Improving Combination Cancer Immunotherapy with a Novel, Dual-Specific Immunotherapeutic Platform That Links T Cell Costimulatory Pathways

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Doctoral Dissertations University of Connecticut Graduate School

5-8-2020

Improving Combination Cancer Immunotherapy with a Novel, Dual-Specific Immunotherapeutic Platform that Links T Cell Costimulatory Pathways

Joseph Ryan University of Connecticut - Storrs, [email protected]

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Recommended Citation Ryan, Joseph, "Improving Combination Cancer Immunotherapy with a Novel, Dual-Specific Immunotherapeutic Platform that Links T Cell Costimulatory Pathways" (2020). Doctoral Dissertations. 2517. https://opencommons.uconn.edu/dissertations/2517 Doctor of Philosophy Dissertation

Improving Combination Cancer Immunotherapy with a Novel, Dual-Specific

Immunotherapeutic Platform that Links T Cell Costimulatory Pathways

Joseph Ryan, Ph.D.

University of Connecticut, 2020

Abstract

Checkpoint-inhibiting antibodies targeting CTLA-4 and PD-1, along with costimulatory agonists, exhibit impressive anti-cancer efficacy and durable tumor regression. Despite this success, however, many patients fail to respond because of multiple immunosuppressive mechanisms used by cancer cells. Combination therapies designed to overcome this show promise, but strategies relying on multiple agents face logistical and regulatory challenges, as well as increased toxicity.

This body of work begins with an in-depth review of antibody-based immunomodulatory cancer therapy, with an emphasis on efficacy, toxicity, and their interconnectedness. Following this background, an innovative approach to overcoming fundamental flaws in the current immunotherapy paradigm is presented. Click chemistry was utilized to fuse two TNFR family costimulatory agonists (anti-CD134 and anti-CD137) into a single biologic (OrthomAb) that harnesses the immunomodulatory effects of both antibodies, essentially functioning as a “single- agent combination therapy”. OrthomAb demonstrated potent costimulatory activity in vitro and antitumor efficacy in an aggressive mouse melanoma model. OrthomAb also elicited secretion of several unique cytokines and exhibited unexpected, possibly beneficial, effects on T cell proliferation. Expanding on OrthomAb as a platform revealed novel solutions to several issues Joseph Ryan – University of Connecticut, 2020 hindering traditional combination therapy, such as the provocation of adverse events. This body of work concludes with an overview of more recent preliminary studies aiming to unravel the mechanism of OrthomAb, as well as that of unlinked anti-CD134 plus anti-CD137 dual costimulation (DCo). Using CD134/CD137 single- and double-knockout mice and additional click chemistry-derived antibody conjugates as controls, costimulatory receptor binding patterns and hybrid signaling mechanisms are explored. Bio-engineering techniques are also discussed as a means by which to alter the structures of antibody-derived conjugates in order to decrease toxicity but leave efficacy intact. These mechanistic studies serve to increase our understanding of T cell costimulation and immunomodulatory cancer therapy to inform strategies to improve upon current treatment options. In sum, this work establishes a new framework for encapsulating the benefits of combination tumor immunotherapy within a single agent, one which may improve treatment efficacy and tolerability, with the ultimate goal of saving more cancer patients while also enabling them to maintain higher quality of life.

Improving Combination Cancer Immunotherapy with a Novel, Dual-Specific

Immunotherapeutic Platform that Links T Cell Costimulatory Pathways

Joseph Ryan

B.S., University of Massachusetts Amherst, 2010

A Dissertation

Submitted in Partial Fulfillment of the

Requirements for the Degree of

Doctor of Philosophy

at the

University of Connecticut

2020

Joseph Ryan

2020

APPROVAL PAGE

Doctor of Philosophy Dissertation

Improving Combination Cancer Immunotherapy with a Novel, Dual-Specific

Immunotherapeutic Platform that Links T Cell Costimulatory Pathways

Presented by

Joseph Ryan, B.S.

Major Advisor ______Adam J. Adler

Major Advisor ______Anthony T. Vella

Associate Advisor ______Robert Clark

Associate Advisor ______Carol Pilbeam

University of Connecticut 2020

iii

Acknowledgments

I would first and foremost like to thank my mentors, Adam and Tony, for their leadership, support, and dedication. I owe much of the success of my graduate career to their strong mentoring abilities, as well as their talent and passion for science. Learning from them has helped me become not only a better researcher, but a better person as well. For this I will always be grateful.

I would like to thank Dr. Jeffrey Wasser for his guidance and friendship along the way. Jeff’s clinical insights were vital in helping to shape the trajectory of my research. His perspective as a clinician also taught me the importance of remembering to frame the science within the context of treating patients.

I would like to thank my thesis committee members for their advice and feedback, and my fellow colleagues and lab members, past and present, for helping me conduct experiments. In particular, I would like to thank Payal Mittal, who has helped me on many occasions to carry this project onward.

I also want to thank Dr. Stephen Beers, Associate Professor in Cancer Immunology and Immunotherapy at the University of Southampton, for agreeing to be an outside reader and for taking the time to offer his constructive criticisms and professional insights.

Additionally, I would like to thank the UConn School of Medicine, the Graduate School, the Department of Immunology, and the MD/PhD Program.

I would also like to thank my family and friends for always being there when I needed them, and for believing in me for as long as I can remember.

Finally, I would like to thank my wife, Julia. Our friendship began while working next to each other in the lab, and ever since then she has become my best friend, my biggest advocate, and my greatest source of strength. None of this would have been possible without her unwavering love and support.

Table of Contents

APPROVAL PAGE ...... iii

Acknowledgments ...... iv

Table of Contents ...... v

List of Tables and Figures ...... vii

Chapter 1. Improving Combination Cancer Immunotherapy ...... 1 1. Introduction ...... 1 2. Tumor immunity ...... 2 3. Checkpoint inhibitors ...... 6 4. Costimulatory agonists ...... 10 5. Adverse events ...... 14 6. Mechanistic contributions of Fc-FcR interactions ...... 19 7. Expert opinion: Is it possible to selectively increase safety while maintaining efficacy? ...... 25 8. Tables and Figures ...... 34

Chapter 2. Materials and Methods ...... 43 1. OrthomAb synthesis ...... 43 2. Mice ...... 44 3. In vitro costimulation assays ...... 45 4. Tumor immunotherapy...... 46 5. Statistics ...... 46

Chapter 3. A Novel Biologic Platform Elicits Profound T Cell Costimulatory Activity and Antitumor Immunity in Mice ...... 48 1. Introduction ...... 48 2. Results ...... 50 3. Discussion ...... 53 4. Figures ...... 54

Chapter 4. Exploring the Mechanisms of OrthomAb and Dual Costimulation Synergy ...... 69 1. Does OrthomAb involve simultaneous colocalization of CD134 and CD137? ...... 69 2. Does OrthomAb engage a hybrid signaling pathway? ...... 74 3. Figures ...... 76

Chapter 5. Developing a Next-generation OrthomAb Engineered to Limit Toxicity ...... 83 1. Generate and test a modified OrthomAb that lacks Fc domains ...... 83 2. How do OrthomAb and Fc-less OrthomAb impact intratumoral Tregs? ...... 85 3. Figures ...... 87

Chapter 6. Conclusions and Future Directions ...... 91

References ...... 96

Appendix...... 114

List of Tables and Figures

Tables:

Table 1.1: Clinical results for representative immunomodulatory mAbs used to treat cancer ..... 35 Table 1.2: Combination immunotherapy with ipilimumab (anti-CTLA-4) and nivolumab (anti- PD-1) in previously-untreated metastatic melanoma ...... 37 Table 1.3: FcR properties, expression patterns and IgG isotype binding affinities in mice and humans ...... 39 Table 1.4: Characterizing potential Fc-FcR interactions required for efficacy and/or adverse events of representative immunomodulatory targets ...... 40

Figures:

Figure 1.1: Role of Fc-FcR interactions in mediating therapeutic efficacy and adverse events of antibody-based immunomodulatory therapy (using anti-CD137 agonist as an example) ...... 41 Figure 2.1: Chemical structures of the click chemicals MTz (top) and TCO (bottom) ...... 44 Figure 3.1: Proposed mechanism of OrthomAb ...... 55 Figure 3.2: OrthomAb synthesis and purification...... 57 Figure 3.3: Optimization of purity and yield by fine-tuning click chemistry ...... 58 Figure 3.4: OrthomAb augments effector T cell activation and expansion ...... 60 Figure 3.5: OrthomAb boosts cytokine secretion by peptide-stimulated CD8 T cells ...... 62 Figure 3.6: OrthomAb boosts cytokine secretion more effectively than anti-CD134 or -CD137 63 Figure 3.7: OrthomAb potently boosts cytokine secretion by anti-CD3-stimulated T cells ...... 64 Figure 3.8: OrthomAb-treated T cells demonstrate enhanced CD4 and CD8 cytokine responses 65 Figure 3.9: OrthomAb demonstrates therapeutic efficacy in B16 melanoma ...... 67 Figure 4.1: CD134 and CD137 knockout mouse spleen and thymus characterization ...... 77 Figure 4.2: Costimulatory receptor-knockout OT-I splenocytes exhibit diminished in vitro activity and impaired response to OrthomAb treatment ...... 78 Figure 4.3: CD134/CD137 knockout cells are less responsive to DCo and to OrthomAb ...... 80 Figure 4.4: Similar functional impairments are observed with single- and double-KO mice ...... 81 Figure 4.5: CD134 and CD137 homodimers ...... 82 Figure 5.1: Preventing FcR-mediated toxicity with Fc-less OrthomAb ...... 88 Figure 5.2: Synthesis of Fc-less OrthomAb ...... 90

vii

Chapter 1. Improving Combination Cancer Immunotherapy

This work was published in Expert Opinion on Biological Therapy, volume 16,

number 5, pages 655-674, on February 24th 2016, under the title “Enhancing the

safety of antibody-based immunomodulatory cancer therapy without compromising

therapeutic benefit: Can we have our cake and eat it too?”, authored by Joseph M.

Ryan, Jeffrey S. Wasser, Adam J. Adler, and Anthony T. Vella. Some minor

modifications to the original text were made in order to accommodate updated results

from clinical trials.

1. Introduction

There is an extensive list of drugs and treatment options at the disposal of clinical oncologists.

Surgery, chemotherapy, and radiation have long been the standard of care therapies for most cancers. Nevertheless, surgery cannot eliminate highly metastatic disease, and chemotherapy and radiation cause significant side effects due to their inability to selectively target malignant cells.

Furthermore, tumors that may initially respond to therapy often develop resistance, leading to disease recurrence.

The identification of genetic mutations common to particular types of cancer has facilitated the development of targeted therapies, such as the tyrosine kinase inhibitor imatinib, which is highly effective in chronic myelogenous leukemia (CML) patients harboring the corresponding Bcr-Abl fusion gene mutant 2. Monoclonal antibodies (mAbs) are also used in

cancer treatment. These mAbs can be categorized into two groups based on their function.

Tumor-targeting mAbs function within the tumor microenvironment (TME), where they bind directly to tumor cells or stromal trophic factors 3. The vascular endothelial growth factor

(VEGF) mAb inhibitor bevacizumab, for example, interferes with survival-promoting signaling pathways important to tumor progression 4,5. The anti-CD20 mAb rituximab works by a different mechanism, first binding to tumor cells (as well as to some healthy cells) expressing surface

CD20, then engaging innate effector mechanisms for elimination 6-9. Tumor-targeting mAbs can also be chemically linked to radioactive or toxic entities so that the cytotoxic payload is selectively delivered to tumor cells without harming healthy tissue 10,11.

The second group of mAbs modulate the immune system and work by promoting tumoricidal activity in a variety of immune effector cells by lowering their thresholds for initiating antitumor responses 12. Tumors are generally considered to be non-immunogenic since they arise from the body’s own cells 13; thus these mAbs are in essence “breaking” peripheral tolerance to self. These immunomodulatory mAbs can work by either antagonizing cell surface receptors that transmit inhibitory signals (i.e., checkpoint inhibitors) or, alternatively, activating stimulatory receptors (i.e., costimulatory agonists). The net effect in both cases is an enhancement of tumoricidal immune effector cell activity. This chapter provides an extensive overview of what is known about antibody-based immunomodulatory cancer therapy, with a specific focus on therapeutic efficacy and toxicity, and then considers whether it might be possible to optimize their design with the goal of limiting adverse events without losing efficacy.

2. Tumor immunity

The immune system constantly surveys the body for potential threats, such as pathogens, with

the goal of neutralizing them to maintain homeostasis. The T lymphocyte (T cell) compartment of the adaptive immune system is particularly effective at employing this “search and destroy” strategy. Individual T cells possess exquisite specificities endowed by the expression of a unique

T cell receptor (TCR) capable of recognizing distinct peptides presented by major histocompatibility complex (MHC) molecules on the surface of cells. Due to recombination events between V, D, and J gene segments that comprise the TCR, the diversity of specificities is immense, allowing for the recognition of virtually any antigen 14,15. Given the potential for many of these TCRs to recognize self-antigens, a variety of tolerance mechanisms must be employed, operating both centrally during thymic development 16,17, as well as in the periphery 18-21, to prevent autoimmunity. Consequently, tumor cells, are more difficult to detect since the majority of their antigens overlap with those expressed in their healthy progenitors to which T cells have already been tolerized. In some cases, vaccination against these non-mutated tumor-associated antigens (TAAs) can elicit effector T cells that simultaneously mediate tumor immunity and autoimmunity 22-24. Alternatively, the genetic instability characteristic of malignant cells 25,26 gives rise to mutations in protein-coding genes, resulting in the formation of tumor-specific

(neo)-antigens (TSAs) that can be targeted by T cells without causing autoimmune disease 27,28.

Naïve T cells are activated when they encounter cognate peptides complexed to MHC molecules on the surface of antigen-presenting cells (APCs). This event, referred to as “signal

1”, is the first of three sequential signals required to program proliferation, differentiation, and survival. Dendritic cells (DCs) represent the most potent APC population, in part owing to their efficiency in capturing and processing antigens into peptide fragments suitable for MHC presentation. Upon sensing pathogen-associated molecular patterns (PAMPs), DCs are also induced to express costimulatory ligands and pro-inflammatory cytokines, delivering signals 2

and 3, respectively 29-31. Costimulation occurs in two waves. First, the immunoglobulin (Ig) superfamily molecules CD80 (B7.1) and CD86 (B7.2) on DCs ligate CD28 on the antigen- responding T cells to facilitate the initial phase of activation 32-34. Tumor necrosis factor receptor

(TNFR) superfamily members then deliver a second costimulatory wave. This process fine-tunes

T cell responses by regulating the magnitude of clonal expansion, determining which particular cytokines the T cells become capable of secreting, and dictating whether long-lived memory is established 35,36. The cytokines that constitute signal 3 further contribute to fine-tuning the T cell response 37.

In the absence of inflammation, however, steady-state DCs express only minimal amounts of costimulatory ligands and cytokines. Under these conditions, T cells encountering cognate antigens (e.g., self-antigens acquired from healthy tissues by DCs) undergo an abortive/tolerogenic response 38-40. This process not only serves to prevent autoimmunity mediated by self-reactive T cells that escape negative selection in the thymus 41, but also can dampen tumor immunity by tolerizing T cells specific for TAAs 24,42 and TSAs 43,44. A critical factor in programming effective antitumor T cell responses is the amount and variety of costimulation and cytokines accompanying DC presentation of tumor epitopes. The PAMPs that help facilitate the potent activation of DCs during infection are generally absent from tumor sites, often resulting in a tolerogenic outcome (as described above). Nevertheless, productive T cell responses to tumor antigens do occur in some cases 45-47. DC activation can be achieved when tumor cells undergoing certain forms of programmed death 48 release damage-associated molecular patterns (DAMPs), such as heat shock proteins 49, uric acid 50 and HMGB1 51, which can act in a manner analogous to that of PAMPs.

Even when tumor-reactive T cells are successfully primed, with the capacity to migrate

into tumors and kill target cells, the efficiency and overall impact of the response can be inadequate. In a process termed “immunoediting”, the most immunogenic tumor cell variants are eliminated during the initial stages of tumorigenesis, while less immunogenic tumor cells are spared and gradually expand 52. Whether T cells become tolerant of tumor antigens at the earliest stages of tumorigenesis due to a lack of DC activation, or alternatively following a period of immunoediting, clinically detectable tumors are inherently non-immunogenic. Furthermore, the resulting non-immunogenic tumor engages a variety of powerful immunosuppressive mechanisms that can thwart the activity of infiltrating effector T cells and foster a tumor- favorable microenvironment. For example, the recruitment of regulatory T cells (Tregs) 53-56 and myeloid-derived suppressor cells (MDSCs) 57 establishes an immune barrier around tumor sites, effectively protecting malignant cells from immune intrusion. Additional mechanisms include the secretion of immune-regulating cytokines such as transforming growth factor beta (TGF-)

58,59 and enzymes such as indoleamine 2,3-dioxygenase (IDO) 60, all of which are capable of altering the immune response within the TME.

