Prosthetic Antigen Receptors As a Platform for Solid Tumor Immunotherapy

PROSTHETIC ANTIGEN RECEPTORS AS A PLATFORM FOR SOLID TUMOR IMMUNOTHERAPY

A DISSERTATION SUBMITTED TO THE FACULTY OF UNIVERSITY OF MINNESOTA BY

Jacob Richard Petersburg

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

ADVISOR: Dr. Carston R Wagner

December, 2017

The following dissertation may be an individual work, but it couldn’t have been accomplished without the help, support and guidance of several individuals. First and foremost, I would like to thank Dr. Carston Wagner for instilling in me the necessary qualities to be a good scientist and researcher. His infectious enthusiasm and unbreakable optimism have been a significant driving force throughout my graduate career. I would also like to thank my committee members, Dr. Daniel Harki, Dr. Barry Finzel, and Dr.

William Pomerantz for their support in preparing and completing this dissertation work.

I would like to acknowledge all the past and current members of the Wagner

Laboratory for their help on my projects. The opportunity to learn from and work with everyone over the last several years has been an honor. Specifically, I would like to thank

Dr. Kari Gabrielse, Dr. Amit Ganger and Dr. Sidath Kumarapperuma for their direction and mentorship when I first joined the lab. I would also like to thank all the members of the Fife lab, especially Dr. Brian Fife and Dr. Justin Spanier, who showed me how much there was to learn in the field of Immunology. I need to give a big thanks to my fellow graduate students and colleagues at the University of Minnesota. I would especially like to thank Cody Lensing, Trent West, Cliff Csizmar for always being there to either celebrate or grab a drink when the time required.

Lastly, I would like to thank all my friends and family who’ve supported me over the last 5 years. I would like to thank my girlfriend Tenley Brown for her endless support and patience as I finished up my Ph.D. I would like to thank my siblings, Brandon and

i Steph, for always keeping me grounded and motivated. Finally, I would like to thank my mother and father, Sheryl and Rick, for their unwavering love and support while providing me with every opportunity for success throughout all the stages of my life.

ii DEDICATION

This dissertation is dedicated to my parents, Sheryl and Rick, who have never failed to encourage me in life and inspired me to become the person I am today. I am truly grateful

for everything you have done.

iii ABSTRACT

The ability to engineer and reprogram cell surfaces has significant potential for enabling the use of cell based therapies in cancer treatment. Unfortunately, a majority of current strategies utilize either genetic engineering or chemical modifications which have a number of significant drawbacks. To address these concerns our lab developed Prosthetic

Antigen Receptors (PARs), a non-genetic system, to direct selective cell-cell interactions.

PARs are formed by engineering fusion proteins that contain a scFv fused to two E. Coli dihydrofolate reductase (DHFR2) molecules which spontaneously assemble into octomeric chemically self-assembled nanorings (CSANs) upon the addition of a chemical dimerizer, bis-methotrexate (Bis-MTX).

This thesis provides the field with foundational work addressing the functional effects of PARs in a solid tumor model, both in vitro and in vivo. Chapter 2 initially addresses the in vivo stability, circulation and tissue distribution of CSANs using a radiolabeled construct affording the direct visualization of in vivo tissue localization and ex vivo organ biodistribution by microPET/CT imaging and tissue-based gamma counting, respectively. As anticipated, CSANs displayed an in vivo profile between that of rapidly clearing small molecules and slow clearing antibodies.

In Chapter 3 we discuss both the in vitro and in vivo development of anti-EpCAM

PARs which are then applied to an in vivo orthotopic Breast Cancer Model. Our results demonstrated that anti-EpCAM/anti-CD3 PARs were found to stably bind T-cells for >4 days, and treating EpCAM+ MCF-7 breast cancer cells with anti-EpCAM/anti-CD3 PAR- functionalized T-cells resulted in the induction of IL-2, IFN-γ and MCF-7 cytotoxicity.

iv Furthermore, an orthotopic breast cancer model validated the ability of anti-EpCAM/anti-

CD3 PAR therapy to direct T-cell lytic activity towards EpCAM+ breast cancer cells in vivo leading to tumor eradication. Following the in vivo success of anti-EpCAM PAR therapy we chose to explore, Chapter 4, the use of both anti-EpCAM/anti-CD3 and anti-

CD133/anti-CD3 CSANs in conjunction. Notably, when applied to a triple negative breast cancer model we found a synergistic effect from targeting EpCAM and CD133; in fact, full tumor eradication was only elicited when both antigens were simultaneously targeted.

Due to the growing need of a more modifiable CSAN platform we developed monovalent streptavidin (mSA)-DHFR2 fusion proteins. When incorporated into bispecific

CSANs, Chapter 5, we were able to rapidly analyze the activation and directed cell lysis of several targeting constructs simultaneously. Additionally, in Chapter 6 we further adapted mSA CSANs into a universal cell membrane labeling technique. This was accomplished by hydrophobically inserting phospholipids conjugated to biotin into the cell membrane. Heterobifunctional CSANs containing mSA are then stably bound to the biotin moieties.

PAR therapy has several unique innovations, such as the capability of quickly reprogramming T cell membranes in hours rather than in days which is typically seen with standard CAR therapy. Additionally, our approach has the capability to remove the PARs from T-cells by incubation with the FDA approved antibiotic trimethoprim, at clinically relevant concentrations, allowing the pharmacological deactivation of T cells. Collectively, our results demonstrate PAR modified T-cells have the potential to be a viable cancer immunotherapy targeting solid tumors.

v TABLE OF CONTENTS

Abstract ...... iv

Table of Contents ...... vi

List of Tables ...... xiii

List of Figures ...... xiv

List of Schemes ...... xix

List of abbreviations ...... xx

CHAPTER 1: ...... 1

INTRODUCTION – IMMUNOTHERAPY IN CANCER ...... 1

1.1 CANCER BIOLOGY ...... 2 1.2 CONTEMPORARY IMMUNOTHERAPY ...... 3 1.2.1 Cancer Specific Overexpression ...... 3

1.2.2 Development of Therapeutic Monoclonal Antibodies ...... 6

1.2.3 Development of Antibody Fragments for Therapeutic Use ...... 11

1.2.4 Development of BiTEs ...... 14

1.2.5 Development of Chimeric Antigen Receptor (CAR) T cells ...... 21

1.3 UTILIZING PROSTHETIC ANTIGEN RECEPTORS IN CANCER THERAPY 25 1.3.1 Chemically Self-Assembled CSANs ...... 25

1.3.2 Development of Prosthetic Antigen Receptors (PARs) ...... 29

1.4 CONCLUSION ...... 32 CHAPTER 2: ...... 34

vi EVALUATING THE IN VIVO STABILITY AND BIODISTRIBUTION OF

CHEMICALLY SELF-ASSEMBLED NANORINGS (CSANS) ...... 34

2.1 INTRODUCTION ...... 35 2.1.1 Principles of Positron Emission Tomography (PET)...... 35

2.1.2 Application of Immuno-Positron Emission Tomography (Immuno-PET) in

Cancer Therapy ...... 38

2.1.3 Utilizing Immuno-PET to Improve Clinical Translation ...... 41

2.1.4 Development of radiolabeled anti-EGFR CSANs ...... 43

2.2 RESULTS AND DISCUSSION ...... 46 2.2.1 Synthesis of bis-MTX-DOTA [64Cu]...... 46

2.2.2 Preparation of anti-EGFR-CSANs ...... 49

2.2.3 Preparation of PEGylated anti-EGFR CSANs ...... 52

2.2.4 In vitro modeling of RES uptake with mouse macrophages...... 60

2.2.5 Characterization of anti-EGFR-CSANs binding ...... 62

2.2.6 Biodistribution of 64Cu labeled CSANs ...... 65

2.2.7 MicroPET/CT Imaging ...... 70

2.3 CONCLUSIONS...... 75 2.4 MATERIALS AND METHODS ...... 77 2.4.1 Materials ...... 77

2.4.2 Synthesis of bis-MTX-DOTA...... 77

2.4.3 Construction of the plasmid and Unnatural Amino Acid Mutagenesis ...... 78

vii 2.4.4 Protein Expression, purification and characterization ...... 79

2.4.5 Site-specific PEGylation of DHFR2 proteins ...... 81

2.4.6 Self-assembly and Characterization of CSANs ...... 81

2.4.7 In Vitro Cell Binding Analysis by Flow Cytometry ...... 82

2.4.8 Determination of CSAN Uptake by Raw 264.7 Cells ...... 82

2.4.9 Preparation of 64Cu Labeled CSANs ...... 83

2.4.10 Small Animal PET Imaging and Evaluation of Tissue Biodistribution ...... 84

CHAPTER 3: ...... 86

ERADICATION OF ESTABLISHED SOLID TUMORS BY CHEMICALLY SELF-

ASSEMBLED NANORING (CSAN) LABELLED T-CELLS ...... 86

3.1 INTRODUCTION ...... 87 3.1.1 Challenges in Solid Tumor Immunotherapy ...... 87

3.1.2 αEpCAM/αCD3 PAR Development ...... 94

3.1.3 Relevance of Targeting the EpCAM Receptor ...... 96

3.2 RESULTS AND DISCUSSION ...... 99 3.2.1 Preparation of αEpCAM/αCD3 bispecific CSANs ...... 99

3.2.2 In Vitro T-cell Activation and Tumor Cell Cytotoxicity ...... 105

3.2.3 In Vivo anti-Tumor Activity ...... 118

3.3 CONCLUSIONS...... 131 3.4 MATERIALS AND METHODS ...... 133 3.4.1 DHFR2 protein expression and purification ...... 133

viii 3.4.2 Cell Lines, Culture Conditions and T-cell isolation ...... 134

3.4.3 CSAN Oligomerization and Characterization ...... 135

3.4.4 Binding Assays ...... 136

3.4.5 Cytotoxicity Assays ...... 137

3.4.6 Immunostaining and Cytokine Analysis ...... 138

3.4.7 MCF-7 Orthotopic Breast Cancer Model ...... 139

3.4.8 DHFR2 In Vivo Immunogenicity Analysis ...... 141

3.4.9 Statistical Analysis ...... 142

3.4.10 Study Approval ...... 143

CHAPTER 4: ...... 144

Synergistic Elimination of CD133 and EpCAM EXPRESSING Triple Negative Breast

Cancer ...... 144

4.1 INTRODUCTION ...... 145 4.1.1 Relevance of Cancer Stem Cells ...... 145

4.1.2 CD133 as a Cancer Stem Cell Marker ...... 146

4.1.3 CD133 Expression on Normal Tissues Cells ...... 149

4.1.4 Current CD133 Targeted Therapies ...... 151

4.1.5 CD133 Expression in Triple Negative Breast Cancer (TNBC) ...... 153

4.2 RESULTS AND DISCUSSION ...... 155 4.2.1 Construction of anti-CD133-DHFR2 (αCD133-DHFR2) Plasmid ...... 155

ix 4.2.2 In Vitro Analysis of αCD133 CSANs ...... 157

4.2.3 In Vivo αEpCAM/αCD133 PAR Anti-Tumor Activity ...... 165

4.2.4 Importance of CD133 in Tumorigenicity ...... 173

4.3 CONCLUSIONS...... 176 4.4 MATERIALS AND METHODS ...... 177 4.4.1 Cell Culture ...... 177

4.4.2 CD133 plasmid Construction ...... 178

4.4.3 αCD133/αCD3 CSAN Oligomerization and Characterization ...... 178

4.4.4 Binding Assays ...... 179

4.4.5 Cytotoxicity Assays ...... 180

4.4.6 Immunostaining and Cytokine Analysis ...... 180

4.4.7 Orthotopic TN Breast Cancer (MDA-MB-231) Model ...... 181

4.4.8 CD133 Depletion Assays ...... 182

CHAPTER 5: ...... 184

STREP-PARS FOR THE OPTIMIZATION OF IMMUNOTHERAPY TARGETING

CONSTRUCTS...... 184

5.1 INTRODUCTION ...... 185 5.1.1 Current Bispecific Scaffold Selection ...... 185

5.1.2 Monovalent Streptavidin as a Chemical Biology Tool ...... 187

5.1.3 Development of Monovalent Streptavidin (mSA) CSANs ...... 188

5.2 RESULTS AND DISCUSSION ...... 190

x 5.2.1 Preparation and Characterization of mSA/αCD3 bispecific CSANs ...... 190

5.2.2 Confirmation of mSA/αCD3 CSAN Biotin Binding ...... 192

5.2.3 mSA/αCD3 Bispecific CSAN Binding Evaluation ...... 193

5.2.4 mSA/αCD3 Bispecific CSAN Cytotoxicity ...... 195

5.3 CONCLUSIONS...... 197 5.4 MATERIALS AND METHODS ...... 198 5.4.1 Cells and Cell Culture ...... 198

5.4.2 Protein Expression and Purification...... 199

5.4.3 CSAN Formation and Characterization ...... 199

5.4.4 Binding Assays ...... 200

5.4.5 Cytotoxicity Assays ...... 200

5.4.6 Cytokine Analysis ...... 201

CHAPTER 6: ...... 202

FUTURE DIRECTIONS – A UNIVERSAL NON-GENETIC MEMBRANE

ENGINEERING APPROACH FOR DIRECTING CELL-CELL INTERACTIONS ... 202

6.1 INTRODUCTION ...... 203 6.1.1 Motivation for a Universal Approach to Cell Membrane Engineering ...... 203

6.1.2 Membrane Engineering by Hydrophobic Insertion ...... 207

6.1.3 CSAN Mediated Cell Surface Engineering ...... 209

6.2 RESULTS AND DISCUSSION ...... 212 6.2.1 Hydrophobic Insertion of Functionalized Phospholipids ...... 212

xi 6.2.2 Installing CSANs on Phospholipid-Modified Cells ...... 213

6.3 CONCLUSIONS...... 219 6.4 MATERIALS AND METHODS ...... 220 6.4.1 Cells and Cell Culture ...... 220

6.4.2 Protein Expression and Purification...... 220

6.4.3 CSAN Formation and Characterization ...... 221

6.4.4 Hydrophobic Insertion of Phospholipid Conjugates ...... 221

6.4.5 Functionalizing Phospholipid-Modified Cells with CSANs ...... 223

6.4.6 Stability Studies ...... 223

6.4.7 Trimethoprim-Induced CSAN Dissociation ...... 225

6.4.8 Statistical Considerations ...... 226

BIBLIOGRAPHY ...... 227

xii

LIST OF TABLES

Table 1.1 Approved Monoclonal Therapeutics ...... 8

Table 2.1 DLS Evaluation of CSAN Hydrodynamic Size ...... 52

xiii LIST OF FIGURES

Figure 1.1 Antibody Fragment Constructs...... 12

Figure 1.2 Bispecific Directed Immune Responses ...... 17

Figure 1.3 DHFR Dimerization with addition of C9-bisMTX ...... 26

Figure 1.4 Formation of CSANs Through the Addition of bis-MTX ...... 27

Figure 1.5 Impact of DHFR2 Amino Acid Linker on CSAN Size...... 28

Figure 1.6 Atomic Force Microscopy (AFM) of DHFR2-scFv Octomeric CSANs...... 31

Figure 2.1 Physics Principles Underlying PET Imaging ...... 37

Figure 2.2 LC-MS/ESI analysis of Bis-MTX-DOTA...... 47

Figure 2.3 LC-MS/ESI analysis of Bis-MTX-DOTA chelation of Cu+2 ...... 49

Figure 2.4 Schematic representations site-specific PEGylation ...... 50

Figure 2.5 SEC Evaluation of CSAN Formation ...... 51

Figure 2.6 Schematic for Final CSAN In Vivo Imaging Platform ...... 52

Figure 2.7 SDS-PAGE analysis of 1DHFR2 constructs ...... 55

Figure 2.8 Mass spectra of 1DHFR2 protein constructs ...... 57

Figure 2.9 Size exclusion chromatography of anti-EGFR CSANs prepared with bis-MTX-

DOTA ...... 58

Figure 2.10 Hydrodynamic diameters distribution of CSANs...... 60

Figure 2.11 In vitro macrophage uptake of FITC labeled CSANs ...... 62

Figure 2.12 Cell Surface Depletion Assay of EGFR on U-87 MG cells ...... 63

Figure 2.13 In Vitro U-87 MG Cell Binding Assay ...... 64

Figure 2.14 In Vivo CSAN Biodistribution (24 Hours) ...... 66

xiv Figure 2.15 Tumor to blood ratio of CSAN Constructs...... 68

Figure 2.16 In Vivo CSAN Biodistribution (48 Hours) ...... 69

Figure 2.17 In Vivo CSAN Stability Assay ...... 70

Figure 2.18 MicroPET/CT Imaging of CSANs at 1, 4 and 24 Hours Post Injection ...... 72

Figure 2.19 Time Dependent CSAN Tumor Accumulation ...... 73

Figure 2.20 Time Dependent CSAN Blood Clearance ...... 73

Figure 2.21 Targeted and non-Targeted In Vivo Biodistribution (24 Hours) ...... 75

Figure 3.1 Prosthetic Antigen Receptor (PAR) Schematic...... 96

Figure 3.2 Carcinoma Specific EpCAM Expression ...... 97

Figure 3.3 Bispecific CSAN characterization ...... 100

Figure 3.4 Binding Characterization of CSANs...... 102

Figure 3.5 Binding of αEpCAM CSANs to MCF-7 Breast Cancer Cells...... 102

Figure 3.6 αEpCAM CSAN binding to Tamoxifen Resistant Breast Cancer Cells...... 103

Figure 3.7 CSAN internalization evaluation by confocal microscopy...... 104

Figure 3.8 CSAN stability study on T-cell membranes...... 104

Figure 3.9 In Vitro Cytotoxicity of αEpCAM/αCD3 CSANs ...... 106

Figure 3.10 In Vitro Cell Killing with Moc31 Competition demonstrating killing is

EpCAM Mediated...... 106

Figure 3.11 Cell Killing visualized by time lapse microscopy...... 108

Figure 3.12 In Vitro PBMC Activation Marker Upregulation Assay ...... 109

Figure 3.13 In Vitro Cytokine Release Assay ...... 111

Figure 3.14 PARs dose dependent cytokine production...... 111

xv Figure 3.15 CSAN Mediated T-Regulatory Cell Activation ...... 113

Figure 3.16 Monitoring pS6 levels in T-cells labelled with Anti-EpCAM/anti-CD3 CSANs.

...... 115

Figure 3.17 Isolated CD8+ and CD4+ T-cells are still capable of selective activation and target cell killing...... 117

Figure 3.18 CD69 and CD25 expressed on purified CD4+ and CD8+ T cells...... 118

Figure 3.19 Confirmation of Tumor Implant by IVIS ...... 119

Figure 3.20 In Vivo efficacy study of bispecific PARs in an orthotopic NSG mouse model.

...... 121

Figure 3.21 Variable dosing schedule does not exhibit toxicity...... 122

Figure 3.22 In Vivo Cytokine Release Assay ...... 124

Figure 3.23 CD4+ and CD8+ memory cell formation...... 127

Figure 3.24 Trimethoprim mediated dissociation of CSAN therapy in vivo...... 129

Figure 3.25 Murine anti-DHFR2 Immune response...... 131

Figure 4.1 PROM1 (CD133) Expression Levels Across Cancer Populations ...... 146

Figure 4.2 PCR amplification of CD133 scFv Specific Sequence ...... 156

Figure 4.3 αCD133-DHFR2 Induction Test ...... 157

Figure 4.4 Oligomerization of αCD133-DHFR2 and αCD3-DHFR2 ...... 158

Figure 4.5 αCD133 CSAN In Vitro Binding Characterization ...... 159

Figure 4.6 ΑCD133/αCD3 CSAN labeled T-cells selectively activate and kill target

CD133+ cells...... 160

Figure 4.7 EpCAM and CD133 Expression profile on MDA-MB-231 cells...... 161

xvi Figure 4.8 ΑCD133/αCD3 and αEpCAM/αCD3 CSAN labeled T-cells selectively activate and kill target MDA-MB-231 cells...... 163

Figure 4.9 Synergistic αEpCAM/αCD133 Cytokine Release ...... 164

Figure 4.10 In Vivo efficacy study of bispecific PARs in an orthotopic TNBC mouse model...... 168

Figure 4.11 CD133 and EpCAM Expression in PAR Treated Tumors...... 169

Figure 4.12 In Vivo survival curve of bispecific PARs in an orthotopic TNBC mouse model...... 171

Figure 4.13 In Vivo efficacy study mouse weights...... 172

Figure 4.14 ΑCD133/mSA CSAN Based CD133 Depletion and Enrichment...... 174

Figure 4.15 Effects of CD133 Depletion and Enrichment on Orthotopic TN Breast Cancer

Model...... 176

Figure 5.1 Scheme for Bispecific mSA/αCD3 CSAN Immunotherapy ...... 190

Figure 5.2 Verification of mSA/αCD3 CSAN Formation by Cryo Electron Microscopy and

Dynamic Light Scattering ...... 191

Figure 5.3 Verification of mSA DHFR2 Biotin Binding by Size Exclusion Chromatography

...... 193

Figure 5.4 Bispecific mSA/αCD3 CSAN Target Cell Binding ...... 194

Figure 5.5 Target Cell Lysis by Bispecific mSA/αCD3 CSANs ...... 196

Figure 5.6 Induction of IL-2 Cytokine Release by Bispecific mSA/αCD3 CSANs ...... 197

Figure 6.1 Applications of Engineered Cell-Cell Interactions...... 204

xvii Figure 6.2 Cell Surface Engineering with Chemically Self-Assembled Nanorings

(CSANs)...... 211

Figure 6.3 Phospholipid Insertion Enables Tunable Cell Surface Modification...... 213

Figure 6.4 Membrane Stability and Controlled Dissociation of Phospholipid-Anchored

CSANs...... 215

Figure 6.5 Membrane Stability of CSANs in Mouse Plasma...... 218

xviii LIST OF SCHEMES

Scheme 2.1 Synthesis of bis-MTX-DOTA ...... 47

xix LIST OF ABBREVIATIONS

Adoptive Cell immunotherapy ACI Antibody Drug Conjugate ADC Antibody dependent cell-mediated cytotoxicity ADCC Atomic Force Microscopy AFM bivalent methotrexate bis-MTX Bispecific T-cell Engager BiTE Chimeric Antigen Receptor CAR computer-aided design CAD Carbonic Anhydrase IX CAIX Cluster of Differentiation CD Compliment Dependent Cytotoxicity CDC Compliment determining Region CDR Carboxyfluorescein succinimidyl ester CFSE Constant Domain of heavy chain CH Constant Domain of light chain CL Cytokine Release Syndrome CRS Chemically Self-Assembled Nanorings CSAN Cancer Stem Cell CSC computerized tomography CT Diethylaminoethyl DEAE Dynamic Light Scattering DLS dihydrofolate reductase DHFR two recombinantly fused DHFRs DHFR2 Dimethylsulfoxide DMSO Deoxyribonucleic acid DNA Ethylenediaminetetraacetic acid EDTA electrospray ionization mass spectrometry ESI-MS Enhanced Permeation Retention effect EPR epithelial growth factor receptor EGFR epithelial cell adhesion molecules EpCAM Fragment antigen-binding Fab Food and Drug Administration FDA Fragment Crystalizable region Fc Fluoresceince isothiocyanate FITC Interferon gamma IFN-γ Interleukin 2 IL-2 Interleukin 6 IL-6 Interleukin 10 IL-10 Isopropylthiogalactoside IPTG Dissociation constant Kd xx

Monoclonal Antibody mAb Myeloid Derived Suppressor Cell MDSC Major Histocompatibility Complex MHC Mononuclear Phagocytic System MPS Magnetic Resonance Imaging MRI Monovalent Streptavidin mSA methotrexate MTX Natural Killer Cell NK Cell p-acetyl phenylalanine pAcF Prosthetic Antigen Receptors PARs polyethylene glycol PEG Positron emission tomography PET Pharmacokinetics pK reticuloendothelial system RES region of interest ROI single chain antibodies scFv size exclusion chromatography SEC single-chain variable fragment scFv T cell Receptor TCR Triple Negative Breast Cancer TNBC S-2-(4-isothiocyanatobenzyl)-1,4,7,10- p-SCN-Bn-DOTA tetraazacyclododecane tetraacetic acid Percent Injected dose per gram % ID/g

xxi

CHAPTER 1: INTRODUCTION – IMMUNOTHERAPY IN CANCER

1.1 CANCER BIOLOGY

Cancer is a disease defined by the uncontrollable proliferation of abnormal cells in disregard to the normal rules of cellular division. Typically, healthy cells are constantly subject to signals dictating whether they should divide, differentiate into another cell or die.1 However, cancer grows a degree of autonomy from these signals resulting in the unchecked cellular proliferation and spread of the disease, until ultimately fatal. The cause for this uncontrolled cell growth results from a number of factors, such as mutations in oncogenes and tumor suppressor genes, that deregulate the cell cycle.2 Normally, two to eight driver mutations are required to initiate tumorigenesis, a varying fraction of which eventually develop into metastatic cancer. These driver mutations often take decades to accumulate and fall into three primary categories of cell regulation, namely: genome maintenance, cell fate and cell survival.2 A variety of endogenous and exogenous factors can initiate tumorigenesis including, stress induced from cellular metabolism, radiation, and carcinogens, however all are mutagenic in nature.3 The resulting accumulation of mutations, in either oncogenes or tumor suppressor genes, leads to tumorigenesis by endowing the mutation-rich cells with the hallmarks of cancer, identified by Hanahan and

Weinberg, that are typically present.4 These include sustained proliferation, resistance to cell death, angiogenesis, evasion of growth suppressors, replicative immortality, genomic instability, escape from immune destruction, tumor-promoting inflammation, deregulated cellular energetics as well as invasive characteristics. Clearly this is an extensive list, and

for a tumor to become an aggressive cancer it must fulfill a majority of these hallmarks, which likely explains why cancer is not overwhelming in the human population.

1.2 CONTEMPORARY IMMUNOTHERAPY

1.2.1 Cancer Specific Overexpression

Multiple methods have been applied to eradicating tumor burden in cancer patients including surgery, chemotherapy and radiotherapy.5 However, the most common method is chemotherapy, which uses small cytotoxic molecules to target overexpressed pathways in cancerous tissue. Chemotherapy is a distinctive approach, differing from surgery and radiation, that uses no physical means of tumor extraction, but instead relies on chemical agents to eradicate or control the growth of cancer. While individual mechanisms of action may differ between small molecule therapeutics the overwhelming majority take advantage of the uncontrolled growth, and rapid cell division that defines cancerous tissue.5, 6

The first chemotherapeutics identified were known as nitrogen mustard, DNA alkylating agents discovered in World War II, for the treatment of lymphomas.7 Following in the wake of these early-stage therapeutics many variations of chemotherapeutics agents have been pioneered and synthesized, such as, antimetabolites, DNA intercalating agents, anti-tubulin agents, molecular targeting agents, and hormones.5 Arguably the most well- known include (1) 5-fluorouracil, which is used in the treatment of breast and gastrointestinal cancers, (2) methotrexate, which is used to treat non-Hodgkin’s lymphoma, acute lymphoblastic leukemia and several solid-phase tumors, and (3) gemcitabine, which

is used in cases of pancreatic, bladder and non-small cell lung cancers that have metastasized.5

While chemotherapeutic agents have successfully extended survival times and led to tumor remission in many cases, there are a number of significant drawbacks to these treatments. As previously stated, chemotherapeutic agents exert their selectivity by targeting molecular pathways linked to the rapid division and growth of cancerous tissue.

However, this approach is not especially selective due to the several healthy tissues that also undergo frequent cell division, namely: hair follicles, the lining of the digestive tract, and bone marrow. The resulting off-target cytotoxicity effectively limits the total deliverable dose patients are able to receive, and even restricts the number of small molecule drugs that are considered for chemotherapy due to their extremely potent cytotoxicity8 Regardless, commonly encountered complications with chemotherapy include hair loss, bone marrow suppression, gastrointestinal tract lesions and nausea.5 As a result of these dose-limiting restrictions, chemotherapy must be given to the patient multiple times at suboptimal doses in order to achieve efficient tumor reduction rates.8

Unfortunately, by reducing the dosage, there is an increased risk for the cancerous tissue to develop a resistance towards the given treatment, and vastly decrease the chance of full tumor reduction.8

On account of the unwanted off‐target cytotoxicity and drug resistance commonly seen with small molecule chemotherapeutics, significant effort has been placed into developing novel therapeutics that selectively target the tumor tissue while avoiding

healthy cells. Arguably the most fundamental step in achieving this goal dates back to the original observations of antigen overexpression by tumor cells through serological techniques in the 1960s.9 The subsequent definition of cell surface antigens expressed by human cancers has revealed a broad array of targets that are overexpressed, mutated or selectively expressed compared with normal tissues.10 The discovery of overexpressed, or completely unique, surface antigens displayed on tumor tissue almost singlehandedly led to the idea that anticancer drugs would exhibit a far greater selectivity if conjugated to a targeting element capable of delivering the drug directly to the cancerous tissue.11 These targeting elements have revitalized previous research for those agents that were deemed too cytotoxic for use as a chemotherapeutic, and now are commonly seen in drug delivery platforms. Furthermore, targeting agents have opened the doors to the application of cancer therapies outside of traditional small molecule therapeutics including systems as large as cell delivery. Several moieties have been developed for utilization as targeting elements of overexpressed surface antigens, including: monoclonal antibodies, small peptide sequences and small molecules.12 While each of these targeting moieties have yielded excellent success in specifically targeting cancer antigens, the ensuing chapters will primarily focus on the use of antibodies, and specifically antibody fragments, as targeting elements; with a special emphasis placed on the development of therapeutics targeting epithelial cell adhesion molecule (EpCAM) and CD133 (PROM1) cell surface antigens.

1.2.2 Development of Therapeutic Monoclonal Antibodies

Upon the discovery that cancerous cells selectively upregulate cell surface markers, methods have been developed to create therapeutic platforms specifically targeting cancer antigens. While small molecules and short peptide sequences have been utilized, perhaps the most successful and widely used targeting ligands have been found through monoclonal antibodies (mAbs). Several classes of antibodies are present in the natural immune system, but the class most commonly adapted for therapeutic use are IgG immunoglobulins. IgG antibodies are composed from two heavy chain fragments and two light chain fragments

(Figure 1.2).13 MAbs recognize and bind cell surface markers through their highly variable, complementarity domain region, and often possess binding affinities that are far superior to other small molecule and peptide therapies. In addition, due to their bivalent nature, mAbs are capable of binding two separate receptors, simultaneously, thus also taking advantage of avidity. MAbs contain several functional modalities including (1) a region known as the crystallizable fragment, or Fc region, that is recognized by several immune response agents including natural killer (NK) cells, macrophages, dendritic cells, phagocytes and neutrophils.13 Through the recruitment of additional immunologic agents, mAbs are able to cause antibody dependent cell‐mediated cytotoxicity (ADCC) in which the recruited immune response agents are activated and elicit direct cell lysis of the mAb bound target cell. (2) A related pathway, complement dependent cytotoxicity (CDC), in which mAb binding initiates activation of the complement system, puncturing holes in the

cell membrane and leading to cell lysis.13 (3) Activation of apoptosis inducing receptors and (4) the delivery of toxins, or other payloads to cancer cells.

Antibodies were first formulated for therapeutic use and drug delivery in the early twentieth century with the work of Paul Ehrlich.14 Over the course of the last century, there have been many scientific advances in the development of antibody therapeutics leading to several mAb-based drugs approved for clinical use.14 However, antibody therapy became a reality in 1975 when the breakthrough hybridoma technology was developed for properly hybridizing monoclonal antibodies and generation of the first licensed monoclonal antibody, OKT3, that specifically binds the CD3 receptor.15 Hybridoma technology has simultaneously allowed for mAbs to retain their high binding affinities for single receptor epitopes, while also achieving greater bioreactivity as clinical therapeutics.16 Further advances led to chimeric antibodies, in which human antibody constant regions (which provide reduced autoimmunological responses) were fused with the murine variable fragments resulting in mAbs with reduced immunogenicity.

Additionally, humanized mAbs have been obtained through phage display techniques and genetic modification of murine antibody sequences, affording reduced rates and potency of immunological responses.17

Since the late 1980s there have been more than fifty mAb-based therapeutics approved by the Food and Drug Administration (FDA), encompassing a wide range of disease targets, including the prevention of organ transplant rejection, leukemias, lymphomas, multiple carcinomas and hematological malignancies. Of those, 17 have been

approved as anti-cancer agents (Table 1.1)10, 13, 14 The most notable unconjugated antibodies used for therapy include Rituximab, which binds to CD20 expressed by non-

Hodgkin lymphoma and chronic lymphocytic leukemia,18 Trastuzumab, which binds to

HER2 on breast cancer,19 and Cetuximab, which binds to Epidermal growth factor receptor

(EGFR) on colorectal cancer.20 All of these monoclonal antibodies have human IgG1 Fc regions allowing for functional Fc based cytotoxicity and target the tumor directly, though there are also a plethora of antibodies targeting the vast array of tumor associated pathways.10

Table 1.1 Approved Monoclonal Therapeutics

Therapeutic Target Disease Target Name (Year Sponsor Company: Receptor: Type: FDA Approved): Muronomab Transplant Johnson & Johnson CD3 (1986) Rejection Rituximab Genentech/Roche/Biogen Non-Hodgkin’s CD20 (1997) Idec lymphoma Trastuzumab Genentech/Roche HER2 Breast Cancer (1998) Alemtuzumab Chronic Myeloid Genzyme/Bayer CD52 (2001) Leukemia Colorectal, Bevacizumab NSCLC, Genentech/Roche VEGF (2004) Glioblastoma, Breast cancer 8

Cetuximab ImClone Systems/Bristol- Breast, Colon, EGFR (2004) Myers Squibb Lung, Head/Neck Panitumumab Amgen EGFR Colorectal Cancer (2006) Chronic Ofatumumab Genmab/GlaxoSmithKline CD20 Lymphocytic (2009) Leukemia Unresectable and Ipilimumab Bristol-Myers Squibb CTLA-4 Metastatic (2011) Melanoma Pertuzumab Roche HER2 Breast Cancer (2012) Obinutuzumab Roche CD20 CLL (2013) Colorectal, Non- squamous Non- Small Cell Lung Bevacizumab Genetech VEGF Cancers, (2014) Glioblastoma, Renal Cell Carcinomas Pembrolizumab Merck Sharp & Dohme PD-1 Melanoma (2014) Limited Carcinoma; non- small-cell lung Nivolumab Bristol-Myers Squibb PD-1 carcinoma; renal (2015) Pharma cell Hodgkin disease melanoma

Elotuzumab Multiple Bristol-Myers Squibb SLAMF7 (2015) myeloma Metastatic non- Atezolizumab Genentech (Roche) PD-L1 small cell lung (2016) cancer Necitumumab Carcinoma, non- Eli Lilly EGFR (2016) small-cell lung Data adapted from Weiner et al., Scott et al., Beck et al., and http://www.cancer.gov/cancertopics/druginfo/fda

Although thought to be initially successful, ‘naked’ antibody therapeutics have left significant room for improvement in their overall effectiveness and therapeutic ability.

Through the conjugation of a cytotoxic drug, mAbs can utilize their unique binding capabilities to selectively deliver their drug cargo, thereby improving upon their overall therapeutic potential. As an example, trastuzumab, which was FDA approved in 1998 for the treatment of breast cancer, has proven inadequate in a number of patients whose disease actually progressed following treatment with several HER‐2 targeted treatments.21 Studies show that while these breast carcinoma cell lines fail to respond to trastuzumab treatments, they still retain expression of the HER‐2 receptor, strongly indicating the development of resistance to the original mAb therapeutic.22 However, a follow-up study using an

Antibody Drug Conjugate (ADC) of trastuzumab, containing the cytotoxic agent emtansine, showed that approximately 30% of patients who were resistant to treatment of trastuzumab alone saw a reduction or remission of their tumor size upon treatment with the

trastuzumab ADC.21 Due to the success achieved during clinical trials, trastuzumab‐ emtansine received FDA approval in February 2013.

1.2.3 Development of Antibody Fragments for Therapeutic Use

In spite of the successes seen with mAb based therapy there have been significant efforts toward generating alternative scaffolds to achieve unique pharmacokinetics, and other desired properties, compared to the parental mAb. Antibody fragments are of varied structure, but typically smaller than native antibodies, and lack an Fc domain. Their smaller size offers more binding events per mass of protein purified and administered, less viscous formulations (and, thus, ease of injection), and likely provide improved tissue penetration. The lack of an Fc domain is one reason Ab-fragments exhibit reduced circulation half-lives and immune system activation.10 Ab-fragments are especially amenable to genetic manipulations or covalent modifications aimed at improving their affinity, stability, and function.23-25 Antibody fragments have been linked with enzymes,26 toxins,27 and radionuclides for cancer treatment,22 as well as viruses for gene therapy, liposomes or nanoparticles for improved drug delivery, and dye or other sensing substances.22

Due to its modular structure, distinct segments of the mAb can be separated from the total form and isolated to provide smaller protein fragments that still retain their unique binding ability (Figure 1.1).28 Most commonly utilized antibody fragments are isolated antigen binding fragments (Fabs), which encompass one heavy chain and one light chain

from one ‘arm’ of the antibody, and single chain variable fragments (scFvs), which consist of the variable fragments from both the heavy and light chains attached through a short amino acid linker. Both Fabs and scFvs contain the highly variable complementarity determining regions responsible for specific high binding of target antigens. Such fragments allow for retention of the high binding affinities and selectivity of the parent mAbs while reducing the overall size of the therapeutic molecule.

Figure 1.1 Antibody Fragment Constructs

Schematic Depicting the fragment subsets of parent mAbs used for initial development of antibody fragment therapeutics. Full IgG mab is seen on the left consisting of constant regions in blue, and variable regions in green. Single chain variable fragment (scFv), single-domain antibody (dAb) and isolated antigen binding fragment (Fab) are depicted on the right. 12

With the use of smaller antibody fragments, researchers have sought to improve tumor tissue distribution due to the smaller fragment size,28 reduce production costs through the use of prokaryotic expression systems,29 and gain the ability to bind rare antigen epitopes that are not available to larger parental mAbs.30 While these fragmented species allow for altered, and often improved, physiochemical properties, they also have the potential for reduced efficacy when compared to the parental mAbs. First, due to their smaller size, antibody fragments have reduced circulation half‐lives, making therapeutic delivery extensively more challenging. Additionally, due to the removal of the heavy chain constant domain regions containing the Fc domain, Fabs and scFvs lose the additional site of reactivity that leads to recognition by other immune agents, as well as Fc recycling pathways for increased circulation.31 Loss of this reactive site may decrease overall activity and the therapeutic potential of the antibody fragments when compared to similar full- length mAb designs. Despite these limitations many groups have developed successful clinical applications for mAb fragments, some of which have received approval from the

FDA.28

While the first developments toward antibody fragment designs began in the late

1980s, most of our understanding and manipulation of these fragments has emerged since the late 1990s.31 Types of fragments currently under both clinical and preclinical development include: scFvs discussed earlier, F(ab’)2 fragments consisting of two Fab segments linked together and formed removal of the Fab region from the Fc region of the mAb through digestion with pepsins, bivalent and trivalent scFv fragments including

genetically fused tandem scFvs, diabodies and triabodies created from the oligomerization between two or three separate scFvs respectively, single domain antibodies that encompass only the heavy chain variable fragment, and finally bispecific F(ab)2 and tandem scFvs that contain two different targeting elements linked together through genetic engineering methods. While several of these antibody-based fragments have successfully reached the stage of clinical trials, many have failed to advance because of their lack of improved efficacy over full-length mAbs currently in use. Therefore, it was imperative to discover other avenues with which these smaller fragments could be incorporated and prove potentially clinically relevant. For this reason, T cell based immunotherapy is proving to be a powerful application for mAb based fragments.

1.2.4 Development of BiTEs

Within immunotherapy there are multiple strategies for achieving anti-tumor activity, one of which is retargeting immune effector cells. In effector cell retargeting, cells such as NK cells, macrophages, and cytotoxic T lymphocytes are brought into contact with target tumor cells through one of their activating receptors and trigger a cytotoxic response.

Although the retargeting of both NK cells and macrophages have definite benefits, T cell retargeting may have the greatest potential in directed immunotherapy. The therapeutic power derived from T cells is a result of their extensive expansion upon activation and their ability to activate host immunity. Unlike dendritic cells, macrophages, and other accessory cells, T cells expand rapidly upon activation, are present in large numbers, and provide a

robust and durable cytotoxic response; often generating immunologic memory.

Furthermore, T cells have been found to independently infiltrate and attack tumors from the outside as well as infiltrating into the tumor. These features make T cells optimal therapeutic effectors for cancer. However, T-cell redirection does contain one significant challenge: the requirement of a second stimulatory signal to achieve full T cell activation and the prevention of anergy.

There have been multiple methodologies developed for directing T cells to tumor cells. These include genetically engineered cell-based therapies, such as the highly potent chimeric antigen receptor (CAR)-expressing T cells (reviewed in the next section), and the rapidly expanding repertoire of antibody-derived molecules which selectively link target and effector cells. More specifically, these cell-linking antibodies belong to a specific class of antibodies known as bispecifics. In contrast to standard antibodies containing specificity for only a single antigen, bispecific antibodies exhibit dual antigen targeting, allowing them to bind two unique antigens simultaneously and thereby facilitating cell-cell interactions.

While bispecific antibodies take several forms, this chapter will examine a particular bispecific format that has been developed specifically for the purpose of T cell retargeting: the bispecific T cell engager, or BiTE.

The practical use of bispecific antibodies for T cell redirection began following the production of the first T cell-engaging trispecific antibodies in the 1980s.32-34 These molecules, were produced using a hybrid-hybridoma (quadroma) method that yielded antibodies with a unique antigen binding specificity in each arm as well as a complete Fc

domain capable of binding Fc receptors.32, 35 By designing one of the bifunctional arms to include an anti-CD3 targeting element, these trispecifics are able to generate an enhanced immune response and cytokine release at the target tissue by recruiting T cells to the antigen expressing cells. Additionally, secondary T cell stimulation is provided by macrophages and accessory cells which are activated upon binding to the antibodies Fc domain (Figure 1.2). Catumaxomab, a trifunctional mAb directed towards ovarian and gastric carcinomas that express the epithelial cell-adhesion molecule (EpCAM) antigen on the tumor cell surface, was the first trifunctional mAb developed.10, 14, 28, 36 Currently, FDA approved catumaxomab has provided a significant increase in life expectancy for patients with malignant ascities, which are associated with gastric adenocarcinomas.36, 37 While catumaxomab has shown promise as a treatment towards EpCAM positive epithelial cancers, it does induce unfortunate, but manageable, side effects including nausea, pyrexia and abdominal pain, which are thought to be caused by the buildup of released cytokines.37

Additionally, the Fc domain of catumaxomab has been associated with liver toxicity by activation of Kupfer cells.38 Furthermore, while trispecific antibodies have been successful both in vitro and in vivo, there has been concern that Fc receptor interactions could lead to undesirable effects, such as downregulation of immune responses in response to IL-10 produced by M2-macrophages.32, 39 Consequently, effort has placed in developing T cell- targeting bispecifics lacking an Fc receptor and eventually contributed to the development of bispecific T cell engagers (BiTEs).

Figure 1.2 Bispecific Directed Immune Responses

Top panel: recruitment of immune response with trifunctional antibodies binding target cancer antigen and CD3 receptor on T cells. Macrophages of NK cells are recruited by Fc domain. Bottom panel: Bispecific T cell Engager directed target cell lysis. 17

BiTEs consist of antibodies or engineered proteins that contain multiple binding sites, each with a unique antigen specificity. As with trispecifics, this configuration allows the bispecific antibody to induce cell-cell interactions between two or more cells by containing a binding region that is specific to an antigen on each of the two cell types.

Importantly, the dual specificity achieved in BiTEs is contained in a structure far smaller than a traditional antibody molecule as they are produced from scFv tandems, composed of two different scFvs, that each have a unique antigen specificity. In fact, the entire BiTE molecule is approximately 55 kDa in size and 11 nm in length, consisting of one continuous polypeptide (Figure 1.2).40

What distinguishes BiTEs from other tandem scFvs is their specificity for the T cell receptor (TCR) complex. In these molecules, one scFv targets a specific tumor antigen while the second scFv targets the CD3 subunit of the TCR. Like other targeted antibody- mediated therapies, the primary goal in antigen selection is something with minimal expression on normal tissues while retaining cell surface expression on tumor cells. This strategy provides the greatest likelihood of an effective tumor-specific targeting while simultaneously minimizing the likelihood of unintended “on-target/off-tumor” responses.

Although the specific mechanism by which BiTEs induce T cell lysis of tumor cells is not completely understood, there are aspects of the process that have been ascertained.

First, the induced linkage between the tumor cell and T cell is critical to the BiTE’s cytotoxic mechanism. More specifically, BiTEs must simultaneously bind to both the T cell and the antigen presented on the tumor cell to elicit a T cell response. For example,

Brischwein and colleagues demonstrated that in the presence of both epithelial cell adhesion molecule (EpCAM) expressing tumor cells and an EpCAM-specific BiTE, T cells could be activated to lyse tumor cells. However, when there were no target cells, or the target cells lacked the EpCAM antigen, there was no activation of T cells.41 Furthermore, without dual binding there was no release of cytokines including interferon gamma, tumor necrosis factor alpha, IL-6, and IL-10 that are upregulated as a result of T cells activation.41

These results suggest that binding of BiTE molecules to only the CD3 receptor of T cells is insufficient to either activate T cells41 or to induce anergy.42 Fortunately, this strict dependence on simultaneous T cell-tumor cell binding circumvents the issue of undesired

T cell activation and the possible therapeutic side effects.

A unique feature of BiTE-mediated immunotherapy is the lack of T cell costimulation required for efficacy. The lack of dependence has been studied in BiTEs with a variety of specificities, all of which induced significant cytotoxicity by T cells in the absence of costimulation (such as anti-CD28 antibodies and IL-2).41, 43-45 Even among the field of bispecific antibodies, this characteristic appears to be unique to BiTEs (in addition to CSANs and PARs which are covered in chapters 3 and 4 of this thesis).46-48 While the reason for this lack of requisite costimulation is unclear, it likely indicates that BiTE mediated T cell activation undergoes an alternate mechanism. One possibility is that many

TCRs cluster within the induced immunological synapse, triggering signaling. Another potential explanation is that memory T cells, which are already antigen experienced and require less stimulation for subsequent activation, may be the predominant effector cells in

BiTE-mediated immunotherapy. Supporting this hypothesis, is the observation that previously primed T cells induce the greatest level of cytotoxicity in BiTE therapy.

Specifically, Dreier and colleagues reported that naïve T cells (CD8+/CD45A+) did not mediate tumor cell lysis in the presence of BiTE while memory T cells (CD8+/CD45O+) elicited robust lysis.43

BiTE efficacy has also been demonstrated in a variety of animal models as well as in humans. Studies of MT110, an anti-EpCAM/anti-CD3 BiTE, have shown that microgram doses are able to both suppress the establishment and promote tumor regression of colorectal cancer cell line mouse xenografts as well as induce tumor regression in primary ovarian cancer explants.49, 50 More recent studies of MT110 have shown that using as little as microgram doses can prevent growth of tumors from the CD133+ specific cancer stem cell population (chapter 5 will discuss this population in further detail).50, 51 An important factor in the use of BiTEs has been the markedly low doses required to observe complete and partial responses in the clinic. For example, blinatumomab (an anti-

CD19/anti-CD3 BiTE) elicited both complete and partial responses at doses of 15, 30, and

60 ug/m2 per day in non-Hodgkin B cell lymphoma patients during a phase I trial.52

As with all therapeutics the pharmacokinetic properties of BiTEs must be taken into consideration, presenting both benefits and challenges to their clinical use. While standard antibody molecules persist in the blood for several days to weeks, due to an FcR-mediated recycling mechanism,23, 53 small antibody-based fragments like BiTEs have a relatively short serum half-life on the magnitude of hours, and in some cases only minutes. This was

confirmed in a human clinical study that demonstrated BiTE half-lives with an average of

1.25 hrs.54 While the short protein half-life significantly reduces the likelihood of long term toxicities it also presents a therapeutic challenge, as the rapid elimination makes maintain serum levels with bolus or intermittent infusion very difficult, thus requiring continuous infusion.55

Results achieved with recent BiTE designs show that these fragmented bispecific antibodies are an excellent prospect for anticancer therapeutic development. Additionally, due to the low BiTE concentrations necessary for therapeutic response, large-scale production for clinical applications is not crucial, which results in easier expression and purification of the antibody‐based therapeutics leading to lower overall drug costs.

