Abstract 5661: Pre-clinical development of a dopamine receptor 2, PD-1, and CD47 trispecific antibody for the treatment of solid tumors
Bibliographic record
Abstract
Abstract Multispecific antibodies can have multiple independent mechanisms of action to achieve better clinical outcomes in cancers with high unmet medical needs. Here we describe the preclinical development of a trispecific antibody (KJ-101) targeting dopamine receptor 2 (DRD2), PD-1, and CD47. DRD2 is a G protein-coupled receptor upregulated in many cancer types where it correlates with decreased patient survival. In pre-clinical studies, DRD2 is associated with cancer cell stemness and tumor growth. Clinical responses were achieved with small molecules targeting DRD2 and dopaminergic drugs for neuroendocrine tumors. In SCLC, representing 15% of lung cancers, 60-70% of patients showed high expression of DRD2. Checkpoint inhibition has shown some efficacy in lung cancer where PD-L1 inhibitors were approved as first-line therapy in SCLC. SCLC patients rapidly fail chemotherapy, develop resistance to treatment and metastases. These observations suggest a link between DRD2 expression and resistance to treatment, making this receptor an attractive target for multispecific antibody therapy. The VHH components of KJ-101 (anti-DRD2, anti-PD-1 and anti-CD47) produce multiple effects to achieve a strong anti-tumor activity. The anti-DRD2 VHH induces intracellular signaling and suppresses tumor growth via ADCC. Treatment with anti-DRD2 antibody significantly suppressed tumor growth in the DRD2-positive NCI-H510A SCLC model in SCID mice. The anti-PD-1 VHH restores T cell function, and the anti-CD47 VHH recruits T cells without their generalized activation and blocks the interaction between CD47 and SIRPα. The KJ-101 anti-tumor efficacy was tested in several in vivo immuno-oncology xenograft models of human SCLC or TNBC, reconstituted with human PBMC or with CD34+ hemopoietic stem cells. KJ-101 treatment led to tumor regression in the TNBC model, blocked metastases formation in CD34+ humanized NCG mice bearing established NCI-H69 tumors, and blocked metastases formation and increased survival in tail vein metastatic models of SCLC. KJ-101 is produced at a high yield (6 g/L) in a manufacturing cell line. Conventional purification yields 99% purity and notably displays high stability under accelerated stability testing. In conclusion, the trispecific KJ-101 antibody has strong in vivo anti-tumor activity mediated via multiple mechanisms of action, is easily expressed and purified, and is very stable. Together, this data supports the clinical development of KJ-101 in advanced metastatic neuroendocrine cancer indications, including SCLC. Citation Format: Shugang Yao, Hiba Zahreddine, Dominic Hou, Elijus Undzys, Liying Gong, Richard Wargachuk, Xiaowei Wang, Alex Zhou, Lucy Lai, Luis A. Da Cruz, David Young. Pre-clinical development of a dopamine receptor 2, PD-1, and CD47 trispecific antibody for the treatment of solid tumors. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5661.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".