An understanding of the mechanisms underlying tumor-induced immunosuppression is paramount to the development of effective cancer therapies, and as such has become a major focus of investigation; a comprehensive review on the subject is provided by Rabinovich and colleagues 61. To be effective, T cell-based immunotherapies will likely need to compensate for insufficiencies during the initial phase of T cell priming, as well as confer the capacity to overcome potent immunosuppression within the tumor microenvironment. Therefore, the most effective cancer therapies will likely consist of multiple agents targeting a variety of cancer- promoting pathways and mechanisms. Combination therapies have already begun to showcase their clinical potential, in some cases demonstrating enhanced efficacy and superiority over

standard of care monotherapies. Although combining multiple agents can cause more frequent and severe adverse events, increases in efficacy may exceed increases in toxicity, suggesting combination approaches as one possibility for improving safety without sacrificing therapeutic benefit.

3. Checkpoint inhibitors

The immune system prevents excessive inflammation or autoimmunity via the engagement of inhibitory feedback networks. A commonly used analogy equates the immune system to an automotive vehicle with the antigen-stimulated TCR representing the transmission in drive,

CD28 costimulatory receptor acting as the accelerator, the TNFR costimulators functioning as turbo boosters, and checkpoint inhibitory receptors serving as the brake.

Cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) was the first checkpoint receptor identified and is the most extensively studied. Following the initial activation of naïve T cells, in which DCs provide signal 1 (MHC-peptide) along with signal 2 in the form of B7.1 and B7.2 ligating CD28, intracellularly stored CTLA-4 is relocated to the T cell surface where it competes with CD28 for binding to B7.1 and B7.2 62, thereby helping to avoid excessive CD28-mediated stimulation. Upon ligation, CTLA-4 engages the protein phosphatases SHP2 and PP2A, which deactivate signaling proteins downstream from TCR engagement 63. The net effect is the prevention of T cell hyper-responsiveness 51,64-67.

Mice harboring a null mutation in the gene encoding CTLA-4 develop fatal lymphoproliferative disease characterized by autoreactive T cell infiltration and extensive tissue destruction 68. This dramatic phenotype results not only from the predicted effect of releasing the brakes on self-reactive T cells, but also from impairment in the function of Tregs, which

constitutively express surface CTLA-4 to maintain tolerance and suppress auto-reactivity 20,69-73.

That CTLA-4 functions on multiple cell types to maintain immune homeostasis raised the critical question of whether it could be targeted therapeutically without unleashing fatal adverse events.

Nevertheless, preclinical studies using a variety of mouse tumor models demonstrated that a blocking mAb to CTLA-4 altering the activities of both tumor-reactive effector T cells and Tregs can produce therapeutic benefit, albeit with toxicity 74-78.

This work paved the way for the development of a humanized CTLA-4 antagonist, ipilimumab 79. A decade of clinical trials culminated in an international phase III trial that led to its 2011 approval by the FDA for treating melanoma, making it one of the first immune-based biologic therapies, and the first checkpoint inhibitor, to be used clinically 80. In this study, 676 patients with late-stage melanoma were given either ipilimumab, a vaccine targeting the melanoma TAA gp100, or ipilimumab plus vaccine. Objective response rates (ORR) for ipilimumab alone and gp100 alone were 10.9% and 1.5%, respectively. Importantly, ipilimumab

(with or without vaccine) boosted median overall survival (OS) by 10 months, compared to 6.4 months for gp100 vaccination alone (Table 1.1). These encouraging results earned for ipilimumab its approval for the treatment of unresectable or metastatic melanoma.

Another checkpoint molecule, programmed cell death protein 1 (PD-1), is expressed primarily on already-activated effector T cells and regulates their activity in the periphery 81,82.

Upon binding of its ligands, PD-L1 83 or PD-L2 84, PD-1 engages phosphatases that inactivate signaling molecules downstream of the TCR to limit proliferation, survival, and cytokine production 85. PD-1 is highly expressed on CD8+ T cells residing within the TME 86. PD-L1 can be constitutively expressed by tumor cells 87,88 due to oncogenic signaling pathway aberrations

89,90 or induced in response to localized T cell secretion of cytokines (e.g., interferons) 91-93 in a

process referred to as adaptive immune resistance 94. Tumor-infiltrating myeloid cells and lymphocytes can express PD-L1, and their co-localization and interaction with PD-1-expressing cells further define PD-1-mediated activity within the TME 95,96. PD-1 also plays a role in Treg function 97, and thus, similar to CTLA-4 blockade, targeting the PD-1/PD-L axis may enhance tumoricidal capacity through effects on both effector and regulatory T cells. Indeed, preclinical testing in mouse models demonstrated that mAb-mediated disruption of PD-1/PD-L1 interaction can boost tumor immunity 98,99.

Two humanized antagonist mAbs targeting PD-1, pembrolizumab and nivolumab, have been approved after yielding significant therapeutic responses in phase III clinical trials 100-102. A double-blind phase III trial of 418 patients receiving either nivolumab or dacarbazine found ORR of 40.0% and 13.9%, respectively, and 1-year OS rates of 72.9% and 42.1%, respectively 103

(Table 1.1). Response to treatment has also been shown to correlate with tumor expression of

PD-L1 100. Additional clinical data show similarly encouraging therapeutic responses in patients treated with anti-PD-L1 mAb 104, and provide preliminary evidence in support of using intratumoral PD-L1 expression as a biomarker to determine likelihood of therapeutic success on a patient-to-patient basis 95,96,105,106.

Checkpoint-inhibiting biologics are now being used routinely to treat patients with malignant melanoma, and numerous ongoing clinical studies raise the likelihood that they will soon be approved for treating patients with a variety of cancers including kidney, bladder, prostate, and lung 79. Recently, nivolumab was approved for additional indications including non-small cell lung carcinoma (NSCLC) and renal cell carcinoma (RCC). Thus, in addition to the durability of treatment response, the potential for use in a number of different clinical conditions sets these mAbs apart from other oncologic agents. As shown in Table 1.1,

checkpoint inhibitors and costimulatory agonists have demonstrated efficacy in both solid tumors and hematologic malignancies 107. Particularly noteworthy is their efficacy in solid tumors, which can be especially difficult to treat due to the existence of localized immunosuppression in the TME 53-60. Intriguingly, immunomodulatory mAbs enable antitumor activities that are relatively nonspecific with respect to cancer subsets, but relatively specific in terms of preferential targeting of cancerous cells while for the most part sparing healthy cells, in essence, approaching the “holy grail” of cancer therapy.

mAbs blocking both CTLA-4 and PD-1/PD-L1, enhance tumor immunity by disrupting T cell inhibitory signaling. However, they act during distinct early (CTLA-4) and late (PD-1) phases of the anti-tumor response. Thus, the possibility is raised that a combination therapy might be superior to either agent alone. Improved response has been confirmed in mice 108, and human data obtained thus far have been encouraging. In one study the combination of nivolumab and ipilimumab given concurrently yielded objective clinical responses 109 exceeding those reported previously for either monotherapy 80,100, although direct comparison was not made.

While objective-response rates may not predict long-term benefit to patients, and survival data are needed, these early studies suggest a potential advantage of combination treatment strategies

109.

A phase III study 106 comparing nivolumab alone, ipilimumab alone, and combination of the two, in previously-untreated metastatic melanoma (major findings highlighted in Table 1.2), demonstrated greater progression-free survival (PFS) for nivolumab, alone or in combination

(both 14.0 months), compared with ipilimumab alone (3.9 months). Notably, in the context of

PD-L1-positive tumors, the addition of ipilimumab to nivolumab did not improve PFS but did increase the overall rates of grades 3/4 adverse events, from 43.5% to 68.7%. In this case it

would appear that combination therapy is not as safe as nivolumab monotherapy (Table 1.2).

However, combination therapy had greater efficacy than either monotherapy in the context of

PD-L1-negative tumors (Median PFS of 11.2 months, compared to 5.3 months and 2.8 months for nivolumab and ipilimumab, respectively). Although the advantage over nivolumab monotherapy dissipated by 16 months of treatment (not shown in Table 1.2), these data speak to the value of combined therapy regimens 106.

Although this study showed no evidence of synergy, the additive effects of combination therapy seen with PD-L1-negative tumors provides some evidence that this multi-pronged approach may offer unique advantages over single-agent therapies in some tumor types.

Nonetheless, definitive conclusions from this study regarding the value of supplementing nivolumab with ipilimumab cannot be drawn until overall survival (OS) data are obtained.

After original publication of this review article, the 3-year update of this study found that

ORR remained steady. 3-year PFS rates for ipilimumab treatment, nivolumab treatment, and nivolumab + ipilimumab treatment were 10%, 32%, and 39%, respectively. 3-year OS rates were: ipilimumab (34%), nivolumab (52%), and nivolumab + ipilimumab (58%). 3-year median

OS were: ipilimumab (19.9 months), nivolumab (37.6 months), and nivolumab + ipilimumab

(not yet reached) 110. A summary of these updated data and more can be found in the second part of Table 1.2.

4. Costimulatory agonists

Agonist mAbs targeting costimulatory receptors on antigen-primed T cells represent the second major category of immunomodulatory antibodies. Primarily targeting receptors of the TNFR superfamily that provide the second wave of signal 2, these antibodies are designed to mimic the

activity of endogenous costimulatory ligands whose availability tends to be low in the context of tumor antigen presentation. In contrast to Ig superfamily costimulatory receptors such as CD28 that modulate activity of signaling proteins located proximally to the TCR, TNFR superfamily costimulatory receptors engage various combinations of TNFR-associated factors (TRAFs) 1-6, which control several downstream signaling pathways that include NF-B and MAP kinase 35,36.

CD40 is a TNFR family member expressed on DCs that, when bound by its ligand

CD40L (CD154) expressed on cognate CD4+ helper T cells, induces expression of MHC molecules, costimulatory ligands (B7.1 and B7.2) and cytokines such as IL-12, which collectively function to boost the response of CD8+ cytotoxic T lymphocytes (CTL) 111-114. A

CD40 agonist mAb can thus activate DCs when CD4+ T cell help is unavailable and lead to robust effector T cell responsiveness and antitumor immunity 115-117.

Agonists can also directly target TNFR costimulatory receptors on T cells. For instance,

CD134 (OX40) expressed on T cells following TCR stimulation 118,119 can be ligated by OX40L

(CD252) expressed on activated, but not steady state, DCs 120 to program T cell effector differentiation, survival, and memory 119,121-123. CD134 agonist thus enables antigen-primed T cells to develop potent effector and tumoricidal capacity under otherwise tolerogenic (i.e., steady state) conditions 124-131. Similarly, T cell responsiveness and tumor immunity in mice can also be elicited with agonists to several other T cell TNFR family costimulatory receptors such as

CD137 (4-1BB) 132, glucocorticoid-induced TNFR-related protein (GITR) 133 and CD27 134.

Extensive mouse studies characterizing the therapeutic potential of TNFR agonists have fueled ongoing efforts to develop humanized therapeutics. Although clinical testing of these agents has lagged behind that of the checkpoint inhibitors by several years, initial results for costimulatory agonists have been encouraging. For instance, a phase II trial evaluating the CD40

agonist dacetuzumab for use in the treatment of relapsed diffuse large B-cell lymphoma demonstrated clinical benefit in a subset of patients 135, complementing previous data from phase

I testing of this agent in other cancers, which found only moderate toxicities associated with therapy 136-138. For example, one study demonstrated that out of 44 patients with multiple myeloma treated with dacetuzumab, adverse events of mild cytokine release syndrome, non- infectious ocular inflammation, and elevated liver enzymes were infrequent and well tolerated, with less than 10% experiencing serious toxicities 138. Additional phase I trials evaluating dacetuzumab in other cancers such as non-Hodgkin’s lymphoma (NHL) 136 and chronic lymphocytic leukemia (CLL) 137 have generated similar results.

CP-870,893, a fully-human IgG2 mAb considered to be a more potent anti-CD40 agonist, has yielded relatively encouraging efficacy data, including a phase I ORR of 20% in combination with carboplatin and paclitaxel to treat various advanced solid tumors 139 (Table 1.1) and another phase I ORR of 19% with 4 partial responses (PRs) in combination with gemcitabine to treat advanced pancreatic ductal adenocarcinoma (PDA) 140, with generally tolerable side effects. CP-

870,893 has since been licensed to Roche and is now, under the name RO7009789, undergoing phase I testing in patients with locally advanced and/or metastatic solid tumors and newly diagnosed resectable PDA.

Alternatively, a mouse mAb agonist specific for human CD134 given in a phase I trial to patients with various advanced cancers elicited objective clinical responses (regression of at least one tumor nodule) in 12 out of 30 patients 141 (Table 1.1). Although none of the patients demonstrated responses according to Response Evaluation Criteria in Solid Tumors (RECIST, tumor shrinkage of at least 30%), the fact that these results were achieved using a murine mAb that could only be given in a single course (due to the production of human anti-mouse

antibodies (HAMA) in patients) is highly encouraging as it suggests that fully humanized CD134 agonists might elicit significant tumor regression, especially if given in multiple courses. A humanized CD137 agonist urelumab has also demonstrated therapeutic activity in phase I testing

142, although liver toxicities led to the termination of phase II testing (Table 1.1). It was later determined that the toxicities that had occurred were dose-dependent, and careful dosing of the agent could avoid liver damage. Humanized agonists to other TNFR members are currently in various stages of clinical development 143-145.

Given the possibility that a variety of humanized TNFR agonists may gain FDA approval for the treatment of human cancer patients, it would be useful to consider if they might be combined to improve therapeutic efficacy, like the checkpoint inhibitors 108,109. The rationale for combining agonists targeting different TNFR family members stems from their non-identical tissue expression patterns as well as the partial (but not complete) overlap in the signaling pathways they engage. These subtle differences likely reflect the potential of each member to uniquely contribute to the fine-tuning of T cell responses needed to optimally handle particular immunogenic challenges 35,36. In a clinical setting, it might be possible to exploit this variation by combining particular TNFR agonists to tailor optimal antitumor responses 146. For instance, co-administration of agonists to CD134 and CD137 147-151 or death receptor 5 (DR5, also known as TRAIL receptor 5) plus CD40 and CD137 152 can be synergistic in programming T cell clonal expansion and effector function enabling the control of tumor growth in mice. Effective combination strategies might also involve the administration of a checkpoint inhibitor with a

TNFR agonist, as has been demonstrated with anti-CTLA-4 plus anti-CD137 153 and also with anti-PD-1 plus anti-CD134 154.

5. Adverse events

The elicitation of adverse events is a risk inherent to virtually any type of therapy. With immune- based therapies, adverse events can potentially involve several mechanisms, which vary depending on the particular nature of therapy. For example, therapeutically-administered cytokines can give rise to nonspecific, systemic immune reactivity due to their widespread sites of action, whereas other immunotherapies such as adoptive cell therapies, tumor vaccines, and immunomodulatory antibodies tend to trigger more localized tissue destruction due to their more targeted and specific immune cell activation 155. With immunomodulatory mAbs, tumoricidal effector T cells that recognize non-mutated TAAs can destroy healthy cells expressing that same

TAA. The classic example of this type of immune-related adverse event (irAE) is vitiligo, in which T cells primed to non-mutated melanocytic antigens destroy both melanoma cells and healthy melanocytes 23,156. While vitiligo may be an acceptable trade-off for clearing aggressive melanomas (and other cancer types), autoimmune disease obviously would be more problematic when treating tumors derived from vital organs.

Another mechanism leading to irAEs is the disengagement of inhibitory pathways critical for maintaining tolerance to self and immune homeostasis. For instance, since part of the overall mechanism by which ipilimumab boosts tumor immunity involves neutralizing the function of

Tregs 76,78, it might be expected that ipilimumab-treated patients would experience irAEs that would otherwise be kept in check by Treg oversight. Consistent with this prediction, in the landmark melanoma phase III clinical trial mentioned previously, 60% of ipilimumab-treated patients experienced irAEs, 10-15% of which were severe (grades 3/4) that included diarrhea, vitiligo, colitis, and endocrinopathies, as well as infusion reactions 80 (Table 1.1). Careful examination of the specific mechanism(s) involved for individual antibodies (shown for a

representative sample of mAbs in Table 1.4) can also shed light on how specific toxicities arise due to therapy. For example, because anti-CTLA-4 works, in part, by depleting Tregs and/or altering their function, the occurrence of diarrhea, colitis, and other gastrointestinal (GI) manifestations can be attributed to the abundant Treg populations located in the GI tract and their critical role in maintaining immune tolerance 157. Tissue-specific and antibody-specific adverse events are discussed in greater depth elsewhere 12.

In contrast, irAEs caused by targeting the PD-1 axis tend to be fewer in frequency and less severe 100,101,104. Early human testing revealed tolerability of adverse events in addition to impressive efficacy, with response rates ranging from 18-27% when used to treat NSCLC, RCC, and melanoma, with grades 3/4 adverse events occurring in 14% of patients 100. Adverse events observed during anti-PD-1 therapy have included hepatitis, colitis, hypophysitis, thyroiditis, pneumonitis, and vitiligo (Table 1.1). Antibodies targeting PD-L1 have demonstrated response rates and safety profiles comparable to those targeting PD-1 104. This difference in adverse event profiles, along with the fact that PD-1 blockade can be effective in ipilimumab-refractory melanoma 109, suggest that these particular checkpoint inhibitors act via distinct cellular and molecular mechanisms. PD-1/PD-L1 interactions primarily take place peripherally at sites where activated T cells interact with PD-L1/2-expressing cells (e.g., within the TME), whereas

B7/CD28/CTLA-4 interactions occur primarily in lymphoid organs 158 harboring bountiful populations of T cells, and Tregs in particular (e.g., Peyer’s patches in the lining of the small intestines). Thus, the action of mAbs targeting PD-1 are likely concentrated within the TME as opposed to anti-CTLA-4 mAbs, manifesting in a decreased likelihood of off-target effects and greater tolerability.