1.2.5 Development of Chimeric Antigen Receptor (CAR) T cells

Over the past decade, genetic engineering has emerged as the most utilized and clinically efficacious cellular engineering approach. Indeed, genetically-engineered chimeric antigen receptor (CAR) T cells were recently approved by the United States Food and Drug Administration (FDA) for relapsed/refractory pediatric B cell precursor acute lymphoblastic leukemia and diffuse large B cell lymphoma.56, 57 In this approach, exogenous genetic material is incorporated into the desired cell’s genome where it encodes an artificial cell surface receptor that targets an antigen of interest.58, 59

Like many adoptive cell immunotherapies (ACIs), Chimeric Antigen Receptor

(CAR) T cells have to be individually made for each patient, which is a challenge for the

robust scalability required for late phase clinical studies. However, their use presents one of the first opportunities for a true “cure” to patient cancer.58, 60 CARs combine the antigen- binding property of monoclonal antibodies with the lytic capacity and self-renewal of T cells and have several advantages over conventional T cells.59, 61 CAR-T cells recognize and kill tumor cells independently of the major histocompatibility complex (MHC), so that target cell recognition is unaffected by some of the major mechanisms by which tumors avoid MHC-restricted T-cell recognition, such as downregulation of human leukocyte antigen (HLA) class I molecules and defective antigen processing.

The most common form of CARs are fusions of single-chain variable fragments (scFv), derived from monoclonal antibodies, that are fused to a CD3- zeta transmembrane- and endodomain. A flexible spacer allows the scFv to orient in different directions to enable antigen binding and the transmembrane domain is a typical hydrophobic alpha helix usually derived from the original molecule of the signaling endodomain that protrudes into the cell and transmits the desired signal. CARs are generated by directly isolating T-cells from the patient which are subsequently induced to express the targeting element of choice by viral transduction. These cells are then expanded and reintroduced back into the patient where they undergo further expansion in the presence of the appropriate antigen stimulation.

The treatment of B-cell malignancy in both children and adults with CAR specific for B cell surface markers has proven to be quite effective. The first success with CAR-T was achieved in a patient with B-cell advanced follicular lymphoma who was treated with

CD19-CAR-T and underwent dramatic regression.63 This was followed up by the treatment of a CLL patient, where CD19-CAR-T was transplanted at a relatively low dose of 1.5x105 cells per kg but expanded more than 1000-fold. The patient went into remission soon after therapy.64 The second success was in the application of CD19-CAR-T in ALL patients, where potent effects were seen initially in treatment, though eventually one ALL patient escaped the CD19 specificity and progressed.65 The following year an additional study was published where 16 patients with B-ALL were treated with CAR-T. 88% of patients went into complete remission and were moved to standard-of-care allogeneic HSCT.66 In a phase

I clinical trial run by the NIH, CD19-CAR-T could be manufactured within 11 days and they reported that all toxicities associated with therapy were reversible, albeit still quite severe.67

The success of CD19-CAR-T has energized the field of adoptive cell therapy, especially with the adoption of this therapy by pharmaceutical companies such as Novartis, but this success may be limited to therapy for leukemia. One of the benefits of targeting this disease and particularly the antigens CD19 and CD20 is their constant representation in the form of healthy B cells to the CAR-T. Elimination of B cells in these patients comes with considerable adverse events resulting from humoral immunity, and requires antibody replacement therapy for the foreseeable future for those treated with CD19-CAR-T.

Nonetheless, this may be an advantage, as this will ensure long-lived protection from progressing disease.

In the treatment of solid tumors CAR therapy success has been less successful. The first trials with solid tumor CAR therapy included targeting carbonic anhydrase IX (CAIX),

CD171, FR-α and GD2. For the treatment of renal cell carcinoma with CAIX-CAR-T no clinical benefit was found. Neuroblastoma patients receiving CD171- specific CAR-T had persistence of T cells for 6 weeks but only one patient had a partial response that relapsed once CAR-T were no longer detectable. The treatment of ovarian cancer with FR-α-CAR-

T also saw no anti-tumor activity. Furthermore, utilizing HER2-CAR-T containing CD28 and 4-1BB co-stimulatory domains had immediate on-target off-tumor toxicity when transferred into the patient.68, 69 This CAR therapy induced a cytokine storm that precipitated the death of the patient.70 A more positive result was found for GD2-CAR-T, while initially not showing any direct effect in a long term follow-up study found that low- levels of CAR-T survived up to 192 weeks and mediated a significant survival benefit.71

This strongly suggests that more refined control CAR-T, and a shift of focus away from

CAR co-stimulatory domain modification is required for successful solid tumor therapy.

While BiTEs and CAR T cells have proven excellent results with immunotherapy our laboratory wanted to develop a safe alternative. To this end we developed a chemically self-assembled nanoring (CSAN) platform that stably bound to T-cells for multiple days without the requirement of daily dosing. Additionally, CSANs are rapidly disassembled in the presence of FDA approved antibiotic, Trimethoprim, providing a safe mechanism for dissembling CSANs in the event of any unforeseen toxicity. The following section will

highlight the development an initial application of CSANs and their eventual use as prosthetic antigen receptors (which will be discussed in chapters 3 and 4).

1.3 UTILIZING PROSTHETIC ANTIGEN RECEPTORS IN CANCER THERAPY

1.3.1 Chemically Self-Assembled CSANs

As a means of manipulating and inducing protein‐protein interactions, our group has taken advantage of the high binding affinity between the E. coli enzyme dihydrofolate reductase (DHFR) and its potent inhibitor methotrexate (MTX). Following the acquisition of a crystal structure with MTX-bound to DHFR, it was observed that while each component remained monomeric, upon crystallization the DHFR‐MTX complex comes together to form a dimeric species (DHFR2).72 Additionally, further inspection led to the conclusion that the 9-angstrom space between the two MTX molecules could be bridged by the addition of a simple carbon linker, linking the MTX molecules, without disturbing the binding interaction between the MTX and DHFR. Shortly following this discovery, a

MTX bivalent molecule was synthesized with a 9-carbon linker that spanned the gap between the two carboxylate groups of the MTX molecules (Figure 1.3). Dimerization of

MTX did not perturb the ability of DHFR to bind C9-bisMTX vigorously. These results indicated that the C9-bisMTX compound could be used as a dimerizer molecule in chemically induced dimerization assemblies.73, 74 Through the C9-bisMTX dimerizer, protein interaction and dimerization can be selectively controlled.73

Figure 1.3 DHFR Dimerization with addition of C9-bisMTX

Graphical representation of MTX binding monovalently to DHFR (left) and bis-MTX driving the dimerization of two DHFR monomers (right).

Subsequent effort was placed in also generating dimeric fusion proteins. Ideally, these DHFR-DHFR dimers DHFR (DHFR2) would undergo chemically induced dimerization upon addition of the C9-bisMTX dimerizer to form larger order species

(Figure 1.4A).73 Successful genetic engineering of E. coli DHFR resulted in a fusion protein containing two DHFR proteins joined together through a peptide linker of varying in length from a single glycine residue up to a thirteen-amino acid linker.73 Initially our laboratory was unsure whether the larger order speices would be linear, however, upon addition of the C9-bisMTX dimerizer, DHFR2 fusion proteins self‐assembled into exceptionally stable nanorings (Figure 1.4B).73 Ring formation was completed within several minutes and remained stable up to temperatures of 64°C (Tm = 64-67°C), or

extreme dilution.73 Ring formation was analyzed and confirmed through transmission electron microscopy (TEM) of Uranyl acetate fixed samples of oligomerized C9-bisMTX and DD proteins (Figure 1.4C).73

Figure 1.4 Formation of CSANs Through the Addition of bis-MTX

(A) DHFR Monomer fused together by short amino acid linkers generating DHFR2 construct. (B) The formation of octomeric CSANs upon the addition of bisMTX with a DHFR2 fusion protein with a single glycine linker. (C) transmission electron microscopy (TEM) imaging of octomeric CSANs.

Further analysis of these self-assembled nanorings was done through manipulation of the peptide linker between the two DHFR proteins. It was discovered that increasing the length of the peptide linker between the two DHFR proteins inversely impacts the size of

nanoring formation.73 Incorporation of a single glycine amino acid between the two DHFR proteins (denoted as 1DD) results in primarily an octameric species upon addition of the

C9-bisMTX dimerizer, with species ranging from approximately 6-10 monomeric units

(Figure 1.5). Conversely, lengthening the peptide linker to thirteen amino acids (denoted as 13DD) results in a primarily dimeric form, with species ranging from 1 to 3 monomeric units. Evaluation of these nanorings through dynamic light scattering has shown that the diameters range from 7 nm for the 13DD proteins to 30 nm for the 1DD proteins.73 By varying the length of the peptide linker between the two DHFR monomers, the number of

DHFR-DHFR proteins self-assembled into each nanoring can be selectively controlled.

Figure 1.5 Impact of DHFR2 Amino Acid Linker on CSAN Size

Affect of DHFR2 amino acid linker length on CSAN size. 13DD, top, results in a dimeric species whereas 1DD, bottom, results in a larger octavalent CSAN.

Controlled assembly of these self-oligomerizing proteins was exciting, however the intention of this research was to develop a platform that provided a safe alternative to

BiTEs and CAR T cells.75, 76 As a result, an avenue for facile and controlled disassembly of these large nanorings species was investigated. Trimethoprim, an FDA approved antibacterial agent is also a potent inhibitor of DHFR, with a binding affinity (Kd) that is similar to that of monomeric MTX.77 It was thought that incubation of the nanorings with an excess amount of trimethoprim would cause a competitive exchange between the two

DHFR inhibitors, and result in the dissociation of the larger order nanostructures.

Following nanoring formation, the addition of excess trimethoprim, in vitro, was found to result in complete dissociation of the rings into monomeric DD species.76 Theoretically, any in vivo adverse effects would be easily remedied with the addition of Trimethoprim.

Once dissociated the smaller, monomeric, protein species would rapidly clear in vivo. This would reduce any toxic side effects in the case of adoptive T cell therapies, as well as reduced accumulation in metabolizing organs such as the liver and spleen if required.

Following the discovery and characterization of these chemically self-assembled DHFR- based nanorings, this scaffold was investigated as a mimic of the naturally occurring multivalent immunoglobulins for future use as a targeted cellular therapeutic.75

1.3.2 Development of Prosthetic Antigen Receptors (PARs)

As previously discussed, scFv fragments are an excellent option for retaining the selective binding capabilities of monoclonal antibodies while simultaneously reducing the

overall molecular weight of both the targeting moiety, as well as the total therapeutic compound. It was hypothesized that the DHFR2 nanorings previously discussed could serve as a scaffold to which a variety of different targeting moieties, such as scFvs, could be easy encoded as fusion proteins. The DHFR2 proteins were again genetically modified to incorporate an scFv (anti-CD3) targeting moiety at the C-terminus of the polypeptide.

With a short, thirteen amino acid linker, the scFv segments were fused onto the C-terminal end of the second DHFR, and the final protein produced by bacterial expression.75

Following expression and purification, these fusion proteins were incubated with the C9- bisMTX dimerizer to observe patterns of oligomerization. Similar to the DHFR2 monomeric proteins, the DHFR2-scFv monomers also formed dimeric or octameric species with the introduction of C9‐bisMTX, depending on the linker present between the two

DHFR proteins.75 Static light-scattering experiments show that the radius of the larger nanorings is approximately 25 nm, suggesting that the primary species present is of octavalent nature. These results were confirmed with Atomic Force Microscopy (AFM), in which the octavalent scFv-nanorings displayed an average diameter between 45‐55 nm

(Figure 1.6).75

Figure 1.6 Atomic Force Microscopy (AFM) of DHFR2-scFv Octomeric CSANs.

Atomic Force Microscopy imagine was performed on DHFR2-anti-CD3 octameric CSANs. Average displayed diameter was 45-55 mm. The above graphic was reprinted with permission from Li, Q.; So, C. R.; Fegan, A.; Cody, V.; Sarikaya, M.; Vallera, D. A.; Wagner, C. R., Chemically self-assembled antibody nanorings (CSANs): design and characterization of an anti-CD3 IgM biomimetic. J Am Chem Soc 2010, 132 (48), 17247- 57. Copyright 2010 American Chemical Society.75

Following the incorporation of anti-CD3 scFvs into the CSAN platforms, our laboratory demonstrated the stable binding of anti-CD3 CSANs to the surface of CD3 expressing T leukemia cells. This formation was shown to be highly stable, forming a prosthetic antigen receptor (PAR). Furthermore PARs, previous studies performed in our lab demonstrated that CSANs displaying single chain antibodies can bind to both the CD3ε subunit of the T-cell-receptor/CD3 complex and CD22 on malignant B cells.78 We demonstrated the multivalent and bispecific format allows the anti-CD3/anti-CD22 CSANs to stably bind to T-cell surfaces for greater than four days, while being easily disassembled on the cell membrane by treatment with the non-toxic FDA approved drug, trimethoprim.

In the presence of CD22+ Raji cells, T-cells modified with anti-CD3/anti-CD22 CSANs were shown to selectively increase the production of interleukin-2 (IL-2) and interferon-γ

(IFN-γ) and initiate cytotoxicity. Importantly the binding exhibited by targeted CSANs showed similar results to the binding affinities, and internalization rates, to those of the parental mAb, UCHT-1.75 Due to the importance of CD3 related T-cell activation, potentially leading to toxicity, we evaluated their proliferation rate and TCR upregulation in response to anti-CD3 CSANs. Importantly, no increase was seen, which is likely due to the scFv being derived from an anti-CD3 mAb reported to exhibit low CD3 stimulation.75

Finally, pioneering work was performed in our lab which utilized a chemically self- assembled nanoring (CSAN) to non-covalently introduce targeting elements to T cell surfaces. For instance, CSANs incorporating anti-EpCAM scFvs and phospholipids were able to hydrophobically insert into T cell membranes, enabling the T cells to selectively recognize and eradicate EpCAM-expressing MCF-7 cells in co-culture with EpCAM- negative U-87 MG cells.79 This reaction was also quickly disassembled in the presence of trimethoprim.

1.4 CONCLUSION

In summarizing the reports to date on modern cancer immunotherapy, three important factors are observed. (1) Antigen selection must be carefully chosen to select epitopes that are only expressed on cancer cells and not healthy tissue. (2) T cell responses in solid tumor applications must be potent and long lasting to elicit full tumor reduction.

However, (3) long lasting, or permanent, therapies exhibit a far greater potential to elicit significant off target toxicities. While CARs are able to selectively target several antigens, their application has thus far been limited to hematological malignencies due to on- target/off-tumor side effects. This is exacerbated by the long-lived nature seen in CAR therapies.

Bispecific T cell engagers (BiTEs) have shown the ability to remedy most of the toxicity seen from CAR therapies, however they exhibit a clearance rate as little as several hours, thus requiring continuous infusion. While attempts have been made to extend this half-life, by PEGylation, BiTEs ultimately run into the issue cytotoxicity due to the increased circulation time.

To address these questions, we have designed a prosthetic antigen receptor (PAR) platform targeting the EpCAM (Chapter 3) and CD133 (Chapter 4) receptors on breast cancer which will be shown to exhibit specific cytotoxic effects. PARs, are stable on T- cells for up to 4 days and rapidly disassemble in the presence of FDA approved

Trimethoprim in the occurrence of unforeseen toxicity. Furthermore, as a means of increasing the modularity of CSANs we engineered a DHFR2 construct fused to a monovalent streptavidin (mSA) that provided a rapid means of evaluating targeting constructs (Chapter 5). MSA CSANs additionally provided a means for universal cell labeling which was further explored in chapter 6. Importantly, prior to the in vivo evaluation of PARs, we successfully demonstrated the in vivo stability and biodistribution of CSANs by PET/CT imaging (chapter 2).

CHAPTER 2: EVALUATING THE IN VIVO STABILITY AND BIODISTRIBUTION OF CHEMICALLY SELF-ASSEMBLED NANORINGS (CSANS)

2.1 INTRODUCTION

Portions of the information presented in the following chapter are reprinted with permission from Shah, R.; Gangar, Petersburg, J.; A. C.; Fegan, A.; Wagner, C. R.;

Kumarapperuma, S. C. In Vivo Evaluation of Site-Specifically PEGylated Chemically

Self-Assembled Protein Nanostructures. Mol Pharm 2016, 13 (7), 2193-203. Copyright

2016 American Chemical Society. The publication was principally written by Jacob

Petersburg, Rachit Shah, and Sidath Kumarapperuma with contributions from coauthors.80

2.1.1 Principles of Positron Emission Tomography (PET)

Medical imaging remains a critical tool for providing the accurate diagnosis and staging of cancer, as well as evaluating the progression and responsiveness of tumor burden to therapy. Evaluation of treatment efficacy through the use of anatomical imaging modalities, primarily magnetic resonance imaging (MRI) and computed tomography (CT), utilizes structural changes within tumors and assesses them in relation to standards, such as Response Evaluation Criteria in Solid Tumors.81 In contrast, positron emission tomography (PET) is a nuclear imaging modality that relies on radiotracers to image tumors based solely on biochemical properties that influence tracer accumulation (i.e. metabolism, proliferation rate, and cell surface markers).82 As biochemical changes manifest in response to therapies far more rapidly than anatomical changes that are visualized by other imaging modalities, PET is able to evaluate efficacy at earlier time points, providing a faster and more sophisticated insight into the efficacy of therapies.82 Importantly this benefit applies

to both preclinical and clinical stages of therapeutic development. PET also has the potential to forecast patient populations that are more likely to have favorable outcomes when evaluated for new, and currently approved, treatments.

PET functions by melding the biochemical properties of a tracer with the physics of positron decay to quantitatively measure, and map, specific biochemical processes in vivo. As with all radiological imaging modalities, radiotracers are required to be injected in a living subject (usually into blood circulation) and distribute within a subject based upon the biological properties of the individual tracer.83 As demonstrated in Figure 2.1, radioisotopes used to label tracers, undergo a process called positron emission decay, which releases a positron that subsequently travels up to a few millimeters in the surrounding tissue before colliding with an electron. The resulting annihilation emits two gamma photons traveling in opposite directions that are oriented 180 degrees from each other.84 Detectors, arranged in a ring configuration, allow for coincidence detection of the emitted photons and provide lines of response with which to reconstruct a tomographic image of the radiotracer distribution within the subject. Due to this quantitative nature, and sensitivity, PET tracers are a powerful tool in evaluating the therapeutic response of tumors.

Figure 2.1 Physics Principles Underlying PET Imaging

Representation of positron emission decay and detection by PET.

In the past decade, small animal imaging has played a crucial role in developing novel therapeutics for the treatment of disease, as well as designing studies to understand the biological underpinnings of cancer.83 The reason being that PET imaging allows for the serial evaluation of the pharmacokinetics (PK) and tissue distribution of tracers in individual animals in an entirely unbiased manner. Prior to PET imaging, models relied completely on using cohorts of animals to quantify the tissue uptake of radiotracers at specific time points to generate a biodistribution “snap shot” valid for only a single point

in time. However, with PET imaging you are able to use the same mouse for multiple static imaging sessions, in addition to continuous dynamic imaging. These efforts have been aided through the development of dedicated small animal PET systems that incorporate CT for anatomical registration.85 In addition, the high resolution afforded by new instrumentation, particularly when combined with the PET/CT based anatomical registration, facilitates accurate tissue localization of the radiotracers and provides a powerful tool for cancer research.

2.1.2 Application of Immuno-Positron Emission Tomography (Immuno-PET) in

Cancer Therapy

Immuno-positron emission tomography (Immuno-PET), the in vivo tracking and quantification of antibody-based radiotracers, has become an attractive tool for diagnostic imaging by virtue of combining the high detection sensitivity and resolution from PET with the specificity of antibodies.10, 83 For example, the capability for noninvasive detection of specific cancer biomarkers can provide the critical information necessary for early diagnosis and prognosis of tumors. Concurrently, immune-PET allows for the quantification of radioactivity uptake, treatment accumulation, and the potential to develop individualized therapy for future treatments.84 Monoclonal antibodies (mAbs) have been approved for use as both diagnostics and therapeutics in a broad range of medical indications, but especially in oncology. In addition, hundreds of new mAbs, engineered mAb fragments, and nontraditional antibody-like scaffolds directed against either validated

or novel tumor targets are under development. Immuno–PET, is an exciting novel option to improve diagnostic imaging, guide mAb-based therapy and help to develop novel immunotherapeutic platforms.

Immuno-PET is commonly referred to as performing “comprehensive immunohistochemical staining in vivo,” for which purpose the mAb, or mAb based fragment, acts as the tracer and is labeled with a positron emitter to enable visualization by

PET.84 In fact, each mAb designed to target a specific tumor cell surface marker or extracellular matrix component is a candidate for use in immuno-PET, allowing the development of a new generation of imaging probes, in addition to existing PET tracers, and suggests the potential for guiding future therapy decisions. Immuno-PET is well suited to confirm antigen expression in non-biopsied lesions to enable selection of patients who are likely to respond to therapy, or to design informed alternative treatment strategies to improve patient response and/or to avoid unnecessary treatment-induced toxicities.86

Additionally, immuno-PET can easily be envisioned as a method to rapidly determine the biodistribution and PKs of new immunotherapies, both during preclinical and clinical development to anticipate potential toxicities.

It is currently postulated that the specificity afforded by antibody-based targeting should both improve tumor detection compared to the small molecule, fluorodeoxyglucose

[18F] (remains the most commonly used PET probe to date), and provide phenotypic information related to primary and metastatic lesions that will guide therapy decisions.87

There are three principle requirements for the effective use of antibodies as immuno-PET

radiotracers: (1) the target antigen must exhibit enriched expression in the tumor, (2) the antibody affinity must be sufficient enough to be stably retained in the tumor, (3) all unbound antibody, or antibody-based fragments must exhibit rapid systemic clearance to maximize the tumor to blood ratio and minimize the time necessary for sufficient image contrast.88 Intact mAbs designed to target specific tumor-associated antigens already meet the first two of these criteria. These mAbs are primarily used for identifying the stage of cancer in patients suspected of recurrent or metastatic disease. However, due to their slow clearance rate the overall clinical effect (regarding clinical imaging) has been limited.89

Recent, advances in protein engineering have facilitated the construction of several antibody-based scaffolds that retain the binding characteristics of intact mAbs while exhibiting PK profiles that are optimized for in vivo diagnostic purposes.89, 90

Importantly, intact mAbs have a long residence time in humans, ranging anywhere from a few days to several weeks. The long circulation life does result in high levels of tumor uptake, however optimal tumor-to-nontumor ratios don’t occur until 2–4 days post injection.90 In stark contrast, mAb based fragments usually have a much faster blood clearance that can occur within as little as a few hours and results in higher tumor-to- nontumor ratios at earlier time points post injection.89 The tradeoff is that the absolute tumor uptake is often lower. These characteristics in general make intact mAbs the format of choice for therapy, while the optimal format for diagnosis is still debated.91

Apart from its imaging capabilities, PET also has the potential for directly quantifying molecular interactions between the tracer and target.81 This is especially

attractive when immuno-PET is being used as a prelude to therapy with an already approved immunotherapy.81 In a personalized therapeutic approach, immuno-PET enables the confirmation of tumor targeting and quantifies the level of therapeutic accumulation

(specifically, the radioactivity uptake) in both the target tissue and non-target tissues. Thus, patients can be selected who have the best chance to benefit from immunotherapy, while treatment schedules can be adapted to improve treatment efficacy and/or reduce toxicity.

Moreover, immuno-PET might also play a role in the efficient selection, characterization, and optimization of novel high-potential therapeutic candidates for further development and optimization.

2.1.3 Utilizing Immuno-PET to Improve Clinical Translation

Despite clinical optimism, it is fair to state that the efficacy of current immunotherapeutic treatments is still quite limited and benefit only a portion of patients.92

The question is how to move forward in identifying the patients with the highest chance of benefit and how to extend the number of patients who are viable candidates for treatment.

In addressing this question, the ability to quantitatively image novel targeted therapeutics at several stages of development and application would be a valuable tool. Furthermore, costs for immunotherapeutic treatments remain extremely high and a method for identifying patients with the highest chance of benefiting from these therapies is desirable.93

From newly developed therapeutics to first-in-man dosing it is critical to learn the ideal dosage for optimal tumor targeting (e.g., saturation of receptors), the uptake in normal tissue and organs (for toxicity anticipation), and the interpatient variation in pharmacokinetics and tumor uptake. Immuno-PET might provide this information in an efficient and safe way, with fewer patients treated at suboptimal doses and step in the right direction for individualized medicine. Especially attractive, is the potential to evaluate new therapeutics targeting a novel tumor target that has not undergone clinical validation.

Furthermore, quantitative immune-PET of already approved mAbs may prove useful in guiding the optimal use of FDA-approved mAbs. In current practice, ex vivo tissue analyses are often performed to confirm target expression and to determine whether patients are eligible for mAb therapy.94 For example, patients with metastatic breast cancer are only eligible for therapy with the anti–human epidermal growth factor receptor (HER)-

2 mAb, trastuzumab, when protein overexpression or gene amplification has been confirmed on a biopsy of the tumor by immunohistochemistry or fluorescence in situ hybridization (roughly 20%–30% of patients).95 It is questionable, however, whether a representative overview of in vivo HER-2 expression status can be obtained by analysis of just one single biopsy.95 It is possible that HER-2 expression in the primary tumor and metastatic lesions differs, or does not remain stable during the course of the disease, for example, upon chemotherapy and/or hormonal therapy. Additionally, repeated or multiple biopsies are not an option, especially because lesions are often difficult to access and heterogeneous in nature.

Finally, pretherapy imaging would likely provide added value for patient selection, as it allows the ability to assess target expression and therapy accumulation in all tumor lesions (as well as normal tissues), noninvasively, quantitatively, and over time (which is extremely valuable for dose selection). Likely, this information will be particularly relevant when the therapy in question is combined with other treatment modalities like chemotherapy, radiotherapy, and checkpoint blockade to find routes for maximum synergism. Ideally, the topographic information detailing tumor extension is obtained to enable assessment of homogeneity of immunotherapy tumor accumulation.

2.1.4 Development of radiolabeled anti-EGFR CSANs

Despite the immense therapeutic potential of both the Chemically Self-assembled

Nanorings (CSANs) and Prosthetic Antigen Receptors (PARs) that were discussed in chapter 1, the in vivo stability and behavior of CSANs has yet to be defined. Due to the high sensitivity of positron emission tomography (PET), we chose to monitor the in vivo behavior of the CSANs using microPET/CT imaging. The successful utility of CSANs as an imaging agent and therapeutic platform in vivo would offer inherent advantages of biocompatibility, ability to precisely manipulate the surface functionalities (protein engineering), as well as size and assembly (and disassembly) of nanostructures by using either chemical or recombinant tools. Hence, the fate and biological effects of CSANs in vivo are critical for future therapeutic applications.

To date we have demonstrated in vitro targeting of various cell surface receptors over-expressed on malignant cancer cells with targeted CSANs.79, 96, 97 In order to evaluate the stability, tissue distribution and targeting of CSANs in vivo, we selected human U-87

MG glioblastoma for a representative mouse xenograft model. Glioblastoma is the most common primary human brain cancer and remains one of the most difficult cancers to treat with current strategies.98 About 60% of the primary glioblastomas are characterized with amplified Epidermal Growth Factor Receptor (EGFR) expression and, recent epidemiological studies have revealed that the EGFR overexpression is of significant prognostic value for predicting survival of glioblastoma patients.99 EGFR is also known to be over-expressed on a variety of other solid cancers such as breast, head and neck, prostate and colorectal cancers.100 Currently a number of small molecule inhibitors, as well as antibodies that block EGFR activation, are at different stages of preclinical and clinical development.101, 102 EGFRs are a class of tyrosine kinase receptors that are key modulators of proliferation and death in both normal and malignant cells. Upon native ligand

(epidermal growth factor, EGF) binding, the receptors form homo/heterodimers triggering intracellular signaling pathways, which lead to cell survival and proliferation, and subsequently undergo clathrin-mediated endocytosis and receptor recycling.103 This rapid internalization of the EGFR has been used effectively in drug delivery applications.104

Therefore, as a proof of concept, we designed and constructed anti-EGFR-CSANs to demonstrate both their in vivo stability and potential for receptor targeted cancer imaging, and therapy, using EGFR positive U-87 MG mouse xenografts.

In the following chapter, we engineered our CSANs to target EGFR. A hexameric peptide (LARLLT), which has been previously reported to successfully target EGFR positive human non-small-cell lung tumors in mice, was recombinantly expressed in the

C-terminus of 1 DHFR2 protein (Anti-EGFR_1DHFR2).105-107 Next, 64Cu was used for

Position Emission Tomography (PET) imaging and to study the biodistribution of CSANs in vivo. In our preliminary studies, greater uptake of the CSANs was observed in highly perfused organs such as the liver and kidneys. This is likely due to the recognition and uptake of the CSANs by the mononuclear phagocyte system (MPS). Correspondingly, surface modification of nanoparticles with polyethylene glycol (PEG) increases the hydrodynamic radius via a so called “hydro-cloud effect”; which has been described as entanglement of PEG chains with hydrogen bonding of water molecules surrounding it.108

Increasing size of PEG chains generates a larger hydro-cloud, which has been successfully used to camouflage and reduce the uptake of biomaterials and nanoparticles by MPS.109,

110 Therefore, in the present study we engineered CSANs bearing different size PEGs chains (Molecular weight of PEG chains = 3000, 10,000 and 20,000 Da) using unnatural amino acid mutagenesis (p-Acetyl Phenylalanine; pAcF) (Figure 1); and evaluated their binding to glioblastoma cell line and uptake by macrophages in vitro. Finally, biodistribution and EGFR targeting ability of the PEGylated CSANs was performed in vivo using PET imaging.

2.2 RESULTS AND DISCUSSION

2.2.1 Synthesis of bis-MTX-DOTA [64Cu]

In order to site specifically and quantitatively radiolabel CSANs, we synthesized a novel DHFR2 protein dimerizer by conjugating bis-MTX to the metal chelator, DOTA

(Scheme 2.1). Previously we reported the synthesis of a versatile DHFR2 dimerizer with an amine terminus (Bis-MTX-NH2), which can be conjugated to a variety of amine reactive payloads.111 In the current study we conjugated p-SCN-Bn-DOTA metal chelator to bis-MTX-NH2 under facile aqueous conditions. The resulting bis-MTX-DOTA was purified by reverse phase flash chromatography and isolated by lyophilization. The LCMS analysis of the product revealed a single peak with the corresponding mass ([MH+] = m/z

1742.8) for bis-MTX-DOTA (Figure 2.2). Having the metal chelator conjugated to bis-

MTX facilitates the chelation of metal radionuclides to the protein dimerizer prior to using it in the self-assembly reaction. This strategy provides a unique non-covalent protein labeling method that avoids non-specific binding of metal ions to proteins. Hence, high radiochemical purities (> 90%) can be achieved for the resulting radiolabeled product.

Scheme 2.1 Synthesis of bis-MTX-DOTA

Schematic for the generation of bis-MTX-DOTA from the reaction of bist-MTX-NH2 woth p-SCN-Bn-DOTA.

Figure 2.2 LC-MS/ESI analysis of Bis-MTX-DOTA

Confirmation of the formation of bis-MTX-DOTA by LC-MS/ESI 47

Due to its moderately long half-life we chose 64Cu (T1/2 = 12.7 hours, β+,

0.653 MeV [17.8 %]) as our positron emitter to evaluate the in vivo fate and tumor targeting ability of CSANs by PET.112 The copper binding ability of bis-MTX-DOTA was evaluated with non-radioactive copper as a surrogate for 64Cu. Bis-MTX-DOTA was titrated with

2+ CuCl2 and found to be completely chelated with 5 eq. of Cu in three hours at room temperature as determined by HPLC-MS (Figure 2.3). After confirming the rapid Cu chelation ability of bis-MTX-DOTA, we followed the general 64Cu labeling conditions from the literature and synthesized the radiolabeled DHFR2 dimerizer.113 Bis-MTX-DOTA

64 was incubated with CuCl2 in 1M sodium acetate buffer (pH 7.0) at 50° C for 30 minutes to obtain the completely (> 99%) radiolabeled bis-MTX-DOTA[64Cu] as determined by iTLC.

Figure 2.3 LC-MS/ESI analysis of Bis-MTX-DOTA chelation of Cu+2

Labeling conditions for Cu chelation was optimized by titrating with Bis-MTX-DOTA and found to be completely labeled with 5 eq. of Cu(II) at room temperature by a shift in 64 mass units. Two peaks eluted closely in the LC-MS indicates [M]+, m/z 1804.9 and [MH]+, m/z 1805.9

2.2.2 Preparation of anti-EGFR-CSANs

Recently, a hexameric peptide (LARLLT) was identified during a campaign to discover EGFR binders by computer-aided design (CAD) and, was successfully shown to target EGFR positive human non-small-cell lung tumors in mice.105, 107 Hence, we chose to utilize this short targeting peptide with moderate binding affinity by fusing it to the

DHFR2 protein. A plasmid encoding DHFR2 was modified via site directed mutagenesis

(QuikChange® Site-Directed Mutagenesis Kit, Stratagene) to express a protein consisting of two Escherichia coli DHFR proteins separated by a single glycine, followed by a C- terminal linker (GGSGG) that connects the EGFR targeting peptide, LARLLT (Figure

2.4A). The protein was expressed in E. coli as a soluble protein using our standard DHFR2 49

expression protocol and purified by methotrexate affinity column chromatography followed by DEAE anion exchange chromatography.114 The typical isolated yield for the purified anti-EGFR-1DHFR2 was found to be around 15-20 mg/L of culture.

Figure 2.4 Schematic representations site-specific PEGylation

A) EGFR targeted DHFR2 fusion protein and B) Met161 to unnatural amino acid (p-acetyl phenylalanine, pAcF) mutated construct of the EGFR targeted DHFR2 fusion protein C) general site-specific PEGylation reaction.

Self-assembly of the EGFR targeted fusion proteins in to CSANs was achieved by incubating the protein with 1.1 equivalents of bis-MTX or bis-MTX-DOTA for 1 h at room

temperature.96 The analysis of the resulting CSANs by SEC confirmed the completion of the self-assembly reaction. The monomeric protein that normally elutes at 33 minutes from the SEC column (Superdex G200, GE Healthcare) disappeared and the peak corresponding to the higher ordered anti-EGFR-CSANs eluted around 20 minutes (Figure 2.5). The size of the CSANs were determined by Dynamic Light Scattering (DLS) and found to increase from 4.5 ± 0.5 nm to 15.4 ± 0.8 nm upon oligomerization (Table 2.1) and was consistent with previously reported values.115 Having confirmed the self-assembly of anti-EGFR

CSANs we then advanced anti-EGFR-1DHFR2 as a programmable platform for in vivo tumor targeting (Figure 2.6).

Figure 2.5 SEC Evaluation of CSAN Formation

Self-assembly of monomeric anti-EGFR-1DHFR2 (green trace) with bis-MTX-DOTA to form CSANs (black trace) observed by Size Exclusion Chromatography (SEC). 51

Table 2.1 DLS Evaluation of CSAN Hydrodynamic Size

Protein construct Average Diameter (nm) anti-EGFR-1DHFR2 4.5 ± 0.5 anti-EGFR-1DHFR2-PEG10k 7.5 ± 0.1 anti-EGFR-1DHFR2-PEG20k 9.0 ± 0.5 anti-EGFR-CSANs 15.4 ± 0.8 anti-EGFR-PEG10k-CSANs 16.8 ± 0.5 anti-EGFR-PEG20k-CSANs 19.6 ± 0.3 Average hydrodynamic diameters of PEGylated and non-PEGylated CSANs determined by DLS (n =10)

Figure 2.6 Schematic for Final CSAN In Vivo Imaging Platform

Schematic representation of programmable and multi-functional CSANs for in vivo tumor targeting.

2.2.3 Preparation of PEGylated anti-EGFR CSANs

One of the major obstacles in the advancement of targeted delivery of nanoparticles is their rapid clearance from the circulation through hepatic and renal clearance mechanisms.116, 117 Typically, once injected, circulating nanoparticles are rapidly

recognized and taken up by phagocytic cells such as macrophages and Kupffer cells, which comprise the reticuloendothelial system (RES). The RES serves to filter the blood for particles and dead cells, and largely reside within the spleen and liver, thus significantly reducing the delivery of nanoparticles to the target tissue or the tumor.117 Renal clearance of the nanoparticles is also a major contributing factor for the rapid loss of the therapeutic or diagnostic nanoparticles from the circulation.118 The resulting elimination of the nanoparticles from the circulation reduces the efficiency of the delivery of the payload to the target tumor site. Indeed, when we performed preliminary in vivo biodistribution experiments with radiolabeled CSANs, we observed rapid clearance and, high accumulation of CSANs in excretory organs such as liver, spleen and kidneys in accordance with the observations for other types of nanoparticles (data not shown).

Various strategies have been developed to extend the circulation half-life of therapeutic proteins by incorporating PEGs or PEG mimetics, covalent or non-covalent linking of albumin, and, by fusion to the Fc region of IgG.119 PEGylation of nanoparticles has been developed to mask nanoparticles thus reducing their recognition by the RES and improving their stealth delivery to the target tissue.120 Moreover, PEGylation of biotherapeutics has been shown to increase their hydrodynamic volume as well as their circulation half-life.119 Therefore, we decided to use PEGylation as our first method to overcome the challenges associated with rapid clearance as well as potential immunogenicity.121-124 Our initial studies revealed that non-specific PEGylation of DHFR2 monomers prevented their assembly into CSANs (data not shown). Furthermore, non-

specific conjugation resulted in various heterogeneous mixtures of formulations that have proven to be ineffective due to their poor in vivo pharmacokinetic and biodistribution properties.108, 125 To address these issues we chose to prepare site specifically PEGylated anti-EGFR-CSANs. While PEGylation of C-terminal cysteine incorporated DHFR2 monomers with maleimido-PEG2k could be self-assembled into CSANs, the PEGylation reaction was incomplete with maximum yields ranging from 60-65%. Our attempts to improve the conjugation reaction proved futile and isolation of the PEGylated product from the unreacted starting material was highly inefficient (data not shown).

To obtain quantitatively PEGylated DHFR2 proteins, we introduced a functional non-natural amino acid into the 1DHFR2 via site-directed mutagenesis of the gene encoding target protein (Figure 2.4B). The residue Met-161 of anti-EGFR-1DHFR2, which is the first residue of the second DHFR unit, was chosen due to its solvent accessibility and distant location from the active site to avoid perturbations on its functional activity. The methionine (161) was replaced with p-acetyl-L-phenylalanine (pAcF) using an orthogonal suppressor aminoacyl-tRNA synthetase/tRNA pair (pEVOL/pAcF) developed by the

Schultz laboratory.126 The selection of pAcF was based on its reactivity towards aminoxy groups to form stable oxime linkages that can be used to install additional functionality to the protein of interest.122-124, 127 The mutant protein was expressed in E. coli as a soluble protein, and purified using methotrexate affinity column chromatography followed by ion exchange chromatography to obtain the pure protein with an isolated yield of 15 mg/L. A single band corresponding to the pure protein was observed by SDS-PAGE analysis

(Figure 2.7A). Electrospray ionization mass spectrometry (ESI-MS) revealed a single peak corresponding to the mass of the anti-EGFR-1DHFR2-pAcF (m/z calculated: 37805; observed: 37807.5) and confirmed a > 99% incorporation efficiency for pAcF at Met-161

(Figure 2.8A).

Figure 2.7 SDS-PAGE analysis of 1DHFR2 constructs

A) DEAE column elution fractions of anti-EGFR-1DHFR2-pAcF (Lanes 1-10); B) 1DHFR2-pAcF (Lane 1) and 1DHFR2-PEG10k (Lane 3); C) 1DHFR2-pAcF (Lane 1), 1DHFR2-PEG10k (Lane 2) and 1DHFR2-PEG20k (Lane 3) [all PEGylated and non- PEGylated protein constructs (B and C) shown in the gel are after performing the column purification]. M = protein ladder

We then prepared protein constructs with increasing hydrodynamic volume by chemically conjugating the anti-EGFR-1DHFR2-pAcF to linear aminooxy-PEGs differing in molecular weight (10 and 20 kDa; Figure 2.4C). Anti-EGFR-1DHFR2-pAcF or

1DHFR2-pAcF proteins (18-22 uM) were incubated with an excess of (10 mM) amino-oxy

PEG. The progress of the reaction was monitored in a time-dependent manner by removing aliquots of the reaction mixture and preparing SDS-PAGE sample for the analysis. More than 95% of the labeling was achieved within 52 hours of reaction across the constructs.

Next, the reaction mixture was loaded onto a DEAE column to remove the unreacted PEG.

After un-retained excess PEG was washed off the column, the protein was eluted using a gradient elution buffer as described in the supplemental material. Site-specific conjugation was confirmed by MALDI-TOF-MS to characterize anti-EGFR-1DHFR2-PEG10k (m/z calculated: 48345; observed: 48347.7, Figure 2.8B) and anti-EGFR-1DHFR2-PEG20k

(m/z calculated: 58445; observed: 58447, Figure 2.8C). The PEGylation efficiency was found to be greater than 98% as determined by SDS-PAGE analysis (Figure 2.7B, C).

Similarly, PEGylated versions of non-targeted control protein constructs (1DHFR2-

PEG10k and 1DHFR2-PEG20k) were also prepared from 1DHFR2-pAcF and characterized by mass spectroscopy (Figure 2.8E, F).

Figure 2.8 Mass spectra of 1DHFR2 protein constructs

A) ESI-MS spectrum of anti-EGFR-1DHFR2-pAcF; B) MALDI-MS spectrum of anti- EGFR-1DHFR2-PEG10k; C) MALDI-MS spectrum of anti-EGFR-1DHFR2-PEG20k; D) ESI-MS spectrum of 1DHFR2-pAcF E) MALDI-MS spectrum of 1DHFR2-PEG10k and F) MALDI-MS spectrum of 1DHFR2-PEG20k

PEGylated-EGFR targeted and PEGylated-non-targeted 1DHFR2 monomeric proteins were self-assembled with bis-MTX-DOTA to form corresponding CSANs and characterized by SEC. Upon incubation of anti-EGFR-1DHFR2-PEG10k and anti-EGFR-

1DHFR2-PEG20k with bis-MTX-DOTA, a peak corresponding to a higher order oligomeric structures with increased hydrodynamic diameter was observed eluting within 57

the void volume around 15 min when compared to the monomer which eluted at 26 and 24 minutes for anti-EGFR-1DHFR2-PEG10k and anti-EGFR-1DHFR2-PEG20k (Figure 2.9).

These results are consistent with our previously observed oligomerization studies of

1DHFR2 with bis-MTX.115 Moreover, the successive decrease in the retention time on the

SEC profile with increasing size of PEG is indicative of the increase in hydrodynamic diameter of PEGylated proteins.

Figure 2.9 Size exclusion chromatography of anti-EGFR CSANs prepared with bis- MTX-DOTA

A) anti-EGFR-1DHFR2-PEG10k B) anti-EGFR-1DHFR2-PEG20k (Black - monomeric protein; Red - Oligomeric CSANs).

DLS studies were carried out to analyze the size distribution of CSANs prepared with 10 and 20 kDa PEGylated CSANs prepared with bis-MTX (Table 2.1). The average diameters of monomeric anti-EGFR-1DHFR2-PEG10k and anti-EGFR-1DHFR2-PEG20k proteins were found to be 7.5 ± 0.1 and 9.0 ± 0.5 nm, respectively, a clear increase in 58

average diameter for the non-PEGylated anti-EGFR-1DHFR2, which was found to be 4.5

± 0.5 nm. Similarly, the average diameter of the corresponding non-PEGylated anti-EGFR-

CSANs increased from 15.4 ± 0.8 to 16.8 ± 0.5 nm when modified with 10 kDa PEG and

19.6 ± 0.3 nm when modified with 20 kDa PEG. The relatively narrow size distribution of

PEGylated and non-PEGylated CSANs observed in DLS studies indicates a relatively homogenous composition of the nanostructures with relatively no aggregate formation (as indicated by no visible particle size formation beyond 100 nM size) (Figure 2.10A).

Similarly, we did not observe significant changes in the average hydrodynamic diameters of the CSANs prepared with bis-MTX-DOTA and EGFR targeted proteins (Figure 2.10B), thus the appended DOTA chelator has negligible impact on the formation and the size of the CSAN.

Figure 2.10 Hydrodynamic diameters distribution of CSANs. A)

DLS analysis of non-PEGylated, and PEGylated, anti-EGFR CSANs generated with bis- MTX (A) and bis-MTX-DOTA (B).

2.2.4 In vitro modeling of RES uptake with mouse macrophages

Based on literature data on in vivo nanoparticle clearance, a protein based nanostructure with an average hydrodynamic diameter of 15-20 nm should in principle avoid renal filtration and escape the renal clearance.116 On the other hand, a site-specifically

PEGylated protein nanostructure with a near homogeneous composition should camouflage the nanostructure and its payload due to the extensive hydration of the PEG and temporarily escape RES recognition.128 An assessment of nanoparticle uptake by 60

macrophages can be a useful method to determine the potential phagocytosis of nanoparticles by the RES.129 Therefore, we prepared non-PEGylated and PEGylated (10 and 20 kDa) anti-EGFR-CSANs with the fluorescent chemical dimerizer, bis-MTX-FITC for in vitro model experiments.111 The ability of mice macrophages (RAW264.7 cells) to internalize fluorescently labeled CSANs was evaluated during a 24-hour period at 37 °C by flow cytometry. The percentage (%) uptake was normalized to non-PEGylated anti-

EGFR-CSANs at 100% (Figure 2.11). A statistically significant decrease in the macrophage uptake by 31% and 47 % was observed upon increasing the size of PEG to 10 and 20 kDa. Thus, PEGylation successfully decreased the uptake of CSANs by macrophages. Importantly, there was no change between the non-pegylated constructs when the EGFR targeting element was removed. Indicating the change seen was solely because of pegylation. The significant decrease in the in vitro macrophage uptake of

PEGylated CSANs (10 and 20 kDa PEG) indicated increased shielding of the oligomers from macrophage uptake in the absence of other contributing factors, such as opsonins or antibodies contained in serum.

Figure 2.11 In vitro macrophage uptake of FITC labeled CSANs

Raw 264.7 mouse macrophage cells were incubated with 1 µM of either non pegylated anti-EGFR-CSANs (green), anti-EGFR-PEG10k-CSANs (red), or anti-EGFR-PEG20k- CSANs (blue), and non-targeted and non-pegylated CSANs (grey) constructed with bis- MTX-FITC for 24 hours at 37° C. Macrophage cells were monitored by flow cytometry to determine the amount of CSAN uptake. Samples were corrected to non-PEGylated anti- EGFR-CSANs at 100%. Statistical significance, *p < 0.05 (n=3).

2.2.5 Characterization of anti-EGFR-CSANs binding

Anti-EGFR-CSANs were shown to specifically bind to the EGFR receptor of interest by use of a cell surface receptor depletion assay. U-87 MG cells were pre-incubated with increasing amounts (0 - 4 µM) of anti-EGFR-CSANs (prepared with anti-EGFR-

1DHFR2 and bis-MTX) for 1 h at 37° C followed by treatment with a high affinity phycoerythrin labeled anti-human EGFR monoclonal antibody at a saturating

concentration (5 µM). Cells were subsequently analyzed by flow cytometry to determine the level of monoclonal antibody binding. We were able to observe, approximately, a 50% decrease in the amount of monoclonal antibody bound to U-87 MG cells, since EGFR undergoes receptor-mediated endocytosis when bound to anti-EGFR-CSANs. These results are consistent with specific binding of the anti-EGFR-CSANs to cell surface expressed EGFR (Figure 2.12).

