Abstract 760: Conjugation of daratumumab with 225actinium greatly increases its antitumor activity against multiple myeloma tumors
Notice bibliographique
Résumé
Abstract Daratumumab is a human cytolytic antibody specific for CD38 that is used clinically for treatment of patients with multiple myeloma (MM). Current therapeutic regimens require multiple injections over months of treatment. Increasing the potency of daratumumab to shorten the length of treatment would be beneficial. 225Ac is an alpha-particle emitting radionuclide that has potent cytotoxic activities over short distances, allowing for precise targeting of a lethal dose of radiation. Previously we have established that labeling daratumumab with 225Ac increased more than 10-fold its ability to kill MM cell lines in vitro (ASH 2017, Poster Number 4427). In this study we evaluated the ability of 225Ac-daratumumab to kill established tumors in mice. Mice deficient in T- and B-cells were injected subcutaneously with human MM tumor cells and once tumors reached an average volume of ~200 mm3, mice were treated with the 225Ac-daratumumab. To determine the localization of daratumumab within the tumor-bearing mice it was labeled with 111In, an γ-emitting radioisotope. 111In-daratumumab can be easily imaged and is used as a surrogate to estimate the localization of 225Ac-daratumumab. The distribution of the 111In-daratumumab was then followed for 10 days using a microSPECT/CT scanner. To evaluate the antitumor ability of the 225Ac-daratumumab, tumor-bearing mice were injected with 225Ac-daratumumab at a dose of of 400 nCi/0.3 μg of antibody, and 200 nCi/0.3 μg of antibody. As a control, mice were injected with either saline or an equivalent amount of unlabeled daratumumab. In addition, a group of mice was also treated with 30 times greater dose of unlabeled daratumumab (10 μg) - a dose which was previously shown to be effective against established tumors. 111In-daratumumab begun to accumulate in the tumor 24 hours after intraperitoneal injection and by 7 days was exclusively present in the tumor. The growth of the tumors in mice treated with 400 nCi/0.3 μg was significantly retarded compared to mice treated with equal concentration of unlabeled daratumumab or saline. Tumor growth was similar between mice treated with 400 nCi/0.3 μg of 225Ac-daratumumab and mice treated with 10 μg of unlabeled daratumumab. In conclusion, this study shows that labeling daratumumab with 225Ac increases its antitumor activity ~30-fold. This study suggests that approach to increase the potency of daratumumab via 225Ac labeling could greatly reduce the amount of daratumumab treatment needed in the clinic. This study also highlights the potential of targeting α-emitters to tumors as a viable therapeutic approach. Citation Format: Wojciech Dawicki, Kevin Allen, Rubin Jiao, Mackenzie Malo, Keisha Thomas, Mark S. Berger, Ekaterina Dadachova. Conjugation of daratumumab with 225actinium greatly increases its antitumor activity against multiple myeloma tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 760.
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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».