Combination therapies targeting CTLA-4 and PD-1 have generated positive data showing

that combining immunomodulatory mAbs might have advantages over either monotherapy, albeit with greater side effect frequency and severity. The phase 3 study discussed previously and outlined in Table 1.2 found that combination of nivolumab plus ipilimumab, compared with nivolumab alone, resulted in a greater incidence of grades 3/4 adverse events (68.7% versus

43.5%, respectively 106). The 3-year follow-up report revealed an even larger gap in severe adverse events between nivolumab + ipilimumab (59%) and nivolumab alone (21%); severe adverse events with ipilimumab alone occurred at a rate of 28% 110 (Table 1.2). There were no drug-related deaths seen with combination therapy, and most adverse events (85-100%) could be managed successfully using standardized treatment guidelines, including steroids and infliximab

106,110, but endocrine-related events were the most resistant to management. Thus, combined therapy targeting CTLA-4 and PD-1 might be advantageous in subsets of patients determined by screening for the presence of predictive biomarkers, such as tumor PD-L1 expression.

Differences among checkpoint inhibitors are also reflected in their dosing regimens

(outlined in their respective package inserts). For the treatment of melanoma, ipilimumab, for example, is given every 3 weeks for a total of four doses, at which point therapy must be stopped. On the other hand, nivolumab, with its milder side effect profile, is given every 2 weeks indefinitely, until the patient experiences either lack of clinical benefit or unacceptable toxicity.

Nivolumab can also be combined with ipilimumab, with the two agents being co-administered every 3 weeks for 4 doses, after which point the normal dosing scheme of nivolumab is followed.

Importantly, nivolumab is also indicated for NSCLC and RCC. Pembrolizumab, the other approved PD-1 antagonist, is currently indicated for melanoma and NSCLC, and is given every 3 weeks. For either anti-PD-1 therapy, treatment is maintained regardless of whether the tumor completely resolves or its size has stabilized. Thus, a major advantage of anti-PD-1 mAbs is

greater tolerability, making them more suitable for maintenance therapy in appropriate patient subsets.

Costimulatory agonists might be expected to elicit irAEs associated with the production of inflammatory mediators that drive T cell expansion and effector differentiation, but on the other hand also have potential toxic properties when present in large quantities systemically. For instance, CD40 ligation on DCs induces secretion of IL-12 111, which facilitates beneficial tumoricidal effector T cell function 159, but when present at high systemic levels can be toxic 160.

Perhaps the most dramatic example of this type of irAE occurred during a phase I clinical trial evaluating the safety of TGN1412, a superagonist to CD28 that had been designed to activate

Tregs, but unfortunately ended in disaster when all six trial participants in the treatment group rapidly developed symptoms characteristic of cytokine release syndrome (cytokine storm involving rapid spikes in systemic TNF-, IFN-, IL-6, IL-2, IL-1 and others, as illustrated in

Figure 1.1), such as headache, nausea, diarrhea, vasodilation, hypotension, and eventually (non- fatal) multi-organ failure 161.

Several mechanisms have been suggested for cytokine release induced by TGN1412. One viewpoint implicates a toxic inflammatory response due to T cell hyper-activation mediated by excessive costimulatory receptor stimulation (depicted in Figure 1.1B, in this case using CD137 as a representative example) 162,163. Another school of thought points to excessive activation of innate effector cell populations (e.g., monocytes and NK cells) via antibody fragment crystallizable (Fc) engagement of Fc receptor (FcR) (discussed in the next section), thus triggering the massive release of pro-inflammatory cytokines 164,165 (Figure 1.1C). Although the severe symptoms elicited by TGN1412 were impossible to predict, it was already known that infusion of immune-reactivity antibodies can trigger responses resembling cytokine release

syndrome 166-168. It is likely that both mechanisms were, at least to some extent, involved in mediating toxicity in these patients. Evidence supporting the latter assertion comes from recent work describing contributions of stimulation-induced FcR signaling to the induction of pro- inflammatory cytokines 169,170, in addition to the suggested role of pro-inflammatory M1 macrophages in mediating immunotherapy-associated toxicity 171.

In the case of the anti-CD137 agonist urelumab, phase II testing had to be terminated due to unanticipated severe toxicity in a substantial portion of patients. Grade 4 hepatitis was the most serious adverse event, although additional toxicities were commonly noted, including fatigue, rash, diarrhea, and neutropenia (Table 1.1). These toxicities may have been related in part to the production of pro-inflammatory cytokines, such as types I and II interferons (IFN) and tumor necrosis factor alpha (TNF-) 107,142. These results were perhaps not entirely surprising since mouse studies have demonstrated that CD137 agonist administered chronically or at high dosage can induce immunologic dysfunction leading to organ-specific toxicities that correlate with increased CD8+ T cell infiltration into those tissues and organs 172,173. Subsequent clinical testing of CD137 agonists has utilized modified protocols with lower dosages, avoiding the dose- dependent hepatotoxicities observed previously 143.

During initial phase I clinical testing of a CD134 agonist for the treatment of various advanced cancers, including melanoma, RCC, squamous cell carcinoma (SCC) of the urethra, prostate cancer, and cholangiocarcinoma, fewer irAEs occurred and an acceptable toxicity profile was observed 141. 12 out of 30 patients had regression of at least one tumor nodule, and in an additional 6 patients there were no changes in target lesion measurements (Table 1.1); however none of the patients demonstrated responses according to RECIST criteria, which mandate tumor shrinkage of at least 30% to be considered positive clinical responses 141.

Differences in adverse events seen with anti-CD134 versus anti-CD137 may in part be attributed to the more widespread expression pattern of CD137 that encompasses not only activated T cells and Tregs but also several innate cell types such as natural killer (NK) cells and DCs 174-176, in contrast to CD134, whose expression appears to be more restricted to T cell subsets.

Management of irAEs should be guided by the severity of symptoms and typically involves early detection, temporary cessation of therapy, careful monitoring, supportive care such as oral hydration, and tailored symptomatic relief. For more severe irAEs, immunosuppressive drugs such as corticosteroids are often successful in mitigating symptoms, and infliximab (which neutralizes TNF-) can be helpful in managing cytokine release syndrome. Additionally, there are clinical algorithms to aid in determining the appropriate strategy to best manage irAEs 107,155,177,178. As mentioned previously, symptomatic relief using these agents has been shown not to negatively impact treatment efficacy, which substantially enhances the clinical utility of immunomodulatory mAbs.

6. Mechanistic contributions of Fc-FcR interactions

An understanding of the structural features of immunomodulatory mAbs illuminates their efficacy and adverse event profiles. Such mAbs generally are IgG isotypes and thus share a common structure composed of two identical, variable fragment antigen-binding (Fab) domains that confer target specificity, as well as a single, non-variable Fc domain corresponding to the particular IgG subtype (1-4 in human; 1, 2a, 2b and 3 in mouse). The Fc domain can bind FcRs on the surface of innate immune effector cells (macrophages, DCs, NK cells, etc.) and B cells.

Depending on cell type and environmental context, Fc binding to surface FcR will engage signaling pathways in the FcR-bearing cell and help shape functional responses. For example,

interaction of macrophage FcR with the Fc domains present on an IgG-coated cell can induce that macrophage to initiate effector functions such as antibody-dependent cell-mediated cytotoxicity (ADCC) and antibody-dependent cell-mediated phagocytosis (ADCP) 6-9,179. Fc-FcR interaction thus serves as a homing signal to direct immune effector mechanisms to a specific target, effectively bridging adaptive (e.g., B cell-generated IgG) and innate (e.g., phagocytosis) immunity and enabling a number of important biological activities 180.

The canonical FcRs belong to the Ig superfamily and can either transmit an activating signal (FcRI, IIA, IIC, IIIA and IIIB in human; FcRI, III and IV in mouse) or alternatively an inhibitory signal (FcRIIB in both human and mouse). The different IgG subtypes possess variable affinities for specific FcRs and thus differ in the balance of activating versus inhibitory signals they transmit into FcR-expressing cells 9. Table 1.3 provides a summary of IgG-FcR interactions relevant to immunomodulatory mAb-based therapy. Due to the fact that human

FcRIIC (expressed in only 20% of patients) and FcRIIIB (a GPI-linked receptor mainly restricted to neutrophils) have not been well characterized 181, they have been left out of Table

1.3 and will not be considered further. Similarly, human IgG3, which is not used therapeutically due to relative instability and immunogenicity 181, and mouse IgG3, which does not interact appreciably with FcRs 181,182, are also excluded from Table 1.3 and from further discussion.

FcRs can be either activating or inhibitory, as determined mainly by their intracellular signaling components. Activating receptors contain intracellular immunoreceptor tyrosine-based activation motifs (ITAMs) which transduce stimulatory signals to the receptor-bearing cell when the extracellular portion of the receptor is ligated. Conversely, inhibitory receptors contain immunoreceptor tyrosine-based inhibitory motifs (ITIMs), which transduce suppressive signals when bound by ligand 179 (Table 1.3). The opposing nature of the activating and inhibitory

FcRs allows for fine-tuning of FcR-mediated immune responses based on the summation of stimulatory and suppressive inputs 183 (see Figure 1.1). The immune-regulating activities mediated by FcRs have been reviewed elsewhere 179.

Recently, it was found that inhibitory ITAM (ITAMi) signaling, in the context of low- valency receptor binding 184, such as that occurring with unbound, soluble IgG (Figure 1.1F), represents another source of FcR-mediated inputs 185. ITAMi signaling after FcRI (an activating receptor) binding by immune complexes has been shown, for example, to attenuate IFN- signaling and induce the secretion of immunosuppressive IL-10 170. The size of immune complexes seems to be an important factor in determining whether FcR signaling generates a pro- or anti-inflammatory response 169, with larger complexes generally triggering pro- inflammatory cytokine activity (Figure 1.1E) and smaller immune complexes (and soluble, monomeric IgG) appearing to promote anti-inflammatory conditions (Figure 1.1F) . This phenomenon likely accounts for the clinical benefits of IVIG therapy in treating patients with rheumatoid arthritis 186, idiopathic thrombocytopenic purpura (ITP) 187, and other autoimmune disorders 188,189. Our understanding of Fc-FcR interactions and their involvements in numerous biological processes, however, is far from complete, and their complexities are only now beginning to be unraveled. Overviews of Fc-FcR interactions and their role in mAb-based cancer therapy (specifically, their contributions to treatment efficacy) are available 8,9,181,190-192.

The role of FcR-mediated interactions in the function of cytotoxic mAbs such as rituximab arises predictably from the involvement of innate effector cells in their mechanisms of cellular elimination 193-196, but defies straightforward prediction in the case of immunomodulatory mAbs. Since checkpoint inhibitors disrupt inhibitory ligand-receptor interactions, the involvement of FcR would not seem necessary, for instance, to prevent CTLA-4

from disrupting B7.1/B7.2 interaction with CD28 during T cell priming in draining lymph nodes.

However, the potency of ipilimumab was found to depend on intratumoral depletion of Tregs 197 due to their constitutive expression of the CTLA-4. Depletion was shown to depend on activating

FcRIV, suggesting macrophage-mediated ADCC as the driving mechanism 78,198,199 (Table 1.4).

The story is further complicated by the fact that ADCC may not be the only mechanism of Treg depletion. There is evidence that Tregs possess a degree of plasticity and under certain circumstances can undergo a phenotypic conversion, in which they lose their suppressive properties and gain effector functionality 200. CD134 agonists were shown to inhibit de novo

Treg induction, expansion, and suppressive function 201, in addition to their ability to promote effector CD4+ and CD8+ T cell proliferation 126,129. Similarly, GITR agonism was shown to downregulate Treg-specific transcription factors and cytokines (with complete loss of Foxp3 expression) and upregulate T-bet and Eomesodermin (Eomes) 202. More recent evidence suggests that costimulation with CD134 plus CD137 agonists can induce Tregs to adopt a cytotoxic CD4+ effector phenotype, expressing Eomes, Granzyme B (GzmB), and IFN-, while retaining Foxp3 expression 203. Additionally, CD137 costimulated Foxp3+ Tregs that express Eomes and GzmB can kill tumor target cells 204. Thus, it appears that immunomodulatory mAb therapy can exploit

Treg plasticity to reverse tumor-mediated immunosuppression and add to the overall effector T cell response (Table 1.4).

Costimulatory signaling by TNFR family members is initiated under physiological conditions when they undergo trimerization upon binding their natural ligands; however, mAbs can only bind a target bivalently (Figure 1.1A). Thus, generally speaking, costimulatory agonists cannot on their own induce costimulation. Nevertheless, FcR-mediated, mAb-induced clustering of receptors facilitates the formation of higher order signaling complexes capable of initiating

costimulation (Figure 1.1B) and appears to be required for the efficacy of at least some agonists.

Since engagement of activating FcR on DCs enhances their antigen presentation and costimulatory capacity 205,206, one might predict that activating FcR would be the most potent in facilitating therapeutic effects of costimulatory agonists. To the contrary, activity of the proapoptotic receptor agonists (PARA) targeting death receptor (DR) 4, DR5, and CD95 (Fas) was found to depend on either activating or inhibitory FcR, and in some contexts, inhibitory

FcRIIB was shown to be sufficient in mediating this activity 207. Similar FcR requirements were later demonstrated for anti-CD40 207-209, thus extending the finding to non-apoptosis-inducing costimulatory TNFR agonists (Table 1.4). These observations suggested a mechanism whereby

FcRIIB engagement on nearby FcR-expressing cells by TNFR-bound agonist mAbs induces clustering of TNFRs, thus enabling sufficient induction of costimulatory signaling (Figure 1.1

B). This proposed model was further supported by the discovery that efficacy did not depend on

FcR-dependent signaling in the accessory cell that expresses it 210. Thus, FcR appears to facilitate agonist-induced costimulation through receptor clustering.

White and colleagues showed that CD40, CD28, and CD137 agonists containing a subdomain from the Fc hinge region of the B isoform of human IgG2 can function independently of Fc-FcR interactions, retaining biological effects even after enzymatic removal of antibody Fc domains 211. The authors proposed that the constrained disulfide hinge configuration facilitates uniquely compact divalent receptor clustering and thereby the induction of costimulatory signaling. On the other hand, activating FcR are required to enable other TNFR agonists, such as

GITR 199, CD27 212 and CD134 213, to deplete intratumoral Tregs (as with anti-CTLA-4 mAbs

78,198,199), implicating innate effector mechanisms (reviewed in 190 and shown in Table 1.4).

Whether activating or inhibitory FcR are involved in the mechanism(s) underlying

immunomodulatory agonist-induced boosting of initial antigen-priming in lymphoid organs, however, remains to be determined in vivo. Interestingly, the therapeutic activity of CD137 agonist in a mouse lymphoma model was actually enhanced in the absence of activating FcRIII

214. This is a surprising finding, particularly in light of earlier work demonstrating FcR- dependent CD137 induction on NK cells 215, whose tumoricidal function is well known to be engaged by CD137 agonist 174. As such, the outcome of FcR-mediated events occurring following administration of CD137 agonist can vary in a context-dependent manner.

More recently, Dahan et. al., described the Fc-FcR interactions involved in the targeting of the PD-1/PD-L1 axis using a variety of antagonist mAbs 216. This study revealed that antagonistic anti-PD-1 mAbs mediate biological activity in a manner that is not dependent on

FcR interaction. As with anti-CD137 agonist 214, engagement of activating FcR leads to a decrease in efficacy (Table 1.4). This inhibition seems to be mediated by FcR-induced ADCC directed toward T cells expressing PD-1, depleting the cells intended to be activated. An additional proposed mechanism of FcR-related diminution of efficacy implicates FcRIIB- induced clustering and consequent stimulation (as with TNFR agonists), in essence converting the intended blockade of PD-1 into agonistic PD-1 stimulation 216.

The same study uncovered entirely different FcR-dependent mechanisms at work in mAbs targeting PD-L1, which require the presence of activating FcR-expressing cells for optimal efficacy. These findings suggest that ADCC-mediated depletion of PD-L1-expressing myeloid cells within the TME is important for the efficacy of PD-L1-targeted immunomodulatory therapy (Table 1.4). Furthermore, this mechanism likely synergizes with the

FcR-independent disruption of PD-1/PD-L signaling facilitated by the antagonistic mAbs 106,110.

These data are in agreement with previous work showing that immunosuppressive myeloid cell

subsets, such as MDSCs 57, can foster a pro-cancer environment barricading the tumor from immune intervention.

The complexities of Fc-FcR interactions and the roles they play in mediating the activity of immunomodulatory antibodies is an area of active investigation and has been reviewed extensively elsewhere 169,179,183,217. Additionally, Offringa and Glennie provide in a Cancer Cell preview 218 to Dahan et. al.’s report 216 a concise overview of Fc-FcR roles in immunomodulatory therapy that includes those just uncovered for anti-PD-1 and anti-PD-L1 antagonists.

7. Expert opinion: Is it possible to selectively increase safety while maintaining

efficacy?

