undergo conformational changes upon ligand binding, such as that described for insulin binding to the insulin receptor (93). The binding of polypeptide hormones to their respective receptors, was thought to involve possible conformational or “induced- fit” changes involving only the receptor with binding of the hormone (ligand) based solely on affinity of the ligand for the receptor (a so called “lock and key” or slightly less rigid

“hand and glove” model).

Previously it has been postulated that one molecule of either PRL and GH binds to two PRL receptors in a sequential manner, with binding of the first receptor occurring at binding site 1 of the protein and subsequently the second PRL receptor binds at site 2 of the protein (94-97). But the mechanism of this sequential binding of hGH or hPRL to the hPRLR or the human prolactin receptor binding protein

(hPRLRbp) was unknown and had been postulated to involve differences in affinity of the hormone for the receptor at sites 1and 2. Recently, our laboratory has shown that binding of hPRL to hPRLbp (the extracellular domain of the human prolactin receptor) occurs in a sequential manner, resulting in a conformational change in the hPRL protein

(ligand). One molecule of hPRL binds two hPRLR’s in a sequential manner at

19 physiologic doses forming an active trimeric complex with dimerization of the receptors. If excessive doses of PRL are available in sufficient quantity to overwhelm the PRLR’s, one to one binding of PRL and the PRLR occur at binding site 1, preventing formation of the trimeric complex, receptor dimerization and subsequent signal transduction. This one to one binding in the presence of excessive PRL concentrations is a form of self-antagonism. Binding of hPRLRbp to binding site 1 of the hPRL molecule induces a conformation change that reorganizes the conformation of the hPRL molecule which forms or structures binding site 2 (an “induced fit model”), permitting binding of the second hPRLRbp at binding site 2 on the hPRL molecule (98).

If binding site 2 on the hPRL molecule is blocked or corrupted, receptor binding at site

1 still occurs. But if binding at site 1 on the hPRL molecule is blocked, binding at site 2 does not occur as binding at site 1 is required for the formation of the second binding site (site 2) on the hPRL molecule (Figure 1.5).

1.6.1 Structural and Functional Binding Epitopes

Protein molecules are described as having both structural and functional epitopes. Structural epitopes consist of any residues of the protein that physically contact the receptor, and often tend to be both hydrophobic and hydrophilic and are scattered over the surface of the molecule. Whereas, functional epitopes are considered to be any amino acids that change the binding properties of the ligand to the receptor, regardless of whether they contact the receptor or not. Functional epitopes usually result in a region (“hot-spot”) of binding energy produced primarily by amino acids with charged side chains (99). It has also been noted that residues outside the binding

20 site, called exosites, can transmit structural conformational changes in the molecules which permit or enhance binding properties (100-102). The importance of this is that while the deleted residues of the Delta41-52 hPRL antagonist lie outside of regions currently identified as structural epitopes, they are considered to represent an exosite important for transmitting the appropriate conformation changes required for functional activation of the hPRLR and hPRLbp and subsequent signal transduction. It is speculated that this deletion allows for binding at site 1 of hPRL, but alters the binding- induced formation of site 2 on hPRL.

Figure 1.5: Binding of hPRL to the hPRLR to form trimeric 1hPRL:2hPRLR (1H:2R) complexes, with formation of binding Site 2 after hPRL site 1 binds the first hPRLR. Active trimeric (1H:2R) complexes activate intracellular signal transduction. Excessive hormone concentrations result in saturation of the hPRLR’s with formation of inactive 1H:1R dimeric complexes.

1.7 Structure of the Human Prolactin Receptor

The gene for the PRL receptor is located on chromosome 5. The PRLR belongs to the cytokine/hematopoietic receptor superfamily which to date includes over 30 different receptors (103-109). Despite a low degree of sequence homology, the receptors of this superfamily share similar structural features. They all consist of a fairly invariant extracellular domain (ECD), a single pass hydrophobic transmembrane

22 domain (TMD) and a variably sized intracellular domain (ICD). Within the ECD, the most highly conserved features of this receptor family include a conserved sequence within the cytokine receptor homology (CRH) domain (110), a WSXWS (Trp-Ser-aa- Trp-Ser) motif and two disulfide bonds (Cys12-Cys22; Cys51– Cys62) (43). The 5’ UTR of the PRLR gene encodes for several different tissue-specific promoters (Table 1.2) (111-114). In humans, the promoter determines which of several different identified first exons (hE13, hE1n, hE1N2-5) will be used to form the 5’ UTR (111, 115, 116). The mature hPRLR protein is encoded primarily by exons 3-10, although recently discovered receptor isoforms exhibit an alternative exon 11 (116).

Promoter # Tissue Specificity

Promoter 1 Gonads

Promoter 2 Liver Promoter 3 Generic (both nongonadal and gonadal tissues)

Table 1.2: Tissue specificity of the promoters for the hPRL receptor.

23 The PRLR is ubiquitous and occurs within almost all cells and tissues of the body at various levels, from approximately 200-30,000 receptors per cell (17), and in a variety of different isoforms. Although PRLR’s from other species were described many years ago, it wasn’t until 1989 that the first hPRLR cDNA for the long form of the hPRLR was cloned from a benign liver tumor (hepatoma) and human breast cancer cells (117).

The long form of the hPRLR has an ECD of 211aa’s which form two fibronectin-type III domains (named S1 and S2 or D1 and D2) consisting of seven antiparallel β-strands making two β-sheets linked by a small segment of 5 aa’s (Figure 1.6).

The N- terminal S1 domain contains the two disulfide bonds, the N-linked glycosylation sites and the majority of proposed ligand binding sites. The S2 domain contains the cytokine receptor family WSXWS motif and is thought to be important for interaction between the two receptors during dimerization. The TMD consists of hydrophobic segment 24 aa’s in length. The intracellular domain is variable in length and consists of the cytokine receptor family conserved motifs: Box 1; Variable Box (V-Box), Box 2,

Extended Box 2 (X-Box). Box 1 is required for interaction of the receptor with Jak2.

Since 1989, several additional isoforms of the hPRLR have been identified which vary primarily within the intracellular domain (intermediate, S1a, S1b), except for one isoform (∆S1hPRLR) which lacks bases 71-373 coding for the S1 motif of the receptor resulting in lack of one extracellular fibronectin type III-like domain (118).

It has been postulated that the various receptor isoforms are partly responsible for the multitude of different functions hPRL performs in various tissues throughout the

24 body. Tissues express the different PRLR isoforms in different concentrations and although it is known that PRLR homodimers actively stimulate signal transduction, it is speculated that various PRLR heterodimers are less functionally active, inactive or stimulate different signal transduction pathways.

Figure 1.6: The hPRLRbp (nonglycosylated extracellular domain of the PRLR) spanning 211aa’s in length and consisting of two fibronectin-type III domains S1/D1 (blue) and S2/D2 (purple) connected by a short 5aa link (red). The outer surface of the cell membrane would be adjacent to the c-terminus (C) (PDB#1BP3) (119).

25 1.7.1 The Human Prolactin Receptor Binding Protein

In 2001, a naturally occurring form of the human prolactin receptor binding protein (hPRLRbp) was described (120). The hPRLRbp is a 32kDa protein corresponding to most of the ECD of the hPRLR and is capable of binding both hPRL and hGH. It is thought to be a nonglycosylated form of the membrane-bound hPRLR.

The hPRLR normally exhibits N-linked glycosylation which is required for targeting the receptor to cell surfaces. It is uncertain whether the hPRLRbp results from proteolysis and deglycosylation of the hPRLR or by an alternative gene splicing mechanism. Up to 36% of serum PRL is bound to hPRLRbp in both males and females

(120).

1.7.2 Intracellular Signal Transduction Pathways Activated by Prolactin Receptor

Binding

Upon formation of an active trimeric complex (1hPRL:2hPRLR’s), receptor dimerization induces downstream intracellular signaling cascades. The PRLR has no intrinsic kinase activity of its own and relies on other kinases to phosphorylate the intracytoplasmic portion of the receptor and signal transduction molecules involved in

PRL signaling events within the cell. Janus kinase 2 (Jak 2) is constitutively associated with the PRLR (121, 122) and autophosphorylation of Jak2 occurs upon PRL binding to the PRLR. Phosphorylated tyrosine residues on the intracytoplasmic domain of the

PRLR then recruit and phosphorylate members of the Stat (signal transducers and activators of transcription) family. Jak 2 phosphorylates and activates Stat5 which then translocates to the nucleus to initiate gene transcription. (reviewed in (43, 123)). In

26 addition to the Jak 2/Stat 5 pathway, various other signaling pathways used by PRL continued to be discovered. Stats 1 and 3 are involved in signaling initiated by the

PRLR and it has been shown that the levels of Stats 1 and 3 are increased in mammary gland tumors (124, 125). Stats 5 and 3 mediate PRL activation of the cyclin D1 promoter (126). The Ras-Raf-Mitogen Activated Protein Kinase, PI3 Kinase, JNK, a

Tec/Vav complex and others have been implicated in PRL-induced signal transduction.

(reviewed in (18)). Within about 30 minutes of PRL binding to the PRLR, the ligand- receptor complex is internalized within vesicles in the cell and degraded by enzyme- containing lysosomes (43, 127-129).

1.8 Rationale Associated with the Design of Human Prolactin Antagonists

Many mutations have been made in the hPRL molecule in the hopes of finding a potent hPRL antagonist capable of disrupting the local autocrine/paracrine secretion of hPRL by tumor cells. The general concept behind all of the mutants created thus far, has been to mutate resides within the hPRL molecule which will increase binding at site

1, thereby allowing occupancy of all of the receptors, but will prevent the initiation of signal transduction by blocking or corrupting binding site 2 (Figure 1.7).

The first generation hPRL antagonists were prepared using residues homologous to those mutated in hGH which had shown decreased lactogenic activity but retained somatotropic activity. One such antagonist, G129R hPRL, was based on the analogous hGH antagonist G120R. The G129R hPRL antagonist has been shown to antagonize the autocrine/paracrine hPRL system, induce apoptosis and decrease intracellular signaling associated with proliferative stimuli in human breast cancer cell lines (2, 3, 130).

27 Another hPRL antagonist, S179D, has been show by some to be an antagonist (131) and by others to be an agonist(132). Delta41-52 hPRL was designed based on the finding that the homologous Delta32-46hGH (Figure 1.8) showed a marked decrease in lactogenic activity but retained full somatotrophic activity (1). Delta41-52hPRL has proved to be a potent first generation prolactin antagonist.

The conflicting reports from different laboratories in relation to the agonist versus antagonist activity of S179D and G129R hPRL’s are most likely due to the variable sensitivity of the assay systems used, lack of standard assays and the multitude of pathways affected by PRL signaling through the PRLR in various cells and tissue.

Both G129R and S179D, although able to function somewhat as antagonists, retain a substantial amount of agonist activity.

Figure 1.7: Human Prolactin (PDB#1N9D) (4)showing the location of G129 on helix 3. In the G129R hPRL antagonist, the glycine (G) molecule within binding site 2 is replaced with the much bulkier arginine (R) molecule (as illustrated), thereby decreasing receptor binding at site 2 on hPRL.

Figure 1.8: Comparison of hPRL (Delta41-52) and hGH (∆32-46) showing the homologous deleted regions in yellow.

30 1.9 Apoptosis Overview 1.9.1 General Mechanisms of Apoptosis Apoptosis is an energy-driven programmed process of cell death that occurs under both physiologic and pathologic conditions. Although many of the same insults to cells or tissue can induce either apoptosis or necrosis depending on the severity of the insult and the physiologic state of the cell or tissue at the time of the insult, several distinct differences separate these two processes. Necrosis is a random poorly controlled process that results in cell swelling, rupture of the plasma membrane and leakage of cell contents into the surrounding tissues resulting in an inflammatory reaction. Apoptosis is a tightly regulated, ATP-dependent process involving a variety of initiators, effectors, inhibitors and intracellular signaling cascades. Apoptosis can be stimulated by a wide variety of both intracellular and extracellular stimuli. Apoptosis can be induced by withdrawal of growth factors or other nutrients required by the cells, cytotoxic chemicals, radiation, excess calcium, reactive oxygen species and binding of ligands (TNF-α, FAS, Trail ) to specific cell surface receptors (TNF-R1, Trail-R1, Fas receptor)(133, 134). Regardless of how apoptosis is stimulated, the events that follow proceed in a similar manner. The initiating event is permeabilization of the mitochondrial membrane, with subsequent release of cytochrome c from the mitochondria, flipping of phosphatidylserine to the outer surface of the plasma membrane, condensation of chromatin with nuclear fragmentation occurring in a laddered size-specific (200bp) fragmentation pattern, cell shrinkage with loss of membrane contact with adjacent cells, blebbing of the plasma membrane forming apoptotic bodies and a lack of inflammation as apoptotic cells are engulfed and phagocytized by adjacent cells without apparent leakage of cellular constituents.

31 The biochemical events involved in apoptosis include formation of pores in the outer mitochondrial membrane (the mitochondrial permeability transition pore) with mitochondrial membrane depolarization, release of inhibitory Bcl-2 from the mitochondrial membrane, release of Apotosis activating factor 1 (Apaf-1) and cytochrome c into the cytoplasm, formation of the apoptosome (a complex of Apaf-1, cytochrome c and procaspace 9), conversion of the inactive zymogens (procaspaces) to active caspaces, activation of caspaces (cysteinyl aspartate-specific proteases/proteinases) resulting in cleavage of intracytoplasmic proteins and crosslinking of proteins by transglutaminase. Initially it was thought that all apoptotic pathways proceed through one of several caspace cascades, but it is now recognized that there are caspace-independent pathways of apoptosis such as those resulting in changes in the proportion of proapoptotic and antiapoptotic Bcl-2 family members. In this mechanism, Apoptosis Inducing Factor (AIF) is released from the mitochondria, translocates to the cell nucleus where it promotes DNA condensation and induces phosphatidylserine exposure on the surface of the plasma membrane without induction of any caspace activity. The Bcl-2 protein family, most of which are intimately associated with mitochondrial membranes, include the proapoptotic (Bid, Bax, Bcl-xs, Bad, Bag, Bak) and the antiapoptotic (Bcl-2, Bcl-xl, Mcl-1, Bim, Bod). There are a multitude of factors known to be associated with either stimulation (caspace 9, cytochrome c, AIF) or inhibition (survivin, AKT/Protein kinase B) of apoptosis with more being discovered at a very rapid rate, making this a very fruitful area for investigation but a very challenging arena in which to keep current with the pace of new discoveries. Due to the vast amount of information on apoptosis and the alarming rate at which new information is being generated, this work will not attempt to

32 provide a complete overview of apoptosis, but will refer the reader to several excellent references on apoptosis (135-143) and will discuss specific apoptosis-related pathways and proteins in the relevant experimental sections. 1.9.2 Physiologic Apoptosis The regulated process of apoptosis occurs in various physiologic conditions, including but not limited to, involution of the mammary gland post-lactation, hormone- dependent involution of the prostate and endometrium in the adult, intestinal crypt epithelial cell turnover, embryogenesis and regulation of lymphoid cells in appropriate numbers and ratios of cell types. 1.9.3 Pathologic Apoptosis Many diseases and disorders have been associated with dysregulation of apoptosis with resultant increased or decreased levels of normal apoptosis with a cellular population or tissue. Diseases noted as being associated with increased apoptosis include ischemic injury in cerebral vascular accidents (stroke) and myocardial infarction, neurodegenerative diseases (Alzheimer’s disease, spinal muscular atrophy), tissue and organ implant rejection and virus-induced lymphocyte depletion in many diseases such as acquired immunodeficiency syndrome (AIDS) in humans. Conditions associated with increased cell survival due to inhibition of apoptosis include several autoimmune diseases in which autoreactive lymphocytes are no longer responsive to normal apoptotic stimuli and cancers, especially hormone-dependent breast, prostate and ovarian tumors and carcinomas with detectable p53 mutations (133). Although cancers result from an initial clonal proliferation of cells which have lost normal responsiveness to growth factors and exhibit autonomous growth, it has been noted that many cancers involve loss or mutation of proapoptotic genes and their corresponding proteins and/or increased antiapoptotic proteins suggesting that

33 decreased apoptosis may be a more important factor in the growth of the tumors than the proliferative rate of the neoplastic cell population.

CHAPTER 2 MATERIALS AND METHODS

Materials and methods used throughout the remainder of this document will be described in detail in this chapter. Many of the protocols are standard procedures in common use in our laboratory. Other techniques that are standard throughout most research laboratories will not be described in detail here, but can be accessed in Current Protocols in Molecular Biology (144) and in Molecular Cloning: A Laboratory Manual (145). Protocols not of original design will be respectfully credited to the original author of the protocol. 2.1 Amino Acid Substitution within Human Prolactin by DNA Mutagenesis 2.1.1 The pT7-7(f-) Phagemid The pT7-7 protein expression plasmid (Figure 2.1) was a gift kindly provided to the laboratory by S. Tabor (Harvard Medical School, Boston, MA). This expression vector uses a ф10T7 RNA polymerase promoter to generate target gene transcripts in E. coli bacterial cells containing the gene for T7 RNA polymerase. To eliminate the need for extensive subcloning and to facilitate the processes of mutagenesis, which uses single stranded DNA which cannot be produced from the pT7-7 plasmid, Dr. Francis Peterson created an f1 origin of replication within the plasmid (146). Briefly, the f1 origin of replication was ligated into a unique Cla 1 site of the pT7-7 plasmid. This created two phagemid products, a pT7-7(f-) negative sense strand and a pT7-7(f+)

35 positive sense strand. Cloning and expression of the target genes, hPRL and hGH, was successful using the pT7-7(f-) phagemid (Figure 2.2).

Figure 2.1: Illustration of the original PT7-7 phagemid provided by S. Tabor (Harvard Medical School).

Figure 2.2: Diagram of the modified PT7-7 phagemid with addition of the f1 origin of replication created by F. Peterson (The Ohio State University). Cloning and expression of the entire coding sequence for WT (native) hPRL was successful using the PT7-7(f-) phagemid.

38 For cloning, poly-A-mRNA was obtained from human pituitary glands from the Cooperative Human Tissue Network. Reverse transcription was used to produce hPRL cDNA and the coding sequence for mature hPRL was amplified by the polymerase chain reaction (PCR). A 5’ primer was used to introduce a methionine residue (ATG) at the start of the coding sequence for hPRL and the first seven residues were changed to those preferred by bacteria to allow for protein expression in E. coli bacterial cells. A unique Nde1 restriction site was added to include the initiation codon and a 3’ primer was designed to add a Hind III restriction site after the termination codon. PCR products were ligated into a TA cloning vector (Invitrogen, Carlsbad, CA) and vectors containing ligated sequences were selected by ampicillin resistance and Eco R1 restriction enzyme digestion. TA cloning vector colonies containing the correct sequence were allowed to proliferate and the coding sequence for hPRL protein with the addition of residues to allow for expression of the protein in bacterial cell cultures was excised with the restriction enzymes Nde I and Hind III. The entire protein coding sequence for wild type (native) hPRL was ligated into the pT7-7(f-) phagemid and transformed into DH5α cells to produce the pT7-7(f-) phagemid for methionyl human prolactin (hPRL). Ampicillin resistance and restriction enzyme digestion were again used to select colonies most likely to have incorporated the correct sequence. The insertion of the correct sequence into the pT7-7 phagemid was confirmed by dideoxy DNA sequencing(147). This PT7-7(f-) containing vector could be used both to produce ssDNA in the RZ1032 E.coli strain of bacterial cells or used for protein expression in the BL21 E. coli strain. The ability to use a single vector for both site-directed mutagenesis and protein expression greatly increased the efficiency of creating proteins with specific amino acid residue mutations.

39 2.1.2 Production of single strand (ss) DNA The pT7-7(f-) phagemid containing the sequenced gene for wild type hPRL was transformed into RZ1032 E. coli bacterial cells, which are ung (-) and dut (-) thereby lacking uracil N-glycosylase and dUTPase. The lack of these two enzymes, allows for the incorporation of uracil into the WT hPRL parent strand DNA. One mL of the initial culture is used to inoculate 50mL of 2X TY broth and grown to log phase optical density (OD600) of 0.3 at which time R408 helper phage (Promega, Madison, WI) at a multiplicity of infection (MOI) of 20 is added to induce the production of single strand DNA (ssDNA) from these bacterial cells. The single strand uracil-containing WT hPRL parent strand DNA was purified from the 2X TY cell culture media by high salt extraction followed by phenol-chloroform-isoamyl (PCI) extraction and ethanol precipitation. The ssDNA was dried, resuspended in sterile water to the appropriate concentration and was ready for use as a template for mutagenesis. 2.1.3 Mutagenic Primer Design Primers used to insert the codon for the desired mutation into the DNA sequence of hPRL were designed to also add or delete a translationally silent restriction site. Restriction site maps were generated by the Genetics Computer Group software or Primer Generator, a public domain program available at http://www.med.jhu.edu/medcenter/primer/primer.cgi (148). This method takes advantage of the degeneracy of the DNA code by manipulating the three letter DNA codon so that the same amino acid is coded but the code is slightly changed to either allow or prohibit a restriction enzyme to cut the DNA within that segment of the DNA sequence. Using this methodology, a restriction enzyme can then be used to rapidly

40 screen for insertion of the desired mutation, as the mutant DNA will have one less or one additional restriction enzyme product compared to the wild type DNA sequence. Primers were designed to be 20-40 base pairs in length with G-C caps at the 5’ and 3’ ends to allow for efficient annealing of the primer to the template DNA. All primers were ordered from Integrated DNA Technologies (Coralville, IA). 2.1.4 Site-Directed Mutagenesis In vitro site-directed mutagenesis was performed using the method originally described by Kunkel (149) (Figure 2.3) as this method allows for multiple simultaneous mutations to be made without additional subcloning. The uracil-containing ssDNA isolated from the vector was then used in in vitro reactions for mutagenesis. Mutagenic primers were phosphorylated, annealed to the parent WT hPRL uracil-containing ssDNA template and the second strand was extended by PCR (MJR thermocycler) using T7 DNA ligase and T7 DNA polymerase (New England Biolabs, Beverly, MA). This procedure produces a double strand DNA (dsDNA) comprised of the parent uracil-containg strand and one strand containing the desired mutation. The dsDNA was subsequently transformed into DH5α E. coli bacterial cells, which degrade the uracil-containing parent WT hPRL DNA strand. The uracil is excised from the plasmid, reducing replication of the parent strand and producing a dsDNA strand with the desired mutation and translationally silent restriction site intact. Colonies were grown on LB agarose plates with ampicillin overnight at 37°C. Colonies with the incorporated mutation were selected by ampicillin resistance. Several colonies were screened for presence of the desired mutation by restriction enzyme digestion and agarose gel electrophoresis. Sequences were confirmed by dideoxy DNA sequencing

41 (The Ohio State University, Neurobiotechnology Center DNA Sequencing Facility) using an ABI 373XL Stretch DNA Sequencer.

Figure 2.3: Schematic illustration of the Kunkel method of site-directed mutagenesis. A) RZ1032 E. coli cells are used to isolate uracil containing ssDNA, B) a primer for the sequence of the desired mutant is annealed to the template ssDNA, C) in vitro second strand synthesis using T7 DNA polymerase, D) the double strand uracil-containing DNA is transformed into DH5α E. coli cells where the uracil containing strand is degraded producing a phagemid containing the desired DNA mutation. This phagemid can then be transformed into BL21(DE3) E. coli cells to produce the recombinant mutated proteins.

43 2.1.5 Production of the Delta41-52/G129R Double Mutant (DM) hPRL A similar strategy to that described above under site-directed mutagenesis (section 2.1.4) was used to produce the double mutant, except that the primer for the G129R mutation was annealed to the Delta41-52 ssDNA and the second strand was extended by T7 DNA polymerase. The dsDNA was transformed into DH5α E. coli bacterial cells (Invitrogen Life Technologies, Carlsbad, CA), as described above, for selection and characterization. 2.2 Production of Full-Length Recombinant Human Prolactin Proteins 2.2.1 Protein Expression Purified phagemids (approximately 10-100ng) containing the dsDNA sequence for wild type or mutant hPRL’s were transformed into competent BL21(DE3) E. coli (Novagen, Madison, WI), plated on LB ampicillin agarose plates, grown in a warm room at 37°C and colonies were selected based on ampicillin resistance. A single colony was isolated, grown in 10mL LB broth for 6-8 hours and then transferred to 1L of LB broth containing 100ug/mL ampicillin. The 1L culture was grown to log phase, at which time they reached an OD600 of 0.3-0.4. Protein expression was induced by adding 0.4mM IPTG (Isopropyl-β-D-thiogalactopyranoside, Sigma, St. Louis, MO) and allowing the culture to grow for an additional four hours. Bacterial cells were collected by centrifugation and the LB broth was aspirated from the cells. The pelleted E. coli cells were resuspended in 45mL of 100mM Tris pH 7.5, 25mM dithiothreitol and 1mM phenylmethylsulfonyl fluoride. 2.2.2 Cell Lysis, Inclusion Body Collection, Solubilization and Protein Refolding The resuspended E. coli cells were passaged twice through a French Pressure cell (SLM-Aminco, Urbana, IL) at 5000 pounds per square inch (psi), to lyse the cells and release the inclusion bodies containing the hPRL protein. The inclusion bodies

44 were collected by high speed centrifugation, the supernatant containing ruptured cell membranes was discarded and the inclusion bodies were resuspended in 100mL of 4.5M urea, 50mM Tris at pH 11-11.5. The inclusion bodies were solubilized at room temperature for two hours to denature (unfold) the aggregated protein in the inclusion bodies. The solubilized proteins were centrifuged to remove any remaining cellular debris and then allowed to air oxidize for two days at 4°C. The proteins were refolded during dialysis by removal of the urea and reduction of the pH by dialysis buffer consisting of 20mM Tris pH 7.5 (4x4L) over a two day period. 2.2.3 Purification of Recombinant Human Prolactin Proteins Initially, proteins were purified using a DE52 anion exchange resin (Whatman, Clifton, NJ) equilibrated with 20mM Tris pH 7.5. The protein solution, also in 20mM Tris after dialysis, was loaded at 1mL per minute. After loading of the entire volume of protein solution on the column, 20mM Tris was run through the column for one hour. Protein was eluted from the column using 500mL of a 0-500mM sodium chloride gradient in 20mM Tris pH 7.5. Fractions were collected and each 5mL fraction was monitored by absorbance spectroscopy at 280nm for the presence of protein. The protein was then dialyzed in 4L of 5-10mM ammonium bicarbonate changed at 12 hour intervals for a total of 6 changes with 0.01% sodium azide added for the first 12 hours only. The proteins were lyophilized and stored in a desiccator box at -20°C until use. The laboratory more recently purchased an ÄKTA Explorer Chromatograph (Amersham Biosciences, Piscataway, NJ). Columns were packed with either POROS affinity resin (Perspective Biosystems, Farmington, MA) or DEAE Sepharose Fast Flow anion exchange resin (Amersham Biosciences, Piscataway, NJ) equilibrated with 20mM Tris pH 7.5. Proteins were loaded on the column at 20mL/min and eluted with a 0- 500mM sodium chloride gradient over a 30 minute period. The elutant was monitored

45 at three wavelengths (250, 280 and 350nm). As correctly folded hPRL exhibits a 280/250 ratio of approximately 2.0, fractions could be monitored for the presence of protein and collected as they eluted off the column. As above, the proteins were dialyzed in ammonium bicarbonate, lyophilized and stored desiccated at -20°C. 2.3 Characterization of Recombinant Full-Length Human Prolactins All newly produced batches of recombinant protein were completely characterized, prior to use in assays, by electrophoresis and spectroscopy, as described below. 2.3.1 Protein Concentration Protein were resuspended in 5-10mM ammonium bicarbonate and concentrations were determined using a bicinchoninic acid/copper sulfate colorimetric assay (BCA)(150). A commercially available BCA assay (Pierce, Rockford, IL) and standardized bovine serum albumin samples of known concentration were used to evaluate the concentration of our protein preparations prior use. 2.3.2 SDS-Polyacrylamide Gel Electrophoresis Proteins were evaluated for purity, size and disulfide bond formation using the Laemmli method (151) sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Protein concentrations were determined by BCA assay and 20ug of each protein to be analyzed was loaded per lane on 15% SDS-PAGE gels run under reducing (with 2-mercaptoethanol in the sample buffer, Sigma-Aldrich, St. Louis, MO) and nonreducing conditions. SDS-PAGE gels run under reducing conditions with an appropriate size molecular weight marker allow for an estimate of the size and purity of the proteins. Nonreducing SDS-PAGE gels can be used to assess correct formation of the disulfide bonds within the mutant proteins by comparing the recombinant protein with a

46 biological hPRL protein isolate (or with WT hPRL previously compared with a biological isolate). Correct disulfide bond formation results in a single band on the gel which migrates to the same position as the biological isolate. Incorrectly folded proteins with disruption of disulfide bonds or disulfide-linked polymers of protein, alter the hydrodynamic radius of the sample, produce multiple bands or a shift in the position of the protein band relative to the biological isolate or previously characterized WT hPRL sample. 2.3.3 Ultraviolet (Absorbance) Spectroscopy Protein solutions at 25µM concentration, as determined by BCA assay, were prepared in 20mM Tris, 150mM sodium chloride (NaCl), pH 8.2 and evaluated by ultraviolet (UV) absorption spectroscopy recorded in the near UV (200-350nm) range with a Lambda 55 UV/VIS Spectrometer (Perkin Elmer, Wellesley, MA). This method can provide several useful pieces of information regarding the protein samples analyzed and some information in relation to the proteins three- dimensional structure. The naturally occurring aromatic amino acids, tryptophan (Trp), tyrosine (Tyr) and phenylalanine (Phe), absorb UV light at approximately 280nm, 274nm and 257nm respectively. Therefore, evaluation of the spectra within this range gives an estimate of protein concentration (peak height) and hydration of the aromatic amino acids (maximal absorption wavelength). As the disulfide bonds partly contribute to the absorption at 250nm, changes in this region of the spectra can indicate alterations in the dihedral angle or length of the disulfide bonds. Proteins in solution normally do not absorb light at 350nm and increased intensity of absorption within this region has been attributed to protein aggregates which scatter light, giving an indication of the quality of the protein preparation.

