Abstract 6012: PSMA x CD3 T-cell engagers show preclinical efficacy for the treatment of prostate cancer
Bibliographic record
Abstract
Abstract Prostate-specific membrane antigen (PSMA) is a clinically validated target in metastatic castration-resistant prostate cancer (mCRPC) that is being prosecuted by a number of different modalities in the clinic. CD3 T-cell engagers (TCEs) targeting PSMA have shown promise in preclinical and early clinical studies, but generating a molecule with a therapeutic window that enables efficacious dosing in patients has been a barrier to development. Here, we present preclinical in vitro and in vivo data on novel PSMA x CD3 TCEs developed using our TCE platform. To address the challenges of TCE development for mCRPC, we screened and identified hundreds of diverse PSMA- and CD3-binding antibodies with different affinities, epitopes, and biophysical properties using our proprietary antibody screening platform. From there, we engineered large panels of OrthomabTM PSMA x CD3 bispecifics, varying TCE parameters that impact function. Detailed in vitro functional assessment and biophysical characterization assays were conducted to identify antibodies with promising functional and developability profiles. IgG-like bispecifics comprised of PSMA- and CD3-binding arms with finely tuned affinity for each target were generated. PSMA binding epitopes were assessed using cryo-electron microscopy, and TCE function was measured using in vitro T cell co-culture assays. TCEs binding membrane-proximal epitopes drove optimal immune synapse formation, leading to potent killing of cells expressing high (C4-2) and low (22Rv1) levels of PSMA with EC50 values in the picomolar range. Molecules show target-dependent T-cell activation with no killing of a low PSMA-expressing cell line (DU-145) in vitro. Further, select molecules show robust CD4+/CD8+ T-cell activation and proliferation in the presence of target cells, as well as sustained killing of target cells over time in a repeat challenge assay. Finally, molecules evaluated in vivo in a humanized C4-2 xenograft mouse model demonstrated anti-tumor activity and a favorable IgG-like pharmacokinetic profile. In summary, we engineered and assessed hundreds of PSMA x CD3 TCEs at high-throughput, conducted detailed in vitro functional and biophysical characterization, and identified molecules with promising preclinical in vivo efficacy that supports further evaluation and development towards the clinic. Citation Format: Peter Bergqvist, Alaa Amash, Kelly Bullock, Lauren Clifford, Patrick Farber, Jessica Fernandes Scortecci, Ingrid Knarston, Tallie Kuang, Ahn Lee, Amy Lee, Cindy-Lee Crichlow, Franco Li, Matt Mai, Stephanie K. Masterman, Janice Reimer, Eduardo Solano Salgado, Raffi Tonikian, Christopher Williamson, Allison Goodman, Lindsay DeVorkin. PSMA x CD3 T-cell engagers show preclinical efficacy for the treatment of prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6012.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".