Modulation of the immune system with checkpoint inhibitors and costimulatory agonists has emerged as a highly promising approach to cancer therapy. Improved durability and rates of response, more tolerable side effect profiles and extensive clinical applicability (in both solid and liquid tumors) set immunomodulatory mAbs apart from previous generations of cancer therapeutics. A growing body of evidence supports the notion that immunomodulatory agents will soon become standard first-line therapies. Table 1.1 summarizes the current development status for representative mAbs and lists for each phase of clinical testing specific conditions/indications in which they are being evaluated. Data on PFS, OS, and best overall response (BOR) rates are essential to evaluate different treatments. Additionally, although rates of grades 3/4 side effects are included in clinical trials and can be used as an indirect measure of quality of life (QOL), direct assessment will be of great value moving forward.

Evidence has shown that the efficacy and adverse event profile of a given agent can vary

significantly from patient to patient. The identification of biomarkers to predict patient likelihood of response and the potential of treatment toxicity is essential to the design of patient-specific treatment strategies, as well as to the proper clinical testing of these agents. Importantly, cancer patients must be screened to assess their eligibility, since inclusion in clinical trials of patients unable to respond can dilute overall efficacy determined by the study and potentially mask the true clinical potency of new agents being developed 157. One potential biomarker identified for ipilimumab response is the cancer/testis antigen NY-ESO-1, which is expressed normally in the testis and placenta, as well as aberrantly in a subset of advanced melanomas. It was found that

NY-ESO-1 seropositivity, and to greater extent the existence of NY-ESO-1 specific CD8+ T cells in the periphery, correlates positively with clinical responsiveness to ipilimumab 219. It was also found that patients with lactate dehydrogenase levels exceeding twice the upper limit of normal were far less likely to benefit from ipilimumab therapy in the long-term 220. Moreover, recent evidence has demonstrated potential value in using PD-L1 expression as a biomarker to determine the likelihood of patient response to PD-1 antagonism and the likelihood of enhanced clinical benefit from supplementing anti-PD-1 with additional therapeutics in combination 106,110

(Table 1.2). Updated results from clinical trials, however, demonstrated that PD-L1 expression may not be a useful marker for predicting patient response. On the other hand, combination therapies may be beneficial in patients with BRAF mutations (Table 1.2), and several other potential biomarkers showed some evidence of predictive value 110.

Interestingly, it was recently shown that gut microbiota composition can influence the efficacy of anti-CTLA-4 therapy. Specifically, the gut microbiota is required for antitumor responses with the anti-CTLA-4 mAb 9D9 in multiple mouse models of melanoma, sarcoma, and colon cancer. Data also showed that the microbiota was necessary for mAb-induced

activation of effector CD4+ T cells in the spleen 221. These findings align with previous knowledge that Tregs are abundant in the GI tract. The identification of individual bacterial species associated with anti-CTLA-4 efficacy suggested that their presence and relative abundance in a patient’s gut microbiota could serve as a biomarker to predict likelihood of treatment response. Furthermore, feces harvested from ipilimumab-treated patients were found to differ in microbiota composition, which gradually shifted in favor of the efficacy-enhancing species. Intriguingly, fecal microbial transplants into tumor-inoculated mice with patient feces samples containing significant numbers of these microbes helped to generate effective antitumor responses, whereas transplantation of feces containing fewer of these specific microbes were unable to respond 221.

There also appears to be a genetic basis for the likelihood of beneficial response to immunomodulatory therapy. Genetic analysis of 64 ipilimumab-treated melanoma patients uncovered a correlation between mutational load and clinical benefit and identified a neo-antigen landscape specific to tumors that are highly responsive to treatment 222. Some specific genetic mutations 223 and the presence of particular single-nucleotide polymorphisms 224 have also been shown to predict clinical response. Interestingly, the single-nucleotide polymorphisms (SNPs) that correlated with beneficial clinical response did not show any correlation with the occurrence or severity of adverse events 224, suggesting that the mechanisms underlying efficacy and toxicity do not overlap entirely and can thus be differentially targeted when designing future immunomodulatory mAbs for greater therapeutic index. This study also supports an earlier hypothesis that some mutations considered silent passengers should instead be classified as immune determinants 225 that collectively define immunogenicity and susceptibility to antitumor effector mechanisms employed by the immune system. Accordingly, genetic screening could be

employed to identify likely responders to therapy and help ensure that patients are offered only those treatments from which they are likely to benefit.

The process of selecting new immunomodulatory antibodies for clinical development also needs to be improved at the preclinical level in order to better predict their effects in humans. The use of in vitro screening assays is convenient, but results obtained must be interpreted with caution, because numerous factors such as cell culture density, microenvironment architecture, and stimulation timeframes often differ substantially from those in real patients 226. The unanticipated consequences of the TGN1412 trial, for example, was later determined to result from failure to take into consideration differences in CD28 expression patterns between humans and cynomolgus macaques 227,228. This unfortunate event has helped lead to the development of new screening techniques and safety measures, which are already being utilized in designing and testing new therapies 228. Prevention of such incidents will be essential to continued progress in this field.

The difference in response kinetics when comparing immunomodulatory mAbs to traditional cancer therapeutics is also important to consider in future clinical testing protocols.

Immunomodulatory antibodies, which function indirectly via immune system activation, can take longer to mount an attack and thus warrant adjustment to currently defined endpoints and other measures used to evaluate agents 229. The importance of this last point is illustrated in the premature halting of a phase III trial with the anti-CTLA-4 agent tremelimumab due to apparent lack of improvement in survival. However, follow-up investigation of study participants eventually revealed improvements occurring after 2 years 230, reflective of the delayed evidence of therapeutic response seen with these agents. Similarly, as discussed earlier, the absence of efficacy reported for an anti-OX40 agonist antibody despite initially promising data

demonstrates the incompatibility of traditional RECIST criteria with immunomodulatory therapies 141. In fact, even with successful therapeutic outcomes tumor shrinkage would not be expected to occur for some time after treatment is initiated. This is because tumoricidal responses induced by immunomodulatory mAbs rely on effector cell infiltration into the TME; thus, upon measurement, any tumor shrinkage would likely be difficult to detect due to lymphocytic influx localized to tumor sites. Therefore, appropriate additional criteria, such as immune cell phenotypes, frequencies, and overall abundances, both in circulation and within

TMEs, need to be incorporated for improved evaluation of clinical trials 231. Only then can we be confident that we are accurately characterizing future generations of immunomodulatory therapeutic candidates.

As mentioned earlier, the ability to selectively enhance efficacy and/or limit toxicity likely depends on the specific mechanism(s) responsible for each. There is considerable overlap in the immune effector mechanisms involved in beneficial therapeutic antitumor effects and harmful adverse events. For instance, TNF- has potent tumoricidal activity, but can be a causative factor in cachexia, insulin resistance and cytokine release syndrome 232-235. Further, initial clinical trials testing ipilimumab found a positive correlation between therapeutic responses and the prevalence and severity of adverse events 178,236,237, raising the critical question as to what extent adverse events can be limited without compromising therapeutic efficacy.

Fortunately, extensive clinical testing of ipilimumab has provided encouraging results in this regard, specifically that ipilimumab-responsive patients who develop irAEs can continue to benefit from an anti-tumor response even after pharmacologic reversal of associated symptoms with, for example, administration of corticosteroids 106,110,177. Reversal of irAEs and cytokine release syndrome without loss of efficacy was also achieved in other T cell-mediated cancer

therapies, in which inhibition of TNF- with etanercept 238 and inhibition of IL-6 signaling with tocilizumab 238,239 were effective. Alternative agents that might be useful in managing cytokine release syndrome during immunotherapy include inhibitors to MCP-1, MIP-1, IL-2R, and IL-

1R 240 (depicted in Figure 1.1).

Combinations of immunotherapies 109, as well as immunotherapies used in conjunction with traditional treatment options such as chemotherapy 241 and radiotherapy 242 have been attempted in search of treatment approaches with enhanced efficacy and improved safety profiles. Combination therapy has opened the possibility of limiting the occurrence of irAEs due to additive (and for certain combinations perhaps even synergistic) effects of multiple agents, which could allow for administration of lower doses. Although the frequency and severity of adverse events have been greater with combinations than with individual monotherapies thus far

106,110 (Table 1.2), the ability to titrate dosages could potentially avoid many adverse events directly. A detailed mechanistic understanding of how these therapeutics elicit their associated beneficial and toxic effects is crucial to designing strategies that selectively block the latter.

Ideally, these approaches will facilitate an overall advantage in favor of enhanced efficacy over adverse events. Ultimately, the benefits and risks of specific combinations will need to be addressed in future trials. Melero and colleagues recently published a comprehensive review summarizing general concepts, specific examples under development, and important considerations in the design of combination immunotherapies 243.

It seems likely that Fc-FcR interactions also play a role in mediating at least some of the adverse events elicited by immunomodulatory mAbs. For instance, target expression on therapeutically-irrelevant cell types could potentially lead to collateral damage of these cells via

ADCC or ADCP (Figure 1.1D). Thus, while ADCC/ADCP might be therapeutically beneficial

by depleting intratumoral Tregs with mAbs to CTLA-4, GITR and OX40 78,198,199,213 (Table 1.4), it might be problematic, for instance, with anti-CD137, since CD137 is expressed on a variety of cell types, some of which appear not to be involved in the antitumor response 244. Neurons, astrocytes and microglia 245, for example, are among these therapeutically-irrelevant, CD137- expressing cell types. Additionally, endothelia can express CD137 in response to inflammatory mediators 246 and in diseases such as atherosclerosis 247.

Furthermore, expression of soluble forms of some targets (e.g., CD134 and CD137) has been found in a variety of pathological conditions 248-250, raising the potential for the formation of immune complexes which can trigger inflammation (Figure 1.1E) 169 and may potentially be involved in mechanisms driving pathological immune hyper-reactivity, such as that occurring in

IgG-mediated anaphylaxis 251. Finally, surface coating of IgG on either therapeutically-relevant or -irrelevant cells could cause innate cells expressing activating FcR to release pro- inflammatory cytokines contributing to adverse events 169,252. In sum, although Fc-FcR interactions may be necessary for the full therapeutic efficacy of immunomodulatory mAbs, they might also be responsible for therapeutically-complicating adverse events through a variety of potential mechanisms. Further, these adverse events might be exacerbated by other pathologies

(e.g., underlying infection or autoimmune predisposition) from which cancer patients might be suffering. Nevertheless, seemingly contradictory evidence showing both pro- and anti- inflammatory cytokine secretion in response to FcR engagement illustrates our incomplete understanding of FcR-mediated immune functions.

Despite these gaps in understanding, Fc-FcR interactions are likely responsible for at least some of the toxicities seen with immunomodulatory mAb therapy. In such cases, preventing these interactions may help limit adverse events to increase therapeutic index and enhance

precision medicine. This notion is additionally supported by the heterogeneity of responses to

FcR-dependent mAb activity. For instance, the absence of a human homolog to the high-avidity

FcRIIB-binding of mouse IgG1 may limit efficacy of some costimulatory agonists (Table 1.3).

Furthermore, patient response heterogeneity can arise from relative levels of FcR expression and functional status, which can vary widely between tissues and cell types. For example, although most innate cells express both activating and inhibitory FcRs, NK cells are known to express only activating receptors in mice and humans (except for a recently discovered subset of NK cells expressing FcRIIB), whereas B cells only express inhibitory receptor 179. The different distributions of such cells likely explains the tissue- and organ-specific differences in overall response to therapy 12. Interestingly, it was recently suggested that in a murine model peritoneal and visceral adiposity can influence the magnitude of cytokine-mediated toxicity associated with the presence of resident M1-polarized macrophages 171. Other factors include current immune status (e.g., active responses to infection), and patient-specific differences in both FcR-mediated signaling summation patterns (i.e., activating vs. inhibitory FcR inputs) and FcR-specific avidities to various IgG isotypes (Table 1.3). Additionally, the existence of allotypic variants with different binding affinities contributes to patient response heterogeneity; so far, human

FcRIIa and FcRIIIa each have had two variants characterized 253.

Establishing FcR-independent mechanisms of immunomodulatory mAb activity is therefore a highly desirable goal. Antibody multimerization has been shown to be an effective strategy to bypass FcR requirements, enabling the preservation of anti-CD40 agonist activity in vitro and in vivo, as well as in a model of lymphoma with mice completely lacking all FcRs 254

(Table 1.4). Immunomodulatory therapy can also be optimized using mAb engineering to alter

FcR binding properties. Early studies focused on increasing binding avidity of IgG to activating

FcR, which could be accomplished using protein engineering 255,256, as well as modification to antibody glycosylation 257,258. Additionally, selective enhancement of FcRIIB binding was used to generate an anti-CD137 agonist with increased agonistic activity in vitro 259. Individual FcRs have also been shown to exhibit differential contributions to cellular functions; for example, it has been demonstrated that FcRI was largely responsible for secretion of both anti- inflammatory IL-10 260 and pro-inflammatory cytokines 261. A suggested implication of this findings was that macrophage-mediated ADCC and ADCP could potentially be uncoupled from antibody-dependent cytokine release (ADCR), a feat which was accomplished recently by

Kinder et. al., using an Fc-engineering approach to modulate cytokine release while leaving cell- killing activity intact 261. The ability to selectively fine-tune or prevent cytokine release thus opens the possibility of limiting cytokine-related adverse events without losing effector capacity and tumoricidal activity. Contrarily, in situations where the secretion of anti-inflammatory cytokines might be hindering efficacy, selective attenuation of ADCR would be advantageous.

Additionally, the human IgG2 isotype (specifically the B isoform) was shown to possess the unique ability to exhibit activity in an FcR-independent manner, likely due to an especially compact geometry and constrained disulfide hinge configuration 211. White and colleagues posited that these properties enable sufficient clustering of TNFRs to reach a signaling threshold beyond which stimulation ensues. Notably, this phenomenon was shown for agonists targeting multiple costimulatory receptors, including CD40, CD28, and CD137, and it was further demonstrated that selective mutagenesis could generate a wide range of agonistic activities, without altering receptor binding avidity (Table 1.4). That human IgG2 is capable of exerting superior agonistic activity in an FcR-independent manner potentially accounts for data from clinical trials demonstrating superior potency of the anti-CD40 agonist CP-870,893, an IgG2

isotype (Table 1.1), compared to those of other isotypes 262,263.

A greater understanding of the mechanisms behind immunomodulatory mAb therapy will be critical for the future optimization of these therapeutic agents. Importantly, the mechanisms underlying efficacy and adverse events need to be further delineated. Recent characterization of

PD-1/PD-L1-targeted therapies 216 further adds to the ever-expanding complexity of the mechanisms at work in immunomodulatory therapy, while also illustrating the importance of proper antibody isotype selection and the value of Fc domain modification in order to optimize efficacy. Much work is also needed to explain the context-dependent pro- and anti-inflammatory responses (Figure 1.1E, F) induced by FcR binding to mAb Fc domain. While many data support the idea that avoiding FcR activity will help limit adverse events, the anti-inflammatory responses to FcR signaling in certain contexts now pose the possibility that FcR engagement actually contributes negatively to therapeutic efficacy, and that circumvention of FcR interaction could lead to an enhancement of activity (perhaps even concurrently with attenuation of adverse events). Conversely, it is possible that FcR-mediated pro-inflammatory cytokine secretion contributes to overall antitumor efficacy, representing a benefit that would be lost if FcR engagement were avoided. Only with continued investigation will we be able to accurately predict how adjustments to Fc-FcR interactions will impact efficacy and toxicity. Therapeutic approaches that do not engage FcR yet retain the ability to effectively stimulate their target pathways, will potentially be capable of inducing beneficial therapeutic responses in cancer patients while sparing them from having to endure the dangerous adverse events of today’s therapies. Hence, perhaps we can have our cake and eat it too.

8. Tables and Figures

Table 1.1: Clinical results for representative immunomodulatory mAbs used to treat cancer

Checkpoint Inhibitors Costimulatory Agonists Target CTLA-4 PD-1 PD-L1 CD40 CD134 (OX40) CD137 (4-1BB) Agent* Ipilimumab Nivolumab Atezolizumab CP-870,893** MEDI6469**** Urelumab Isotype IgG1 IgG4 IgG1 IgG2 murine IgG1 IgG4 Genentech/ MedImmune/ Bristol-Myers Company Bristol-Myers Squibb Bristol-Myers Squibb Pfizer/Roche Roche AstraZeneca Squibb Highest Phase of Approved/Marketed Approved/Marketed Phase III Phase I Phase I/II Phase II Testing Marketed/ Malignant melanoma, registered Malignant melanoma - - - - NSCLC, RCC Indications Glioblastoma, Bladder, Phase III Glioblastoma, gastric, NSCLC, RCC, SCLC, breast, - - - Indications HNC, SCLC prostate NSCLC, RCC AML, CLL, breast, Gastric, MDS, DLBCL, MDS, UGC, CRC, solid Phase II esophageal, ovarian, CLL, malignant esophageal, ovarian, tumors, soft - - Indications UGC, lymphoma, melanoma follicular and tissue sarcoma brain metastases Hodgkin’s lymphomas CRC, HCC, NHL, DLBCL, Breast, DLBCL, Phase I/II solid tumors, NHL, solid Solid tumors follicular - prostate cancer, Indications hematological tumors lymphoma solid tumors malignancies Malignant melanoma, Phase I PDA, solid - CML, hepatitis C MM, MDS, CRC, HNC MM, CRC, HNC Indications tumors hematological malignancies No PR, but ORR 5.6% (3 of ORR 10.9%, phase III, tumor shrinkage ORR 40.0%, phase III, 54), phase I, stage III/IV melanoma ORR 38%, in 40% (12 of stage III/IV melanoma; vs 1.5% gp100 alone phase II, ORR 20% (6 30) following melanoma, vs 13.9% phase II study OS=10.1 months advanced PR), phase I, single dose; for dacarbazine 103 terminated due Efficacy vs 6.4 (gp100 alone) 80 NSCLC, PD- with induction of to L1+; compared chemotherapy, HAMA ORR 43.7%, phase III, hepatotoxicity; ORR 19.0%, phase III, to 13% for solid tumors 139 prevented stage III/IV melanoma newer trials stage III/IV melanoma docetaxel 264 additional doses 106 using lower 106 being given dosages 142 141*** Toxicities Cytopenias and Toxicities generally Generally, more similar to those Well-tolerated, liver Fatigue (81%) immune-related; rash, tolerable than seen with anti- brief grade 3 inflammation most common; Adverse colitis, diarrhea, ipilimumab; fatigue, PD-1; grades lymphopenia, (elevated does-limiting Events hepatotoxicity, rash, diarrhea, pruritis, 3/4 adverse fatigue, fevers, ALT/AST), dose grade 3 CRS, endocrinopathies, pneumonitis, fever can events have chills, mild rash dependent; grade 4 TIA 139 neuropathies 80,106,265 occur 100,101,106 been observed 141*** fatigue, rash, uncommon 264 fever 142 Information on clinical trials obtained from ClinicalTrials.gov.