Figure 2.12 Cell Surface Depletion Assay of EGFR on U-87 MG cells

0 (Red), 0.5 (blue), 1 (green), 2 (orange), and 4 (purple) µM of anti-EGFR-CSANs were treated with U-87 MG cells for 1 hour at 37° C prior to incubation with anti-human EGFR monoclonal antibody conjugated to phycoerythrin for an additional 30 minutes (5 nM). The black trace represents the untreated control.

Furthermore, the binding ability of the non-PEGylated and PEGylated anti-EGFR-

CSANs with EGFR positive human U-87 MG cells was compared using fluorescent anti-

EGFR-CSANs. Cells were incubated with anti-EGFR-CSANs prepared with bis-MTX- 63

FITC at 37° C for 2 h, and the cell binding was quantified. In contrast to non-targeted

CSANs, which demonstrated no U-87 MG cell binding, both PEGylated and non-

PEGylated anti-EGFR-CSANs were found to bind preferably to U-87 MG cells demonstrating that the binding is mediated by the LARLLT peptide. Additionally, both the

PEGylated and non-PEGylated anti-EGFR-CSAN constructs bound U-87 MG cells to a similar extent indicating that target cell binding was not hindered by PEGylation (Figure

2.13).

Figure 2.13 In Vitro U-87 MG Cell Binding Assay

Binding of anti-EGFR-CSANs to U-87 MG cells determined by flow cytometry. All o treatments were performed with 1 µM of CSANs for 1 hour at 37 C (n=3).

2.2.6 Biodistribution of 64Cu labeled CSANs

To characterize the in vivo biodistribution of the anti-EGFR-CSANs, three monomeric constructs were selected for radiolabeling self-assembly. Monomeric anti-

EGFR-1DHFR2, anti-EGFR-1DHFR2-PEG10k and anti-EGFR-1DHFR2-PEG20k were incubated with three equivalents of bis-MTX-DOTA[64Cu] at room temperature to form the relevant 64Cu labeled CSAN, followed by purification with a Bio-Spin6 size exclusion column. The labeling efficiencies of the 64Cu-CSANs were determined by iTLC and found to be greater than 93%.

Figure 2.14 In Vivo CSAN Biodistribution (24 Hours)

Biodistribution (n = 3) of anti-EGFR-PEG20k-CSANs (green), anti-EGFR-PEG10k- CSANs (blue), and anti-EGFR-CSANs (red) at 24 hours post intravenous injection in mice bearing EGFR positive U-87 MG flank tumors. Results are reported as percentage injected dose per gram of tissue. Statistical significance, *p < 0.05 (two tailed T-test).

Athymic nude mice (n = 3) bearing EGFR overexpressing U-87 MG glioblastoma xenografts were intravenously injected through the tail vein with doses of 170 to 200

µCi/µmol of each purified 64Cu-anti-EGFR-CSANs, 64Cu-anti-EGFR-PEG10k-CSANs and 64Cu-anti-EGFR-PEG20k-CSANs. The mice were euthanized at 24 h p.i. or 48 h p.i. and organs were harvested and counted for the amount of residual radioactivity using a

single-tube well counter. At 24 h, mice treated with non-PEGylated 64Cu-anti-EGFR-

CSANs showed a significant accumulation of activity in the liver (34.0 ± 6.7 % ID/g), the spleen (9.4 ± 1.8 % ID/g) and the kidneys (24.4 ± 2.7 % ID/g) while relatively low activity was observed in the tumor (4.9 ± 0.7 % ID/g) and blood (1.1 ± 0.1 % ID/g) (Figure 2.14).

Mice treated with 64Cu-anti-EGFR-PEG10k-CSANs exhibited an almost 2-fold reduction in accumulated activity in the liver (18.8 ± 2.7 % ID/g) and the spleen (5.5 ± 1.4 % ID/g) and a greater than 3 fold reduction in accumulated activity in the kidneys (8.0 ± 0.9 %

ID/g) at 24 h. Radioactivity in the blood (1.5 ± 0.1 % ID/g) and tumor (7.4 ± 0.8 % ID/g) was found to have increased by 28% and 34%, respectively. However, the greatest decrease in accumulated activity within the liver (13.1 ± 0.9 % ID/g), spleen (4.0 ± 0.7 % ID/g) and kidneys (6.4 ± 1.1 % ID/g) was observed with mice treated with 64Cu-anti-EGFR-PEG20k-

CSANs at 24 h. In addition, a significant increase in accumulated activity for the tumor

(8.0 ± 0.9 % ID/g) and blood (2.0 ± 0.3 % ID/g) was observed with the PEG20 construct.

Nevertheless, the tumor to blood ratios remained comparable (~ 4.4:1) across all three constructs at 24 h (Figure 2.15).

Figure 2.15 Tumor to blood ratio of CSAN Constructs

Anti-EGFR-CSANs, anti-EGFR-PEG10K-CSANs and anti-EGFR-PEG20K-CSANs were analyzed for the tumor:blood ratio at 24 and 48 hours post tail vein injection. Ratio was determined using percent-injected dose per gram of tissue (% ID/g) for each tissue (n = 3).

Biodistribution was analyzed at 48 h p.i. to determine the ability of the CSANs to be retained in circulation and thus enhance tumor targeted accumulation. Once again, the activity levels were significantly reduced in the major RES associated organs (i.e. liver, spleen and kidneys) for mice treated with PEGylated 64Cu-anti-EGFR-CSANs and the activity in the tumor was increased (5.6 ± 0.9 % ID/g) (Figure 2.16). Thus, the lower accumulated activity observed for RES associated organs in mice treated with PEGylated

CSANs at 24 h p. i. was also observed at 48 h p.i. Additionally, a minor increase in accumulated activity was observed for the tumor (8.7 ± 1.9 % ID/g with the 64Cu-anti-

EGFR-PEG20k-CSANs) at 48 h p. i. Similar to the results for 24 h p. i., the mean tumor to blood ratios remained comparable (~ 5.3:1) across all three constructs (vide supra) (Figure 68

2.15). These observations suggest that the targeted PEGylated CSANs have a unique drug delivery profile that enables them to be observed in the target tumor more rapidly than non- targeted CSANs while remaining is circulation for at least 48 h.

Figure 2.16 In Vivo CSAN Biodistribution (48 Hours)

Biodistribution (n = 3) of anti-EGFR-PEG20k-CSANs (green), anti-EGFR-PEG10k- CSANs (blue), and anti-EGFR-CSANs (red) at 48 hours post intravenous injection in mice bearing EGFR positive U-87 MG flank tumors. Results are reported as percentage injected dose per gram of tissue. Statistical significance, *p < 0.05 (two tailed T-test).

To ascertain the stability of the injected 64Cu-anti-EGFR-CSANs in vivo, blood samples were collected at 24 h and 48 h. Protein bound and non-protein bound radioactive

64Cu was separated by Bio-spin 6 columns and counted. More than 90% of the 64Cu found in the blood was found to be protein bound (Figure 2.17). Since free bis-MTX-

DOTA[64Cu] is rapidly eliminated within 30 min after i.v. injection, these results are

consistent with the 64Cu-anti-EGFR-CSANs being stable in blood circulation for at least

48 h.

Figure 2.17 In Vivo CSAN Stability Assay

In vivo stability of anti-EGFR-CSANs, anti-EGFR-PEG10k-CSANs, and anti-EGFR- PEG20k-CSANs as represented by percent protein bound 64Cu at 24 and 48 hours post tail vein injection (n = 3).

2.2.7 MicroPET/CT Imaging

Our observations from the biodistribution studies were further supported by in vivo microPET/CT imaging of the EGFR positive U-87 MG xenografts. In this experiment, mice (n = 3) were administered 50 to 70 µCi/µmol of 64Cu labeled EGFR targeted (64Cu- anti-EGFR-PEG20k-CSAN) or non-targeted CSANs (64Cu-PEG20k-CSAN). Post- injection (p.i.) static microPET/CT scans were performed at 1, 4 and 24 h p.i. to investigate the time dependent biodistribution by quantitative region of interest (ROI) analysis. The 70

delivery of 64Cu-anti-EGFR-PEG20k-CSANs to the tumor was observed within the first hour of intravenous administration and could be visualized with excellent image contrast at 4 h (Figure 2.18). The signal intensity for the targeted CSAN was significantly higher

(P < 0.01) at 4 h p.i in the tumor (11.5 ± 0.6 % ID/g) compared to the non-targeted CSAN

(8.4 ± 1.3 % ID/g). However, over the 24 h period the signal intensity in tumor for both non-targeted and targeted constructs reached 11.1 ± 1.9 % ID/g and 11.7 ± 0.2 % ID/g respectively. This observation indicated that at longer time points the accumulation of

CSANs in tumor was independent of the receptor targeting (Figure 2.19). On the other hand, the observed signal intensity in the heart peaked at 1 h p.i. for both constructs and a dynamic intensity of approximately 2% ID/g was maintained after 4 h p.i. suggesting a persistent circulation of CSANs in blood (Figure 2.20).

Figure 2.18 MicroPET/CT Imaging of CSANs at 1, 4 and 24 Hours Post Injection

MicroPET/CT images of coronal (C) and sagittal (S) sections of mice bearing U-87 MG xenografts. Static microPET/CT scans were performed 1, 4 and 24 hours following intravenous tail vein injection of 64Cu-PEG20k-CSANs(above) and 64Cu-anti-EGFR- PEG20k-CSAN (below).

Figure 2.19 Time Dependent CSAN Tumor Accumulation

Accumulation of 64Cu-anti-EGFR-PEG20k-CSANs (Squares) and non-targeted PEG20k- CSANs over 24 h. Data is represented by quantitative pixel analysis of microPET/CT images utilizing regions of interest (ROI) encompassing the tumor (n = 3)

Figure 2.20 Time Dependent CSAN Blood Clearance

Heart tissue percent injected dose for targeted 64Cu-anti-EGFR-PEG20k-CSANs (Squares) and non-targeted 64Cu-PEG20k-CSANs at 1, 4 and 24 h post injection. Data is represented by quantitative pixel analysis of microPET/CT images utilizing regions of interest (ROI) encompassing the heart (n = 3)

The observed incremental accumulation of the signal intensity in the tumor can be attributed to circulating CSANs in the blood pool. Plateauing of the signal intensities for both targeted and non-targeted CSANs at 24 h p.i also indicated that the Enhanced

Permeation Retention effect (EPR) was predominant over targeting at later time points.130

A visible decrease in signal intensity for the liver, kidneys and spleen and a remarkable improvement in the signal compared to the background was observable. Therefore, high contrast images of the tumor could be acquired. Consistent with image analysis, the post- imaging ex-vivo organ activity measurements at 24 h for the same study revealed a significant increase in tumor accumulation (8.0 ± .9 % ID/g) relative to the kidneys (6.4 ±

1.1 % ID/g) or the liver (13.1 ± .9 % ID/g) (Figure 2.21).

Figure 2.21 Targeted and non-Targeted In Vivo Biodistribution (24 Hours)

Organ biodistribution of 64Cu-anti-EGFR-PEG20k-CSANs (Red) and 64Cu-PEG20k- CSANs (Blue) at 24 hours post intravenous injection in mice bearing EGFR positive U-87 MG flank tumors. Results are reported as percentage injected dose per gram of tissue. Statistical significance, *p < 0.05 (two tailed T-test).

2.3 CONCLUSIONS

In summary, we have demonstrated that chemically self-assembled protein based

CSANs are stable and capable of targeting tumor tissue in vivo. Similar to findings from studies of other targeted and PEGylated nanoparticles, the amount of accumulation of the nanoparticles by non-targeted tissues can be suppressed by PEGylation. In addition, while the initial kinetics of accumulation in a mouse xenograft tumor is greater with targeted nanoparticles, including CSANs, over time little difference is observed between the tumor accumulation of targeted and non-targeted nanoparticles.130 This behavior can be attributed to the prolonged circulation of the nanoparticles in blood. 131 Consequently, it appears that

the relatively flat ring structure of CSANs behaves similar to spheroid based nanostructures with regard to the characteristics governing tumor accumulation, such as the EPR effect.132

Radiolabeling of antibodies and other targeting proteins typically depends on conjugation to a chelator of choice at a non-ambient temperature.133 We have shown that targeted and radiolabeled CSANs can be prepared by quantitative labeling of the chemical dimerizer before self-assembly, thus avoiding the potential for induced thermal aggregation and denaturation.

Taken together, our results demonstrate that a designed protein based self- assembled nanostructure can exhibit the characteristics required for in vivo use, including tissue imaging and potentially drug delivery. The modular and multivalent nature of

CSANs allows the targeting ability of ligands with a range of affinities to be evaluated and compared. Moreover, as we have recently demonstrated, the CSANs platform can be used to prepare not only multivalent but bispecific targeting nanoparticles with high specificity,97 thus further enhancing their potential selective tissue targeting ability.

Upon the confirmation of the in vivo stability and biodistribution of CSANs our laboratory proceeded in furthering their application for anti-cancer immunotherapy. In chapter 3 we will discuss the use of CSANs in developing the novel platform, Prosthetic antigen receptors (PARs), for the treatment of breast cancer. Chapter 3 will discuss both the in vitro development as well as their in vivo efficacy when applied to an orthotopic breast cancer model.

2.4 MATERIALS AND METHODS

2.4.1 Materials

64 p-Bn-DOTA-SCN was purchased from Macrocyclics. [ Cu]-Cl2 was obtained from

Department of Medical Physics, University of Wisconsin - Madison, WI, USA. The unnatural amino acid p-acetyl phenylalanine was synthesized and characterized as describe previously with a minor modification to the final deprotection, refluxing overnight with

6N HCl.134 The BL21 (DE3) competent cells were purchased from Invitrogen™.

Aminooxy-PEG-10 kDa and aminooxy-PEG-20 kDa were purchased from NOF America

Corporation. All other chemicals were purchased from Sigma-Aldrich Co. (St. Louis, MO) and used without further purification. Amicon® stirred cells with YM-30 ultrafiltration discs (NMWL 30 kDa) were used in all protein purifications and buffer exchange procedures. All purified proteins were stored in phosphate buffer with 10 % glycerol at -

80 °C until used in experiments. RAW246.7 mouse blood macrophage and U-87 MG human glioblastoma cell lines were obtained from American Type Culture Collection

(ATCC, Rockville MD).

2.4.2 Synthesis of bis-MTX-DOTA

A solution of previously reported DHFR dimerizer,111 bisMTX-NH2 (14.3 mg, 12 µmol) in 0.1 M sodium bicarbonate buffer (1.5 mL, pH 8.5) was added to S-2-(4- isothiocyanatobenzyl)-1,4,7,10-tetraazacyclododecane tetraacetic acid (p-Bn-DOTA-

SCN, 12.4 mg, 18 µmol) and stirred overnight (18 h) at room temperature. The resulting

reaction mixture was loaded on to a Celite® 545 cartridge and purified by reverse phase chromatography on a RediSep Rf-C18 column (43 g) using a Combiflash Rf-200 system

(mobile phase gradient 2% - 50 % acetonitrile/0.1% trifluoroacetic acid in water/0.1% trifluoroacetic acid) to obtain the final product, bis-MTX-DOTA as a lyophilized powder

(21 mg, 98%). The product was characterized by 1HNMR and LC-MS. 1H NMR (500

MHz, DMSO-d6) δ 8.68 (s, 2H), 8.28 (m, 2H), 7.82 (m, 2H), 7.74 (d, J = 8 Hz, 4H), 7.40

(m, 2H), 7.21 (m, 2H), 7.19 (m, 2H), 6.82 (d, J = 8 Hz, 4H), 4.86 (s, 4H), 4.29 (m, 2H),

3.97 (m, 3H), 3.7 - 3.5 (overlapping m, 12H), 3.24 (s, 6H), 3.1 - 3.0 (overlapping m, 20H),

2.64 (s, 2H); 2.36 (m, 6H), 2.18 (m, 6H), 2.09 (m, 6H), 2.05 (m, 4H), 1.91 (m, 4H), 1.59

(m, 4H), 1.40 (m, 4H), 1.24 (m, 4H), 1.15 (m, 4H). ESI-MS calcd. for C80H112N25O18S

[M+H]+ 1742.8, found 1742.8.

Labeling conditions for Cu chelation was optimized by titrating with Bis-MTX-

DOTA and found to be completely labeled with 5 eq. of Cu(II) at room temperature. Two peaks eluted closely in the LC-MS indicates [M]+, m/z 1804.9 and [MH]+, m/z 1805.9

2.4.3 Construction of the plasmid and Unnatural Amino Acid Mutagenesis

Experimental details of the plasmid encoding two cysteine free DHFR fusion proteins connected with 1 amino acid linker (1DHFR2 ) is described previously.114 An EGFR binding peptide sequence (LARLLT) was inserted at the C-terminus of the sequence using non-overlapping primers Fwd_ GGAAGC GGC GGC TTG GCC CGA CTC CTC ACG and Rev_ TTG GCC CGA CTC CTC ACG TAA TTA ATT AAT TCA CTG. The site for

the unnatural amino acid incorporation (M161TAG) was chosen on the basis of surface accessibility of the residue. The site were Quick changed to amber (TAG) stop codon with

Quick change® site directed mutagenesis kit (strategene). The plasmid pEVOL_pAcF encoding amino acyl-tRNA synthetase (MjTyrRS) and tRNACUA evolved from

Methanococcus jannaschi was provided by Dr. Schultz group and has been described previously.126

2.4.4 Protein Expression, purification and characterization

To express 1DHFR2 fusion protein with p-acetyl phenylalanine, plasmid encoding

1DHFR2 M161TAG was co-transformed (Z-COMPETENT E.coli transformation kit,

Zymoresearch) with pEVOL_pAcF into BL21 (DE3) competent E.coli cells. Overnight cultures (50 mL) in LB (LuriaBertani) media were used to inoculate 1 L of LB media containing Chloramphenicol (34 mg/ml) and Ampicillin (50 mg/ml). Cultures were than used to grow at 37 °C until O.D reached 0.57 after which the protein expression was induced by adding 0.3 mM IPTG, 0.04% arabinose and 1 mM pAcF (210 mg), the cultures were than transferred at 30 °C shaking for an additional 18 hrs. The cells were than harvested using centrifuge at 7,500 rpm for 10 minutes. The cells pellet was than resuspended into the lysis buffer containing 1mg/ml of Lysozyme, 20 mM sodium phosphate, 300 mM NaCl 10 mM Imidazole was incubated with gentle shaking for 30 min.

The partially lysed cells were than cooled and sonicated. The cell lysate was than centrifuge at 16,000 rpm for 45 min. The supernatant from the centrifuge was than loaded onto the

Ni-NTA agarose column. The column was washed with buffer A (20 mM sodium phosphate, 300 mM NaCl, 25 mM Imidazole) and eluted with gradient buffer B (20 mM sodium phosphate, 300 mM NaCl, 500 mM Imidazole). The elution fractions were checked for DHFR activity and SDS gel was ran to check the purity of the protein. Fractions containing protein was pooled together and buffer exchanged with 0.1 M PB (Phosphate

Buffer) pH 7.0 using amicon 30kDa. Incorporation of pAcF was confirmed by walters

UPLC Q-TOF mass spectrometry (Calculated m/z 37023.2, found 37020.00).

In the case of 1DHFR2 M161TAG EGFR expression, since EGFR peptide was at the c-terminus of the sequence, the protein was purified using a MTX affinity column. Cell lysate was loaded onto 4 the MTX column and then washed with high salt buffer (50 mM

KH2PO4, 1 mM EDTA and 1M KCl pH 6.0). The protein was then eluted using folate elution buffer (50 mM KH2PO4, 1 mM EDTA, 1M KCl and 5 mM folate pH 9.0). The elution fractions were then analyzed for the DHFR activity. The fractions containing activity were than combined and concentrated with amicon YM- 30. The concentrated protein was then dialyzed overnight and loaded on to a DEAE column to remove folate.

The protein was than eluted with the gradient elution buffer A (10 mM Tris, 10 mM EDTA pH 7.2) and B (Buffer A + 0.5 M KCl). The elution fractions were checked for A280 absorbance and SDS gel was ran to check the purity of the protein. Fractions containing protein was pooled together and buffer exchanged with 0.1 M phosphate buffer pH 7.0 using amicon 30kDa. The final yield of the protein was 17 mg/L and was stored in – 80

°C. Incorporation of pAcF was confirmed by Waters UPLC Q-TOF mass spectrometry

(Calculated m/z 37805.2, found 37807.5).

2.4.5 Site-specific PEGylation of DHFR2 proteins

Unnatural amino acid, p-acetyl phenylalanine incorporated (at M161) anti-EGFR-1DHFR2 or 1DHFR2 (18-22 µM) was incubated with 5 - 10 mM PEG-ONH2 (10 or 20 kDa) at room temperature in phosphate buffer (0.1 M, pH 7.0). The progress of the PEGylation reaction was monitored in a time-dependent manner using SDS-PAGE analysis. More than

95% of the labeling was achieved in approximately 52 hours across all the constructs. The

PEGylated proteins were then purified by DEAE anion exchange chromatography. Single

PEG labeling of the protein was confirmed by MALDI mass spectroscopy for both 10 and

20 kDa PEG.

2.4.6 Self-assembly and Characterization of CSANs

CSANs were prepared by incubating monomeric proteins (5-26 uM) with 1- 3 equivalents of bis-MTX, bis-MTX-DOTA, bis-MTX-DOTA-Cu or bis-MTX-FITC in P500 buffer (50 mM Potassium phosphate, 0.5 M NaCl, 1mM EDTA, pH 7.0) for 30 minutes. Unreacted small molecules were removed by filtration through Amicon centrifugational filter devices

[30 kDa MWCO at 12000 rpm for 3 min (x3 times)]. All proteins were analyzed by size exclusion chromatography (SEC) by passing through a Superdex G200 column connected to a Beckman Coulter HPLC equipped with a diode array detector using P500 buffer as the

mobile phase. The elution was monitored at 280 nm and the relevant protein peak was collected for the DLS analysis. DLS measurements were performed at room temperature

(1 mg/mL in PBS) on a Brookhaven 90Plus Particle Analyzer (Holtzville, NY) with a 35 mW red diode laser.

2.4.7 In Vitro Cell Binding Analysis by Flow Cytometry

U-87 MG cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% FBS, 100 U/mL penicillin, 100 µg/mL streptomycin, and L- glutamine at 37°C in 5% CO2. Protein samples (5-26 uM) were incubated with 1.1 equivalent of bis-MTX-FITC in P500 (50 mM Potassium phosphate, 0.5 M NaCl, 1mM

EDTA pH 7.0 filtered with 0.22 µm filter) for 1 hour at room temperature to generate the following four constructs: CSANS, anti-EGFR-CSANs, anti-EGFR-PEG10k-CSANs, and anti-EGFR-PEG20k-CSANs. All four CSANs (1 µM) were incubated with 1 million EGFR positive U-87 MG cells at 37 °C for 1 hour and subsequently washed three times with PBS.

Samples were filtered to remove any cell aggregate prior to analysis by flow cytometry using a BD LSR II Flow cytometer.

2.4.8 Determination of CSAN Uptake by Raw 264.7 Cells

RAW246.7 mouse blood macrophage cells were cultured in DMEM media supplemented with 10% FBS, 100 U/mL penicillin, 100 µg/mL streptomycin, and L-glutamine at 37°C in 5% CO2. As previously described, CSANS, anti-EGFR-CSANs, anti-EGFR-PEG10k-

CSANs, and anti-EGFR-PEG20k-CSANs constructs were generated using bis-MTX-

FITC. Each CSAN construct (1 µM) was then incubated with 5 million RAW246.7 mouse macrophage cells at 37 °C for 24 hours in a 24 well plate. Macrophage cells were gently scraped off of plates following allotted incubation times and washed 3 times with PBS.

The amount of non-specific binding of CSANs to macrophages was quantified using a BD

LSR II flow cytometer to monitor FITC absorbance. The percent uptake was normalized to anti-EGFR-CSANs at 100%.

2.4.9 Preparation of 64Cu Labeled CSANs

64Cu Labeling of bis-MTX-DOTA was performed by addition of approximately 50 µL of bis-MTX-DOTA to roughly 10 mCi/µmol of 64CuCl2 neutralized in 1M sodium acetate buffer (pH 7.0). The reaction mixture was incubated for 30 minutes at 50° C, following which the extent of 64Cu chelation was determined by iTLC. The resulting excess of bis-

MTX-DOTA[64Cu] was incubated with 0.5 mg of anti-EGFR-1DHFR2, anti-EGFR-

1DHFR2-PEG10k, or anti-EGFR-1DHFR2-PEG20k at room temperature for 30 minutes to prepare each respective CSAN construct. Excess 64Cu was bound by addition of 10 mM ethylenediaminetetraacetic acid for 10 minutes and removed, along with excess bis-MTX-

DOTA[64Cu], by Bio-spin 6 Tris column. The extent of labeling was once again determined by iTLC and found to be greater than 90% for all three constructs. The specific activity for each construct was approximately 1.75 mCi/µmol.

2.4.10 Small Animal PET Imaging and Evaluation of Tissue Biodistribution

All in vivo animal experiments were performed under a protocol approved by the

University of Minnesota Institutional Animal Care and Use Committee in accordance with both federal and institutional regulations. Six weeks old female athymic nude mice (Harlan

Sprague Dawley Inc.) were irradiated with 300 cGy to fully suppress any remaining immune activity and following 24 hours were subcutaneously injected with 3 million U-87

MG cells into the right flank. Two weeks following xenograft implant the tumors were roughly 5 to 10 mm in diameter. Mice were intravenously injected with 50 to 170 µCi/µmol of anti-EGFR-CSANs, anti-EGFR-PEG10k-CSANs, anti-EGFR-PEG20k-CSANs and non-targeted PEG20k-CSANs by tail vein (n = 3), then anesthetized with isoflurane at 4% induction and 1.5% maintenance in oxygen at 1 L min-1 flow rate. Static scans were performed at 1, 4 and 24 hours post injection with 15, 30, and 45 minute scan times respectively using a micro-PET rodent scanner (Siemens Inveon preclinical microPET/CT). PET/computed tomographic (CT) co-registered images were acquired by immobilizing the anesthetized mouse on the micro-PET imaging platform for each static

PET scan followed by a 5 minute with the micro-CT unit (40 micron resolution). Images were co-registered by a modified Feldkamp algorithm and signals in both the tumor and hind leg muscle were quantified utilizing regions of interest (ROI).

Mice utilized for biodistribution studies were given xenograft tumors identically to those implanted for PET studies. Mice were injected intravenously by tail vein with 170 to

200 µCi/µmol of anti-EGFR-CSANs, anti-EGFR-PEG10k-CSANs, and anti-EGFR-

PEG20k-CSANs and sacrificed at 24 and 48 hours post injection (n =3 for all construct at

24 hours, n =3 for all constructs at 48 hours). The blood, liver, spleen, pancreas, heart, kidney, lung, bone, brain, and tumor were collected and weighed prior to measurement with a gamma ray counter. Decay correction was performed to allow for injected dose per gram of tissue calculation.

CHAPTER 3:

ERADICATION OF ESTABLISHED SOLID TUMORS BY

CHEMICALLY SELF-ASSEMBLED NANORING (CSAN)

LABELLED T-CELLS

3.1 INTRODUCTION

Information from the following chapter is currently under review for publication, and is being reproduced in part with permission from: Petersburg, J.; Shen, J.; Csizmar, C. M.;

Murphy, K. A.; Spanier, J.; Gabrielse, K.; Griffith, T. S.; Fife, B.; Wagner, C.R.

Eradication of Established Tumors by Chemically Self-Assembled Nanoring (CSAN) labelled T-cells. The publication was principally written by the current author, Jacob

Petersburg, and Carston Wagner with contributions from the coauthors.

3.1.1 Challenges in Solid Tumor Immunotherapy

Despite the significant strides immunotherapy has achieved in patient outcomes for several hematological malignancies, all attempts to recapitulate this success in solid tumors have produced less than desirable results. The three primary obstacles to translating this success are: (1) the immunosuppressive effect of tumor microenvironments, (2) the limited trafficking of adoptively transferred cells to tumor sites, and (3) the identification of proper tumor associated antigens (often resulting in off target toxicity).

Immunosuppressive Tumor Microenvironment

A significant obstacle in solid tumor immunotherapy is the exhaustion of T cells as a result of the immune suppressive milieu within the tumor microenvironment.135 Cancer patients with advanced disease commonly harbor tumor antigen-specific T cells and antibodies, indicating that simply generating an immune response isn’t sufficient for

disease protection.136 Tumors possess several mechanisms for downregulating anti-tumor responses, including the recruitment and induction of both myeloid derived suppressor cells (MDSC) and regulatory T cell populations (Treg), upregulating inhibitory ligands, and enhancing secretion of anti-inflammatory cytokines (both directly and indirectly) such as Transforming Growth Factor beta (TGFβ) and IL-10.137 By using a combination of these mechanisms, tumors are able to both inhibit antigen presenting cells (APCs) responsible for initiating the T-cell response and directly inhibit effector CD4+ and CD8+ T cells.

Additionally, Treg cells (a subset of CD4+ lymphocytes) have demonstrated significant immunosuppressive capabilities, and high numbers of circulating Treg cells have been correlated with poor prognosis and metastasis in cancer patients.138, 139 In fact the depletion of Tregs has been shown to benefit survival rates and is now a priority of many cancer immunotherapy strategies.140

Turning off T cell function with “immune checkpoint” signals is a natural mechanism used to dampen cell signaling downstream of the T cell receptor (TCR) upon recognition of a cognate antigen, preventing excessive immune activation and subsequent damage to endogenous tissue. The most notable immune checkpoint example is CTLA-4, a molecule on the surface of T lymphocytes, which is homologous to the T cell costimulatory ligand CD28. Both CTLA-4 and CD28 bind to CD80 and CD86 (B7-1 and

B7-2) on APCs; however, CTLA-4 binds with a greater affinity than CD28 and produces and inhibitory effect, whereas CD28 sends a stimulatory signal. Importantly, immune checkpoint molecules have been identified on tumor infiltrating lymphocytes (TILs)

exhibiting an impaired ability to secrete cytokines in response to tumor antigen, thus exhibiting exhaustion.141 When CTLA-4 signaling is blocked by a monoclonal antibody

(such as Ipilimumab), its inhibition of effector T cells is released, eliciting a powerful anti- tumor response.142 However, the anti-tumor effects of CTLA-4 blockade are accompanied by a strong autoimmune response, likely due to the parallel expression of CTLA-4 on Treg cells.143 Blockade of PD-1 with the FDA approved drugs Pembrolizumab and Nivolumab or its ligand, B7-H1 (PDL1) with Atezolizumab, have also been found to be effective in mouse models and clinical trials, with a lower induction of autoimmunity as compared to

CTLA-4 blockade.144 Several additional immune checkpoint moieties exist on dysfunctional T cells including LAG-3, Tim-3 and Adenosine 2a Receptor (A2aR). Taken together it is clear that a promising avenue of future research will involve the evaluation of combination therapies that combine the adoptive transfer of T cells with the increasing arsenal of immunomodulatory agents that target T cell inhibitory molecules such as CTLA-

4 and PD-1.

Limited Tumor Infiltration

While checkpoint inhibitors have shown great success in many cases they are still unable to induce anti-tumor activity in “cold tumors” (tumors lacking pre-existing immune cell infiltrate) and limited to only a small subset of cancer patients. In the future, the main challenge will be generating T cell responses in patients with immunologically “cold” tumors by effectively trafficking engineered T cells to sites of disease. Significant work to decipher the mechanisms for T cell trafficking has revealed receptors, soluble factors, and

adhesion molecules important for the mediation of T cell trafficking,145 and pioneering work to engineer chemokine receptor expression on T cells has highlighted the considerable promise of this approach for enhancing anti-tumor activity.146 However, significant challenges still remain with regard to understanding the obstacles and mechanisms impacting the effective T cell infiltration of solid tumors.147 For example, fever significantly enhances the adherence of T cells to the tumor microvasculature,148 indicating that the induction of hyperthermia may augment the efficacy of adoptive T cell transfer; parenthetically, a portion of the beneficial effects reported following IL-2 co- administration with T cells may also be due to pyrogenic effects.

Identification of Solid Tumor Antigens

The ideal target antigen on cancer cells would be fully restricted to the tumor cell and provide a critical survival signal to the malignant clone. Unfortunately, the majority of targets available for immunotherapy platforms have shared expression between cancerous and normal tissues, with some degree of “on-target/off-tumor” toxicity occurring on nonpathogenic tissues through engagement of “off-tumor” target antigen.59 This is particularly the case in solid tumors as antigens associated with solid tumors are often also expressed on normal tissues.59, 70, 149, 150 The severity of reported events range from manageable lineage depletion (B-cell aplasia) to highly severe toxicity that can be fatal.

“On-target/off-tumor” recognition is often seen in a very predictable manner, in a variety of organ systems, including gastrointestinal, hematologic, and pulmonary. For example,

the targeting of normal B cells by CD19-specific CAR T cells is known to result in B-cell aplasia requiring intermittent infusion of pooled immunoglobulins as prophylaxis from infectious complications.151

Unique to cellular therapies is the extraordinary long-term persistence, up to a decade, of adoptive cellular therapy in human trials.152, 153 Ultimately, this persistence extends the timeline for occurrence of potential toxicities far beyond that of conventional small-molecule pharmaceuticals and resulting toxicities of therapeutic cell infusion may be immediate, delayed, mild, severe, and/or persist for the entire lifespan of the engineered immune cell. Adverse events encountered thus far, include cytokine release syndrome

(CRS), neurologic toxicity, “on target/off tumor” recognition resulting in solid organ damage, and anaphylaxis. While there are other theoretical toxicities (including clonal expansion secondary to insertional oncogenesis), these have not been clinically evident thus far.151

To date, the most prevalent adverse effect following infusion of CAR T cells, or any potent immune cell therapy, is the onset of immune activation, known as cytokine release syndrome (CRS).154 Once immunotherapeutic applications had been improved to the point of generating significant T cell activation, rapid expansion, cytokine production, and most notably dramatic antitumor responses in patients with hematologic malignancies, there was a corresponding increase in the similarly impressive and potentially life- threatening CRS.66 The hallmark of CRS is immune activation resulting in elevated inflammatory cytokines ranging from mild CRS (constitutional symptoms and/or grade-2

organ toxicity) to severe CRS (grade ≥3 organ toxicity, aggressive clinical intervention, and/or potentially life threatening).65 Elevated cytokine levels have additionally been indicated as the event responsible for neurological toxicities reported in patients receiving

CD19-specific CAR T cells.66, 67 The presence of CRS predominantly correlates with the expansion and progressive immune activation of adoptively transferred cells. Interestingly, it has been demonstrated that the disease burden at the time of infusion dictates the degree of CRS severity as patients with high tumor burden experience a more severe CRS. In the context of hematologic malignancies, the vast majority of patients who respond to treatment exhibit at least mild CRS (fever) following CAR T-cell infusion. While the systemic infusion of corticosteroids has been shown to rapidly reverse symptoms of severe

CRS without compromising initial antitumor response, prolonged use of corticosteroids results in the ablation of adoptively transferred CAR T-cell populations, and potentially limits their long-term antileukemia effect.66 For this reason, the use of IL-6 receptor (IL-

6R) blockade with the FDA-approved mAb, tocilizumab is currently used as front-line treatment for the near-immediate reversal of CRS.151 However, despite this advance, IL-

6R blockade has still shown decreases in resulting antitumor efficacy when used early in therapy.

The majority of genetically modified T cells utilized in clinical trials contain antigen-recognition domains derived from murine mAb.59 Therefore, it comes as little surprise that both cellular and humoral rejection of CAR T cells have been demonstrated due to the immunogenicity of foreign protein.155 This is of particular concern for CAR

therapy due to the long-lived nature of these epitope expressing cells. Efforts remain ongoing to humanize the components of expressed proteins to prevent the generation of neutralizing antibodies, with a goal of improving persistence and, potentially, efficacy.

However, the more concerning, and immediate, toxicity is acute anaphylaxis as a result of host recognition of infused foreign components. Patients receiving genetically modified T cells require diligent surveillance, prompt recognition, and immediate treatment of this life- threatening side effect.

To minimize these toxicities, yet maintain their significant potency, a number of techniques have been developed to either enhance tumor specificity or regulate their persistence. Both transient mRNA transfection and suicide genes have been used to successfully regulate the lifetime of CAR T-cells while dual targeting CAR T-cells have been shown to increase tumor specificity.156, 157 The development of small molecule strategies which either control the formation of the functional CAR complex or the binding event to the target antigen has also shown promise as an approach to address potential toxicities.158, 159 Unfortunately, attempts thus far, to eliminate the “permanence” of genetic engineering have either resulted in only a partial decrease in expression, or significantly lowered the efficacy of the intended therapy.

In practice, the use of bispecific molecules has also demonstrated significant potential to harness T-cells for specific targeted killing of cancer cells for immunotherapy, without eliciting the drawbacks associated with genetically engineering T cells.160 The most well-known of these bispecific designs are Bispecific T-cell Engagers (BiTEs). The

first FDA approved BiTE, Blinatumomab, targets both the tumor antigen CD19 and the T cell receptor CD3 and is used for the treatment of refractory acute lymphoblastic leukemia.160 While BiTEs have achieved excellent success, they are typically constructed from monovalent single chain antibodies (scFvs) for the respective receptors, which greatly limits their avidity for binding both the T-cell and target cancer antigen. In addition to the relatively low avidity, the small size of BiTEs results in their rapid in vivo elimination

(mins), thus requiring continuous infusion.54, 161, 162 There have been advances to increase the circulating half-life of BiTEs, such as pegylation, however with the increased circulation time there is still the potential to elicit the same toxicities seen in CARs, such as CRS and other off-target toxicities, as a result of their long term persistence.161, 163 In the unfortunate event that this would occur, a safe and effective method of rapidly triggering elimination of the bispecific agent would prove advantageous.

3.1.2 αEpCAM/αCD3 PAR Development

As an alternative approach to current CAR and bispecific antibody agents, we explored the use of prosthetic antigen receptors (PARs) as a non-genetic system for directing selective cell-cell interactions. As discussed in Chapter 1, PARs are formed by fusing an scFv to two E. Coli dihydrofolate reductase (DHFR2) molecules that spontaneously assemble into multivalent chemically self-assembled nanorings (CSANs) upon the addition of a chemical dimerizer, bis-methotrexate (bisMTX).75, 164 The combination of an anti-CD3 fusion protein with a tumor targeting fusion protein results in

the formation of bispecific, multivalent, CSANs that stably bind to CD3+ T cell surfaces, generating PARs, and selectively target tumor cells.78 PAR therapy has several unique innovations, such as the capability of quickly labeling T cell membranes in a matter of minutes and is stable on the cell surface for multiple days.78 Importantly, our approach has the capability to remove PARs from T cells by incubation with the FDA approved antibiotic trimethoprim, at clinically relevant concentrations, allowing pharmacological deactivation of T cells in the event of any toxicities or off-target effects.79 Additionally, as

PAR targeting is multivalent, labeled cells display excellent tumor homing and we envision they would combine well with current checkpoint therapies to overcome the immunosuppressive tumor microenvironment. Due to these innovations, the application of

PAR therapy to solid tumors cells offers significant potential. Herein, we have characterized the use of PARs T cells to target solid tumors expressing the EpCAM receptor for anti-cancer cell directed immunotherapy using an orthotopic xenograft model

(Figure 3.1).

Figure 3.1 Prosthetic Antigen Receptor (PAR) Schematic.

Bispecific CSANs are constructed from anti-CD3 DHFR2, anti-EpCAM DHFR2, and BisMTX to form multivalent nanorings. Effector T-cells are engaged with bispecific CSANs which tightly bind, due to their high avidity, and generate PARs that facilitate the cell lysis of target cells. Additionally, the use of clinically relevant concentrations of trimethoprim is able to disassemble CSANs on the cell surface.

3.1.3 Relevance of Targeting the EpCAM Receptor

Epithelial cell adhesion molecule (EpCAM) is a single transmembrane glycoprotein that is involved in intercellular adhesion.165 The epithelial cell adhesion molecule (EpCAM, CD326) receptor is a viable target for anti-cancer bispecific antibodies,166-168 as the EpCAM receptor is overexpressed on a variety of different tumor cell types including breast, ovarian, colon, pancreatic, prostate, and lung cancer (Figure

3.2).169-171 Even more attractive is the EpCAM receptor expression on cancer stem cells

(CSCs), which are thought to be responsible for the reemergence of tumors in patients that have been in remission.172 While normal tissues, such as the colon, express EpCAM, recent 96

data suggest that these receptors are found predominately along the basolateral surface and are therefore inaccessible to EpCAM-targeting drugs.170, 173, 174 However, the irregular interaction of cells within tumors and dysregulation of EpCAM expression has been shown to make EpCAM more available for targeting in a neoplastic context. In support of this assertion, transgenic mice expressing human EpCAM do not exhibit significant binding by anti-EpCAM antibodies to normal tissues, while retaining high binding to EpCAM+ tumors.175

Figure 3.2 Carcinoma Specific EpCAM Expression

Figure adapted from CBioPortal: compiled clinical data for EpCAM expression across carcinoma types, as quantified by RNA Seq.

Accordingly, anti-EpCAM bispecific antibodies have shown promise in preclinical and clinical studies.176, 177 The trifunctional anti-EpCAM/anti-CD3 antibody, catumaxomab, has shown clinical efficacy against ovarian ascites and has recently received

European approval.168 Nevertheless, the Fc domain of catumaxomab has been associated with liver toxicity by activation of Kupfer cells.178 Amgen, Inc. (Thousand Oaks, CA) has also advanced an anti-EpCAM/anti-CD3 BiTe, solitomab, into the clinic for solid tumors.179-181 Unfortunately, while tumor growth was suppressed, there were associated dose-limiting toxicities that prevented drug concentrations from approaching the IC90 values during continuous infusion.182 To address these issues, anti-EpCAM CART cells prepared by transient RNA transfection have been generated.183 While anti-EpCAM CART cells demonstrated the suppression of tumor growth, they’ve been unable to completely eradicate tumors, resulting in tumor growth rebounding when dosing with the anti-EpCAM

RNA transfected T cells was stopped.183 On-going clinical trials with anti-EpCAM CART cell therapy are underway in order to address the efficacy of this approach. Nevertheless, the development of a less evasive, more efficacious, and safe alternative for the targeting of EpCAM-expressing cancer cells by T cells could significantly advance solid tumor immunotherapy.

3.2 RESULTS AND DISCUSSION

3.2.1 Preparation of αEpCAM/αCD3 bispecific CSANs

The development and preparation of DHFR2-anti-EpCAM (DHFR2-αEpCAM) and

DHFR2-anti-CD3 (DHFR2-αCD3) proteins have been previously described.75, 79 Once prepared the purified DHFR2-αEpCAM and DHFR2-αCD3 fusion proteins were incubated with bisMTX dimerizer (1:1:2.2 equivalents) for 30 minutes to form αEpCAM/αCD3

CSANs which were characterized by size exclusion chromatography (Figure 3.3A). These octameric rings are generated by random combinations, and statistically calculated to be greater than ninety-nine percent bispecific in makeup.78 As expected bispecific CSANs generate larger, octameric species, which eluted at 18.5 minutes with nearly 100%

2 oligomerization whereas the smaller DHFR -αEpCAM and DHFR2-αCD3 monomer proteins eluted at 28.5 minutes. Similar to previously prepared CSANs, the bispecific

CSANs were found by dynamic light scattering (DLS) to exhibit a higher hydrodynamic radius, 16.1 ± 0.1 nM (Figure 3.3B), compared to those of the monomeric proteins,

DHFR2-αEpCAM and DHFR2-αCD3, at 9.7 ± 0.1 nM (Figure 3.3C) and 9.6 ± 0.1 nM

(Figure 3.3D), respectively.78, 80 Cryo-transmission electron microscopy directly visualized CSAN ring formation and reinforced these size dimensions with a mean diameter of 19.8 ± 4.3 nM (Figure 3.3E-F). Importantly, the self-assembled

αEpCAM/αCD3 CSANs exhibited the same size dimensions (20-25 nM diameter) and thus polyvalency (7-10) found for previous bispecific CSANs.75, 79

Figure 3.3 Bispecific CSAN characterization

(A) The assembly of bispecific CSANs was characterized by size exclusion chromatography. Blue curve; anti-CD3 DHFR2 monomer; red curve: anti-EpCAM DHFR2 monomer; black curve: bispecific CSANs. The hydrodynamic size of bispecific CSANs was measured by dynamic light scattering: (B) anti-EpCAM/anti-CD3 bispecific CSANSs (16.1 ± 0.1 nM), (C) anti-EpCAM DHFR2 monomer (9.7 ± 0.1 nM) and (D) anti-CD3 DHFR2 monomer (9.6 ± 0.1 nM). Cryo-Transmission Electron Microscopy (Cryo-TEM): (E) Cryo- TEM image and (F) the corresponding size distribution analysis.

100

Once we confirmed ring formation, binding studies were performed using flow cytometry to ensure the functionality of CSAN antigen targeting. αEpCAM/αCD3 CSANs,

αCD3 monospecific CSANs, and αEpCAM monospecific CSANs were generated using a previously described fluorescein-labeled bisMTX (FITC-bisMTX) dimerizer.76 The

αEpCAM/αCD3 CSANs were incubated with either the breast cancer cell line MCF-7

(EpCAM+) cells or peripheral blood mononuclear cells (PBMCs), containing T-cells which express the CD3 receptor. Binding of the bispecific CSANs to both MCF-7 cells and

PBMCs was observed (Figure 3.4). Additionally, upon analysis of anti-EpCAM binding affinity we were able to confirm the importance of the avidity affect in CSAN constructs

2 (Figure 3.5). As a monomeric unit anti-EpCAM DHFR bound with a Kd of 54.4 ± 1.1 nM while dimeric αEpCAM CSANs bound with an affinity of 26.2 ± 0.9 nM and octomeric

αEpCAM CSANs bound with a Kd of 10.9 ± 0.5 nM. Interestingly, when we characterized

MCF-7 cells that had been chronically cultured in the presence of Tamoxifen (an in vitro model designed to replicate acquired Tamoxifen resistance in breast cancer following

Tamoxifen therapy) we found that EpCAM was still highly expressed (Figure 3.6), indicating that EpCAM targeted PAR therapy would still be viable in a Tamoxifen resistant breast cancer cell line.

101

Figure 3.4 Binding Characterization of CSANs.

FITC labeled CSANs which were generated utilizing FITC-bisMTX and then analyzed by flow cytometry to monitor binding to (A) CD3+ PBMC cells and (B) EpCAM+ MCF-7 cells.

Figure 3.5 Binding of αEpCAM CSANs to MCF-7 Breast Cancer Cells.

Flow cytometric competitive binding assay was applied to determine the disassociation constant of 1DDEpCAM monomer (circles; Kd 54.4 ± 1.1 nM), EpCAM Dimeric CSANs (triangles; Kd 26.2 ± 0.9 nM) and EpCAM octavalent CSANs (squares; Kd 10.9 ± 0.5 nM) to breast cancer MCF-7 Cells.

102

Additionally, since EpCAM is known to not undergo internalization, we utilized confocal microscopy to confirm that αEpCAM CSANs were not internalized by MCF-7 cells to any significant extent (Figure 3.7). Similar to previous studies with αCD22/αCD3 CSANs,

αEpCAM/αCD3 CSANs stably bound to the surface of PBMCs, with only a 16% loss of nanorings from the cell surface observed after three days (Figure 3.8A).

Figure 3.6 αEpCAM CSAN binding to Tamoxifen Resistant Breast Cancer Cells.