47 2.3.4 Fluorescent Spectroscopy Protein samples for fluorescent spectroscopy were resuspended at 0.5-1.0µM, concentration determined by BCA, in 10mM Tris, 150mM NaCl, pH 8.2. Trp, Tyr and Phe emit fluorescence. Trp is the most intense of the three chromophores, with a maximal absorption around 295nm and an emission (fluorescence) spectra ranging from 307-353nm depending on the local environment and the degree of solvation of the Trp residues. The emission of Trp shifts towards 353nm as the degree of exposure to water increases. Emission spectra for Tyr and Phe have maximal absorptions at 274nm and 257nm, respectively, and exhibit minimal change in response to alterations in the solvation of their environment. Using an excitation wavelength of 290nm, minimizes signals from Tyr and Phe, and although this slightly lowers the signal generated from Trp it permits evaluation of Trp emission alone. The fluorescence emission spectra from Trp can be used to monitor changes in the overall structure and packing of the protein, as looser packing or slight unfolding of the protein will cause a shift in the spectra due to greater exposure of Trp to water in the external environment versus Trp’s emission when packed in the hydrophobic core of the protein molecule. Samples were excited at 290nm and emission spectra were recorded over the range of 300-400nm using a LS55 Luminescence Spectrometer (Perkin Elmer, Wellesley, MA). Each protein has a characteristic emission spectra and shifts in the maximal emission greater than 2nm or considered significant. The emission spectra of each of the hPRL mutants were compared to Wt hPRL to assure that the mutations had not caused major structural changes in the recombinant protein. 2.3.5 Circular Dichroism Spectroscopy Every protein exhibits a characteristic circular dichroism spectra resulting from properties of the amide groups within the peptide backbone. CD spectroscopy, although

48 it does not provide a complete analysis of the 3-D structure of the protein, can be used to evaluate the secondary structure of the protein by estimating the percent of the protein forming α-helices, β-sheets and random coils. Proteins were prepared at 25µM concentrations, assessed by BCA assay, resuspended in 10mM Tris, 150mM NaCl, pH 8.2. An AVIV Circular Dichroism Spectrometer Model 202 (AVIV Instruments, Lakewood, NJ) was used to record CD spectra in the far-UV (200-260nm) range at 20°C. Typical α-helical structures characteristically exhibit one positive peak at 190nm and two negative peaks at 208nm and 222nm. β-sheets exhibit a negative peak at 218nm and 180nm and a positive 190nm band. Unstructured random coils have a negative band close to 200nm and weak positive or negative bands at longer wavelengths. Far-UV CD spectroscopy for hPRL estimates that approximately 50% or more of the protein is α-helical with some random coil and no β-sheets. If the mutant hPRL proteins exhibit > 10% alteration in the α-helical content compared with Wt hPRL, the perturbations in the global protein structure of the protein may alter biological activity and should be excluded from use in biological assays. To date, none of the mutant hPRL’s have exhibited significant changes in CD spectra suggesting that the mutations do not significantly affect the secondary structure of the protein. 2.3.6 Mass Spectrometry Mass spectrometry was used to confirm that the sample of interest matched the calculated molecular weight of the protein based on the combined molecular weights of the constituent amino acid residues. In addition, mass spectrometry allowed for examination and estimation of the percent of possible sample contaminates including low molecular weight truncated protein and high molecular weight dimers. A peptide

49 trap with reverse phase HPLC packing (Michrome Bioresources INc., Auburn, CA) was used to clean the protein sample and remove salts and miscellaneous contaminants. Approximately 20ug of protein, as determined by BCA assay, was loaded onto the column and eluted with 50% acetonitrile. The samples were submitted to The Ohio Sate University, Campus Chemical Instrumentation Center (CCIC). A Bruker Reflex III MALDI-TOF mass spectrometer (Billerica, MA) was used for sample analysis. 2.4 General Cell Culture Reagents 2.4.1 Sera for Cell Culture Defined Fetal Bovine Serum (hereafter referred to as FBS) was purchased from Hyclone Cat#SH30070, Logan, UT. Hyclone uses only fetal bovine blood from USDA inspected bovine in the United States and adheres to strict quality assurance protocols, including GMP (Good Manufacturing Practices) and ISO 9001 quality assurance systems. The serum is filtered through a 0.04µm pore-size filter and assays are performed for more than fifty biochemical components and assay results are included with each individual lot of serum purchased. In addition, Hyclone strictly evaluates the sera for mycoplasma, bacteria, fungi, endotoxin and most known bovine viral diseases. Defined equine serum (ES) was also purchased from Hyclone Cat#SH30074, Logan, UT and underwent similar filtering and testing for biochemical constituents, mycoplasma, bacteria and fungal contaminants, endotoxin and equine viral diseases. Charcoal Dextran Stripped Fetal Bovine Serum (CSS) was purchased from Gemini Bio-Products (http://www.gembio.com), Cat#100-119, Woodland, CA. Sera is collected by cardiocentesis from bovine within the U.S. and from U.S.D.A. inspected virus-free herds outside of the U.S. Sera is collected and processed following GMP quality assurance protocols and is sterile filtered through 0.1µm pore-size filters and sterility is assessed following U.S. Federal Regulation CFR 9 113.26. Additionally,

50 each lot of sera undergoes biochemical analysis, testing for endotoxin, mycoplasma and known bovine viral diseases. Charcoal dextran stripping of serum has been shown to reduce the concentration of sterol ring containing compounds and is used to reduce the concentration of hormones such as testosterone, estradiol, progesterone, T3, T4 and cortisol which may confound analysis of experimental results of hormone assays. Equine gelding serum (GS) was formerly purchased from Hyclone, but is no longer available. We are currently testing a gelding serum from Gemini Bio-Products, Woodland, CA which is processed in a similar manner to their GemCell™ Donor Horse Serum. As gelding serum is not a product currently advertised in their catalog, a specific request must be placed for gelding serum only. 2.4.2 General Cell Culture Media and Reagents The following products (Table 2.1) were purchased from Gibco Invitrogen Life

Technologies (http://www.invitrogen.com), Carlsbad, CA. All Gibco Invitrogen cell culture products are sterile-filtered and extensively tested for endotoxin, bacterial, fungal and mycoplasma contamination.

Catalog Product Description Number 11875-093 RPMI Medium 1640 1X liquid with L-glutamine and phenol red 11835-030 RPMI Medium 1640 with L-glutamine and without phenol red 10370-021 Minimum Essential Medium (MEM) 1X Liquid – contains Earle’s salts, nonessential amino acids and phenol red, but no L-glutamine 51200-038 Minimum Essential Medium (MEM) 1X Liquid – contains Earle’s salts, but no L-glutamine or phenol red. 11039-021 DMEM/F12 1X Liquid Dulbecco’s Modified Eagle Medium/Nutrient Mixture F12(Ham)(1:1) – with 15mM HEPES buffer, L-glutamine, pyridoxine HCl, without pyridoxal HCl and without phenol red 15140-122 Penicillin-Streptomycin liquid – contains 10,000 units of penicillin G (sodium salt) and 10,000ug of streptomycin sulfate per mL in 0.85% saline 11811 Geneticin® Selective Antibiotic (G418 sulfate) 13007-018 Insulin, bovine lyophilized 4mg/mL, activity >26 units/mg 11360-070 MEM Sodium Pyruvate Solution 100mM (100X) liquid 11140-050 MEM Non-essential Amino Acids Solution 10mM (100X) liquid 21985-023 2-Mercaptoethanol (2ME) (1,000X) liquid 25030-081 L-glutamine 200mM (100X) liquid 25200-056 Trypsin-EDTA (0.25% Trypsin, 1mM EDTA·4Na) 1X liquid

Table 2.1: Cell culture reagents purchased from Gibco, Invitrogen Life Technologies.

52 2.4.3 Cell Culture Environment All maintenance stocks of cell lines were grown in sterile 75cm2 (T75) canted neck, vented cap tissue culture flasks (Corning Brand, Fisher Scientific Cat#10-126-37), http://www.fishersci.com/). Cells were maintained in a 37°C tissue culture incubator in an atmosphere of 95% oxygen/5% carbon dioxide and 95% humidity. 2.5 Experimental Assessment of Function and Relative Bioactivity of Recombinant

Human Prolactins 2.5.1 The FDC-P1 hPRLR Cell Line The FDC-P1 cell line was established by long-term culture of normal bone marrow cells from the DBA/2 strain mouse. The FDC-P1 cells are a growth factor-dependent hematopoietic precursor cell line (Dexter, 1980). The FDC-P1 cell line used in these studies was transfected with the gene for the human prolactin receptor (hPRLR). The FDC-P1/hPRLR cell line was created by Genentech, Inc (South San Francisco, CA) and provided to our laboratory under a materials transfer agreement between The Ohio State University and Genentech. 2.5.1.1 Maintenance of the FDC-P1 hPRLR Cell Line The FDC-P1 hPRLR cells are maintained in RPMI 1640 with phenol red (Gibco), 10% FBS (Hyclone), 440µg/mL G418 sulfate (Invitrogen, Carlsbad, CA) used as both an antibiotic and cell selective agent, 10µM 2ME (Gibco) and either 10ng/mL IL-3 (Peprotech Inc., Rocky Hill, NJ) or 1nM recombinant wild-type human growth hormone (94). These cells have a doubling time of approximately 12 hours and were subcultured (1:5-1:10) every 2-3 days. They can occasionally be subcultured at lower densities (1:20-1:30), if they cannot be split within 2-3 days, but they tend to loose their responsiveness to lactogens if subcultured at low densities for extended periods of time.

53 To maintain stocks of cells, cells were resuspended in a medium consisting of 80%FBS, 10% normal maintenance media and sterile 2µM filtered 10% Dimethyl sulfoxide (DMSO, Sigma-Aldrich, St. Louis, MO), frozen overnight at -80°C and then transferred to liquid nitrogen for long-term storage. 2.5.1.2 FDC-P1 hPRLR Cell Bioassays For the FDC-P1 cell bioassays, 20-24 hours prior to the start of the assay cells in the log phase of growth were centrifuged at 1,000rpm x 5 minutes and washed three times in RPMI without phenol red. Cells were then placed in 30-40mL RPMI 1640 without phenol red supplemented with 10% equine gelding serum (GS), G418 sulfate and 10 µM 2ME (assay medium) and placed back in the incubator until the start of the bioassay. Concentrations of the wild-type and mutant hPRL’s were determined by BCA assay (as described above) and diluted in assay medium to two times the desired assay concentrations (0.02 to 20,000nM). The starved cells were centrifuged, the media was aspirated and the cells were resuspended in 20mL of fresh assay media. A 50µL sample of resuspended cells was placed in a 0.5mL Eppendorf tube, stained with Trypan Blue and cell concentration was determined by manual cell counts on a hemacytometer. Cells were diluted to a final concentration of 300,000/mL, giving 15,000cells/50µL. Fifty microliters of the cell suspension was added to each well of a sterile 96 well tissue culture plate (Falcon, Benton Dickinson). Fifty microliters of each 2X hormone dose was added to triplicate wells of the 96 well plate, giving a final assay volume of 100µL per well (50µL cells and 50µL 2X hormone concentration providing a final dose range of 0.010-10,000 nM of the desired prolactin treatment). Plates were gently agitated to mix the cells with the added prolactin doses and the plates were placed in the cell culture incubator at 37°C for 48 hours. The vital dye (Alamar Blue, Accumed

54 International, West Lake, OH) was added at 10 µL /well to assess hormone-induced proliferation and changes in viable cell numbers. Plates were incubated at 37°C for 2-4 hours and then the oxidation/reduction of Alamar Blue by viable cells was measured at 570nm and 600nm on a UVmax microplate reader (Molecular Devices, Palo Alto, CA). The 570 and 600nm readings are used to calculate the percent reduction of Alamar Blue by viable cells and this has been previously shown to correlate well with viable cell numbers (r2 > 0.99; F. Peterson). Dose response curves were plotted and the percent

Alamar Blue reduction was used to determine ED50 and ID50 values for the recombinant hPRL’s using a four parameter fit method (61). 2.5.2 The NB2-11C Cell Line The NB2-11C cell originated from lymphoma in the lymph nodes of an estrogen- pelleted Nb strain rat (152). This lymphoma cell line depends on prolactin for cell proliferation (152-154), is extremely sensitive to PRL stimulation because it expresses high levels of an alternatively spliced intermediate PRLR isoform which has high affinity for PRL (155, 156) and for many years has been used as a standard bioassay for lactogenic hormones (154). The cell line was received as a generous gift from Dr. A. Buckley (University of Cincinnati). 2.5.2.1 Maintenance of the NB2-11C Cell Line NB2-11C rat lymphoma cells are a suspension cell culture maintained in RPMI 1640 with Phenol Red (Gibco Cat#11875-03, Carlsbad, CA), 10% Fetal Bovine Serum (FBS)(Hyclone Cat#SH30070.03, 10% Equine Serum (ES), 3 mL of Penicillin/Streptomycin liquid (Gibco, Cat#15140-122) and 10-100µM 2- Mercaptoethanol (2ME) (Gibco, 1,000X liquid Cat#21985-023; the 2ME 1,000X liquid is used to prepare a 5mM stock solution of 2ME in 0.9% NaCl which is stored at -20°C until use and discarded after 3 freeze/thaw cycles). Equine serum (ES) has been found

55 to be essential in the maintenance medium to retain the cells sensitivity to lactogens. As the doubling time of this cell line is approximately 13 hours during exponential growth, the cells were subcultured (1:20-30) three times per week. These cells are routinely subcultured at a low density in order to maintain a constant doubling time, viability, active growth and response to lactogenic stimuli. Overpopulation of these cells during maintenance can result in lack of response to lactogens and at limiting cell densities, approximately 1.2x106 cells per milliliter, cell lysis occurs. For storage, NB2-11C cells at concentrations of approximately 1-5 x 106 cells/mL were periodically placed in a medium consisting of 92% normal maintenance media and 8% sterile 0.2µM filtered DMSO (Sigma-Aldrich, St. Louis, MO), placed in the -80°C freezer overnight and then transferred to liquid nitrogen. 2.5.2.2 The NB2-11C Cell Bioassays Assay medium consisted of RPMI 1640 without phenol red supplemented with 10% equine gelding serum (GS), 3mL of penicillin/streptomycin liquid and 100µM 2ME (assay medium). Log phase cells were washed 3 times in RPMI 1640 without phenol red (as described above for the FDC-P1 bioassays) and resuspended in 30-40mL assay media 20-24 hours prior to the assay. At the start of the assay, cells were centrifuged, resuspended in fresh assay media, counted (as described above) and diluted with assay media to a final concentration of 400,000cells/mL. Cells were plated in 50µL aliquots (containing approximately 20,000 cells) in each well of a sterile 96 well tissue culture plate. Concentrations of recombinant wild-type and mutant human prolactins were determined by BCA assay and the prolactins were diluted to the appropriate 2X concentrations (0.02-2000nM) in assay media. Fifty µL doses were added to triplicate wells of the 96 well plate, giving a final volume of 100µL (50µL cell suspension and 50µL 2X prolactin dose). Plates were placed in the cell culture

56 incubator at 37°C for 48 hours. At the end of the 48 hour assay period, the vital dye Alamar Blue was added (10 µL/well) and percent oxidation/reduction of Alamar blue and ED50 and ID50 values were calculated as described above (for FDC-P1 cell bioassays). 2.5.3 The Human Jurkat Cell Line Human Jurkat cells were purchased from ATCC (#TIB152). This human T lymphocyte cell line was derived from a clone of the original Jurkat cells established from the peripheral blood of a young patient with acute T cell leukemia. Jurkat cells were maintained under standard cell culture incubation in sterile T75 tissue culture flasks in a maintenance media containing RPMI 1640 with phenol red, 15% FBS, 1% penicillin/streptomycin liquid and 1% L-glutamine. Cells were subcultured (1:10-20) three times per week. As required for assays, Jurkat cells were centrifuged and rinsed as for the FDC-P1 and NB2-11C cells and placed in assay media consisting of RPMI 1640 without phenol red, 1% penicillin/streptomycin liquid, 10% CSS, and 1% L-glutamine. 2.6 Analysis of Recombinant Human Prolactins in Breast Cancer Cells All breast cancer cell lines were maintained in sterile T75 flasks in a 37°C dedicated tissue culture incubator in an atmosphere of 95% oxygen, 5% carbon dioxide and 95% humidity. Initially, bioassays were performed using cell numbers published by the National Cancer Institute’s Developmental Therapeutics Program (NIH/NCI-Frederick, DTP; http://dtp.nci.nih.gov/) which has performed extensive studies on a series of 60 cancer cell lines (NCI 60). Several bioassays were performed replacing the FBS (maintenance medium) with various concentrations of CSS (assay medium) and testing bioassay endpoints

57 (time in hours from addition of prolactin doses) to determine the correct starting number of cells for our bioassay system. Cell numbers were then adjusted up or down as required based on the specific requirements of our bioassay system and in order to obtain adequate Alamar blue oxidation/reduction readings within the sensitivity range of our microplate reader.

Cell Line Tissue Origin Doubling Time NCI 60 Bioassays (hours) Cell numbers Cell numbers

T-47D Breast 45.5 20,000 30,000/50µL

T-47Dco Breast N/A N/A 10,000/50µL MCF7 Breast 25.4 10,000 20,000/50µL

MDA-MB-231 Breast 41.9 20,000 10,000/50µL

Table 2.2: Various cancer cell lines used in bioassays, including tissue of origin, NCI 60 recommendations and doubling times, where available, and cell numbers calculated to work optimally in our bioassay system at 48hours post-prolactin or prolactin antagonist treatment. (N/A – no NCI 60 information available on this cell line)

2.6.1. The T47Dand T47Dco Human Breast Cancer Cell Lines

The T47D cell line was purchased from American Type Culture Collection

(ATCC, Cat#HTB-133, Manassas, VA). This cell line is an adherent breast cancer epithelial cell line that originated from the pleural effusion of a woman with mammary ductal carcinoma. The T47Dco cell line is a strain derived from the T47D cells and they possesses a mutation in the estrogen receptor.

58 2.6.1.1 Maintenance of the T47D and T47Dco Human Breast Cancer Cell Line T47D and T47Dco cells were maintained in RPMI 1640 with phenol red, 5% FBS, 0.01 unit/mL insulin (50µL of 100U/mL insulin stock solution/500mL media) and 5mL of penicillin/streptomycin liquid/500mL media. Cells were subcultured 1- 2X/week, depending on their growth rate, by aspiration of maintenance media, addition of 1-2mL of trypsin solution with incubation for 5 minutes at room temperature in the cell culture hood, followed by 2 washes with sterile filtered 1X phosphate buffered saline (PBS) with a 5 minute centrifugation at 1000rpm and aspiration of PBS between each wash. Cells were resuspended in 20mL RPMI 1640 without phenol red. The T47D cells were split 1:20 by placing 1mL of cells in suspension into 19mL of maintenance media in a new T75 tissue culture flask. The T47Dco cells were split 1:20 to 1:40, depending on growth rate, by placing 0.5-1mL of cells in suspension into 19- 19.5mL of maintenance media in a new T75 tissue culture flask. To maintain cell stocks, cells were grown to approximately 75-80% confluent in a T75 tissue culture flask. The cells were then trypsinized to remove them from the surface of the flask, as described above, washed 2X in normal maintenance media with centrifugation between washes, resuspended in 1mL DMSO Freeze Medium (Igen Cat#50-0715, Gaithersburg, MD), placed in a sterile 1.2mL cryovial (Corning Brand, Fisher Scientific, Cat#09-761-70, http://www.fishersci.com/), frozen overnight at -80°C and then transferred to liquid nitrogen storage. 2.6.1.2 T-47D and T47Dco breast cancer cell bioassays For bioassays, 75-80% confluent T-47D cells were starved for 24 hours prior to the start of the assays in assay media (1% CSS) consisting of RPMI 1640 without phenol red, 1% CSS, 0.01 unit/mL insulin (50µL of 100U/mL insulin stock solution) and 5mL of penicillin/streptomycin liquid per 500mL media. At initiation of the assays,

59 the starvation media was removed, the cells were trypsinized for removal from the culture flask, rinsed twice with RPMI 1640 without phenol red, a small aliquot was removed and stained with Trypan Blue for manual hemacytometer cell counts, cells were resuspended in sufficient 1% CSS to achieve the desired cell concentration and 50µl of the cell suspension was added to each well of a 96-well tissue culture plate. Lyophilized WT hPRL or human prolactin antagonist (Delta41-52, G129R) protein was reconstituted in 5-10% ammonium bicarbonate, protein concentrations were determined by BCA assay and the appropriate prolactin (WT, Delta41-52, G129R) protein was diluted to the desired 2X dose in 1%CSS. A 50µl aliquot of the appropriate 2X hPRL protein in 1%CSS was added to each well of the 96-well plate. Plated cells with hPRL doses added were returned to the incubator for 48 or 72 hours depending on the assay. At the end of the designated treatment time, the plates were removed from the incubator and estimates of viable cell numbers were determined by the addition of Alamar blue vital dye with a 2-4 hour incubation (as described above). 2.6.2. The MCF7 Human Breast Cancer Cell Line The MCF7 cell line was purchased from American Type Culture Collection (ATCC, Cat#HTB-22, Manassas, VA). This cell line is an adherent breast cancer epithelial cell line that originated from the pleural effusion of a woman with mammary adenocarcinoma. 2.6.2.1 Maintenance of the MCF7 Human Breast Cancer Cell Line MCF7 cells were maintained in Minimum Essential Meida (MEM, Gibco #10370-021) with phenol red, 10% FBS, 1mM sodium pyruvate (MEM sodium pyruvate solution, Gibco #11360-070), 2mM l-glutamine (L-Glutamine 100X liquid, Gibco #25030-081), 1.25mL insulin/500mL media (4mg/mL insulin stock solution,

60 Gibco#13007-018) and 5mL of penicillin/streptomycin liquid/500mL media (Gibco#15140-122). Cells were subcultured 1-2X/week, depending on their growth rate, by aspiration of maintenance media, addition of 1-2mL of trypsin solution with incubation for 5 minutes at room temperature in the cell culture hood, 2 washes with sterile filtered 1X phosphate buffered saline (PBS) with a 5 minute centrifugation at 1000rpm and aspiration of PBS between each wash and resuspension of the cells in 20mL MEM without phenol red. The cells were split 1:10-1:20 by placing 1-2mL of cells in suspension into 18-19mL of maintenance media in a new T75 tissue culture flask. To maintain cell stocks, cells were grown to approximately 75-80% confluence in a T75 tissue culture flask. The cells were then trypsinized to remove them from the surface of the flask, as described above, washed 2X in normal maintenance media with centrifugation between washes, resuspended in 1mL Origin™ DMSO Freeze Medium (Igen Cat#50-0715, Gaithersburg, MD), placed in a sterile 1.2mL cryovial (Corning

Brand, Fisher Scientific, Cat#09-761-70, http://www.fishersci.com/), frozen overnight at -80°C and then transferred to liquid nitrogen storage. 2.6.1.2 MCF7 breast cancer cell bioassays For bioassays, 75-80% confluent MCF7 cells were starved for 24 hours prior to the start of the assays in assay media (1% CSS) consisting of MEM without phenol red

(Gibco#51200-038), 1% CSS, 5mL media MEM non-essential amino acids (Gibco#11140-050), 1mM sodium pyruvate (MEM sodium pyruvate solution, Gibco #11360-070), 2mM l-glutamine (L-Glutamine 100X liquid, Gibco #25030-081), 1.25mL insulin (4mg/mL insulin stock solution, Gibco#13007-018) and 5mL of penicillin/streptomycin liquid (Gibco#15140-122) per 500mL media.

61 At initiation of the assays, the starvation media was removed, the cells were trypsinized for removal from the culture flask, rinsed twice with MEM without phenol red, a small aliquot was removed and stained with Trypan Blue for manual hemacytometer cell counts, cells were resuspended in sufficient 1% CSS to achieve the desired cell concentration and 50µl of the cell suspension was added to each well of a 96-well tissue culture plate. Lyophilized WT hPRL or human prolactin antagonist (Delta41-52, G129R) protein was reconstituted in sterile, filtered 5-10% ammonium bicarbonate, protein concentrations were determined by BCA assay and the appropriate prolactin (WT, Delta41-52, G129R) protein was diluted to the desired 2X dose in 1%CSS. A 50µl aliquot of the appropriate 2X hPRL protein in 1%CSS was added to each well of the 96-well plate. Plated cells with hPRL doses added were returned to the incubator for 48 or 72 hours depending on the assay. At the end of the desired treatment time, the plates were removed from the incubator and estimates of viable cell numbers were determined by the addition of Alamar blue vital dye with a 2-4 hour incubation (as described above). 2.6.3 Rationale for Selection of Cancer Cell Types Breast cancer cell lines (T47D, T47Dco, MCF7) were chosen based on their cell surface receptor status and their ability to respond to and produce prolactin in an autocrine/paracrine fashion. All three cells lines are hPRLR receptor positive, thereby responding to hPRL stimuli, and also produce endogenous hPRL. T47D cells originating from the pleural effusion associated with an infiltrating mammary ductal carcinoma and MCF7 human breast cancer cells from pleural effusion secondary to mammary adenocarcinoma are both estrogen receptor positive cell lines (9). The T47Dco cell line is a mutant form of the T47D human breast cancer cells that possesses a nonfunctional estrogen receptor.