*Particular agents listed here are only representative; there are a number of other agents to the same and/or other targets in various stages of development.

**Pfizer’s CP-870,893 is now licensed to Roche and has been renamed RO7009789; ongoing clinical trials are listed under RO7009789.

***Efficacy and adverse events based on phase I testing of a different OX40 agonist, 9B12.

****MedImmune/AstraZeneca has recently begun recruiting for a phase I trial with a humanized anti-CD134 agonist (MEDI0562) in adults with selected advanced solid tumors

(NCT02318394).

NSCLC, non-small cell lung carcinoma; RCC, renal cell carcinoma; SCLC, small cell lung carcinoma; MDS, myelodysplastic syndromes; UGC, urogenital carcinoma; HNC, head and neck cancers; AML, acute myeloid leukemia; CLL, chronic lymphocytic leukemia; DLBCL, diffuse large B cell lymphoma; NHL, non-Hodgkin’s lymphoma; CML, chronic myeloid leukemia; CRC, colorectal cancer; MM, multiple myeloma; PDA, pancreatic ductal adenocarcinoma; CRS, cytokine release syndrome; TIA, transient ischemic attack; ORR, objective response rate; PR, partial response; HAMA, human anti-mouse antibodies.

Table 1.2: Combination immunotherapy with ipilimumab (anti-CTLA-4) and nivolumab (anti-

PD-1) in previously-untreated metastatic melanoma

Treatment* Ipilimumab Nivolumab Both ORR** 19.0% 43.7% 57.6% Median PFS (Intention-to-treat) 2.9 months 6.9 months 11.5 months Efficacy Median PFS (PD-L1-positive) 3.9 months 14.0 months 14.0 months Median PFS (PD-L1-negative) 2.8 months 5.3 months 11.2 months Adverse Rate of any adverse event 99% 99.4% 99.7% events Severe*** 55.6% 43.5% 68.7% This table represents an abbreviated version of findings from the randomized, double-blind, phase 3 study 106 deemed most important

*Number of patients per group (n) ranged from 311-316.

**Response rates determined by the investigator using Response Evaluation Criteria in Solid

Tumors (RECIST), version 1.1.

***Defined as grades 3/4 based on severity determined using the National Cancer Institute

Common Terminology Criteria for Adverse Events (CTCAE), version 4.0.

ORR, objective response rate; PFS, progression-free survival.

Recently reported 3-year update 110 on results from the clinical trial referenced above:

Treatment* Ipilimumab Nivolumab Both ORR** 19% 44% 58% 3 Year PFS Rate 10% 32% 39% 3 Year OS Rate 34% 52% 58% Efficacy 3 Year Median PFS 2.9 months 6.9 months 11.5 months 3 Year Median OS 19.9 months 37.6 months 38.2 months# 3 Year OS Rate (BRAF mut.) 37% 56% 68% 3 Year OS Rate (BRAF WT) 32% 50% 53% Adverse Rate of treatment-related irAE 86% 86% 96% events Severe*** 28% 21% 59% *Number of patients per group (n) ranged from 311-316.

**Response rates determined by the investigator using Response Evaluation Criteria in Solid

Tumors (RECIST), version 1.1.

***Defined as grades 3/4 based on severity determined using the National Cancer Institute

Common Terminology Criteria for Adverse Events (CTCAE), version 4.0.

# Median PFS not yet reached.

ORR, objective response rate; PFS, progression-free survival; OS, overall survival.

Table 1.3: FcR properties, expression patterns and IgG isotype binding affinities in mice and humans

Species Mouse Receptor FcRI FcRIII FcRIV FcRIIB Function Activating Activating Activating Inhibitory Signaling ITAM ITAM ITAM ITIM Allotype n/a n/a n/a n/a IgG1 - ++ - +++ IgG2a ++++ ++ +++ ++ IgG2b ++++ ++ ++ +++ B DC DC DC Expression Mac Mac Mac DC patterns** PMN PMN PMN NK NK NK T***

Species Human Receptor FcRI FcRIIa FcRIIIa FcRIIB

Function Activating Activating Activating Inhibitory Signaling ITAM ITAM ITAM ITIM

Allotype* n/a H131 R131 F158 V158 n/a IgG1 ++++ +++ +++ ++ +++ ++ IgG2 - ++ + - + - IgG4 ++++ ++ ++ ++ ++ ++ B DC DC Mac DC Expression Mac Mac PMN Mac patterns** PMN PMN NK PMN NK**** *Only human allotypes that have been sufficiently characterized are included. For each

receptor, the more common variant appears first.

**Low expression levels indicated by italics.

***Expressed by mouse memory CD8+ T cells.

****Expressed by a subset of human NK cells.

ITAM, immunoreceptor tyrosine-based activation motifs; ITIM, immunoreceptor tyrosine-

based inhibitory motifs; B, B cell; DC, dendritic cell; Mac, macrophage/monocyte; PMN,

polymorphonuclear cell (neutrophil); NK, NK cell; T, T cell.

Table 1.4: Characterizing potential Fc-FcR interactions required for efficacy and/or adverse

events of representative immunomodulatory targets

FcR Requirements for FcR- FcR- Biological Functions Independent Dependent Counter- Deplete/ Deplete/Alter Tumor mAb Block ligand Activate Additional mAb Class regulatory Alter Treg Myeloid Cells Depletion/ Target binding Costim comments signaling* in TME in TME Apoptosis CTLA-4 Yes Yes - Yes - - Checkpoint FcR engagement PD-1 Yes Yes - - - - Inhibitors diminishes efficacy PD-L1 Yes - - - Yes Yes**

FcRIIB- CD40 - - Yes - - Yes** dependent*** Treg depletion due CD134 to ADCC and/or - - Yes Yes - - (OX40) phenotypic conversion Costim FcRIII diminishes Agonists CD137 - - Yes Yes - - efficacy; FcRIIB- (4-1BB) dependent*** Treg depletion due to ADCC and/or GITR - - Yes Yes - - phenotypic conversion FcRIIB- DR5 - - - - - Yes dependent**** PARA CD95 FcRIIB------Yes (Fas) dependent**** Mechanisms that occur only during particular circumstances are italicized.

*Possibly FcR-independent; not yet characterized.

**Some tumors cells can express surface this target.

***Can be activating FcR-dependent and/or FcR-independent in certain contexts.

****Can be activating FcR-dependent in specific circumstances.

Fc, fragment crystallizable; FcR, Fc receptor; mAb, monoclonal antibody; Treg, regulatory

T cell; TME, tumor microenvironment; ADCC, antibody-dependent cell-mediated

cytotoxicity; PARA, pro-apoptotic receptor agonists.

Figure 1.1: Role of Fc-FcR interactions in mediating therapeutic efficacy and adverse events of antibody-based immunomodulatory therapy (using anti-CD137 agonist as an example)

Monoclonal antibodies (mAbs) bind costimulatory tumor necrosis factor receptor (TNFR) superfamily members bivalently, which is insufficient to initiate costimulatory signaling in the T cell (A) unless fragment crystallizable receptor (FcR) is present on nearby innate accessory cells to facilitate costimulatory receptor clustering (B). Clustering of activating FcR can also signal to the FcR-bearing accessory cell (C), leading to the release of pro-inflammatory cytokines (TNF-

, IL-1, IL-6, etc.), which can potentially contribute to cytokine release syndrome. Conversely, cytotoxic or phagocytic innate cells expressing activating FcR can kill therapeutically-irrelevant cells expressing the mAb target via antibody-dependent cell-mediated cytotoxicity (ADCC) or antibody-dependent cellular phagocytosis (ADCP), respectively (D). It might also be directed against the T cells undergoing costimulation (not shown), which could account for recent findings that activating FcR engagement can negatively impact efficacy in certain scenarios. The precise nature of FcR-triggered responses by accessory cells depends ultimately on a variety of factors, such as the relative ratio of activating to inhibitory FcRs engaged (not depicted here), as well as the structural/geometric context of FcR ligation; for example, large immune complexes comprised of IgG-coated soluble antigens have been shown to increase inflammatory cytokine production (E), whereas interaction with soluble, unbound IgG (i.e., under homeostatic conditions) or small immune complexes appears to suppress hyper-activation of immune cells by inducing the secretion of anti-inflammatory cytokines, such as IL-10, or by suppressing the secretion or signaling of inflammatory cytokine secretion (F). Although pro-inflammatory cytokines play a causative role in therapy-associated adverse events, their effects could also contribute to overall antitumor efficacy. This last point is an important consideration, since disruption of Fc-FcR interactions could impact both adverse events and efficacy, depending on the particular context. Worth noting is that avoiding FcR-induced inflammatory responses would not completely prevent therapy-associated adverse events, which is thought to be mediated in part through the activation of specific effector T cells themselves.

Chapter 2. Materials and Methods

1. OrthomAb synthesis

The heterobifunctional chemical linkers trans-cyclooctene-PEG4-NHS ester (TCO) and methyltetrazine-PEG5-NHS ester (MTz) (Figure 2.1, both from KeraFast) were coupled to the mAbs anti-CD137 (clone 3H3, rat IgG2a) and -CD134 (clone OX86, rat IgG1) (10 mg each, both from BioXCell) in 4 ml PBS at a linker:mAb molar ratio of 7:1 at room temperature for 1 hour.

Coupled mAbs were desalted using Amicon Ultra-4 Centrifugal Filter Units with Ultracel-10 membranes, concentrated to a volume of 1 ml each, and then clicked together by mixing followed by 1-hour incubation at room temperature. The resulting heteroconjugate (OrthomAb) was then isolated from the heterogeneous mixture of reaction products (that also included unlinked monomers and higher-order multimers) using a BioLogic DuoFlow QuadTec 10 medium-pressure liquid chromatography system (BioRad) to perform 3 successive rounds of size-exclusion chromatography with a HiPrep 16/60 Sephacryl S-300 HR column (GE

Healthcare Life Sciences). Chromatographic tracings of A280 versus time and SDS-PAGE were used to visualize species present in each fraction, and appropriate fractions were pooled for subsequent purifications. Purity of the final isolated OrthomAb heterodimer was determined using ImageJ densitometry software (NIH), and concentration was determined by Pierce BCA

Protein Assay (Thermo Fisher Scientific). An isotype control heteroconjugate was generated using similar methodology and anti-HRP (clone HRPN, IgG1) and anti-TNP (clone 2A3, rat

IgG2a) (both from BioXCell).

Figure 3.2 is an illustrated outline of OrthomAb synthesis.

Figure 3.3 shows how click reaction parameters were optimized to improve yield and purity.

Anti-CD134 and anti-CD137 homodimers were also synthesized using a similar protocol. These are depicted in Figure 4.5, but not used in experiments included in this work.

Fc-less OrthomAb was also generated using a similar protocol, except that each antibody was digested with pepsin prior to click coupling. Refer to Figure 5.2 for more details.

Figure 2.1: Chemical structures of the click chemicals MTz (top) and TCO (bottom)

2. Mice

6- to 8- week old male or female C57BL/6 (WT) mice (purchased from the Jackson Laboratory) or H2Kb-restricted, ovalbumin (OVA) epitope (257SIINFEKL264) TCR-transgenic (Tg) Rag1-/- mice on the C57BL/6 background (OT-I RagKO mice, bred and maintained in-house) were used as sources of splenocytes for in vitro cultures. 6- to 8- week old female WT mice were used for

B16-F10 tumor therapy experiments, that were performed as previously described 266. Additional mouse strains that were bred for and used in the experiments outlined in Chapters 4 and 5 include the following:

• CD134-/- mice on C57BL/6 background and on OT-I Rag-/- background

• CD137-/- mice on C57BL/6 background and on OT-I Rag-/- background

• CD134-/-CD137-/- (DKO) mice on C57BL/6 background and on OT-I Rag-/- background

Pups from TCR transgenic (Tg) breeder cages were phenotyped by performing FACS analysis on blood samples (1-2 drops) that were collected by nicking the tip of the tail. Pups from some of the other transgenic and knockout breeder cages were genotyped by PCR analysis of genomic

DNA samples prepared from small (0.5 cm) tail biopsies. B16 tumor cells in 100-200 l HANKS were injected intradermally. Procedures involving mice were conducted in a manner to ensure that discomfort, distress, pain and injury would be limited to that which is unavoidable.

Procedures including collection of blood and DNA samples from the tail were performed using sharp scissors that subject the mice to minimal amounts of pain and discomfort. Tumor- inoculated mice were euthanized when they develop tumors that reach a size of 200 mm2 or become necrotic. All mice were maintained in the UConn Health Animal Facility in accordance with National Institutes of Health and UConn Health Institutional Animal Care and Use

Committee (IACUC) guidelines.

3. In vitro costimulation assays

B6 or OT-I splenocytes (1 x 105 cells in 200 l RPMI plus 10% FBS per well in a 96-well plate) were stimulated for the indicated times with the indicated amounts of anti-CD3 mAb (clone 145-

2C11, BD Biosciences) or SIINFEKL peptide (NE BioLabs), respectively, plus OrthomAb, unlinked costimulators or control polyclonal rat IgG. Secreted cytokines in culture supernatants were measured using ELISA kits from BD Biosciences (for IFN-, IL-2 and IL-6) and R&D

Systems (for IL-17) as per the manufacturers’ instructions. Cytokine concentrations were calculated using MARS Data Analysis Software from absorbance values measured using a

CLARIOstar microplate reader (BMG LABTECH). Flow cytometry was used to measure cell proliferation (dilution of CellTrace Violet, Thermo Fisher Scientific), and induction of CD134

(OX86), CD137 (1AH2) and CD25 (PC61.5) surface expression on conventional (Foxp3neg)

CD4+ and CD8+ T cells and Foxp3+CD4+ T cells. Ghost Dyes (Tonbo Biosciences) were used to assess cell viability. Intracellular staining for Foxp3 (FJK-16s), GzmB (NGBZ) and Eomes

(Dan11mag) was performed following fixation and permeabilization using Foxp3 staining buffer

(Tonbo Biosciences). Intracellular cytokine staining was performed after 4-hour restimulation with PMA + Ionomycin (CALBIOTECH) and GolgiPlug (BD Biosciences). Antibodies were purchased from BD Biosciences, eBioscience, or Tonbo Biosciences, and data were acquired using an LSR II (BD Biosciences) or MACSQuant Analyzer 10 (Miltenyi Biotec), and analyzed using FlowJo software (FlowJo, LLC).

4. Tumor immunotherapy

B16-F10 melanoma cells (1 x 105, American Type Culture Collection) that were passaged less than 1 month were intradermally injected into the shaved back of 6-8 weeks old female C57BL/6 mice. Costimulation therapy was administered at a dose of 150 g, when tumors first became visible (day 2 or 3, when tumors were at least 1 mm x 1 mm surface area), and tumor growth monitored every 1-2 days at the indicated times. Booster dose(s) were administered as indicated.

Surface area (mm2) was calculated by multiplying the longest diameter and the diameter perpendicular to it, both measured with calipers. Area under the curve (AUC) analysis was performed previously described 267.

5. Statistics

Graphs were generated and statistical analyses performed using GraphPad Prism (GraphPad

Software, Inc.). Comparisons between two groups were performed using unpaired, two-tailed, t

tests plus Welch’s correction. Comparisons between three or more groups were performed using one-way ANOVA plus Tukey’s multiple comparison test. Comparisons between titration curves or time courses of two groups were performed using two-way ANOVA plus Sidak’s multiple comparison test. Comparisons between titration curves or time courses of three of more groups were performed using two-way ANOVA plus Tukey’s multiple comparison test. Quantitative data are expressed as mean value  SEM or SD for data sets with n≥3 or n=2, respectively.

Tumor survival curve comparisons were performed using the log-rank (Mantel-Cox) test.

Chapter 3. A Novel Biologic Platform Elicits Profound T Cell Costimulatory Activity and

Antitumor Immunity in Mice

This work was published in Cancer Immunology, Immunotherapy, published online

on January 11th 2018, under the title “A novel biologic platform elicits profound T

cell costimulatory activity and antitumor immunity in mice”, authored by Joseph M.

Ryan, Payal Mittal, Antoine Menoret, Julia Svedova, Jeffrey S. Wasser, Adam J.