FITC Labelled αEpCAM CSANs were generated by nonspecific labeling utilizing NHS- FITC were analyzed by flow cytometry to monitor binding tamoxifen resistance MCF-7 Breast Cancer Cells.

103

Figure 3.7 CSAN internalization evaluation by confocal microscopy.

Evaluation CSAN Binding to MCF-7 EpCAM+ cells. (A-B) Treatment of MCF-7 cells at 4°C. (A) MCF-7 cells in the absence of CSAN treatment. (B) MCF-7 cells treated with anti- EpCAM CSANs generated with FITC-bisMTX. (C-D) Treatment of MCF-7 cells at 37°C. (C) MCF-7 cells in the absence of CSAN treatment. (D) MCF-7 cells treated with anti- EpCAM CSANs generated with FITC-bisMTX.

Figure 3.8 CSAN stability study on T-cell membranes.

(A) Time course stability study measuring the % inhibition of anti-CD3 Monoclonal antibody binding to PBMCs. Cells were coated with either Bispecific CSANs or anti- DHFR2 monomer on day zero and the media was changed each subsequent day prior to determining the level of antibody binding. (B) The disassembly of Bispecific CSANs on the surface of the T-cell by increasing trimethoprim concentration. 104

As previously discussed, a unique feature of the PAR T-cell approach is our ability to pharmacologically disassemble the rings in the presence of the FDA approved drug, trimethoprim.78, 79 To characterize the ability of trimethoprim to disassemble

αEpCAM/αCD3 CSANs bound to the T-cells, we incubated PBMCs with the bispecific

CSANs (100 nM) prepared with FITC-bisMTX. After washing the cells, the

αEpCAM/αCD3 CSANs modified T-cells were incubated with variable concentrations of trimethoprim for 30 min. The percentage of CSANs remaining on the cell surface was then monitored by flow cytometry. Similar to previous studies, at a trimethoprim concentration of 3.9 µM, approximately 50% of the CSANs were removed from the surface, while at a concentration of 60 µM approximately 90% of the αEpCAM/αCD3 CSANs were removed from the cell surface (Figure 3.8B).78

3.2.2 In Vitro T-cell Activation and Tumor Cell Cytotoxicity

Cytotoxicity studies were performed with unactivated T-cells treated with increasing αEpCAM/αCD3 concentrations for 30 minutes, and then incubated with target

MCF-7 cells for 24 hours at an effector-to-target ratio of 10:1 (Figure 3.9A). Maximal cytotoxicity was observed for cells incubated with 50 nM of the αEpCAM/αCD3 CSANs, with significant cytotoxicity observed at a concentration of 10 nM. At a fixed CSAN concentration of 50 nM, a 4-fold specific lysis was achieved at an effector to target ratio of

10:1 and 20:1 using bispecific CSANs (Figure 3.9B).

105

Figure 3.9 In Vitro Cytotoxicity of αEpCAM/αCD3 CSANs

Target MCF-7 cell lysis was evaluated at a (A) set 10:1 E:T ratio with increasing concentrations of CSANs as well as at a (B) set concentration of CSANs (50 nM) with increasing E:T ratio. Data shown was obtained from one donor (n=3), but representative of three donors. *P<0.05 with respect to anti-EpCAM CSAN and no treatment controls, by 2-tailed Student’s t test.

Figure 3.10 In Vitro Cell Killing with Moc31 Competition demonstrating killing is EpCAM Mediated.

Targeted Cell Killing of MCF-7 (EpCAM+) cells using unactivated T-cells with increasing concentration of CSANs at a set 10:1 E:T ratio. Addition of 250 nM Moc31 (Parent EpCAM mAb) was shown to completely block cell killing of bispecific CSANs.

106

To further confirm the specificity of αEpCAM/αCD3 CSAN targeting, we carried out competition studies using the parental αEpCAM mAb, Moc31. PBMCs were treated with increasing αEpCAM/αCD3 CSAN concentrations and then incubated with MCF-7 cells at an effector-to-target ratio of 10:1 for 24 hours with or without Moc31 (Figure

3.10). Inclusion of Moc31 significantly decreased target cell killing to a level comparable to the non-targeted control, αCD3 monospecific CSANs. These data suggest the αEpCAM scFv of the αEpCAM/αCD3 CSANs selectively targets the EpCAM receptor and is required to bind for target cell killing.

Time-lapse microscopy was performed using live cell imaging methods to observe selective cell killing events in the presence of EpCAM+ MCF-7 cells co-cultured with the

EpCAM negative U-87 MG glioblastoma cells (Figure 3.11). In addition to observing the interactions between the target and effector cells, we wanted to observe the selective cytotoxicity of the bispecific CSAN-treated T-cells against EpCAM+ cells without affecting the growth and proliferation of an EpCAM negative cell line. Over the course of

25 hours, the redirected T-cells were selectively attached to and interacted with the

EpCAM+ cell line leading to cell death while leaving EpCAM negative cells unharmed.

Similarly, when in the presence of untreated T-cells neither cell line was compromised but instead continued to grow and divide normally (Figure 3.11).

107

Figure 3.11 Cell Killing visualized by time lapse microscopy.

Time Lapse Microscopy of co-cultured MCF-7 (EpCAM+) and U-87 (EpCAM-) cells incubated with PBMCs at a 10:1 E:T ratio with bispecific CSANs. 108

Figure 3.12 In Vitro PBMC Activation Marker Upregulation Assay

Unactivated PBMCs were co-cultured with media, monospecific CSANs or bispecific CSANs in the presence or absence of target MCF-7 cells. CD69 expression levels was measured on (A) CD4+ T cells and (B) CD8+ T cells following a 12-hour incubation while CD25 expression was measured on (C) CD4+ Tells and (D) CD8+ T cells following a 24 hour incubation. CD4+ and CD8+ T-cells were gated on the lymphocyte population as determined by the forward and side scatter as well as live/dead cell dye. Data shown was obtained from one donor (n=3), but representative of three donors. *P<0.05 with respect to anti-EpCAM CSAN and no treatment controls, by 2-tailed Student’s t test.

As observed with αCD22/αCD3 PAR T-cells, full activation of the αEpCAM/αCD3

PAR T-cells was dependent on the presence of antigen-positive tumor cells. PBMC T-cell signaling activation was monitored by measuring CD69 and CD25 upregulation following cytotoxicity assays, as well as the amount of IL-2 and IFN-γ produced. Both CD8+ and

109

CD4+ T-cells increased CD69 (Figure 3.12A-B) and CD25 expression (Figure 3.12C-D) in the presence of either αCD3 or αEpCAM/αCD3 CSANs. However, for both CD4+ and

CD8+ T-cells labeled with αEpCAM/αCD3 CSANs, the presence of EpCAM+ MCF-7 cells led to significantly higher levels of CD69+CD25+ populations within CD4+ and CD8+ T- cells. Similarly, when PBMCs were treated with αEpCAM/αCD3 CSANs in the presence of MCF-7 cells, the production of IL-2 (Figure 3.13A) and IFN-γ (Figure 3.13B) was enhanced by 7.0- and 2.7-fold, respectively. This observation is consistent with previous studies of the parental monoclonal antibody, UCHT1, which, unlike other αCD3 antibodies

(e.g. OKT-3), is unable to induce IL-2 production directly.184, 185 Additionally, IL-2 and

IFN-γ production was shown to be dose dependent on the concentration of αEpCAM/αCD3

CSANs (Figure 3.14A-B) and correlates well with the selective cytotoxicity of the T-cells toward MCF-7 cells when in the presence of αEpCAM/αCD3 CSANs (vide supra). Of particular note, the level of increased CD69, CD25, and IFN-γ expression was comparable to αCD22/αCD3 CSANs.78 Therefore, even though the T-cell donor was different and the targeting scFv for the bispecific CSANs was different, the effect of the incorporated αCD3 svFv when interacting with the T-cells remained the same. Thus, the degree of scFv polyvalent display by the two bispecific CSANs appears to be proportional.

110

Figure 3.13 In Vitro Cytokine Release Assay

Unactivated PBMCs were co-cultured with media, monospecific CSANs or bispecific CSANs in the presence or absence of target MCF-7 cells. Following the 24 hour incubation, the media was analyzed for (A) IL-2 and (BH) IFN-γ by ELISA. Data shown was obtained from one donor (n=3), but representative of three donors. *P<0.05 with respect to anti-EpCAM CSAN and no treatment controls, by 2-tailed Student’s t test.

Figure 3.14 PARs dose dependent cytokine production.

Unactivated PBMCs were co-cultured with media, monospecific CSANs or bispecific CSANs in the presence or absence of target MCF-7 cells for 24 hours with increasing concentration of CSANs. Following incubation the media was analyzed for (A) IL-2 and (B) IFN-γ by ELISA. Data shown was obtained from one donor, but representative of three donors. *P<0.05 with respect to antiEpCAM CSAN and no treatment controls. 111

Our results are also comparable to the αEpCAM/αCD3 BiTe, MT110. For instance, the level of CD69 expression (40%) at non-toxic doses was similar. Efficient cell killing over 24 hours was also observed for both αEpCAM/αCD3 PARs and MT110, resulting in

CD69 expression levels of 80%, and IL-2 production increase of 3.5-fold.49, 186 However, the total amount of IFN-γ and IL-2 produced by the PBMCs in the presence of MT-110 and a gastric cell carcinoma was found to be 5- to 10-fold greater than αEpCAM/αCD3

PARs.49 Additionally, unlike MT100, αEpCAM/αCD3 PAR T-cells produced significantly greater amounts of IL-2 (1.4-fold) than IFN-γ, in vitro, when in the presence of the target tissue.

An important consideration in immunotherapeutic applications is the activation of tumor resident T-Regulator Cells (Treg). Tregs, formerly known as suppressor T cells, are a subpopulation of T cells which modulate the immune system, maintain tolerance to self- antigens, and prevent autoimmune disease. Tregs are immunosuppressive and generally suppress or downregulate induction and proliferation of effector T cells. Tregs express the biomarkers CD4, FOXP3, and CD25 and are thought to be derived from the same lineage as naïve CD4 cells. Because Treg cells also express CD3 they can commonly be activated in bispecific constructs which can be a concern for tumor immunotherapy do to their potent immune suppression. To evaluate the potential for Treg activation we evaluated unstimulated PBMCs for the upregulation of FOXP3 and found only a slight increase from 2.9% to 4.4%, however the increase was statistically significant (Figure

3.15). Fortunately, as shown later in this chapter bispecific PARs were still capable of

112

eliciting complete tumor eradication; indicating any Treg activation was insufficient to elicit a significant immunosuppressive effect.

Figure 3.15 CSAN Mediated T-Regulatory Cell Activation

Unactivated PBMCs were co-cultured with media, monospecific CSANs or bispecific CSANs in the presence or absence of target MCF-7 cells. Following the 24 hour incubation, the media was analyzed for CD4, CD25 and FOXP3 expression. Cells positive for CD8 and live dead dye were removed from analysis. *P<0.05 with respect to αEpCAM CSAN and no treatment controls, by one-way ANOVA.

Strong, and prolonged, stimulation of the TCR has been shown to result in T cell anergy.187-189 For this reason our laboratory decided to evaluate the affect CSANs have on the TCR receptor to determine whether there was any subsequent activation. There are multiple phosphorylation events downstream of TCR signaling which have been shown to determine the fate of T cells upon recognition of their cognate antigen. For example, engagement of the TCR stimulates activation of Phosphatidylinositol-4,5-bisphosphate 3- kinase (PI3K) and protein kinase B (AKt), which lead to the activation of mammalian target 113

rapamycin (mTOR) and phosphorylation of pS6.190 We chose to monitor the biochemical signal pS6 as a representative readout of TCR stimulation. When in the presence of CSANs alone there was no significant increase in the levels of pS6 for both CD4+ and CD8+ naïve

T-cells and only a 1.5-fold increase in the expression levels for CD4+ and CD8+ memory

T-cells (Figure 3.16). Importantly, while there was an increase in memory cell activation, these same culture conditions elicited no increase in IL-2 (Figure 3.13A) over 24 hours and only a partial increase in IFN-γ (Figure 3.13B) production. In contrast to CSANs alone, incubation with both bispecific CSANs and target MCF-7 cells resulted in a significant increase in pS6 levels, similar to that of the CD3/CD28/CD2 activation complex, for CD4+ and CD8+ memory T-cells and a 2-fold increase in pS6 levels for naïve

T-cells (Figure 3.16). This is mirrored by the significantly greater IL-2 and IFN-γ production under these same conditions. These results suggest that αEpCAM/αCD3 bispecific CSANs alone do not directly stimulate the TCRs of naïve T-cells and thus are unlikely to induce anergy.

114

Figure 3.16 Monitoring pS6 levels in T-cells labelled with Anti-EpCAM/anti-CD3 CSANs.

Unactivated PBMCs were co-cultured with media, MCF-7 cells, bispecific CSANs, both bispecific CSANs and target MCF-7 cells or CD3/CD28/CD2 activator complex. PBMCs were incubated for 3 hours before measuring internal pS6 levels by flow cytometry. Lymphocytes were determined by forward and side scatter as well as removal of CD20, CDllb/c positive cells. CD4+ and CD8+ cells were gated for further categorization as naïve (CD45RA+CD45RO-) or memory cells (CD45RA-CD45RO+). *P<0.05 with respect to non-treated controls, by one-way ANOVA analysis.

Since both CD4+ and CD8+ T-cells can have effector function, we characterized the activation and cytotoxicity of isolated CD4+ and CD8+ T-cells in the presence

αEpCAM/αCD3 CSANs. Over the course of 24 hours, the greatest level of targeted cytotoxicity resulted from CD8+ T-cells (55%) treated with αEpCAM/αCD3 CSANs and the least from treated CD4+ cells (10%; Figure 3.17A). The presence of CD4+ T-cells was not required for CD8+ T-cell targeted cytotoxicity in vitro. Indeed, as the ratio of CD4+ to

CD8+ T-cells decreased from 4:1 to 1:4, as targeted cellular cytotoxity increased. Further analysis revealed the bispecific CSAN-modified CD8+ T-cells in the presence of the target cells were fully capable of producing IL-2 (Figure 3.17D) and IFN-γ (Figure 3.17C).

115

Interestingly, both CD4+ and CD8+ T-cells in the presence of either αCD3 CSANs or

αEpCAM/αCD3 CSANs and target MCF-7 cells expressed the same amount of CD69 and

CD25 (Figure 3.18). However, the CD4+ and CD8+ T-cells treated with the bispecific

CSANs produced 10- to 12-fold, respectively, more IL-2 than cells treated with αCD3

CSANs. Similarly, a 2- and 3-fold increase in the amount of IFN- γ released by CD4+ and

CD8+ T-cells, respectively, was found for cells treated with αEpCAM/αCD3 CSANs than

αCD3 CSANs in the presence of MCF-7 cells. Thus, while an increase in the amount of

CD69 and CD25 is observed for CD4+ and CD8+ T-cells treated with αEpCAM/αCD3

CSANs, the magnitude of cytotoxicity correlated with the amount of IFN-γ and, to an even greater extent, IL-2 produced. When the time of incubation was extended to 36 hours, cellular toxicity induced by CD4+ T-cells treated αEpCAM/αCD3 CSANs was similar to that mediated by CD8+ T-cells (Figure 3.17B).

116

Figure 3.17 Isolated CD8+ and CD4+ T-cells are still capable of selective activation and target cell killing.

(A) CD8+ and CD4+ T cells were isolated separately by negative selection and used for targeting cell killing with 50 nM Bispecific CSANs and a 10:1 E:T ratio at various CD4:CD8 ratios. (B) Targeted Cell lysis of Isolated CD4+ and CD8+ T cells at both 24 hours and 36 hours. Cytokine production produced from CD4+ and CD8+ T cells isolated by negative selection. Unactivated PBMCs were co-cultured with media, monospecific CSANs or bispecific CSANs in the presence or absence of target MCF-7 cells for 24 hours at various CD4:CD8 ratios. Following incubation, the media was analyzed for (C) IFN-γ and (D) IL-2 by ELISA. Data shown was obtained from one donor (n=3), but representative of three donors. *P<0.05 with respect to antiEpCAM CSAN and no treatment controls, by 2-tailed Student’s t test.

117

Figure 3.18 CD69 and CD25 expressed on purified CD4+ and CD8+ T cells.

Unactivated CD4+ and CD8+ T-cells were isolated by negative selection. T-cells were co- cultured with media, monospecific CSANs or bispecific CSANs in the presence of target MCF-7 cells for 24 hours. Data was analyzed by flow cytometry to measure the upregulation of (A) CD69 and (B) CD25 on the T-cell surface. Data shown was obtained from one donor, but representative of data from 3 donors.

3.2.3 In Vivo anti-Tumor Activity

The most commonly used mouse model in oncoimmunology consists of the inoculation of histocompatible cancer cell lines into immunocompetent inbred mice, generally from the C57Bl/6 or BALB/c strains.191 Predominately, tumor cells are subcutaneously injected into the flank due to the ease of subsequent analysis and monitoring (greatly facilitates tumor monitoring by palpation and visual inspection).

However, recent evidence has pointed to the need for orthotopically injecting tumor cells to evaluate their growth and evolution in their ‘normal’ environment. Alternatively, labs occasionally perform systemic injections (intraperitoneally or intravenously) to specifically monitor the metastatic spread of cancer.

118

To characterize the in vivo anti-tumor activity of the αEpCAM/αCD3 PAR T-cells, we used an orthotopic NSG mouse model. Because NSG mice are unable to produce NK cells, T-cells, or B-cells and are therefore highly immunodeficient, they have become the model animal of choice for antigen targeted, immunotherapeutic, pre-clinical studies for both CAR-T cells and bispecific antibodies.192 MCF-7-Luc breast cancer cells were unilaterally injected into the fourth mammary fat pad of NOD.Cg-Prkdcscid Il2rγtm1Wjl/SzJ

(NSG) mice and placement was confirmed by in vivo bioluminescence imaging (IVIS) on day 9 (Figure 3.19).

Figure 3.19 Confirmation of Tumor Implant by IVIS

In vivo bioluminescence imaging was used to confirm the placement of MCF-7 luciferase tumors. NSG mice were IP injected with 150 mg/kg luciferin and subsequently anesthetized with isoflurane for imaging.

119

Ten days after tumor implantation, mice were separated into control and treatment groups and dosed intravenously with either PBS, PBMCs (20x106), αEpCAM/αCD3

CSANs (1 mg/kg), PBMCs treated with αCD3 CSANs (50 nM), or PBMCs treated with

αEpCAM/αCD3 CSANs (50 nM). The αEpCAM/αCD3 CSANs-treated PBMC group was subsequently dosed intravenously with injections of αEpCAM/αCD3 CSANs (1 mg/kg) dosage every 2 days following the initial infusion with PBMCs treated with

αEpCAM/αCD3 CSANs on day 10. Similarly, the αCD3 CSANs PBMC treatment group was given additional injections of αCD3 CSANs (1 mg/kg) every 2 days following the initial infusion with PBMCs treated with αCD3 CSANs on day 10. Over the course of the next eight days full tumor eradication was observed for the αEpCAM/αCD3 CSANs

PBMC treatment group. The response was found to be durable, with no tumor reemergence observed over the next two and half weeks. In contrast, rapid tumor growth was observed for all the control groups (Figure 3.20A).

120

Figure 3.20 In Vivo efficacy study of bispecific PARs in an orthotopic NSG mouse model.

NSG mice were inoculated in the mammary fat pad with 5.0x105 MCF-7 Luciferase cells. (A) Ten days following tumor implantation mice were IV injected with either PBS, 20x106 unstimulated human PBMCs, 1 mg/kg anti-EpCAM/anti-CD3 bispecific CSANs, 20x106 unstimulated PBMCs modified with 50 nM antiCD3 monospecific PARs, and the treatment group of 20x106 unstimulated PBMCs modified with 50 nM anti-EpCAM/antiCD3 bispecific PARs (n=5). Each cohort was given additional booster injections of the relevant CSAN construct at 1 mg/kg, or PBS, every two days following the initial infusion on day 10. Tumor growth was monitored every by caliper and recorded as mm3. (B) The same NSG model was applied with booster injections provided at varying time intervals, including: daily, every two days, every four days and every 8 days. (C) Body weight was monitored and recorded. All in vivo experiments were performed independently and at least twice. *P<0.05 with respect to readings statistically significant from the PBS control group, by 2-tailed Student’s t test.

Unlike CAR T-cells which constitutively express the targeting antibody, the amount of the bispecific ring on αEpCAM/αCD3 PAR T-cells will be diluted as the activated T-cells expand and proliferate. Consequently, we reasoned that subsequent dosing with the αEpCAM/αCD3 CSANs would result in rearming the T-cells and thus maintain their anti-tumor potency. To assess the importance of the αEpCAM/αCD3

CSANs dosing schedule on tumor regression, αEpCAM/αCD3 CSAN labeled PBMC were

121

administered prior to intravenously injections of the bispecific CSANs either every day, every two day, every four days or every eight days. One, two, and four-day dosing resulted in full tumor eradication after initial dosing with αEpCAM/αCD3 CSANs PBMC. While complete tumor regression was not observed when dosing occurred every eight days, the rate of tumor growth was still reduced by 72% (Figure 3.20B). Over the course of the anti- tumor studies, no significant weight loss was observed, regardless of dosing schedule

(Figure 3.20B & Figure 3.21). However, due to tumor burden, as well as graft-vs-host

(GVH) disease, a small decrease was observed by the end of the study for the animals treated with PBS and PBMC only controls (Figure 3.20C).

Figure 3.21 Variable dosing schedule does not exhibit toxicity.

Body weight was monitored and recorded throughout the course of the treatments.

An explanation for the potent anti-tumor activity of αEpCAM/αCD3 PAR T-cells may rest on the fact that MCF-7 cells and their associated tumorigenic stem cells express

EpCAM.172 This conclusion is consistent with the observation that tumor re-emergence is not observed over two weeks after either the every day or two day αEpCAM/αCD3 CSANs 122

dosing schedule (Figure 3.20). Nevertheless, the inability to significantly reduce tumor size for the 8-day dosing schedule implies that once tumors have reached a certain size, it may be difficult to achieve the necessary infiltration of αEpCAM/αCD3 PAR T-cells.

Future studies examining the impact of the tumor type, tumor size and αEpCAM/αCD3

CSANs dosing on tumor proliferation and eradication will provide important insights of the potential and limitations of PAR T-cells anti-tumor activity.

Targeting EpCAM+ tumors has also been attempted with an αEpCAM/αCD3 BiTe,

MT110.49 Dosing of mice with established tumors, although not orthotopic, did lead to tumor eradication if MT110 was given daily.49 By comparison, tumor eradication with the

αEpCAM/αCD3 PAR T-cells could be achieved by dosing every four days with a comparable amount of the bispecific CSANs. Thus, the longer half-life of the

αEpCAM/αCD3 CSANs on the T-cells is likely responsible for the decreased dosing schedule compared to the BiTes, which require daily infusion to achieve clinical efficacy.

Additionally, similar to MT110, no significant toxicities were observed following administration of the αEpCAM/αCD3 PAR T-cells, suggesting specific interaction with the EpCAM+ tumor cells.

123

Figure 3.22 In Vivo Cytokine Release Assay

NSG mice were inoculated in the mammary fat pad with 5.0x105 MCF-7 Luciferase cells. Ten days following tumor implantation mice were IV injected with either PBS, 20x106 unstimulated human PBMCs, 1 mg/kg anti-EpCAM/anti-CD3 bispecific CSANs, 20x106 unstimulated PBMCs modified with 50 nM antiCD3 monospecific PARs, and the treatment group of 20x106 unstimulated PBMCs modified with 50 nM anti-EpCAM/antiCD3 bispecific PARs (n=5). Each cohort was given additional booster injections of the relevant CSAN construct at 1 mg/kg, or PBS, every two days following the initial infusion on day 10. Tumor growth was monitored every by caliper and recorded as mm3. On days 1, 5 and 9 following treatment the level of IFN-γ (A), IdL-2 (B), IL-6 (C) and TNF-α (D) was quantified. All in vivo experiments were performed independently and at least twice. *P<0.05 with respect to readings statistically significant from the Bispecific PARs group, by 2-tailed Student’s t test.

124

Since IL-2, IFN-γ, TNF-α, IL-6 and IL-10 production is hallmark of T-cell activation, the plasma cytokine levels of NSG mice bearing orthotopic MCF-7-Luc tumors treated with αEpCAM/αCD3 CSANs was determined by ELISA and compared to non- treated groups. The cytokine analysis indicated IL-2 and IFN-γ production was detectable within one day of treatment and rose slowly over the course of the next eight days (Figure

3.22A-D). In contrast, neither IL-2 nor IFN-γ production was observed in the plasma for the non-treated PBS control group. By day five, both IL-2 and IFN-γ could be observed in the plasma for the non-treated PBMC control group suggesting the emergence of GVH disease. In addition, IL-6 and TNF-α production by the treatment group and not the PBS control group was also observed after one day. The amount of IL-6 in the plasma doubled over the next four days, but was unchanged by day eight, while the amount of TNF-α rose by 25% by day four and day eight. Thus, T-cell activation by the αEpCAM/αCD3 CSANs could be observed by at least the first day of treatment. Interestingly, within the first 24 h

6.5-fold more IFN-γ was produced than IL-2 which is in contrast to the in vitro results where IL-2 production was slightly higher than that of IFN-γ. Additionally, compared to previous studies with CAR T-cells and BiTes, similar or lower levels of cytokine production by αEpCAM/αCD3 CSANs were observed.

Persistent effector and central memory T-cell phenotypes correlate with total remissions in clinical trials for CAR T-cell therapy.60, 193 To evaluate the effect

αEpCAM/αCD3 CSANs were having on T-cell populations we dosed NSG mice bearing the MCF-7-Luc tumors as previously discussed. Mice were dosed with either PBMCs or

125

PBMCs treated with αEpCAM/αCD3 CSANs and redosing was performed every 4 days.

CD4+ and CD8+ T-cells in the mouse peripheral blood were analyzed for CD45RO and

CCR7 on day 0 and 4. The αEpCAM/αCD3 CSAN treatment demonstrated significant expansion of CD45RO+CCR7- (effector memory T-cells) for both the CD4+ and CD8+ cells compared to the non-treated PBMC population at day 4 (Figure 3.23). The bispecific treatment additionally showed a greater decrease in the CD45RO-CCR7+ (naïve T-cells) population compared to the non-treated control. In addition, the increased levels of both

IL-2 and IFN-γ appear to correlate with both the rise in number of CD4+ and CD8+ T

+ + effector memory cells (Tem) and decrease in the number of CD4 and CD8 naïve T-cells

(Tn) relative to the non-PAR T-cell treated mice.

126

Figure 3.23 CD4+ and CD8+ memory cell formation.

The phenotype of T cells in the peripheral blood from mice treated with PBMCs and anti- EpCAM/anti-CD3 Bispecific CSANs on day 0, 4 and 30. They are displayed as the proportion of (A) CD4+ cells and (B) CD8+ cells by flow cytometry with staining for CCR7and CD45RO (n = 5). The gating strategy is displayed indicating isolation of single cells, removal of dead/dump gate and isolation of CD4+ and CD8+ cells. All SD < 1.9%.

127

Previously, we have demonstrated that surface bound CSANs can be removed from

T-cells by the addition of trimethoprim. Next, we wanted to evaluate whether this ability extended to in vivo applications as well. To determine the ability of trimethoprim to affect the activation of T-cells bound to αEpCAM/αCD3 CSANs, we prepared NSG mice bearing orthotopic MCF-7-Luc tumors and treated them with PBMCs and αEpCAM/αCD3

CSANs. One day after treatment, the amount of IFN-γ, IL-2, IL-6 or TNF-α in the blood was determined and compared to the amounts before treatment, as well as to the non- treatment controls. In each case, the amount of each cytokine significantly increased above the background amounts and the control groups, indicating T-cell activation. The mice were then dosed intravenously (2 mg/kg) with clinically used trimethoprim/sulfamethoxazole or PBS. Twenty-four hours later, plasma samples were taken and cytokine levels determined. The amount of IL-2, IL-6, IFN-γ or TNF-α remained unchanged for the trimethoprim/sulfamethoxazole treated group, while the levels of each cytokine significantly increased for the mice not treated with trimethoprim/sulfamethoxazole (Figure 3.24). This result is consistent with removal of the bispecific rings from the surface of the cells, since the production of the cytokines is dependent on the targeted interaction of the T-cells with tumor tissue. Whether a higher dose or more frequent dosing would result in a more profound affect remains to be determined. Regardless, these results suggest the toxic side-effects resulting from T-cell activating immunotherapies may be addressable pharmacologically for PAR T-cells with an FDA approved drug.

128

Figure 3.24 Trimethoprim mediated dissociation of CSAN therapy in vivo.

Three groups of NSG Mice (n=5) previously engrafted with MCF-7 tumors were treated with either PBS, 20 million unstimulated PBMCs or 20 million unstimulated PBMCs functionalized with 50nM anti-EpCAM/anti-CD3 CSANs by IV. One day following therapy mice received 2 mg/kg of trimethoprim/sulfamethoxazole. Each day their levels of IFN-γ (A), IL-2 (B), IL-6 (C) and TNF-α (D) was quantified (n=5). *P<0.05 with respect to readings that were statistically significant from bispecific PAR therapy, by 2-tailed Student’s t test.

As with all biologics and especially with those derived from foreign sources, the development of immunogenicity may be a clinically important issue that limits efficacy.

This is of particular concern for CSANs, since they are composed of E. coli DHFR.

Consequently, we evaluated the inherent immunogenicity of our CSAN based therapy.

When either CSANs or free DHFR2 were incubated with fresh splenocytes from untreated

BALB/c mice for 24 h at 37oC no significant increase in the production of IL-6 was 129

observed (Figure 3.25). No significant increase in the expression of CD40 or CD86 was observed indicating that the CSANs do not activate B-cells (Figure 9A). Additionally, this indicates that while CSANs alone elicit a mild activation in memory cells, there is no B- cell activation as a result of CD4+ memory cells. To further address the potential immunoreactivity of CSANs we injected BALB/c mice with 30 µg of the CSANs on day

1 and day 13 and then measured the amount of DHFR specific IgG antibody ELISA on days 13, 21 and 30. As can be seen in Figure 9, over the course of the 30 days, no significant difference in the production of αDHFR IgG was observed in the plasma of the CSANs treated mice compared to the untreated PBS control (Figure 9C). Thus, CSANs exhibit negligible immunogenicity when mice were dosed intravenously. Although speculative, the apparent inability of the DHFR2 CSANs to display innate immune response pathogen associated molecular patterns could be a factor in limiting potential immune cell activation.

In addition, the high stability of the CSANs, even when endocytosed, may also limit their ability to undergo antigen presentation and thus generation of an adaptive immune response. Nevertheless, while the inability to elicit an immune response in mice does not preclude the possibility they may be immunogenic in humans, the development of an adaptive immune response in mice would predict a likely potent immune response in humans.194

130

Figure 3.25 Murine anti-DHFR2 Immune response.

Freshly isolated spleen cells from naïve mice were incubated with DHFR2 protein, non- targeted CSANs and CpG 1826 (positive control) for 24 hours and monitored for (A) CD40 and CD86 expression as well as (B) IL-6 release. Mice were injected with non-targeted CSANs and (C) monitored on day 13, 21 and 30 since the first immunization. Sera were collected for estimation of anti-DHFR IgG antibodies by ELISA. Data were shown as absorbance values at 450 nm wavelength at appropriate dilutions. Each bar represents the mean value of absorbance value OD450 ± SD for each group (n=4). Values of p < 0.05 were considered significant and were indicated as follows: *p < 0.05. Statistical differences between the groups were determined by one-way ANOVA analysis and Student t test.

3.3 CONCLUSIONS

Our laboratory has successfully developed αEpCAM/αCD3 PARs as a non-genetic method for modifying cell surfaces. The αEpCAM/αCD3 PARs were found to stably bind

T-cells for >4 days, and treating EpCAM+ MCF-7 breast cancer cells with anti-

EpCAM/anti-CD3 PAR-functionalized T-cells resulted in the induction of IL-2, IFN-γ and

MCF-7 cytotoxicity. Furthermore, an orthotopic breast cancer model validated the ability of anti-EpCAM/anti-CD3 PAR therapy to direct T-cell lytic activity towards EpCAM+ breast cancer cells in vivo leading to tumor eradication. Following PAR treatment, the production of IL-2, IFN-γ, IL-6 and TNF-α could be significantly reduced by an infusion

131

of clinically-relevant concentrations of the FDA-approved antibiotic, trimethoprim, signaling pharmacologic PAR deactivation. Importantly, the CSANs had no significant immunogenicity in mice and were not shown to initiate naïve T-cell activation without the presence of target EpCAM+ breast cancer cells. Additionally, our results indicated that

PAR T cells traffic well to solid tumors within several days and did not stimulate Treg cells sufficiently enough to induce immunosuppression. Collectively, our results demonstrate

PAR modified T-cells have the potential to be a viable alternative to existing T-cell engagers and CAR T-cell based immunotherapy approaches targeting solid tumors. In addition, the demonstration that bispecific and polyvalent CSANs can guide and reversibly control cell-cell interactions, both in vitro and in vivo, supports their development as a synthetic biological tool.

Future studies will likely include the combination of PAR therapy with check point inhibitors to overcome tumors already containing an immunosuppressive microenvironment. Furthermore, the MCF-7 cancer cells used in chapter 3 exhibited extremely high levels of EpCAM receptor and the translation of PARs to a lower target antigen expressing cell line was uncertain. For this reason, in chapter 4 we explore the application of PARs to a triple negative breast cancer (TNBC) model expressing low

EpCAM levels. In addition, we delve into the simultaneous targeting of tumor antigens, including a bulk tumor marker (EpCAM) and cancer stem cell (CSC) marker, and evaluate the potential for synergistic targeting.

132

3.4 MATERIALS AND METHODS

3.4.1 DHFR2 protein expression and purification

The development and preparation of DHFR2-anti-EpCAM and DHFR2-anti-CD3 proteins have been previously described.75, 79, 164 Briefly, E. coli BL21-DE3 OneShot

Ultracompetent cells were purchased from Invitrogen and transformed with either DHFR2- anti-EpCAM and DHFR2-anti-CD3 plasmids per Invitrogen specifications. Following transformation, individual starting cultures were grown in 4L of LB media containing 0.1

μg/mL ampicillin in 4 separate 2L flasks. The cultures were shaken at 250 RPM at 37°C until the OD600 was within the ranges of 0.4-0.8 and subsequently induced with isopropyl

β-D-1-thiogalactopyranoside (IPTG; Sigma Aldrich, St. Louis, MO) at a final concentration of 0.3 mM. Cultures were shaken for an additional 3 hours following induction and centrifuged to obtain a bacterial pellet. The cell pellet was suspended in a

50mM Tris-HCl buffer containing 50mM NaCl, 5mM EDTA, 1 mg/mL lysozyme, and a protease inhibitor cocktail (phenylmethanesulfonyl fluoride, Pepstatin A, and Leupeptin).

All insoluble material was isolated by centrifugation and further washed using a detergent- based buffer containing 1% sodium deoxycholate, Triton X-100, and glycerin to isolate the inclusion bodies (PPIB). The inclusion bodies were solubilized in 2.5% sodium N-lauroyl- sarcosine (SLS) buffer and air oxidized using 50 μM CuSO4 for 20 hours. All detergent in the SLS buffer was removed by treatment with Dowex 10% 1-X8 anion-exchange resin and 6M urea. Oxidized inclusion bodies were diluted 40-fold into refolding buffer containing 50mM Tris, 0.5 M L-arginine, and 20% glycerol (pH 8) and allowed to sit for

133

48 hours. Refolded protein was dialyzed against 20mM Tris buffer, and loaded onto a Fast

Flow Q-sepharose (FFQ) anion exchange column prior to elution with 720mL of Tris buffer containing 1M sodium chloride (NaCl).

3.4.2 Cell Lines, Culture Conditions and T-cell isolation

MCF-7 breast cancer cells and U-87 MG human glioblastoma cells were obtained from

American Type Culture Collection (ATCC, Rockville, MD). MCF-7 Luciferase cells were kindly provided by Dr. Daniel Vallera (University of Minnesota, Minneapolis, MN).

Human cancer lines were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% FBS, 100 U/mL penicillin, 100 µg/mL streptomycin, and L- glutamine at 37°C in 5% CO2. Human PBMCs were isolated from buffy coats of healthy donor blood samples (obtained from Memorial Blood Centers, St. Paul, MN) by Ficoll density gradient centrifugation. Unactivated CD8+ or CD4+ T-cells were isolated from

PBMCs by positive selection using CD8+ or CD4+ T-cell isolation kit (Invitrogen Life

Technologies, Grand Island, NY). PBMCs were cultured in complete RPMI 1640 medium

(Lonza) supplemented with 10% (v/v) fetal bovine serum, L-glutamine (final concentration of 2mM), Penicillin (100 units/mL), and Streptomycin (100 µg/mL) in a humidified incubator with 5% CO2 at 37 ˚C.

134

3.4.3 CSAN Oligomerization and Characterization

To create bispecific CSANs, equal parts of purified DHFR2-αEpCAM and DHFR2-αCD3 proteins (2-8 µM) were combined with 2.2 equivalents (1:1:2.2 ratio) of either C9-bisMTX dimerizer or FITC-conjugated bisMTX trilinker in phosphate-buffered saline (PBS). For monospecific CSANs, single purified fusion proteins were incubated with 2.2 equivalents

(1:2.2 ratio) of either C9-bisMTX dimerizer or FITC-conjugated bisMTX trilinker in PBS.

CSANS were allowed to incubate at room temperature for 30 minutes, in the absence of light. All proteins and CSAN constructs were analyzed by size exclusion chromatography

(SEC) to observe the average size of ring formation, by injection onto a Superdex G200 column connected to a Beckman Coulter HPLC equipped with a diode array detector and using PBS as a mobile phase. Elution times were monitored at 280 nm to observe the change in hydrodynamic radius compared to monomeric species. DLS measurements were performed on a Brook haven 90 Plus Particle Analyzer (Holtzville, NY) with a 35 mW red diode laser. Samples (1.5 mL) were measured at room temperature in suspensions of PBS at (1.5 mg/mL). Cryo-TEM samples were prepared using an FEI Vitrobot Mk IV

(Hillsboro, OR). Briefly, glow discharged lacey formvar/carbon, 300 mesh, copper grids

(Ted Pella Inc., Redding, CA, cat: 01883) were loaded with 3 μL of a 6.6 μM solution of

CSANs in PBS within a 95% humidity chamber at 25˚C. After blotting for 5.5 seconds, grids were plunge frozen in liquid ethane, and kept under liquid nitrogen until loading into a cryo-transfer holder (Gatan Inc., Pleasanton, CA, cat: 626). Imaging occurred on an FEI

135

Tecnai G2 Spirit BioTWIN transmission electron microscope with a LaB6 emitter and FEI

Eagle 2k CCD detector.

3.4.4 Binding Assays

Protein samples (4-20 µM) were incubated with 1.1 equivalent of bis-MTX-FITC in PBS for 1 hour at room temperature to generate the following three constructs: anti-EpCAM

CSANs, anti-CD3 CSANs and anti-EpCAM/anti-CD3 Bispecific CSANs. All three CSAN constructs (1 M) were incubated with 1 million EpCAM+ MCF-7 cells at 37C for 1 hour and subsequently washed three times with PBS supplemented with 1% BSA and 0.1% sodium azide (FACS buffer). Samples were filtered to remove cell aggregate prior to analysis by flow cytometry using a BD LSR II flow cytometer. The mean fluorescence intensity (MFI) was monitored and compared to unstained PBMCs as a background control. To monitor cell surface stability of CSANs, 5x105 PBMCs were incubated with saturating concentrations (1 µM) of either anti-EpCAM/anti-CD3 bispecific CSANs or anti-CD3 DHFR2 monomer for 1 hour at room temperature. Cells were subsequently washed and plated in 48-well plates. For the following 5 days cells were washed with FACs buffer and then replated into the 48-well plate. Each day one of each sample was washed with FACs buffer and treated with saturating concentrations of anti-CD3 mAb-FITC and analyzed for FITC fluorescence. To determine the maximum fluorescence, the same number of PBMCs not previously stained with bispecific CSANs or anti-CD3 DHFR2 monomer were additionally stained with anti-CD3 mAb-FITC. This experiment was run in

136

triplicate for each time point. Percent fluorescence inhibition was determined by subtracting the mean fluorescence at each time point from the maximum 100% cell binding which was set with the absence of competition.

Binding affinities were determined by generating a saturation curve for 1DHFR2-

αEpCAM and the Moc31 mAb, against the same epitope on the EpCAM receptor, to determine the 90% saturation amount. 40 nM a Moc31-PE conjugate (BioLegend) was subsequently used in a competition assay against varying concentrations of 1DHFR2-

αEpCAM and αEpCAM octameric and dimeric structures. Decreasing MFI values of

Moc31 binding was used for Kd measurements.

3.4.5 Cytotoxicity Assays

Measurement of cell lysis was evaluated by measuring LDH (lactate dehydrogenase) release from cells with the non-radioactive cytotoxicity assay (CytoTox 96® Non-

Radioactive Cytotoxicity Assay, Promega). The day previous to the experiment 5x103 target MCF-7 cells or non-target U-87 MG cells were seeded into a 96-well plate in 200

μL of RPMI-1640 media per well. The following day the appropriate number of resting

PBMCs (according the requested effector (E) to target (T) cell (E:T) ratio as indicated in the respective experiment) were counted and incubated with 0.01-1 μM of the

αEpCAM/αCD3 bispecific CSANs for one hour at 37°C with 5% C02. Following the initial incubation, PBMCs were washed and resuspended in RPMI before addition to 96-well plate containing target MCF-7 or U-87 MG cells and incubated for 24 hours under standard

137

conditions. MOC-31 (Abcam), which competitively binds the same epitope as αEpCAM

DHFR2,79 was co-incubated when indicated to test target receptor specificity. Lysis buffer

(provided in assay kit) was added to control wells with only MCF-7 cells to estimate the maximum LDH release. The absorbance at 490 nm was measured and recorded using a

Synergy H1 Multi-Mode Reader (Biotek). Data was corrected for media absorbance, and values were determined per the following equation: ((LDH release sample – SReffector –

SRtarget)(MRtarget – SRtarget)) x 100. SR: spontaneous release; MR: maximum release.

3.4.6 Immunostaining and Cytokine Analysis

IL-2 and IFN-γ measurements in the cytotoxicity assay supernatants were analyzed using

ELISA per the conditions provided by IFN-γ ELISA kit (Invitrogen) and IL-2 ELISA kit

(Invitrogen). In brief, following the incubation period the supernatant was removed and

10-fold diluted into ELISA buffer (provided in the kit) prior to placing 50 µL into the respective well of the included ELISA 96-well plate. IFN-γ and IL-2 production of experimental wells was determined through a standard curve generated from known control sample concentrations. T-cell activation was measured using the cells from the cytotoxicity assay, which were stained with anti-human CD4 (FITC), anti-human CD8 (PE) and either anti-human CD25 (APC) or anti-human CD69 (APC) (Biolegend) and analyzed by flow cytometry to determine the proportion of CD4+ and CD8+ T-cells activated (CD25+CD69+).

Cells analyzed for CD69+ expression were incubated in the cytotoxicity assay for 12 hours while those analyzed for CD25+ expression were incubated for 24 hours. In vitro

138

immunogenicity assays were performed with freshly isolated spleen cells from naïve

Balb/c mice plated into 96-well plates with the indicated treatments. Cells were stained with anti-mouse CD40-PE-Cy5 (clone: 3/23) (BioLegend) and anti-mouse CD86

(clone:GL1). Cells were analyzed on the BD LSR II flow cytometer. To measure pS6 upregulation PBMCs were incubated for 3 hours at 37°C with either PBS, target MCF-7 cells, 50 nM αEpCAM/αCD3 bispecific CSANs, 50 nM αEpCAM/αCD3 bispecific

CSANs which were pre-plated overnight at 37°C, 50 nM αEpCAM/αCD3 bispecific

CSANs and target MCF-7 cells, or CD3/CD28/CD2 activator complex. PBMCs were harvested and washed once with PBS before resuspending in 1 ml of 1.6%

Paraformaldehyde/PBS. Cells were incubated at RT for 15 min before the addition of 4 ml of 100% methanol at -80°C. Cells were incubated for an additional 15 minutes, spun down at 4°C and washed with FACs buffer. Cells were stained with CD4-PE, CD8a-BV421,

CD45RO-BV605, CD45RA-APC, CD11b-APC-ef780, CD11c-APC-ef780, CD20-APC- ef780 and pS6-AF488 before analysis with an LSRFortessa H0081.

3.4.7 MCF-7 Orthotopic Breast Cancer Model

All protocols conformed to institutional regulations. Cohorts of five NSG mice were used.

Six- to 8-wk-old female NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice were injected unilaterally into the fourth mammary fat pad with 1.0x106 MCF-7 cells. The injection was performed in 30 µL of 50:50 Matrigel/PBS directly through the nipple. Four days prior to tumor implant and every subsequent four days throughout the remainder of the study mice

139

were SQ injected with 1 µg/kg of 17β-estradiol valerate. Ten days following tumor implantation mice were separated into treatment groups: a control group injected with PBS, a control group infused with 20x106 unmodified peripheral Blood Mononuclear Cells

(PBMCs) by IV injection, a control group infused with 1 mg/kg αEpCAM/αCD3 CSANs by IV injection, a control group infused with 20x106 αCD3 monospecific PARs modified with 50 nM αCD3 CSANs, and a treatment group infused with 20x106 αEpCAM/αCD3 bispecific PARs modified with 50 nM αEpCAM/αCD3 CSANs. The treatment group was given additional booster injections of αEpCAM/αCD3 CSANs at 1 mg/kg dosage every 2 days following the initial PAR infusion on day 10. The αCD3 PAR group was given additional booster injections of αCD3 CSANs at 1 mg/kg dosage every 2 days following the initial PAR infusion on day 10. PBS and PBMC control groups were dosed every two days with PBS while the αEpCAM/αCD3 CSANs control group was dosed every two days with 1 mg/kg of additional αEpCAM/αCD3 CSANs. When indicated, additional booster injections were provided at alternate time intervals including: daily dosing, every 2 days, every 4 days and every 8 days. Body weight was monitored daily, and tumor growth was monitored daily by caliper to measure the height x width x length and recorded as mm3.

Blood was obtained by facial vein bleeds and spun down at 400g for ten minutes to obtain the plasma. The plasma was analyzed by ELISA assay kits (AbCAM) as previously described to quantify the amount of IL-2, IFN-γ gamma, TNF-α, and IL-6. Mice were sacrificed at 35 days and the blood and spleen were immediately harvested for FACs analysis. PBMCs from the blood were obtained by spinning at 400g for 10 minutes in

140

lymphocyte separation media and subsequently washed with FACs buffer. PBMCs from the spleen were obtained by maceration with a wire filter and RPMI media. Red blood cells were lysed using FACs lysing solution and the solution was then spun down and the pellet was washed with FACs buffer to isolate viable PBMCs. These were then stained with CD4

(FITC) (eBioscience), CD8 (PE) (eBioscience), CD20 (APC-ef780) (eBioscience), CD11b

(APC-ef780) (eBioscience), CD11c (APC-ef780) (eBioscience), Live/Dead ghost red

(Tonbo), CD45RO (BV605) (Biolegend), CCR7 (Percp Cy5.5) (Biolegend) for memory cell analysis. Cells were analyzed using an BD LSR II flow cytometer. In Vivo disassembly of PARs was evaluated with an IV infusion of 2 mg/kg trimethoprim/sulfamethoxazole

(Sigma Aldrich) 1 day following the initial infusion of PBMCs or treated PARs.

3.4.8 DHFR2 In Vivo Immunogenicity Analysis

Female BALB/c mice (7 weeks old), stock #01B05, were purchased from the National

Cancer Institute (Frederick, MD, USA). Four mice per group were immunized intravenously with 30 µg (834.7 pmol) of CSANs in PBS in a total volume of 300

µl/animal. A booster injection with the same concentration and volume was administered on day 14. Blood samples were taken on day 0, 13, 21 and 30 by retro-orbital bleeding.