62 2.7 Total RNA Extraction for Microarray and QRT-PCR Experiments T-47D cells were grown in individual sterile 25cm2 (T25) tissue culture flasks flasks (Corning Brand, Fisher Scientific, Cat#10-126-28) to approximately 75-80% confluent. Adherent cells were rinsed 3X with RPMI 1640 without phenol red. Media was replaced with T-47D assay medium containing RPMI 1640 without phenol red and replacing the 5% FBS with 1% CSS, as described above under T-47D bioassays, and cells were returned to the incubator for 24 hours. At the start of the assay, starvation media (CSS) was replaced with 8.5mL T-47D assay media containing the desired wild type or prolactin antagonist doses as determined by BCA assay. The control samples received assay media only with no added prolactin. Cells were returned to the incubator and total RNA was extracted at designated time intervals post-treatment. For the first experiment, cells were treated for 48hours with assay media only

(CSS control), 0.3nM wild-type hPRL, 500nM Delta41-52hPRL or a combined dose of 0.3nM wild-type hPRL/500nM Delta. Cells were returned to the incubator for 48 hours. At the end of the 48 hour experiment, all treated T25 flasks were removed from the incubator at the same time and placed on ice. The media and cells from each flask were collected into sterile 15mL conical tubes (Falcon Blue Max Jr. 15mL graduated tubes, Fisher Scientific Cat#05-527-90) in order to harvest any detached cells and placed on ice. One mL of trypsin was added to each flask and adherent cells were allowed to detach. Once detached, the media from the 15mL conical tube matching that individual flask was sterilely pipetted back into the flask and used to collect all of the harvested cells. Individually wrapped sterile cell scrapers (B-D Falcon Brand, Fisher Scientific, Cat#08-771-1A) were used to scrape the adherent cells into the media in each individual flask and to prevent cross contamination of samples between flasks. The

63 15mL conical tubes containing the samples were centrifuged at 1,000 rpm for 5 min, the supernatant was aspirated and the sample was washed 2X with 11mL of 1X PBS with centrifugation between each wash. The cell culture hood and any equipment to be used during RNA extraction, including pipetters, were wiped with RNase Away Surface Decontaminant (Molecular Bio-Products, Fisher Scientific, Cat#21-236-21). Total RNA from each sample was extracted using the RNeasy® Mini Kit (Qiagen, Cat# 74106, Valencia, CA) and QIAshredder Homogenizers (Qiagen, Cat#79656, Valencia, CA) following the manufacturer’s protocol for isolation of total RNA from animal cells (spin protocol). Hemacytometer cell counts on previous similarly treated T25 flasks of T-47D cells used in other experiments and estimates of total RNA per 106 cells based on known RNA content of similar cell types was used to determine that the concentration of cells, and therefore total RNA, within each flask would be within the optimum RNA binding capacity of the RNeasy® mini columns. Total RNA samples were eluted from the columns with two 30uL volumes of nuclease-free water (Ambion Cat#9932, Austin, TX). Total RNA extracted from each sample was quantitated spectrophotometrically using the GenQuant (Pharmacia, Piscataway, NJ). The purity of the RNA samples was determined by evaluating the 260/280nm absorbance (A) ratio of spectrophotometric readings. The integrity of the RNA was determined by denaturing agarose gel electrophoresis with ethidium bromide staining following the protocol for formaldehyde agarose gel electrophoresis (Qiagen RNeasy ® Mini Handbook). Samples with an

A260/A280 absorbance ratio 0f 1.8-2.0 and yielding 2 distinct ribosomal RNA bands (18s and 28s rRNA of approx. 1.9 and 5.0 kb in size, respectively) with the 28s rRNA band appearing approximately 2X as intense as the 18s band were considered appropriate for

64 use in microarray and QRT-PCR experiments. A 20ug aliquot (prepared at concentrations < 1µg/µL as required for microarray analysis) was removed from each sample and placed in sterile RNase-free 0.5mL eppendorf tubes for submission for microarray analysis with the remainder of the sample being retained for parallel QRT- PCR experiments. Samples were appropriately labeled and frozen at -80°C until use. A second experiment examining a larger time and dose response was performed exactly as described above with 75-80% confluent T25 flasks of T-47D cells starved for 24 hours in assay medium and then treated with assay medium (CSS control) or assay media containing 0.3nM WT hPRL, 500nM Delta41-52 hPRL, 500nM G129R hPRL or combined doses of 0.3nM WT hPRL/500nM Delta41-52 hPRL and 0.3nM WT hPRL/500nM G129R hPRL. RNA extraction was performed as described above at 0 hours (CSS control only), 1 hour, 3 hours, 6 hours, 12 hours, 18 hours, 24 hours, 36 hours, 48 hours, 72 hours and 96 hours. 2.8 Microarray (Genechip) Experiments Total RNA from 2 separate experiments using T-47D human breast cancer cells was extracted as described in section 2.7. The 20ug RNA samples (at concentrations <1µg/µL) along with a copy of the formaldehyde agarose gel image were submitted to The Ohio State University Comprehensive Cancer Center Microarray Unit (OSUCCC- MAU; http://www.dnaarrays.org/), a campus “shared resource” facility. All further processing of the samples for microarray analysis was performed by the staff at the OSUCCC-MAU including reevaluation of the purity and integrity of the total RNA samples, first and second strand cDNA synthesis reactions, in vitro cRNA synthesis with biotinylated nucleotides, cRNA fragmentation and hybridization to the gene chips, scanning of fluorescent images from phycoerythrin stained cRNA samples bound to probes on the gene chips, initial image comparison and analysis using Affymetrix

65 Microarray User’s Suite 5 (MAS 5.0) software (Affymetrix, Santa Clara, CA; http://www.affymetrix.com/). Affymetrix human U133A and U133B chip sets consisting of two genechip® arrays were used for all experiments. These high density in situ-synthesized oligonucleotide arrays produced using photolithographic technology use 25-mer oligonucleotide probes (11-20) for each gene target, and represent approximately 33,000 well-characterized human genes. These arrays provide for multiple independent measurements of hybridization of each transcript, provide several controls (hybridization, poly-A, normalization, housekeeping genes), produce qualitative and quantitative data and are considered the industry standard against which all new microarray technology is currently measured (157). The arrays use human genome sequences from GenBank®, dbEST and RefSeq. Initial analysis of the microarray probe set hybridization data (fluorescence) was performed by the staff at the OSUCCC-MAU using Affymetrix MAS 5.0 software. Additional analysis of the data (158) was provided by the statistician, Karl Kornacker, recommended by the OSUCCC-MAU staff. For the first microarray experiment, samples consisted of a zero hour control

(1% CSS only), 0.3nM WT hPRL, 500nM Delta41-52 hPRL and a combined 0.3nMWT/500nM Delta41-52 hPRL treatment groups. The zero hour control samples represented the background level of gene expression at the start of treatment. One and two-way ANOVA were calculated and p- values were derived from two-way ANOVA testing for significance of individual treatments. The p-values were converted to the negative log of the p-value (NLP) in order to prioritize data. A Bonferroni correction was then applied to the data (threshold p-value/number of tested genes on the arrays, which adds approximately 5.3 or the log of 20,000 to the threshold NLP). Significance flags were set at NLP>5.3 and NLP >

66 5.6, for more stringent data analysis. Scaled differential expression estimates, as described above, were then used to compare changes in gene expression associated with the WT or prolactin antagonist treatment. The larger second microarray experiment (32 samples) consisted of additional treatment groups: 0 and 48 hour assay media (CSS controls), FBS (normal maintenance media), 0.3nM WT hPRL, 500nM Delta41-52 hPRL, 500nM G129R hPRL and combined 0.3nM WT hPRL/500nM Delta41-52 hPRL and 0.3nM WT/500nM G129R treatments. Each treatment was also evaluated over time (0-96 hours) with total RNA samples extracted at 0, 1, 3 6, 12, 18, 24, 36 and 48 hours post hPRL treatment. Samples were initially analyzed by Affymetrix MAS 5.0 software with additional statistical analysis by Karl Kornacker. Unbiased differential expression estimates for all genes and all microarray (MAS 5.0 CEL file) data was performed. As for the 1st microarray experiment, p-values were calculated (p values >0.05 were considered significant), a Bonferroni correction was applied and data was sorted by the NLP. Those genes whose expression levels differed significantly between treatments were extracted from the microarray data and evaluated. This selected set of data was then partitioned into distinctive co-expression groups (i.e. groups of genes whose expression profiles differ significantly between groups but were highly similar within groups).

For each selected co-expression group, the mean gene expression level was computed for each sample and the time-series analysis was applied to the group mean. Results were then graphed to exhibit their dependence on treatment and time. Statistically significant results were evaluated using Affymetrix NetAffix data analysis center and files were converted to file types for analysis by mapping and gene ontology by public domain software, such as GenMapp (Gene Microarray Pathway

67 Profiler, MAPPFinder, http://www.GenMAPP.org )(159, 160) and gene hierarchical clustering and visualization (Cluster, Treeview; http://rana.lbl.gov/EisenSoftware.html)(161) programs. These programs assist in managing large sets of microarray data by allowing mapping and visualization of microarray data into biologically meaningful clusters and pathways to aid in understanding, interpreting and comparing the vast amount of data obtained from each microarray sample (162). 2.9 Quantitative Real-Time RT-PCR 2.9.1 Primer Selection Based on the results of the first microarray experiment, a specific set of genes showing significant differential expression in T47D human breast cancer cells treated with hPRL antagonists versus either control or WT hPRL treatment were selected for evaluation of mRNA levels by QRT-PCR. These genes included API5 (Apoptosis

Inhibitor 5), AVEN (Homo sapiens Apoptosis Caspace Activation Inhibitor), hPRL

(human prolactin), hPRLR (human prolactin receptor), hGH (human growth hormone),

NFκβIA (Nuclear factor of kappa light chain Inhibitor Alpha) and PIP (Prolactin-

Inducible Protein).

2.9.2 Primer Design

Primers for quantitative real-time reverse transcriptase polymerase chain reaction (QRT-PCR) were design to be approximately 20-25bp in length, produce a

PCR product within the range of 100-200bp long, span at least 2 exons (an exon/intron boundary) and have melting temperatures (TM’s) within the range of 50-60°C with less than a 5°C difference in TM’s between the forward (5’) and reverse (3’) primer pair.

Sequences used for design of the QRT-PCR primers were obtained from the 68 National Center for Biotechnology Information (NCBI) database

(http://www.ncbi.nlm.nih.gov/entrez). A list of approximately 50 candidate primers for each sequence was generated by the freely accessible primer database websites, using either Primer 3 (http:www-genome.wi.mit.edu/cgi-bin/primer/primer3) or PrimerBank

(http://pga.mgh.harvard.edu/primerbanl/index.html). The list of candidate primers, for each gene mRNA sequence, was screened to select the primer pair meeting the strictest criteria for RT-PCR primers. The best primer pair selected from the candidate primer list was subsequently evaluated using the Basic Logical Alignment Search Tool

(BlastN) (http://www.ncbi.nlm.nih.gov/blast/) to determine primer alignment and specificity for the mRNA sequence of the gene being evaluated. If the BlastN inquiry showed nonspecific alignment to mRNA sequences other than the desired sequence, additional primer sets were chosen and screened.

All RT-PCR primers were ordered from Integrated DNA Technologies, Inc.

(IDT) and were prepared by RNase-free HPLC or PAGE purification.

The human prolactin receptor (hPRLR) primers were designed within a region of the sequence encoding portions of the transmembrane and extracellular domain, spanning exons 7-8, common to all known hPRLR isoforms at the time of primer design.

69 Gene Gene GenBank Amplicon Primer Symbol Name Accession# Size(bp) Sequence *API5 Apoptosis NM_006595 133bp for – 5’ CGA Inhibitor 5 CAG TAG AGG AGC TTT ACC G 3’ rev – 5’ GCT GCT AAT CGC TTT TCC TTA GT 3’ *AVEN Apoptosis, NM_020371 145bp for – 5’ GAG Caspace TTA TTG GTT Activation CGA GCC CTT 3’ Inhibitor rev – 5’ ACT GCA TCC CTA ATC CCT TGC 3’ hPRL Human Prolactin NM_000948 for – 5’ CCT TCG AGA CCT GTT TGA C 3’ rev – 5’ GCC ATG GGT ATA CCG TTT AT 3’ hPRLR Human Prolactin NM_000949 98bp for – 5’ CTC Receptor GGA TGA ACT TTA TGT GG 3’ rev – 5’ TAG GGT TTT CTG TCT TCT GG 3’ hGH Human Growth NM_002059 116bp for – 5’ GGA Hormone GCA GAA GTA TCC ATT CC 3’ rev – 5’ GGA GCA GCT CTA GGT TAG ATT 3’ *NFkBIA Nuclear Factor NM_020529 102bp for – 5’ TCG kappa • CAG TGG ACC Inhibitor Alpha TGC AAA AT 3’ rev – 5’TGA GCT GGT AGG GAG AAT AGC 3’ *PIP Prolactin- NM_0002652 for – 5’ GCT Inducible CAG GAC AAC Protein ACT CGG AA 3’ rev – 5’ ATA ACA TCA ACG ACG GCT GC 3’

Table 2.3: Primer Sequences for QRT-PCR (* denotes that the PT7 sequence 5’ TAA TAC GAC TCA CTA TAG GGA 3’ was added to the 5’ end of the forward primer for production of gene-specific standard controls for mRNA quantification).

70 2.9.3 QRT-PCR Standard controls

For quantification of mRNA, gene-specific cDNA standard controls were prepared for each gene of interest using methods similar to those described by Wickert et. al. (163) followed by DNA sequencing for verification of the correct sequence. The controls were used to prepare a standard curve consisting of serial 10-fold log dilutions of gene-specific cDNA based on calculated cDNA copy numbers. Normally, at least six log dilutions of control cDNA are used to create each standard curve.

For sequences which had been previously cloned into the PT7-7 phagemid for recombinant protein DNA production (hPRL, hPRLR, hGH), the plasmids were linearized and RNA was produced from the DNA template using the MAXIscript™ In vitro Transcription kit (Ambion, Cat#1308-1326).

Initial attempts at producing RNA from our DNA templates failed. Several different restriction enzymes can be used to linearize PT7-7 and initially, the enzyme

Cla1 was chosen. Further investigation of this problem revealed that the competent cell line used to produce the plasmids was dam+, and the Cla1 enzyme fails to cut or only partially cuts plasmid DNA within dam+ cells. Subsequently, the restriction enzyme HindIII was used and all plasmids linearized successfully as determined by

DNA agarose gel electrophoresis and RNA was transcribed. After preparation, the

RNA was quantified, analyzed for purity and evidence of any degradation by formaldehyde agarose gel electrophoresis and copy numbers of RNA/ug were calculated.

For gene sequences not already in a PT7-7 plasmid, the primers as listed above were used in PCR to amplify the desired DNA sequence from T47D human breast 71 cancer cell extracts. The sequence was then cloned into a TopoCloning vector

(Invitrogen, Carlsbad, CA). For this set of experiments, the PT7 sequence was added to the 5’ end of the forward primers to facilitate transcription. All sequences prepared in this manner were verified by dideoxy DNA sequencing (The Ohio State University,

Neurobiotechnology Center DNA Sequencing Facility) using an ABI 373XL Stretch

DNA Sequencer and RNA was produced from the DNA template.

2.9.4 Experimental Conditions

A portion of each total RNA sample extracted from treated T47D human breast cancer cells for microarray analysis was preserved at -80°C for QRT-PCR assays. The

1st Strand cDNA Synthesis Kit for RT-PCR (AMV) (Roche Molecular Biochemicals,

Cat#1483188) was used to reverse transcribe sample RNA to cDNA. Real-time RT-

PCR was performed using the Roche LightCycler™, LightCycler™ RNA Amplification

KIT SYBR Green 1 and glass capillary tubes. Typically, 50-150ng of sample ( T47D cell RNA) was required for each QRT-PCR reaction. Cell samples were run in tandem with gene-specific standard curves of known copy number (as described above) and data for quantification was collected during the exponential phase of amplification.

Preliminary experiments were required for each specific primer pair to determine experimental parameters, including annealing temperature and cycle number, which varied for each specific target sequence.

2.10 ATP Assays

Human breast cancer cells (T47D, T47Dco, MCF7) were grown to 75-80% confluence in maintenance media. Twenty four hours prior to the assay, media was removed from the cells, the cells were rinsed twice with RPMI 1640 without phenol red, 72 the media was replaced with starvation/assay media (1% CSS) and the cells were returned to the incubator for 24 hours.

Prior to initiation of the assay, cells were removed from the incubator, media was removed, cells were trypsinized for removal from the flask, rinsed twice with

RPMI 1640 without phenol red, counted, resuspended in 1% CSS, plated in 96-well plates, received the appropriate hPRL dose diluted in 1% CSS and were returned to the incubator (as described above for human breast cancer cell bioassays). Seventy two hours after addition of the hormone dose, the plated cells were removed from the incubator and processed. An ATPlite™ Luminescence ATP Detection Assay System

(PerkinElmer™ Life Sciences, Boston, MA) was used for evaluation of cellular ATP levels and cells were processed following the provided protocol. ATP luminescence was measured on a microplate reader.

2.11 AKT Kinase Assay

T-47D human breast cancer cells were grown in maintenance medium to approximately 75-80% confluent in T25 tissue culture flasks. Twenty four hours prior to the start of the assay, the maintenance media was aspirated off, the adherent cells were washed three times in RPMI 1640 without phenol red, 8 mL of assay media was added to each flask and the cells were placed back in the incubator until the start of the assay.

A BCA assay was run to determine protein concentrations. At the start of the assay, the assay (starvation) medium was aspirated from the flasks and replaced with 8 mL of fresh assay media to which the appropriate hPRL doses had been added to achieve the desired hormone concentrations (0.3 nM WT hPRL, 500nM Delta41-52 73 hPRL, 500nM G129R hPRL and combined 0.3nM WT hPRL/500nM Delta41-52 hPRL and 0.3nM WT/500nM G129R). Cells treated with WT hPRL and hPRL antagonists were placed back in the incubator for 72 hours.

At the end of the 72 hour treatment, cell lysates (including all adherent and detached cells) were were collected following the protocol in the Akt Kinase Assay Kit

(Cells Signaling Technology™, Cat#9840, Beverly, M.A). Cell isolates were stored at

-80°C. Immunoprecipitation with Akt antibodies and the kinase assays were performed as described in the kit protocol. Twenty µL of each sample was loaded per lane on a

12% SDS-PAGE mini gel, the GSK-3 fusion proteins were transferred to nitrocellulose and Western immunoblotting was performed following the Akt kinase assay Kit protocol.

2.11 Western Blot

T47D human breast cancer cells were grown in T25 flasks and treated exactly as for the AKT kinase assays, except the duration of prolactin treatment for this set of experiments was 48 hours. After the 48 hour treatment period the media was aspirated from the cells, the cells were rinsed with ice-cold PBS, scraped from the flask with sterile cell scrapers and both adherent and detached cells were collected and lysed with

1X Cell Lysis Buffer (Cell Signaling Technologies, Inc.; http://www.cellsignal.com/).

The cellular protein was extracted using the Cell Signaling Technologies Western

Immunoblotting protocol for Cleaved Caspace protein blotting. Protein concentrations of each sample were determined by BCA assay. Samples were diluted so the equal amounts of total protein were loaded per lane on 15% or 4-20% gradient Tris-HCl SDS-

PAGE minigels along with both a visible prestained and biotinylated molecular weight 74 marker for electrophoresis. Proteins were transferred to nitrocellulose. Membrane blocking and antibody incubations followed the caspace protein blotting protocol.

Proteins were detected with LumiGLO Reagent and Peroxide (Cell Signaling

Technologies, Inc.) and images of the protein bands were captured on radiographic film.

2.13 Cell morphology and Oil Red O Lipid Staining

T47D human breast cancer cells were seeded at a density of 4x104 in 4-well covered chamber glass slides (Nunc Lab-Tek II Chamber Slide System, Fisher

Scientific Cat#12-565-7) in 2.0mL normal maintenance media. Cells were grown on the slides to approximately 75-80% confluent, at which time the media was aspirated, cells were rinsed twice with non-phenol red containing media, the media was replaced with 2mL assay media and the slides were returned to the incubator for 24 hour starvation. After starvation, the assay media was aspirated, the cells were rinsed twice with assay media and 2.0mL of fresh assay media containing the desired WT or prolactin antagonist dose was added. Cells were returned to the incubator for the desired treatment time (48-72 hours).

At the termination of the assay, media was aspirated from the wells, the growth chamber was removed from the slides and the cells were fixed in 2% paraformaldehyde, stained for 15 minutes with 500uL saturated Oil Red O solution, washed with distilled water and counterstained with Erlich’s (2 minutes) or Harris’s (30-60 seconds) hematoxylin solution. Stained slides were rinsed with distilled water, treated with 0.5% lithium carbonate and rinsed twice with distilled water (protocol adapted from (164) and references therein).

75 Positive control cells were treated 4 days prior to the desired end point of the assay with Oncostatin M and stained as above for the prolactin treated cells. Digital photomicrographs were recorded immediately after staining as Oil Red O stain tends to dissipate rapidly.

2.14 Flow Cytometric Analysis for Mitochondrial Transmembrane Potential (∆Ψm)

FDC-P1 cells in sterile T75 tissue culture flasks were grown to approximately

75-80% confluence in normal maintenance media. Twenty four hours prior to the start of assays, cells were collected, placed in sterile 50mL conical tubes, centrifuged

1000rpm x 5 minutes, media was aspirated and cells were rinsed twice in plain RPMI

1640 without phenol red with centrifugation and aspiration between rinses. Cells were then resuspended in 20mL FDC-P1 assay media and returned to the incubator for 24 hours.

At initiation of the assay, FDC-P1 cells were placed in sterile conical tubes, centrifuged as above, media was aspirated and replaced with fresh assay media sufficient to give a concentration of 1 x 106 cells/mL based on manual hemacytometer counts of an aliquot of the cells removed and stained with Trypan Blue. One mL of cells, at a concentration of 1x106cells/mL, was placed in each well of sterile 6 or 12- well tissue culture plates. WT and hPRL antagonist proteins were added to each well in amounts calculated to give the desired final prolactin dose based on BCA calculations of the prolactin concentration of each reconstituted recombinant human prolactin.

Several untreated wells of cells were also plated to be used as staining controls. Treated cells were returned to the incubator for the desired treatment time (normally 48-72 hours). 76 Due to variations in cell size and staining characteristics, control cells are required for each experiment to set gating and recognition parameters used by the flow cytometer. As The Ohio State University, College of Veterinary Medicine flow cytometry staff had previous experience with and were most familiar with the characteristics of human Jurkat cells, these cells were chosen as the most appropriate control cells.

Jurkat control cells were grown in sterile T75 tissue culture flasks in normal maintenance media to 75-80% confluent. Cells were collected into sterile 50mL conical tubes, rinsed twice in RPMI 1640 without phenol red, counted, resuspended in an appropriate volume of media to yield 1 x 106 cells/mL and plated in 6 or 12-well tissue culture plates and returned to the incubator.

A protocol for flow cytometric analysis of live, apoptotic and necrotic cells was developed for these assays using modifications of the protocols previously published by

Zamzami and Castedo et. al.(165, 166) This protocol uses carbamoyl cyanide m- chlorophenylhydrazone (m-CICCP) as a control for disruption of mitochondrial transmembrane potential and two fluorochromes, propidium iodide (PI) and 3,3’- dihexyloxacarbocyanine ((DiOC6(3)) to assess the metabolic state of the cell (live, dead, apoptotic) and alterations in mitochondrial transmembrane potential.

Camptothecin (C20H16O4) (Sigma #C9911) was resuspended in DMSO to produce a 10mM stock solution, stored at -80°C and used at a final concentration of

100uM to induce apoptosis in the Jurkat positive control cells.

77 Carbamoyl cyanide m-chlorophenylhydrazone (m-CICCP)(C9H5CIN4) (Sigma

#C2759) was resuspended in ethanol to yield a stock concentration of 20mM and stored at -80°C. m-CICCP was used at a final concentration of 100µM in assays.

A 40uM stock solution of 3, 3'-dihexyloxacarbocyanine iodide ((DiOC6(3))

(C29H37IN2O2) (Sigma #31,842-6) in DMSO was prepared and stored in the dark at -20 to -80°C. Immediately prior to use, the DiOC6(3) was thawed and diluted with sterile

1X PBS to a final concentration of 40nM. A total of 20nM DiOC6(3) was used to treat the samples prior to flow cytometry.

On the final day of the assay, on which cells were submitted for analysis by flow cytometry, one or more wells of Jurkat cells were treated with 100µM Camptothecin 3-

4 hours prior to the start of flow analysis and returned to the incubator. These cells are used as a positive control for evaluating the induction of apoptosis.

Once the Camptothecin treated control cells were ready, cells from each individual well were counted, and media volume was adjusted if necessary, to ensure that a minimum of 1x106cells/mL was present as required for flow cytometry. One mL of each sample of treated or untreated control cells was transferred to individual labeled

12x75mm borosilicate glass tubes (Fisher Scientific) and returned to the incubator.

Samples to be used as positive controls for complete disruption of mitochondrial transmembrane potential were treated first, receiving a dose of 100uM m-CICCP and returned to the 37°C incubator for 15-20 minutes. Sample tubes receiving DiOC6(3) were treated next and received a 20nM dose of DiOC6(3) and were returned to the incubator (37°C ) for 15 minutes. Propidium iodide was added last at a final concentration of 5ug/mL and incubated at 37°C for 10 minutes. All sample tubes were 78 covered with foil to protect samples from light, placed on ice and submitted for immediate analysis by flow cytometry.

Cells were analyzed by the Ohio State University, College of Veterinary

Medicine Flow Cytometry Center personnel on a Coulter Epics Elite Flow Cytometer

(Beckman Coulter, Inc., Miami, FL) with a 15mW air-cooled argon ion laser (Cyonics,

Uniphase, San Jose, CA) operated at 488nm. Collection of fluorescence emission was accomplished using a 525nm band pass filter for DiOC6(3) and a 635nm band pass filter for propidium iodide.

Normal viable control cells, including unstained and stained Jurkat and FDC-P1 cells, were used to adjust gating, forward and side scatter. Camptothecin treated Jurkat cells served as positive controls for induction of apoptosis and m-CICCP treated cells functioned as controls for DiOC6(3) staining for analysis of complete mitochondrial transmembrane potential disruption.

