Abstract 3127: Development of three-dimensional cancer cell line spheroid models for the <i>in vitro</i> functional characterization of cytotoxic antibody-drug conjugates
Notice bibliographique
Résumé
Abstract Background: Antibody-drug conjugates (ADCs) are an effective class of cancer therapeutics which have gained prominence for the treatment of several malignancies. A cytotoxic ADC consists of a linker-payload conjugated to a monoclonal antibody, which targets a distinct tumor-associated antigen (TAA) to enable the delivery of the cytotoxic payload to cancer cells. Presently, there is a need for in vitro models that better recapitulate in vivo tumor tissue complexity to aid in the screening and evaluation of ADCs during preclinical development. Hence, efforts have been made to develop in vitro three-dimensional (3D) models with improved translation to in vivo tumor models compared to traditional two-dimensional (2D) cancer cell line monolayer models. We aimed to generate monoculture cancer cell line spheroids in a high-throughput manner. Subsequently, we sought to evaluate the spheroid penetration capability of structurally distinct ADCs and to assess the 3D cytotoxic activity of a variety of microtubule inhibitor (MTI) and topoisomerase 1 inhibitor (TOPO1i)-bearing ADCs targeting multiple TAAs, comparing to activity in 2D models. Methods: Monoculture cancer cell spheroids were generated by seeding cells from a variety of tumor types, using an automated liquid-handling robot, into microtiter plates treated with ultra-low attachment coating, which allows for scaffold-free self-assembly of cancer cells into a 3D arrangement. Following spheroid formation by incubation for 2-3 days under standard culturing conditions, spheroids were treated with ADCs at a range of concentrations for functional evaluation: the spheroid penetration capability of ADCs of different antibody formats was assessed using high-content confocal imaging of spheroids treated with fluorescently labeled antibodies; the cytotoxic activity of ADCs was characterized using an ATP quantification luminescent reagent, live/dead cell fluorescent stains, and confocal imaging. Results: Monoculture spheroids of varying morphologies were successfully and reproducibly generated with a large panel of >50 cancer cell lines derived from >10 tumor types. Antibodies with different formats demonstrated target-mediated binding and a range of spheroid penetration depths. Additionally, MTI and TOPO1i ADCs evaluated in a panel of cancer cell spheroids demonstrated robust 3D cytotoxicity and differentiated activity when compared to the 2D monolayer assay. In a number of cases, the potency trends across multiple ADCs in 3D cytotoxicity assays were more predictive of in vivo efficacy compared to the 2D assay. Taken together, our high-throughput spheroid assays present important and straightforward in vitro tools to aid in the screening and selection of therapeutic cytotoxic ADC candidates for the treatment of solid tumors. Citation Format: Jodi Wong, Andrea Hernández Rojas, Allysha Bissessur, Lemlem T. Degefie, Araba P. Sagoe-Wagner, Samir Das, Vincent Fung, Kevin Yin, Renee Duan, Sam Lawn, Laurence Madera, Catrina Mi Jung Kim, Alex Wu, Mark E. Petersen, Raffaele Colombo, Jamie R. Rich, Stuart D. Barnscher. Development of three-dimensional cancer cell line spheroid models for the in vitro functional characterization of cytotoxic antibody-drug conjugates [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3127.
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) | 0,001 | 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 ».