Abstract 1737: Understanding the geometry and valency of bispecific antibodies in the optimization of tumor-dependent activation of 4-1BB
Bibliographic record
Abstract
Abstract 4-1BB is a TNF family receptor expressed on the surface of tumor-infiltrating T cells. Activation of 4-1BB enhances the activation, metabolism and function of tumor-infiltrating T cells and promotes tumor regression. Several anti-4-1BB antibodies have entered the clinic and have suffered from liver toxicity or lack of activity. To address the clinical liabilities with 4-1BB targeting, we designed bispecific 4-1BB x tumor associated antigen (TAA) antibodies to selectively activate T cells within the tumor microenvironment. To understand the impact of antibody format on potency of T cell activation, we generated a panel of 4-1BBxTAA bispecific antibodies in different formats with the AzymetricTM and EFECTTM platforms. We compared potency and maximal activity of these constructs in co-culture assays with tumor cells and T or Jurkat reporter cells, in comparison to urelumab as a clinical benchmark. The AzymetricTM platform allowed the production and evaluation of unique antibody formats from which an extensive structure activity relationship analysis was performed. We also examined the accessible epitope space by sampling the possible paratope binding conformations of the molecule. From this we determined the geometric limits of antigen engagement. Bispecific antibody constructs utilizing monovalent 4-1BB targeting showed inferior activity than urelumab in co-culture assays with TAAhi tumor cells. Activity greater than urelumab was seen with constructs containing two 4-1BB arms with one or two TAA binding scFv on the C-terminus of the Fc. Bivalent 4-1BB antibodies with an anti-TAA scFv fused to the N-terminus of the 4-1BB Fab showed decreased activity, potentially due to reduced ability to engage 4-1BB in a bivalent manner. Critically, the activity seen was transferable across multiple TAAs. The activity of the 4-1BB bispecific constructs was dependent on the expression level of the TAA. Without the presence of tumor cells, or with constructs where the TAA scFv was replaced by an irrelevant scFv, minimal activity was seen. The modelling of the space accessible to the 4-1BB paratopes showed that the constructs with which we saw the most activity had a distance between 4-1BB and TAA binding paratopes similar to that seen between T and APC membranes as part of an immune synapse, suggesting that this may be a key characteristic for the development of conditional T cell agonist bispecifics. This work represents an investigation of 4-1BBxTAA formats which would be difficult to make without an efficient bispecific technology. We identified a series of 4-1BBxTAA bispecific agonist antibody formats which were transferable between multiple TAAs. These formats also allowed optimization of activity and selectivity to promote maximal therapeutic index and efficacy, key factors which are potentially able to contribute to improved clinical outcomes. Citation Format: Anna von Rossum, Harsh Pratap, Lisa Newhook, Elizabeth C. Halvorsen, Lee Freiburger, Renee Duan, Charles Stevens, Dimitri Tcaciuc, Gesa Volkers, Duncan Browman, Brandon Clavette, David Mills, Thomas Spreter, Daniel T. Patton. Understanding the geometry and valency of bispecific antibodies in the optimization of tumor-dependent activation of 4-1BB [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1737.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".