CHAPTER 3 INITIAL CHARACTERIZATION AND EVALUATION OF THE BIOLOGICAL ACTIVITY OF RECOMBINANT HUMAN PROLACTIN ANTAGONISTS

3.1 Introduction Due to the sensitive nature of most of the bioassays and the fact that subtle differences or impurities in recombinant protein preparations could alter experimental results, all batches of recombinant proteins were stringently characterized prior to use in assays. Characterization of each new batch of protein consisted of reducing and nonreducing SDS polyacrylamide gel electrophoresis, ultraviolet (UV), fluorescent and circular dicroism (CD) spectroscopy. In addition, the biologic activity of each new batch of protein was verified in NB2 or FDC-P1 cell bioassays. 3.2 Protein Characterization and Biologic Activity

Recombinant Wild type (WT) and mutated human prolactins (Delta41-52, G129R) were expresses in competent E. coli cells, purified and analyzed for purity and biologic activity prior to use. Typical yields of WT and G129R hPRL were 25-40mg/liter fermentation, while Delta41-52 hPRL tended to produce lower yields in the range of 12- 20mg/liter of fermentation. Purified recombinant hPRL proteins were evaluated by both reducing and non-reducing 15% SDS polyacrylamide gel electrophoresis. A molecular weight marker and a WT hPRL standard, either as a biological isolate from human pituitary procured from the National Hormone and Pituitary Program (NHPP) or a recombinant WT hPRL previously compared with the NHPP standard, were run on every gel along with the newly prepared recombinant proteins. Non-reducing gels are a reflection of hydrodynamic radius and provide information on correct disulfide bond

80 formation and protein folding. In many of the preparations of Delta41-52 hPRL and some batches of G129R hPRL, the formation of additional higher molecular weight bands was evident. Based on comparison with the molecular weight marker, these high molecular weight bands consisted primarily of protein dimer, although in some instances oligomers and large protein aggregates were also evident near the top of the gels. Only protein preparations with no or minimal (<5%) dimer and no oligomerization or aggregation were retained for use in cell assays. Reducing gels showed recombinant proteins that migrated at the correct molecular weights (WT hPRL

23kDa; Delta41-52 hPRL 21.6 kDa; G129RhPRL 23.1kDa) and the recombinant WT migrated to the same relative position as the human prolactin standard (approximately 23kDa). Preparations of G129R migrated to a position close to that of WT hPRL. All proteins exhibiting > 95% purity on SDS polyacrylamide gel electrophoresis were additionally characterized by UV, fluorescent and circular dichroism spectroscopy. UV absorbance spectroscopy showed that all recombinant proteins had a 280/250nm ratio of approximately 1.8-2.0 and showed no evidence of light scattering at 350nm indicating proper disulfide bond formation and lack of protein aggregation, respectively. When UV absorbance spectra were normalized to 277nm and compared with the WT hPRL spectra, a slight shift in maximum absorbance was noted for Delta41- 52 (280nm) as compared WT hPRL (276nm) along with mild reduction within the 250-

270nm region. The slight shift in the absorbance spectra of Delta41-52 hPRL was considered to be due to the deletion of 12 amino acids and not significant enough to be associated with alterations in disulfide bond formation. Fluorescent spectra were normalized to 338nm and all recombinant proteins exhibited similar emission patterns as compared to WT hPRL. Delta41-52 hPRL exhibited decreased maximum amplitude compared to WT hPRL. These data indicate

81 that the hydrophobic packing of the recombinant proteins were similar to WT hPRL, suggesting proper protein refolding. Alterations in fluorescent amplitude are due to either variation in protein concentration or hydrophobic packing of the protein. As the alteration in maxima was present in all batches of Delta41-52 hPRL examined, and has been noted by several others in the lab, this finding is considered to be associated with slight alteration in packing of the tryptophan residues possibly permitting increased hydration about the tryptophan residue in this mutant due to the amino acid deletions. Circular dichroism (CD) spectroscopy evaluates the structure of the protein and indicates the presence of α-helices, β-sheets and unstructured regions of the protein. The CD spectra of all proteins examined exhibited characteristics of typical α-helical proteins with two strong negative peaks at 222nm and 208nm and a strong positive peak at 190nm suggesting that the majority of the protein formed α-helical structures with no evidence of β-sheet conformations. These data are consistent with the recently described structure of hPRL (4) which indicates that hPRL consists of four α-helical bundles, comprising the majority of the molecule, with interconnecting structured and unstructured protein loops. Mass Spectrometry confirmed that the proteins were of the correct molecular weight as calculated based on their individual amino acid compositions. Molecular weights of the three prolactin proteins as determined by mass spectrometry were approximately 23,000 daltons (WT hPRL), 23,130 daltons (G129R hPRL) and 21,598 daltons (Delta41-51 hPRL). 3.3 Biologic Activity of Recombinant Human Prolactins All recombinant proteins were tested lactogenic assays, either FDC-P1 cells transfected with the human prolactin receptor or NB2-11C cells, and biologic activity was compared with previous data obtained from bioassays of WT, Delta41-52 and G129R

82 hPRL’s. Only those protein preparations with biologic activity comparable to previous bioassay data were used in the breast cancer cell assays. Bioassays in the NB2-11C and FDC-P1 hPRLR cells showed a typical bell-shaped curve with an agonist followed by an antagonist phase. The lactogenic activity of Delta41-52 hPRL was reduced greater than 10,000 fold compared with WT hPRL and G129R showed lactogenic activity intermediate between WT and Delta41-52 hPRL. 3.4 Biologic Activity of Recombinant Human Prolactins in Human Breast Cancer Cell

Lines Prior to commencing the human breast cancer cell assays, assay conditions and appropriate cell numbers had to be determined for each cell line based on the length of the proposed experiment and the detection limits of the Alamar blue vital dye. A large portion of the initial work consisted of testing different assay media conditions and cell numbers in the 96-well microplate format using Alamar blue vital dye to indicate the level of metabolically active cells in each well. Media preparations containing various percents of either fetal bovine serum (FBS) or charcoal-stripped fetal bovine serum (CSS) were tested in order to define a media capable of starving the cells (removing all growth factors) without inducing significant cell death. Human breast cancer cells, 10,000-40,000cells/well in 96-well plates, were evaluated in several different media preparations over a 96 hour time course. Figures (3.1-3.3) show the results of the various media preparations. Media containing 1%, but not 5 or 10% CSS, was sufficient to stop proliferation of the human breast cancer cells (baseline percent Alamar Blue reduction) and to maintain the cells in a metabolically active state without addition of growth factors for 72-74 hours. After 74 hours, cells began to die if left in 1%CSS without addition of growth factors. All media containing FBS, even when the concentration of FBS was dropped to 1%, contained sufficient growth factors to

83 stimulate proliferation of the breast cancer cells as indicated by the percent Alamar blue reduction above baseline levels. Appropriate cell starting numbers for the 96-well bioassays were determined and are listed above in Table 2.2.

Figure 3.1: Evaluation of varying percentages of fetal bone serum and charcoal-stripped fetal bovine serum on growth and proliferation of T47D human beast cancer cells. 85

Figure 3.2: Evaluation of 5% fetal bone serum (FBS) on growth and proliferation of T47D human beast cancer cells with both 2.5hour and 4.5hour Alamar Blue vital dye incubations.

Figure 3.3: Evaluation of fetal bone serum and charcoal-stripped fetal bovine serum on growth and proliferation of T47D human beast cancer cells with both 2.5hour and 4.5hour Alamar Blue vital dye incubations.

87 The results of human breast cancer cell bioassays using Alamar blue vital dye as an indicator of cell proliferation were sporadic and often inconsistent. None of the human breast cancer cell bioassays showed a typical bell-shaped curve indicating an agonist followed by an antagonist phase at high doses sufficient to bind all available hPRLR receptors. In several bioassays, particularly with the T47D cells, the addition of WT hPRL or either of the hPRL antagonists (Delta41-52, G129R) caused an initial decline in Alamar blue reduction. It is thought that perhaps the stimulatory effect of adding growth factors back to the cells initially enhances death in cells already partially committed to a cell death pathway, similar to the type of response noted with reperfusion injury in live tissues. The T47Dco cells showed an initial modest cell proliferation with all three hPRL treatments, followed by a steep decline in Alamar blue reduction which occurred to a greater extent and earlier in the Delta41-52 and G129R hPRL treated cells as compared to WT hPRL treated cells (Figure 3.4). In the MCF7 breast cancer cell line, doses of WT or prolactin antagonist between 0-3,500nm had no significant effect on cell proliferation. Beyond 3,500 nm, decreased metabolic activity was evident in the WT and G129R treated cells while the Delta41-52 hPRL treated cells showed enhanced metabolic activity (Figure 3.5).

Figure 3.4: T47Dco human breast cancer cell bioassay 89 MCF7 Human Breast Cancer Cell BioAssay

40 Wt hPRL Delta hPRL G129R hPRL 30 % Alamar Blue Reduction 20

0 0 10 20 30 40 50 100 200 300 400 500 1000 2000 3000 4000 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 75000 1E+05 1E+05 2E+05 2E+05 Prolactin Dose (nM)

Figure 3.5: MCF7 human breast cancer cell bioassay. 90 3.4.2 Cell morphology and evaluation of lipid accumulation by Oil Red O lipid stain

During the course of performing other experiments, I noted a distinct difference in the morphology and adhesion properties of the human breast cancer cells treated with prolactin antagonists, Delta41-52 hPRL and to a lesser extent the G129R hPRL, when compared with WT hPRL treated cells. These visible morphologic changes included gradual lack of the normal “cobblestone” appearing monolayer, loss of contact between adjacent cells with individualization of cells, often an unusual angularity followed by rounding in individualized cells and decreased adhesion to the growth surface as evidenced by increased numbers of detached cells suspended in the media and greatly diminished trypsinization time required to detach cells when required for assays.

Review of published literature revealed that similar morphologic changes had been noticed in T47D human breast cancer cells treated with WT human prolactin, but this phenomenon occurred only in the presence of added hydrocortisone (164). This group also noted and documented increased numbers of lipid droplets in T47D cells treated with the combination of hPRL or hGH plus hydrocortisone. Somewhat similar changes in morphology and lipid accumulation had also been detected in MCF7 and

MDA-MB-231 human breast cancer cells treated with the cytokine, Oncostatin M, and these alterations were attributed to increased cellular differentiation in treated cells

(167).

The similarities between cell alterations these researchers previously described in response to treating breast cancer cells with either Oncostatin M or hPRL/hGH plus hydrocortisone and the changes noted in human breast cancer cells treated with hPRL antagonists, but not WT hPRL, were very intriguing. The protocols used in these two 91 publications were modified and adapted for use to examine T47D human breast cancer cells treated for 48-72 hours with either WT hPRL or the hPRL antagonists, Delta41-52 or G129R hPRL. Oncostatin M treated T47D cells were used as a positive control for this experiment. Oncostatin M, a growth-regulating member of the cytokine family known to be secreted by activated T lymphocytes and macrophages, has been shown to inhibit growth of several human tumor cell lines (168) and to stimulate increased IL-6 and urokinase type plasminogen activator production in some cell types.

T47D human breast cancer cells treated with 500nM Delta41-52 (Figure 3.6) or

500nM G129R (Figure 3.7) hPRL antagonist (pharmacologic dose range) for 48 hours exhibited marked alterations in cell morphology and lipid vacuole numbers and distribution, as compared with T47D cells treated with 0.3nM WT hPRL (physiologic dose) (Figure 3.7). Several repeat experiments and additional evaluation of T47D cells treated with 500nM WT hPRL, a dose comparable with the prolactin antagonsist doses, showed consistent changes only in cells treated with the prolactin antagonists.

T47D human breast cancer cells treated with WT hPRL alone at doses of 0.3nM and 500nM retained the typical individual and monolayer cell morphology characteristic of this cell type in routine maintenance cultures. T47D cells treated with

WT hPRL retained normal cytoplasmic and nuclear morphology throughout the treatment period. Numbers of cells detached from the growth surface in WT hPRL treated T47D cells varied from 1-5%, similar to routinely growing cells, with a slight decrease in detached cells and no evidence of gross morphologic changes noted at the

500nM WT hPRL dose. Lipid vacuoles remained low to moderate in number and

92 tended to be fairly evenly distributed within the cytoplasm. Some cells contained no evident lipid vacuoles.

The Delta41-52 and G129R hPRL antagonist treated cells, on the other hand, exhibited dramatic morphologic changes which were initially evident at approximately

12 hours post treatment initiation. These morphologic alterations became increasingly more evident as hPRL antagonist treatment length increased over the 48-72 hour time course of these experiments.

T47D human breast cancer cells treated with Delta41-52 hPRL antagonist displayed elevated numbers of detached cells (40-60%), loss of contact between adjacent cells, marked morphologic alterations ranging from increased cellular angularity associated with cytoplasmic streaming (pseudopod-like cytoplasmic extensions) and decreased nuclear size/chromatin condensation to marked cellular cytoplasmic swelling with nuclear fragmentation. Cytoplasmic lipid vacuoles were increased in number and were most often distributed eccentrically in relation to the nucleus, often forming dense perinuclear bands.

The alterations in T47D cells treated with G129R hPRL antagonists were similar to those noted in Delta41-52 hPRL treated cells, but were considered less severe. By 24 hours post 500nM G129R hPRL administration, approximately 10% of the cells had detached from the growth surface. By 48 hours post treatment, detached cells were estimated to be 30-35% of the total cell population. Loss of contact between adjacent cells, pseudopod-like cytoplasmic extensions and cytoplasmic/nuclear swelling with nuclear fragmentation were evident. Lipid vacuoles were increased in number, completely obscuring the nucleus in some cells. In many cells, the lipid vacuoles were 93 eccentrically located in relation to the nucleus often densely concentrated at the periphery of a clear perinuclear space.

Figure 3.6: Photomicrographs of two different groups of T47D human breast cancer cells treated for 48 hours with 500nM Delta41- 52hPRL. As noted above, individualization, nuclear condensation, cell swelling, nuclear fragmentation and increased numbers of cells containing Oil Red O positive staining are evident. 95

Figure 3.7: Composite diagram of T47D human breast cancer cells treated for 48 hours with 0.3nM WT hPRL (left photomicrograph) or 500nM G129R hPRL (right hotomicrograph).

96 3.5 Discussion

Each new batch of proteins used in the assays were carefully characterized and only proteins considered to be > 95% pure and folded in correct conformation were used for further analysis. The biologic activity of each new protein produced was tested in lactogenic cell lines, in which the response to human prolactin and prolactin antagonsists had previously been well characterized. Earlier work using the FDC-P1 hPRLR and NB2-11C cell lines, which are extremely sensitive to lactogenic stimulation, had shown that WT and hPRL antagonists induced cell proliferation. In these two cell types, WT hPRL was able to stimulate proliferation with a significantly

41-52 41-52 lower dose (ED50) than either Delta or G129R hPRL. Delta and to a lesser extent, G129R, hPRL right-shifted the dose response curve in both NB-211 and FDC-

P1 cells.

It was initially anticipated that WT hPRL would exhibit a similar proliferative effect in human breast cancer cell lines known to express the hPRL receptor and that hPRL antagonists would increase the ED50 required to induce proliferation or decrease the maximal response to hPRL stimulation. Based on the results of many repetitions of human breast cancer cell bioassays using T47D, T47Dco and MCF7 cells treated with

WT hPRL or prolactin antagonists (Delta41-52 and G129R hPRL), it was postulated that rather than increasing cell proliferation through stimulation of the lactogenic hPRLR, prolactin was functioning more specifically as a survival factor in the breast cancer cells.

These results indicated that more sensitive assays designed to evaluate cell survival rather than cell proliferation were required to address the action of PRL 97 antagonists compared to WT hPRL in breast cancer cells. This data seemed to correlate well with the results of the initial microarray experiment which will be discussed in a subsequent chapter. Future experiments were designed to evaluate hPRL antagonist treated breast cancer cells for evidence of apoptosis or alterations in cell signaling pathways implicated as critical to cell survival.

Many of the alterations in cytoplasmic and nuclear morphology noted in T47D cells treated with hPRL antagonists are indicative of cell death and are suggestive of apoptosis, necrosis or possibly the occurrence of both processes depending on the individual cell examined. Based on the morphologic changes noted in the treated cells as described above, it was not possible to determine the exact mechanism of cell death.

The alterations evident in the hPRL antagonist treated T47D human breast cancer cells resemble morphologic changes induced by Oncostatin M (OSM) treatment of MCF7 and MDA-MB-231 human breast cancer cell lines.

Although some researchers have indicated that decreased cellular adhesion and increased lipid vacuoles may indicate a more aggressive and possibly metastatic phenotype, other researchers argue that the increase in lipid vacuoles is suggestive of increased cellular differentiation. (reviewed in (164))

Douglas et. al. (167) propose that the Oncostatin M-induced alterations in human breast cancer cells are consistent with increased differentiation and reduced cell proliferation. This group provides data showing that OSM increases c-myc, c-fos and

TGFα mRNA expression, increases cells in G0/ G1 phase and decreases cells in the S phase of the cell cycle.

98 Based on the dramatic alterations in cell morphology exhibited by hPRL antagonsist versus WT hPRL treated T47D human breast cancer cells, it is evident that

24-48 hours of hPRL antagonist treatment induces irreversible cell damage leading to cell death. The percent of cells exhibiting altered morphology increased with longer hPRL antagonist treatment times (data not shown). The exact mechanism leading to eventual cell death was not apparent, but the cellular alterations are very similar to those described for OSM treated human breast cancer cells. Microarray data, which will be presented in a later chapter, documented increased c-myc, c-fos and TGFα gene expression in hPRL antagonist treated T47D human breast cancer cells as compared with WT hPRL or control (serum starved, CSS) cells.

99 CHAPTER 4 EFFECT OF HUMAN PROLACTIN ANTAGONISTS ON APOPTOSIS

4.1 Introduction Apoptosis is a complex, multifaceted, active energy-requiring process leading to eventual cellular death which exhibits marked differences from necrotic cell death both in cell morphology and reaction of the surrounding tissue to cell death. Apoptosis occurs as both a normal physiologic process in embryogenesis/morphogenesis and involution of glandular tissue such as occurs in the mammary gland post-lactation and also as a pathologic process. As a pathologic event, apoptosis is usually triggered by non-lethal cellular damage which is insufficient to induce necrosis but causes alterations in the cell. Examples of this type of low level cell damaging stimuli include ultraviolet radiation, toxins, drugs, early growth factor withdrawal and many other insults most of which produce DNA damage. Additionally, apoptosis often occurs secondary to ligands binding specific death receptors (FasL, TNF-α) on the cell membrane. The process of apoptosis involves numerous, often interconnecting, intracellular signaling pathways and an intricate control system to keep this system in check thereby preventing inadvertent cell death. Numerous intracellular signaling molecules have been associated with the process of apoptosis, acting as initiators, effectors, inhibitors and regulators of this process. The most notable of these are the cysteine aspartate- specific proteases, also known as caspaces. Caspaces have long been considered the

100 central regulators of apoptosis, but recent reports in the literature have indicated that apoptosis can also occur independent of caspace activation (169). Regardless of the signaling pathways used or mechanism of apoptosis induction, initiation of apoptosis results in a set of uniform, characteristic biochemical and morphologic changes in all cells undergoing apoptosis (170). Morphologic alterations, evident at the level of the light microscope, include cell shrinkage, membrane blebbing, nuclear condensation and the formation of apoptotic bodies. The DNA fragmentation that occurs during apoptosis is not a random process, but rather a highly regulated process resulting in uniform precisely sized fragments of DNA due to internucleosomal DNA cleavage. Numerous pathologic processes, including autoimmune disorders, stroke, Alzheimer’s disease, transplant rejection, acquired immunodeficiency syndrome (AIDS), Hodgkin’s disease and many other types of cancer have been associated with inappropriately elevated or depressed levels of apoptosis. Several of the diseases listed are associated with increased induction of apoptosis. Tumor associated alterations in apoptosis often involve cell evasion of apoptosis, thereby allowing the uncontrolled proliferation of tumor cells even in the presence of DNA damage that under normal circumstances would have resulted in removal of the cell from the cell cycle and destruction of the damaged cell. Cancer related alterations in apoptosis typically involve down-regulation of tumor suppressor genes or up-regulation of oncogenes, decreasing levels of apoptosis in the tumor cell population. It is postulated that the increased survival of tumor cells associated with down-regulation of apoptosis is often more significant in enhancing tumor growth than is actual proliferation of tumor cells by cell division.

101 The complex mechanism of apoptotic cell death is still an area of intense scientific investigation. Many different signaling pathways are involved in the process of apoptosis and the pathway utilized may vary with the cell type and the apoptotic stimulus applied to the cell. There is still considerable debate as to the actual order of the sequence of intracellular events that occur in response to an apoptotic stimulus. What is known to date is that changes in both the outer and inner mitochondrial membranes, flipping of phosphatidylserine residues on the cell surface and often caspace activation occur as early events. Energy in the form of ATP is required for apoptosis to proceed, but then ATP levels decrease as mitochondrial oxidative phosphorylation is disrupted. The exact timing of ATP depletion in the apoptotic process is still a matter of debate and may vary depending on the apoptotic signal and cell type undergoing apoptosis. Late changes include DNA fragmentation, protein aggregation and formation of apoptotic bodies. Based on the results of previous bioassays and the initial microarray data analysis, it was hypothesized that human prolactin might be acting more prominently as a survival rather than a growth factor, particularly in the human breast cancer cells. As withdrawal of growth factors has been shown to induce apoptosis and decrease cell survival, we decided it might be more beneficial to develop methods to examine apoptosis rather the cell proliferation as determined by the Alamar blue bioassays. Several methods were chosen to explore various portions of the apoptotic pathway. These methods included detection of activated caspaces by western immunoblotting, measurement of alterations in cellular ATP levels and flow cytometry to evaluate mitochondrial membrane potential in correlation with percent live, necrotic and apoptotic cell populations.

102 Assays measuring cell proliferation and the results of the morphologic evaluation of human breast cancer cells treated with prolactin antagonists, indicated that more sensitive methods were needed to evaluate early cell alterations and cell survival parameters to adequately evaluate the subtle early effects of human prolactin antagonists. Based on the previously published work of Zamzami and Castedo et. al. (165, 166), a protocol was developed for rapid screening of alterations in cells treated with WT versus hPRL antagonists by flow cytometry. This protocol uses carbamoyl cyanide m-chlorophenylhydrazone (m-CICCP) as a control for disruption of mitochondrial transmembrane potential, Camptothecin as a positive control for induction of apoptosis and two fluorochromes, propidium iodide (PI) and 3,3’- dihexyloxacarbocyanine ((DiOC6(3)) to assess the metabolic state of the cell (live, dead, apoptotic) and alterations in mitochondrial transmembrane potential.

Campthothecin (C20H16O4) blocks the cell cycle in S-phase (at low doses) and induces cell cycle dependent and independent apoptosis in many normal and malignant cell types. Camptothecin irreversibly binds the DNA-topoisomerse I complex by a covalent linkage with DNA and inhibits reassociation of DNA after topoisomerase I cleavage. The covalently bound complex is ubiquinated and removed by proteosomes, thereby depleting cellular topoisomerase I.

Carbamoyl cyanide m-chlorophenylhydrazone (m-CICCP; CCCP)(C9H5CIN4) is a protonophore capable of completely disrupting the inner mitochondrial transmembrane potential (∆Ψm) by uncoupling mitochondrial oxidative phosphorylation. Cells treated with m-CICCP serve as a control for DiOC6(3) staining.

3, 3'-dihexyloxacarbocyanine iodide ((DiOC6(3) (C29H37IN2O2) is a cationic lipophilic fluorochrome that detects disruptions in inner mitochondrial transmembrane potential. Disruptions in ∆Ψm are indicated by decreased cellular uptake of DiOC6(3)

103 and a left shift in DiOC6(3) staining intensity on the x-axis of the flow cytometry histograms. Propidium iodide (PI) is a fluorescent stain that preferentially binds nucleic acids. An intact cell membrane, as is present in both viable and apoptotic cells, will exclude PI staining. In necrotic cells, the cell membrane is no longer intact, allowing for entry of PI into the cells and increasing the intensity of PI staining (as indicated on the y-axis of flow cytometry histograms). 4.2 Results 4.2.1 Caspace Western Immunoblotting Western immunoblotting for caspaces indicated elevated levels of cleaved caspace-7 in T47D human breast cancer cells treated for 48 hours with Delta41-52 hPRL antagonist as compared with WT hPRL and serum starved cells (both 0 and 48 hour samples) (Figure 4.1). The cleaved caspace-7 (Asp 198) antibody from Cell Signaling Technology™ recognizes only the large (20kDa) fragment of cleaved caspace-7. The immunoblot was reprobed with β-actin to ensure equal protein loading in all lanes (data not shown). Evaluation for cleaved caspaces-3 and 9 yielded spurious results and the data was considered inconclusive.

104

Figure 4.1: Western immunoblot for cleaved caspace 7 in T47D human breast cancer cells treated with WT hPRL or hPRL antagonists.

4.2.2 ATP Assays ATP assays were performed as described above (Chapter 2.10) using the PerkinElmer™ ATPlite Luminescence ATP Detection Assay System based on firefly (Photinus pyralis) luciferase which produces a long duration signal with a half-life of more than 5 hours and inactivates endogenous ATPases. This prolonged signal allows for simultaneous analysis of multiple samples in microplate format. The luminescence is produced by the reaction of ATP with luciferase and D-luciferin and is proportional to the ATP concentration within the given sample.

105

The ATPlite reaction is outlined below:

Luciferase ATP + D-Luciferin + O2 ------! Mg2+

------Oxyluciferin + AMP + CO2 + PPi + Light ------! Luminescence (measurable ATP concentration)

Using the ATP standard provided by the manufacturer, serial 100 fold dilutions of ATP standard (107- 10-11 nM) were prepared in each different cell assay media, plated in assay microplates and luminescence was measured as for the actual cell samples. The calculation of the ATP standard curve allows for definition of the limits of ATP detection with our system, indicates any differences produced by the different assay media and allows for calculation of ATP concentration within the cell samples.

The ATP standard curves using both T47D/T47Dco (Figure 4.2) and MCF7 assay media (Figure 4.3) show an ATP detection range of (107- 10-1 nM). There is very slight variation in the two different media at the highest and lowest end of the detection range, but overall the standard curves appear very similar with little media effect

(Figure 4.4).

106 ATP Standards in T47D/Dco Media

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Figure 4.2: Serial dilutions of ATP standard prepared in T47D/T47Dco cell assay media.

107 ATP Standards in MCF7 Media

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Figure 4.3: Serial dilutions of ATP standard prepared in MCF7 cell assay media

108 ATP Standards in MCF7 & T47D/T47Dco ATP Assay Media

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Figure 4.4: Composite diagram illustrating the similarity in ATP standard curves in MCF7 and T47D/Dco assay media.

109 The range of ATP dilutions between (10-1- 10-11 nM) was beyond the level of detection and is illustrated by a plateau on the ATP standard curve.

In the T47D human breast cancer cells (Figure 4.5), a significant decrease in cellular ATP levels occurred at approximately 15,000nM in both the Delta41-52 and

G129R hPRL antagonist treated cells. ATP levels in the Delta41-52 hPRL samples continued to decline as the dose of antagonist increased from 15,000-175,000nM. In contrast, the G129R hPRL treated cells showed a decline in cellular ATP levels from

15,000-27,000nM, reached a plateau where ATP levels remained fairly steady from

27,000-50,000nM and then declined with doses of G129R from 50,000-175,000. In the

WT hPRL treated cells, ATP levels rose from 15,000-30,000nM WT dose range and then began to decline slowly and steadily from 30,000-70,000nM. From 70,000-

125,00nM, ATP levels declined rapidly and beyond 125,000nM, ATP levels dropped below the level of detection of the assay system. Cellular ATP levels in T47D human breast cancer cells treated with Wt, Delta41-52 and G129R hPRL within the dose range of

0-15,000nM were similar. The ATP levels in T47D human breast cancer cells treated with WT hPRL doses ranging from 15,000-125,000nM were consistently higher than

ATP levels in either of the prolactin antagonist (Delta41-52, G129R) treatment groups.