Mice were sacrificed by cervical dislocation. Single cell suspension was prepared aseptically from the spleens. Mouse splenocytes were grown in RPMI media for FACS and in vitro activation assay. Levels of antibodies binding to DHFR were measured by enzyme- linked immunosorbent assay (ELISA). Briefly, Maxisorp 96-well plates (Thermo

141

scientific) were coated first with DHFR2 (1 µg/well) in ELISA diluent (PBS containing

10% FBS) overnight at 4˚C. Following 1 h blocking with ELISA diluent, diluted sera (1:10) of immunized mice were transferred to the coated plates and incubated for 2 h at room temperature. Horseradish peroxidase-conjugated rabbit anti-mouse IgG-HRP (Sigma–

Aldrich) diluted 1:80,000, or goat anti-mouse IgG1-HRP (Santa Cruz) diluted 1:4,000, or goat anti-mouse IgG2a-HRP (Santa Cruz) diluted 1:4,000, in the same diluent were incubated for 1 h at room temperature. The amount of bound peroxidase was visualized by incubation with tetramethylbenzidine and hydrogen peroxide (BD Bioscience). After 15 min, the reaction was stopped with 0.2 M H2SO4 and A450 was measured with a microplate reader (Biotek)

3.4.9 Statistical Analysis

All data analysis was analyzed using PRISM (v4.0; GraphPad Inc.). Data was analyzed using a 2-tailed, equal variance Student’s t test and ANOVA analysis with Bonferroni’s correction for multi group comparisons. Data acquired from in vitro assays using experimental replicates are presented as the mean ± SD and data acquired in vitro or in vivo using biological replicates are presented as the mean ± SEM. Data analyses were not blinded. Outliers were not excluded. Statistical significant threshold was set at P < 0.05.

142

3.4.10 Study Approval

All in vivo animal experiments were performed under a protocol approved by the

University of Minnesota Institutional Animal Care and Use Committees in accordance with both federal and institutional regulations for humane treatment of animals. Human blood samples were obtained from the Memorial Blood Centers which maintains an IRB- approved protocol for use of deidentified human donor specimens.

143

CHAPTER 4:

SYNERGISTIC ELIMINATION OF CD133 AND EPCAM

EXPRESSING TRIPLE NEGATIVE BREAST CANCER

144

4.1 INTRODUCTION

Information from the following chapter is currently under development for publication, and is being reproduced in part with permission from: Petersburg, J.; Vallera, D.A.; Wagner,

C.R. Synergistic Elimination of CD133 and EpCAM Expressing Triple Negative Breast

Cancer. The publication was principally written by the current author, Jacob Petersburg, and Carston Wagner with contributions from the coauthors.

4.1.1 Relevance of Cancer Stem Cells

Reponses to targeted anti-cancer approaches have been encouraging, yielding both growth inhibition and, in some cases, clearance of primary tumors. Nevertheless, long-term remission is still difficult to achieve. Cancer stem cells (CSCs) have been of significant interest since Dick and Bonnet identified a population in human myelomonocytic acute myeloid leukemia (AML) in 1997.195 The last decade has generated evidence confirming the existence of cancer stem cells (CSCs), which comprise anywhere from 0.1% to 20% of the cells within bulk tumors.196 Cancer stem cells (CSCs), also known as tumor- propagating cells or tumor-initiating cells, are subpopulations of undifferentiated, highly tumorigenic, cells responsible for promoting tumor initiation, self-propagation, and differentiation into the various tumor cell entities of a carcinoma.197-199 Additionally, CSCs appear to commonly be at the root of refractive relapse, following an apparent remission, due to their chemotherapy and radiation resistance.200, 201 For these reasons, there has been a growing skepticism of whether chemotherapy alone is likely to ever provide sustained,

145

high quality, remissions. Of those CSC markers recently identified, CD133 has been reported as a biomarker on the surface of various CSC tumor types, most notably: breast, brain, pancreatic, colon, and prostate, liver, lung and ovarian (Figure 4.1).202-209

Figure 4.1 PROM1 (CD133) Expression Levels Across Cancer Populations

Figure adapted from CBioPortal: compiled clinical data for PROM1 (CD133) expression across carcinoma types, as quantified by RNA Seq.

4.1.2 CD133 as a Cancer Stem Cell Marker

CD133, also known as prominin-1, is a five-transmembrane protein originally identified as a cell surface antigen present on CD34+ hematopoietic stem cells.210 Thus far the biological function for CD133 remains poorly understood as no endogenous ligands, or signaling mechanisms, have been defined.211 The current hypothesis is that CD133 acts as an organizer of cell membrane topology and organization due to the observation that

CD133 is commonly located on cell membrane protrusions, such as microvilli-like

146

structures on epithelial cells, which is important for increasing the surface area and reabsorption characteristics of those cells.212, 213 Additionally, CD133 may be involved in primitive cell differentiation, due to its connection with the WNT signal transduction pathway,213-215 which has been shown to be negatively associated with patient outcomes.216-

218

CD133 primarily gained interest after demonstrating that a CD133+ brain tumor subpopulation displayed in vivo stem cell properties. More specifically, the expression of

CD133 epitopes, AC133 and AC141, were shown to define a subpopulation of brain tumor cells with a significantly increased capacity for tumor initiation in xenograft models. In fact, following the transplantation of only 100 CD133+ cells into immune deficient mice, the exact same parent tumor was induced.208, 219 Whereas, transplanting the same number of CD133- cells did not yield any tumor outgrowth. Following the discovery of the

AC133/AC141+ population of brain tumor stem cells, the AC133 and AC141 epitopes have been extensively used as markers for purifying CSCs in other solid tumors.220-222

Consistently, these solid tumor models displayed the same CD133+ dependence to induce tumor regrowth in an immunodeficient mouse.

Although there are many commercially available anti-CD133 antibodies, they have several limitations. It is well known that, at any given time, the cell cycle status of tumor cells is highly heterogenous. In fact, when using an AC133 mAb, the CD133 immunoreactivity is highest in cells with the most DNA content, indicative of cells in the

S phase of the cell cycle. Conversely, CD133 detection was lowest in the G1–G0 phase.223

147

There for the detection of CD133 expression levels by commercial mABs is modulated by cell cycle phase and the state of differentiation.224 Indeed, Kemper and coworkers found a correlation between reduced glycosylation (an enzymatic, posttranslational modification whereby glycans are added to specific residues of a protein, usually in the plasma membrane, altering the tertiary and quaternary protein structure) and reduced detection of

AC133 and 293C/AC141 mAbs upon differentiation.225 This lack of detection was not due to CD133 downregulation, as confirmed by western blotting.226 Thus, CD133 epitopes not detected by commercial antibodies are not actually downregulated, but rather masked by changes in the structure of CD133, likely through differential glycosylation. Kemper and coworkers further demonstrated that commercial CD133 antibodies only recognize epitopes on extracellular loop 2 of CD133, which is inaccessible via conformational changes induced by differential glycosylation. Importantly loop 2 does not contain alternatively spliced exons, from the seven known splice variants, confirming glycosylation as the sole cause of conformational change.226

Equally important is the increase, and decrease, CD133 exhibits in response to hypoxia and chemotoxic stress.211 These facts, combined with the realization that cancer cell differentiation is likely not unidirectional, have resulted in controversy over the utility of CD133 as a CSC marker, and the relevance of the CSC hypothesis in general. To address these shortcomings, Swaminathan, Ohlfest, and coworkers generated a novel anti-CD133 monoclonal antibody (named clone 7) that specifically recognizes an epitope on CD133 independent of the glycosylation state.227 This led to an improvement of reliability and

148

specificity in CD133 binding and formed the backbone of several new cancer targeting antibody constructs.

4.1.3 CD133 Expression on Normal Tissues Cells

In addition to its presence on CSCs from multiple diseases (vide supra), CD133 is commonly found as a marker of somatic stem cells, ranging from hematopoietic, neural, prostate, kidney, liver, and pancreas.216 Thus, targeting of CD133+ bears the potential risks for on target, off tumor, side effects. For example, in the bone marrow, CD133 is expressed on hematopoietic cells which are crucial for the process of hematopoiesis.228 Fortunately, the anti-CD133 scFv derived from clone 7 generated by Swaminathan, Ohlfest, and coworkers is cross-reactive between mice and humans. The Vallera lab took advantage of this and developed a potent genetically engineered targeted toxin, known to inhibit the growth of tumor initiating cells in cancer xenograft models, and evaluated the effects in various progenitor assays including long-term culture and colony-forming assays.229 In each of their assays, including long term progenitor assays, minimal effects were found indicating that normal progenitors were not affected. Several explanations are possible for this outcome. (1) Normal stem and progenitor cells may express a lower level of CD133 than is seen on CSCs, leading to more toxicity in target cells than in physiologic progenitors. Indeed, this is the case in colorectal, pancreatic, gastric, and hepatocellular carcinomas.230 (2) Perhaps the plasticity of the human hematopoietic cells prevents off- target toxicity by selecting a normal stem cell population with a CD133- phenotype still

149

capable of differentiating into multiple hematopoietic cell types.231 Surronen et al. revealed that CD133+ cells have plasticity meaning that CD133+ cells can be generated from a population of CD133- cells.232 (3) CD133+ cells might be generated from myeloid precursors or monocytes that act as pluripotent stem cells.233 (4) The lack of toxicity may be based on de-differentiation which was described not only in mammalian, myeloblast and pancreatic cells,234 but also in late endothelial progenitors before their differentiation to mature endothelial cells.235 Upon loss of the capability to express CD133, these cells might still have the potential to again express CD133.

In a healthy central nervous system, CD133+ progenitor cells have not been identified, however, CD133-enriched membrane particles in the neural tube fluid have been detected.236 Fortunately, due to the brain-blood barrier, neither monospecific antibody conjugated immunotoxins nor bispecific antibodies should be able to pass into the central nervous system due to their large molecular size.237 Confirming this rationale, an in vivo mouse model demonstrated that mice exposed to a CD133 targeted immunotoxin showed no neurotoxicity, despite continuous infusion.238 Gehling and coworkers identified CD133+ progenitor cells in human peripheral blood capable of differentiating into hematopoietic lineages but also into endothelial cells.239 They showed that CD133 receptor directly interacts with the angiogenetic vascular endothelial growth factor which might be relevant for physiologic neovascularization but also for angiogenesis in cancer patients. In vivo angiogenesis could be inhibited by downregulation of CD133 using lentiviral short hairpin

RNA sequences to silence prominin-1 gene capillary formation.240 A study that

150

histologically analyzed lung tissue from lung cancer patients stated that CD133+ endothelial progenitor cells contributed to neovascularization and tumor growth vascular damage was not reported after using CD133 targeted constructs but data implicate the potential of capillary complications after administration.

4.1.4 Current CD133 Targeted Therapies

Several, diverse, approaches for selectively eliminating CD133+ cells have been developed. Typically, they fall into one of three broad categories: Immunotoxins, BiTES,

CAR-T cells, Bispecific NK-cell Engagers (BiKEs). Nano-particles, conjugated with anti-

CD133 antibody (clone 7) and loaded with paclitaxel (a microtubule targeting anticancer drug) were developed by Swaminathan et al.241 When Bulb/c nu/nu mice, in an MDA-MB-

231 orthotopic breast cancer model, were treated with targeted nano-particles they demonstrated greater tumor reduction than those of the control, as well as lower relapse rates. Swaminathan and coworkers further developed a scFv, derived from clone 7, that targeted CD133 and was species crossreactive.242 The scFv was then cloned onto a truncated form of pseudomonas exotoxin A (a catalytic toxin) and used for targeted toxin delivery in several in vivo xenograft models, including: head and neck,229 ovarian,243 and triple negative breast cancer (TNBC) models.244

Zhao and coworkers developed an asymmetric bispecific antibody (MS133), containing binding sites against CD133 and CD3, to generate BiTEs targeting CD133 that demonstrated cytotoxicity in vitro against a colorectal carcinoma cell line (HCT116).245

151

Furthermore, when activated T-cells were dosed in vivo to NOD/SCID mice a significant tumor repression was observed. Huang and coworkers also developed a CD133 targeting

BiTE which was applied against pancreatic (SW1190) cells both in vitro and in vivo.246 In addition to BiTEs, T-cells were also utilized as CAR-T cells engineered to target CD133.

Zhu and coworkers developed a CD133 targeted CAR-T which was shown to exhibit a significant reduction in tumor growth rate of an in vivo orthotopic glioblastoma model.247

However, CAR-T cells did exhibit signs of exhaustion during the course of therapy.

Interestingly, there has been one example of CD133 targeting CAR-T cells used clinically in a single case report.248 The patient presented with unrespectable/metastatic cholangiocarcinoma (CCA) and was treated with a cocktail of anti-EGFR and anti-CD133

CAR-T cells and following CD133 CAR-T infusion demonstrated a significant reduction in the size of metastasis. However, significant toxicities were observed following anti-

EGFR treatment and metastatic lesions reoccurred 4 months following CAR infusion.

While cytotoxic T-cells are the most commonly used cell type for immunotherapy there are labs that have demonstrated great success with Natural Killer (NK) cells. For example, the Vallera lab generated a bispecific antibody target CD133 and CD16 on NK- cells that, when used, formed bispecific NK-cell engager (BiKE) targeting CD133.249 Like bispecific T-cells and BiTEs, when the NK effector cell and target tumor cell are forced to interact they generate a synapse, triggering ADCC, and demonstrated efficacy against

CD133 expression Caco-2 colorectal cells. Furthermore the Vallera lab continued advancing NK cell therapy with the development of various Trispecific NK cell Engagers

152

(TriKEs).250 Examples include the formation of a TriKE targeting CD133 and EpCAM, which showed efficacy against cell lines expressing either CD133 or EpCAM, as well as the formation of a TriKE targeting CD133 and carrying interleukin (IL) 15. TriKEs carrying IL-15 to the immunological synapse were shown to be superior to standard BiKEs in vivo due to the improved cytotoxicity and activation levels induced by IL-15.

4.1.5 CD133 Expression in Triple Negative Breast Cancer (TNBC)

Breast cancer is the most frequently diagnosed cancer and a leading cause of death amongst women. In the United States, approximately, 250,000 women are diagnosed with breast cancer annually and over 40,000 die each year of breast cancer.251 Breast cancer that does not express the estrogen receptor (ER), progesterone receptor (PR), or HER-2, is referred to as TNBC and comprises approximately 15% of all diagnosed breast cancers.

Current highly successful therapies targeting the ER, PR and HER-2/Neu cannot be used for the treatment of TNBC. Thus, given the limited treatment options and enhanced aggressiveness, the outcomes for TNBC patients is significantly lower than for other breast cancer sub-types.251 Consequently, the development of new treatment approaches for

TNBC is a significant un-met need. Recently, immune checkpoint inhibitors have begun to undergo clinical evaluation for the treatment of TNBC. Although final results will not be known for some time, initial results have been mixed, due to the inherent heterogeneity of checkpoint expression among TNBC tumors that makes targeted therapy challenging.

153

Expression of CD133 has been recently reported in breast cancer cell lines generated from Brca1Δexon11/p53+/- mouse mammary tumors.252 In fact, it was found that 2-

4% of CD133+ cells in multiple breast cancer cell lines derived from a Brca1Δexon11/p53+/- tumor had stem cell like characteristics. This included the expression of stem cell genes, the ability to form spheroids and the in vivo reconstitution of tumors in an immunocompromised mouse with as few as 100 cells.252 TNBC represents a unique subgroup of breast cancer with a specific molecular profile, aggressive behavior pattern, lack of effective therapies and relatively poor prognosis.253 Furthermore, TN breast cancer has been shown to have a CD133+ CSCs population that is responsible for tumor vasculogenesis.254 Importantly, vasculogenic mimicry has been associated with highly aggressive tumor cells.255

Due to our results in chapter 3, demonstrating the ability to eliminate EpCAM+ breast cancer tumors, we chose to target both EpCAM and CD133 in TNBC tumors using anti-CD133 (αCD133) and anti-EpCAM (αEpCAM) PARs (αCD133/αEpCAM PARs).

Our central hypothesis is that the destruction of both primary tumor cells and CSCs is necessary for long-term cancer eradication and that specifically targeting therapeutic T- cells to both a primary tumor marker (e.g., EpCAM) and a CSC marker (e.g., CD133) will contribute to TNBC eradication and improve clinical outcomes.

154

4.2 RESULTS AND DISCUSSION

4.2.1 Construction of anti-CD133-DHFR2 (αCD133-DHFR2) Plasmid

Due to the importance of being able to target both glycosylated and non- glycosylated forms of CD133, we chose to incorporate the scFv designed by Ohlfest and coworkers (derived from the anti-CD133 targeting clone 7 mAb) into our DHFR2 construct as a fusion protein. The anti-CD133 sequence was generously obtained from Dr. Dan

Vallera in a PET28b vector and the CD133 scFv specific sequence was amplified and ligated onto the N-terminus of a plasmid encoding DHFR2 and terminating in a FLAG tag

(Figure 4.2). Additionally, the anti-CD133 scFv was separated from the DHFR2 construct with a flexible 13 amino acid linker. All plasmid constructs were verified by classic sanger sequencing before transformation into BL21 E. coli expression cells and expressed as an insoluble inclusion body. To ensure proper protein induction and expression, a small-scale protein induction test was performed using several 5 mL cultures isolated from distinct

BL21 E. coli colonies isolated from the previous transformation. Each culture was separated into two equal fractions followed by induction of one of the fractions with 300

µM IPTG (Figure 4.3). The cultures were pelleted through centrifugation following a 2- hour incubation period and lysed to release cell contents into solution. Samples from each cell lysate were run on an SDS-PAGE electrophoresis gel to observe the increased protein expression upon induction. The correct molecular weight is observed in only induced lanes at 63 kDa. Protein refolding was performed as previously described and purified by methotrexate affinity column chromatography followed by DEAE anion exchange

155

chromatography.75, 114 The typical isolated yield for the purified anti-CD133-1DHFR2

(αCD133-DHFR2) was found to be around 1-2 mg/L of culture.

Figure 4.2 PCR amplification of CD133 scFv Specific Sequence

PET28b vector containing αCD133 scFv underwent PCR amplification of the scFv specific segment (Lane 2) and was ligated into a DHFR2 PET28a vector (lane 2). Lane 1 depicts a standard molecular weight ladder.

156

Figure 4.3 αCD133-DHFR2 Induction Test

Induction test of αCD133-DHFR2 protein with and without IPTG present in three separate colonies. The protein is apparent at 63 kDa in +IPTG lanes only.

4.2.2 In Vitro Analysis of αCD133 CSANs

Following the production and purification of the αCD133-DHFR2 monomer, we incubated the fusion protein, in addition to αCD3-DHFR2, with bisMTX dimerizer (1:1:2.2 equivalents) for 30 minutes to form αCD133/αCD3 CSANs which were characterized by size exclusion chromatography (Figure 4.4). These octameric rings are generated by random combinations, and statistically calculated to be greater than ninety-nine percent bispecific in makeup.78 As expected bispecific CSANs generate larger, octameric species, which eluted at 19 minutes with nearly 100% oligomerization whereas the smaller

αCD133-DHFR2 monomer proteins eluted at 28.5 minutes. Importantly, the self-assembled

157

αCD133/αCD3 CSANs exhibited the same size dimensions, and thus polyvalency (7-10), found for previous bispecific CSANs discussed in chapter 3.

Figure 4.4 Oligomerization of αCD133-DHFR2 and αCD3-DHFR2

Size exclusion chromatography of αCD133-DHFR2 monomer (black trace) and αCD133- DHFR2 with αCD3-DHFR2 and bis-MTX dimerizer at a 1:1:2.2 ratio (red trace).

Upon the confirmation of ring formation, binding studies were performed using flow cytometry to ensure the functionality of the CD133 targeting scFv. We chose to evaluate their binding potential against a colorectal carcinoma cell line (HT-29) as they universally express CD133 making them an excellent cell line of choice for initial binding studies. αCD133 CSANs were generated using bisMTX dimerizer and incubated with HT-

29 cells in addition to co-staining with anti-FLAG-PE to probe for the FLAG tag present on αCD133-DHFR2.76 As seen in figure 4.5 binding of the αCD133 CSANs to HT-29 cells was observed and comparable to binding seen from a commercially available αCD133

158

mAb. Interesting, only the αCD133 constructs with the scFv fused to the N-terminus of

DHFR2 were capable of binding (data not shown). This was likely due to an unforeseen conformational change in the scFv of steric hindrance that disallowed binding.

Figure 4.5 αCD133 CSAN In Vitro Binding Characterization

Left: CD133+ HT-29 cells stained with αCD133 CSANs plus anti-FLAG-PE (orange), anti- FLAG-PE alone (blue) and non-treated (red). Right: CD133+ HT-29 cells stained with αCD133-APC mAb (blue) and non-treated (red).

A colorectal carcinoma cell line (HT-29) was initially used for cytotoxicity studies due to their universal, high levels, of CD133 expression. Unactivated T-cells treated with increasing αCD133/αCD3 concentrations and then incubated with target HT-29 cells for

24 hours at an effector-to-target ratio of 10:1 (Figure 4.6). Maximal cytotoxicity, 59% target cell lysis, was observed for cells incubated with 100 nM of the αCD133/αCD3

CSANs, with significant cytotoxicity observed at concentrations as low as 10 nM.

Following the confirmation of αCD133/αCD3 PAR induced cytotoxicity we explored the

159

combination of targeting both CD133 and EpCAM simultaneously with MDA-MB-231 cells.

Figure 4.6 ΑCD133/αCD3 CSAN labeled T-cells selectively activate and kill target CD133+ cells.

Target cancer cell (HT-29 colon carcinoma) lysis by unactivated PBMCs was evaluated at a set 10:1 E:T ratio with increasing concentrations of CSANs.

Following the confirmation that αCD133/αCD3 CSANS were capable of both target antigen binding and target cancer cell lysis we chose to move onto a true triple negative breast cancer (TNBC) model. To address the specific hypothesis that targeting T- cells to a primary tumor marker (such as EpCAM) and a CSC marker (such as CD133) are necessary for TNBC eradication, we prepared both αEpCAM/αCD3 CSANs and

αCD133/αCD3 CSANs. Approximately, 10-20% of MDA-MB-231 cells (a TNBC cell

160

line) have been shown to be positive for CD133.203, 244, 252, 254, 256 Consistent with literature values, when grown in spheroid, we found that MDA-MB-231 cells exhibited the following heterogeneity: 81.2±1.5% EpCAM+CD133+, 11.3±2.0% EpCAM+CD133+, 6.9±1.7%

EpCAMlowCD133+ and 1.1±0.5% EpCAMlowCD133- (Figure 4.7).

Figure 4.7 EpCAM and CD133 Expression profile on MDA-MB-231 cells.

MDA-MB-231 cells were grown in spheroid and analyzed for CD133 and EpCAM expression by αEpCAM-AF647 mAb and αCD133 CSANs. Dead cells were eliminated with ghost red viability dye and only single cells were analyzed. αCD133 CSANs were identified by anti-FLAG-PE. Experiment was performed in triplicate to provide 81.2±1.5% EpCAM+CD133+, 11.3±2.0% EpCAM+CD133+, 6.9±1.7% EpCAMlowCD133+ and 1.1±0.5% EpCAMlowCD133-.

161

As expected, when MDA-MB-231 cells were treated with αCD133 PARs the maximal target cell killing was achieved at a much lower concentration of αCD133/αCD3

CSANs, 50 nM, due to the lower total expression of CD133 on MDA-MB-231 cells

(Figure 4.8). In fact, decreased levels of cell killing at concentrations were seen at concentration immediately above 50 nM indicating we were slowly saturating the cell surface. Furthermore, this same effect was seen with αEpCAM PARs due to the relatively low level of EpCAM expression seen on MDA-MB-231 cells; which is in contrast to the majority of breast cancer cell lines. However, when both αEpCAM and αCD133 PARs were used simultaneously we observed a significantly higher level of target cell lysis (62%) than either αEpCAM (47%) or αCD133 (38%) PARs exhibited individually. Of special note, no decreased cell killing was seen as the concentrations increased, up to 200 nM, which is likely in response to the dilution of targeting elements used when two CSAN constructs are used.

162

Figure 4.8 ΑCD133/αCD3 and αEpCAM/αCD3 CSAN labeled T-cells selectively activate and kill target MDA-MB-231 cells.

Target cancer cell (MDA-MB-231 TNBC cells) lysis by unactivated PBMCs was evaluated at a set 10:1 E:T ratio with increasing concentrations of CSANs. Cells were treated with αEpCAM, αCD133, αCD3, αEpCAM/αCD3, αCD133/αCD3, or a combination of αCD133/αCD3 and αEpCAM/αCD3 PARs. Data shown was obtained from one donor (n=3), but representative of three donors. *P<0.05 with respect to αEpCAM CSAN and no treatment controls, by 2-tailed Student’s t test.

As observed with αEpCAM PAR T-cells, full activation of the αCD133 and

αCD133/αEpCAM PAR T-cells was dependent on the presence of antigen-positive tumor cells. PBMC T-cell signaling activation was monitored the amount of IL-2 produced and the results were highly consistent with what was previously seen. When PBMCs were treated with αEpCAM PARs in the presence of EpCAM expressing MCF-7 and HT-29 cells the production of IL-2 (Figure 4.9) was enhanced by 12.0- and 12.7-fold, respectively. However, in the presence of MDA-MB-231 cells, which are very low

163

Figure 4.9 Synergistic αEpCAM/αCD133 Cytokine Release

Unactivated PBMCs were co-cultured with media, 1DD/αCD3 CSANS, αCD133/αCD3 CSANs, αEpCAM/αCD3 CSANs, or both αCD133/αCD3 and αEpCAM/αCD3 CSANs to generate non-labeled PBMCS, non-targeted PARs, αCD133 PARs, αEpCAM PARs or dual targeting αCD133/αEpCAM PARs, respectively. Generated constructs were incubated in the presence of no target cells, U-87 MG cells (EpCAMnegCD133neg), MCF-7 cells (EpCAMhighCD133neg), HT-29 cells (EpCAMhighCD133pos), or MDA-MB-231 cells (EpCAMlowCD133partial pos). Following the 24-hour incubation, the media was analyzed for IL-2. Data shown was obtained from one donor (n=3), but representative of three donors. *P<0.05, by 2-tailed Student’s t test and one-way ANOVA.

expressers of EpCAM the enhancement was only 5.7-fold. Likely, the higher expression of EpCAM receptor on MCF-7 and HT-29 cells lead to more robust engagement between the cell surface of PBMCs and the target cell leading to a stronger activation signal.

Additionally, αCD133 PARs showed a very similar level of IL-2 production (10.1-fold increase) when targeting HT-29 cells which universally express CD133 receptor, albeit at

164

a lower density than EpCAM, leading to the lower level of activation seen from αEpCAM

PARs. Interestingly when αCD133 PARs were incubated with MDA-MB-231 cells, which exhibit CD133 expression on 20% of the total population (Figure 4.7), there was only a

50% reduction in IL-2 production compared to the universally CD133 expressing HT-29 cells. While there was only 20% of the cells that express CD133 in the total population, each individual cell did express similar levels to HT-29 cells and likely explain the full activation seen. Furthermore, while αEpCAM and αCD133 PARs targeting MDA-MB-231 cells (which express low EpCAM and are only 20% CD133 positive) individually produced less of IL-2 response compared to higher expressing cell lines (HT-29 cells), when combined in αEpCAM/αCD133 PARs they were able to produce a far greater response to target MDA-MB-231 cells (10.9-fold).

4.2.3 In Vivo αEpCAM/αCD133 PAR Anti-Tumor Activity

To characterize the in vivo anti-tumor activity of the αEpCAM/αCD3 and

αCD133/αCD3 PAR T-cells, we used the previously established orthotopic breast cancer model, in NSG mice, as discussed in chapter 3. MDA-MB-231 cells were unilaterally injected into the fourth mammary fat pad of NOD.Cg-Prkdcscid Il2rγtm1Wjl/SzJ (NSG) mice.

Once tumors reached 50 mm3 mice were randomized in cohorts of 5 and treatment groups including T-cells were IV infused with 20 million PBMCs, and allowed 4 days to engraft the NSG mice and begin the process of generating a humanized immune system. Following the 4-day engraftment period, IV treatments were initiated, including: PBS, PBMCs (dosed

165

with only PBS following initial PBMC infusion), αCD3 CSANs (1 mg/kg),

αEpCAM/αCD3 CSANs (1 mg/kg), αCD133/αCD3 CSANs (1 mg/kg), and both

αCD133/αCD3 and αEpCAM/αCD3 CSANs together (1 mg/kg total) every two days, for

6 total treatments. A two-day dosing schedule was chosen based on previous results, performed in chapter 3, demonstrating that PARs are stable on the cell surface up to 4 days and that daily dosing was not required for in vivo tumor clearance. Furthermore, by

IV infusing CSANs, PARs are formed in vivo and avoid the complication of ex vivo T-cell modification. The prevailing belief is that directly infusing protein constructs, multivalently displaying αCD3, systemically activate T-cells by oligomerization of TCRs.

This systemic activation would subsequently result in extensive T-cell anergy within the mouse. However, we have previously demonstrated that CSAN labelling alone only activates memory cells and that naïve T-cell activation only occurred when CSANs directed their interaction with antigen expressing tumor cells (Chapter 3). Implying that naïve T-cells not in the tumor microenvironment will remain unactivated, and unchanged, by PAR therapy.

When αCD133 and αEpCAM PARs were dosed to mice bearing MDA-MB-231 tumors a partial response in tumor reduction was observed (Figure 4.10). ΑEpCAM PARs were capable of immediately inducing a small decrease in tumor mass, however following completion of the dosing schedule tumor volume quickly rebounded to similar growth rates of the PBS control. Considering we previously demonstrated αEpCAM PARs were capable of completely eliminating MCF-7 (high EpCAM expressers) breast cancer tumors, we

166

reasoned the inability to decrease MDA-MB-23 tumor mass further was due to the relatively low expression of EpCAM. In contrast to αEpCAM PARs, αCD133 PARs didn’t show immediate activity. However, 8 days following the initial treatment tumors ceased growing and remained stagnant for over 8 days following the final treatment. An explanation for the significantly delayed regrowth rate likely rests on the fact that CD133+

MDA-MB-231 cells have been associated with tumorigenic stem cells. By selectively

167

Figure 4.10 In Vivo efficacy study of bispecific PARs in an orthotopic TNBC mouse model.

NSG mice were inoculated in the mammary fat pad with 1.0x106 MDA-MB-231 cells. Cohorts were randomized when tumors were ~80 mm3 and IV inoculated with 20 million PBMCs. Treatments were initiated 4 days later, including: PBS, PBMC only (this experimental group acquired treatments of PBS only following the initial PBMC engraftment), 1 mg/kg αCD3 monospecific CSANs, 1 mg/kg αCD133/αCD3 bispecific CSANs, 1 mg/kg αEpCAM/αCD3 bispecific CSANs, and both αCD133/αCD3 and αEpCAM/αCD3 bispecific CSANs at .5 mg/kg each. Treatments were administered every 2 days for a total of 6 treatments. Tumor growth was monitored every by caliper and recorded as mm3. *P<0.05 with respect to readings statistically significant from the PBS control group, by 2-tailed Student’s t test.

targeting this population, we likely reduced the most tumorigenic population enough to delay regrowth. Indeed, when tumors were isolated and analyzed for EpCAM and CD133 expression we can see that αCD133 PARs were capable of preferentially eliminating

CD133+ cells, while αEpCAM PARs also selectively targeted EpCAM+ cells (Figure

4.11). Interestingly, targeting EpCAM appears to have enriched the tumors for CD133,

168

which is likely due to CD133+ cells containing a distinct population lower in EpCAM expression. Furthermore, this effect likely contributed to the rapid rebound in tumor growth seen following the conclusion of αEpCAM therapy.

Figure 4.11 CD133 and EpCAM Expression in PAR Treated Tumors.

Tumors were isolated from PBS, PBMC, αCD133 PAR and αEpCAM PAR treated mice 12 days following initiation of treatment. Tumor tissue was homogenized and cells were stained with CD133-PE, anti-Human-BV421, anti-Human-BV605, αEpCAM-AF647 and ghost red viable dye before analysis with an LSRFortessa H0081. Cells positive for ghost red viability and anti-mouse dyes were removed from analysis. Anti-human positive cells were characterized for expression levels of CD133 and EpCAM.

169

Remarkably, when both αCD133 and αEpCAM PARs were used in conjunction we observed a full tumor regression (Figure 4.10). Importantly, the total protein concentration of PARs used in the dual targeting application was the same as the individual αCD133 and

αEpCAM PARs, half the amount of each, implying a significant synergism between the two. We postulated that elimination of the bulk EpCAM+ tumor cells allowed for additional infiltration of T-cells to eliminate CD133+ tumorigenic cells. Of note, when simultaneously targeting CD133 and EpCAM we observed no tumor regrowth and a durable response with only a single remission out to 90 days (Figure 4.10 & 4.12).

170

Figure 4.12 In Vivo survival curve of bispecific PARs in an orthotopic TNBC mouse model.

NSG mice were inoculated in the mammary fat pad with 1.0x106 MDA-MB-231 cells. Cohorts were randomized when tumors were ~80 mm3 and IV inoculated with 20 million PBMCs. Treatments were initiated 4 days later, including: PBS, PBMC only (this experimental group acquired treatments of PBS only following the initial PBMC engraftment), 1 mg/kg αCD3 monospecific CSANs, 1 mg/kg αCD133/αCD3 bispecific CSANs, 1 mg/kg αEpCAM/αCD3 bispecific CSANs, and both αCD133/αCD3 and αEpCAM/αCD3 bispecific CSANs at .5 mg/kg each. Treatments were administered every 2 days for a total of 6 treatments. Survival was monitored out to 90 days when graft vs host (GVH) disease symptoms began. Kaplan-Mier Survival Plot. *P<0.0001 with respect to PBS control, by log rank test.

While all targeted PAR therapy demonstrated a significant increase in survival

(Figure 4.12) only the dual targeting of EpCAM and CD133 resulted in full tumor remission, with four of five mice surviving tumor free. Interesting while αEpCAM PARs demonstrated a more robust initial response in tumor clearance (Figure 4.10), αCD133 171

PARs provided a more sustained tumor reduction with a significantly greater median survival 9 days longer than αEpCAM. Over the course of the anti-tumor studies, no significant weight loss was observed, regardless of dosing schedule. However, upon the initiation of therapeutic treatment, a transient decrease in weight was observed for mice experiencing PAR therapy. As the decrease was transient and less than 5% of the total mouse weight the likely cause is tumor cell lysis. Additionally, due to tumor burden, a small decrease was observed by the end of the study for the animals treated with PBS,

PBMCs and αCD3 PAR controls (Figure 4.13).

Figure 4.13 In Vivo efficacy study mouse weights.

Tumor growth was monitored every by caliper and recorded as mm3.

172

4.2.4 Importance of CD133 in Tumorigenicity

In order to further evaluate the importance of CD133+ in TN breast cancer we developed a technology for directly isolating cells expressing CD133 with the same

αCD133 scFv used in our PAR platform. This is important due to the ability to recognize both the glycosylated and non-glycosylated forms of CD133 to ensure all CD133+ are detected. To accomplish this, we used non-coated NH2-Dynabeads that were easily functionalized with Biotin-PEG4-NHS ester. αCD133/mSA CSANs (a bispecific CSAN including both a CD133 targeting element and monovalent streptavidin; mSA-DHFR2 fusion protein development will be described in chapter 5 with greater detail) could then be rapidly bound to biotin functionalized beads in addition to the non-targeted 1DD/mSA

CSAN control. Beads are then incubated with cell populations expressing CD133 and subsequently removed by magnetic separation. Importantly, even cells expressing low levels of CD133 are isolated due to the highly multivalency effect the functionalized beads possess. Additionally, by using Dynabeads coated in biotin, instead of streptavidin, we were able to avoid the issue of non-specific binding typically seen with streptavidin coated beads. As CSANs are rapidly disassembled in the presence of trimethoprim we would be able to quickly disassemble the multivalent CSANs and release CD133+ from the beads for further use. Cells are then validated with a commercially available αCD133 mAb.

173

Figure 4.14 ΑCD133/mSA CSAN Based CD133 Depletion and Enrichment.

Non-coated NH2-Dynabeads functionalized with an excess of Biotin-PEG4-NHS ester and coated with αCD133/mSA CSANs. Beads were MDA-MB-231 cells for 30 minutes at 4°C to isolate a CD133 depleted (supernatent) and CD133 enriched (bound to beads) before magnet bead isolation. The beads were incubated with trimethoprim to disassemble the αCD133/mSA CSANs and release pure CD133+ cells into the supernatant. Isolated CD133 positive cells were added to cultured MDA-MB-231 cells for an enriched population. Isolation controls were run with a non-targeted 1DD/mSA Bispecific CSAN to ensure no non-specific binding occurred. Isolations were validated by flow cytometry with αCD133- PE mAB.

174

We were able to show the removal of CD133+ cells following incubation with

αCD133 coated dynabeads as well as CD133 enrichment (Figure 4.14). Interestingly, two weeks following the removal of CD133+ cells we observed a prominent population of

CD133+ spontaneously arose after two weeks. This occurrence lends credence to the observation that cancer cells undergo “plasticity” in differentiation and are capable of generating CD133+ cells from a CD133- population. The dynamic nature of CD133+ cells in breast cancer underscores the importance of targeting both EpCAM and CD133 to prevent regrowth following sufficient time for dedifferentiation of CD133- cells. When

MDA-MB-231 cells were enriched, and depleted, for CD133 were implanted into immunocompetent mice we observed a difference in growth rate emphasizing the importance of CD133 (figure 8). All three implantations concluded in similar tumor growth rates, however the initial rate, and onset, were markedly different. The greater initial rate for CD133 enriched cells emphasizes the importance CD133 tumorigenicity, while the similar final rates point to the dynamic expression of CD133 in MDA-MB-231 cells.

175

Figure 4.15 Effects of CD133 Depletion and Enrichment on Orthotopic TN Breast Cancer Model.

8 to 10 week old female NSG Mice were injected with either 106 standard MDA-MB-231 cells, Enriched CD133+ cells or depleted CD133- cells in the mammary fat pad through the 4th nipple. Injection was performed in 50 µL 50:50 Matrigel/PBS while the mouse was under general anesthesia. Tumor growth was monitored daily by caliper to measure the height x width x length and recorded as mm3.

4.3 CONCLUSIONS

In conclusion, our laboratory has successfully developed dual targeting

αCD133/αEpCAM PARs which were capable of stably binding to T-cells and inducing the production of IL-2 and cytotoxicity in a wide range of target antigen (CD133 and EpCAM) expressing cells. Furthermore, an orthotopic breast cancer model validated the ability of

αCD133 and αEpCAM targeting to combine synergistically in targeting TNBC MDA-MB-

231 cells. Complete tumor eradication only occurred when EpCAM and CD133 were targeted simultaneously and lead to full remission in 4 out 5 mice. Following PAR 176

treatment, the tumors were isolated and quantified for EpCAM and CD133 expression to indicate the ability of PARs to eliminate specific cell populations when targeting a single antigen. Importantly, the depletion and enrichment of CD133 specific cells, within the

MDA-MB-231 cell population, highlighted the tumorigenicity of CD133 positive cancer cells. When CD133 cells were depleted there was a significant decrease in tumor growth rate. However, the final growth velocity was the same for all three constructs emphasizing the ability for CD133 to upregulate when required. Collectively, our results demonstrate the importance of targeting both the bulk tumor and more tumorigenic cells (stem cells) when providing immunotherapy.

4.4 MATERIALS AND METHODS

4.4.1 Cell Culture

HT-29, colon carcinoma, cells were obtained from American Type Culture

Collection (ATCC, Rockville, MD) and were monolayer cultured in Dulbecco’s Modified

Eagle’s Medium (DMEM) supplemented with 10% FBS, 100 U/mL penicillin, 100 µg/mL streptomycin, and L-glutamine at 37°C in 5% CO2. MDA-MB-231 cells (ATCC,

Rockville, MD) were cultured with Dulbecco’s modified Eagle’s medium supplemented with 10% FBS, 100 U/mL penicillin and 100 µg/mL streptomycin at 37°C in 5% CO2.

MDA-MB-231 cells were grown in 3D culture by mixture-seeded with Matrigel. Briefly, cells were resuspended in ice cold 100% Matrigel and then plated. Plates were incubated for 10 minutes at 37°C before overlaying cells with complete media.

177

4.4.2 CD133 plasmid Construction

A PET28b vector containing the CD133 nucleic acid sequence was kindly obtained from the Vallera Lab. The following primers were designed to amplify the CD133 sequence only while additionally adding restriction sites for Xba1 and Sac1: Forward-5’-

GCGCTCTAGATGACATTGTTCTCTCCCAGT-3’ and Reverse-5’-

GCGCGAGCTCTCACTATGAGGAGACTGT-3’. PCR amplification was performed and subsequently subjected to 1 ul of Dpn1 for 1 hour to eliminate parent plasmid. PCR mixture was then purified with a PCR purification kit and eluted into 20 ul H20. Double digestion was performed with Xba1 and Sac1 enzymes and then purified by PCR purification kit.

Double digestion of PET28a Vector containing previous 1DHFR2 sequence was performed with Xba1 and Sac1 enzymes. Vector was isolated by gel electrophoresis and then excised and purified by gel extraction kit and eluted into 33 ul H20. Vector was dephosphorylated and ligated with CD133 PCR product. Following incubation the entire ligation mixture was transformed into XL1-blue cells and plated onto kanamycin containing plates. Control ligation yielded one colony while true ligation yielded 30 to 40 colonies. Colonies were picked and verified by plasmid sequencing.

4.4.3 αCD133/αCD3 CSAN Oligomerization and Characterization

To create bispecific CSANs, equal parts of purified αCD133-DHFR2 and DHFR2-

αCD3 proteins (2-8 µM) were combined with 2.2 equivalents (1:1:2.2 ratio) of either C9- bisMTX dimerizer or FITC-conjugated bisMTX trilinker in phosphate-buffered saline

178

(PBS). For monospecific CSANs, single purified fusion proteins were incubated with 2.2 equivalents (1:2.2 ratio) of either C9-bisMTX dimerizer or FITC-conjugated bisMTX trilinker in PBS. CSANS were allowed to incubate at room temperature for 30 minutes, in the absence of light. All proteins and CSAN constructs were analyzed by size exclusion chromatography (SEC) to observe the average size of ring formation, by injection onto a

Superdex G200 column connected to a Beckman Coulter HPLC equipped with a diode array detector and using PBS as a mobile phase. Elution times were monitored at 280 nm to observe the change in hydrodynamic radius compared to monomeric species.

4.4.4 Binding Assays

DHFR2-αEpCAM and αCD133-DHFR2 samples (4-20 µM) were incubated with

1.1 equivalent of bis-MTX-FITC and bis-MTX, respectively, in PBS for 1 hour at room temperature to generate αCD133 and αEpCAM CSANs. Both CSAN constructs (1 M) were incubated with 1 million EpCAM+ MDA-MB-231, or CD133+ HT-29, cells at 37C for 1 hour and subsequently washed three times with PBS supplemented with 1% BSA and

0.1% sodium azide (FACS buffer). Samples were subsequently incubated with anti-FLAG-

PE to bind the flag epitope on αCD133 CSANs prior to an additional 3x washing steps in

FACs buffer. Samples were filtered to remove cell aggregate prior to analysis by flow cytometry using a BD LSR II flow cytometer. The mean fluorescence intensity (MFI) was monitored and compared to unstained PBMCs as a background control.

179

4.4.5 Cytotoxicity Assays

Cell lysis was evaluated by measuring LDH (lactate dehydrogenase) release from cells with the non-radioactive cytotoxicity assay (CytoTox 96® Non-Radioactive

Cytotoxicity Assay, Promega). The day previous to the experiment 5x103 target cells, colon carcinoma (HT-29) or TN Breast cancer (MDA-MB-231) cells, were seeded into a 96-well plate in 200 μL of RPMI-1640 media per well. The following day the resting PBMCs, at a

10:1effector (E) to target (T) cell (E:T) ratio, were counted and incubated with 0 to 200 nM of the αEpCAM/αCD3 bispecific CSANs, αCD133/αCD3 bispecific CSANs or both for one hour at 37°C with 5% C02. Following the initial incubation, PBMCs were washed and resuspended in RPMI before addition to 96-well plate containing target cells and incubated for 24 hours under standard conditions. Lysis buffer (provided in assay kit) was added to control wells with only MCF-7 cells to estimate the maximum LDH release. The absorbance at 490 nm was measured and recorded using a Synergy H1 Multi-Mode Reader

(Biotek). Data was corrected for media absorbance, and values were determined per the following equation: ((LDH release sample – SReffector – SRtarget)(MRtarget – SRtarget)) x 100. SR: spontaneous release; MR: maximum release.

4.4.6 Immunostaining and Cytokine Analysis

IL-2 and IFN-γ measurements in the cytotoxicity assay supernatants were analyzed using

ELISA per the conditions provided by IFN-γ ELISA kit (Invitrogen) and IL-2 ELISA kit

(Invitrogen). In brief, following the incubation period the supernatant was removed and

180

4.4.7 Orthotopic TN Breast Cancer (MDA-MB-231) Model

Six- to 8-wk-old female NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice were injected unilaterally into the fourth mammary fat pad with 1.0x106 MDA-MB-231 cells while the mouse was under 2% isoflurane. The injection was performed in 50 µL of 50:50

Matrigel/PBS directly through the nipple. Once tumors were ~50 mm3 mice were randomized into cohorts of 5 mice, outliers were removed from the study, and those treatment groups receiving PBMC based therapy were IV infused with 20 million peripheral Blood Mononuclear Cells (PBMCs) for the engraftment of a human immune system. Treatments were initiated 4 days later, including: PBS, PBMC only (this experimental group acquired treatments of PBS only following the initial PBMC engraftment), 1 mg/kg αCD3 monospecific CSANs, 1 mg/kg αCD133/αCD3 bispecific

CSANs, 1 mg/kg αEpCAM/αCD3 bispecific CSANs, and both αCD133/αCD3 and

αEpCAM/αCD3 bispecific CSANs at .5 mg/kg each. Treatments were administered every

2 days for a total of 6 treatments. Body weight was monitored daily, and tumor growth was monitored daily by caliper to measure the height x width x length and recorded as mm3.

181

A second cohort of mice, undergoing the same treatments as above, were sacrificed

12 days after the initial treatment and their tumors were isolated. Tissue was minced into very fine pieces and transferred into a 50-ml Conical tube. 10-15ml of warm tumor

Collagenase solution was added tubes were shaken on rotary shaker for 2-3 hours until all larger tissue fragments were digested. HBSS with 2% FBS was added to the 50 mL tube and each sample was passed through a 40 uM cell filter. Samples were spun down, washed in HBSS and counted prior to flow cytometry analysis. Cells were stained with CD133-PE, anti-Human-BV421, anti-Human-BV605, αEpCAM-AF647 and ghost red viable dye before analysis with an LSRFortessa H0081.

4.4.8 CD133 Depletion Assays

Non-coated NH2-Dynabeads functionalized with an excess of Biotin-PEG4-NHS ester (per manufacturer recommended instructions). ΑCD133/mSA CSANs were generated at 100 nM (.1 mg total protein) and coated onto 500 µl of Biotin functionalized beads. Beads were washed with PBS x3 prior to incubation with 100 million MDA-MB-

231 cells for 30 minutes at 4°C before magnet bead isolation. The supernatant, CD133- population, was removed and the beads were washed 3x with PBS to acquire pure CD133+ cells. The beads were incubated with 200 µM Trimethoprim, in PBS, for 30 minutes at room temp to disassemble the αCD133/mSA CSANs and release pure CD133+ cells into the supernatant. Isolated CD133 positive cells were added to cultured MDA-MB-231 cells for an enriched population. Isolation controls were run with a non-targeted 1DD/mSA

182

Bispecific CSAN to ensure no non-specific binding occurred. Isolations were validated by flow cytometry with αCD133-PE mAB.