Adler, and Anthony T. Vella. Some modifications to the original text were made to

accommodate additional figures and to incorporate it into the overall context of this

dissertation.

1. Introduction

Biologics that target tumor cell surface proteins are effective in treating certain cancers. For instance, the anti-CD20 mAb (rituximab) elicits ~50% response rates in non-Hodgkin's B cell lymphoma patients who previously failed chemotherapy 194,269. Nevertheless, relapse can occur due to outgrowth of resistant tumors 270, and many cancers are not amenable to treatment with these types of mAbs that target antigens expressed on both tumors and the healthy tissues from which they arise. Alternatively, immunomodulatory mAbs can target tumors indirectly by activating antitumor immune responses. Thus, although tumors express mutated proteins that give rise to neoepitopes that can be recognized by CTL 271,272, they employ a variety of immunosuppressive mechanisms to evade T cell-mediated elimination 57,273,274. For example, T

cell function can be dampened through engagement of checkpoint receptors by ligands expressed on APC 275, tumor cells or tumor-infiltrating myeloid cells 276. So far, mAb antagonists to the checkpoint molecules CTLA-4 and PD-1/PD-L1 have been approved to treat patients with melanoma and other advanced cancers 79,80,100,104, and antagonists to other checkpoint molecules such as LAG-3, VISTA, Tim-3 and TIGIT are under development 277,278. Another mechanism that contributes to ineffectual antitumor T cell responses is presentation of tumor epitopes by

APC expressing low levels of costimulatory ligands 116,117. To counter this, agonist mAbs to costimulatory TNFR superfamily members such as CD134 (OX40), CD137 (4-1BB), GITR and

CD27 133,134,279,280 have been developed that are therapeutic in pre-clinical mouse models and currently undergoing testing in human cancer clinical trials.

Combining immunomodulatory mAbs within the same class can augment therapeutic outcomes. For example, since anti-CTLA-4 and -PD-1/PD-L1 are generally thought to act during distinct early and late stages of the antitumor response, respectively 62,276,281, it is perhaps not surprising that combining the two checkpoint inhibitors boosts therapeutic response compared to either alone 106,110. We found over a decade ago that combining anti-CD134 plus -CD137 elicits robust CD8 CTL responses and tumor immunity 147,148, a result confirmed by others and in multiple systems 150,151. Importantly, this CD134 CD137 "dual costimulation" also programs

CD4 T cells to develop cytotoxic tumor cell killing potential 131, as well as deliver potent therapeutic help 266. Thus, dual costimulation induces key antitumor responses.

While cancer immunotherapy is clearly moving towards the implementation of combination therapies, there are regulatory complexities involved in approval for multi-agent clinical testing 282, as well as increased potential for adverse events 106,110,282. Although 2-drug combination therapies are being tested clinically (e.g., 106,107,110,243), and CD134 CD137 dual

costimulation is in Phase 1 (NCT02315066), combinations involving three or more agents may have even greater efficacy 150,152,283. Thus, a major limitation is the lack of novel approaches to combination therapy that avoid complex mixtures of reagents. Here, we have addressed this scientific gap by covalently linking CD134 and CD137 agonists into a single drug platform, termed “OrthomAb”, which not only retains the costimulatory activity of the unlinked agonists, but additionally programs unique T cell functions and preferentially expands effector T cells over Tregs. Importantly, OrthomAb also elicits therapeutic tumor immunity in an aggressive melanoma model. This approach provides a blueprint for distilling complex combination immunotherapies into more clinically-feasible delivery approaches.

2. Results

OrthomAb was synthesized by conjugating anti-CD134 with anti-CD137 using MTz and TCO couplers that were attached to the mAbs at an optimized 7:1 ratio (Figure 3.2A) via click chemistry 284. SDS-PAGE indicated that the conjugation reaction contained heterodimers (~300 kDa), higher-order multimers and residual monomers (Figure 3.2B). The heterodimers were enriched by three successive rounds of FPLC size-exclusion chromatography using Sephacryl

300 (Figure 3.2C-E) to yield a final OrthomAb product that was >90% dimer (Figure 3.2F).

To test if OrthomAb costimulates T cells, C57BL/6 (B6) splenocytes were stimulated in vitro with a very low concentration of soluble anti-CD3 mAb (50 ng/ml) that only partially induced CD25 (Figure 3.4). Importantly, addition of OrthomAb to the cultures (1.25 g/ml) substantially increased CD25 expression on both CD4 and CD8 T cells (Figure 3.4A), and also increased proliferation (CellTrace Violet dilution) of conventional CD4 and CD8 T cells in a dose-dependent manner (Figure 3.4B, upper and middle panels). Strikingly, however, Treg

proliferation appeared to be inhibited by OrthomAb (Figure 3.4B, lower panels), which prompted further analysis of the effect of OrthomAb and unlinked costimulators on the different

T cell subsets. In contrast to conventional T cells that express CD134 and CD137 following TCR stimulation, Foxp3+ Tregs constitutively express CD134 and CD137, and agonists to both can impact Treg expansion and function 285-288. Unlinked CD134 and CD137 agonists individually, as well as in combination, augmented the expansion of anti-CD3-stimulated Foxp3+ Tregs, whereas at the doses used only anti-CD137 and the unlinked combination boosted Foxp3neg

(conventional) CD4 and CD8 T cell expansion (Figure 3.4C). Notably, although OrthomAb boosted the expansion of conventional CD4 T cells beyond that elicited by unlinked CD137 agonist and the unlinked combination, it actually elicited weaker Treg expansion in comparison to the unlinked combination (Figure 3.4C, bottom panel). CellTrace proliferation analysis revealed that OrthomAb, but not unlinked single and dual costimulators, actually inhibited anti-

CD3-induced Treg cell division (Figure 3.4D, E). The net outcome of this effect of OrthomAb on the different T cell subsets was an increased ratio of Foxp3neg effector T cells to Foxp3+ Tregs with OrthomAb compared to unlinked single and dual agonists (Figure 3.4F).

A key clinical consideration is the capacity of OrthomAb to impact the amount and type of cytokine secreted by stimulated T cells. This was first tested using Rag-/- OT-I TCR transgenic

CD8 T cells stimulated in vitro with cognate SIINFEKL peptide (Figure 3.5). OrthomAb addition to the SIINFEKL-stimulated cell cultures elicited significantly greater secretion of IL-2 and IFN- compared to isotype control IgG, a control conjugate of irrelevant specificity, or media alone (Figure 3.5A). Secondly, in a titratable manner, OrthomAb augmented secretion of

IL-2, IFN- and, unexpectedly, IL-6 (Figure 3.5B). Further, we tested the individual costimulators against OrthomAb for cytokine production (Figure 3.6A, B) and CD25 expression

(Figure 3.6C), and the data show that OrthomAb induced responses far beyond anti-CD134 or -

CD137. Similarly, OrthomAb elicited much higher levels of IFN-, IL-6 and IL-17 secretion from soluble anti-CD3-stimulated B6 splenocytes compared to unlinked anti-CD134 and -CD137

(Figure 3.7A), and curiously, only OrthomAb elicited IL-6 secretion in the absence of anti-CD3

(Figure 3.7B, bottom panel). Furthermore, OrthomAb elicited much greater secretion of IFN-,

IL-6 and IL-17 from soluble anti-CD3-stimulated B6 splenocytes compared to the unlinked anti-

CD134 plus anti-CD137 combination (Figure 3.7C) Finally, OrthomAb, but not unlinked anti-

CD134 plus anti-CD137 combination, elicited IL-10 secretion with or without anti-CD3 stimulation (Figure 3.7D). OrthomAb’s enhanced cytokine response was also found to be mediated through both CD4 and CD8 T cells (Figure 3.8). These data suggest that OrthomAb has a unique capacity to influence not only proliferation but also the amount and type of cytokine produced, which may prove efficacious during a biological response.

Next, the aggressive B16-F10 (B16) melanoma model 289 was used to examine if

OrthomAb could costimulate T cells in vivo and elicit antitumor immunity. In the first study, mice harboring established B16 tumors were treated with OrthomAb (150 g) or control conjugate on day 3 (after tumors became visible) and then again on day 6 (Figure 3.9A).

OrthomAb reduced tumor size relative to the control, with statistically significant differences on days 4-6, 9 and 10, and reduced overall tumor burden (area under the curve 290), through day 13

(Figure 3.9B). Analysis of TIL on day 18 revealed that the percentages of CD8+ and CD4+ TIL that were double-positive for the cytolytic granule protein granzyme B (GzmB) and the T-box transcription factor Eomesodermin (Eomes) that programs CTL function 291 were ~2-fold higher

(p<0.001) with OrthomAb compared to control-treated tumors (Figure 3.9C). In a second experiment, mice with established B16 tumors were treated with OrthomAb, anti-CD134, anti-

CD137 or control IgG on days 2 (after tumors became visible), 5 and 8 (Figure 3.9D). At doses used, monotherapy with the individual costimulators elicited, at best, only modest reductions in tumor growth (Figure 3.9E) as quantified by tumor size at day 14 (Figure 3.9F) or area under the curve through day 14 (Figure 3.9G). In contrast, OrthomAb significantly reduced tumor burden ~2-fold (Figure 3.9E-G) and extended survival compared to control IgG (Figure 3.9H).

3. Discussion

Combination immunotherapies can more effectively treat cancer compared to monotherapies

106,110, and increasing the number of agents included in these therapeutic cocktails can further boost efficacy 110,150,152,283. Nevertheless, this approach, while feasible in mouse models, poses various challenges for human clinical translation, including regulatory complexities involved in approval for multi-agent clinical testing 282. The OrthomAb approach provides a means to streamline combination immunotherapy by covalently joining two separate agents, CD134 and

CD137 agonists, into a single drug platform. Ultimately, this approach could be replicated by conjugating other agents that, when administered with OrthomAb, would in essence distill a 4- drug combination therapy into a simpler 2-drug combination. This would be advantageous in several ways, including reducing the number of clinical trial arms.

In contrast to other well-established dual-specific immunotherapeutics, such as bispecific antibodies that bind a tumor surface antigen (CD20, EpCAM, HER2, or others) as well as CD3 to enable tumor cell killing by tethering CTL to tumor cells 292, OrthomAb is a tetravalent heteroconjugate comprised of mAb agonists to two separate costimulatory receptors that are each expressed on T cells. This might co-cluster CD134 and CD137 within the same synapse, initiating a unique or "hybrid" downstream signal that programs unexpected, but potentially

useful, T cell functions (illustrated in Figure 3.1, and further explored in Chapter 4). This possibility is consistent with our current findings that OrthomAb elicits greater secretion of the T cell effector cytokines IFN- and IL-17 compared to unlinked CD134 and CD137 single and dual mAb agonists. Alternatively, simply multimerizing individual agonists may be sufficient to augment costimulatory activity. Nevertheless, OrthomAb was unique in its ability to elicit IL-6 secretion, even in the absence of TCR stimulation. Given that IL-6 is known to inhibit Treg stability and function 293-296, this result might also help to explain another unexpected property of

OrthomAb, which is its ability to favor the expansion of effector T cells over Tregs (in comparison to unlinked dual agonists). This effect appears fortuitous given that a major issue in developing T cell-based immunotherapies is the potential of modalities to promote the expansion of effector T cells while minimizing that of Tregs, particularly given that both use IL-2 as a growth factor, and thus likely contributes to the ability of OrthomAb to elicit better antitumor efficacy compared to the individual unlinked agonists. Ultimately, the mechanisms underlying these responses elicited by OrthomAb may be highly complex given that multiple T cell and non-T cell populations express CD134 and CD137, and hence the responses of certain cell types may be the consequence of either direct effects by OrthomAb or indirect effects mediated by other responding cells. These ideas will be explored further in Chapters 4 and 5.

In sum, fusing two anti-cancer biologics into a single drug platform provides a novel blueprint for distilling complex combination therapies into a smaller number of therapeutic agents, thus simplifying clinical translation.

4. Figures

Figure 3.1: Proposed mechanism of OrthomAb

(A) Costimulation therapy with anti-CD134 (left panel) or anti-CD137 (middle panel) can bolster

a patient’s antitumor immune response, but single-agonist therapy often falls short of generating a sufficient result. Dual costimulation (DCo) combination therapy (right panel) provides a much more potent effect and can help mount a more substantial tumoricidal response that can be synergistic, especially when co-expressing cells are being targeted. (B) OrthomAb’s dual specificity and multi-valency can likely promote even greater costimulatory receptor clustering and colocalization (middle and right panels). This may drive greater signaling strengths that lead to enhanced tumoricidal responses (middle panel) or potentially trigger a hybrid signaling cascade that unleashes novel antitumor responses (right panel).

Figure 3.2: OrthomAb synthesis and purification

(A) Schematic depicting click conjugation of anti-CD134 and -CD137. (B) Non-reducing SDS-

PAGE showing species at different stages of synthesis, with the two right-most lanes showing a representative unpurified reaction product mixture. Chromatographic tracing of A280 versus time (C) and SDS-PAGE (D) indicate the species present in each fraction. (E) Chromatographic tracings with SDS-PAGE image overlays depicting species present at each purification round for a representative triple-purified OrthomAb batch, with calculated yields shown at each step. (F)

Representative SDS-PAGE showing purified OrthomAb dimer.

Figure 3.3: Optimization of purity and yield by fine-tuning click chemistry

(A) Non-reducing SDS-PAGE showing the effect that linker-to-mAb ratio has on final products resulting from a representative conjugation reaction. Linker-to-mAb ratios for coupled species are shown for methyltetrazine-PEG5-NHS ester (MTz) and anti-CD134 (left third), and trans- cyclooctene-PEG4-NHS ester (TCO) and anti-CD137 (middle third). Final species present after conjugation of coupled mAbs using different linker-to-mAb ratios are shown in the rightmost third of the gel. (B) Tracings of representative initial size-exclusion chromatography rounds

during purification of products obtained from conjugation reactions using the indicated linker-to- mAb ratios. Theoretical yields are calculated by dividing the A280 area under the curve for only those fractions that contain appreciable quantities of OrthomAb dimer and would be pooled for subsequent purification steps (dashed box) by the total A280 area under the curve.

Figure 3.4: OrthomAb augments effector T cell activation and expansion

B6 splenocytes (1 x 105) were incubated with 0 or 50 ng/ml (A) or 20 ng/ml (B) soluble anti-

CD3 mAb +/- OrthomAb. (A) Surface CD25 expression on CD8+ and CD4+ T cells at 24 hours post anti-CD3 stimuation +/- OrthomAb (1.25 μg/ml). (B) Anti-CD3-stimulated splenocytes labeled with CellTrace Violet were costimulated with 0, 0.2 or 2 μg/ml OrthomAb, and cell division (CellTrace dilution) of CD8+, CD4+Foxp3neg, and CD4+Foxp3+ T cells measured at 72 hours. Data shown are representative of multiple similar experiments. In a separate experiment

(C-F), B6 splenocytes (1 x 105) were labeled with CellTrace Violet and cultured 72 hours with

15 ng/ml soluble anti-CD3 and control IgG (2 g/ml), anti-CD134 (2 g/ml), anti-CD137 (2

g/ml), anti-CD134 plus anti-CD137 (1 g/ml each) or OrthomAb (2 g/ml), n=4 per group. (C)

Total numbers of CD8+, CD4+Foxp3neg, and CD4+Foxp3+ T cells. (D) CellTrace dilution histogram overlays for cultures treated with soluble anti-CD3 (black) or soluble anti-CD3 plus

OrthomAb (red). (E) Division Index and % Divided CD4+Foxp3+ Tregs were calculated using

FlowJo Proliferation Tool. (F) Ratio of effector T cells (CD3+CD8+ + CD3+CD4+Foxp3neg) to

regulatory T cells (CD3+CD4+Foxp3+). *, **, *** and **** indicate p<0.05, 0.01, 0.001 and

0.0001, respectively, compared to the control or delineated group (One-way ANOVA).

Figure 3.5: OrthomAb boosts cytokine secretion by peptide-stimulated CD8 T cells

OT-I Rag KO splenocytes (1 x 105) were cultured 24 hours with SIINFEKL (SFKL) peptide at

50 pg/ml (A) or the indicated concentrations (B) plus 2 g/ml isotype control IgG, control conjugate or OrthomAb. (A) Supernatant IL-2 and IFN- measured by ELISA, mean +/- SD, n=2-4, representative of at least 3 independent, similar experiments. (B) Supernatant IL-2, IFN-, and IL-6 with the indicated SFKL peptide and OrthomAb concentrations.

Figure 3.6: OrthomAb boosts cytokine secretion more effectively than anti-CD134 or -CD137

OT-I Rag KO splenocytes (1 x 105) were cultured 48 hours with SFKL peptide and costimulators at the indicated concentrations. (A) Supernatant IFN-, IL-6, and IL-17 with titrated concentrations of SFKL peptide and costimulators. (B) Supernatant IFN-, IL-6, and IL-17 pooled from the 30 pg/ml SFKL peptide plus 0.2, 0.6, and 2.0 g/ml costimulator wells in (A).

Figure 3.7: OrthomAb potently boosts cytokine secretion by anti-CD3-stimulated T cells

B6 splenocytes (1 x 105) were cultured with soluble anti-CD3 at 15 ng/ml (A), 0, 5 or 20 ng/ml

(B, D) or 20 ng/ml (C) plus the indicated concentrations of costimulators for 48 h (A, C), 24 h

(B), or 72 h (D). Significance between OrthomAb and anti-CD134 or -CD137 are indicated by * and #, respectively (A, B); significance between OrthomAb and unlinked anti-CD134 plus -

CD137 are indicated by * (C, D). N=3 in each panel, which are representative of multiple similar trials.