Overall, cellular ATP levels in the T47D cells at the initiation of the assay were approximately 40,000RU (equivalent to an ATP concentration of approximately 1 x 106 nM) and remained at this level until doses of greater than 15,000nM hPRL were administered. At doses greater than 15,000nM hPRL, ATP levels in the hPRL antagonist treated groups declined from baseline while ATP levels for the WT hPRL

110 treated cells rose above baseline to an ATP concentration of approximately 1 x 107 nM and then declined.

In the T47Dco treated cells (Figure 4.6), ATP levels at prolactin doses between

0-15,000nM followed a similar pattern with the G129R treated cells having slightly lower levels of ATP than the WT or Delta41-52 treated cells. Between 10,000-15,000nM

Delta41-52 hPRL induced a sharp rapid decline in cellular ATP levels followed by a slower steady decline between 15,000-100,000nM Delta41-52hPRL treatment. The WT treated cells exhibited elevated ATP levels with doses of WT from 10,000-35,000nM.

From 35,000nM-75,000nM, the ATP levels in WT hPRL treated cells began a sharp decline, but still remained above the levels of ATP in both of the hPRL antagonist treated groups. G129R hPRL treated cells started to show a decline in cellular ATP levels at 20,000nM G129R, but the exhibited a spike in ATP levels at 30,000nM at lower ATP levels but mirroring the WT spike at 30,000nM. ATP levels began to decline in the G129R treated cells at doses higher than 30,000nM G129R, but consistently remained above the level of ATP in Delta41-52 hPRL treated cells and below the level of WT hPRL treated cells within the 15,000-75,000nM dose range. Cellular

ATP levels at the beginning of the assay were lower in T47Dco cells (1 x 104-5nM) versus the starting ATP level in T47D cells

(1x106nM). Within the 0-10,000nM hPRL dose range, all T47Dco cell treatment groups showed a slight rise in ATP levels above baseline. At doses higher than

10,000nM, the agonist (WT) and antagonist (Delta41-52, G129R) effects became apparent as illustrated by increased and decreased cellular ATP levels, respectively.

111

Figure 4.5: Measurement of cellular ATP levels in T47D breast cancer cells treated with WT, Delta41-52 and G129R hPRL.

112 T47Dco Human Breast Cancer Cell ATP Assay

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Figure 4.6: ATP levels measured in T47Dco breast cancer cells treated with WT, Delta41-52 and G129R hPRL. Data represent the mean of triplicate samples from two individual assays. 113 ATP levels expressed in the MCF7 treated cells (Figure 4.7) at the start of treatment were much higher (1 x 107nM) than in either the T47D or T47Dco cells. The

ATP levels remained high in all 3 treatment groups within the 0-1000nM dose range, with the Delta41-52 and G129R hPRL treated cells showing slightly lower levels of ATP than the WT hPRL treated cells. Beyond the 1,000nM dose, all, three treatment groups induced a rapid decrease in cellular ATP levels, with slightly more significant decreases in the WT and Delta41-52 as compared with the G129R hPRL treatment. At doses above

5,000nM, WT hPRL treated cells showed consistently lower levels of ATP than either the Delta41-52 or G129R hPRL treated cells. A sharply elevated ATP spike was noted with G129R treatment in the 30,000-40,000nM dose range.

Although it was noted previously that these three cell types, all human breast cancer cells, appeared to exhibit differences in both their morphology and behavior in bioassays despite similar hPRL or hPRL antagonist treatment, this is the first experiment to actually document a distinct difference in response based on the breast cancer cell line examined. The T47D and T47Dco human breast cancer cell lines show a significant decrease in cellular ATP levels with hPRL antagonist (Delta41-52, G129R) versus WT hPRL treatment, but they vary in their initial response to dosing with T47D cells maintaining a fairly steady ATP level while T47Dco cells show a rise in ATP levels at low doses (0-10,000nM) hPRL. The MCF7 breast cancer cells display a pattern similar to the T47D cells at very low hPRL doses (0-1,000nM) maintaining a fairly steady state ATP level. At doses beyond 1,000nM, the MCF7 cells are significantly different from the T47D and T47Dco cells in their response to hPRL treatment. Delta41-52 and G129R hPRL do not appear to exhibit an antagonist effect by 114 decreasing cellular ATP levels, in the MCF7 cells, as exhibited in the other two breast cancer cell lines. In fact, cellular ATP levels in the WT hPRL treated MCF7 cells drop below the level of either of the antagonist treatments at doses above 5,000nM and high doses of G129R hPRL (approximately 30,000-40,000nM) actually increase cellular

ATP levels.

115 MCF7 Human Breast Cancer Cell ATP Assay

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0 0 0 0 0 0 0 0 20 40 0 0 0 0 0 0 0 100 3 500 0 0 0 0 0 0 2000 4000 0 0 0 0 0 0 1 2 3 4 5 5 100000 1 Prolactin Dose (nM)

Figure 4.7: Luminescent detection of cellular ATP levels in MCF7 cells treated with WT, Delta41-52 and G129R hPRL. Quantification of cellular ATP levels is based on dilutions of ATP standard in appropriate cell culture media (Figures 4.2 and 4.3). (RU=relative units; luminescence).

116 4.2.3 Flow Cytometry A flow cytometry protocol was developed as both a rapid screening method for newly developed PRL antagonists and as a more sensitive method to detect early changes associated with apotosis that were undetectable by other less sensitive methods, such as the cell proliferation assays. Using dual fluorochrome labeling, the percent of live, apoptotic and necrotic (dead) cells populations present after treatment of the cells with Wt or hPRL antagonists can be readily assessed. Cells were treated and prepared for flow cytometry as described in Chapter 2.14 (Materials and Methods). A minimum of 10,000 cells were analyzed for each sample. Three to five separate experiments were performed on different days for each analysis. Human Jurkat cells were used as control cells for gating and assessment of appropriate staining quality as the flow cytometry staff had experience and were most familiar with the use of this cell line. Several controls were required for each experiment. Samples of untreated, unstained Jurkat cells and experimental cells (FDC- P1 or breast cancer cells) were analyzed for evidence of autofluorescence which could potentially confound experimental results. Untreated, unstained cells lacking autofluorescence should be concentrated with quadrant D3 on the flow histogram (as illustrated in Figure 4.8). None of our control Jurkat (Figure 4.9), FDC-P1 (Figure 4.10) or human breast cancer cells (Figure 4.11) showed any evidence of autofluorescence with 99-100% of the cell population appearing in quadrant D3.

117

Figure 4.8: Diagramatic representation of a flow cytometry histogram showing the location of untreated, unstained normal cell populations lacking inherent autofluorescence in quadrant D3 (lower left).

118

Figure 4.9: Untreated, unstained Jurkat cells showing lack of autofluorescence with the majority of cells located in quadrant D3.

119

Figure 4.10: Flow cytometry histogram of untreated, unstained FDC-P1 hPRLR cells exhibiting lack of autofluorescence.

120

Figure 4.11: Untreated, unstained human T47D breast cancer cells

Staining with propidium iodide (PI) allows for distinction between dead (quadrant D1) and live/apoptotic cell populations (quadrant D3). Live cells with intact cell membranes prohibit the entry of PI into the cell, but necrotic or dying cells with disruption of their cytolplasmic membrane allow entry of propidium iodide into the cell. Propidium iodide binds nuclei acids and intercalates cellular DNA, causing an increased PI (red) fluorescence with an elevation of values along the y-axis (Figure 4.12). Propidium iodide does not permit for differentiation between the live and apoptotic cell populations, which both coexist in quadrant D3.

121

Figure 4.12: Propidium iodide (PI) fluorescence for detection of live/apoptotic versus dead cells by flow cytometry.

The green fluorescing fluorochrome, 3, 3'-dihexyloxacarbocyanine iodide

(DiOC6(3)), measures alterations in the inner mitochondrial transmembrane potential

(∆Ψm), is capable of detecting early changes associated with apoptosis and can aid in distinguishing live from apoptotic cell populations. In contrast with PI, DiOC6(3) cannot completely differentiate apoptotic from necrotic (dead) cell populations. Cells with normal ∆Ψm, are evident in quadrant D4. As alterations begin to occur in ∆Ψm, the cell population moves to the left along the x-axis with apoptotic and necrotic cells located in quadrant D3 (Figure 4.13). Carbamoyl cyanide m-chlorophenylhydrazone

(m-CICCP) is used as a control for evaluating DiOC6(3) staining as it is capable of 122 completely disrupting inner mitochondrial membrane potential (∆Ψm), shifting all live cells present in quadrant D4 down the x-axis to quadrant D3 (Figures 4.14 and 4.15).

Figure 4.13: Diagramatic illustration of cell populations as stained by the fluorochrome 3, 3'-dihexyloxacarbocyanine iodide (DiOC6(3)) analyzed by flow cytometry.

123

Figure 4.14: Normal live FDC-P1 cell population stained with DiOC6(3) only. The majority of cells (99%), exhibit normal inner mitochondrial membrane potential and are displayed in quadrant D4 of the flow cytometry histogram.

124

Figure 4.15: Carbamoyl cyanide m-chlorophenylhydrazone (m-CICCP) rapidly and completely disrupts inner mitochondrial membrane potential resulting in a marked decrease in DiOC6(3) staining shifting cells left on the x-axis. The live cell population present in quadrant D4 (Figure 4.14) has been almost completely shifted to quadrant D3 by 15 minute treatment with m-CICCP demonstrating that the cell population used for the assay had normal, functioning mitochondrial.

By combining PI and DiOC6(3) fluorochrome staining for use in flow cytometry, live, apoptotic and necrotic cell populations can be identified from one another (Figure 4.16).

One additional positive control used in this assay is the treatment of cells with an apoptosis inducing agent, capable of decreasing ∆Ψm and thereby decreasing DiOC6(3), but to a much less severe extent than that induced by m-CICCP (which completely uncouples mitochondrial oxidative phosphorylation). Campthothecin was used to induce apoptosis. Camptothecin induced a robust apoptosis in Jurkat cells within 4 125 hours at a dose of 100uM (Figure 4.17), but exhibited only a modest effect on the FDC-

P1 cells and had no significant effect on the human breast cancer cell lines. Treatment of FDC-P1 cells with Camptothecin overnight (approximately 12 hours) or at a higher dose (200-300uM) was sufficient to induce apoptosis in the FDC-P1 cells but was still ineffective in the breast cancer cells. Treatment of breast cancer cells with > 1uM

Staurosporine was required to induce apoptosis in these cells.

Figure 4.16: Diagram illustrating the pattern of cells detected by flow cytometry using dual fluorochrome staining (PI and DiOC6(3)). The percent of live, apoptotic and necrotic/dead cell populations can be readily assessed by this method.

126

Figure 4.17: Robust apoptosis and moderate levels of necrosis are induced by 4 hour treatment of human Jurkat cells with 100uM Camptothecin. Live cells are evident in quadrant D4, apoptotic cells in quadrant D3 and necrotic (dead) cells in quadrant D1.

Untreated Jurkat cell populations showed approximately 80% live and 20% dead cells. Treatment with 100uM Camptothecin for 4 hours resulted in a reduction of live cells to approximately 8-10%, with increades apoptotic cells (approximately 38-40%) and dead cells (50%). Normal FDC-P1 cell populations in maintenance media consisted of approximately 85% live cells and 15% apoptotic and 5% necrotic cells as measured by flow cytometry. Starvation of FDC-P1 cells in CSS resulted in a decline in live cells from 85% to 55-60%, with a significant increase in cells undergoing apoptosis (40%) with no significant increase in necrotic cells.

127 Results of flow cytometry after treatment of FDC-P1 cells with WT hPRL and hPRL antagonists are listed in Table 4.1 and 4.2. Delta and the combined Delta/WT hPRL treatment induced a robust apoptosis (70% and 55% respectively) in FDC-P1 cells at 48 hours post treatment. G129R alone induced approximately 20% apoptosis, not as robust as Delta41-52 hPRL, but definitely increased over WT hPRL treatment. The combined G129R/WT treatment was slightly more effective than G129R alone, inducing apoptosis in 38.6% of cells. The double mutant (Delta41-52 and G129R combined), appeared to be similar in effect to Delta41-52hPRL. Two mutants, Q74A and S179E, showed significant increases in necrotic cell populations. The significance of these results is uncertain without further evaluation. Q74A has been previously shown to exhibit biologic activity and receptor binding (95). S179D is a controversial molecule, exhibiting both antagonist and (super) agonist activity depending on the assay system used for evaluation (132, 171). It is possible though, that the mutation S179E mutation may function as a more potent antagonist than S179D.

128

WT Delta Delta/WT G129R G129R/WT Delta/G129R 0.3nM 500nM 500/0.3nM 500nM 500/0.3nM Double Mutant (DM) 500nM D1 Necrotic 1.8 1.0 1.0 1.5 1.0 0.3 D2 0.4 0.2 0 0.5 0.3 0.1 Cell/Nuclear Debris D3 Apoptotic 1.5 70.5 55.0 20.2 38.6 77.1 D4 Live 96.3 28.3 44.0 77.8 60.1 22.5

Table 4.1: Analysis of WT and hPRL antagonists in FDC-P1 cells by flow cytometry

S26W Q74A L98E H173E S179A S179E DM/WT 500nM 500nM 500nM 500nM 500nM 500nM 500/0.3nM D1 Necrotic 1.4 14.8 1.4 1.5 1.7 47.4 0.2 D2 0.9 5.2 0.6 1.4 1.3 13.9 0.1 Cell/Nuclear Debris D3 Apoptotic 1.9 6.3 1.4 1.5 1.2 8.9 49.3 D4 Live 95.8 73.7 96.6 95.6 95.3 29.8 50.5

Table 4.2: Analysis of mutant hPRL recombinant proteins in FDC-P1 cells by flow cytometry for evaluation of potential antagonist activity.

129

CHAPTER 5

RECOMBINANT HUMAN PROLACTIN AND SIGNAL TRANSDUCTION PATHWAYS IN BREAST CANCER CELLS

5.1 Introduction Protein kinase B, also known as AKT, is a serine/threonine kinase that promotes cell survival by relaying growth factor receptor signals through the phosphatidylinositol 3-kinase (PI3 kinase) pathway. AKT exists as three distinct highly homologous isoforms (AKT 1-3), each encoded by a separate gene. AKT has been shown to inhibit apoptosis in various cell types via a variety of mechanisms including phosphorylation of BAD, blockade of mitochondrial cytochrome c release (172), activation of Mdm2 inhibition of p53 (173), c-MYC suppression (174), and inactivation of caspaces (175). AKT has been associated with several human cancers. In human breast cancer, Akt2 is often overexpressed and the presence of phosphorylated AKT has been associated with erbB2 (HER-2/neu) overexpression, poor prognosis and decreased response to some forms of cancer therapy (172). Results of the initial microarray experiment and the modest proliferative response of human breast cancer cells to exogenous prolactin treatment in bioassays suggested the possibility that prolactin might be acting primarily as a survival rather than a growth/proliferation factor, at least in the breast cancer cell lines studied in these

130 experiments. As signaling through the AKT (PKB)/PI3 kinase pathway had been described as a primary pathway increasing cell survival by decreasing apoptotic mechanisms in several cell types, it seemed reasonable that this mechanism might explain the meager proliferative response seen in the breast cancer cells treated with wild-type hPRL and the decreased survival noted in human breast cancer cells treated with hPRL antagonists. T47D human breast cancer cells were treated for 72 hours with maintenance media (FBS), assay media (CSS), WT, Delta41-52 , G129R and combined WT/ Delta41-52 or WT/G129R in assay media as described above in materials and methods. A nonradioactive AKT kinase assay kit (Cell Signaling Technology™), which selectively immunoprecipitaes AKT and measures kinase activity by the ability of AKT in the samples to phosphorylate a GSK-3 fusion protein was used. GSK-3 phosphorylation is analyzed by Western immunoblotting using a phospho-specific GSK-3α/β antibody and chemiluminescent detection. 5.2 Results

As illustrated in Figure 5.1, Delta41-52 (500nM) significantly decreased AKT kinase activity in T47D human breast cancer cells at 72 hours post hPRL antagonist treatment. The highest levels of AKT kinase activity were noted in T47D in the FBS (maintenance media), G129R (500nM) and WT (500nM) treatment groups.

Intermediate levels of AKT kinase activity were evident in the starved cells (CSS assay media), WT (0.3nM)/ Delta41-52 (500nM) and WT (0.3nM)/G129R (500nM) treated cells. These data are consistent with reports in the current literature suggesting that prolactin and growth factors (maintenance media) are associated with elevated AKT levels. Growth factor withdrawal (starved cells, CSS) and a lower level of WT hPRL

131 (0.3nM), resulted in decreased AKT levels as compared with the WT (500nM) and FBS (maintenance media) treated cells. The significant decrease in AKT kinase activity in Delta41-52 (500nM) hPRL treated cells, below the level of starved cells, suggests a couple of possibilities. Either there is some residual growth factor present in the starvation media, and Delta41-52 hPRL acts as an effective antagonist to growth factor mediated stimulation of AKT kinase activity or Delta41-52 hPRL directly or indirectly activates/inactivates a signaling pathway that suppresses AKT (PKB). The combined WT/Delta treatment resulted in intermediate AKT levels as compared with either WT or Delta hPRL treatment alone. G129R hPRL, although shown to be a modest hPRL antagonist, retains sufficient hPRL agonist activity to stimulate cells, particularly at higher doses. Therefore, a 500nM dose of G129R hPRL would be expected to result in elevated AKT levels, but elevation above the level for a similar dose of WT hPRL (500nM) was not anticipated. The combined WT (0.3nM)/G129R (500nM) treatment resulted in a level of AKT activity markedly decreased from G129R (500nM) alone and was similar to the response of the combined WT/Delta hPRL treatment and growth factor withdrawal (starvation). One possible explanation for this result could be that the mutation designed to create this antagonist, which is reported to increase the affinity of binding site 1 for the hPRLR, results in a slower off rate for the G129R prolactin molecule thereby prolonging receptor activation. In the combined WT/G129R treatment, binding of WT hPRL which has a lower site 1 binding affinity and therefore a faster off rate, to some of the hPRLR receptors in competition with G129R, could reduce receptor activated AKT elevation. It is also possible, that in this instance, the antagonist G129R activates a signaling pathway different from that activated by native (WT) hPRL.

132 Further studies evaluating the AKT/PI3 and interacting signaling pathways would be required to definitely identify the mechanism by which Delta41-52 hPRL significantly decreases and G129R increases AKT kinase activity in T47D human breast cancer cells.

Figure 5.1: Western blot of immunoprecipitated AKT demonstrating AKT kinase activity as measured by AKT-induced phosphorylation of GSK-3α/β(Ser21/9) in T-47D human breast cancer cells treated with wild-type and hPRL antagonists alone or in combination for 72 hours.

133

CHAPTER 6

GLOBAL ANALYSIS OF RECOMBINANT HUMAN PROLACTIN EFFECTS ON HUMAN BREAST CANCER CELLS 6.1 Introduction Two sets of microarray experiments were performed. The first was a preliminary experiment to assess the utility of this type of assay for the work we had proposed. Samples for the first microarray experiment consisted of T47D human breast cancer cells treated for 48 hours with WT hPRL(0.3nM), Delta41-52hPRL (500nM), combined Delta(500nM)/WT (0.3nM) and a control (starved, CSS). The T47D cells were grown to approximately 75-80% confluence, starved for 24 hours in 1%CSS, and then treated with the appropriate concentrations of WT or Delta hPRL in 1%CSS media. The control cells received fresh 1% CSS at the start of the assay and remained in 1% CSS for the 48 hour duration of the experiment. Based on the results obtained from the first set of samples, it was decided that a larger time and dose response experiment was warranted. The second experiment consisted again of T47D human breast cancer cells starved for 24 hours in 1% CSS and then treated with the desired hPRL dose. G129RhPRL, which recent literature described as a significant hPRL antagonist with minimal agonist activity, was included in this assay for comparison of antagonist activity with Delta41-52hPRL in this breast cancer cell line. Treatment groups consisted of a 1%CSS control, WT (0.3nM), Delta41-

134 52 (500nM), G129R (500nM), Delta (500nM)/WT(0.3nM) and G129R(500nM)/WT(0.3nM) hPRL’s. A time course was also proposed for this study with cell samples collected at 1, 3, 6, 9, 12, 18, 24, 36, 48, 72 and 96 hours following initiation of treatment. Total RNA was extracted from the cells at the designated times, samples were separated into aliquots for both microarray and QRT-PCR analysis and stored at -80°C. Due to the size and cost of this assay, samples evaluated by microarray analysis included only the 1, 3, 6, 12, 24 and 48 hour samples. All time points from 0-96 hours were evaluated by QRT-PCR for those genes chosen for evaluation. High density cDNA oligonucleotide arrays (microarrays) have demonstrated significant utility for identifying global alterations in gene expression, such as those involved in signaling pathways, and clusters of related genes between different biological samples (176). Microarrays have been used successfully to identify altered gene expression among various cancer cell lines (177) and clinical samples from tumor biopsies (178, 179). These assays have also been used to assess changes in gene expression between various treatment groups. The sensitivity and specificity of these assays is demonstrated by the fact that they can be used to accurately identify specific classes of tumors based on their patterns of gene expression within an individual patient or within a specific tumor class (180-184), and metastatic tumors express the same gene patterns as the primary tumor in most cases (178). A recent publication utilizes microarray data to evaluate gene expression linked to transcriptional regulation of prolactin’s biological functions in an effort to better understand the many diverse roles of prolactin. The goal was to attempt to understand how prolactin can influence such a wide variety of functions in various cell types, tissues and different, often unrelated, species (185).

135 Microarrays offer an excellent tool for initial screening to identify avenues for further investigation, but there are also several drawbacks to the use of the assays. For one, depending on the type of array, these assays can be very costly. Another major drawback is the immense volume of data that is generated and must be analyzed before any conclusions can be made concerning the data. Until recently, it was difficult, if not impossible, for most researchers to analyze microarray data. A number of various normalization and statistical methods are required to standardize data between individual cDNA arrays in any given experiment in order to account for experimental variables including differences in hybridization. Consultation with a statistician is recommended and often required to properly design and analyze microarray data. The quality of the data generated is also significantly affected by the quality of the initial samples. RNA extracted for later microarray analysis must be closely evaluated for purity and evidence of degradation prior to use in cDNA arrays in order to retrieve accurate data on alterations in gene expression. A typical formaldehyde agarose gel for analysis of RNA samples is demonstrated below in Figure (6.1). As T47D cells are a human cancer cell line, they are expected to exhibit two distinct RNA bands at 18s and 28s, with the 28s band approximately twice the intensity of the 18s band.

136

Figure 6.1: Image of a formaldehyde agarose gel of total RNA samples extracted from T47D human breast cancer cells posttreatment with WT hPRL and hPRL antagonists alone or in combination for varying times from 0-96 hours. The gels illustrate two distinct bands in each lane representing 28s and 18s human ribosomal RNA, respectively.

6.2 Results 6.2.1 Results of Microarray Experiment #1 RNA samples extracted from the T47D cells 48 hours after initiation of treatment were evaluated for quality and submitted to the OSU-CCC Microarray Facility for cDNA preparation and hybridization to the Affymetrix U133A&B human gene chip set. Initial evaluation of microarray data was performed by the OSU-CCC Microarray Facility staff using Affymetrix 5.0 software. Additional statistical analysis was performed by Karl Kornacker as described in Chapter 2.8. This second statistical

137 analysis normalized the data by averaging the mean for each gene across all microarray chips in the experiment, subtracted the background level of gene expression (control cells), provided correction to eliminate false positive and false negative data and determined p-values for all data generated. After this second analysis, data determined to be highly statistically significant between treatment groups were within a >95% confidence interval. Due to the enormous volume of data generated by each microarray chip, and particularly for the second microarray experiment, only a select set of the most highly statistically significant results will be presented. The full set of all statistically significant data from microarray experiment 1 is listed in Appendix A for review or future reference. The first experiment consisted of evaluation and comparison of genes up or down-regulated beyond control cell expression levels by 48 hour treatment with WT hPRL, Delta41-52 hPRL or combined WT/ Delta41-52hPRL treatment in T47D human breast cancer cells. Of the 33,000 human gene sequence present on the Affymetrix U133A&B chip set, WT hPRL up-regulated a total of 2,553 genes of which 76 were considered highly statistically significant and down-regulated only 7 genes, of which 2 were considered significant. The majority of the genes exhibiting increased expression in T47D cells treated with WT human prolactin encode for ribosomal proteins (Figure

6.2). Other major categories of up-regulated expression include genes involved with DNA replication, glycolysis, oxidative phosphorylation, electron transport chain, cholesterol biosynthesis and kinase activity. Delta41-52 hPRL both alone and when combined with WT hPRL, induced increased gene expression for 613 of the 33,000 transcripts examined. Of these, 28 genes were considered to be highly up-regulated (Table 6.1) and were comprised

138 primarily of genes which have been associated with apoptosis, cell cycle arrest and carbohydrate metabolism (Figure 6.3) including NfκβIA, CEBP delta (186), DNA damage inducible transcript 3 (DDIT3) and immediate early response 3 (IER3). Within the larger set of 613 genes up-regulated by Delta41-52 hPRL treatment of T47D cells, broad categories include genes involved in apoptosis, ATPases, glucose and amino acid metabolism and catabolism, protein ubiquination, immune and heat shock response pathways. Similar to WT, Delta41-52 hPRL down regulated a small number of genes with only one showing statistical significance.

139

Significant WT hPRL Dependent Gene Upregulation (Microarray Experiment 1)

600.0

500.0

400.0

300.0

200.0

100.0 Delta 0.0 Wild DeltaWild Relative to Control -100.0

Differential Gene Expression Expression Gene Differential -200.0 RPL34 RPS6 RPL37 RPS20 RPL39 RPL35 RPS17 RPS3A RPS27A RPL41 RPL5 FAU RPL6 RPS17

Gene Symbol HSDJ753D5

Figure 6.2: Figure illustrating genes in T47D human breast cancer cells exhibiting significantly elevated expression induced by WT hPRL treatment as compared with expression levels in control and Delta41-52hPRL treated cells. Most genes displayed are associated with ribosomal proteins. Analysis was performed using the Affymetrix U133A&B chip set with MAS 5.0 and additional statistical analysis. 140 Significant Delta-dependent Upregulation (Microarray Experiment 1)

250.0

200.0

150.0

100.0

50.0 Wild

Relative to Control 0.0 Delta DeltaWild Differential GeneExpression -50.0

-100.0 BF C3 OPTN NFKBIA MYC DDIT3 PLAB RARRES3 C8FW GPRC5B TNFAIP3 RPL10 Gene Symbol MAFF CYP7A1

Figure 6.3: Gene expression significantly upregulated in T47D human breast cancer cells by 48 hour treatment with Delta41-52hPRL antagonist as compared with WT hPRL treated or untreated control cells. Analysis using Affymetrix U133A&B chip set with MAS 5.0 and additional statistical analysis.