8 to 10 week old female NSG Mice were injected with either 106 standard MDA-

MB-231 cells, Enriched CD133+ cells or depleted CD133- cells in the mammary fat pad through the 4th nipple. Injection was performed in 50 µL 50:50 Matrigel/PBS while the mouse was under general anesthesia. Tumor growth was monitored daily by caliper to measure the height x width x length and recorded as mm3.

183

CHAPTER 5: STREP-PARS FOR THE OPTIMIZATION OF IMMUNOTHERAPY TARGETING CONSTRUCTS

184

5.1 INTRODUCTION

Portions of the information from the following chapter are currently under review for publication, and are being reproduced in part with permission from: Petersburg, J.;

Csizmar, C. M.; Case, B.; Hackel, B. A.; Wagner, C. R. Strep-PARs for the Optimization of Immunotherapy Targeting Constructs. The publication was principally written by the current author, Jacob Petersburg.

5.1.1 Current Bispecific Scaffold Selection

As discussed in chapter 1 and 3, bispecific antibodies are emerging as an important class of biopharmaceutical. To date, the vast majority of bispecific antibodies are created from either conventional antibodies or antibody fragments engineered into more complex configurations. However, the early identification of components optimized for inclusion in the final format (in order to deliver both efficacy and robust biophysical properties) is a recurring challenge in the development of bispecific antibodies.

The first-generation of bispecific antibodies were produced by means of hybrid hybridomas or chemical cross-linking; however, in both of these approaches the generated antibody populations exhibit heterogeneous structural properties, leading to sub-optimal efficacy in the clinical setting.257, 258 Recent advances in recombinant approaches have enabled the production of homogenous bispecific antibody molecules, of which several have shown efficacy in clinical trials. One of the advantages of the recombinant approach

185

for bispecific antibody design is the downsizing of antibody because the bispecific function can be generated by using Fvs only.48,259

These potential advantages of small T-cell recruiting antibodies have driven researchers to generate a large number of these antibodies with different cancer targets and bispecific structure formats; the studies have shown that the cytotoxic activities of these antibodies depend on the antigen target and the antibody structure format; for instance, changing the target can cause a ~103 -fold difference in cytotoxicity, and the cytotoxicity is strongly dependent on the bispecific structure (diabody, single-chain diabody, tandem single chain antibodies, etc) and arrangement of the specific antibody domains.260-262

However, the relationships between these factors are complicated, and we have no optimized approach for choosing the appropriate Fvs and domain arrangements to construct bispecific antibodies with sufficiently high cytotoxicity to be clinically effective. In fact, current scaffold evaluation is performed only through the arduous task of producing, and individually testing, each bispecific construct.

For this reason, the ability to generate a single, highly modifiable, construct that can easily swap targeting elements would be extremely useful in the evaluation of bispecific constructs. To this end we developed a highly modular bispecific CSAN format that contained a monospecific streptavidin (mSA) modality, mSA/αCD3 CSANs, that could be conjugated to virtually any biotinylated targeting element. We subsequently assessed whether an ‘in-format’ screening approach, designed to select format-compatible domain antibodies, could expedite lead discovery in our CSAN platform.

186

5.1.2 Monovalent Streptavidin as a Chemical Biology Tool

Streptavidin (SA) is a ~56-kDa homotetramer from the bacterium Streptomyces avidinii that binds up to four biotin molecules with Kd ~ 10−14 M.263 However, the four high-affinity binding sites of streptavidin bind multiple biotinylated ligands simultaneously and is highly prone to aggregation.264 Additionally, in the presence of ligands nonspecifically biotinylated (i.e. containing multiple biotin moieties per ligand) multiple streptavidin proteins can bind the same ligand and exacerbate the rate of aggregation.264

Taking care to ensure that streptavidin is present in excess does not always avoid the problem. Importantly, any multivalent targeting agent derived from wild type streptavidin is subject to this limitation of aggregation.

For these reasons, many groups have undertaken the task of generating a streptavidin fragment capable of monovalent biotin binding. One of the most sought-after concepts is the ability to use a structural monomer corresponding to a single streptavidin subunit (~14 kDa or approximately 25% of a tetramer) which is capable of binding one biotin molecule at a time. Thus, offering a simple solution for biotin recognition that does not result in target aggregation. However, structural and biochemical studies have also established the importance of intersubunit interaction for biotin binding.265 It was believed that the loss of such intersubunit contacts would inevitably result in a low affinity monomer. Fortunately, the discovery of rhizavidin and shwanavidin have shown that at least in principle high affinity biotin binding may be achieved using the residues from a single subunit.266

187

Both rhizavidin and shwanavidin are native dimers, whose binding sites are comprised of residues from a single subunit without explicit contribution from a neighboring subunit.266 Using this knowledge, the Park Lab engineered a monomer, mSA, that combined the rhizavidin and streptavidin sequences and had sequence similarity of

~60% with each parent, binding to biotin with a Kd of 3 nM.267 As a structural monomer, mSA may be fused to other proteins to generate a high affinity biotin binding tag.267 The

Park lab demonstrated this ability by forming a bifunctional molecule formed from both mSA and green fluorescent protein (GFP), which was then purified from Escherichia coli and used to fluorescently label biotinylated proteins on the cell surface. Importantly, the

Park lab demonstrated that the engineered monomer retained significant solubility and stability (a melting temperature of 60°C) exemplifying its use as a future biochemical tool.

Therefore, both cell biology and biochemical studies strongly support the novel and useful properties of mSA as a bifunctional handle.

5.1.3 Development of Monovalent Streptavidin (mSA) CSANs

Despite the immense therapeutic potential of both the Chemically Self-assembled

Nanorings (CSANs) and Prosthetic Antigen Receptors (PARs) that were discussed in chapters 3 and 4, the evaluation of novel targeting constructs remains a rate limiting step.

Due to the high specificity and simplicity of monovalent streptavidin, we chose to incorporate the technology into the CSAN platform for more rapid evaluation of targeting ligands. The successful utility of monovalent streptavidin containing CSANs would offer

188

the inherent advantage of producing only a single fusion protein based CSAN construct while still affording the ability to rapidly evaluate a wide panel of biotinylated targeting elements.

To date we have demonstrated that bispecific αCD3 containing PARs are capable of selectively eliminating target cancer cells. Building upon this platform we fused mSA to DHFR2 (mSA DHFR2) and generated bispecific CSANs formed from both αCD3

DHFR2 and mSA DHFR2 (mSA/αCD3 CSANs). These CSANs can be subsequently mixed with virtually any biotinylated targeting moiety at a 1:1.5 ratio in order to develop a rapid panel of targeted CSANs. Therefore, as a proof of concept, in the following chapter we designed and constructed mSA/αCD3 CSANs and evaluated their use with a panel of

EGFR targeting moieties to selectively target and induce cell killing against EGFR expressing U-87 MG cells (Figure 5.1).

189

Figure 5.1 Scheme for Bispecific mSA/αCD3 CSAN Immunotherapy

Bispecific mSA/αCD3 CSANs are constructed from αCD3 DHFR2, mSA DHFR2, and BisMTX to form multivalent nanorings. These Bifunctional CSANs can then be armed with virtually any biotinylated targeting element. Armed bifunctional CSANs then direct a selective interaction between a T-cell and antigen expressing cancer cell to induce target cell lysis.

5.2 RESULTS AND DISCUSSION

5.2.1 Preparation and Characterization of mSA/αCD3 bispecific CSANs

The development and preparation of αCD3 DHFR2 proteins have been previously described.75, 79 mSA DHFR2 proteins were formed by the genetic incorporation of mSA to the N-terminus of DHFR2 to generate a mSA DHFR2 fusion protein which were then expressed and purified as an inclusion body. Once prepared the purified fusion proteins were incubated with bisMTX dimerizer (1:1:2.2 equivalents) for 30 minutes to form mSA/αCD3 CSANs which were characterized by both Dynamic Light Scattering (DLS) and cryo transmission electron microscopy and found to be consistent with previous results 190

(Figure 5.2). As seen in figure Figure 5.2A-C both monospecific CSAN constructs, mSA

CSANs and αCD3 CSANs, and the bispecific mSA/αCD3 CSANs form rings consistent with past results. Furthermore, their size of 19.0 ± 0.1 nM, by Dynamic Light Scattering,

(Figure 5.2D) is congruent with past results and continues to show no sign of aggregation as indicated by the lack of species greater than 20 nM.

Figure 5.2 Verification of mSA/αCD3 CSAN Formation by Cryo Electron Microscopy and Dynamic Light Scattering

The formation of (A) mSA CSANs, (B) αCD3 CSANs, and (C) bispecific mSA/αCD3 CSANs was demonstrated by cryo-EM. (D) The size distribution of bispecific mSA/CD3 CSANs is consistent with past results as demonstrated by Dynamic Light Scattering (DLS).

191

5.2.2 Confirmation of mSA/αCD3 CSAN Biotin Binding

Following the confirmation of mSA/αCD3 CSAN formation the biotin binding potential was analyzed by size exclusion chromatography (SEC). As can be seen in Figure

5.3 both individually injected mSA DHFR2 and the smaller biotinylated lysozyme

(biotinylated lysozyme was used as a surrogate control for any biotinylated targeting element) elute at later time points due to their smaller individual size. However, when incubated together at a 1:1 ratio for 30 minutes at room temperature followed by infusion onto the SEC column they elute together at an earlier timepoint due to their larger cumulative size. Thus, demonstrating the ability of mSA DHFR2 to bind to the biotinylated lysozyme. Additionally, there is a complete loss of signal corresponding to the smaller biotinylated lysozyme indicating there is no remaining unbound biotin. The remaining mSA DHFR2 is likely explained by a slight excess of starting material. Furthermore, these bound constructs are still capable of forming octomeric CSANs when in the presence of bisMTX dimerizer resulting in the far larger species which elute in the void volume

(Figure 5.3).

192

Figure 5.3 Verification of mSA DHFR2 Biotin Binding by Size Exclusion Chromatography

Size Exclusion Chromatography (SEC) analysis of mSA DHFR2 (Blue) binding to biotinylated Lysozyme (Black) resulting in the larger dimeric species (Pink). These mSA DHFR2 monomers were still capable of forming octomeric CSANs when armed with biotinylated lysozyme (Brown).

5.2.3 mSA/αCD3 Bispecific CSAN Binding Evaluation

To evaluate the binding potential of mSA/αCD3 CSANs to target cells a panel of biotinylated EGFR targeting moieties were obtained and tested for binding against U-87

MG cells (EGFR+) (Figure 5.4). The analyzed EGFR targeting constructs included an

αEGFR binding peptide (KD = 111 µM), a low affinity αEGFR fibronecting (KD = 850 nM)

L H (αEGFR Fn3 ), a high affinity αEGFR fibronectin (αEGFR Fn3 ) (KD = 31 nM) and a

αEGFR monoclonal antibody (mAb) (KD = 11 nM). In brief, mSA/αCD3 CSANs were formed and mixed at a 1:1.5 ratio with the biotinylated EGFR targeting moieties for 30 193

minutes at room temperature. Following incubation these were incubated with U-87 MG cells followed by analysis of the FLAG tag present on mSA DHFR2. As we can see in

Figure 5.4 all αEGFR constructs successfully bound to U-87 MG cells with the greatest extent of binding seen in the high affinity mAb varient and the lowest seen in the low affinity peptide. As expected, the effective binding of each construct to the the U-87 MG cells correclates to the relative binding affinity of each biotinylated EGFR targeting moiety.

Figure 5.4 Bispecific mSA/αCD3 CSAN Target Cell Binding

Target U-87 MG (EGFR+) cells were labeled with bispecific mSA/αCD3 CSANs through the binding interaction of biotinylated (A) anti-EGFR peptide, (B) low affinity anti-EGFR Fibronectin, (C) high affinity anti-EGFR fibronectin and (D) anti-EGFR monoclonal antibody. Binding was evaluated by anti-FLAG-PE and all experiments were performed in triplicate, with a representative histogram shown for each scenario.

194

5.2.4 mSA/αCD3 Bispecific CSAN Cytotoxicity

Cytotoxicity studies were performed with unactivated T-cells treated with increasing mSA/αCD3 concentrations for 24 hours at an effector-to-target ratio of 10:1

(Figure 5.5). mSA/αCD3 CSANs were previously incubated with each respective EGFR targeting moiety at a 1:1.5 ratio for 30 minutes at room temperature prior to incubation with U-87 MG cells. Maximal cytotoxicity was observed for cells incubated with 50 nM of each biotinylated fibronectin and mAb construct, with significant cytotoxicity observed at a concentration of 10 nM. However, no significant cell killing was observed for the low affinity EGFR targeting peptide until a concentration of at least 200 nM which still resulted in a far lesser extent of cell killing than the higher affinity variants. This likely suggests that the affinity of the EGFR targeting peptide (111 µM) was likely too low to induce cell killing even when oligomerized into the higher valency CSAN construct. Interestingly while the highest level of target cell binding was observed with the αEGFR mAb construct a greater level of cell killing was observed with the two fibronectins, with the high affinity construct affording the best cell killing. This observation is likely due to the large size of the mAb that may inhibit an efficient synapse formation between the T-cell and target cancer cell. Furthermore, we can see that when two similar moieties (the two fibronectin constructs) were compared, the construct with the higher affinity exhibited the highest level of target cell lysis.

195

Figure 5.5 Target Cell Lysis by Bispecific mSA/αCD3 CSANs

Target U-87 MG cell lysis was evaluated at a set 10:1 E:T ratio with increasing concentrations of CSANs. CSANs were armed with nothing, αEGFR mAb, αEGFR Fn3H, αEGFR Fn3L or an αEGFR peptide. Data shown was obtained from one donor (n=3), but representative of three donors.

The ability of mSA/αCD3 CSANs to induce cell lysis was further confirmed by IL-

2 release following a 24 hour cell killing assay. As expected, all constructs that were capable of inducing cell lysis additionally released IL-2 into the supernatent (Figure 5.6).

Interestingly, while we were able to observe a difference in the level of target cell killing for each fibronectin and mAb evaluated, there was no observable difference in the level of

IL-2 release. However, we were able to observe a far greater extent of IL-2 release when compared to that of the EGFR targeted peptide. This likely indicates that the peptide did

196

not induce a significant level of T-cell actiation compared to the other constructs; while each higher affinity construct induced similar levels of T-cell activation, but did not produce similar levels of efficiency in target cell killing.

Figure 5.6 Induction of IL-2 Cytokine Release by Bispecific mSA/αCD3 CSANs

Target U-87 MG cell lysis was evaluated at a set 10:1 E:T ratio with increasing concentrations of CSANs. CSANs were armed with nothing, αEGFR mAb, αEGFR Fn3H, αEGFR Fn3L or an αEGFR peptide. Following the 24 hour incubation, the media was analyzed for IL-2 by ELISA. Data shown was obtained from one donor (n=3), but representative of three donors.

5.3 CONCLUSIONS

Our laboratory has successfully developed mSA/αCD3 PARs as a non-genetic method for modifying cell surfaces that can readily evaluate a wide panel of biotinylated

197

targeting elements. When incubated with EGFR targeting biotinylated moieties CSANs were capable of selectively binding to target EGFR expressing cancer cells. Additionally, the induced interaction between target cancer cells and T-cells successfully induced target cell lysis and activation of T-cells.

Ultimately, mSA/αCD3 CSANs provided a platform which allowed for the far more rapid evaluation of several EGFR targeting constructs within the same fusion protein construct. Collectively, our results demonstrate mSA containing PARs provides a rapid manner for testing virtually any biotinylated moiety within the CSAN platform. In fact, future studies (Chapter 6) will expand this universal biotin binding capability outside of bispecific construct evaluation and into the universal labeling of any cell type.

5.4 MATERIALS AND METHODS

5.4.1 Cells and Cell Culture

U-87 MG human glioblastoma cells were obtained from American Type Culture

Collection (ATCC, Rockville, MD). Human cancer lines were cultured in Dulbecco’s

Modified Eagle’s Medium (DMEM) supplemented with 10% FBS, 100 U/mL penicillin,

100 µg/mL streptomycin, and L-glutamine at 37°C in 5% CO2. Human PBMCs were isolated from buffy coats of healthy donor blood samples (obtained from Memorial Blood

Centers, St. Paul, MN) by Ficoll density gradient centrifugation. PBMCs were cultured in complete RPMI 1640 medium (Lonza) supplemented with 10% (v/v) fetal bovine serum,

198

L-glutamine (final concentration of 2mM), Penicillin (100 units/mL), and Streptomycin

(100 µg/mL) in a humidified incubator with 5% CO2 at 37 ˚C.

5.4.2 Protein Expression and Purification

The mSA-DHFR2 fusion proteins produced in E. coli and purified from the insoluble fraction of the cell lysates according to our previously reported refolding methods in Chapter 3. Purified proteins were analyzed by SEC on a Superdex 200 Increase 10/300 gel filtration column (GE Healthcare Life Sciences, Cat: 28990944) in PBS running buffer.

Fusion protein retention times were compared to those of commercial molecular weight standards (Sigma Aldrich, Cat: MWGF1000-1KT). The EGFR targeting Fibronectins were obtained from the Hackle lab where they were nonspecifically biotinylated by biotin-NHS ester.

5.4.3 CSAN Formation and Characterization

CSANs were formed by adding a 1.1-3.0 fold molar excess of the desired chemical dimerizer – bisMTX– to a solution of targeted DHFR2 fusion protein monomers in PBS.

Consistent with our previous studies, CSAN oligomerization occurs within minutes of adding the dimerizer. Cryo-EM samples were prepared using a Vitrobot Mark IV (FEI).

Briefly, 3 µL of CSANs in PBS was applied to a lacey formvar/carbon grid (Ted Pella,

Inc.; Cat: 01883) in a humidified chamber, blotted, and plunged into liquid ethane for vitrification. Grids were imaged on a Tecnai Spirit G2 BioTWIN (FEI) equipped with an

199

Eagle 2k CCD camera (FEI) under a high tension of 120 kV. Images were analyzed in

ImageJ and, for the size distribution analysis, only nanoparticles with ≥70% circularity were included. For DLS, 60 µL of CSANs in PBS was loaded into a cuvette and analyzed on a Punk DLS unit (Unchained Labs). Hydrodynamic diameter values represent the mean

± standard deviation of at least three measurements.

5.4.4 Binding Assays

Flow cytometry was used to determine whether the mSA CSAN constructs bound to EGFR expressing U-87 MG cells. The cell surface was washed three times with PBS as above and resuspended in 50 µL of anti-FLAG-PE (Thermo Fisher Scientific, Cat: S32354;

10 µg/mL in PBS). After incubating at 4 ºC for 1 h, the cells were pelleted (500g, 5 min, 4

ºC) and washed thrice with 1 mL cold PBS before the fluorescence was analyzed on an

LSR II flow cytometer.

5.4.5 Cytotoxicity Assays

Measurement of cell lysis was evaluated by measuring LDH (lactate dehydrogenase) release from cells with the non-radioactive cytotoxicity assay (CytoTox 96® Non-

Radioactive Cytotoxicity Assay, Promega). The day previous to the experiment 5x103 target U-87 MG cells were seeded into a 96-well plate in 200 μL of RPMI-1640 media per well. The following day the appropriate number of resting PBMCs (according the requested effector (E) to target (T) cell (E:T) ratio as indicated in the respective experiment) were

200

counted and incubated with 0.01-1 μM of the mSA/αCD3 bispecific CSANs (previously incubated with a 1:1.5 ratio of biotinylated targeting elements for 30 minutes at room temperature) for one hour at 37°C with 5% C02. Following the initial incubation, PBMCs were resuspended in RPMI before addition to 96-well plate containing target U-87 MG cells and incubated for 24 hours under standard conditions. Lysis buffer (provided in assay kit) was added to control wells with only U-87 MG cells to estimate the maximum LDH release. The absorbance at 490 nm was measured and recorded using a Synergy H1 Multi-

Mode Reader (Biotek). Data was corrected for media absorbance, and values were determined per the following equation: ((LDH release sample – SReffector –

SRtarget)(MRtarget – SRtarget)) x 100. SR: spontaneous release; MR: maximum release.

5.4.6 Cytokine Analysis

IL-2 measurements in the cytotoxicity assay supernatants were analyzed using ELISA per the conditions provided by the IL-2 ELISA kit (Invitrogen). In brief, following the incubation period the supernatant was removed and 10-fold diluted into ELISA buffer

(provided in the kit) prior to placing 50 µL into the respective well of the included ELISA

96-well plate. IL-2 production of experimental wells was determined through a standard curve generated from known control sample concentrations.

201

CHAPTER 6: FUTURE DIRECTIONS – A UNIVERSAL NON-GENETIC MEMBRANE ENGINEERING APPROACH FOR DIRECTING CELL-CELL INTERACTIONS

202

6.1 INTRODUCTION

Portions of the information from the following chapter are currently under review for publication, and are being reproduced in part with permission from: (1) Csizmar, C. M.;

Petersburg, J.; Hendricks, A.; Stern, L. A.; Hackel, B. A.; Wagner, C. R. Reversible Cell

Membrane Engineering with Chemically Self-Assembled Nanorings. (2) Csizmar, C. M.;

Petersburg, J.; Wagner, C. Non-Genetic Membrane Engineering for Directing Specific

Intercellular Interactions. The publications were principally written by the current author,

Jacob Petersburg, Clifford Csizmar and Carston Wagner with contributions from the coauthors.

6.1.1 Motivation for a Universal Approach to Cell Membrane Engineering

Cell therapy has rapidly emerged as an invaluable tool in translational medicine and has led to significant advances in several diverse fields, including tissue engineering, regenerative medicine, and immunotherapy. Stem cells – in particular mesenchymal stem cells (MSCs) and, more recently, induced pluripotent stem cells (iPSCs) – have emerged as both a cornerstone of regenerative medicine and a versatile therapy for immune disorders. Meanwhile, T cells have been at the forefront of cancer immunotherapy for over a decade. However, the efficacy of these cellular therapies is ultimately contingent upon the ability to appropriately control the fate and function of the therapeutic cells.

Specifically, the cells must be successfully directed to engage in productive cell-cell interactions. For example, systemic infusion of MSCs following a myocardial infarction

203

results in only a 1% accumulation of cells in the ischemic myocardium.268 In contrast,

MSCs induced to upregulate chemotactic receptors prior to infusion exhibit more than a 2- fold increase in ischemic tissue homing.269-272 For this reason, cellular engineering has become a crucial area of interest in cell therapy research, frequently applied to four fields

– tissue engineering, cell-based immunotherapy, regenerative medicine, and targeted cell adhesion (Figure 6.1).

Figure 6.1 Applications of Engineered Cell-Cell Interactions.

Non-genetically engineered cell-cell interactions are broadly applicable to a variety of fields. (A) The linking of multiple tissue types in vitro is useful for tissue engineering. (B) Cytotoxic T cells can be directed to – and subsequently kill – antigen expressing cells for immunotherapy. (C) Therapeutic cells can be modified to more efficiently tether, roll, and extravasate through the vascular, improving their delivery to target tissues. (D) Regenerative stem and progenitor cells can be functionalized with targeting ligands that enhance their homing to sites of injury.

Initial efforts in cellular engineering involved either preconditioning cells ex vivo via exposure to various stimuli (such as pharmacological agents, soluble cytokines, or

204

stimulatory ligands) or the simultaneous administration of supportive adjuvant therapies.

The goals of these approaches were to enhance the in vivo function of the infused cells, generate longer cell lifetimes, and promote self-renewal mechanisms to combat the inherent variability of cell biodistribution. While these strategies increased overall in vivo cell retention, they did little to directly influence the desired cell-cell interactions.

Since then, genetic engineering has emerged as the most utilized and clinically efficacious cellular engineering approach. As previously discussed, genetically-engineered chimeric antigen receptor (CAR) T cells were recently approved by the United States Food and Drug Administration (FDA) for relapsed/refractory pediatric B cell precursor acute lymphoblastic leukemia and diffuse large B cell lymphoma.56, 57 In this approach, exogenous genetic material is incorporated into the desired cell’s genome where it encodes an artificial cell surface receptor that targets an antigen of interest.58, 59 While genetic engineering is a robust strategy, the drawbacks covered previously in this thesis are not restricted solely to immunotherapy applications. For instance, not all cell types are amenable to such genetic alteration without deleterious effects – stem cells in particular as the genetic manipulation typically causes a decrease in pluripotency.273-275 Furthermore, the process is time consuming and produces results with variable and often unpredictable efficiency. Finally, the permanence and irreversibility of the genetic modification has resulted in significant adverse events in patients and raised long-term safety concerns for clinical applications, including B cell aplasia, solid organ damage, and neurotoxicity.151

Due to these complications it is imperative to continue pursuing alternative routes toward

205

cell surface modifications that are straight forward, result in uniform and functional cell populations, and can be easily amended to include a wide variety of functional elements and targeting moieties.

While our lab, as well as others, have shown that utilizing bispecific constructs (i.e.

PARs and BiTEs discussed in previous chapters) can sidestep these limitations they are still limited to applications where a known cell-surface receptor is accessible. This is particularly important to current stem cell and regenerative medicine applications where a limited number of viable surface markers are available and you want to neither drive the differentiation of the cell, nor reduce multipotency in any way.276, 277 In an attempt to circumvent these limitations and expand the scope of cell-based therapies, effort has been placed in developing non-genetic and universal strategies to engineer cell surfaces with targeting elements capable of directing specific cell-cell interactions. Typically, these approaches are more transient (or outright reversible) and applicable to numerous cell types, including stem cells. Furthermore, non-genetic approaches have been developed around lipid-, glycan-, and protein-based modifications, which is in contrast to bispecific and genetic engineering methodologies focusing primarily on protein expression.

An important aspect for membrane engineering approaches is the degree to which they can be generalized to different cell types, increasingly so for tissue engineering applications where a key goal is to drive interactions between the numerous cell lineages that comprise a functional tissue or organ. Fortunately, many of the non-genetic approaches have each been applied to a wide array of cell types – including lymphocytes,79 MSCs,278

206

cardiomyocytes,279 and vascular endothelial cells280 – suggesting that non-genetic alterations relying solely upon membrane modification may be uniquely flexible and thus find use in a variety of applications.

In order for a membrane modification to be universal it must also be innocuous.

This is especially important for stem cells, as the modification should neither drive the differentiation of the cell nor reduce multipotency in any way. While genetically encoded modifications have met little success in the arena of stem cells, non-genetic approaches – including hydrophobic insertion,281 chemical modification,282 liposome fusion,283 metabolic engineering,284 and enzymatic remodeling285 – have been successfully applied to stem cell populations without altering their multi-lineage differentiation capabilities.

This suggests that these non-genetic approaches, which don’t typically rely upon the engagement of a physiologic receptor on the cell membrane, may be uniquely suited to directed stem cell therapies and a more universal approach for inducing cell-cell interactions.

6.1.2 Membrane Engineering by Hydrophobic Insertion

Integral cell surface proteins are anchored into the membrane through hydrophobic transmembrane domains that interact with the hydrophobic interior of the lipid bilayer.286

The hydrophobic effect dictates both the incorporation and orientation of integrated proteins and locks them on the cell surface, barring cell membrane internalization.287 These same principles have been utilized for cellular engineering, where the desired ligand or

207

chemical moiety is conjugated to a hydrophobic anchor and then incubated with the to-be- labeled cell population. Driven by enthalpy, the hydrophobic anchor will spontaneously insert into the lipid bilayer and effectively tether the attached species to the membrane.288

Such membrane insertion has been accomplished with a variety of hydrophobic tags, including alkyl chains,288 lipid moieties,278 and glycophosphatidylinositol (GPI) anchors.289 Multiple methods for attaching these tags to the desired cargo have also been developed. Perhaps the most common approach is the chemical ligation of the tag using such means as peptide couplings with activated esters,281 sulfhydryl-based Michael additions,271 or click ligations between azide groups and various alkynes.290 In contrast, others have devised methods to produce hydrophobically-tagged ligands recombinantly, thereby omitting the additional conjugation step.289, 291

The relative ease with which cell surfaces can be “painted” with these hydrophobically-tagged species has made it a popular approach for the attachment of a wide variety of cargo.278, 281 Targeting elements – including aptamers,292, 293 antibody- derived single chain variable fragments (scFvs),291 and peptides278, 294 – are commonly installed on the cell membrane in this fashion. By first anchoring proteins A and G, several laboratories have functionalized cells with full antibodies281, 295 and Fc-tagged fusion proteins.296 Oligonucleotides have been installed as well, enabling the clustering of cells functionalized with complimentary sequences.297, 298 Finally, other groups have attached larger cell-targeting scaffolds, including nanoparticles79, 288 and polymers.299 Notably, these methods were further developed into synthetic targeting systems used to direct

208

artificial cell-cell interactions in vitro and have been demonstrated in numerous cell types, including stem cells.

6.1.3 CSAN Mediated Cell Surface Engineering

Expanding upon this body of prior work, our group sought to design a cell membrane engineering methodology that would both be broadly applicable to a variety of cell types and possess a reversal mechanism that could more feasibly be used in vivo. Our method utilized the same chemically self-assembled nanoring (CSAN) scaffold previously discussed in this thesis (Figure 6.2A). Briefly, CSANs were still formed when bivalent dihydrofolate reductase (DHFR2) fusion proteins are spontaneously oligomerized by a chemical dimerizer, bis-methotrexate (bisMTX). We further functionalized these CSANs by fusing binding domains – in this case to monovalent streptavidin (mSA), as previously discussed in chapter 5, and any other targeting element – to the DHFR2 subunits. Using stochastic combinations of the fusion proteins and the bisMTX, we can generate multivalent, heterobifunctional CSANs capable of targeting a desired cell surface marker and any biotinylated moiety. Importantly, the CSAN scaffold still disassembled through exposure to the FDA-approved antibiotic trimethoprim, providing a pharmacologic mechanism for removing the targeting ligands from the cell surface.

Consistent with our aim to develop a surface engineering approach that would be applicable to multiple cell types, we devised a system based upon the spontaneous hydrophobic insertion of commercially-available phospholipid conjugates (Figure 6.2B).

209

Using 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[biotinyl(polyethylene glycol)] (DSPE-PEG2000-Biotin), cell surfaces can be decorated with biotin moieties. We then attach our targeted CSANs to the lipid-modified cells via a non-covalent biotin/mSA interaction, thereby functionalizing the cell with CSANs. Finally, the targeting ligands can be removed from the cell surface via trimethoprim-induced dissociation of the CSAN.

Using this system, we have successfully directed cell-cell interactions between

CSAN-labeled cells and EpCAM-expressing target cells in vitro. Furthermore, we demonstrate that these induced intercellular interactions can be rapidly reversed with trimethoprim. To our knowledge, this is the first example of a non-genetic cell surface targeting modification capable of driving cellular interactions than can be reversed by a method suitable for broad in vivo use.

210

Figure 6.2 Cell Surface Engineering with Chemically Self-Assembled Nanorings

(CSANs).

Schematic representation of a non-genetic, universal, cell membrane labeling CSAN technology. (A) Formation of bispecific CSANs incorporating monovalent streptavidin (mSA) and a targeting domain with engineered specificity for epithelial cell adhesion molecule (EpCAM). Cell Membranes decorated with (B) biotin phospholipid moieties are functionalized with αEpCAM CSANs via a non-covalent biotin/mSA interaction, respectively, and directed towards EpCAM expressing cells.

211

6.2 RESULTS AND DISCUSSION

6.2.1 Hydrophobic Insertion of Functionalized Phospholipids

For our studies, we elected to use the commercially-available phospholipid conjugate DSPE-PEG2000-biotin. This conjugate was chosen because we hypothesized that the hydrophobic lipid would enable membrane insertion while the long, flexible PEG linker would improve the accessibility of the biotin groups. We also envisioned two approaches to labeling the cells with the phospholipids: (1) resuspending the cells ex vitro in PBS supplemented with the lipids; and (2) actively culturing the cells in vitro in lipid- supplemented media.

To determine whether the phospholipids had inserted into the membrane and that the biotin groups were accessible, we probed for the presence of these species on the cell surface via flow cytometry using streptavidin-conjugated fluorophores. Both MCF-7 and

Raji cells were modified with increasing concentrations of DSPE-PEG2000-biotin through both the buffer and culture methods. In all instances, the biotin moieties were readily detected on the cell surface after lipid modification, indicating both successful membrane insertion and availability of the functional groups for subsequent labeling (Figure 6.3).

Furthermore, the extent of the modification could be modulated in a largely dose-dependent manner simply by varying the concentration of the phospholipid conjugate that was used.

212

Figure 6.3 Phospholipid Insertion Enables Tunable Cell Surface Modification.

1 µM to 100 µM of DSPE-PEG2000-biotin were labelled onto MCF-7 and Raji cells and probed with by streptavidin-conjugated fluorophores. Samples were analyzed by fluorescence activated cell sorting (FACS)

Collectively, this data shows that a variety of cell types can be effectively modified with phospholipid conjugates via hydrophobic insertion into the cell membrane without effecting cell viability. These results are in congruence to those obtained by others performing similar hydrophobic insertions and further validates this approach as a universal method for cell surface modification.278, 288

6.2.2 Installing CSANs on Phospholipid-Modified Cells

After confirming the membrane insertion of the phospholipid conjugates, we sought to use the associated functional groups as handles for the attachment of our nanoring platform. Cells were first modified with DSPE-PEG2000-biotin ex vitro. They were subsequently incubated with mSA-CSANs at 4 ºC for 1 h. As mSA-DHFR2 monomers contain a FLAG-tag we were able to confirm their binding to the lipid modified cells.

213

While the insertion of hydrophobic anchors into the lipid bilayer is an enthalpically- favored process, it is typically a transient modification with a half-life on the order of hours for cells in active culture.291 Additionally, because the lipids can insert into essentially any cell membrane, it was conceivable that a lipid-anchored species could dissociate from the membrane into which it was principally installed and subsequently label a neighboring cell, essentially “hopping” from the intended cell to a bystander cell. However, we hypothesized that by engaging multiple lipid anchors per nanoring, the multivalency of the CSAN would portend an improved surface stability relative to single lipid species and keep the CSANs localized to the principally modified cell.

To test both the surface stability of lipid-anchored CSANs and their potential to transfer amongst cells, two populations of Raji cells were differentially labeled. The first population was labeled only with Cell Trace Violet (CTV) dye. The second population was modified with DSPE-PEG2000-biotin in vitro and then labeled with “reduced valency” mSA

CSANs. To more accurately recapitulate the valency of mSA domains that would be present in a bifunctional mSA/targeted CSAN, the CSANs used in this study were co- assembled with an equal ratio of mSA-DHFR2 monomers and non-targeted DHFR2 monomers. In this manner, the reduced valency CSANs used in this experiment serve as a surrogate for any bispecific mSA/targeted CSAN, including the mSA/Fn3 CSANs previously introduced.

214

Figure 6.4 Membrane Stability and Controlled Dissociation of Phospholipid- Anchored CSANs.

(A) Biotin-modified Raji cells were labeled with reduced-avidity mSA CSANs and analyzed by flow cytometry every 24 h, staining for either the CSANs (black) or, in the case of the lipid-only control (grey), for biotin. For this analysis, the MFI values are corrected for the number of cell divisions (as determined by CellTrace Violet labeling) and scaled relative to the MFI values obtained at t=0 h. (B) Biotin-modified Raji cells were labeled with mSA/Fn3 CSANs and then resuspended in culture media with or without 2 µM trimethoprim for 1-2 h at 37 ºC. Cells were then analyzed by flow cytometry to detect the surface-bound CSANs. (C) Biotin-modified Raji cells labeled with reduced-avidity mSA CSANs were pooled with CTV-labeled Raji cells at a 7:3 ratio and co-cultured for 72 h. Cells were analyzed by flow cytometry every 24 h to ascertain whether the lipid-anchored CSANs had migrated onto the membranes of the CTV+ Raji cells. (D) Raji cells modified with only DSPE-PEG2000-biotin (no CSANs) were pooled with CTV-labeled Raji cells at a 7:3 ratio and co-cultured for 72 h. Cells were analyzed by flow cytometry every 24 h to ascertain whether the phospholipid conjugates had migrated onto the membranes of the CTV+ Raji cells. For all panels, data is presented as the mean ± standard deviation of at least three trials. 215

The CTV-labeled and CSAN-labeled Raji cell populations were combined and co- cultured for 72 h; every 24 h, the culture media was refreshed (to partially simulate the effect of clearance) and a sample of the pooled population was analyzed for CTV and

CSAN presence by flow cytometry. For comparison, the same analysis was performed for a mixed population of CTV-labeled Raji cells and Raji cells only modified with the DSPE-

PEG2000-biotin (no CSANs). As shown in Figure 6.4A, the lipid-anchored CSANs remained stably bound to the cell surface for ≥72 h. In contrast, significant loss of the monomeric phospholipid conjugates was observed over this same time frame (p<0.0025).

This indicates that, through the engagement of multiple phospholipid conjugates, the multivalent CSANs possesses an increased avidity for the cell surface and thus an enhanced surface stability relative to species that are anchored by only a single lipid.

As previously discussed, genetically encoded artificial receptors (such as CARs) are permanently expressed on the cell surface. While this is a powerful feature, it also limits the use of genetically engineered cells and can lead to irreversible side effects when used clinically. For example, CAR T cells targeting CD19 eradicate both leukemic and healthy

CD19+ cells, leading to B cell aplasia and crippling the adaptive immune system of patients treated with this approach.66, 151 Such “on target, off tumor” toxicities have so far restricted the use of the CAR T cell platform to hematologic malignancies where the damaged healthy tissue can be replaced by the infusion of analogous blood products (e.g., intravenous immunoglobulins). Thus, it is widely hypothesized that the ability to regulate and temporally control the expression of the artificial receptor on the cell surface would

216

both improve the safety profile and enable the translation of membrane engineered cells to other applications, including solid tumors.

Accordingly, we sought to utilize the trimethoprim-induced disassembly of the

CSAN scaffold as a pharmacologic mechanism for removing the targeting ligands from the surface of a CSAN-functionalized cell. To demonstrate this, Raji cells were sequentially modified with DSPE-PEG2000-biotin in vitro and labeled with mSA-CSANs. The CSAN- functionalized Raji cells were then resuspended in culture media supplemented with a clinically-relevant concentration of trimethoprim (2 µM) and incubated at 37 ºC for up to

2 h. An aliquot of cells was analyzed by flow cytometry with fluorescently-labeled anti- myc antibodies at, 0, 1, and 2 h. As shown in Figure 6.4B, the targeting ligands were dissociated from the cell surface in a time-dependent manner, with 95% of the EpCAM- targeted Fn3 domains removed within 2 h.

Furthermore, Figure 6.4C demonstrates that there is minimal migration of a lipid- anchored CSAN from one cell to another. Specifically, the percentage of CTV+/CSAN+

Raji cells in the population increases only marginally over the course of three days, from

0.9 ± 0.3% of the population on day zero to 2.9 ± 0.9% on day three; this correlates to a decrease in the number of CTV+/CSAN- Raji cells from 27.1 ± 0.9% to 24.5 ± 0.4% over the same time period. A similar effect is observed for the monomeric DSPE-PEG2000-biotin moieties (Figure 6.4D), with an increase in the number of CTV+/lipid+ cells from 0.6 ±

0.6% to 4.1 ± 0.8% and a corresponding decrease in the number of CTV+/lipid- cells from

26.9 ± 0.5% to 23.3 ± 0.5% over three days. This data suggests that, while the phospholipid

217

conjugates and their tethered cargo can dissociate from the cell surface, very few of the dissociated species re-insert themselves into the membranes of neighboring cells. This is likely due to the low concentration of the dissociated species in the media and the fact that the media was refreshed frequently (every 24 h), reducing the accumulation of free phospholipid conjugates.

Importantly, for future in vivo applications, lipid-anchored CSANs were also found to be relatively stable in mouse plasma (Figure 6.5), with only a 66% decrease in percent fraction bound to the cell surface compared to the media control. This loss is likely due to the combination of high levels of serum albumin, present in the plasma, binding to the phospholipids and serum proteases non-specifically cleaving the protein construct.

Figure 6.5 Membrane Stability of CSANs in Mouse Plasma.

mSA CSAN labeled Raji cells were incubated in either media or mouse plasma for 24 hours prior to analysis by FACS. Anti-FLAG was used to probe for the FLAG-tag on mSA-DHFR2 protein. Fraction bound are presented as mean ± standard error of three trials.

218

6.3 CONCLUSIONS

In conclusion, the CSAN platform offers a modular approach for reversibly functionalizing cell membranes with targeting ligands. Through the spontaneous membrane insertion of phospholipids conjugated to biotin, CSANs can be installed on essentially any cell surface. In contrast to genetic engineering approaches, which require both manipulation of the target cell’s genome and extensive culturing to expand the modified cells, the method described here is rapid, scalable to large cell numbers, and broadly applicable to diverse cell types. Additionally, these interactions were rapidly reversed through exposure to trimethoprim.

That CSAN-based surface modifications are pharmacologically removed trimethoprim makes them distinct from other reversal approaches that have been developed. While photoirradiation, enzymatic degradation, and changes in redox potential or temperature have all been demonstrated, none of the mechanisms are applicable in an in vivo setting, especially when the modified cells are broadly distributed throughout an organism (as would be the case for immunotherapy applications). Because trimethoprim is an FDA-approved antibiotic that is currently used systemically, it is conceivable that

CSAN-directed cell-cell interactions could theoretically be readily reversed in vivo via trimethoprim administration, providing a safe mechanism for deactivating the targeted cells in the case of adverse events. While demonstrating this in vivo deactivation is outside the scope of the present study, it is a feature our group will continue to develop and explore.

219

Ultimately, this work provides a broadly-applicable approach to cell surface engineering that could be used to expand the formation of targeted, reversible cell-cell interactions across diverse fields, including immunotherapy, tissue engineering, and regenerative medicine.

6.4 MATERIALS AND METHODS

6.4.1 Cells and Cell Culture

The MCF7, U-87 MG, and Raji cell lines were previously purchased from the

American Type Culture Collection (ATCC). MCF7 and U-87 MG cells were grown at 37

ºC in a humidified atmosphere with 5% CO2 in Dulbecco’s Modified Eagle’s Medium

(DMEM) with 4.5 g/L glucose, L-glutamine, and supplemented with 10% fetal bovine serum (FBS), 100 U/mL penicillin, and 100 µg/mL streptomycin. Raji cells were grown at

37 ºC in a humidified atmosphere with 5% CO2 in Roswell Park Memorial Institute (RPMI) media with L-glutamine and supplemented with 10% FBS, 100 U/mL penicillin, and 100

µg/mL streptomycin. When needed for passaging or harvesting, adherent cell lines MCF7 and U-87 MG were detached via trypsin. Cell count and viability was determined via trypan blue staining/exclusion using an automated cell counter.

6.4.2 Protein Expression and Purification

The mSA-DHFR2 fusion proteins produced in E. coli and purified from the insoluble fraction of the cell lysates according to our previously reported refolding methods

220

in Chapter 5. Purified proteins were analyzed by SEC on a Superdex 200 Increase 10/300 gel filtration column (GE Healthcare Life Sciences, Cat: 28990944) in PBS running buffer.

Fusion protein retention times were compared to those of commercial molecular weight standards (Sigma Aldrich, Cat: MWGF1000-1KT).

6.4.3 CSAN Formation and Characterization

As previously described, CSANs were formed by adding a 1.1-3.0 fold molar excess of bisMTX dimerizer to a solution of targeted DHFR2 fusion protein monomers in

PBS. Consistent with our previous studies, CSAN oligomerization occurs within minutes of adding the dimerizer.

6.4.4 Hydrophobic Insertion of Phospholipid Conjugates

DSPE-PEG2000-biotin was purchased from Avanti Polar Lipids (Cat: 880229P, respectively) and resuspended in phosphate buffered saline (PBS) at pH 7.4. Cells were modified with DSPE-PEG2000-biotin via one of two methods: (1) through resuspension in phospholipid-containing PBS (ex vitro), or (2) through active culture in media supplemented with the phospholipid (in vitro).

For the ex vitro (buffer) method, cells were harvested from culture, pelleted at 300g for 5 min, and washed with 1 mL PBS. Cells were then resuspended in PBS containing the desired concentration of phospholipid (0-100 µM) at a ratio of 2.5x106 cells/mL. The cell suspension was then placed on a rotating platform and incubated at room temperature for

221

1 h. Cells were then pelleted at 300g for 5 min, and washed thrice with 1 mL cold PBS to remove uninserted DSPE-PEG2000-biotin. Cells were then used directly for subsequent applications.

For the in vitro (culture) method, cells were grown in culture media (DMEM or RPMI, as above) supplemented with the desired concentration (0-100 µM) of DSPE-PEG2000-biotin for 24-48 h. Cells were then harvested from culture (adherent cells were detached with trypsin), pelleted at 300g for 5 min, and washed thrice with 1 mL cold PBS to remove uninserted DSPE-PEG2000-biotin. Cells were then used directly for subsequent applications.

Following each modification, flow cytometry was used to determine whether the

DSPE-PEG2000-biotin had inserted into the cell membrane. To probe for the biotin moieties on the cell surface, the phospholipid-modified cells were washed as above and resuspended in 50 µL of streptavidin Alexa Fluor 488 conjugate (Thermo Fisher Scientific, Cat: S32354;

10 µg/mL in PBS). After incubating at 4 ºC for 1 h, the cells were pelleted (500g, 5 min, 4

ºC) and washed thrice with 1 mL cold PBS before the fluorescence was analyzed on an

LSR II flow cytometer. For data analysis, the maximum MFI obtained within each experimental series is normalized to 1.0, with the other samples in that series scaled relative to this value.

222

6.4.5 Functionalizing Phospholipid-Modified Cells with CSANs

Cells were cultured, harvested, and modified with 10 µM of DSPE-PEG2000-biotin ex vitro, as described above. Generally, 0.5x106 cells were then labeled with 500 µL of 100 nM CSANs of the desired functionality in PBS at 4ºC for 1 h. After the primary incubation, cells were washed once with 1 mL cold PBS to remove unbound CSANs. The cells were then resuspended in 50 µL of anti-FLAG PE conjugate (Biolegend, Cat: 637309; 1 µg/mL in PBS) to probe for the FLAG epitope tag present on the mSA-DHFR2 subunits. After incubating at 4 ºC for 1 h, the cells were pelleted (500g, 5 min, 4 ºC) and washed thrice with 1 mL cold PBS before the fluorescence was analyzed on an LSR II flow cytometer.

6.4.6 Stability Studies

The in vitro longevity of the phospholipid-anchored CSANs on the cell surface was assessed by flow cytometry. Briefly, Raji cells were modified with 10 µM DSPE-PEG2000- biotin in vitro, labeled with 100 nM “reduced-avidity” mSA CSANs (CSANs formed with a 1:1 ratio of mSA-DHFR2 subunits and non-targeted DHFR2 subunits), and then returned to culture for 0-72 h. At 24 h intervals, an aliquot of 0.5x106 cells was taken, labeled with an anti-FLAG PE conjugate (1 µg/mL in PBS) to detect cell surface CSANs, and analyzed on an LSR II flow cytometer, as described above. To compare the surface longevity of the

CSANs to that of the individual DSPE-PEG2000-biotin moieties themselves, a separate population of Raji cells was modified with only 10 µM DSPE-PEG2000-biotin in vitro (no

CSANs) and returned to culture for 0-72 h. An aliquot of these cells was taken, labeled

223

with streptavidin Alexa Fluor 488 conjugate (10 µg/mL in PBS) to detect cell surface biotin moieties, and analyzed on an LSR II flow cytometer in parallel with the CSAN-labeled samples. To determine the number of cell divisions over the course of the experiment, a third aliquot of Raji cells was labeled with CellTrace Violet (CTV; Thermo Fisher

Scientific, Cat: C34571) according to the manufacturer’s instructions and cultured/analyzed in parallel with the CSAN and phospholipid samples. For data analysis, the MFI of the samples at t=0 was normalized to 1.0, representing maximum labeling, and the MFI on subsequent days was scaled relative to this value. Because cell division reduces the MFI value through dilution of the CSANs/phospholipids across daughter cell membranes and not due to loss of the constructs, the MFI values of subsequent analyses were corrected for the number of cell divisions, as determined by the CTV labeling.

