Abstract P200: Pre-clinical development of a dopamine receptor 2, PD-1 and CD47 trispecific antibody for treatment of small cell lung cancer
Notice bibliographique
Résumé
Abstract We developed a single domain VHH multi-specific antibody format. Multispecific antibodies have multiple mechanisms of action which may work independently or together, to achieve better clinical outcomes in cancers with high unmet medical need such as SCLC. Here we describe the preclinical development of a trispecific antibody (KB-436) that targets 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. 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 including to immunotherapy associated with lack of tumor infiltrating immune cells, appearance of metastases and large numbers of circulating tumor cells. These observations suggest a link between DRD2 expression and resistance to treatment, making this receptor an attractive target for a multispecific therapy. CD47 is overexpressed by many cancers and is also expressed on lymphocytes. Here, targeting CD47 is integral to T-cell engagement and redirection, in a mechanism distinct from CD3 mediated T-cell engagement. The VHH modules of KB-436 (anti-DRD2, anti-PD-1 and anti-CD47) mediate multiple mechanisms of action to achieve anti-tumor effect. The anti-DRD2 VHH induces intracellular signaling, the anti-PD-1 VHH restores T cell function, and the anti-CD47 VHH recruits T cells without their generalized activation and blocks interaction of CD47 with SIRPa. Treatment with anti-DRD2 antibody significantly suppressed tumor growth in the DRD2-positive NCI-H510A SCLC model in SCID mice. KB-436 anti-tumor efficacy was tested in several in vivo immuno-oncology xenograft models of human SCLC and other solid tumors , reconstituted with human PBMC or with CD34+ hemopoietic stem cells. Treatment suppressed tumor growth, enhanced the in vivo effect of cisplatin-treatment in a less chemosensitive NCI-H69 variant, 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. Trispecific KB-436 has a half-life in mice of around 5 days similar to that of other antibodies. It is produced at 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 KB-436 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 KB-436 in advanced metastatic solid cancer indications, including SCLC. Citation Format: Shugang Yao, Yun Cui, Anna Kazanats, Liying Gong, Claire Bonfils, Dominic Hou, Emily Chen, Elijus Undzys, Jacynthe Toulouse, Milica Krstic, Hiba Zahreddine, Israel Matos, Alex Zhou, Aniel Moya-Torres, Richard Wargachuk, Carl Gay, Lauren Byers, Gordon Ngan, Luis da Cruz, David Young. Pre-clinical development of a dopamine receptor 2, PD-1 and CD47 trispecific antibody for treatment of small cell lung cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P200.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».