141

Delta>WT Delta/WT>WT Gene Gene Description 5.7 5.4 RPL19 ribosomal protein L19 5.2 5.4 EEF2 eukaryotic translation elongation factor 2 2.5 7.9 DUSP1 dual specificity phosphatase 1 2.2 2.2 BHLHB2 basic helix-loop-helix domain containing, class B, 2 5.1 nuclear factor of kappa light polypeptide gene 6.2 NFKBIA enhancer in B-cells inhibitor, alpha 2.4 9.0 IER3 immediate early response 3 3.4 4.6 OPTN optineurin 1.1 2.9 TRIB1 tribbles homolog 1 (Drosophila) 3.1 3.3 BF B-factor, properdin 3.4 3.6 FAM38A family with sequence similarity 38, member A 0.9 2.8 CEBPD CCAAT/enhancer binding protein (C/EBP), delta retinoic acid receptor responder (tazarotene 2.8 4.1 RARRES3 induced) 3 2.2 2.9 DDIT3 DNA-damage-inducible transcript 3 3.3 6.0 KYNU kynureninase (L-kynurenine hydrolase) 3.4 interleukin 6 signal transducer (gp130, oncostatin M 4.9 IL6ST receptor) 2.6 2.9 C3 complement component 3 1.6 2.2 GDF15 growth differentiation factor 15 5.6 ATP-binding cassette, sub-family C (CFTR/MRP), 3.6 ABCC11 member 11 5.2 6.6 TnCRNA trophoblast-derived noncoding RNA 2.9 1.6 IRF2BP2 interferon regulatory factor 2 binding protein 2 EST: 602363024F1 NIH_MGC_90 Homo sapiens 3.0 3.2 BG250721 cDNA clone IMAGE:4471541 5.3 3.4 TALD01 transaldolase 1 3.6 1.4 COL12A1 collagen, type XII, alpha 1 3.6 2.8 CDC91LT CDC91 cell division cycle 91-like 1 (S. cerevisiae) 2.4 1.8 SLC26A11 solute carrier family 26, member 11 3.3 1.6 COL12A1 collagen, type XII, alpha 1 4.5 2.6 HYPK Huntingtin interacting protein K 2.0 1.3 TnCRNA trophoblast-derived noncoding RNA

Table 6.1: Genes significantly upregulated by treatment of T47D human breast cancer cells for 48 hours with Delta41-52hPRL antagonist. Values listed represent the fold difference induced by Delta41-52hPRL alone (column 1) or combined Delta41-52/WT hPRL (column 2) treatment above gene expression in cells treated with WT hPRL alone after subtraction of background gene expression (as measured in untreated control cells).

142 6.2.2 Results of Microarray Experiment #2

The second microarray experiment included a time course analysis in addition to comparison of WT hPRL and Delta41-52 hPRL with the well-documented prolactin antagonist G129R hPRL. Overall numbers of genes exhibiting altered expression, either up or down regulated, are listed in table format (Table 6.2). Due to difficulties with hybridization to the U133B chips, only the U133A chips were analyzed for this experiment. The U133A chip contains the majority of the well-characterized human genes, whereas the U133B contains many transcripts for hypothetical proteins and expressed sequence tags. This lack of U133B chip data, although decreasing the overall number of gene expression level alterations identified, did not significantly alter global patterns based on comparison of similar samples from both the first and second experiment.

During the entire 48 hour time course evaluated, Delta41-52 hPRL treatment alone exhibited very distinct regulation of a small set of specific genes, many of which are apoptosis related. G129R hPRL treated T47D breast cancer cells showed alterations similar to Delta41-52 hPRL during the 1,3,12, and 24 hour time periods. At 6 and 48 hours, G129R hPRL, although still regulating some apoptosis related genes, exhibited agonist activity similar to WT hPRL. The combined G129R/WT treated samples were most similar to WT hPRL from 6-48 hours post treatment, exhibiting significant agonist activity. The combined Delta41-52 /WT hPRL treated cells exhibited some evidence agonist activity at 12 and 24 hours post treatment, but were still capable of altering expression of genes regulating the induction of apoptosis. WT hPRL treated samples showed little activity at the 1,3 and 6 hour time points, but began to show significant 143 agonist activity from 24-48 hours inducing upregulation of numerous genes associated with ribosomal protein, protein biosynthesis and protein transport.

6.2.3 Evaluation of the repeatability of microarray data between experiments

Comparison of the U133A gene chip data for the WT, Delta41-52 hPRL, Delta41-52

/WT hPRL treated 48 hours samples between the two experiments showed excellent correlation with similar patterns of global alterations in gene expression. A few minor differences were noted in individual gene expression, but this is most likely a result of statistical analysis of the data. As the mean values are normalized across all chips, minor differences would be expected when comparing three versus thirty samples.

These minor differences did not alter the overall trends in expression patterns.

6.3 Discussion

This data set provides evidence that both Delta41-52 and G129R hPRL exhibit antagonist activity and are capable of increasing the expression of genes which are known to be associated with induction of apoptosis and decreasing genes which inhibit

41-52 apoptosis. Delta hPRL treatment alone retained antagonist activity during the full

48 hour time course with little evidence of agonist activity. G129R, on the other hand, exhibited considerable agonist activity, similar to WT hPRL, at both 6 and 48 hours.

The combined Delta41-52 /WT and G129R/WT hPRL treatments exhibited results compatible with both antagonist and agonist activity, respectively. For some of the genes evaluated, the combined Delta41-52 /WT hPRL treated induced higher levels of apoptosis related genes when compared with antagonist treatment alone. The combined treatments were capable of altering many genes associated with apoptosis and inhibition

144 of the cell cycle, but also exhibited evidence of both up and down-regulating other genes associated with agonist activity.

145

Time Delta Delta WT/Delta WT/Delta G129R G129R WT/G129R WT/G129R WT WT (hours) UpReg DownReg UpReg DownReg UpReg DownReg UpReg DownReg UpReg DownReg 1 hr 10 0 432 3 8 1 16 3 6 1 3 hr 10 2 6 1 24 0 13 2 6 10 6 hr 20 2 15 0 1148 2060 2376 2121 0 0 12 hr 16 0 1226 2679 8 8 1249 2526 2385 3338 24 hr 26 2 1521 2847 24 2 1649 2675 1264 2635 48 hr 23 1 18 0 1507 1998 1119 2704 987 2931

Table 6.2: Microarray experiment #2 data table showing the total number of genes significantly up or down-regulated at six different time points in T47D human breast cancer cells treated with human prolactin antagonsists (Delta41-52, G129R), WT hPRL or receiving combined antagonist/WT hPRL treatment. Data was collected utilizing the Affymetrix U133A human gene chip. Numbers above represent the number of gene exhibiting significantly altered expression out of a total of approximately 22,000 genes evaluated for each sample.

146

CHAPTER 7 COMPARISON OF QUANTITATIVE RT-PCR AND MICROARRAY DATA

7.1 Introduction Microarray analysis is an excellent tool for evaluating gene expression and overall trends in response to different treatments, but changes in gene expression may not always correlate with functional changes occurring at the level of the cell. Quantitative real-time RT-PCR is a powerful and highly sensitive technique for quantifying cellular mRNA expression thereby providing evidence of functional consequences in the cell due to induction or inhibition of specific gene expression. Based on the results of the first microarray experiment, a select set of genes including several involved in apoptosis were chosen for quantification of mRNA levels and comparison with corresponding gene expression. The genes include API5, AVEN, hPRL, hPRLR, hGH, NFκβIA and PIP. For this set of experiments, genes specific primers were used to prepare standards for quantification of mRNA copy numbers to ensure accurate QRT-PCR results. The decision to produce genes specific standards was based on reports in the recent literature that currently used housekeeping genes (β-actin, 18S rRNA, 28S rRNA, cyclophilin, GAPDH) may vary greatly in expression among different tissue and cell types thereby significantly affecting mRNA quantification and interpretation of experimental results (163, 187-189).

147

7.2 Apoptosis Inhibitor 5 (API5) Expression Results Apoptosis Inhibitor 5 (API5) is a nuclear antiapoptotic factor that has been shown to inhibit apoptosis (190) after growth factor withdrawal and to interact specifically with Fibroblast Growth Factor 2 (FGF2)(191). Results of microarray analysis showed that treatment of T47D human breast cancer cells with 500nM Delta41- 52 hPRL alone or the combined 500nM Delta41-52/0.3nM WT hPRL significantly decreased API5 gene expression as compared with WT, G129R and G129R/WT. The level of API5 gene expression (Figure 7.1) in the Delta/WT treated cells was lower than that of the Delta only treatment group and only slightly higher than the control (starved) treatment group. When examined at a single time point (48hours), results of QRT-PCR analysis (Figure 7.2) showed low levels of API5 mRNA expression for all treatment groups except for G129R, which showed marked elevation. When examined over a 96 hour time course, all samples showed marked variation in mRNA expression, except for G129R, which showed marked elevation of API5 mRNA (Figure 7.3). At 18 hours post treatment, the combined Delta/WT treatment group showed the lowest level of API5 mRNA expression. By 48 hours, the levels of API5 mRNA had dropped significantly in all groups except the G129R treated cells. By 96 hours, all treatment groups showed elevated API5 mRNA levels with the G129R, Delta41-52, G129R/WT and CSS treated groups expressing slightly higher API5 mRNA than the WT and Delta/WT treated cells. These data suggest that at 18 hours after treatment with hPRL antagonists, the combined Delta41-52/WT treatment significantly down regulates API5 (an inhibitor of apoptosis) while the combined G129R/WT and Delta41-52 hPRL treatments modestly decrease API5 mRNA as compared to WT hPRL. G129R hPRL alone significantly

148 elevates this apoptosis inhibitor at all time points examined from 0-96 hours. Between 48-96 hours, all treatments appear similar, except for the elevated API5 with G129R alone, suggesting that the most prominent changes in API5 mRNA levels occur within 0-36 hours of hPRL treatment.

149

Apoptosis Inhibitor 5 (API5) Gene Expression (in T47D Human Breast Cancer Cells 48 hours post Prolactin treatment)

2.0

1.8

1.6

1.4

1.2

1.0 (log base 2) 0.8

API5 Gene Expression 0.6

0.4

0.2

0.0 0hr Cont Delta Delta/WT G129R G129R/WT WT Prolactin Treatment Group

Figure 7.1: Apoptosis Inhibitor 5 (API5) gene expression in T47D human breast cancer cells 48 hours after hPRL treatment. Values are expressed as normalized mean gene expression in log base 2 (value of 1=2-fold upregulation; 2=4-fold upregulation). Fold changes >1.5-2.0 are considered significant; therefore all samples illustrated show upregulation at 48 hours. The G129R, G129R/WT and WT treatments show significant upregulation as compared to the control, Delta41-52 and Delta41-52/WT groups.

150 Apoptosis Inhibitor 5 (API5) QRT-PCR 2 (T47D Human Breast Cancer Cells)

1.8

1.6

1.4

1.2

0.8

API5 mRNA ExpressionAPI5 mRNA 0.6

0.4 (copy numbers relative to gene specific control)

0.2

0 Control Delta Delta/WT G129R G129R/WT WT Prolactin Antagonist Treatment Group (48 hours post prolactin treatment)

Figure 7.2: Apoptosis Inhibitor 5 mRNA expression in T47D human breast cancer cells 48 hours post prolactin treatment (mRNA copy numbers x 106). 151 API5 mRNA Expression (QRT-PCR) in T47D Human Breast Cancer Cells

2.5

2 CSS Wt hPRL Delta hPRL 1.5 G129R hPRL Wt/Delta hPRL Wt/G129R hPRL

API5 mRNA Expression Expression mRNA API5 1 (relative to gene specific control)

0.5

0 9 hr 18hr 36hr 48hr 72hr 96hr Human Prolactin Treatment Time (hours)

Figure 7.3: API5 mRNA expression inT47D human breast cancer cells from 0-96 hours post prolactin treatment (mRNA copy numbers x 106 relative to an API5 gene specific positive control). 152 7.3 AVEN Expression Results Aven has been described as an inhibitor of caspace activation. The mechanism by which Aven blocks caspace activation is thought involve binding and inactivation of Apaf-1 and Bcl-xl (192). Aven mRNA expression (Figure 7.4) varies over the 96 hour time period for all treatments, but three time points appear significant (18, 48 and 96 hours). At 18 and 48 hours, Aven mRNA is highest in the WT and G129R treated cells and lowest in the Delta/WT group (18 hours) and in the Delta only group (48 hours). Between 48-96 hours, there is a significant decrease in Aven mRNA expressed by cells treated with WT and G129R and an elevation in Aven mRNA expressed by cells treated with Delta hPRL. By 96 hours post treatment, Aven mRNA expression is highest in the Delta treated group, with all other groups clustering together at a lower level of Aven mRNA expression. A couple of different interpretations are possible for this data. One is that WT and G129R are capable of elevating Aven mRNA, and thus inhibiting apoptosis, at least during the first 48 hours after treatment of the cells. Another possible explanation is that during the first 48 hours, with spikes at 18 and 48 hours, the agonist activity of WT and G129R support increased mRNA expression in the cells, including Aven. But by 48-96 hours, as agonist activity begins to decline so do levels of Aven mRNA in the WT and G129R groups. Between 72-96 hours, only Delta hPRL treatment is capable of increasing Aven mRNA, and therefore inducing apoptosis, in the cells. The overall trends in gene expression offer most support to the second scenario.

153 AVEN (Caspace Activation Inhibitor) mRNA Expression by QRT-PCR

4 CSS WT Delta 3 G129R WT/Delta AVEN mRNA WT/G129R 2

1 (copies numbers relative to gene specific control) specific gene to relative numbers (copies

0 9 1836487296 Time (hours post Prolactin treatment)

Figure 7.4: Time course following Aven (Caspace Activation Inhibitor) mRNA expression in T47D human breast cancer cells following treatment with WT or hPRL antagonists (copy numbers x 105 relative to Aven gene specific control).

154 7.4 Human Prolactin (hPRL) Expression Results Prolactin gene expression and mRNA levels do not appear to correlate well in these studies. At 48 hours, prolactin gene expression is decreased only in the Delta hPRL treated cells (Figure 7.5). Prolactin mRNA expression (Figure 7.6) shows two peaks, one at 36 hours for the starved cells and another peak at 72 hours for WT hPRL. G129R treated cells show a low level of prolactin mRNA expression over the entire 96 hour time course and Delta hPRL treated cells exhibit a level of expression somewhat higher than G129R treatment. The level of hPRL mRNA decreases gradually over the 96 hour time course in the Delta hPRL samples with a very slight elevation at 72 hours. Prolactin mRNA rises rapidly in the starved cells until 36 hours and then decline significantly from 36-96 hours. In the WT hPRL treated cells, hPRL mRNA rises gradually for the first 72 hours and then declines rapidly from 72-96 hours. The combined Delta/WT and G129R/WT both exhibit an intermediate level of hPRL mRNA expression, higher than either G129R or Delta alone, and lower than the starved and WT treated cells at some but not all time points. There does not appear to be any correlation between hPRL gene expression at 48 hours and hPRL mRNA levels at any of the time points between 0-96 hours. It appears, at least at the time points selected, no distinct conclusions can be made regarding hPRL mRNA levels expressed by T47D human breast cancer cells based on hPRL gene expression.

155

Figure 7.5: Prolactin gene expression in T47 human breast cancer cells 48 hours post prolactin or prolactin antagonist treatments. (Normalized mean gene expression relative to zero hour control in log base 2).

156 Human Prolactin mRNA Expression in T47D Human Breast Cancer Cells by QRT-PCR

CSS 20 WT Delta G129R 15 Delta/WT G129R/WT Human ProlactinmRNA

(copy numbers relative to hPRL gene specific control) specific gene hPRL to relative numbers (copy 5

0 18 36 72 96 Time (hours post Prolactin treatment)

Figure 7.6: Prolactin mRNAexpression in T47D human breast cancer cells treated with prolactin or prolactin antagonists (copy numbers x 102 relative to hPRL gene specific control).

157 7.5 Human Prolactin Receptor (hPRLR ) Expression Results During the 96 hour time course, human prolactin receptor mRNA decreases sharply during the first 36 hours in all groups with the most significant decrease in the WT hPRL treated cells. Delta and G129R treated groups show intermediate hPRLR mRNA expression at 36 hours, while the starved (CSS) cells and combined Delta/WT and G129R/WT groups exhibit the highest level of hPRLR mRNA. WT hPRL exhibits an elevation in hPRLR mRNA levels from 36-96 hours post prolactin treatment (Figure 7.7). Human PRLR gene expression at 48 hours post treatment (Figure 7.8) appears to have an inverse relationship to mRNA expression at 36 hours, except for the combined G129R/WT treatment. At 96 hours, samples exhibiting elevated gene expression also show elevated mRNA expression and those with low gene expression show low mRNA levels. Without further experimentation, it is not possible to determine whether increased hPRLR mRNA at 36 hours led to decreased gene expression at 48 hours post treatment (negative regulation) or whether increased hPRLR gene expression at 48hours led to increased mRNA levels (positive regulation) at 96 hours. Based on what is known about the mechanisms of action of human prolactin and the prolactin receptor, a negative feedback system seems the most likely explanation.

158 Human Prolactin Receptor (hPRLR) mRNA Expression QRT-PCR in T47D Human Breast Cancer Cells

8 CSS WT Delta 6 G129R WT/Delta WT/G129R mRNA Expression Expression mRNA 4 (Relative to hPRLR positve control mRNA) 2

0 9 18367296 Prolactin Treatment Time (hours)

Figure 7.7: Human prolactin receptor (hPRLR) mRNA expression in T47D human breast cancer cells (copy numbers x 106 relative to hPRLR gene specific control).

159 Human Prolactin Receptor (hPRLR) Gene Expression in T47D Human Breast Cancer Cells (48 hours post prolactin treatment) 1.8

1.6

1.4

1.2

0.8 (log base 2)

hPRLR Gene Expression Expression Gene hPRLR 0.6

0.4

0.2

0 Control Delta Delta/WT G129R G129R/WT WT Human Prolactin Treatment

Figure 7.8: Human prolactin receptor (hPRLR) gene expression in T47D human breast cancer cells 48 hours post prolactin treatment (normalized mean in log base 2).

160 7.6 NFκβIA Expression Results Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha (NFκβIA) is an inhibitor of the transcription factor NF-κβ. NFκβIA blocks NF-κβ translocation from the cytoplasm to the nucleus, thereby inhibiting NF-κβ induced transcription and inducing apoptosis in some cell types (193). NFκβIA gene expression was significantly increased in T47D human breast cancer cells by treatment with combined 500nM Delta/0.3nM WT from 6-24 hours with a rapid decrease between 24-48 hours. Between 6-12 hours, the 500nM Delta hPRL also increased NFκβIA gene expression, but to a much lesser extent than the combined Delta/WT treatment. G129R showed a slightly elevated gene expression at 6 hours and a marked elevation between 24-48 hours, but never quite reached the level of expression exhibited by Delta/WT. Delta hPRL treatment alone modestly increased NFκβIA gene expression between 6-12 hours, with a slow steady decline from 12-48 hours (Figure 7.9). NFκβIA mRNA levels (Figure 7.10) at 48 hours closely mirror the gene expression levels with the highest levels expressed by G129R hPRL treatment alone. Between 48-96 hours, G129R treated cells show a steep decline in NFκβIA mRNA, whereas Delta and Delta/WT treated cells begin to exhibit increased NFκβIA mRNA. By 96 hours, NFκβIA mRNA is significantly higher in the Delta and Delta/WT groups than with any of the other treatments (WT, G129R, G129R/WT or starvation). Starved (CSS) treated cells exhibit the lowest level of NFκβIA mRNA from 40-96 hours post treatment. During the 40-72 hour time period, G129R caused the most significant elevation of NFκβIA mRNA, and this data shows excellent correlation with the 48 hour gene

161 expression data. Beyond 72 hours, Delta hPRL alone or in combination with WT hPRL induce the highest levels of NFκβIA mRNA.

162 NFkBIA Gene Expression (T47D Human Breast Cancer Cells)

4.500

4.000

3.500

3.000

Delta 2.500 Delta/WT G129R 2.000 G129R/WT (log base 2) (log base WT Gene Expression Expression Gene

1.500

1.000

0.500

0.000 136122448 Time (hours post Prolactin treatment)

Figure 7.9: NFκβIA gene expression 48 hours post prolactin treatment in T47D human breast cancer cells (normalized mean log base 2).

163 NF-κβ Inhibitor Alpha (NF-κβIA; I κβA) mRNA Expression (T47D Human Breast Cancer Cells)

4.5

3.5

3 CSS WT IA positive control mRNA)

κβ Delta 2.5 WT/Delta G129R

IAmRNA Expression 2 WT/G129R κβ

NF- 1.5

(copy numbers relative to NF- to relative numbers (copy 0.5

0 9 1836487296 Himan Prolactin Treatment Time (hours)

Figure 7.10: NFκβIA mRNA expression in T47D human breast cancer cells (copy numbers x 107 relative to NFκβIA gene specific control). 164 7.7 Prolactin-Inducible Protein (PIP) Expression Results Prolactin-inducible protein (PIP), also known as gross cystic disease fluid protein 15 (GCDFP-15), is a protein present within the fluid of benign mammary cysts and normal secretions including seminal fluid, sweat and tears (194). PIP mRNA has been detected in most mammary tumors and breast tumor cell lines (195) (196). Immunohistochemistry has demonstrated PIP protein expression in greater than 90% of breast cancers (197) and their associated metastases. Although PIP is also expressed within the skin, salivary glands, normal mammary epithelium and some white blood cells, clinically PIP is considered to be a fairly specific marker for human breast cancer. PIP is primarily used to assist in identifying metastases of mammary origin (198). Higher levels of PIP expression have been associated with estrogen and progesterone receptor positive tumors and apocrine differentiation (198). Gene expression profiling shows that PIP gene expression remains lower in Delta hPRL treated cells than with any of the other hPRL treatments (Figure 7.11). A slight increase in PIP gene expression in the Delta treated sample was evident between 12-24 hours, but still remained significantly lower then all other treatments. G129R hPRL showed a sharp steady rise between 3-12 hours, started to decline and then rose again slightly between 24-48 hours. Overall, G129R treatment resulted in gene expression intermediate between the lowest (Delta treated) and highest (G129R/WT treated) samples until the sharp rise noted at 48 hours. The highest PIP gene expression was displayed by the combined G129R/WT treatment at approximately 12 hours post treatment, showing a rapid increase from 3-12 hours followed by a slight decline at 24 hours and elevation again from 24-48 hours. WT hPRL and the combined Delta/WT treatment showed a very similar gene expression signature, both rising steadily in

165 parallel from 6-48 hours and exhibiting the highest level of PIP expression among all treatments at 48 hours. Quantification of PIP mRNA levels by QRT-PCR showed significant variations in PIP mRNA expression over time for all treatments, except the starved (CSS) cells which remained at a fairly low level throughout the entire 96 hour time course (Figure 7.12). G129R and the combined Delta/WT treatments tended to mirror one another with peaks at 36 and 96 hours, troughs at 18 and 48 hours and significant elevation above all other treatment groups at 96 hours. Delta hPRL treated samples showed a modest rise between 18-36 hours, a plateau between 36-48 hours, a decline at 72 hours and again modest elevation at 96 hours. WT hPRL exhibited peaks at 36 and 72 hours then declined rapidly between 72-96 hours, at which time WT hPRL treated cells exhibited the lowest level of PIP mRNA expression. There appeared to be no significant correlation between PIP gene expression and PIP mRNA levels at any of the time points examined. The fairly steady low level of PIP mRNA expression in the serum starved cells (CSS) and the higher levels in cells treated with human prolactins, in particular the samples treated with WT hPRL, correspond well with reports that prolactin or perhaps other growth stimuli are required to induce PIP expression. G129R and Delta hPRL, respectively, remained at fairly low levels of PIP mRNA expression until rising between 72-96 hours post treatment.

166

Human Prolactin-Induced Protein (PIP) Gene Expression (T47D Human Breast Cancer Cells)

4.500

4.000

3.500

3.000

Delta 2.500 Delta/WT G129R 2.000 G129R/WT (log base 2) WT PIP Gene Expression 1.500

1.000

0.500

0.000 136122448 Time (hours post Prolactin treatment)

Figure 7.11: Prolactin-Inducible Protein (PIP) Gene Expression in T47D human breast cancer cells treated from 0-96 hours with human prolactin or prolactin antagonists (normalized mean log base 2).

167 Prolactin-Inducible Protein (PIP) QRT-PCR (T47D human breast cancer cells)

10 CSS WT Delta 8 G129R WT/Delta WT/G129R Human PIP mRNA 6

(copy numbersrelative to PIPgene specific control) 2

0 9 1836487296 Time (hours post prolactin treatment)

Figure 7.12: Prolactin-Inducible Protein (PIP) mRNA levels in T47D human breast cancer cells treated from 0-96 hours with human prolactin or prolactin antagonists (copy numbers x 105 relative to hPIP gene specific control).

168 7.8 Human Growth Hormone The most notable changes in human growth hormone (hGH) mRNA levels measured by QRT-PCR (Figure 7.13) were evident during the 9-36 hour period after prolactin or prolactin antagonist treatment, either alone or in combination. A significant rapid rise in hGH mRNA (9-18 hours) followed by a steep decline (18-36) hours was noted for all treatments (WT, G129R, Delta, and G129R/WT), except the combined Delta/WT treatment. The Delta/WT treated sample showed minimal elevations at 18 and again at 72 hours post prolactin treatment. Human GH mRNA levels for the Delta/WT group remained lower than all other samples except the starved cells at all time points from 0-72 hours. From 72-96 hours, the Delta/WT treated cells exhibited declining hGH mRNA at levels similar to all other prolactin treated samples. Data for the starved (CSS) cells was not available for the 9-36 time frame due to insufficient sample quantity. During the 72-96 hour time period, CSS cells showed the lowest level of hGH mRNA. All samples exhibited a decrease in hGH mRNA levels to baseline between 72-96 hours after treatment.

169 Human Growth Hormone mRNA Expression measured by QRT-PCR in T47D Human Breast Cancer Cells

20 CSS WT Delta 15 G129R WT/Delta WT/G129R

specific positive control) 10

5 hGH mRNA Expression (copy numbers relativeto hGH gene

0 9 18367296 Time (hours post prolactin treatment)

Figure 7.13: hGH mRNA levels measured in T47D human breast cancer cells treated with human prolactin or prolactin antagonists (copy numbers x 102 relative to hGH gene specific control).

170 7.9 Discussion The data presented above clearly illustrates that gene expression and mRNA levels within treated cells sometimes, but not always, correspond well with one another. In some cases, good correlation was present between mRNA and gene expression. In other examples such as for hPRLR, a significant lag time existed between changes in gene expression and cellular mRNA levels. In two of the examples presented, hPRL and PIP, no evident correlation was noted between mRNA and gene expression levels. This lack of correlation between gene expression and quantified mRNA levels in some samples could signify a true lack of association in these cells or might be related to the time points chosen for evaluation. It is possible that earlier or later time points may be needed for evaluation of functional cellular evidence related to alterations in gene expression for some of the genes examined. The quantitative mRNA data reveals high levels of cellular mRNA expression of

API5 (copy numbers x 106), Aven (x 105), NFκβIA (x 107), PIP (x 105) and hPRLR (x 106). Much lower levels of hPRL (x 102) and hGH (x 102) mRNA were present in all samples examined. These data are consistent with published reports that high levels of the hPRLR and much lower levels of hPRL mRNA are expressed in T47D human breast cancer cells. Copy numbers for hPRLR, hPRL and hGH are within the range noted by other investigators attesting to the quality of the mRNA data presented here.

