Meet the Authors: Harkamal S. Jhajj and Peter M. Tessier.

In an interview with Dr. Mishtu Dey, Editor-in-chief of Cell Chemical Biology, two authors of the Technology article entitled "Facile generation of biepitopic antibodies with intrinsic agonism for activating tumor necrosis factor receptors"-Dr. Peter M. Tessier and Dr. Harkamal S. Jhajj-share more about their paper and their lives as scientists.

Facile generation of biepitopic antibodies with intrinsic agonism for activating tumor necrosis factor receptors.

Agonist antibodies are being pursued for therapeutic applications ranging from neurodegenerative diseases to cancer. For the tumor necrosis factor (TNF) receptor superfamily, higher-order clustering of three or more receptors is key to their activation, which can be achieved using antibodies that recognize two unique epitopes. However, the generation of biepitopic (i.e., biparatopic) antibodies typically requires animal immunization and is laborious and unpredictable. Here, we report a simple method for identifying biepitopic antibodies that potently activate TNF receptors without the need for additional animal immunization. Our approach uses existing, receptor-specific IgGs, which lack intrinsic agonist activity, to block their corresponding epitopes, then selects single-chain antibodies that bind accessible epitopes. The selected antibodies are fused to the light chains of IgGs to generate human tetravalent antibodies. We highlight the broad utility of this approach by converting several clinical-stage antibodies against OX40 and CD137 (4-1BB) into biepitopic antibodies with potent agonist activity.

Unlocking the potential of agonist antibodies for treating cancer using antibody engineering.

Agonist antibodies that target immune checkpoints, such as those in the tumor necrosis factor receptor (TNFR) superfamily, are an important class of emerging therapeutics due to their ability to regulate immune cell activity, especially for treating cancer. Despite their potential, to date, they have shown limited clinical utility and further antibody optimization is urgently needed to improve their therapeutic potential. Here, we discuss key antibody engineering approaches for improving the activity of antibody agonists by optimizing their valency, specificity for different receptors (e.g., bispecific antibodies) and epitopes (e.g., biepitopic or biparatopic antibodies), and Fc affinity for Fcγ receptors (FcγRs). These powerful approaches are being used to develop the next generation of cancer immunotherapeutics with improved efficacy and safety.

Facile generation of biepitopic antibodies with intrinsic agonism for activating receptors in the tumor necrosis factor superfamily.

Agonist antibodies that activate cellular receptors are being pursued for therapeutic applications ranging from neurodegenerative diseases to cancer. For the tumor necrosis factor (TNF) receptor superfamily, higher-order clustering of three or more receptors is key to their potent activation. This can be achieved using antibodies that recognize two unique epitopes on the same receptor and mediate receptor superclustering. However, identifying compatible pairs of antibodies to generate biepitopic antibodies (also known as biparatopic antibodies) for activating TNF receptors typically requires animal immunization and is a laborious and unpredictable process. Here, we report a simple method for systematically identifying biepitopic antibodies that potently activate TNF receptors without the need for additional animal immunization. Our approach uses off-the-shelf, receptor-specific IgG antibodies, which lack intrinsic (Fc-gamma receptor-independent) agonist activity, to first block their corresponding epitopes. Next, we perform selections for single-chain antibodies from human nonimmune libraries that bind accessible epitopes on the same ectodomains using yeast surface display and fluorescence-activated cell sorting. The selected single-chain antibodies are finally fused to the light chains of IgGs to generate human tetravalent antibodies that engage two different receptor epitopes and mediate potent receptor activation. We highlight the broad utility of this approach by converting several existing clinical-stage antibodies against TNF receptors, including ivuxolimab and pogalizumab against OX40 and utomilumab against CD137, into biepitopic antibodies with highly potent agonist activity. We expect that this widely accessible methodology can be used to systematically generate biepitopic antibodies for activating other receptors in the TNF receptor superfamily and many other receptors whose activation is dependent on strong receptor clustering.

Agonist antibody discovery: Experimental, computational, and rational engineering approaches.

Agonist antibodies that activate cellular signaling have emerged as promising therapeutics for treating myriad pathologies. Unfortunately, the discovery of rare antibodies with the desired agonist functions is a major bottleneck during drug development. Nevertheless, there has been important recent progress in discovering and optimizing agonist antibodies against a variety of therapeutic targets that are activated by diverse signaling mechanisms. Herein, we review emerging high-throughput experimental and computational methods for agonist antibody discovery as well as rational molecular engineering methods for optimizing their agonist activity.

Atorvastatin Reduces In Vivo Fibrin Deposition and Macrophage Accumulation, and Improves Primary Patency Duration and Maturation of Murine Arteriovenous Fistula.

BACKGROUND: Arteriovenous fistulas placed surgically for dialysis vascular access have a high primary failure rate resulting from excessive inward remodeling, medial fibrosis, and thrombosis. No clinically established pharmacologic or perisurgical therapies currently address this unmet need. Statins' induction of multiple anti-inflammatory and antithrombotic effects suggests that these drugs might reduce arteriovenous fistula failure. Yet, the in vivo physiologic and molecular effects of statins on fistula patency and maturation remain poorly understood. METHODS: We randomized 108 C57Bl/6J mice to receive daily atorvastatin 1.14 mg/kg or PBS (control) starting 7 days before end-to-side carotid artery-jugular vein fistula creation and for up to 42 days after fistula creation. We then assessed longitudinally the effects of statin therapy on primary murine fistula patency and maturation. We concomitantly analyzed the in vivo arteriovenous fistula thrombogenic and inflammatory macrophage response to statin therapy, using the fibrin-targeted, near-infrared fluorescence molecular imaging agent FTP11-CyAm7 and dextranated, macrophage-avid nanoparticles CLIO-VT680. RESULTS: In vivo molecular-structural imaging demonstrated that atorvastatin significantly reduced fibrin deposition at day 7 and macrophage accumulation at days 7 and 14, findings supported by histopathologic and gene-expression analyses. Structurally, atorvastatin promoted favorable venous limb outward remodeling, preserved arteriovenous fistula blood flow, and prolonged primary arteriovenous fistula patency through day 42 (P<0.05 versus control for all measures). CONCLUSIONS: These findings provide new in vivo evidence that statins improve experimental arteriovenous fistula patency and maturation, indicating that additional clinical evaluation of statin therapy in patients on dialysis undergoing arteriovenous fistula placement is warranted.

Understanding and overcoming trade-offs between antibody affinity, specificity, stability and solubility.

The widespread use of monoclonal antibodies for therapeutic applications has led to intense interest in optimizing several of their natural properties (affinity, specificity, stability, solubility and effector functions) as well as introducing non-natural activities (bispecificity and cytotoxicity mediated by conjugated drugs). A common challenge during antibody optimization is that improvements in one property (e.g., affinity) can lead to deficits in other properties (e.g., stability). Here we review recent advances in understanding trade-offs between different antibody properties, including affinity, specificity, stability and solubility. We also review new approaches for co-optimizing multiple antibody properties and discuss how these methods can be used to rapidly and systematically generate antibodies for a wide range of applications.