Abstract 1005: The bispecific antibody zanidatamab's (ZW25's) unique mechanisms of action and durable anti-tumor activity in HER2-expressing cancers
Bibliographic record
Abstract
Abstract HER2-directed therapies have improved clinical outcomes for many patients with HER2-positive breast and gastric cancer. Despite these successes, there remains a need to develop improved HER2-targeted therapies for these and other HER2-expressing tumors, particularly in the setting of recurrent or metastatic disease. Zanidatamab (ZW25) is a humanized, bispecific, immunoglobulin (Ig) G1-like antibody directed against the juxtamembrane extracellular domain (ECD4) and the dimerization domain (ECD2) of human epidermal growth factor receptor 2 (HER2), the same domains targeted by trastuzumab (T) and pertuzumab (P), respectively. Data from the ongoing phase 1 study (NCT02892123) demonstrate that zanidatamab is well tolerated and has single agent activity in patients with advanced HER2-expressing cancers that have progressed after standard of care (SOC) therapies, including HER2-targeted agents such as T, P, and trastuzumab emtansine.1,2 We have previously shown that the unique design and bispecific binding of zanidatamab results in multiple mechanisms of action including increased antibody binding density, potent effector function, improved receptor internalization and HER2 downregulation relative to T.3 To better understand the mechanism by which zanidatamab differentiates itself from T, P and T+P, we recently expanded our mechanistic evaluations including cell surface HER2 aggregation, complement-dependant cytotoxicity (CDC) and inhibition of both tumor cell growth and intracellular signaling. Single molecule-sensitive direct stochastic optical reconstruction microscopy (dSTORM) was used to map HER2 receptor distribution and quantitate the size, density, and frequency of receptor clusters induced by antibody binding. In vitro assessments were performed in a panel of HER2-expressing cell lines using standard assays including CDC with human complement serum and inhibition of both tumor cell growth and intracellular signaling. Using dSTORM, we observed that zanidatamab binding resulted in enhanced HER2 aggregation and distinct HER2 capping on the tumor cell surface compared to T, P or T+P. Evaluation of CDC activity in HER2-overexpressing tumor cells demonstrated that zanidatamab, but not T, P or T+P, elicited CDC suggesting that the enhanced HER2 aggregation and capping on the tumor cell surface provides high avidity docking sites to which C1 binds and is activated. Zanidatamab showed further differentiation in the inhibition of both tumor growth and intracellular signaling of HER2-overexpressing cells compared to T, P and T+P. Zanidatamab has novel cell surface binding and additional mechanisms of action compared to T, P and T+P. Zanidatamab is actively being evaluated in clinical trials in multiple HER2-expressing solid tumors, including a registration-enabling clinical trial in HER2 gene amplified biliary tract cancer (NCT04466891). Citation Format: Nina E. Weisser, Grant Wickman, Libin Abraham, Jason O'Toole, Bryant Harbourne, Joy Guedia, Chi Wing Cheng, Peter Chan, Duncan Browman, Michael R. Gold, Neil Josephson, Surjit Dixit, Gerry Rowse. The bispecific antibody zanidatamab's (ZW25's) unique mechanisms of action and durable anti-tumor activity in HER2-expressing cancers [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 1005.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".