The data presented also demonstrate the utility of a time course study, when possible, for evaluating gene and mRNA expression data. Changes in gene and mRNA expression varied widely over the 0-96 hour time course of this study, even within individual treatments. Selecting a single time point for examining alterations in mRNA or gene expression may not reveal an accurate reflection of events occurring at the cellular level, particularly if the chosen time point lies outside of the active range of

171 alterations in gene or mRNA expression. Also, by selecting only a single time point for evaluation, important trends such as the biphasic responses for some of the genes examined would not have been noted.

172

APPENDIX A

MICROARRAY DATA – EXPERIMENT 1

173 A.1 Genes with statistically significant up-regulation by Delta41-52hPRL (fold change as compared with WT hPRL)

Delta>WT Delta/WT>WT Gene Gene Description 5.7 5.4 RPL19 ribosomal protein L19 5.2 5.4 EEF2 eukaryotic translation elongation factor 2 2.5 7.9 DUSP1 dual specificity phosphatase 1 2.2 2.2 BHLHB2 Basic helix-loop-helix domain containing, class B, 2 5.1 6.2 NFKBIA nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha 2.4 9.0 IER3 immediate early response 3 3.4 4.6 OPTN Optineurin 1.1 2.9 TRIB1 tribbles homolog 1 (Drosophila) 3.1 3.3 BF B-factor, properdin 3.4 3.6 FAM38A family with sequence similarity 38, member A 0.9 2.8 CEBPD CCAAT/enhancer binding protein (C/EBP), delta 2.8 4.1 RARRES3 retinoic acid receptor responder (tazarotene induced) 3 2.2 2.9 DDIT3 DNA-damage-inducible transcript 3 3.3 6.0 KYNU kynureninase (L-kynurenine hydrolase) 3.4 4.9 IL6ST interleukin 6 signal transducer (gp130, oncostatin M receptor) 2.6 2.9 C3 complement component 3 1.6 2.2 GDF15 growth differentiation factor 15 5.6 3.6 ABCC11 ATP-binding cassette, sub-family C (CFTR/MRP), member 11 5.2 6.6 TnCRNA trophoblast-derived noncoding RNA 2.9 1.6 IRF2BP2 interferon regulatory factor 2 binding protein 2 3.0 3.2 BG250721 EST: 602363024F1 NIH_MGC_90 Homo sapiens cDNA clone IMAGE:4471541 5', mRNA sequence. 5.3 3.4 TALD01 transaldolase 1 3.6 1.4 COL12A1 collagen, type XII, alpha 1 3.6 2.8 CDC91LT CDC91 cell division cycle 91-like 1 (S. cerevisiae) 2.4 1.8 SLC26A11 solute carrier family 26, member 11 3.3 1.6 COL12A1 collagen, type XII, alpha 1 4.5 2.6 HYPK Huntingtin interacting protein K 174

A.2 Genes significant down regulated by Delta41-52hPRL (fold changes as compared with WT hPRL).

Delta/WT Delta < WT < WT Gene Gene Description -1.0 -2.0 PKM2 pyruvate kinase, muscle -3.0 -2.1 GMFB glia maturation factor, beta -1.7 -1.0 HPRT1 hypoxanthine phosphoribosyltransferase 1 (Lesch-Nyhan syndrome) -12.9 -10.6 OPHN1 oligophrenin 1 -12.6 -12.1 RECK reversion-inducing-cysteine-rich protein with kazal motifs ESTs, Weakly similar to I57588 HSrel-1 - human (fragment) -2.0 -2.0 [H.sapiens] -2.1 -1.9 TBC1D15 TBC1 domain family, member 15 -1.9 -1.0 KIF20A kinesin family member 20A -10.9 -10.7 SCD4 stearoyl-CoA desaturase 4 -17.1 -16.6 FLJ23558 hypothetical protein FLJ23558 -3.7 -2.8 Pfs2 DNA replication complex GINS protein PSF2 -19.9 -21.5 CDNA: FLJ23566 fis, clone LNG10880 -13.3 -16.0 FLJ45803 FLJ45803 protein

175 A.3 Gene expression significantly altered by treatment of T47D human breast cancer cells with WT hPRL alone or in combination with Delta41-52hPRL for 48 hours duration (normalized mean values for each gene).

WT Delta Delta/WT GENE Gene Title 227.3 29.7 513.9 TMSL6 thymosin, beta 4, X-linked /// thymosin-like 6 218.4 -59.2 198.0 PGK1 phosphoglycerate kinase 1 207.2 -32.4 138.0 C14orf2 chromosome 14 open reading frame 2 186.4 3.4 652.6 EEF1A1 eukaryotic translation elongation factor 1 alpha 1 165.4 -90.0 348.2 RPS20 ribosomal protein S20 164.7 -34.9 495.0 TFRC transferrin receptor (p90, CD71) 160.0 -35.0 293.8 RPL39 ribosomal protein L39 132.5 -91.7 561.2 RPS17 ribosomal protein S17 129.7 -14.5 93.2 C9orf156 chromosome 9 open reading frame 156 116.9 -25.9 193.5 ------107.4 8.1 70.6 ------105.6 -48.9 281.7 RPL3 ribosomal protein L3 /// ribosomal protein L3 95.4 -128.0 440.6 RPS17 ribosomal protein S17 85.4 -65.0 227.2 RPL5 ribosomal protein L5 81.5 -27.7 195.8 PTP4A2 protein tyrosine phosphatase type IVA, member 2 76.4 1.9 112.6 ------73.6 1.2 154.4 CRISP3 cysteine-rich secretory protein 3 72.9 -78.7 149.0 HMGCS1 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 (soluble) 71.8 -21.2 75.8 DEPDC6 DEP domain containing 6 69.2 -126.2 352.5 TPT1 tumor protein, translationally-controlled 1 68.1 7.4 65.7 STK10 serine/threonine kinase 10 67.7 -29.8 78.5 UQCRB ubiquinol-cytochrome c reductase binding protein solute carrier family 25 (mitochondrial carrier; adenine nucleotide translocator), 66.6 0.5 158.9 SLC25A6 member 6 61.6 2.7 46.5 MS4A1 membrane-spanning 4-domains, subfamily A, member 1 58.7 -16.1 65.0 GYG2 glycogenin 2 50.2 -10.5 66.3 PSPN persephin 176

WT Delta Delta/WT GENE Gene Title

48.2 -8.3 98.0 TOMM20 translocase of outer mitochondrial membrane 20 homolog (yeast) 47.4 -8.1 67.5 EXOC7 exocyst complex component 7 46.5 7.5 45.6 ZNF305 zinc finger protein 305 45.9 1.2 62.5 SLCO1A2 solute carrier organic anion transporter family, member 1A2 43.7 -4.0 46.3 ------40.2 -142.7 315.7 NACA nascent-polypeptide-associated complex alpha polypeptide 36.6 -7.4 30.9 FBXO31 F-box protein 31 33.8 -5.0 79.2 PRKD2 protein kinase D2 27.1 2.0 29.4 KRT24 keratin 24 21.6 -18.6 31.4 MGC4859 hypothetical protein MGC4859 similar to HSPA8 20.2 -13.8 18.4 LOC88523 CG016 -58.6 2.3 -34.6 RFNG radical fringe homolog (Drosophila) -153.1 -74.7 -147.4 CLPTM1 cleft lip and palate associated transmembrane protein 1

177 LIST OF REFERENCES AND LITERATURE CITED

1. Peterson, F. C. and Brooks, C. L. Different elements of mini-helix 1 are required for human growth hormone or prolactin action via the prolactin receptor. Protein Engineering, Design & Selection, 17: 417-424, 2004.

2. Chen, W. Y., Ramamoorthy, P., Chen, N.-y., Sticca, R., and Wagner, T. E. A Human Prolactin Antagonist, HPRL-G129R, Inhibits Breast Cancer Cell Proliferation through Induction of Apoptosis. Clinical Cancer Research, 5: 3583-3593, 1999.

3. Llovera, M., Pichard, C., Bernichtein, S., Jeay, S., Touraine, P., Kelly, P., A, and Goffin, V. Human prolactin (hPRL) antagonists inhibit hPRL-activated signaling pathways involved in breast cancer cell proliferation. Oncogene, 19: 4695-4705, 2000.

4. Keeler, C., Dannies, P.S., Hodsdon, M.E., The Tertiary Structure and Backbone Dynamics of Human Prolactin. Journal of Molecular Biology, 328: 1105-1121, 2003.

5. Degenerative neurologic disease in patients formerly treated with human growth hormone. Report of the Committee on Growth Hormone Use of the Lawson Wilkins Pediatric Endocrine Society, May 1985. Journal of Pediatrics, 107: 10- 12, 1985.

6. Yamauchi, T., Yamauchi, N., Ueki, K., Sugiyama, T., Waki, H., Miki, H., Tobe, K., Matsuda, S., Tsushima, T., Yamamoto, T., Fujita, T., Taketani, Y., Fukayama, M., Kimura, S., Yazaki, Y., Nagai, R., and Kadowaki, T. Constitutive Tyrosine Phosphorylation of ErbB-2 via Jak2 by Autocrine Secretion of Prolactin in Human Breast Cancer. The Journal of Biological Chemistry, 275: 33937-33944, 2000.

178

7. Das, R. and Vonderhaar, B. Prolactin as a mitogen in mammary cells: prolactin, growth hormone, and placental lactogen. Journal of Mammary Gland Biology and Neoplasia, 2: 29-39, 1997.

8. Llovera, M., Touraine, P., Kelly, P., A, and Goffin, V. Involvement of prolactin in breast cancer: redefining the molecular targets. Experimental Gerontology, 35: 41-51, 2000.

9. Vonderhaar, B. K. Prolactin: The Forgotten Hormone of Human Breast Cancer. Pharmacol, 79: 169-178, 1998.

10. Touraine, P., Martini, J., Zafrani, B., Durand, J., Labaille, F., Malet, C., Nicolas, A., Trivin, C., MC, P.-V., Kuttenn, F., and Kelly, P. Increased expression of prolactin receptor gene assessed by quantitative polymerase chain reaction in human breast tumors versus normal breast tissues. Journal of Clinical Endocrinology and Metabolism, 83: 667-674, 1998.

11. Ginsburg, E. and Vonderhaar, B. Prolactin synthesis and secretion by human breast cancer cells. Cancer Research, 55: 2591-2595, 1995.

12. Naylor, M., J, Lockefeer, J., A, Horseman, N., D, and Ormandy, C. J. Prolactin regulates mammary epithelial cell proliferation via autocrine/paracrine mechanism. Endocrine, 20: 111-114, 2003.

13. Bonneterre, J., Mauriac, L., Weber, B., Roche, H., Fargeot, P., Tubiana-Hulin, M., Sevin, M., Chollet, P., and Cappelaere, P. Tamoxifen plus bromocriptine vs. tamoxifen plus placebo in advanced breast cancer: results of a double blind multicenter clinical trial. European Journal of Cancer, 24: 1851-1853, 1988.

14. Anderson, E., Ferguson, J., Morten, H., Shalet, S., Robinson, E., and Howell, A. Serum immunoreactive and bioactive lactogenic hormones in advanced breast cancer patients treated with bromocriptine and octreotide. European Journal of Cancer, 29A: 209-217, 1993.

15. McMurray, R., Weidensaul, D., Allen, S., and Walker, S. Efficacy of bromocriptine in an open label therapeutic trial for systemic lupus erythematosus. Journal of Rheumatology, 22: 2084-2091, 1995.

179 16. Goffin, V., Touraine, P., Pichard, C., Bernichtein, S., and Kelly, P. A. Should prolactin be reconsidered as a therapeutic target in human breast cancer? Molecular and Cellular Endocrinology, 151: 79-87, 1999.

17. Goffin, V., Binart, N., Touraine, P., and Kelly, P. A. Prolactin: The New Biology of an Old Hormone. Annu. Rev. Physiol., 64: 47-67, 2002.

18. Clevenger, C. V., Furth, P. A., Hankinson, S. E., and Schuler, L. A. The Role of Prolactin in Mammary Carcinoma. Endocrine Reviews, 24: 1-27, 2003.

19. Miller, W. and Eberhardt, N. Structure and evolution of the growth hormone gene family. Endocrine Reviews, 4: 97-130, 1983.

20. Boulay, J. and Paul, W. The interleukin-4-related lymphokines and their binding to hematopoietin receptors. Journal of Biological Chemistry, 267: 20525-20528, 1992.

21. Horseman, N. and Yu-Lee, L. Transcriptional regulation by helix bundle peptide hormones: growth hormone, prolactin and hematopoietic cytokines. Endocrine Reviews, 15: 627-649, 1994.

22. Goffin, V., Shiverick, K. T., Kelly, P. A., and Martial, J. A. Sequence-function Relationships Within the Expanding Family of Prolactin, Growth Hormone, Placental Lactogen, and Related Proteins in Mammals. Endocrine Reviews, 17: 385-410, 1996.

23. Niall, H., Hogan, M., Sauer, R., Rosenblum, I., and Greenwood, F. Sequences of pituitary and placental lactogenic and growth hormones: evolution from a primordial peptide by gene reduplication. Proceedings of the National Academy of Science USA, 68: 866-870, 1971.

24. Cooke, N., Coit, D., Shine, J., Baxter, J., and Martial, J. Human prolactin cDNA structural analysis and evolutionary comparisons. Journal of Biological Chemistry, 256: 4007-4016, 1981.

25. Cooke, N. E., Coit, D., Shine, J., Baxter, J., and Martial, J. A. Human Prolactin. The Journal of Biological Chemistry, 256: 4007-4016, 1981.

180 26. Cooke, N., E, Coit, D., Weiner, R., I, Baxter, J., D, and Martial, J. A. Structure of cloned DNA complementary to rat prolactin messenger RNA. The Journal of biological chemistry, 255: 6502-6510, 1980.

27. Owerbach, D., Rutter, W., J, Martial, J., A, Baxter, J., D, and Shows, T. B. Genes for growth hormone, chorionic somatommammotropin, and growth hormones-like gene on chromosome 17 in humans. Science, 209: 289-292, 1980.

28. Miller, W., L, Coit, D., Baxter, J., D, and Martial, J. A. Cloning of bovine prolactin cDNA and evolutionary implications of its sequence. DNA (Mary Ann Liebert Inc), 1: 37-50, 1981.

29. Freeman, M. E., Kanyicska, B., Lerant, A., and Nagy, G. Prolactin: Structure, Function and Regulation of Secretion. Physiological Reviews, 80: 1523-1631, 2000.

30. Walker, W., Fitzpatrick, S., Barrera-Saldana, H., Resendes, D., and Saunders, G. The human placental lactogen gene: structure, function, evolution and transcriptional regulation. Endocrine Reviews, 12: 3165-3328, 1991.

31. Seeburg, P. The human growth hormone gene family nucleotide sequences show recent divergence and predictable polypeptide. DNA, 1: 239-249, 1982.

32. Nicoll, C. S., Mayer, G. L., and Russell, S. M. Structural Features of Prolactins and Growth Hormones That Can Be Related to Their Biological Properties. Endocrine Reviews, 7: 169-203, 1986.

33. Goffin, V., Martial, J. A., and Summers, N. L. Use of a model to understand prolactin and growth hormone specificities. Human prolactin binding sites and specificity, Protein Engineering, 8: 1215-1231, 1995.

34. Bazan, F. and McKay, D. B. Unraveling the Structure of IL-2. Science, Vol. 257: 410-413, 1992.

35. Mott, H. R. and Campbell, I. D. Four-helix bundle growth factors and their receptors: protein-protein interactions. Current Opinion in Structural Biology, 5: 114-121, 1995.

36. Robinson, R. C., Grey, L. M., Staunton, D., Vankelecom, H., Vernallis, A. B., 181 Moreau, J. F., Stuart, D. I., Heath, J. K., Jones, E. Y. The crystal structure and biological function of leukemia inhibitory factor: implications for receptor binding. Cell, 77: 1011-1016, 1994.

37. Walter, M., R, Cook, W., J, Ealick, S., E, Nagabhushan, T., L, Trotta, P., P, and Bugg, C. E. Three-dimensional structure of recombinant human granulocyte- macrophage colony-stimulating factor. Journal of Molecular Biology, 224: 1075-1085, 1992.

38. Chantalat, L., Jones, N.D., Korber, F., Navaza, J., Pavlovsky, A.G., The crystal structure of wild-type growth hormone at 2.5 A resolution. Protein and Peptide Letters, 2: 333-340, 1995.

39. Robinson, R., C, Grey, L., M, Staunton, D., Stuart, D., I, Heath, J., K, and Jones, E. Y. The crystal structure of murine leukemia inhibitory factor. Annals of the New York Academy of Sciences, 762: 179-187; discussion 187, 1995.

40. Robinson, R., C, Grey, L., M, Staunton, D., Vankelecom, H., Vernallis, A., B, Moreau, J., F, Stuart, D., I, Heath, J., K, and Jones, E. Y. The crystal structure and biological function of leukemia inhibitory factor: implications for receptor binding. Cell, 77: 1101-1116, 1994.

41. Cheetham, J. C., Smith, D.M., Aoki, K.H., Stevenson, J.L., Hoeffel, T.J., Syed, R.S., Egrie, J., Harvey, T.S. NMR structure of human erythropoietin and a comparison with its receptor bound conformation. Nature Structural Biology, 5: 861-866, 1998.

42. Riddle, O., Bates, R.W., Dykshorn, S.W., The Preparation, Identification and Assay of Prolactin-A Hormone of the Anterior Pituitary. American Journal of Physiology, 105: 191-216, 1933.

43. Bole-Feysot, C., Goffin, V., Edery, M., Binart, N., and Kelly, P. A. Prolactin (PRL) and its receptor: actions, signal transduction pathways and phenotypes observed in PRL receptor knockout mice. Endocrine reviews, 19: 225-268, 1998.

44. Bern, H. and Nicoli, C. The comparative endocrinology of prolactin. Recent Progress in Hormone Research, 24: 681-720, 1968.

182 45. Cohen, L., Wondisford, F., and Radovick, S. Role of Pit-1 in the gene expression of growth hormone, prolactin, and thyrotropin. Endocrinol Metab Clin North AM, 25: 523-540, 1996.

46. Gonzalez-Parra, S., Chowen, J., Garcia, S., and Argente, J. Ontogeny of pituitary transcription factor-1 (Pit-1), growth hormone (GH) and prolactin (PRL) mRNA levels in male and female rats and the differential expression of Pit-1 in lactotrophs and somatotrophs. Journal of Neuroendocrinology, 8: 211- 225, 1996.

47. Parks, J., Adess, M., and Brown, M. Genes regulating hypothalamic and pituitary development. Acta Paediatr, 86: 28-32, 1997.

48. Sharp, Z. Rat pit-1 stimulates transcription in vitro by influencing preinitiation complex assembly. Biochem Biophys Res Commun, 206: 40-45, 1995.

49. Halmi, N., Parsons, J., Erlandsen, S., and Duello, T. Prolactin and growth hormone cells in the human hypophysis: a study immunoenzyme histochemistry and differential staining. Cell Tissue Res, 158: 497-507, 1975.

50. Baker, B. and Yu, Y. An immunocytochemical study of human pituitary mammotrophes from fetal life to old age. American Journal of Anatomy, 148: 217-240, 1977.

51. Pasteels, J., Gausser, P., Danguy, A., Ectors, F., and Nicoll, C. Morphology of the lactotropes and somatotropes of man and rhesus monkey. Journal of Clinical Endocrinology and Metabolism, 34: 959-967, 1972.

52. Frawley, L. and Boockfor, F. Focusing on hormone release. Nature, 321: 793- 793, 1986.

53. Frawley, L., Boockfor, F., and Hoeffler, J. Identification by plaque assays of a pituitary cell type that secretes both growth hormone and prolactin. Endocrinology, 116: 734-737, 1985.

54. Frawley, L. and Neill, J. A reverse hemolytic plaque assay for microscopic visualization of growth hormone release from individual cells: evidence for somatotrophic heterogeneity. Neuroendocrinology Letters, 39: 484-487, 1984. 183 55. Frawley, S. Mammosomatotropes: current status and possible functions. Trends Endocrinol Metab, 1: 31-34, 1989.

56. Hoeffler, J., Boockfor, F., and Frawley, L. Ontogeny of prolactin cells in neonatal rats: initial prolactin secretors also release growth hormone. Endocrinology, 117: 187-195, 1985.

57. Boockfor, F., Hoeffler, J., and Frawley, L. Estradiol induces a shift in cultured cells that release prolactin or growth hormone. Am J Physiol Endocrinol Metab, 250: E100-E103, 1986.

58. Faria, T., N, Deb, S., Kwok, S., C, Talamantes, F., and Soares, M. J. Ontogeny of placental lactogen-I and placental lactogen-II expression in the developing rat placenta. Developmental Biology, 141: 279-291, 1990.

59. Faria, T., N, Deb, S., Kwok, S., C, Vandeputte, M., Talamantes, F., and Soares, M. J. Transplantable rat choriocarcinoma cells express placental lactogen: identification of placental lactogen-I immunoreactive protein and messenger ribonucleic acid. Endocrinology, 127: 3131-3137, 1990.

60. Ogren, L. and Talamantes, F. Prolactins of pregnancy and their cellular source. International Review of Cytology, 112: 1-65, 1988.

61. Sinha, Y. N. Structural Variants of Prolactin: Occurrence and Physiological Significance. Endocrine Reviews, 16: 354-369, 1995.

62. Greep, R., O, Knobil, E., Wilhelmi, A., E, and Wolf, R. C. Effect of a primate pituitary growth hormone preparation on nitrogen metabolism in the hypophysectomized rhesus monkey. Endocrinology, 60: 166-168, 1957.

63. Knobil, E., Best, G., R, and Goodman, H. M. The hypoglycemic action of simian and bovine growth hormone in hypophysectomized rhesus monkeys. Endocrinology, 68: 723-725, 1961.

64. Knobil, E., Kostyo, J., L, Wolf, R., C, and Greep, R. O. Lack of competitive inhibition between beef and monkey growth hormones in rhesus monkeys. Science, 127: 1394, 1958.

184 65. Knobil, E., Morse, A., Wolf, R., C, and Greep, R. O. The action of bovine, porcine and simian growth hormone preparations on the costochondral junction in the hypophysectomized rhesus monkey. Endocrinology, 62: 348-354, 1958.

66. Peckham, W., D, Hotchkiss, J., Knobil, E., and Nicoll, C. S. Prolactin activity of homogeneous primate growth hormone preparations. Endocrinology, 82: 1247- 1248, 1968.

67. Kaye, P., L and Harvey, M. B. The role of growth factors in preimplantation development. Progress in Growth Factor Research, 6: 1-24, 1995.

68. Owerbach, D., Rutter, W., Cooke, N., Martial, J., and Shows, T. The prolactin gene is located on chromosome 6 in humans. Science, 212: 815-816, 1981.

69. Truong, A., Duez, C., Belayew, A., Renard, A., Pictet, R., Bell, G., and Martial, J. Isolation and charcaterization of the human prolactin gene. EMBO Journal, 3: 429-437, 1984.

70. Berwaer, M., Monget, P., Peers, B., Mathy-Hartert, M., Bellefroid, E., Davis, J., Belayew, A., and Martial, J. Multihormonal regulation of the human prolactin gene expression from 5000 bp of its upstream sequence. Molecular and Cellular Endocrinology, 80: 53-64, 1991.

71. Berwaer, M., Martial, J., and Davis, J. Characterization of an up-stream promoter directing extrapituitary expression of the prolactin gene. Molecular Endocrinology, 8: 635-642, 1994.

72. Shaw-Bruha, C., Pirrucell, S., and Shull, J. Expression of the prolactin gene in normal and neoplastic human breast tissues and human mammary cell lines: prooter usage and alternative mRNA splicing. Breast Cancer Research and Treatment, 44: 243-253, 1997.

73. Ben-Jonathan, N., Mershon, J. L., Allen, D. L., and Steinmetz, R. W. Extrapituitary Prolactin: Distribution, Regulation, Functions, and Clinical Aspects. Endocrine Reviews, 17: 639-669, 1996.

74. Clapp, C. and De La Escalera, G. Prolactins: novel regulators of angiogenesis. News Physiol Sci 231-237, 1997.

185 75. Clapp, C. and Weiner, R. A specific, high affinity, saturable binding site for the 16-kilodalton fragment of prolactin on capillary endothelial cells. Endocrinology, 130: 1380-1386, 1992.

76. Li, C. H. Studies on pituitary lactogenic hormone. The primary structure of the porcine hormone. International Journal of Peptide and Protein Research, 8: 205- 224, 1976.

77. Li, C., H, Dixon, J., S, Lo, T., B, Schmidt, K., D, and Pankov, Y. A. Studies on pituitary lactogenic hormone. The primary structure of the sheep hormone. Archives of Biochemistry and Biophysics, 141: 705-737, 1970.

78. Wallis, M. The primary structure of bovine prolactin. FEBS Letters, 44: 205- 208, 1974.

79. Shome, B. and Parlow, A. F. Human pituitary prolactin (hPRL): the entire linear amino acid sequence. The Journal of Clinical Endocrinology and Metabolism, 45: 1112-1115, 1977.

80. Kohmoto, K., Tsunasawa, S., and Sakiyama, F. Complete amino acid sequence of mouse prolactin. European Journal of Biochemistry, 138: 227-237, 1984.

81. Emanuele, N., Jurgens, J., Halloran, M., Tentler, J., Lawrence, A., and Kelley, M. The rat prolactin gene is expressed in brain tissue: detection of normal and alternatively spliced prolactin messenger RNA. Molecular Endocrinology, 6: 35-42, 1992.

82. Wilson, D., Emanuele, N. I., Jurgens, J., and Kelley, M. Prolactin message in brain and pituitary of adult male rats is identical: PCR cloning and sequencing of hypothalamic prolactin cDNA from intact and hypophysectomized adult male rats. Endocrinology, 131: 2488-2490, 1992.

83. Ferrara, N., Clapp, C., Weiner, R., The 16K Fragment of Prolactin Specifically Inhibits Basal or Fibroblast Growth Factor Stimulated Growth of Capillary Endothelial Cells. Endocrinology, 129: 896-900, 1991.

84. Clapp, C., Sears, P.S., Nicoll, C.S., Binding Sutdies with Intact Rat Prolactin and 16K Fragment of the Hormone. Endocrinology, 125: 1054-1059, 1989.

85. Clapp, C., Martial, J.A., Guzman, R.C., Rentier-Delrue, F., Weiner, R., The 16- 186 Kilodalton N-Terminal Fragment of Human Prolactin Is a Potent Inhibitor of Angiogenesis. Endocrinology, 133: 1292-1299, 1993.

86. Clapp, C., Torner, L., Gutierrez-Ospina, G., Alcantara, E., Lopez-Gomez, F., Nagano, M., Kelly, P., Mejia, S., Morales, M., and Martinez De La Escalara, G. The prolactin gene is expressed in the hypothalamic-neurohypophyseal system and the protein is processed into a 14-kDa fragment with activity like 16-kDa prolactin. Proceedings of the National Academy of Science USA, 91: 10384- 10388, 1994.

87. Ultsch, M., H, Somers, W., Kossiakoff, A., A, and de Vos, A. M. The crystal structure of affinity-matured human growth hormone at 2 A resolution. Journal of Molecular Biology, 236: 286-299, 1994.