The stability of phospholipid-anchored CSANs in plasma was directly compared to

6 that of media. Raji cells (0.5x10 ) were modified with 10 µM DSPE-PEG2000-biotin in vitro and labeled with 100 nM “reduced-avidity” mSA CSANs, as above. The cells were then divided into two aliquots of 0.5x106 cells each; one aliquot was resuspended in 200 µL

RPMI while the other was resuspended in 200 µL mouse plasma. The cells were incubated at 37 ºC, 5% CO2 for 24 h, labeled with anti-FLAG PE conjugate (1 µg/mL in PBS) to detect cell surface CSANs, and analyzed on an LSR II flow cytometer, as described above.

To ascertain whether the phospholipid-anchored CSANs could “migrate” from the principally modified cell to an unmodified neighbor cell, two populations of Raji cells were prepared. The first population was labeled only with CTV. The second population was

224

modified with 10 µM DSPE-PEG2000-biotin in vitro and then labeled with “reduced valency” mSA CSANs (see above). The CTV-labeled and CSAN-labeled Raji cell populations were combined at a 3:7 ratio and co-cultured in RPMI for 72 h; every 24 h, the culture media was refreshed (to partially simulate the effect of clearance) and a sample of the pooled population was analyzed for CTV and CSAN presence by flow cytometry.

CSANs were detected by labeling the cells with anti-FLAG PE conjugate (1 µg/mL in

PBS), as above. At each time point, the percentage of CTV+/CSAN- (original CTV- modified population), CTV+/CSAN+ (CTV cells that had acquired a “migrating” CSAN),

CTV-/CSAN+ (original CSAN-functionalized population), and CTV-/CSAN- (cell that has lost their CSAN functionalization) cells was quantified by flow cytometry. For comparison, the same analysis was performed for a mixed population of CTV-labeled Raji cells and

Raji cells modified with only the 10 µM DSPE-PEG2000-biotin (no CSANs).

6.4.7 Trimethoprim-Induced CSAN Dissociation

6 Raji cells (0.5x10 ) were modified with 10 µM DSPE-PEG2000-biotin ex vitro and then labeled with 100 nM mSA/Fn3 CSANs, as above. The CSAN-labeled cells were then divided into two equal aliquots, one of which was resuspended in 200 µL of RPMI and the other in 200 µL of RPMI supplemented with 2 µM trimethoprim (Fisher Scientific, Cat:

AAJ66646MD). Cells were then incubated at 37 ºC, 5% CO2 for 1-2 h, labeled with anti-

FLAG PE conjugate (1 µg/mL in PBS) to detect cell surface CSANs, and analyzed on an

LSR II flow cytometer, as described above. For data analysis, the MFI of the samples in

225

plain RPMI was normalized to 1.0, representing maximum labeling, and the MFI of the samples in RPMI with was scaled relative to this value.

6.4.8 Statistical Considerations

Unless otherwise stated, experiments were performed in triplicate and data is presented as the mean ± standard deviation of three independent trials. Differences between means are compared using a two-tailed Student’s t-test, and a p-value <0.05 is denoted in graphics with an (*), p<0.01 is denoted with (**), and p<0.001 is denoted with (***).

226

BIBLIOGRAPHY

1. Vogelstein, B.; Papadopoulos, N.; Velculescu, V. E.; Zhou, S.; Diaz, L. A.; Kinzler, K. W., Cancer genome landscapes. Science 2013, 339 (6127), 1546-58. 2. Croce, C. M., Oncogenes and cancer. N Engl J Med 2008, 358 (5), 502-11. 3. Lawrence, M. S.; Stojanov, P.; Polak, P.; Kryukov, G. V.; Cibulskis, K.; Sivachenko, A.; Carter, S. L.; Stewart, C.; Mermel, C. H.; Roberts, S. A.; Kiezun, A.; Hammerman, P. S.; McKenna, A.; Drier, Y.; Zou, L.; Ramos, A. H.; Pugh, T. J.; Stransky, N.; Helman, E.; Kim, J.; Sougnez, C.; Ambrogio, L.; Nickerson, E.; Shefler, E.; Cortés, M. L.; Auclair, D.; Saksena, G.; Voet, D.; Noble, M.; DiCara, D.; Lin, P.; Lichtenstein, L.; Heiman, D. I.; Fennell, T.; Imielinski, M.; Hernandez, B.; Hodis, E.; Baca, S.; Dulak, A. M.; Lohr, J.; Landau, D. A.; Wu, C. J.; Melendez-Zajgla, J.; Hidalgo-Miranda, A.; Koren, A.; McCarroll, S. A.; Mora, J.; Crompton, B.; Onofrio, R.; Parkin, M.; Winckler, W.; Ardlie, K.; Gabriel, S. B.; Roberts, C. W. M.; Biegel, J. A.; Stegmaier, K.; Bass, A. J.; Garraway, L. A.; Meyerson, M.; Golub, T. R.; Gordenin, D. A.; Sunyaev, S.; Lander, E. S.; Getz, G., Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 2013, 499 (7457), 214-218. 4. Hanahan, D.; Weinberg, R. A., Hallmarks of cancer: the next generation. Cell 2011, 144 (5), 646-74. 5. Nussbaumer, S.; Bonnabry, P.; Veuthey, J. L.; Fleury-Souverain, S., Analysis of anticancer drugs: a review. Talanta 2011, 85 (5), 2265-89. 6. Leamon, C. P.; Reddy, J. A.; Vlahov, I. R.; Westrick, E.; Parker, N.; Nicoson, J. S.; Vetzel, M., Comparative preclinical activity of the folate-targeted Vinca alkaloid conjugates EC140 and EC145. Int J Cancer 2007, 121 (7), 1585-92. 7. KARNOFSKY, D. A.; BURCHENAL, J. H., Experimental observations on the effects of the nitrogen mustards on neoplastic tissues. Cancer Res 1947, 7 (1), 50. 8. Foote, M., The Importance of Planned Dose of Chemotherapy on Time: Do We Need to Change Our Clinical Practice? Oncologist 1998, 3 (5), 365-368. 9. Rettig, W. J.; Old, L. J., Immunogenetics of human cell surface differentiation. Annu Rev Immunol 1989, 7, 481-511. 10. Scott, A. M.; Wolchok, J. D.; Old, L. J., Antibody therapy of cancer. Nat Rev Cancer 2012, 12 (4), 278-87. 11. Goldenberg, D. M.; DeLand, F.; Kim, E.; Bennett, S.; Primus, F. J.; van Nagell, J. R.; Estes, N.; DeSimone, P.; Rayburn, P., Use of radiolabeled antibodies to carcinoembryonic antigen for the detection and localization of diverse cancers by external photoscanning. N Engl J Med 1978, 298 (25), 1384-6. 12. Gerber, D. E., Targeted therapies: a new generation of cancer treatments. Am Fam Physician 2008, 77 (3), 311-9. 13. Weiner, L. M.; Surana, R.; Wang, S., Monoclonal antibodies: versatile platforms for cancer immunotherapy. Nat Rev Immunol 2010, 10 (5), 317-27. 227

14. Scott, A. M.; Allison, J. P.; Wolchok, J. D., Monoclonal antibodies in cancer therapy. Cancer Immun 2012, 12, 14. 15. Köhler, G.; Milstein, C., Continuous cultures of fused cells secreting antibody of predefined specificity. Nature 1975, 256 (5517), 495-7. 16. Liu, J. K., The history of monoclonal antibody development - Progress, remaining challenges and future innovations. Ann Med Surg (Lond) 2014, 3 (4), 113-6. 17. Winter, G.; Griffiths, A. D.; Hawkins, R. E.; Hoogenboom, H. R., Making antibodies by phage display technology. Annu Rev Immunol 1994, 12, 433-55. 18. McLaughlin, P.; Grillo-López, A. J.; Link, B. K.; Levy, R.; Czuczman, M. S.; Williams, M. E.; Heyman, M. R.; Bence-Bruckler, I.; White, C. A.; Cabanillas, F.; Jain, V.; Ho, A. D.; Lister, J.; Wey, K.; Shen, D.; Dallaire, B. K., Rituximab chimeric anti-CD20 monoclonal antibody therapy for relapsed indolent lymphoma: half of patients respond to a four-dose treatment program. J Clin Oncol 1998, 16 (8), 2825-33. 19. Slamon, D. J.; Leyland-Jones, B.; Shak, S.; Fuchs, H.; Paton, V.; Bajamonde, A.; Fleming, T.; Eiermann, W.; Wolter, J.; Pegram, M.; Baselga, J.; Norton, L., Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med 2001, 344 (11), 783-92. 20. Meads, C.; Round, J.; Tubeuf, S.; Moore, D.; Pennant, M.; Bayliss, S., Cetuximab for the first-line treatment of metastatic colorectal cancer. Health Technol Assess 2010, 14 Suppl 1, 1-8. 21. Hughes, B., Antibody-drug conjugates for cancer: poised to deliver? Nat Rev Drug Discov 2010, 9 (9), 665-7. 22. Beck, A.; Goetsch, L.; Dumontet, C.; Corvaïa, N., Strategies and challenges for the next generation of antibody-drug conjugates. Nat Rev Drug Discov 2017, 16 (5), 315-337. 23. Weir, A. N.; Nesbitt, A.; Chapman, A. P.; Popplewell, A. G.; Antoniw, P.; Lawson, A. D., Formatting antibody fragments to mediate specific therapeutic functions. Biochem Soc Trans 2002, 30 (4), 512-6. 24. Chapman, A. P., PEGylated antibodies and antibody fragments for improved therapy: a review. Adv Drug Deliv Rev 2002, 54 (4), 531-45. 25. Chapman, A. P.; Antoniw, P.; Spitali, M.; West, S.; Stephens, S.; King, D. J., Therapeutic antibody fragments with prolonged in vivo half-lives. Nat Biotechnol 1999, 17 (8), 780-3. 26. Coelho, V.; Dernedde, J.; Petrausch, U.; Panjideh, H.; Fuchs, H.; Menzel, C.; Dübel, S.; Keilholz, U.; Thiel, E.; Deckert, P. M., Design, construction, and in vitro analysis of A33scFv::CDy, a recombinant fusion protein for antibody-directed enzyme prodrug therapy in colon cancer. Int J Oncol 2007, 31 (4), 951-7. 27. Kim, G. B.; Wang, Z.; Liu, Y. Y.; Stavrou, S.; Mathias, A.; Goodwin, K. J.; Thomas, J. M.; Neville, D. M., A fold-back single-chain diabody format enhances the bioactivity of an anti-monkey CD3 recombinant diphtheria toxin-based immunotoxin. Protein Eng Des Sel 2007, 20 (9), 425-32. 28. Nelson, A. L.; Dhimolea, E.; Reichert, J. M., Development trends for human monoclonal antibody therapeutics. Nat Rev Drug Discov 2010, 9 (10), 767-74.

228

29. Ahmad, Z. A.; Yeap, S. K.; Ali, A. M.; Ho, W. Y.; Alitheen, N. B.; Hamid, M., scFv antibody: principles and clinical application. Clin Dev Immunol 2012, 2012, 980250. 30. Ward, E. S.; Güssow, D.; Griffiths, A. D.; Jones, P. T.; Winter, G., Binding activities of a repertoire of single immunoglobulin variable domains secreted from Escherichia coli. Nature 1989, 341 (6242), 544-6. 31. Nelson, A. L., Antibody fragments: hope and hype. MAbs 2010, 2 (1), 77-83. 32. Lindhofer, H.; Menzel, H.; Günther, W.; Hültner, L.; Thierfelder, S., Bispecific antibodies target operationally tumor-specific antigens in two leukemia relapse models. Blood 1996, 88 (12), 4651-8. 33. Staerz, U. D.; Kanagawa, O.; Bevan, M. J., Hybrid antibodies can target sites for attack by T cells. Nature 1985, 314 (6012), 628-31. 34. Perez, P.; Hoffman, R. W.; Shaw, S.; Bluestone, J. A.; Segal, D. M., Specific targeting of cytotoxic T cells by anti-T3 linked to anti-target cell antibody. Nature 1985, 316 (6026), 354-6. 35. Lindhofer, H.; Mocikat, R.; Steipe, B.; Thierfelder, S., Preferential species- restricted heavy/light chain pairing in rat/mouse quadromas. Implications for a single-step purification of bispecific antibodies. J Immunol 1995, 155 (1), 219-25. 36. Chames, P.; Baty, D., Bispecific antibodies for cancer therapy: the light at the end of the tunnel? MAbs 2009, 1 (6), 539-47. 37. Heiss, M. M.; Murawa, P.; Koralewski, P.; Kutarska, E.; Kolesnik, O. O.; Ivanchenko, V. V.; Dudnichenko, A. S.; Aleknaviciene, B.; Razbadauskas, A.; Gore, M.; Ganea-Motan, E.; Ciuleanu, T.; Wimberger, P.; Schmittel, A.; Schmalfeldt, B.; Burges, A.; Bokemeyer, C.; Lindhofer, H.; Lahr, A.; Parsons, S. L., The trifunctional antibody catumaxomab for the treatment of malignant ascites due to epithelial cancer: Results of a prospective randomized phase II/III trial. Int J Cancer 2010, 127 (9), 2209-21. 38. Borlak, J.; Länger, F.; Spanel, R.; Schöndorfer, G.; Dittrich, C., Immune-mediated liver injury of the cancer therapeutic antibody catumaxomab targeting EpCAM, CD3 and Fcγ receptors. Oncotarget 2016, 7 (19), 28059-74. 39. Weiner, G. J.; Kostelny, S. A.; Hillstrom, J. R.; Cole, M. S.; Link, B. K.; Wang, S. L.; Tso, J. Y., The role of T cell activation in anti-CD3 x antitumor bispecific antibody therapy. J Immunol 1994, 152 (5), 2385-92. 40. Klein, J. S.; Gnanapragasam, P. N.; Galimidi, R. P.; Foglesong, C. P.; West, A. P.; Bjorkman, P. J., Examination of the contributions of size and avidity to the neutralization mechanisms of the anti-HIV antibodies b12 and 4E10. Proc Natl Acad Sci U S A 2009, 106 (18), 7385-90. 41. Brischwein, K.; Parr, L.; Pflanz, S.; Volkland, J.; Lumsden, J.; Klinger, M.; Locher, M.; Hammond, S. A.; Kiener, P.; Kufer, P.; Schlereth, B.; Baeuerle, P. A., Strictly target cell-dependent activation of T cells by bispecific single-chain antibody constructs of the BiTE class. J Immunother 2007, 30 (8), 798-807. 42. Amann, M.; D'Argouges, S.; Lorenczewski, G.; Brischwein, K.; Kischel, R.; Lutterbuese, R.; Mangold, S.; Rau, D.; Volkland, J.; Pflanz, S.; Raum, T.; Münz, M.; Kufer, P.; Schlereth, B.; Baeuerle, P. A.; Friedrich, M., Antitumor activity of an EpCAM/CD3-

229

bispecific BiTE antibody during long-term treatment of mice in the absence of T-cell anergy and sustained cytokine release. J Immunother 2009, 32 (5), 452-64. 43. Dreier, T.; Lorenczewski, G.; Brandl, C.; Hoffmann, P.; Syring, U.; Hanakam, F.; Kufer, P.; Riethmuller, G.; Bargou, R.; Baeuerle, P. A., Extremely potent, rapid and costimulation-independent cytotoxic T-cell response against lymphoma cells catalyzed by a single-chain bispecific antibody. Int J Cancer 2002, 100 (6), 690-7. 44. Lutterbuese, R.; Raum, T.; Kischel, R.; Lutterbuese, P.; Schlereth, B.; Schaller, E.; Mangold, S.; Rau, D.; Meier, P.; Kiener, P. A.; Mulgrew, K.; Oberst, M. D.; Hammond, S. A.; Baeuerle, P. A.; Kufer, P., Potent control of tumor growth by CEA/CD3-bispecific single-chain antibody constructs that are not competitively inhibited by soluble CEA. J Immunother 2009, 32 (4), 341-52. 45. Lutterbuese, R.; Raum, T.; Kischel, R.; Hoffmann, P.; Mangold, S.; Rattel, B.; Friedrich, M.; Thomas, O.; Lorenczewski, G.; Rau, D.; Schaller, E.; Herrmann, I.; Wolf, A.; Urbig, T.; Baeuerle, P. A.; Kufer, P., T cell-engaging BiTE antibodies specific for EGFR potently eliminate KRAS- and BRAF-mutated colorectal cancer cells. Proc Natl Acad Sci U S A 2010, 107 (28), 12605-10. 46. Bohlen, H.; Manzke, O.; Patel, B.; Moldenhauer, G.; Dörken, B.; von Fliedner, V.; Diehl, V.; Tesch, H., Cytolysis of leukemic B-cells by T-cells activated via two bispecific antibodies. Cancer Res 1993, 53 (18), 4310-4. 47. Manzke, O.; Titzer, S.; Tesch, H.; Diehl, V.; Bohlen, H., CD3 x CD19 bispecific antibodies and CD28 costimulation for locoregional treatment of low-malignancy non- Hodgkin's lymphoma. Cancer Immunol Immunother 1997, 45 (3-4), 198-202. 48. Kipriyanov, S. M.; Moldenhauer, G.; Schuhmacher, J.; Cochlovius, B.; Von der Lieth, C. W.; Matys, E. R.; Little, M., Bispecific tandem diabody for tumor therapy with improved antigen binding and pharmacokinetics. J Mol Biol 1999, 293 (1), 41-56. 49. Brischwein, K.; Schlereth, B.; Guller, B.; Steiger, C.; Wolf, A.; Lutterbuese, R.; Offner, S.; Locher, M.; Urbig, T.; Raum, T.; Kleindienst, P.; Wimberger, P.; Kimmig, R.; Fichtner, I.; Kufer, P.; Hofmeister, R.; da Silva, A. J.; Baeuerle, P. A., MT110: a novel bispecific single-chain antibody construct with high efficacy in eradicating established tumors. Mol Immunol 2006, 43 (8), 1129-43. 50. Herrmann, I.; Baeuerle, P. A.; Friedrich, M.; Murr, A.; Filusch, S.; Rüttinger, D.; Majdoub, M. W.; Sharma, S.; Kufer, P.; Raum, T.; Münz, M., Highly efficient elimination of colorectal tumor-initiating cells by an EpCAM/CD3-bispecific antibody engaging human T cells. PLoS One 2010, 5 (10), e13474. 51. Cioffi, M.; Dorado, J.; Baeuerle, P. A.; Heeschen, C., EpCAM/CD3-Bispecific T- cell engaging antibody MT110 eliminates primary human pancreatic cancer stem cells. Clin Cancer Res 2012, 18 (2), 465-74. 52. Bargou, R.; Leo, E.; Zugmaier, G.; Klinger, M.; Goebeler, M.; Knop, S.; Noppeney, R.; Viardot, A.; Hess, G.; Schuler, M.; Einsele, H.; Brandl, C.; Wolf, A.; Kirchinger, P.; Klappers, P.; Schmidt, M.; Riethmüller, G.; Reinhardt, C.; Baeuerle, P. A.; Kufer, P., Tumor regression in cancer patients by very low doses of a T cell-engaging antibody. Science 2008, 321 (5891), 974-7.

230

53. BRAMBELL, F. W.; HEMMINGS, W. A.; MORRIS, I. G., A THEORETICAL MODEL OF GAMMA-GLOBULIN CATABOLISM. Nature 1964, 203, 1352-4. 54. Klinger, M.; Benjamin, J.; Kischel, R.; Stienen, S.; Zugmaier, G., Harnessing T cells to fight cancer with BiTE® antibody constructs--past developments and future directions. Immunol Rev 2016, 270 (1), 193-208. 55. Topp, M. S.; Kufer, P.; Gökbuget, N.; Goebeler, M.; Klinger, M.; Neumann, S.; Horst, H. A.; Raff, T.; Viardot, A.; Schmid, M.; Stelljes, M.; Schaich, M.; Degenhard, E.; Köhne-Volland, R.; Brüggemann, M.; Ottmann, O.; Pfeifer, H.; Burmeister, T.; Nagorsen, D.; Schmidt, M.; Lutterbuese, R.; Reinhardt, C.; Baeuerle, P. A.; Kneba, M.; Einsele, H.; Riethmüller, G.; Hoelzer, D.; Zugmaier, G.; Bargou, R. C., Targeted therapy with the T- cell-engaging antibody blinatumomab of chemotherapy-refractory minimal residual disease in B-lineage acute lymphoblastic leukemia patients results in high response rate and prolonged leukemia-free survival. J Clin Oncol 2011, 29 (18), 2493-8. 56. FDA approves CAR-T cell therapy to treat adults with certain types of large B-cell lymphoma. In Yescarta is the second gene therapy product approved in the U.S., FDA News Release, 2017. 57. FDA approval brings first gene therapy to the United States. In CAR T-cell therapy approved to treat certain children and young adults with B-cell acute lymphoblastic leukemia, FDA News Release, 2017. 58. Sadelain, M.; Rivière, I.; Riddell, S., Therapeutic T cell engineering. Nature 2017, 545 (7655), 423-431. 59. Curran, K. J.; Pegram, H. J.; Brentjens, R. J., Chimeric antigen receptors for T cell immunotherapy: current understanding and future directions. J Gene Med 2012, 14 (6), 405-15. 60. Rosenberg, S. A.; Restifo, N. P.; Yang, J. C.; Morgan, R. A.; Dudley, M. E., Adoptive cell transfer: a clinical path to effective cancer immunotherapy. Nat Rev Cancer 2008, 8 (4), 299-308. 61. Ramos, C. A.; Dotti, G., Chimeric antigen receptor (CAR)-engineered lymphocytes for cancer therapy. Expert Opin Biol Ther 2011, 11 (7), 855-73. 62. Fesnak, A. D.; June, C. H.; Levine, B. L., Engineered T cells: the promise and challenges of cancer immunotherapy. Nat Rev Cancer 2016, 16 (9), 566-81. 63. Kochenderfer, J. N.; Wilson, W. H.; Janik, J. E.; Dudley, M. E.; Stetler-Stevenson, M.; Feldman, S. A.; Maric, I.; Raffeld, M.; Nathan, D. A.; Lanier, B. J.; Morgan, R. A.; Rosenberg, S. A., Eradication of B-lineage cells and regression of lymphoma in a patient treated with autologous T cells genetically engineered to recognize CD19. Blood 2010, 116 (20), 4099-102. 64. Porter, D. L.; Levine, B. L.; Kalos, M.; Bagg, A.; June, C. H., Chimeric antigen receptor-modified T cells in chronic lymphoid leukemia. N Engl J Med 2011, 365 (8), 725- 33. 65. Grupp, S. A.; Kalos, M.; Barrett, D.; Aplenc, R.; Porter, D. L.; Rheingold, S. R.; Teachey, D. T.; Chew, A.; Hauck, B.; Wright, J. F.; Milone, M. C.; Levine, B. L.; June, C.

231

H., Chimeric antigen receptor-modified T cells for acute lymphoid leukemia. N Engl J Med 2013, 368 (16), 1509-18. 66. Davila, M. L.; Riviere, I.; Wang, X.; Bartido, S.; Park, J.; Curran, K.; Chung, S. S.; Stefanski, J.; Borquez-Ojeda, O.; Olszewska, M.; Qu, J.; Wasielewska, T.; He, Q.; Fink, M.; Shinglot, H.; Youssif, M.; Satter, M.; Wang, Y.; Hosey, J.; Quintanilla, H.; Halton, E.; Bernal, Y.; Bouhassira, D. C.; Arcila, M. E.; Gonen, M.; Roboz, G. J.; Maslak, P.; Douer, D.; Frattini, M. G.; Giralt, S.; Sadelain, M.; Brentjens, R., Efficacy and toxicity management of 19-28z CAR T cell therapy in B cell acute lymphoblastic leukemia. Sci Transl Med 2014, 6 (224), 224ra25. 67. Lee, D. W.; Kochenderfer, J. N.; Stetler-Stevenson, M.; Cui, Y. K.; Delbrook, C.; Feldman, S. A.; Fry, T. J.; Orentas, R.; Sabatino, M.; Shah, N. N.; Steinberg, S. M.; Stroncek, D.; Tschernia, N.; Yuan, C.; Zhang, H.; Zhang, L.; Rosenberg, S. A.; Wayne, A. S.; Mackall, C. L., T cells expressing CD19 chimeric antigen receptors for acute lymphoblastic leukaemia in children and young adults: a phase 1 dose-escalation trial. Lancet 2015, 385 (9967), 517-528. 68. Dotti, G.; Gottschalk, S.; Savoldo, B.; Brenner, M. K., Design and development of therapies using chimeric antigen receptor-expressing T cells. Immunol Rev 2014, 257 (1), 107-26. 69. Gilham, D. E.; Debets, R.; Pule, M.; Hawkins, R. E.; Abken, H., CAR-T cells and solid tumors: tuning T cells to challenge an inveterate foe. Trends Mol Med 2012, 18 (7), 377-84. 70. Morgan, R. A.; Yang, J. C.; Kitano, M.; Dudley, M. E.; Laurencot, C. M.; Rosenberg, S. A., Case report of a serious adverse event following the administration of T cells transduced with a chimeric antigen receptor recognizing ERBB2. Mol Ther 2010, 18 (4), 843-51. 71. Louis, C. U.; Savoldo, B.; Dotti, G.; Pule, M.; Yvon, E.; Myers, G. D.; Rossig, C.; Russell, H. V.; Diouf, O.; Liu, E.; Liu, H.; Wu, M. F.; Gee, A. P.; Mei, Z.; Rooney, C. M.; Heslop, H. E.; Brenner, M. K., Antitumor activity and long-term fate of chimeric antigen receptor-positive T cells in patients with neuroblastoma. Blood 2011, 118 (23), 6050-6. 72. Carlson, J. C.; Kanter, A.; Thuduppathy, G. R.; Cody, V.; Pineda, P. E.; McIvor, R. S.; Wagner, C. R., Designing protein dimerizers: the importance of ligand conformational equilibria. J Am Chem Soc 2003, 125 (6), 1501-7. 73. Carlson, J. C.; Jena, S. S.; Flenniken, M.; Chou, T. F.; Siegel, R. A.; Wagner, C. R., Chemically controlled self-assembly of protein nanorings. J Am Chem Soc 2006, 128 (23), 7630-8. 74. Fegan, A.; White, B.; Carlson, J. C.; Wagner, C. R., Chemically controlled protein assembly: techniques and applications. Chem Rev 2010, 110 (6), 3315-36. 75. Li, Q.; So, C. R.; Fegan, A.; Cody, V.; Sarikaya, M.; Vallera, D. A.; Wagner, C. R., Chemically self-assembled antibody nanorings (CSANs): design and characterization of an anti-CD3 IgM biomimetic. J Am Chem Soc 2010, 132 (48), 17247-57. 76. Fegan, A.; Kumarapperuma, S. C.; Wagner, C. R., Chemically self-assembled antibody nanostructures as potential drug carriers. Mol Pharm 2012, 9 (11), 3218-27.

232

77. Dauber-Osguthorpe, P.; Roberts, V. A.; Osguthorpe, D. J.; Wolff, J.; Genest, M.; Hagler, A. T., Structure and energetics of ligand binding to proteins: Escherichia coli dihydrofolate reductase-trimethoprim, a drug-receptor system. Proteins 1988, 4 (1), 31-47. 78. Shen, J. J.; Vallera, D. A.; Wagner, C. R., Prosthetic Antigen Receptors. J. Amer. Chem. Soc. 2015, 137 (32), 10108-10111. 79. Gabrielse, K.; Gangar, A.; Kumar, N.; Lee, J. C.; Fegan, A.; Shen, J. J.; Li, Q.; Vallera, D.; Wagner, C. R., Reversible re-programing of cell-cell interactions. Angew Chem Int Ed Engl 2014, 53 (20), 5112-6. 80. Shah, R.; Petersburg, J.; Gangar, A. C.; Fegan, A.; Wagner, C. R.; Kumarapperuma, S. C., In Vivo Evaluation of Site-Specifically PEGylated Chemically Self-Assembled Protein Nanostructures. Mol Pharm 2016, 13 (7), 2193-203. 81. Tumeh, P. C.; Radu, C. G.; Ribas, A., PET imaging of cancer immunotherapy. J Nucl Med 2008, 49 (6), 865-8. 82. Fass, L., Imaging and cancer: a review. Mol Oncol 2008, 2 (2), 115-52. 83. Gambhir, S. S., Molecular imaging of cancer with positron emission tomography. Nat Rev Cancer 2002, 2 (9), 683-93. 84. van Dongen, G. A.; Vosjan, M. J., Immuno-positron emission tomography: shedding light on clinical antibody therapy. Cancer Biother Radiopharm 2010, 25 (4), 375- 85. 85. Knowles, S. M.; Wu, A. M., Advances in immuno-positron emission tomography: antibodies for molecular imaging in oncology. J Clin Oncol 2012, 30 (31), 3884-92. 86. Mayer, A. T.; Natarajan, A.; Gordon, S. R.; Maute, R. L.; McCracken, M. N.; Ring, A. M.; Weissman, I. L.; Gambhir, S. S., Practical Immuno-PET Radiotracer Design Considerations for Human Immune Checkpoint Imaging. J Nucl Med 2017, 58 (4), 538- 546. 87. Bailly, C.; Cléry, P. F.; Faivre-Chauvet, A.; Bourgeois, M.; Guérard, F.; Haddad, F.; Barbet, J.; Chérel, M.; Kraeber-Bodéré, F.; Carlier, T.; Bodet-Milin, C., Immuno-PET for Clinical Theranostic Approaches. Int J Mol Sci 2016, 18 (1). 88. Goldenberg, D. M.; Chatal, J. F.; Barbet, J.; Boerman, O.; Sharkey, R. M., Cancer Imaging and Therapy with Bispecific Antibody Pretargeting. Update Cancer Ther 2007, 2 (1), 19-31. 89. Holliger, P.; Hudson, P. J., Engineered antibody fragments and the rise of single domains. Nat Biotechnol 2005, 23 (9), 1126-36. 90. Hackel, B. J.; Kimura, R. H.; Gambhir, S. S., Use of (64)Cu-labeled fibronectin domain with EGFR-overexpressing tumor xenograft: molecular imaging. Radiology 2012, 263 (1), 179-88. 91. Yang, D. J.; Kim, E. E.; Inoue, T., Targeted molecular imaging in oncology. Ann Nucl Med 2006, 20 (1), 1-11. 92. Mano, M., The burden of scientific progress: growing inequalities in the delivery of cancer care. Acta Oncol 2006, 45 (1), 84-6.

233

93. Neyt, M.; Albrecht, J.; Cocquyt, V., An economic evaluation of Herceptin in adjuvant setting: the Breast Cancer International Research Group 006 trial. Ann Oncol 2006, 17 (3), 381-90. 94. Gancberg, D.; Di Leo, A.; Cardoso, F.; Rouas, G.; Pedrocchi, M.; Paesmans, M.; Verhest, A.; Bernard-Marty, C.; Piccart, M. J.; Larsimont, D., Comparison of HER-2 status between primary breast cancer and corresponding distant metastatic sites. Ann Oncol 2002, 13 (7), 1036-43. 95. Zidan, J.; Dashkovsky, I.; Stayerman, C.; Basher, W.; Cozacov, C.; Hadary, A., Comparison of HER-2 overexpression in primary breast cancer and metastatic sites and its effect on biological targeting therapy of metastatic disease. Br J Cancer 2005, 93 (5), 552- 6. 96. Li, Q.; So, C. R.; Fegan, A.; Cody, V.; Sarikaya, M.; Vallera, D. A.; Wagner, C. R., Chemically Self-Assembled Antibody Nanorings (CSANs): Design and Characterization of an Anti-CD3 IgM Biomimetic. J. Am. Chem. Soc. 2010, 132 (48), 17247-17257. 97. Shen, J.; Vallera, D. A.; Wagner, C. R., Prosthetic Antigen Receptors. J. Am. Chem. Soc. 2015, 137 (32), 10108-11. 98. Price, R. L.; Chiocca, E. A., Evolution of malignant glioma treatment: from chemotherapy to vaccines to viruses. Neurosurgery 2014, 61 Suppl 1, 74-83. 99. Shinojima, N.; Tada, K.; Shiraishi, S.; Kamiryo, T.; Kochi, M.; Nakamura, H.; Makino, K.; Saya, H.; Hirano, H.; Kuratsu, J.; Oka, K.; Ishimaru, Y.; Ushio, Y., Prognostic value of epidermal growth factor receptor in patients with glioblastoma multiforme. Cancer Res. 2003, 63 (20), 6962-6970. 100. Yarden, Y.; Sliwkowski, M. X., Untangling the ErbB signalling network. Nat. Rev. Mol. Cell Biol. 2001, 2 (2), 127-37. 101. Baselga, J.; Arteaga, C. L., Critical update and emerging trends in epidermal growth factor receptor targeting in cancer. J. Clin. Oncol. 2005, 23 (11), 2445-59. 102. Hurvitz, S. A.; Hu, Y.; O'Brien, N.; Finn, R. S., Current approaches and future directions in the treatment of HER2-positive breast cancer. Cancer Treat Rev 2013, 39 (3), 219-29. 103. Tomas, A.; Futter, C. E.; Eden, E. R., EGF receptor trafficking: consequences for signaling and cancer. Trends. Cell Biol. 2014, 24 (1), 26-34. 104. Mamot, C.; Drummond, D. C.; Greiser, U.; Hong, K.; Kirpotin, D. B.; Marks, J. D.; Park, J. W., Epidermal growth factor receptor (EGFR)-targeted immunoliposomes mediate specific and efficient drug delivery to EGFR- and EGFRvIII-overexpressing tumor cells. Cancer Res. 2003, 63 (12), 3154-3161. 105. Song, S.; Liu, D.; Peng, J.; Deng, H.; Guo, Y.; Xu, L. X.; Miller, A. D.; Xu, Y., Novel peptide ligand directs liposomes toward EGF-R high-expressing cancer cells in vitro and in vivo. FASEB J. 2009, 23 (5), 1396-404. 106. Han, C. Y.; Yue, L. L.; Tai, L. Y.; Zhou, L.; Li, X. Y.; Xing, G. H.; Yang, X. G.; Sun, M. S.; Pan, W. S., A novel small peptide as an epidermal growth factor receptor targeting ligand for nanodelivery in vitro. Int J Nanomedicine 2013, 8, 1541-9.

234

107. Ongarora, B. G.; Fontenot, K. R.; Hu, X.; Sehgal, I.; Satyanarayana-Jois, S. D.; Vicente, M. G., Phthalocyanine-peptide conjugates for epidermal growth factor receptor targeting. J Med Chem 2012, 55 (8), 3725-38. 108. Nischan, N.; Hackenberger, C. P., Site-specific PEGylation of proteins: recent developments. J. Org. Chem. 2014, 79 (22), 10727-33. 109. Dobrovolskaia, M. A.; McNeil, S. E., Immunological properties of engineered nanomaterials. Nat Nanotechnol 2007, 2 (8), 469-78. 110. Perry, J. L.; Reuter, K. G.; Kai, M. P.; Herlihy, K. P.; Jones, S. W.; Luft, J. C.; Napier, M.; Bear, J. E.; DeSimone, J. M., PEGylated PRINT nanoparticles: the impact of PEG density on protein binding, macrophage association, biodistribution, and pharmacokinetics. Nano Lett 2012, 12 (10), 5304-10. 111. Fegan, A.; Kumarapperuma, S. C.; Wagner, C. R., Chemically Self-Assembled Antibody Nanostructures as Potential Drug Carriers. Mol. Pharm. 2012, 9 (11), 3218-3227. 112. Anderson, C. J.; Ferdani, R., Copper-64 Radiopharmaceuticals for PET Imaging of Cancer: Advances in Preclinical and Clinical Research. Cancer Biotherapy and Radiopharmaceuticals 2009, 24 (4), 379-393. 113. Chen, X. Y.; Park, R.; Hou, Y. P.; Tohme, M.; Shahinian, A. H.; Bading, J. R.; Conti, P. S., MicroPET and autoradiographic imaging of GRP receptor expression with Cu-64-DOTA- Lys(3) bombesin in human prostate adenocarcinoma xenografts. J. Nucl. Med. 2004, 45 (8), 1390-1397. 114. Li, Q.; Hapka, D.; Chen, H.; Vallera, D. A.; Wagner, C. R., Self-Assembly of Antibodies by Chemical Induction. Angew. Chem. Int. Ed. Engl. 2008, 47 (52), 10179- 10182. 115. Carlson, J. C. T.; Jena, S. S.; Flenniken, M.; Chou, T.-F.; Siegel, R. A.; Wagner, C. R., Chemically Controlled Self-Assembly of Protein Nanorings. J. Am. Chem. Soc. 2006, 128 (23), 7630-7638. 116. Longmire, M.; Choyke, P. L.; Kobayashi, H., Clearance properties of nano-sized particles and molecules as imaging agents: considerations and caveats. Nanomedicine 2008, 3 (5), 703-717. 117. Yu, M.; Zheng, J., Clearance Pathways and Tumor Targeting of Imaging Nanoparticles. ACS Nano 2015, 9 (7), 6655-6674. 118. Choi, H. S.; Liu, W.; Misra, P.; Tanaka, E.; Zimmer, J. P.; Ipe, B. I.; Bawendi, M. G.; Frangioni, J. V., Renal clearance of quantum dots. Nat. Biotechnol. 2007, 25 (10), 1165-1170. 119. Kontermann, R. E., Strategies for extended serum half-life of protein therapeutics. Curr. Opin. Biotech. 2011, 22 (6), 868-876. 120. Wattendorf, U.; Merkle, H. P., PEGylation as a Tool for the Biomedical Engineering of Surface Modified Microparticles. J. Pharm. Sci. 2008, 97 (11), 4655-4669. 121. Basu, A.; Yang, K.; Wang, M. L.; Liu, S.; Chintala, R.; Palm, T.; Zhao, H.; Peng, P.; Wu, D. C.; Zhang, Z. F.; Hua, J.; Hsieh, M. C.; Zhou, J.; Petti, G.; Li, X. G.; Janjua, A.; Mendez, M.; Liu, J.; Longley, C.; Zhang, Z.; Mehlig, M.; Borowski, V.; Viswanathan, M.; Filpula, D., Structure-function engineering of interferon-beta-1b for improving stability,

235

solubility, potency, immunogenicity, and pharmacokinetic properties by site-selective mono-PEGylation. Bioconjug. Chem. 2006, 17 (3), 618-630. 122. Kularatne, S. A.; Deshmukh, V.; Ma, J.; Tardif, V.; Lim, R. K.; Pugh, H. M.; Sun, Y.; Manibusan, A.; Sellers, A. J.; Barnett, R. S.; Srinagesh, S.; Forsyth, J. S.; Hassenpflug, W.; Tian, F.; Javahishvili, T.; Felding-Habermann, B.; Lawson, B. R.; Kazane, S. A.; Schultz, P. G., A CXCR4-targeted site-specific antibody-drug conjugate. Angew Chem Int Ed Engl 2014, 53 (44), 11863-7. 123. Lu, H.; Wang, D.; Kazane, S.; Javahishvili, T.; Tian, F.; Song, F.; Sellers, A.; Barnett, B.; Schultz, P. G., Site-specific antibody-polymer conjugates for siRNA delivery. J Am Chem Soc 2013, 135 (37), 13885-91. 124. Cho, H.; Daniel, T.; Buechler, Y. J.; Litzinger, D. C.; Maio, Z.; Putnam, A. M.; Kraynov, V. S.; Sim, B. C.; Bussell, S.; Javahishvili, T.; Kaphle, S.; Viramontes, G.; Ong, M.; Chu, S.; Becky, G. C.; Lieu, R.; Knudsen, N.; Castiglioni, P.; Norman, T. C.; Axelrod, D. W.; Hoffman, A. R.; Schultz, P. G.; DiMarchi, R. D.; Kimmel, B. E., Optimized clinical performance of growth hormone with an expanded genetic code. Proc Natl Acad Sci U S A 2011, 108 (22), 9060-5. 125. Strop, P.; Liu, S. H.; Dorywalska, M.; Delaria, K.; Dushin, R. G.; Tran, T. T.; Ho, W. H.; Farias, S.; Casas, M. G.; Abdiche, Y.; Zhou, D.; Chandrasekaran, R.; Samain, C.; Loo, C.; Rossi, A.; Rickert, M.; Krimm, S.; Wong, T.; Chin, S. M.; Yu, J.; Dilley, J.; Chaparro-Riggers, J.; Filzen, G. F.; O'Donnell, C. J.; Wang, F.; Myers, J. S.; Pons, J.; Shelton, D. L.; Rajpal, A., Location matters: site of conjugation modulates stability and pharmacokinetics of antibody drug conjugates. Chem. Biol. 2013, 20 (2), 161-7. 126. Young, T. S.; Ahmad, I.; Yin, J. A.; Schultz, P. G., An Enhanced System for Unnatural Amino Acid Mutagenesis in E. coli. J. Mol. Biol. 2010, 395 (2), 361-374. 127. Lim, R. K.; Yu, S.; Cheng, B.; Li, S.; Kim, N. J.; Cao, Y.; Chi, V.; Kim, J. Y.; Chatterjee, A. K.; Schultz, P. G.; Tremblay, M. S.; Kazane, S. A., Targeted Delivery of LXR Agonist Using a Site-Specific Antibody-Drug Conjugate. Bioconjug. Chem. 2015. 128. Veronese, F.; Mero, A.; Pasut, G., Protein PEGylation, basic science and biological applications. In PEGylated Protein Drugs: Basic Science and Clinical Applications, Veronese, F., Ed. Birkhäuser Basel: 2009; pp 11-31. 129. Cole, A. J.; David, A. E.; Wang, J.; Galbán, C. J.; Hill, H. L.; Yang, V. C., Polyethylene glycol modified, cross-linked starch-coated iron oxide nanoparticles for enhanced magnetic tumor targeting. Biomaterials 2011, 32 (8), 2183-93. 130. Bertrand, N.; Wu, J.; Xu, X.; Kamaly, N.; Farokhzad, O. C., Cancer nanotechnology: The impact of passive and active targeting in the era of modern cancer biology. Adv. Drug Deliver. Rev. 2014, 66, 2-25. 131. Farkas, M. E.; Aanei, I. L.; Behrens, C. R.; Tong, G. J.; Murphy, S. T.; O'Neil, J. P.; Francis, M. B., PET Imaging and Biodistribution of Chemically Modified Bacteriophage MS2. Mol. Pharm. 2013, 10 (1), 69-76. 132. Jensen, S. A.; Day, E. S.; Ko, C. H.; Hurley, L. A.; Luciano, J. P.; Kouri, F. M.; Merkel, T. J.; Luthi, A. J.; Patel, P. C.; Cutler, J. I.; Daniel, W. L.; Scott, A. W.; Rotz, M. W.; Meade, T. J.; Giljohann, D. A.; Mirkin, C. A.; Stegh, A. H., Spherical Nucleic Acid

236

Nanoparticle Conjugates as an RNAi-Based Therapy for Glioblastoma. Sci. Transl. Med. 2013, 5 (209). 133. Zeglis, B. M.; Lewis, J. S., A practical guide to the construction of radiometallated bioconjugates for positron emission tomography. Dalton T. 2011, 40 (23), 6168-6195. 134. Wang, L.; Zhang, Z.; Brock, A.; Schultz, P. G., Addition of the keto functional group to the genetic code of Escherichia coli. Proc. Natl. Acad. Sci. USA 2003, 100 (1), 56-61. 135. Baitsch, L.; Baumgaertner, P.; Devêvre, E.; Raghav, S. K.; Legat, A.; Barba, L.; Wieckowski, S.; Bouzourene, H.; Deplancke, B.; Romero, P.; Rufer, N.; Speiser, D. E., Exhaustion of tumor-specific CD8⁺ T cells in metastases from melanoma patients. J Clin Invest 2011, 121 (6), 2350-60. 136. Domschke, C.; Schuetz, F.; Ge, Y.; Seibel, T.; Falk, C.; Brors, B.; Vlodavsky, I.; Sommerfeldt, N.; Sinn, H. P.; Kühnle, M. C.; Schneeweiss, A.; Scharf, A.; Sohn, C.; Schirrmacher, V.; Moldenhauer, G.; Momburg, F.; Beckhove, P., Intratumoral cytokines and tumor cell biology determine spontaneous breast cancer-specific immune responses and their correlation to prognosis. Cancer Res 2009, 69 (21), 8420-8. 137. Drake, C. G.; Jaffee, E.; Pardoll, D. M., Mechanisms of immune evasion by tumors. Adv Immunol 2006, 90, 51-81. 138. Sato, E.; Olson, S. H.; Ahn, J.; Bundy, B.; Nishikawa, H.; Qian, F.; Jungbluth, A. A.; Frosina, D.; Gnjatic, S.; Ambrosone, C.; Kepner, J.; Odunsi, T.; Ritter, G.; Lele, S.; Chen, Y. T.; Ohtani, H.; Old, L. J.; Odunsi, K., Intraepithelial CD8+ tumor-infiltrating lymphocytes and a high CD8+/regulatory T cell ratio are associated with favorable prognosis in ovarian cancer. Proc Natl Acad Sci U S A 2005, 102 (51), 18538-43. 139. Zhao, E.; Wang, L.; Dai, J.; Kryczek, I.; Wei, S.; Vatan, L.; Altuwaijri, S.; Sparwasser, T.; Wang, G.; Keller, E. T.; Zou, W., Regulatory T cells in the bone marrow microenvironment in patients with prostate cancer. Oncoimmunology 2012, 1 (2), 152-161. 140. Laheru, D.; Lutz, E.; Burke, J.; Biedrzycki, B.; Solt, S.; Onners, B.; Tartakovsky, I.; Nemunaitis, J.; Le, D.; Sugar, E.; Hege, K.; Jaffee, E., Allogeneic granulocyte macrophage colony-stimulating factor-secreting tumor immunotherapy alone or in sequence with cyclophosphamide for metastatic pancreatic cancer: a pilot study of safety, feasibility, and immune activation. Clin Cancer Res 2008, 14 (5), 1455-63. 141. Keenan, B.; Jaffee, E. M., Immunotherapy in preneoplastic disease: targeting early procarcinogenic inflammatory changes that lead to immune suppression and tumor tolerance. Ann N Y Acad Sci 2013, 1284, 12-6. 142. Phan, G. Q.; Yang, J. C.; Sherry, R. M.; Hwu, P.; Topalian, S. L.; Schwartzentruber, D. J.; Restifo, N. P.; Haworth, L. R.; Seipp, C. A.; Freezer, L. J.; Morton, K. E.; Mavroukakis, S. A.; Duray, P. H.; Steinberg, S. M.; Allison, J. P.; Davis, T. A.; Rosenberg, S. A., Cancer regression and autoimmunity induced by cytotoxic T lymphocyte-associated antigen 4 blockade in patients with metastatic melanoma. Proc Natl Acad Sci U S A 2003, 100 (14), 8372-7.