Figure 3.8: OrthomAb-treated T cells demonstrate enhanced CD4 and CD8 cytokine responses

Intracellular IFN- production by 4 h PMA + Ionomycin-stimulated CD8+ (A-C) and Foxp3neg

CD4+ (D-F) T cells amongst unpurified splenocytes following 24 (B, E, left panels) or 48 h (A,

D; B, E, right panels; C, F) culture of 1 x 105 C57BL/6 splenocytes stimulated with 15 ng/ml

anti-CD3 plus 2.0 g/ml (A, B; D, E) or plus 0, 0.02, 0.06, 0.2, 0.6, or 2.0 g/ml (C, F) control

IgG, anti-CD134, anti-CD137, anti-CD134 plus anti-CD137, or OrthomAb). (A, D) IFN- staining of CD8+ (A) and Foxp3neg CD4+ (D) T cells, with percentages of IFN-+ cells indicated above gates. (B, E) IFN- histogram overlays (normalized to modes) for CD8+ (B) and Foxp3neg

CD4+ (E) T cells. (C, F) Titration curves showing percentages of IFN-+ CD8+ (C) and Foxp3neg

CD4+ (F) T cells. Data representative of at least 3 independent, similar experiments.

Figure 3.9: OrthomAb demonstrates therapeutic efficacy in B16 melanoma

(A) Female C57BL/6 mice were injected intra-dermally with 1 x 105 B16-F10 melanoma cells on day 0. When tumors became visible on day 3, mice were administered 150 g isotype control conjugate (Control) or OrthomAb intra-peritoneally (indicated by first arrow beneath x-axis).

Identical treatment boosters were administered in the same manner on day 6 (indicated by second arrow beneath x-axis). Tumor sizes were measured daily until day 18, when tumors had reached

~200mm2 and all mice were sacrificed and TIL isolated for flow cytometric analysis. (B) Daily tumor sizes (mm2), determined by multiplying together the longest diameter and the corresponding perpendicular diameter. Data is shown up to day 14 post-tumor inoculation. (C)

Graphical representation showing percentage of CD8+ (top panel) and CD4+ (bottom panel) TIL that were GzmB+ Eomes+, measured by flow cytometry. (D) In an independent experiment, female C57BL/6 mice were injected intra-dermally with 1 x 105 B16-F10 melanoma cells on day

0. When tumors became visible on day 2, mice were administered 150 g control IgG, anti-

CD134, anti-CD137, or OrthomAb intra-peritoneally. Identical treatment boosters were administered in the same manner on days 5 and 8. Tumor sizes were measured every 1-2 days until mice reached a pre-defined endpoint (tumor size > 250 mm2 or moribundity), which occurred between days 15 and 32. (E) Individual tumor growth curves (mm2), determined by multiplying together the longest diameter and the corresponding perpendicular diameter. Data is shown up to day 14 post-tumor inoculation. (F) Scatter plot of day 14 tumor sizes (mm2). (G)

Scatter plot of area under the curve (AUC) values calculated up to day 14. (H) Survival curves for control IgG-treated mice and OrthomAb-treated mice.

Chapter 4. Exploring the Mechanisms of OrthomAb and Dual Costimulation Synergy

1. Does OrthomAb involve simultaneous colocalization of CD134 and CD137?

Dual costimulation (DCo) is a particularly potent combination therapy, synergistically boosting

CD8+ T cell clonal expansion and effector function 148, as well as inducing differentiation of cytotoxic CD4+ Th1 cells 131. The mechanism by which these two pathways converge to program highly tumoricidal T cells, however, is not yet fully understood. Although OrthomAb and DCo both target CD134 and CD137, they likely differ in terms of how they engage the receptors and the quantity and quality of signaling they impart. DCo consists of two distinct antibodies (i.e.,

“unlinked” combination therapy). This means that one of the antibodies is equally capable of binding to a cell that expresses only that antibody’s target receptor as it is to binding to a cell that expresses both receptors. One consequence of this relates to the fact that some therapeutically- irrelevant cells can express low levels of one of the receptors (CD137 in particular), which can get bound by antibody and trigger immune attack and collateral damage244,246,247. These “on- target, off-tumor” interactions contribute to the overall toxicity that occurs during treatment.

On the other hand, some immune cells may get costimulated by one of the antibodies but not the other, either because that cell happens to express one receptor only (e.g., CD134 and

CD137 expression kinetics and cellular distributions do not overlap completely), or because individual mAbs are not necessarily confined in proximity and are free to bind independently of the other. It is possible that synergistic activity observed with DCo treatment is the result of costimulation through CD134 and CD137 strictly on cells expressing both receptors, as depicted in Figure 3.1; if this was the only mechanism driving DCo synergy, then, ideally, only cells expressing both receptors would be bound and costimulated by anti-CD134 and anti-CD137.

However, this is not the only mechanistic scenario that could manifest as DCo synergy. It is possible that synergy does not require co-expressing T cells to be costimulated by both mAbs.

For example, cellular interactions between anti-CD137-costimulated dendritic cells and anti-

CD134-costimulated T cells could drive a much stronger effector response than would occur with anti-CD134 or anti-CD137 monotherapy alone. There also is the possibility that multiple mechanisms are at play, and each one contributes differently to the overall synergy.

OrthomAb’s structure may confer unique biological activity that is not observed with

DCo. The click chemical linkage ensures that both constituent antibodies are kept in close proximity to one another, which should preferentially focus dual costimulation onto

CD134/CD137 co-expressing cells. This receptor binding pattern is referred to as “cis-acting”

(illustrated in Figure 3.1B). This would be a major advantage if simultaneous costimulation of both receptors on the same cell is the primary (or sole) mechanism of synergy. Another advantage is that this should limit some of the undesirable “on-target, off-tumor” effects that can happen with unlinked DCo therapy. Another plausible mechanism of OrthomAb involves a type of binding pattern known as “trans-acting”. For instance, the anti-CD137 part of OrthomAb could bind a dendritic cell while the anti-CD134 portion of OrthomAb binds a T cell; in this case, OrthomAb would costimulate both cells and also serve as a tether, pulling the two cells closer together and promoting enhanced interaction and greater activation.

In order to investigate these questions, we bred the following mice:

• CD134-/- mice on C57BL/6 background and on OT-I Rag-/- background

• CD137-/- mice on C57BL/6 background and on OT-I Rag-/- background

• CD134-/-CD137-/- (DKO) mice on C57BL/6 background and on OT-I Rag-/-

background

We first confirmed that the single and double knockout mice had no obvious anatomical or developmental abnormalities, with normal spleens and thymuses, and T cell subset distributions that are consistent with WT mice (Figure 4.1). To determine if OrthomAb co-ligates CD134 and

CD137 on the same T cell (i.e., cis-acting) or, alternatively, if co-ligation occurs between adjacent T cells expressing one or the other receptor (i.e., trans-acting), we performed in vitro T cell stimulation assays comparing OrthomAb’s potentiation of cytokine secretion from

SIINFEKL-stimulated OT-I CD8+ T cells that are:

1) WT (positive control where both cis and trans co-ligation can occur)

2) CD134/CD137 double KO (negative control where neither cis nor trans ligation can

occur)

3) CD134 single KO (only CD137 can be ligated)

4) CD137 single KO (only CD134 can be ligated)

5) Co-culture of CD134 single KO with CD137 single KO (only trans co-ligation can

occur)

We also measured surface expression levels of CD134, CD137, and CD25; differential expression of the CD45 congenic marker allowed us to distinguish between the CD134 and

CD137 single KO OT-I cells during flow cytometric analysis.

After a 48-hour stimulation with SIINFEKL peptide only, the single knockout cells demonstrated a diminished ability to upregulate CD25, even when co-cultured together (Figure

4.2A). Interestingly, the CD134 KO cells expressed CD137 at lower levels than WT, and the

CD137 KO cells expressed CD134 at much lower levels than WT (Figure 4.2A). OrthomAb treatment substantially increased expression of CD25 on WT cells, but CD25 expression was decreased by about half on the CD134 KO cells. The CD137 KO cells did not express CD25

when cultured alone, but they were able to when co-cultured with the CD134 KO cells (Figure

4.2B). Cytokine secretion from single KO cells was also substantially impaired relative to WT cells, especially at the lower SIINFEKL concentrations, and co-culturing the cells did not rescue their ability to secrete cytokine (Figure 4.2C). These results suggested that only cis co-ligation

(i.e., on the same T cell) is important mechanistically to OrthomAb’s in vitro activity.

A follow-up study revealed that DCo’s activity was also severely blunted with CD134 and CD137 single KO cells; intriguingly, co-culturing the single KO cells did not rescue IFN-

 secretion or CD25 expression for either DCo or OrthomAb (Figure 4.3). These data suggest that cis co-ligation is necessary for both OrthomAb and DCo to exhibit synergy in vitro.

Once we had DKO mice, we were able to compare them to the single KO mice and WT mice. During a 12 or 24 h culture with SIINFEKL and DCo, CD134 KO and CD137 KO cells expressed slightly lower levels of CD25 than did WT cells, and DKO expression levels of CD25 were the lowest (Figure 4.4A). Strikingly, however, IFN- secretion was massively reduced in both single KOs and DKO cells (Figure 4.4B). These data suggest that loss of one receptor is as detrimental as the loss of both receptors, at least with regard to in vitro IFN- secretion from

CD8+ OT-I cells. In other words, for both DCo and OrthomAb, cis-acting dual costimulation of

T cells appears to be the predominant mechanism of synergy driving CD8+ T cell cytokine potentiation.

Additional in vitro experiments planned for the more distant future involve culturing purified T cells from WT or single-KO mice (alone or co-cultured) with purified APCs from

DKO mice. These experiments will offer more insight into whether synergy involves only co- expressing T cells, or if, for example, the presence of CD137 on activated dendritic cells contributes at all to synergy.

Subsequent in vivo experiments will involve adoptively transferring the same OT-I CD8+

T cells just described into syngeneic, WT recipient mice immunized with SIINFEKL plus

OrthomAb. In vivo readouts will be performed using splenocytes 5 days post-immunization and will include clonal expansion and intracellular expression of the cytotoxic effector molecule granzyme B (GzmB) and the T-box transcription factors T-bet and Eomesodermin (Eomes) directly ex vivo, as well as the tumoricidal cytokines IFN- and TNF- following in vitro restimulation with SIINFEKL 131,148,297,298. In co-transfer experiments, CD134 and CD137 single

KO OT-I cells can be distinguished from each other and from the endogenous non-specific CD8+

T cells through the differential expression of the CD45 congenic marker, as they were in co- culture experiments. It is important to keep in mind that there is always the possibility that we will observe different outcomes in vitro versus in vivo, in which case we will need to modify in vitro assay conditions to more accurately reflect in vivo responses (e.g., alter the culture density or the accessory cell composition). This will be important for certain mechanistic studies, and future translational studies using human T cells where, outside of clinical trials, in vivo response assays are not feasible.

Lastly, CD134/CD137 single- and double-KO mice will be used in tumor challenge experiments. WT, CD134 KO, CD137 KO, or DKO mice (all on the C57BL/6 background) will be inoculated with B16 melanoma and treated with DCo or OrthomAb, either in the same experiment or in separate experiments. Antitumor efficacy will be evaluated as in Figure 3.9.

Another important tumor challenge experiment will involve adoptively transferring OT-I CD8+ T cells from the single- and double-knockout (or WT) OT-I mice into syngeneic, WT (C57BL/6) recipient mice inoculated with B16-OVA and immunized with SIINFEKL plus OrthomAb or

DCo. Single-KO cells will also be co-transferred to see if any loss of efficacy can be rescued.

This experimental tumor challenge setup will use T cell activation functional readouts (as described above); antitumor efficacy will also be assessed as in Figure 3.9.

2. Does OrthomAb engage a hybrid signaling pathway?

Because of OrthomAb’s dual-specificity and multi-valency, cis-binding might simultaneously co-localize and cluster both receptors within the same synapse, allowing their subunits to interact in a non-physiological context. This, in turn, could influence signaling events to unlock hybrid costimulation programs, ultimately generating unique functional responses. A hybrid signaling mechanism could explain not only OrthomAb’s potency, but also some of its unique properties such as IL-6, IL-17, and IL-10 secretion (Figure 3.6, Figure 3.7), as well as its differential effects on Treg proliferation (Figure 3.4).

To explore whether OrthomAb engages hybrid signaling, we generated homodimers of

CD134 and CD137 (Figure 4.5). Future experiments will test these new reagents using in vitro assays similar to those we have used previously, and then comparing them to OrthomAb in terms of cytokine secretion and T cell proliferation. The combination of both homodimers (CD134 homodimer + CD137 homodimer) will be vital to compare to OrthomAb. If only OrthomAb elicits some of the “atypical” cytokines such as IL-6, IL-10, and IL-17, then that would support the hypothesis that OrthomAb’s mechanism is unique and functions through hybrid signaling.

We will also use a more direct approach to study intracellular signaling. TNFR ligation mediates costimulatory function via engagement of various combinations of six separate TNF receptor-associated factors (TRAF1-6) that assemble signaling complexes that activate downstream kinases and transcription factors such as JNK and NFB 299. Although there is overlap in the TRAF combinations used by various TNFRs, they are not identical. For example,

CD134 and CD137 have been reported, in varying degrees and in different models, to engage

TRAFs 1, 2, 3, 5, and 6 300-304, and TRAFs 1, 2, and 3 300,301, respectively. We do not know which TRAFs are engaged by OrthomAb, and whether this combination represents the summation of both agonists or hybrid signaling that may fuse both pathways.

To analyze the signaling pathways induced by OrthomAb, standard in vitro costimulation assays used previously will be modified as follows: since early costimulatory signaling events will be measured, and naïve T cells lack CD134 and CD137, cell cultures will be pre-stimulated overnight with anti-CD3 or SIINFEKL to induce receptor expression, antigen presenting cells with potential to express the natural ligands will be removed using MHC class II-conjugated magnetic beads, and the T cells will be rested in fresh media for 3 h to allow costimulatory signaling to return to baseline. Next, T cells will be treated with OrthomAb, IsomAb or media alone (negative controls), unlinked CD134 and/or CD137 agonists (to determine signaling associated with the individual pathways), or CD134 and/or CD137 homodimers (to determine the effect of dimerization). Phosphorylation of JNK and IB (upstream of NF-B) will be measured at 0, 5, 10, 15, 30 and 60 min, association of TRAF1-6 with the receptors will be measured at 10 min via co-immunoprecipitation, and TRAF degradation will be measured at 5 h as previously described 305.

Whether or not OrthomAb engages downstream signaling distinct from unlinked dual costimulation will be important to know to help guide future mechanistic studies. OrthomAb may engage the sum of signaling events elicited by each individual agonist, but our preliminary data are suggestive of signaling events not seen with either alone or in combination. It is possible that differences in signaling may reflect quantitative, rather than qualitative, differences in receptor ligation. One last thing worth noting is that TRAFs and their associated pathways might

not be the best readout for hybrid signaling. If this turned out to be the case, a non-biased proteomics approach could be helpful in identifying other ways to address the issue of hybrid signaling.

3. Figures

Figure 4.1: CD134 and CD137 knockout mouse spleen and thymus characterization

Thymocytes (left panel) and splenocytes (right panel) were harvested from WT, CD134-/-,

CD137-/-, or CD134-/-CD137-/- (DKO) mice, all on the C57BL/6 background. Harvested cells were then stained for flow cytometric analysis to determine cellular phenotypes and T cell subset distributions. Plots are gated on live, single cells (left) or live, single, CD4+, CD8neg cells (right).

Figure 4.2: Costimulatory receptor-knockout OT-I splenocytes exhibit diminished in vitro activity and impaired response to OrthomAb treatment

Splenocytes were obtained from WT (black line), CD134KO (blue line), or CD137KO mice (red line), all on OT-I RagKO background, and 1 x 105 OT-I cells were cultured for 48 h with the indicated concentrations of SIINFEKL peptide (SFKL) +/- OrthomAb. (A) Expression of

CD134, CD137, and CD25 on cells cultured with peptide only; dashed lines and "*" indicate that cells were co-cultured at a 1:1 ratio. (B) CD25 expression on cells cultured at the indicated SFKL

concentrations +/- different OrthomAb concentrations. (C) Supernatant cytokine levels obtained at 48 h from the cultures described in A & B; knockout co-cultures are indicated with purple, dashed lines. N = 1, representative of multiple experiments.

Figure 4.3: CD134/CD137 knockout cells are less responsive to DCo and to OrthomAb

Splenocytes were obtained from WT, CD134-/-, or CD137-/- mice (all on OT-I Rag-/- background), and 1 x 105 OT-I cells were cultured with 5, 10, or 15 pg/ml SIINFEKL peptide (SFKL) +/- Rat

IgG, DCo or OrthomAb. Supernatant IFN-g levels (left) and OT-I cell surface expression of

CD25 (right) were measured after 48 h culture. In the left panel, “KO + KO” indicates that supernatant was collected from wells that contained both single-knockout cell types at a 1:1 ratio. In the right panel, "*" indicates cells that were co-cultured, but that could be gated on analysis to determine CD134-/- and CD137-/- cell type expression levels separately. N = 3.