88. Elkins, P. A., Christinger, H.W., Sandowski, Y., Sakal, E., Gertler, A., De Vos, A.M., Kossiakoff, A.A., Ternary Complex between Placental Lactogen and the Extracellular Domain of the Prolactin Receptor. Nature Structural Biology, 7: 808-815, 2000.

89. De Vos, A., Ultsch, M., and Kossiakoff, A. Human Growth Hormone and Extracellular Domain of its Receptor: Crystal Structure of the Complex. Science, 255: 306-312, 1992.

90. Abdel-Meguid, S., S, Shieh, H., S, Smith, W., W, Dayringer, H., E, Violand, B., N, and Bentle, L. A. Three-dimensional structure of a genetically engineered variant of porcine growth hormone. Proceedings of the National Academy of Sciences of the United States of America, 84: 6434-6437, 1987.

91. Bewley, T. and Li, C. Circular dichroism studies on human pituitary growth hormone and ovine pituitary lactogenic hormone. Biochemistry, 11: 884-888, 1972.

92. Koshland, D. E., Nemethy, G., Filmer, D., Comparison of Experimental Binding Data and Theoretical Models in Protein Containing Subunits. Biochemistry, 5: 365-385, 1966.

93. Yu-Lee, L. Molecular actions of prolactin in the immune system. Proc Soc Exp Biol Med, 215: 35-52, 1997.

94. Fuh, G., Colosi, P., Wood, W., and Wells, J. Mechanism-based design of 187 prolactin receptor antagonists. Journal of Biological Chemistry, 268: 5376-5381, 1993.

95. Goffin, V., Norman, M., and Martial, J. Alanine-Scanning Mutagenesis of Human Prolactin: Importance of the 58-74 Region for Bioactivity. Molecular Endocrinology, 6: 1381-1392, 1992.

96. Goffin, V., Struman, I., Mainfroid, V., Kinet, S., and Martial, J. Evidence for a second receptor binding site on human prolactin. Journal Biological Chemistry, 269: 32598-32606, 1994.

97. Gertler, A., Grosclaude, J., Strasburger, C. J., Nir, S., and Djiane, J. Real-time Kinetic Measurements of the Interactions between Lactogenic Hormones and Prolactin-Receptor Extracellular Domains from Several Species Support the Model of Hormone-induced Transient Receptor Dimerization. The Journal of Biological Chemistry, 271: 24482-24491, 1996.

98. Sivaprasad, U., Canfield, J. M., and Brooks, C. L. Mechanism for Ordered Receptor Binding by Human Prolactin. Biochemistry, 2004.

99. Clackson, T. and Wells, J. A hot spot of binding energy in a hormone-receptor interface. Science, 267: 383-386, 1995.

100. Duda, K. M. and Brooks, C. L. Human Growth Hormone Site 2 Lactogenic Activity Requires a Distant Tyrosine 164. FEBS Letters, 449: 120-124, 1999.

101. Dennis, M., S, Eigenbrot, C., Skelton, N., J, Ultsch, M., H, Santell, L., Dwyer, M., A, O'Connell, M., P, and Lazarus, R. A. Peptide exosite inhibitors of factor VIIa as anticoagulants. Nature, 404: 465-470, 2000.

102. Stroppolo, M., E, Pesce, A., Falconi, M., O'Neill, P., Bolognesi, M., and Desideri, A. Single mutation at the intersubunit interface confers extra efficiency to Cu, Zn superoxide dismutase. FEBS Letters, 483: 17-20, 2000.

103. Boutin, J.-M., Jolicoeur, C., Okamura, H., Gagnon, J., Edery, M., Djiane, J., Kelly, P.A., Cloning and expression of the rat prolactin receptor, a member of the growth hormone/prolactin receptor gene family. Cell, 53: 69-77, 1988.

104. Bazan, J. F. A novel family of growth factor receptors: a common binding 188 domain in the growth hormone, prolactin, erythropoietin and IL-6 receptors, and the p75 IL-2 receptor beta-chain. Biochemical and Biophysical Research Communications, 164: 788-795, 1989.

105. Bazan, J. Haematopoeitic receptors and helical cytokines. Immunology Today, 11: 350-354, 1990.

106. Thoreau, E., Petridou, B., Kelly, P., A, Djiane, J., and Mornon, J. P. Structural symmetry of the extracellular domain of the cytokine/growth hormone/prolactin receptor family and interferon receptors revealed by hydrophobic cluster analysis. FEBS Letters, 282: 26-31, 1991.

107. Kelly, P., A, Djiane, J., Banville, D., Ali, S., Edery, M., and Rozakis, M. The growth hormone/prolactin receptor gene family. Oxford Surveys on Eukaryotic Genes, 7: 29-50, 1991.

108. Kelly, P., A, Djiane, J., Postel-Vinay, M., C, and Edery, M. The prolactin/growth hormone receptor family. Endocrine Reviews, 12: 235-251, 1991.

109. Kelly, P., Ali, S., Rozakis, M., Goujon, L., Nagano, M., Pellegrini, I., Gould, D., Djiane, J., Edery, M., Finidori, J., and al, e. The Growth Hormone/ Prolactin Receptor Family. Recent Progress in Hormone Research, 48: 123-164, 1993.

110. Wells, J., A and de Vos, A. M. Hematopoietic receptor complexes. Annual Review of Biochemistry, 65: 609-634, 1996.

111. Hu, Z.-Z., Zhuang, L., Meng, J., Leondries, M., Dufau, M.L., The human prolactin receptor gene structure and alternative promoter utilization: the generic promoter hPIII and a novel human promoter hPN. The Journal of Clinical Endocrinology and Metabolism, 84: 1153-1156, 1999.

112. Ormandy, C., J, Binart, N., Helloco, C., and Kelly, P. A. Mouse prolactin receptor gene: genomic organization reveals alternative promoter usage and generation of isoforms via alternative 3'-exon splicing. DNA and Cell Biology, 17: 761-770, 1998.

113. Moldrup, A., Ormandy, C., Nagano, M., Murthy, K., Banville, D., Tronche, F.,

189 and Kelly, P. A. Differential promoter usage in prolactin receptor gene expression: hepatocyte nuclear factor 4 binds to and activates the promoter preferentially active in the liver. Molecular Endocrinology (Baltimore Md), 10: 661-671, 1996.

114. Hu, Z., Z, Zhuang, L., Meng, J., and Dufau, M. L. Transcriptional regulation of the generic promoter III of the rat prolactin receptor gene by C/EBPbeta and Sp1. The Journal of Biological Chemistry, 273: 26225-26235, 1998.

115. Hu, Z. Z., Zhuang, L., Dufau, M.L., In: The Endocrine Society's 81st Annual Meeting, San Diego, CA, June 12-14, 1999.

116. Hu, Z.-Z., Meng, J., and Dufau, M. L. Isolation and Characterization of Two Novel Forms of the Human Prolactin Receptor Generated by Alternative Splicing of a Newly Identified Exon 11. Journal Biological Chemistry, 276: 41086-41094, 2001.

117. Boutin, J., Edery, M., Shirota, M., Jolicoeur, C., Lesueur, L., Ali, S., Gould, D., Djiane, J., and Kelly, P. Identification of a cDNA encoding a long form of prolactin receptor in human hepatoma and breast cancer cells. Molecular Endocrinology, 3: 1455-1461, 1989.

118. Kline, J. B., Rycyzyn, M. A., and Clevenger, C. V. Characterization of a Novel and Functional Human Prolactin Receptor Isoform ({Delta}S1PRLr) Containing Only One Extracellular Fibronectin-Like Domain. Molecular Endocrinology, 16: 2310-2322, 2002.

119. Somers, W., Ultsch, M., De Vos, A., M, and Kossiakoff, A. A. The X-ray structure of a growth hormone-prolactin receptor complex. Nature, 372: 478- 481, 1994.

120. Kline, J. B., Moore, D. J., and Clevenger, C. V. Activation and Association of the Tec Tyrosine Kinase with the Human Prolactin Receptor: Mapping of a Tec/Vav1-Receptor Binding Site. Molecular Endocrinology, 15: 832-841, 2001.

121. Lebrun, J., Ali, S., Sofer, L., Ullrich, A., and Kelly, P. Prolactin-induced proliferation of Nb2 cells involves tyrosine phosphorylation of the prolactin receptor and its associated tyrosine kinase JAK2. Journal of Biological Chemistry, 269: 14021-14026, 1994.

190 122. Goupille, O., Daniel, N., Bignon, C., Jolivet, G., Djiane, J., Prolactin signal transduction to milk protein genes: carboxy-terminal part of the prolactin receptor and its tyrosine phosphorylation are not obligatory for JAK2 and STAT5 activation. Molecular and Cellular Endocrinology, 127: 155-169, 1997.

123. Horseman, N. D. (ed.) Prolactin: Kluwer Academic Publishers, 2001.

124. Watson, C. and Miller, W. Elevated levels of members of the STAT family of transcription facrors in breast carinoma nuclear extracts. British Journal of Cancer, 71: 840-844, 1995.

125. Bowman, T., Garcia, R., Turkson, J., and Jove, R. STATs in oncogenesis. Oncogene, 19: 2474-2488, 2000.

126. Brockman, J., L, Schroeder, M., D, and Schuler, L. A. PRL activates the cyclin D1 promoter via the Jak2/Stat pathway. Molecular Endocrinology (Baltimore Md), 16: 774-784, 2002.

127. Josefsberg, Z., Posner, B.I., Patel, B., Bergeron, J.J.M., The uptake of prolactin into female rat liver. The Journal of Biological Chemistry, 254: 209-214, 1979.

128. Suard, Y. M., Kraehenbuhl, J. P., and Aubert, M. L. Dispersed mammary epithelial cells. Receptors of lactogenic hormones in virgin, pregnant, and lactating rabbits. The Journal of Biological Chemistry, 254: 10466-10475, 1979.

129. Kane, S., Raymond, M.N., Dusanter-Fourt, I., Houdebine, L.M., Djiane, J., Ollivier-Bousquet, M., Endocytose de la prolactine dans la cellule epitheliale mammaire: effets des agents lysosomotropes et des inhibiteurs de la transglutaminase. European Journal of Cell Biology, 30: 244, 1983.

130. Beck, M., T, Peirce, S., K, and Chen, W. Y. Regulation of bcl-2 gene expression in human breast cancer cells by prolactin and its antagonist, hPRL-G129R. Oncogene, 21: 5047-5055, 2002.

131. Schroeder, M., D, Brockman, J., L, Walker, A., M, and Schuler, L. A. Inhibition of prolactin (PRL)-induced proliferative signals in breast cancer cells by a molecular mimic of phosphorylated PRL, S179D-PRL. Endocrinology, 144: 5300-5307, 2003.

191 132. Bernichtein, S., Kinet, S., Jeay, S., Llovera, M., Madern, D., Martial, J. A., Kelly, P. A., and Goffin, V. S179D-Human PRL, a Pseudophosphorylated Human PRL Analog, Is an Agonist and Not an Antagonist. Endocrinology, 142: 3950-3963, 2001.

133. Robbins Pathologic Basis of Disease, 6th edition: W.B. Saunders Company in, 1999.

134. Castro-Alcaraz, S., Miskolci, V., Kalasapudi, B., Davidson, D., and Vancurova, I. NF-{kappa}B Regulation in Human Neutrophils by Nuclear I{kappa}B{alpha}: Correlation to Apoptosis. J Immunol, 169: 3947-3953, 2002.

135. Majno, G. and Joris, I. Apoptosis, Oncosis, and Necrosis An Overview of Cell Death. American Journal of Pathology, 146: 3-15, 1995.

136. Cohen, G. M. Caspaces: the executioners of apoptosis. Biochemistry Journal, 326: 1-16, 1997.

137. Fischer, U., Janicke, R., and Schultze-Osthoff, K. Many cuts to ruin: a comprehensive update of caspace substrates. Cell Death and Differentiation, 10: 76-100, 2003.

138. Nagata, S. Apoptosis by Death Factor. Cell, 88: 355-365, 1997.

139. Budihardjo, I., Oliver, H., Lutter, M., Luo, X., and Wang, X. Biochemical Pathways of Caspace Activation During Apoptosis. Annu Rev Cell Dev Biol, 15: 269-290, 1999.

140. Granville, D. J., Carthy, C. M., Hunt, D. W. C., and McManus, B. M. Apoptosis: Molecular Aspects of Cell Death and Disease. Laboratory Investigation, 78: 893-913, 1998.

141. Alnemri, E. S. Mammalian Cell Death Proteases: A Family of Highly Conserved Aspartate Specific Cysteine Proteases. Journal of Cellular Biochemistry, 64: 33-42, 1997.

192 142. Cryns, V. and Yuan, J. Proteases to die for. Genes and Development, 12: 1551- 1570, 1998.

143. Zangemeister-Wittke, U. and Simon, H.-U. Apoptosis - Regulation and clinical implications. Cell Death and Differentiation, 8: 537-544, 2001.

144. Current Protocols in Molecular Biology: John Wiley and Sons, Inc, 1995.

145. Sambrook, J., Fritsch, E. F., and Maniatis, T. Molecular Cloning: A Laboratory Handbook, Vol. 1,2,&3. USA: Cold Spring Harbor Laboratory Press, 1989.

146. Peterson, F. C., Anderson, P. J., Berliner, L. J., and Brooks, C. L. Expression, Folding, and Characterization of Small Proteins with Increasing Disulfide Complexity by a pT7-7-Derived Phagemid. Protein Expression and Purification, 15: 16-23, 1999.

147. Sanger, F., Nicklen, S., Coulson, A.R., DNA Sequencing with Chain- Terminating Inhibitors. Proceedings of the National Academy of Sciences, 74: 5463-5467, 1977.

148. Turchin, A. and Lawler, J. J. The primer generator: a program that facilitates the selection of oligonucleotides for site-directed mutagenesis. Biotechniques, 26: 672-676, 1999.

149. Kunkel, T., Bebenek, K., and McClary, J. Efficient Site- Directed Mutagenesis Using Uracil-Containing DNA. Methods in Enzymology, 204: 125-139, 1991.

150. Smith, P., Krohn, R., Hermanson, G., Mallia, A., Gartner, F., Provenzano, M., Fujimoto, E., Goeke, N., Olson, B., and Klenk, D. Measurement of protein using bicinchoninic acid. Analytical Biochemistry, 150: 76-85, 1987.

151. Laemmli, U. Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature, 227: 680-685, 1970.

152. Gout, P. W., Beer, C.T., Noble, R.L., Prolactin-stimulated growth of cell cultures established from malignant Nb rat lymphomas. Cancer Research, 40: 2433-2436, 1980.

193 153. Gout, P., W, Noble, R., L, and Beer, C. T. Cultured Nb rat lymphoma cells in endocrine and cancer research. Biochemistry and Cell Biology = Biochimie et Biologie Cellulaire, 64: 659-666, 1986.

154. Shiu, R., P, Elsholtz, H., P, Tanaka, T., Friesen, H., G, Gout, P., W, Beer, C., T, and Noble, R. L. Receptor-mediated mitogenic action of prolactin in a rat lymphoma cell line. Endocrinology, 113: 159-165, 1983.

155. Ali, S., Pellegrini, I., and Kelly, P. A prolactin-dependent immune cell line (Nb2) expresses a mutant form of prolactin receptor. Journal of Biological Chemistry, 266: 20110-20117, 1991.

156. O'Neal, K., D and Yu-Lee, L. Y. Differential signal transduction of the short, Nb2, and long prolactin receptors. Activation of interferon regulatory factor-1 and cell proliferation. The Journal of Biological Chemistry, 269: 26076-26082, 1994.

157. Sasik R, W. C., Corbeil J. Microarray truths and consequences. Journal of Molecular Endocrinology, 33: 1-9, 2004.

158. Schadt, E., E, Li, C., Su, C., and Wong, W. H. Analyzing high-density oligonucleotide gene expression array data. Journal of Cellular Biochemistry, 80: 192-202, 2000.

159. Dahlquist, K., D, Salomonis, N., Vranizan, K., Lawlor, S., C, and Conklin, B. R. GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nature Genetics, 31: 19-20, 2002.

160. Doniger, S., W, Salomonis, N., Dahlquist, K., D, Vranizan, K., Lawlor, S., C, and Conklin, B. R. MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biology, 4: R7, 2003.

161. Eisen, M., B, Spellman, P., T, Brown, P., O, and Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America, 95: 14863-14868, 1998.

162. Chiang, D., Y, Brown, P., O, and Eisen, M. B. Visualizing associations between genome sequences and gene expression data using genome-mean expression profiles. Bioinformatics (Oxford England), 17 Suppl 1: S49-55, 2001.

194 163. Wickert, L., Steinkruger, S., Abiaka, M., Bolkenius, U., Purps, O., Schnabel, C., and Gressner, A. M. Quantitative monitoring of the mRNA expression pattern of the TGF-beta-isoforms (beta 1, beta 2, beta 3) during transdifferentiation of hepatic stellate cells using a newly developed real-time SYBR Green PCR. Biochemical and Biophysical Research Communications, 295: 330-335, 2002.

164. Shiu, R. P. C. and Paterson, J. A. Alteration of Cell Shape, Adhesion, and Lipid Accumulation in Human Breast Cancer Cells (T47D) by Human Prolactin and Growth Hormone. Cancer Research, 44: 1178-1186, 1984.

165. Zamzami, N., Marchetti, P., Castedo, M., Zanin, C., Vayssiere, J., L, Petit, P., and XKroemer, G. Reduction in mitochondrial potential constitutes an early irreversible step of programmed lymphocyte death in vivo. The Journal of Experimental Medicine, 181: 1661-1672, 1995.

166. Castedo, M., Ferri, K., Roumier, T., Metivier, D., Zamzami, N., and Kroemer, G. Quantitation of mitochondrial alterations associated with apoptosis. Journal of Immunological Methods, 265: 39-47, 2002.

167. Douglas, A., M, Grant, S., L, Goss, G., A, Clouston, D., R, Sutherland, R., L, and Begley, C. G. Oncostatin M induces the differentiation of breast cancer cells. International Journal of Cancer, Journal International du Cancer, 75: 64- 73, 1998.

168. Hutt, J.,A and DeWille, J. W. Oncostatin M induces growth arrest of mammary epithelium via a CCAAT/enhancer-binding protein delta-dependent pathway. Molecular Cancer Therapeutics, 1: 601-610, 2002.

169. Bidere, N. and Senik, A. Caspace-independent apoptotic pathways in T lymphocytes: A minireview. Apoptosis, 6: 371-375, 2001.

170. Dragovich, T., Rudin, C. M., and Thompson, C. B. Signal transduction pathways that regulate cell survival and cell death. Oncogene, 17: 3207-3213, 1998.

171. Bernichtein, S., Kayser, C., Dillner, K., Moulin, S., Kopchick, J., J, Martial, J., A, Norstedt, G., Isaksson, O., Kelly, P., A, and Goffin, V. Development of pure prolactin receptor antagonists. The Journal of Biological Chemistry, 278: 35988-35999, 2003.

195 172. Stal, O., Perez-Tenorio, G., Akerberg, L., Olsson, B., Nordenskjold, B., Skoog, L., and Rutqvist, L. E. Akt kinases in breast cancer and the results of adjuvant therapy. Breast Cancer Research : BCR, 5: R37-44, 2003.

173. Mayo, L., D and Donner, D. B. A phosphatidylinositol 3-kinase/Akt pathway promotes translocation of Mdm2 from the cytoplasm to the nucleus. Proceedings of the National Academy of Sciences of the United States of America, 98: 11598-11603, 2001.

174. Kauffmann-Zeh, A., Rodriguez-Viciana, P., Ulrich, E., Gilbert, C., Coffer, P., Downward, J., and Evan, G. Suppression of c-Myc-induced apoptosis by Ras signalling through PI(3)K and PKB. Nature, 385: 544-548, 1997.

175. Tessier, C., Prigent-Tessier, A., Ferguson-Gottschall, S., Gu, Y., and Gibori, G. PRL antiapoptotic effect in the rat decidua involves the PI3K/protein kinase B- mediated inhibition of caspase-3 activity. Endocrinology, 142: 4086-4094, 2001.

176. Perou, C., M, Jeffrey, S., S, van de Rijn, M., Rees, C., A, Eisen, M., B, Ross, D., T, Pergamenschikov, A., Williams, C., F, Zhu, S., XLee, J., C, Lashkari, D., Shalon, D., Brown, P., O, and Botstein, D. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proceedings of the National Academy of Sciences of the United States of America, 96: 9212-9217, 1999.

177. Ross, D., T, Scherf, U., Eisen, M., B, Perou, C., M, Rees, C., Spellman, P., Iyer, V., Jeffrey, S., S, Van de Rijn, M., Waltham, M., Pergamenschikov, A., Lee, J., C, Lashkari, D., Shalon, D., Myers, T., G, Weinstein, J., N, Botstein, D., and Brown, P. O. Systematic variation in gene expression patterns in human cancer cell lines. Nature Genetics, 24: 227-235, 2000.

178. Perou, C., M, Sorlie, T., Eisen, M., B, van de Rijn, M., Jeffrey, S., S, Rees, C., A, Pollack, J., R, Ross, D., T, Johnsen, H., Akslen, L., A, Fluge, O., Pergamenschikov, A., Williams, C., Zhu, S., XLonning, P., E, Borresen-Dale, A., L, Brown, P., O, and Botstein, D. Molecular portraits of human breast tumours. Nature, 406: 747-752, 2000.

179. Henshall, S., M, Afar, D. E., H, Hiller, J., Horvath, L., G, Quinn, D., I, Rasiah, K., K, Gish, K., Willhite, D., Kench, J., G, Gardiner-Garden, M., Stricker, P., D, Scher, H., I, Grygiel, J., J, Agus, D., B, Mack, D., H, and Sutherland, R. L. Survival analysis of genome-wide gene expression profiles of prostate cancers identifies new prognostic targets of disease relapse. Cancer Research, 63: 4196- 4203, 2003.

196 180. Sorlie, T., Perou, C., M, Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M., B, van de Rijn, M., Jeffrey, S., S, Thorsen, T., Quist, H., Matese, J., C, Brown, P., O, Botstein, D., Eystein Lonning, P., and Borresen-Dale, A. L. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proceedings of the National Academy of Sciences of the United States of America, 98: 10869-10874, 2001.

181. Pusztai, L., Ayers, M., Stec, J., Clark, E., Hess, K., Stivers, D., Damokosh, A., Sneige, N., Buchholz, T., A, Esteva, F., J, Arun, B., Cristofanilli, M., Booser, D., Rosales, M., Valero, V., Adams, C., Hortobagyi, G., N, and Symmans, W. F. Gene expression profiles obtained from fine-needle aspirations of breast cancer reliably identify routine prognostic markers and reveal large-scale molecular differences between estrogen-negative and estrogen-positive tumors. Clinical cancer research : an official journal of the American Association for Cancer Research, 9: 2406-2415, 2003.

182. Ciro, M., Bracken, A., P, and Helin, K. Profiling cancer. Current Opinion in Cell Biology, 15: 213-220, 2003.

183. Jacobsen, B., M, Richer, J., K, Sartorius, C., A, and Horwitz, K. B. Expression profiling of human breast cancers and gene regulation by progesterone receptors. Journal of Mammary Gland Biology and Neoplasia, 8: 257-268, 2003.

184. Bertucci, F., Viens, P., Tagett, R., Nguyen, C., Houlgatte, R., and Birnbaum, D. DNA arrays in clinical oncology: promises and challenges. Laboratory Investigation; a journal of technical methods and pathology, 83: 305-316, 2003.

185. Gass, S., Harris, J., Ormandy, C., and Brisken, C. Using gene expression arrays to elucidate transcriptional profiles underlying prolactin function. Journal of Mammary Gland Biology and Neoplasia, 8: 269-285, 2003.

186. O'Rourke, J., P, Newbound, G., C, Hutt, J., A, and DeWille, J. CCAAT/enhancer-binding protein delta regulates mammary epithelial cell G0 growth arrest and apoptosis. The Journal of Biological Chemistry, 274: 16582- 16589, 1999.

187. Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., and Speleman, F. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome biology, 3: Research 0034, 2002.

197 188. Goidin, D., Mamessier, A., Staquet, M., J, Schmitt, D., and Berthier-Vergnes, O. Ribosomal 18S RNA prevails over glyceraldehyde-3-phosphate dehydrogenase and beta-actin genes as internal standard for quantitative comparison of mRNA levels in invasive and noninvasive human melanoma cell subpopulations. Analytical Biochemistry, 295: 17-21, 2001.

189. Aerts, J., L, Gonzales, M., I, and Topalian, S. L. Selection of appropriate control genes to assess expression of tumor antigens using real-time RT-PCR. BioTechniques, 36: 84-86, 88, 90, 2004.

190. Gianfrancesco, F., Esposito, T., Ciccodicola, A., D'Esposito, M., Mazzarella, R., D'Urso, M., and Forabosco, A. Molecular cloning and fine mapping of API5L1, a novel human gene strongly related to an antiapoptotic gene. Cytogenetics and Cell Genetics, 84: 164-166, 1999.

191. Van den Berghe, L., Laurell, H., Huez, I., Zanibellato, C., Prats, H., and Bugler, B. FIF [fibroblast growth factor-2 (FGF-2)-interacting-factor], a nuclear putatively antiapoptotic factor, interacts specifically with FGF-2. Molecular Endocrinology (Baltimore Md), 14: 1709-1724, 2000.

192. Chau, B., N, Cheng, E., H, Kerr, D., A, and Hardwick, J. M. Aven, a novel inhibitor of caspase activation, binds Bcl-xL and Apaf-1. Molecular Cell, 6: 31- 40, 2000.

193. Ding, G.-R., Honda, N., Nakahara, T., Tian, F., Yoshida, M., Hirose, H., and Miyakoshi, J. Radiosensitization by inhibition of IkappaB-alpha phosphorylation in human glioma cells. Radiation Research, 160: 232-237, 2003.

194. Myal, Y., Gregory, C., Wang, H., Hamerton, J., L, and Shiu, R. P. The gene for prolactin-inducible protein (PIP), uniquely expressed in exocrine organs, maps to chromosome 7. Somatic Cell and Molecular Genetics, 15: 265-270, 1989.

195. Murphy, L., Tsuyuki, D., Myal, Y., and Shiu, R. Isolation and sequencing of a cDNA clone for a prolactin-inducible protein (PIP). Regulation of PIP gene expression in the human breast cancer cell line, T-47D. J. Biol. Chem., 262: 15236-15241, 1987.

196. Shiu, R., P and Iwasiow, B. M. Prolactin-inducible proteins in human breast cancer cells. The Journal of Biological Chemistry, 260: 11307-11313, 1985.

198 197. Myal, Y., Iwasiow, B., Cosby, H., Yarmill, A., Blanchard, A., Tsuyuki, D., Fresnoza, A., Duckworth, M., L, and Shiu, R. P. Analysis of tissue- and hormone-specific regulation of the human prolactin-inducible protein/gross cystic disease fluid protein-15 gene in transgenic mice. Journal of Molecular Endocrinology, 21: 217-223, 1998.

198. Clark, J., W, Snell, L., Shiu, R., P, Orr, F., W, Maitre, N., Vary, C., P, Cole, D., J, and Watson, P. H. The potential role for prolactin-inducible protein (PIP) as a marker of human breast cancer micrometastasis. British Journal of Cancer, 81: 1002-1008, 1999.

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