237

143. Peggs, K. S.; Quezada, S. A.; Chambers, C. A.; Korman, A. J.; Allison, J. P., Blockade of CTLA-4 on both effector and regulatory T cell compartments contributes to the antitumor activity of anti-CTLA-4 antibodies. J Exp Med 2009, 206 (8), 1717-25. 144. Brahmer, J. R.; Drake, C. G.; Wollner, I.; Powderly, J. D.; Picus, J.; Sharfman, W. H.; Stankevich, E.; Pons, A.; Salay, T. M.; McMiller, T. L.; Gilson, M. M.; Wang, C.; Selby, M.; Taube, J. M.; Anders, R.; Chen, L.; Korman, A. J.; Pardoll, D. M.; Lowy, I.; Topalian, S. L., Phase I study of single-agent anti-programmed death-1 (MDX-1106) in refractory solid tumors: safety, clinical activity, pharmacodynamics, and immunologic correlates. J Clin Oncol 2010, 28 (19), 3167-75. 145. Nolz, J. C.; Starbeck-Miller, G. R.; Harty, J. T., Naive, effector and memory CD8 T-cell trafficking: parallels and distinctions. Immunotherapy 2011, 3 (10), 1223-33. 146. Mitchell, D. A.; Karikari, I.; Cui, X.; Xie, W.; Schmittling, R.; Sampson, J. H., Selective modification of antigen-specific T cells by RNA electroporation. Hum Gene Ther 2008, 19 (5), 511-21. 147. Fisher, D. T.; Chen, Q.; Appenheimer, M. M.; Skitzki, J.; Wang, W. C.; Odunsi, K.; Evans, S. S., Hurdles to lymphocyte trafficking in the tumor microenvironment: implications for effective immunotherapy. Immunol Invest 2006, 35 (3-4), 251-77. 148. Fisher, D. T.; Chen, Q.; Skitzki, J. J.; Muhitch, J. B.; Zhou, L.; Appenheimer, M. M.; Vardam, T. D.; Weis, E. L.; Passanese, J.; Wang, W. C.; Gollnick, S. O.; Dewhirst, M. W.; Rose-John, S.; Repasky, E. A.; Baumann, H.; Evans, S. S., IL-6 trans-signaling licenses mouse and human tumor microvascular gateways for trafficking of cytotoxic T cells. J Clin Invest 2011, 121 (10), 3846-59. 149. Lamers, C. H.; Sleijfer, S.; van Steenbergen, S.; van Elzakker, P.; van Krimpen, B.; Groot, C.; Vulto, A.; den Bakker, M.; Oosterwijk, E.; Debets, R.; Gratama, J. W., Treatment of metastatic renal cell carcinoma with CAIX CAR-engineered T cells: clinical evaluation and management of on-target toxicity. Mol Ther 2013, 21 (4), 904-12. 150. Parkhurst, M. R.; Yang, J. C.; Langan, R. C.; Dudley, M. E.; Nathan, D. A.; Feldman, S. A.; Davis, J. L.; Morgan, R. A.; Merino, M. J.; Sherry, R. M.; Hughes, M. S.; Kammula, U. S.; Phan, G. Q.; Lim, R. M.; Wank, S. A.; Restifo, N. P.; Robbins, P. F.; Laurencot, C. M.; Rosenberg, S. A., T cells targeting carcinoembryonic antigen can mediate regression of metastatic colorectal cancer but induce severe transient colitis. Mol Ther 2011, 19 (3), 620-6. 151. Bonifant, C. L.; Jackson, H. J.; Brentjens, R. J.; Curran, K. J., Toxicity and management in CAR T-cell therapy. Mol Ther Oncolytics 2016, 3, 16011. 152. Heslop, H. E.; Slobod, K. S.; Pule, M. A.; Hale, G. A.; Rousseau, A.; Smith, C. A.; Bollard, C. M.; Liu, H.; Wu, M. F.; Rochester, R. J.; Amrolia, P. J.; Hurwitz, J. L.; Brenner, M. K.; Rooney, C. M., Long-term outcome of EBV-specific T-cell infusions to prevent or treat EBV-related lymphoproliferative disease in transplant recipients. Blood 2010, 115 (5), 925-35. 153. Scholler, J.; Brady, T. L.; Binder-Scholl, G.; Hwang, W. T.; Plesa, G.; Hege, K. M.; Vogel, A. N.; Kalos, M.; Riley, J. L.; Deeks, S. G.; Mitsuyasu, R. T.; Bernstein, W. B.; Aronson, N. E.; Levine, B. L.; Bushman, F. D.; June, C. H., Decade-long safety and

238

function of retroviral-modified chimeric antigen receptor T cells. Sci Transl Med 2012, 4 (132), 132ra53. 154. Lee, D. W.; Gardner, R.; Porter, D. L.; Louis, C. U.; Ahmed, N.; Jensen, M.; Grupp, S. A.; Mackall, C. L., Current concepts in the diagnosis and management of cytokine release syndrome. Blood 2014, 124 (2), 188-95. 155. Kershaw, M. H.; Westwood, J. A.; Parker, L. L.; Wang, G.; Eshhar, Z.; Mavroukakis, S. A.; White, D. E.; Wunderlich, J. R.; Canevari, S.; Rogers-Freezer, L.; Chen, C. C.; Yang, J. C.; Rosenberg, S. A.; Hwu, P., A phase I study on adoptive immunotherapy using gene-modified T cells for ovarian cancer. Clin Cancer Res 2006, 12 (20 Pt 1), 6106-15. 156. Di Stasi, A.; Tey, S. K.; Dotti, G.; Fujita, Y.; Kennedy-Nasser, A.; Martinez, C.; Straathof, K.; Liu, E.; Durett, A. G.; Grilley, B.; Liu, H.; Cruz, C. R.; Savoldo, B.; Gee, A. P.; Schindler, J.; Krance, R. A.; Heslop, H. E.; Spencer, D. M.; Rooney, C. M.; Brenner, M. K., Inducible apoptosis as a safety switch for adoptive cell therapy. N Engl J Med 2011, 365 (18), 1673-83. 157. Zhao, Y.; Moon, E.; Carpenito, C.; Paulos, C. M.; Liu, X.; Brennan, A. L.; Chew, A.; Carroll, R. G.; Scholler, J.; Levine, B. L.; Albelda, S. M.; June, C. H., Multiple injections of electroporated autologous T cells expressing a chimeric antigen receptor mediate regression of human disseminated tumor. Cancer Res 2010, 70 (22), 9053-61. 158. Wu, C. Y.; Roybal, K. T.; Puchner, E. M.; Onuffer, J.; Lim, W. A., Remote control of therapeutic T cells through a small molecule-gated chimeric receptor. Science 2015, 350 (6258), aab4077. 159. Ma, J. S.; Kim, J. Y.; Kazane, S. A.; Choi, S. H.; Yun, H. Y.; Kim, M. S.; Rodgers, D. T.; Pugh, H. M.; Singer, O.; Sun, S. B.; Fonslow, B. R.; Kochenderfer, J. N.; Wright, T. M.; Schultz, P. G.; Young, T. S.; Kim, C. H.; Cao, Y., Versatile strategy for controlling the specificity and activity of engineered T cells. Proc Natl Acad Sci U S A 2016, 113 (4), E450-8. 160. Turner, J.; Schneider, S. M., Blinatumomab: A New Treatment for Adults With Relapsed Acute Lymphocytic Leukemia. Clin J Oncol Nurs 2016, 20 (2), 165-8. 161. Kontermann, R. E.; Brinkmann, U., Bispecific antibodies. Drug Discov Today 2015, 20 (7), 838-47. 162. Cochlovius, B.; Kipriyanov, S. M.; Stassar, M. J.; Christ, O.; Schuhmacher, J.; Strauss, G.; Moldenhauer, G.; Little, M., Treatment of human B cell lymphoma xenografts with a CD3 x CD19 diabody and T cells. J Immunol 2000, 165 (2), 888-95. 163. Stork, R.; Campigna, E.; Robert, B.; Müller, D.; Kontermann, R. E., Biodistribution of a bispecific single-chain diabody and its half-life extended derivatives. J Biol Chem 2009, 284 (38), 25612-9. 164. Li, Q.; Hapka, D.; Chen, H.; Vallera, D. A.; Wagner, C. R., Self-assembly of antibodies by chemical induction. Angew Chem Int Ed Engl 2008, 47 (52), 10179-82. 165. M., B.; J., W. M.; J., d. B. C.; V., L. S., The Biology of the 17-1A Antigen (EpCAM). Journal of Molecular Medicine 1999, 77, 699-712.

239

166. Fiedler, W.; Honemann, D.; Ritter, B.; Bokemeyer, C.; Fettes, P.; Klinger, M.; Reinhardt, C.; Zugmaier, G.; Kaubitzsch, S.; Wolf, M., Safety and pharmacology of the EpCAM/CD3-bispecific BiTE antibody MT110 in patients with metastatic colorectal, gastric or lung cancer. Ejc Supplements 2009, 7 (2), 136-137. 167. Fiedler, W.; Wolf, M.; Kebenko, M.; Goebeler, M.; Ritter, B.; Quaas, A.; Vieser, E.; Hijazi, Y.; Patzak, I.; Friedrich, M.; Kufer, P.; Frankel, S.; Seggewiss-Bernhardt, R.; Kaubitzsch, S., A phase I study of EpCAM/CD3-bispecific antibody (MT110) in patients with advanced solid tumors. Journal of Clinical Oncology 2012, 30 (15). 168. Mau-Sorensen, M.; Dittrich, C.; Dienstmann, R.; Lassen, U.; Buchler, W.; Martinius, H.; Tabernero, J., A phase I trial of intravenous catumaxomab: a bispecific monoclonal antibody targeting EpCAM and the T cell coreceptor CD3. Cancer Chemotherapy and Pharmacology 2015, 75 (5), 1065-1073. 169. Balzar, M.; Winter, M. J.; de Boer, C. J.; Litvinov, S. V., The biology of the 17-1A antigen (Ep-CAM). J Mol Med (Berl) 1999, 77 (10), 699-712. 170. El-Sahwi, K.; Bellone, S.; Cocco, E.; Casagrande, F.; Bellone, M.; Abu-Khalaf, M.; Buza, N.; Tavassoli, F. A.; Hui, P.; Rüttinger, D.; Silasi, D. A.; Azodi, M.; Schwartz, P. E.; Rutherford, T. J.; Pecorelli, S.; Santin, A. D., Overexpression of EpCAM in uterine serous papillary carcinoma: implications for EpCAM-specific immunotherapy with human monoclonal antibody adecatumumab (MT201). Mol Cancer Ther 2010, 9 (1), 57-66. 171. Stefan, N.; Martin-Killias, P.; Wyss-Stoeckle, S.; Honegger, A.; Zangemeister- Wittke, U.; Plückthun, A., DARPins recognizing the tumor-associated antigen EpCAM selected by phage and ribosome display and engineered for multivalency. J Mol Biol 2011, 413 (4), 826-43. 172. Jahchan, N. S.; Lim, J. S.; Bola, B.; Morris, K.; Seitz, G.; Tran, K. Q.; Xu, L.; Trapani, F.; Morrow, C. J.; Cristea, S.; Coles, G. L.; Yang, D.; Vaka, D.; Kareta, M. S.; George, J.; Mazur, P. K.; Nguyen, T.; Anderson, W. C.; Dylla, S. J.; Blackhall, F.; Peifer, M.; Dive, C.; Sage, J., Identification and Targeting of Long-Term Tumor-Propagating Cells in Small Cell Lung Cancer. Cell Rep 2016, 16 (3), 644-56. 173. Gostner, J. M.; Fong, D.; Wrulich, O. A.; Lehne, F.; Zitt, M.; Hermann, M.; Krobitsch, S.; Martowicz, A.; Gastl, G.; Spizzo, G., Effects of EpCAM overexpression on human breast cancer cell lines. BMC Cancer 2011, 11, 45. 174. Winkler, J.; Martin-Killias, P.; Plückthun, A.; Zangemeister-Wittke, U., EpCAM- targeted delivery of nanocomplexed siRNA to tumor cells with designed ankyrin repeat proteins. Mol Cancer Ther 2009, 8 (9), 2674-83. 175. McLaughlin, P. M. J.; Harmsen, M. C.; Dokter, W. H. A.; Kroesen, B. J.; van der Molen, H.; Brinker, M. G. L.; Hollema, H.; Ruiters, M. H. J.; Buys, C.; de Leij, L., The epithelial glycoprotein 2 (EGP-2) promoter-driven epithelial-specific expression of EGP- 2 in transgenic mice: A new model to study carcinoma-directed immunotherapy. Cancer Research 2001, 61 (10), 4105-4111. 176. Fiedler, W. M.; Wolf, M.; Kebenko, M.; Goebeler, M. E.; Ritter, B.; Quaas, A.; Vieser, E.; Hijazi, Y.; Patzak, I.; Friedrich, M.; Kufer, P.; Frankel, S.; Seggewiss- Bernhardt, R.; Kaubitzsch, S., A phase I study of EpCAM/CD3-bispecific antibody

240

(MT110) in patients with advanced solid tumors. Journal of Clinical Oncology 2012, 30 (15). 177. Brischwein, K.; Schlereth, B.; Guller, B.; Steiger, C.; Wolf, A.; Lutterbuese, R.; Offner, S.; Locher, M.; Urbig, T.; Raum, T.; Kleindienst, P.; Wimberger, P.; Kimmig, R.; Fichtner, I.; Kufer, P.; Hofmeister, R.; da Silva, A. J.; Baeuerle, P. A., MT110: A novel bispecific single-chain antibody construct with high efficacy in eradicating established tumors. Mol. Immunol. 2006, 43 (8), 1129-1143. 178. Borlak, J.; Langer, F.; Spanel, R.; Schondorfer, G.; Dittrich, C., Immune-mediated liver injury of the cancer therapeutic antibody catumaxomab targeting EpCAM, CD3 and Fc gamma receptors. Oncotarget 2016, 7 (19), 28059-28074. 179. Baeuerle, P. A.; Reinhardt, C., Bispecific T-Cell Engaging Antibodies for Cancer Therapy. Cancer Research 2009, 69 (12), 4941-4944. 180. Cioffi, M.; Dorado, J.; Baeuerle, P. A.; Heeschen, C., EpCAM/CD3-Bispecific T- cell Engaging Antibody MT110 Eliminates Primary Human Pancreatic Cancer Stem Cells. Clinical Cancer Research 2012, 18 (2), 465-474. 181. Haas, C.; Krinner, E.; Brischwein, K.; Hoffmann, P.; Lutterbüse, R.; Schlereth, B.; Kufer, P.; Baeuerle, P. A., Mode of cytotoxic action of T cell-engaging BiTE antibody MT110. Immunobiology 2009, 214 (6), 441-453. 182. Klinger, M.; Benjamin, J.; Kischel, R.; Stienen, S.; Zugmaier, G., Harnessing T cells to fight cancer with BiTE (R) antibody constructs - past developments and future directions. Immunol. Rev. 2016, 270 (1), 193-208. 183. Ang, W. X.; Li, Z. D.; Chi, Z. X.; Du, S. H.; Chen, C.; Tay, J. C. K.; Toh, H. C.; Connolly, J. E.; Xu, X. H.; Wang, S., Intraperitoneal immunotherapy with T cells stably and transiently expressing anti-EpCAM CAR in xenograft models of peritoneal carcinomatosis. Oncotarget 2017, 8 (8), 13545-13559. 184. Schwab, R.; Crow, M. K.; Russo, C.; Weksler, M. E., Requirements for T cell activation by OKT3 monoclonal antibody: role of modulation of T3 molecules and interleukin 1. J Immunol 1985, 135 (3), 1714-8. 185. Van Wauwe, J. P.; Goossens, J. G.; Beverley, P. C., Human T lymphocyte activation by monoclonal antibodies; OKT3, but not UCHT1, triggers mitogenesis via an interleukin 2-dependent mechanism. J Immunol 1984, 133 (1), 129-32. 186. Haas, C.; Krinner, E.; Brischwein, K.; Hoffmann, P.; Lutterbüse, R.; Schlereth, B.; Kufer, P.; Baeuerle, P. A., Mode of cytotoxic action of T cell-engaging BiTE antibody MT110. Immunobiology 2009, 214 (6), 441-53. 187. Zheng, Y.; Collins, S. L.; Lutz, M. A.; Allen, A. N.; Kole, T. P.; Zarek, P. E.; Powell, J. D., A role for mammalian target of rapamycin in regulating T cell activation versus anergy. J Immunol 2007, 178 (4), 2163-70. 188. Zheng, Y.; Delgoffe, G. M.; Meyer, C. F.; Chan, W.; Powell, J. D., Anergic T cells are metabolically anergic. J Immunol 2009, 183 (10), 6095-101. 189. Sarbassov, D. D.; Ali, S. M.; Sabatini, D. M., Growing roles for the mTOR pathway. Curr Opin Cell Biol 2005, 17 (6), 596-603.

241

190. Salmond, R. J.; Emery, J.; Okkenhaug, K.; Zamoyska, R., MAPK, phosphatidylinositol 3-kinase, and mammalian target of rapamycin pathways converge at the level of ribosomal protein S6 phosphorylation to control metabolic signaling in CD8 T cells. J Immunol 2009, 183 (11), 7388-97. 191. Suggitt, M.; Bibby, M. C., 50 years of preclinical anticancer drug screening: empirical to target-driven approaches. Clin Cancer Res 2005, 11 (3), 971-81. 192. Zitvogel, L.; Pitt, J. M.; Daillere, R.; Smyth, M. J.; Kroemer, G., Mouse models in oncoimmunology. Nature Reviews Cancer 2016, 16 (12), 759-+. 193. Terakura, S.; Yamamoto, T. N.; Gardner, R. A.; Turtle, C. J.; Jensen, M. C.; Riddell, S. R., Generation of CD19-chimeric antigen receptor modified CD8+ T cells derived from virus-specific central memory T cells. Blood 2012, 119 (1), 72-82. 194. Sauerborn, M.; Brinks, V.; Jiskoot, W.; Schellekens, H., Immunological mechanism underlying the immune response to recombinant human protein therapeutics. Trends Pharmacol Sci 2010, 31 (2), 53-9. 195. Bonnet, D.; Dick, J. E., Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med 1997, 3 (7), 730-7. 196. Cho, R. W.; Clarke, M. F., Recent advances in cancer stem cells. Curr Opin Genet Dev 2008, 18 (1), 48-53. 197. Al-Hajj, M.; Clarke, M. F., Self-renewal and solid tumor stem cells. Oncogene 2004, 23 (43), 7274-82. 198. Boman, B. M.; Wicha, M. S., Cancer stem cells: a step toward the cure. J Clin Oncol 2008, 26 (17), 2795-9. 199. Reya, T.; Morrison, S. J.; Clarke, M. F.; Weissman, I. L., Stem cells, cancer, and cancer stem cells. Nature 2001, 414 (6859), 105-11. 200. Eyler, C. E.; Rich, J. N., Survival of the fittest: cancer stem cells in therapeutic resistance and angiogenesis. J Clin Oncol 2008, 26 (17), 2839-45. 201. Germano, S.; O'Driscoll, L., Breast cancer: understanding sensitivity and resistance to chemotherapy and targeted therapies to aid in personalised medicine. Curr Cancer Drug Targets 2009, 9 (3), 398-418. 202. Ferrandina, G.; Petrillo, M.; Bonanno, G.; Scambia, G., Targeting CD133 antigen in cancer. Expert Opin Ther Targets 2009, 13 (7), 823-37. 203. Zhao, P.; Lu, Y.; Jiang, X.; Li, X., Clinicopathological significance and prognostic value of CD133 expression in triple-negative breast carcinoma. Cancer Sci 2011, 102 (5), 1107-11. 204. Lin, W. M.; Karsten, U.; Goletz, S.; Cheng, R. C.; Cao, Y., Expression of CD176 (Thomsen-Friedenreich antigen) on lung, breast and liver cancer-initiating cells. Int J Exp Pathol 2011, 92 (2), 97-105. 205. Collins, A. T.; Berry, P. A.; Hyde, C.; Stower, M. J.; Maitland, N. J., Prospective identification of tumorigenic prostate cancer stem cells. Cancer Res 2005, 65 (23), 10946- 51. 206. Vermeulen, L.; Todaro, M.; de Sousa Mello, F.; Sprick, M. R.; Kemper, K.; Perez Alea, M.; Richel, D. J.; Stassi, G.; Medema, J. P., Single-cell cloning of colon cancer stem

242

cells reveals a multi-lineage differentiation capacity. Proc Natl Acad Sci U S A 2008, 105 (36), 13427-32. 207. Haraguchi, N.; Ishii, H.; Mimori, K.; Tanaka, F.; Ohkuma, M.; Kim, H. M.; Akita, H.; Takiuchi, D.; Hatano, H.; Nagano, H.; Barnard, G. F.; Doki, Y.; Mori, M., CD13 is a therapeutic target in human liver cancer stem cells. J Clin Invest 2010, 120 (9), 3326-39. 208. Singh, S. K.; Clarke, I. D.; Terasaki, M.; Bonn, V. E.; Hawkins, C.; Squire, J.; Dirks, P. B., Identification of a cancer stem cell in human brain tumors. Cancer Res 2003, 63 (18), 5821-8. 209. Ferrandina, G.; Bonanno, G.; Pierelli, L.; Perillo, A.; Procoli, A.; Mariotti, A.; Corallo, M.; Martinelli, E.; Rutella, S.; Paglia, A.; Zannoni, G.; Mancuso, S.; Scambia, G., Expression of CD133-1 and CD133-2 in ovarian cancer. Int J Gynecol Cancer 2008, 18 (3), 506-14. 210. Shmelkov, S. V.; St Clair, R.; Lyden, D.; Rafii, S., AC133/CD133/Prominin-1. Int J Biochem Cell Biol 2005, 37 (4), 715-9. 211. Griguer, C. E.; Oliva, C. R.; Gobin, E.; Marcorelles, P.; Benos, D. J.; Lancaster, J. R.; Gillespie, G. Y., CD133 is a marker of bioenergetic stress in human glioma. PLoS One 2008, 3 (11), e3655. 212. Weigmann, A.; Corbeil, D.; Hellwig, A.; Huttner, W. B., Prominin, a novel microvilli-specific polytopic membrane protein of the apical surface of epithelial cells, is targeted to plasmalemmal protrusions of non-epithelial cells. Proc Natl Acad Sci U S A 1997, 94 (23), 12425-30. 213. Rappa, G.; Fodstad, O.; Lorico, A., The stem cell-associated antigen CD133 (Prominin-1) is a molecular therapeutic target for metastatic melanoma. Stem Cells 2008, 26 (12), 3008-17. 214. Mak, A. B.; Nixon, A. M.; Kittanakom, S.; Stewart, J. M.; Chen, G. I.; Curak, J.; Gingras, A. C.; Mazitschek, R.; Neel, B. G.; Stagljar, I.; Moffat, J., Regulation of CD133 by HDAC6 promotes β-catenin signaling to suppress cancer cell differentiation. Cell Rep 2012, 2 (4), 951-63. 215. Takenobu, H.; Shimozato, O.; Nakamura, T.; Ochiai, H.; Yamaguchi, Y.; Ohira, M.; Nakagawara, A.; Kamijo, T., CD133 suppresses neuroblastoma cell differentiation via signal pathway modification. Oncogene 2011, 30 (1), 97-105. 216. Wu, Y.; Wu, P. Y., CD133 as a marker for cancer stem cells: progresses and concerns. Stem Cells Dev 2009, 18 (8), 1127-34. 217. Horst, D.; Kriegl, L.; Engel, J.; Kirchner, T.; Jung, A., CD133 expression is an independent prognostic marker for low survival in colorectal cancer. Br J Cancer 2008, 99 (8), 1285-9. 218. Wu, B.; Sun, C.; Feng, F.; Ge, M.; Xia, L., Do relevant markers of cancer stem cells CD133 and Nestin indicate a poor prognosis in glioma patients? A systematic review and meta-analysis. J Exp Clin Cancer Res 2015, 34, 44. 219. Singh, S. K.; Hawkins, C.; Clarke, I. D.; Squire, J. A.; Bayani, J.; Hide, T.; Henkelman, R. M.; Cusimano, M. D.; Dirks, P. B., Identification of human brain tumour initiating cells. Nature 2004, 432 (7015), 396-401.

243

220. Peichev, M.; Naiyer, A. J.; Pereira, D.; Zhu, Z.; Lane, W. J.; Williams, M.; Oz, M. C.; Hicklin, D. J.; Witte, L.; Moore, M. A.; Rafii, S., Expression of VEGFR-2 and AC133 by circulating human CD34(+) cells identifies a population of functional endothelial precursors. Blood 2000, 95 (3), 952-8. 221. Corbeil, D.; Röper, K.; Hellwig, A.; Tavian, M.; Miraglia, S.; Watt, S. M.; Simmons, P. J.; Peault, B.; Buck, D. W.; Huttner, W. B., The human AC133 hematopoietic stem cell antigen is also expressed in epithelial cells and targeted to plasma membrane protrusions. J Biol Chem 2000, 275 (8), 5512-20. 222. Uchida, N.; Buck, D. W.; He, D.; Reitsma, M. J.; Masek, M.; Phan, T. V.; Tsukamoto, A. S.; Gage, F. H.; Weissman, I. L., Direct isolation of human central nervous system stem cells. Proc Natl Acad Sci U S A 2000, 97 (26), 14720-5. 223. Jaksch, M.; Múnera, J.; Bajpai, R.; Terskikh, A.; Oshima, R. G., Cell cycle- dependent variation of a CD133 epitope in human embryonic stem cell, colon cancer, and melanoma cell lines. Cancer Res 2008, 68 (19), 7882-6. 224. Bidlingmaier, S.; Zhu, X.; Liu, B., The utility and limitations of glycosylated human CD133 epitopes in defining cancer stem cells. J Mol Med (Berl) 2008, 86 (9), 1025- 32. 225. Kemper, K.; Sprick, M. R.; de Bree, M.; Scopelliti, A.; Vermeulen, L.; Hoek, M.; Zeilstra, J.; Pals, S. T.; Mehmet, H.; Stassi, G.; Medema, J. P., The AC133 epitope, but not the CD133 protein, is lost upon cancer stem cell differentiation. Cancer Res 2010, 70 (2), 719-29. 226. Pavon, L. F.; Gamarra, L. F.; Marti, L. C.; Amaro Junior, E.; Moreira-Filho, C. A.; Camargo-Mathias, M. I.; Okamoto, O. K., Ultrastructural characterization of CD133+ stem cells bound to superparamagnetic nanoparticles: possible biotechnological applications. J Microsc 2008, 231 (3), 374-83. 227. Swaminathan, S. K.; Olin, M. R.; Forster, C. L.; Cruz, K. S.; Panyam, J.; Ohlfest, J. R., Identification of a novel monoclonal antibody recognizing CD133. J Immunol Methods 2010, 361 (1-2), 110-5. 228. Yin, A. H.; Miraglia, S.; Zanjani, E. D.; Almeida-Porada, G.; Ogawa, M.; Leary, A. G.; Olweus, J.; Kearney, J.; Buck, D. W., AC133, a novel marker for human hematopoietic stem and progenitor cells. Blood 1997, 90 (12), 5002-12. 229. Waldron, N. N.; Kaufman, D. S.; Oh, S.; Inde, Z.; Hexum, M. K.; Ohlfest, J. R.; Vallera, D. A., Targeting tumor-initiating cancer cells with dCD133KDEL shows impressive tumor reductions in a xenotransplant model of human head and neck cancer. Mol Cancer Ther 2011, 10 (10), 1829-38. 230. Smith, L. M.; Nesterova, A.; Ryan, M. C.; Duniho, S.; Jonas, M.; Anderson, M.; Zabinski, R. F.; Sutherland, M. K.; Gerber, H. P.; Van Orden, K. L.; Moore, P. A.; Ruben, S. M.; Carter, P. J., CD133/prominin-1 is a potential therapeutic target for antibody-drug conjugates in hepatocellular and gastric cancers. Br J Cancer 2008, 99 (1), 100-9. 231. Rutella, S.; Bonanno, G.; Marone, M.; De Ritis, D.; Mariotti, A.; Voso, M. T.; Scambia, G.; Mancuso, S.; Leone, G.; Pierelli, L., Identification of a novel subpopulation

244

of human cord blood CD34-CD133-CD7-CD45+lineage- cells capable of lymphoid/NK cell differentiation after in vitro exposure to IL-15. J Immunol 2003, 171 (6), 2977-88. 232. Suuronen, E. J.; Wong, S.; Kapila, V.; Waghray, G.; Whitman, S. C.; Mesana, T. G.; Ruel, M., Generation of CD133+ cells from CD133- peripheral blood mononuclear cells and their properties. Cardiovasc Res 2006, 70 (1), 126-35. 233. Zhao, Y.; Glesne, D.; Huberman, E., A human peripheral blood monocyte-derived subset acts as pluripotent stem cells. Proc Natl Acad Sci U S A 2003, 100 (5), 2426-31. 234. Urbich, C.; Heeschen, C.; Aicher, A.; Dernbach, E.; Zeiher, A. M.; Dimmeler, S., Relevance of monocytic features for neovascularization capacity of circulating endothelial progenitor cells. Circulation 2003, 108 (20), 2511-6. 235. Bouckenooghe, T.; Vandewalle, B.; Moerman, E.; Danzé, P. M.; Lukowiak, B.; Muharram, G.; Kerr-Conte, J.; Gmyr, V.; Laine, B.; Pattou, F., Expression of progenitor cell markers during expansion of sorted human pancreatic beta cells. Gene Expr 2005, 12 (2), 83-98. 236. Dubreuil, V.; Marzesco, A. M.; Corbeil, D.; Huttner, W. B.; Wilsch-Bräuninger, M., Midbody and primary cilium of neural progenitors release extracellular membrane particles enriched in the stem cell marker prominin-1. J Cell Biol 2007, 176 (4), 483-95. 237. Jones, A. R.; Shusta, E. V., Blood-brain barrier transport of therapeutics via receptor-mediation. Pharm Res 2007, 24 (9), 1759-71. 238. Donnenberg, V. S.; Landreneau, R. J.; Donnenberg, A. D., Tumorigenic stem and progenitor cells: implications for the therapeutic index of anti-cancer agents. J Control Release 2007, 122 (3), 385-91. 239. Gehling, U. M.; Ergün, S.; Schumacher, U.; Wagener, C.; Pantel, K.; Otte, M.; Schuch, G.; Schafhausen, P.; Mende, T.; Kilic, N.; Kluge, K.; Schäfer, B.; Hossfeld, D. K.; Fiedler, W., In vitro differentiation of endothelial cells from AC133-positive progenitor cells. Blood 2000, 95 (10), 3106-12. 240. Adini, A.; Adini, I.; Ghosh, K.; Benny, O.; Pravda, E.; Hu, R.; Luyindula, D.; D'Amato, R. J., The stem cell marker prominin-1/CD133 interacts with vascular endothelial growth factor and potentiates its action. Angiogenesis 2013, 16 (2), 405-16. 241. Swaminathan, S. K.; Roger, E.; Toti, U.; Niu, L.; Ohlfest, J. R.; Panyam, J., CD133- targeted paclitaxel delivery inhibits local tumor recurrence in a mouse model of breast cancer. J Control Release 2013, 171 (3), 280-7. 242. Swaminathan, S. K.; Niu, L.; Waldron, N.; Kalscheuer, S.; Zellmer, D. M.; Olin, M. R.; Ohlfest, J. R.; Vallera, D. A.; Panyam, J., Identification and characterization of a novel scFv recognizing human and mouse CD133. Drug Deliv Transl Res 2013, 3 (2), 143- 51. 243. Skubitz, A. P.; Taras, E. P.; Boylan, K. L.; Waldron, N. N.; Oh, S.; Panoskaltsis- Mortari, A.; Vallera, D. A., Targeting CD133 in an in vivo ovarian cancer model reduces ovarian cancer progression. Gynecol Oncol 2013, 130 (3), 579-87. 244. Ohlfest, J. R.; Zellmer, D. M.; Panyam, J.; Swaminathan, S. K.; Oh, S.; Waldron, N. N.; Toma, S.; Vallera, D. A., Immunotoxin targeting CD133(+) breast carcinoma cells. Drug Deliv Transl Res 2013, 3 (2), 195-204.

245

245. Zhao, L.; Yang, Y.; Zhou, P.; Ma, H.; Zhao, X.; He, X.; Wang, T.; Zhang, J.; Liu, Y.; Zhang, T., Targeting CD133high Colorectal Cancer Cells In Vitro and In Vivo With an Asymmetric Bispecific Antibody. J Immunother 2015, 38 (6), 217-28. 246. Huang, J.; Li, C.; Wang, Y.; Lv, H.; Guo, Y.; Dai, H.; Wicha, M. S.; Chang, A. E.; Li, Q., Cytokine-induced killer (CIK) cells bound with anti-CD3/anti-CD133 bispecific antibodies target CD133(high) cancer stem cells in vitro and in vivo. Clin Immunol 2013, 149 (1), 156-68. 247. Zhu, X.; Prasad, S.; Gaedicke, S.; Hettich, M.; Firat, E.; Niedermann, G., Patient- derived glioblastoma stem cells are killed by CD133-specific CAR T cells but induce the T cell aging marker CD57. Oncotarget 2015, 6 (1), 171-84. 248. Feng, K. C.; Guo, Y. L.; Liu, Y.; Dai, H. R.; Wang, Y.; Lv, H. Y.; Huang, J. H.; Yang, Q. M.; Han, W. D., Cocktail treatment with EGFR-specific and CD133-specific chimeric antigen receptor-modified T cells in a patient with advanced cholangiocarcinoma. J Hematol Oncol 2017, 10 (1), 4. 249. Schmohl, J. U.; Gleason, M. K.; Dougherty, P. R.; Miller, J. S.; Vallera, D. A., Heterodimeric Bispecific Single Chain Variable Fragments (scFv) Killer Engagers (BiKEs) Enhance NK-cell Activity Against CD133+ Colorectal Cancer Cells. Target Oncol 2016, 11 (3), 353-61. 250. Vallera, D. A.; Felices, M.; McElmurry, R.; McCullar, V.; Zhou, X.; Schmohl, J. U.; Zhang, B.; Lenvik, A. J.; Panoskaltsis-Mortari, A.; Verneris, M. R.; Tolar, J.; Cooley, S.; Weisdorf, D. J.; Blazar, B. R.; Miller, J. S., IL15 Trispecific Killer Engagers (TriKE) Make Natural Killer Cells Specific to CD33+ Targets While Also Inducing Persistence, In Vivo Expansion, and Enhanced Function. Clin Cancer Res 2016, 22 (14), 3440-50. 251. Siegel, R. L.; Miller, K. D.; Jemal, A., Cancer Statistics, 2017. CA Cancer J Clin 2017, 67 (1), 7-30. 252. Wright, M. H.; Calcagno, A. M.; Salcido, C. D.; Carlson, M. D.; Ambudkar, S. V.; Varticovski, L., Brca1 breast tumors contain distinct CD44+/CD24- and CD133+ cells with cancer stem cell characteristics. Breast Cancer Res 2008, 10 (1), R10. 253. Dean, M., Cancer stem cells: redefining the paradigm of cancer treatment strategies. Mol Interv 2006, 6 (3), 140-8. 254. Liu, T. J.; Sun, B. C.; Zhao, X. L.; Zhao, X. M.; Sun, T.; Gu, Q.; Yao, Z.; Dong, X. Y.; Zhao, N.; Liu, N., CD133+ cells with cancer stem cell characteristics associates with vasculogenic mimicry in triple-negative breast cancer. Oncogene 2013, 32 (5), 544-53. 255. Sun, T.; Zhao, N.; Zhao, X. L.; Gu, Q.; Zhang, S. W.; Che, N.; Wang, X. H.; Du, J.; Liu, Y. X.; Sun, B. C., Expression and functional significance of Twist1 in hepatocellular carcinoma: its role in vasculogenic mimicry. Hepatology 2010, 51 (2), 545- 56. 256. Aomatsu, N.; Yashiro, M.; Kashiwagi, S.; Takashima, T.; Ishikawa, T.; Ohsawa, M.; Wakasa, K.; Hirakawa, K., CD133 is a useful surrogate marker for predicting chemosensitivity to neoadjuvant chemotherapy in breast cancer. PLoS One 2012, 7 (9), e45865.

246

257. Raso, V.; Griffin, T., Hybrid antibodies with dual specificity for the delivery of ricin to immunoglobulin-bearing target cells. Cancer Res 1981, 41 (6), 2073-8. 258. Kriangkum, J.; Xu, B.; Nagata, L. P.; Fulton, R. E.; Suresh, M. R., Bispecific and bifunctional single chain recombinant antibodies. Biomol Eng 2001, 18 (2), 31-40. 259. Zhu, Z.; Zapata, G.; Shalaby, R.; Snedecor, B.; Chen, H.; Carter, P., High level secretion of a humanized bispecific diabody from Escherichia coli. Biotechnology (N Y) 1996, 14 (2), 192-6. 260. Takemura, S.; Asano, R.; Tsumoto, K.; Ebara, S.; Sakurai, N.; Katayose, Y.; Kodama, H.; Yoshida, H.; Suzuki, M.; Imai, K.; Matsuno, S.; Kudo, T.; Kumagai, I., Construction of a diabody (small recombinant bispecific antibody) using a refolding system. Protein Eng 2000, 13 (8), 583-8. 261. Asano, R.; Kumagai, T.; Nagai, K.; Taki, S.; Shimomura, I.; Arai, K.; Ogata, H.; Okada, M.; Hayasaka, F.; Sanada, H.; Nakanishi, T.; Karvonen, T.; Hayashi, H.; Katayose, Y.; Unno, M.; Kudo, T.; Umetsu, M.; Kumagai, I., Domain order of a bispecific diabody dramatically enhances its antitumor activity beyond structural format conversion: the case of the hEx3 diabody. Protein Eng Des Sel 2013, 26 (5), 359-67. 262. Asano, R.; Sone, Y.; Makabe, K.; Tsumoto, K.; Hayashi, H.; Katayose, Y.; Unno, M.; Kudo, T.; Kumagai, I., Humanization of the bispecific epidermal growth factor receptor x CD3 diabody and its efficacy as a potential clinical reagent. Clin Cancer Res 2006, 12 (13), 4036-42. 263. Helppolainen, S. H.; Nurminen, K. P.; Määttä, J. A.; Halling, K. K.; Slotte, J. P.; Huhtala, T.; Liimatainen, T.; Ylä-Herttuala, S.; Airenne, K. J.; Närvänen, A.; Jänis, J.; Vainiotalo, P.; Valjakka, J.; Kulomaa, M. S.; Nordlund, H. R., Rhizavidin from Rhizobium etli: the first natural dimer in the avidin protein family. Biochem J 2007, 405 (3), 397-405. 264. Sakahara, H.; Saga, T., Avidin-biotin system for delivery of diagnostic agents. Adv Drug Deliv Rev 1999, 37 (1-3), 89-101. 265. Aslan, F. M.; Yu, Y.; Vajda, S.; Mohr, S. C.; Cantor, C. R., Engineering a novel, stable dimeric streptavidin with lower isoelectric point. J Biotechnol 2007, 128 (2), 213- 25. 266. Meir, A.; Helppolainen, S. H.; Podoly, E.; Nordlund, H. R.; Hytönen, V. P.; Määttä, J. A.; Wilchek, M.; Bayer, E. A.; Kulomaa, M. S.; Livnah, O., Crystal structure of rhizavidin: insights into the enigmatic high-affinity interaction of an innate biotin-binding protein dimer. J Mol Biol 2009, 386 (2), 379-90. 267. Lim, K. H.; Huang, H.; Pralle, A.; Park, S., Stable, high-affinity streptavidin monomer for protein labeling and monovalent biotin detection. Biotechnol Bioeng 2013, 110 (1), 57-67. 268. Barbash, I. M.; Chouraqui, P.; Baron, J.; Feinberg, M. S.; Etzion, S.; Tessone, A.; Miller, L.; Guetta, E.; Zipori, D.; Kedes, L. H.; Kloner, R. A.; Leor, J., Systemic delivery of bone marrow-derived mesenchymal stem cells to the infarcted myocardium: feasibility, cell migration, and body distribution. Circulation 2003, 108 (7), 863-8. 269. Cheng, Z.; Ou, L.; Zhou, X.; Li, F.; Jia, X.; Zhang, Y.; Liu, X.; Li, Y.; Ward, C. A.; Melo, L. G.; Kong, D., Targeted migration of mesenchymal stem cells modified with

247

CXCR4 gene to infarcted myocardium improves cardiac performance. Mol Ther 2008, 16 (3), 571-9. 270. Shi, M.; Li, J.; Liao, L.; Chen, B.; Li, B.; Chen, L.; Jia, H.; Zhao, R. C., Regulation of CXCR4 expression in human mesenchymal stem cells by cytokine treatment: role in homing efficiency in NOD/SCID mice. Haematologica 2007, 92 (7), 897-904. 271. Won, Y. W.; Patel, A. N.; Bull, D. A., Cell surface engineering to enhance mesenchymal stem cell migration toward an SDF-1 gradient. Biomaterials 2014, 35 (21), 5627-35. 272. Karp, J. M.; Leng Teo, G. S., Mesenchymal stem cell homing: the devil is in the details. Cell Stem Cell 2009, 4 (3), 206-16. 273. Rombouts, W. J.; Ploemacher, R. E., Primary murine MSC show highly efficient homing to the bone marrow but lose homing ability following culture. Leukemia 2003, 17 (1), 160-70. 274. Guo, L.; Zhou, Y.; Wang, S.; Wu, Y., Epigenetic changes of mesenchymal stem cells in three-dimensional (3D) spheroids. J Cell Mol Med 2014, 18 (10), 2009-19. 275. Li, Z.; Liu, C.; Xie, Z.; Song, P.; Zhao, R. C.; Guo, L.; Liu, Z.; Wu, Y., Epigenetic dysregulation in mesenchymal stem cell aging and spontaneous differentiation. PLoS One 2011, 6 (6), e20526. 276. Sui, B. D.; Hu, C. H.; Liu, A. Q.; Zheng, C. X.; Xuan, K.; Jin, Y., Stem cell-based bone regeneration in diseased microenvironments: Challenges and solutions. Biomaterials 2017. 277. Zheng, Y.; Huang, J.; Zhu, T.; Li, R.; Wang, Z.; Ma, F.; Zhu, J., Stem Cell Tracking Technologies for Neurological Regenerative Medicine Purposes. Stem Cells Int 2017, 2017, 2934149. 278. Kean, T. J.; Duesler, L.; Young, R. G.; Dadabayev, A.; Olenyik, A.; Penn, M.; Wagner, J.; Fink, D. J.; Caplan, A. I.; Dennis, J. E., Development of a peptide-targeted, myocardial ischemia-homing, mesenchymal stem cell. J Drug Target 2012, 20 (1), 23-32. 279. Rogozhnikov, D.; O'Brien, P. J.; Elahipanah, S.; Yousaf, M. N., Scaffold Free Bio- orthogonal Assembly of 3-Dimensional Cardiac Tissue via Cell Surface Engineering. Sci Rep 2016, 6, 39806. 280. Gong, P.; Zheng, W.; Huang, Z.; Zhang, W.; Xiao, D.; Jiang, X., A Strategy for the Construction of Controlled, Three-Dimensional, Multilayered, Tissue-Like Structures. Advanced Functional Materials 2013, 23 (1), 42-46. 281. Ko, I. K.; Kean, T. J.; Dennis, J. E., Targeting mesenchymal stem cells to activated endothelial cells. Biomaterials 2009, 30 (22), 3702-10. 282. Cheng, H.; Byrska-Bishop, M.; Zhang, C. T.; Kastrup, C. J.; Hwang, N. S.; Tai, A. K.; Lee, W. W.; Xu, X.; Nahrendorf, M.; Langer, R.; Anderson, D. G., Stem cell membrane engineering for cell rolling using peptide conjugation and tuning of cell-selectin interaction kinetics. Biomaterials 2012, 33 (20), 5004-12. 283. Pulsipher, A.; Dutta, D.; Luo, W.; Yousaf, M. N., Cell-surface engineering by a conjugation-and-release approach based on the formation and cleavage of oxime linkages

248

upon mild electrochemical oxidation and reduction. Angew Chem Int Ed Engl 2014, 53 (36), 9487-92. 284. Du, J.; Yarema, K. J., Carbohydrate engineered cells for regenerative medicine. Adv Drug Deliv Rev 2010, 62 (7-8), 671-82. 285. Merzaban, J. S.; Imitola, J.; Starossom, S. C.; Zhu, B.; Wang, Y.; Lee, J.; Ali, A. J.; Olah, M.; Abuelela, A. F.; Khoury, S. J.; Sackstein, R., Cell surface glycan engineering of neural stem cells augments neurotropism and improves recovery in a murine model of multiple sclerosis. Glycobiology 2015, 25 (12), 1392-409. 286. White, S. H.; von Heijne, G., Transmembrane helices before, during, and after insertion. Curr Opin Struct Biol 2005, 15 (4), 378-86. 287. Simons, K.; Sampaio, J. L., Membrane organization and lipid rafts. Cold Spring Harb Perspect Biol 2011, 3 (10), a004697. 288. Jeong, J. H.; Schmidt, J. J.; Kohman, R. E.; Zill, A. T.; DeVolder, R. J.; Smith, C. E.; Lai, M. H.; Shkumatov, A.; Jensen, T. W.; Schook, L. G.; Zimmerman, S. C.; Kong, H., Leukocyte-mimicking stem cell delivery via in situ coating of cells with a bioactive hyperbranched polyglycerol. J Am Chem Soc 2013, 135 (24), 8770-3. 289. Hamdy, N.; Goustin, A. S.; Desaulniers, J. P.; Li, M.; Chow, C. S.; Al-Katib, A., Sheep red blood cells armed with anti-CD20 single-chain variable fragments (scFvs) fused to a glycosylphosphatidylinositol (GPI) anchor: a strategy to target CD20-positive tumor cells. J Immunol Methods 2005, 297 (1-2), 109-24. 290. Lu, L.; Gao, J.; Guo, Z., Labeling Cell Surface GPIs and GPI-Anchored Proteins through Metabolic Engineering with Artificial Inositol Derivatives. Angew Chem Int Ed Engl 2015, 54 (33), 9679-82. 291. de Kruif, J.; Tijmensen, M.; Goldsein, J.; Logtenberg, T., Recombinant lipid-tagged antibody fragments as functional cell-surface receptors. Nat Med 2000, 6 (2), 223-7. 292. Altman, M. O.; Chang, Y. M.; Xiong, X.; Tan, W., Modifying cellular properties using artificial aptamer-lipid receptors. Sci Rep 2013, 3, 3343. 293. Xiong, X.; Liu, H.; Zhao, Z.; Altman, M. B.; Lopez-Colon, D.; Yang, C. J.; Chang, L.-J.; Liu, C.; Tan, W., DNA Aptamer-Mediated Cell Targeting. Angewandte Chemie International Edition 2013, 52 (5), 1472-1476. 294. Lim, K. S.; Lee, D. Y.; Valencia, G. M.; Won, Y. W.; Bull, D. A., Cell surface- engineering to embed targeting ligands or tracking agents on the cell membrane. Biochem Biophys Res Commun 2017, 482 (4), 1042-1047. 295. Kim, S. A.; Peacock, J. S., The use of palmitate-conjugated protein A for coating cells with artificial receptors which facilitate intercellular interactions. J Immunol Methods 1993, 158 (1), 57-65. 296. Lo, C. Y.; Antonopoulos, A.; Dell, A.; Haslam, S. M.; Lee, T.; Neelamegham, S., The use of surface immobilization of P-selectin glycoprotein ligand-1 on mesenchymal stem cells to facilitate selectin mediated cell tethering and rolling. Biomaterials 2013, 34 (33), 8213-22.

249

297. Todhunter, M. E.; Jee, N. Y.; Hughes, A. J.; Coyle, M. C.; Cerchiari, A.; Farlow, J.; Garbe, J. C.; LaBarge, M. A.; Desai, T. A.; Gartner, Z. J., Programmed synthesis of three-dimensional tissues. Nat Methods 2015, 12 (10), 975-81. 298. Selden, N. S.; Todhunter, M. E.; Jee, N. Y.; Liu, J. S.; Broaders, K. E.; Gartner, Z. J., Chemically programmed cell adhesion with membrane-anchored oligonucleotides. J Am Chem Soc 2012, 134 (2), 765-8. 299. Takeo, M.; Li, C.; Matsuda, M.; Nagai, H.; Hatanaka, W.; Yamamoto, T.; Kishimura, A.; Mori, T.; Katayama, Y., Optimum design of amphiphilic polymers bearing hydrophobic groups for both cell surface ligand presentation and intercellular cross- linking. J Biomater Sci Polym Ed 2015, 26 (6), 353-68.

250