Figure 4.4: Similar functional impairments are observed with single- and double-KO mice

Splenocytes were obtained from WT, CD134-/-, CD137-/-, or CD134-/-CD137-/- (DKO) mice (all on OT-I Rag-/- background), and 1 x 105 OT-I cells were cultured with 10 or 20 pg/ml SIINFEKL peptide plus 0.2 g/ml DCo. (A) CD8+ T cell surface expression of CD25 before culture, and after 12 or 24 h culture. (B) Supernatant IFN- levels after 12 or 24 h culture. N = 1 of multiple pooled culture wells (A), or n = 3 comprised of culture triplicates (B).

Figure 4.5: CD134 and CD137 homodimers

Homodimers of anti-CD134 and of anti-CD137 were generated using a similar protocol that was used to make OrthomAb (refer to Figure 3.2). (A) Cartoon depictions of OrthomAb (top), anti-

CD134 homodimer (middle), and anti-CD137 homodimer (bottom). Note that click linkages are identical in all three. (B) SDS-PAGE showing anti-CD134 and anti-CD137 monomers (2 left lanes), next to each of the homodimers and OrthomAb (middle lanes), and rat IgG (last lane).

Chapter 5. Developing a Next-generation OrthomAb Engineered to Limit Toxicity

1. Generate and test a modified OrthomAb that lacks Fc domains

As already discussed extensively in Chapter 1, a major cause of adverse events occurring with immunotherapeutic mAb therapy is the crystallizable fragment (Fc), which interacts with Fc receptors (FcR) on innate cells (e.g., monocytes, NK cells) and can drive massive release of pro- inflammatory cytokines 162,164,169,170,306,307 (Figure 1.1C, Figure 5.1A). Additionally, coating of therapeutically-irrelevant cells expressing the target receptors can lead to antibody-dependent cellular cytotoxicity or phagocytosis (ADCC or ADCP)-mediated collateral damage 244-247

(Figure 1.1D, Figure 5.1A). Moreover, FcR could potentially mediate ADCC/ADCP directed toward costimulated T cells, thereby limiting efficacy.

Although the procedure is trivial to remove Fc domains from antibodies using the enzyme pepsin, doing so generally abrogates efficacy because it is the Fc domains that orchestrate the FcR-mediated clustering of mAb-bound receptors that initiate costimulatory signaling 9,190,208-210.

However, there have been reports of FcR-independent costimulatory activity, suggesting that Fc requirements are not absolute 192,211,216,254,263. In particular, antibody multimerization has been shown to be an effective strategy to bypass FcR requirements of anti-CD40 agonist while preserving activity in vitro and in vivo, as well as in a model of lymphoma with FcR-knockout mice 254.

Similarly, OrthomAb’s multivalent structure raises the possibility that its therapeutic activity does not require FcR, suggesting that a modified OrthomAb lacking Fc will retain activity, without triggering FcR-mediated toxicity caused by innate cell activation and cytokine

storm 1,169,252,306 (Figure 5.1C). An added benefit is that the activity of Fc-less OrthomAb would not be reliant on FcR availability, which can vary substantially between different tissues, fluctuate based on immune status (e.g., recent infection), is prone to patient-to-patient differences in Fc-FcR binding avidities and ratios of activating to inhibitory FcRs, and can further be influenced by FcR-SNPs in patients 1,253,308-312.

Fc-less OrthomAb is synthesized using the same protocol used to make OrthomAb (as in

Figure 3.2), with the following modification: Fc domains from CD134 agonist (clone OX86,

IgG1) and CD137 agonist (clone 3H3, IgG2a) are digested with pepsin to generate F(ab’)2 fragments 313-315 prior to click coupling and conjugation. Figure 5.2A is a schematic showing the protocol for Fc-less OrthomAb synthesis. We first had to carefully optimize pepsin digestion conditions for each mAb (Figure 5.2B) before scaling up the reactions to obtain CD134 and

CD137 F(ab’)2 fragments, clicking them together and isolating Fc-less OrthomAb (Figure 5.2C).

Note that lane 5 of the SDS-PAGE gel in Figure 5.2C contains Fc-less OrthomAb that has been enriched with only a single round of size-exclusion chromatography. Nevertheless, this initial

Fc-less OrthomAb batch was tested for costimulatory activity in vitro. Indeed, this Fc-less reagent induced IFN- secretion with a potency comparable to that of standard OrthomAb

(Figure 5.2D).

In follow-up experiments, we will confirm this result using new Fc-less OrthomAb dimer preparations purified through multiple FPLC rounds (as with standard OrthomAb in Figure 3.2).

These experiments will also test the activity of the unclicked F(ab’)2 monomers, which we expect will lack optimal costimulatory capacity (as previously observed with anti-CD137 316), even when combined and added at high concentrations, since they can cluster at most only 2 receptors. If observed, this result would indicate that Fc-less OrthomAb does indeed possess Fc-

independent costimulatory capacity.

Next, the in vivo immunotherapeutic potential of Fc-less OrthomAb will be assessed using the aggressive B16-F10 melanoma model 289 that we have used previously to test

OrthomAb 268 (Figure 3.9) and to study unlinked DCo 131,297,298. If Fc-less OrthomAb does exhibit therapeutic activity, we will then assess its ability to act in an Fc-independent manner by testing the unlinked anti-CD134 and anti-CD137 F(ab’)2 monomers given in combination. If they are therapeutically inert (in contrast to the active Fc-containing monomers), this would indicate that linking the F(ab’)2 fragments indeed bypasses the necessity for Fc to effectively cluster the receptors.

A central facet of our hypothesis is that removal of the Fc domains will reduce toxicities and adverse events elicited by OrthomAb (Figure 5.1C). This idea will be tested in the B16 model by measuring serum levels of pro-inflammatory cytokines associated with cytokine release syndrome, such as TNF-, IL-6, IL-1, MCP-1, and others 169,252,306, as well as liver enzymes indicative of hepatic damage 107,306,317. Thus, even if standard OrthomAb and Fc-less

OrthomAb control tumor growth to similar extents, our hypothesis would be supported if Fc-less

OrthomAb elicits lower serum levels of pro-inflammatory cytokines and liver enzymes from organ damage.

2. How do OrthomAb and Fc-less OrthomAb impact intratumoral Tregs?

A surprising aspect of immunomodulatory mAbs that has emerged recently is that they not only boost the response of tumor-specific effector T cells but can also mediate therapeutic efficacy by altering the function of T regulatory cells (Tregs) residing within the tumor microenvironment.

For instance, both anti-CTLA-4 78,197,198 and CD134 agonist 318 have been shown to delete

intratumoral Foxp3+ Tregs via FcR-dependent mechanisms that likely involve ADCC or ADCP.

On the other hand, CD137 agonist programs Tregs to acquire cytotoxic potential 319. We also recently found that although unlinked DCo reduces the frequency of intratumoral Tregs (similar to CD134 agonist given alone 318), the remaining Foxp3+CD4+ T cells acquire certain characteristics of effector T cells (expression of GzmB, IFN- and Eomes) and perhaps aid the therapeutic response 298. We have not yet determined whether this effect involves Treg depletion, or alternatively whether DCo induces intratumoral Tregs to undergo reprogramming to become effector T cells 320. Importantly, we do not know whether this effect depends on Fc-FcR interactions, which is a critical consideration given that Fc-less OrthomAb is designed to avoid

Fc-FcR interactions.

Future studies will use the "exFoxp3" fate mapping approach developed by Bluestone and colleagues 200 to determine whether Fc-less OrthomAb induces deletion of intratumoral

Tregs, or alternatively reprograms them to differentiate into effector T cells. Briefly, transgenic mice expressing a GFP-Cre fusion protein from the Foxp3 locus will be crossed to mice that contain a stop-floxed tdTomato reporter within the constitutive ROSA locus, such that CD4+ T cells actively expressing Foxp3 (Foxp3+GFP+TOM+) can be distinguished from exFoxp3 cells that previously expressed Foxp3 (Foxp3negGFPnegTOM+). The crossed double transgenic mice will be given B16 tumors and then treated with unlinked CD134 plus CD137 agonists, standard

OrthomAb, Fc-less OrthomAb or corresponding isotype or IsomAb controls.

Analysis of the exFoxp3 mice will indicate how unlinked DCo reduces intratumoral Treg frequency while inducing expression of GzmB and Eomes in the remaining Tregs 298. In control

(IgG-treated) mice we expect to observe a high intratumoral frequency of Tregs but very few exFoxp3 cells. If unlinked DCo diminishes Treg frequency without increasing exFoxp3 cells,

this would indicate that DCo depletes a portion of intratumoral Tregs, while inducing the remaining Tregs to express Eomes and GzmB. This possibility would be consistent with both the observation that CD134 agonist can induce Treg deletion 318 and that Tregs can gain effector capacity while maintaining Foxp3 expression 294,321. Alternatively, if exFoxp3 cell frequency increases, this would indicate that DCo induces Treg reprogramming.

Standard (Fc-containing) OrthomAb may elicit a similar effect as unlinked DCo

(regardless of the mechanism revealed), given that both have the capacity to bind costimulatory receptors as well as FcR. If the mechanism is shown to involve Treg reprogramming (i.e., generation of exFoxp3 cells), and Fc-less OrthomAb also mediates this effect, this result would suggest that reprogramming only requires costimulatory receptor clustering on the Tregs.

Alternatively, if Treg deletion is induced by DCo and standard OrthomAb, it may not occur with

Fc-less OrthomAb given that Treg deletion would likely involve Fc-FcR interactions 78,197,198,318.

These results will be integrated into a fuller understanding of how costimulation elicits therapeutic tumor immunity and further inform us how to best improve subsequent generations of OrthomAb.

3. Figures

Figure 5.1: Preventing FcR-mediated toxicity with Fc-less OrthomAb

(A) Combining elements of Figure 1.1 and Figure 3.1, this model illustrates the intra- and extra-

cellular interactions driving the efficacy and adverse events due to FcR engagement that occur during unlinked DCo therapy. (B) Since OrthomAb is made from whole antibodies, it has two Fc domains that still likely have the ability to interact with FcR located on adjacent FcR-expressing cells, which could trigger some of the same adverse events that occur with unlinked DCo. (C)

Removal of the Fc domains of anti-CD134 and anti-CD137 prior to click coupling and conjugation enables the synthesis of an “Fc-less” OrthomAb, which should have efficacy comparable to that of OrthomAb, but would avoid FcR-related toxicity.

Figure 5.2: Synthesis of Fc-less OrthomAb

(A) Cartoon depicting synthesis of Fc-less OrthomAb. (B) SDS-PAGE showing species present following pepsin digestion of anti-CD134 or anti-CD137 at pH 4.0 for various durations at 37 degrees celcius. (C) SDS-PAGE showing initial mAbs, Fc-less mAbs (F(ab’)2) following 24 h

(anti-CD134) or 13 h (anti-CD137) digestion, and then clicked Fc-less OrthomAb dimer enriched once by size-exclusion chromatography (purple arrow). (D) Supernatant IFN- following 24 h culture of C57BL/6 splenocytes stimulated with 20 ng/ml anti-CD3 plus titrated dosages of Fc-less OrthomAb, standard OrthomAb and individual agonists; n=3.

Chapter 6. Conclusions and Future Directions

Cancer is the 2nd leading cause of death in the United States, afflicting over one-third of the population and killing half of those diagnosed 322. Discovery of the immune system’s intrinsic ability to recognize and kill tumor cells spurred an explosion of interest and quickly became a major focus of investigation; not too long thereafter, immunomodulatory antibodies have brought about a revolution in cancer therapy. Patient success stories continue to make headlines, and results from ongoing clinical trials have provided us with an ever-expanding body of evidence highlighting that there is new hope in the fight against this terrible disease.

Thus far, however, these agents as monotherapies have had limited success in curing all but subsets of patients. This is likely due to the existence of not one, but several immunosuppressive mechanisms employed by tumors to avoid elimination by the immune system. Response rates can be improved by combining therapies that target multiple immunosuppressive pathways 106,110,243, but translation is impeded by regulatory complexities involved in the approval process for multi-agent clinical trials 282,323, in addition to increased rates and severity of adverse events 106,282. These barriers to clinical translation currently limit the feasibility of multi-targeted approaches.

Taking a step back, the idea for OrthomAb began as a relatively simple one: CD134 agonist works pretty well…CD137 agonist works pretty well too…CD134 agonist plus CD137 agonist works really well…what would happen if CD134 agonist and CD137 agonist were covalently linked…? This question is what I have spent the last 4 years of my life thinking about.

On the one hand, it might seem as though OrthomAb was a novel and intriguing idea that inspired a “throw it against the wall and see what sticks” type of approach without any precisely-

defined hypotheses. On the other hand, it might seem possible that the goal of making OrthomAb was to be able to ask whether “OrthomAb is better than DCo”. I came to appreciate that making

OrthomAb eventually served to simultaneously test multiple different, albeit overlapping, hypotheses, and that there exist several possible, non-mutually-exclusive, reasons that OrthomAb will ultimately prove to be a worthwhile science experiment after all.

At the core of this project are two overarching ideas or themes that OrthomAb tested:

1) Combination therapy bundled into a single drug

• Conjugating two immunotherapeutics into a single biologic offers the

benefits of combination therapy while also avoiding the logistical

complications involved in simultaneous co-administration of multiple

unlinked monotherapies.

2) FcR-independent efficacy

• OrthomAb should enable removal of Fc domains while preserving the

ability to cluster costimulatory receptor subunits to induce a therapeutic

response without triggering FcR-mediated toxicity.

Additional questions and ideas gradually surfaced along the way. For example, the fact that OrthomAb targets two different (yet similar) TNFR family members (i.e., CD134 and

CD137) opened the possibility that hybrid signaling might be taking place, which might elicit unique functions that may or may not be advantageous. Sure enough, our data suggest this likely may be the case (Figure 3.4, Figure 3.6, Figure 3.7, Figure 4.2). Evidence strongly supports the argument that OrthomAb is valuable therapeutically. Importantly, the “value” of OrthomAb in relation to unlinked DCo would, in this case, be a matter of quality rather than quantity; this is just one example of how asking the question of whether “OrthomAb is better than DCo” is much

more complex than simply comparing magnitudes of response readouts.

A more detailed summary of the conceptual advances that may be revealed and better understood with continued studies on the OrthomAb platform include the following:

1) OrthomAb links two drugs (CD134 agonist and CD137 agonist), each targeting distinct

pathways, into one drug. This will simplify translation and clinical implementation of

DCo combination therapy

2) OrthomAb should preferentially engage co-localized CD134 and CD137 on

therapeutically-relevant cells (i.e., T cells), in contrast to standard, unlinked DCo, which

can also target therapeutically-irrelevant cells expressing only one of the targets (e.g.,

endothelia that express CD137 244,246,247) and trigger collateral damage

3) Simultaneous and co-localized CD134/CD137 costimulation may involve intermingling

between the subunits of both receptor types within the same synapse, which may initiate

hybrid downstream signaling and potentially lead to unique biological responses with

increased efficacy

4) OrthomAb’s multivalent structure raises the possibility that its therapeutic activity does

not require FcR interactions, suggesting that a modified OrthomAb lacking Fc domains

could retain costimulatory activity without triggering FcR-mediated toxicity from innate

cell activation and consequent cytokine storm 1,169,252,306

5) The activity of Fc-less OrthomAb would not be reliant on the local availability of FcR,

which can vary substantially between different tissues, can fluctuate based on current

immune status (e.g., recent infection), is prone to the patient-to-patient variability in Fc-

FcR binding avidities and ratio of activating-to-inhibitory FcRs and, finally, is not subject

to FcR-SNPs in patients 1,253,308-312

6) This work will lay a general framework for single-agent engineering of many other mAb-

based combinations targeting distinct tumoricidal pathways

Looking back, the original hypothesis of my dissertation proposal nicely summarizes the

OrthomAb platform:

The overarching hypothesis is that OrthomAb will possess the combined costimulatory capabilities and therapeutic effects of both CD134 and CD137 agonists all in one drug, while also exhibiting a more favorable side effect profile compared to unlinked combination therapy

Future work will focus on understanding the mechanism(s) that underlie OrthomAb’s biological activity, knowledge from which will guide its modification to increase its therapeutic index. One such aspect of OrthomAb relates to the biochemical/biophysical factors that define OrthomAb’s structure and, consequently, determine the cellular interactions that influence OrthomAb’s mechanism(s) at a fundamental level. Further discussion related to this topic is beyond the scope of this dissertation, but I predict that antibody engineering, which is already a well-established and productive area of investigation 192,211,261,324-330, will become a major driving force in advancing the field of cancer immunotherapy.

This next point has already been belabored, but it is worth reemphasizing the notion that continued studies of OrthomAb will help lay the foundation for a solid understanding on which to build the next generation of “single-agent combination therapies”, as well as other immunomodulatory agents that are optimally engineered for maximum efficacy and minimal

toxicity.

Cancer immunotherapy is one of the most exciting and fast-moving fields in medical science today, and it will truly be exciting to see where the future takes us. Depending on who you ask, many people believe that we will eventually have a cure for cancer, and I believe that it is only a matter of time before we do. Of course, it is difficult to predict when and how we will find the cure, and what that cure will look like. I obviously don’t know the answers to these questions. But what I can say is that my money is on future generations of the same types of immunotherapies we have today that we are just now beginning to perfect.

And I believe that the OrthomAb platform could turn out to be one of the avenues that helps us get there as quickly as possible.

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