Abstract B001: Comparative exploration of cultured spheroids and organoids as models to study epithelial ovarian cancer pathobiology
Notice bibliographique
Résumé
Abstract Epithelial ovarian cancer (EOC) is a devastating disease with a unique metastatic progression involving spheroids. Our extensive research into spheroid pathobiology has provided insight into several molecular and cellular changes implicated during EOC metastasis. We speculate that EOC cells change between tumor and spheroid states to withstand stress and promote cell survival during metastasis, yet this switching behavior is not fully understood. Established high-grade serous (OVCAR3, OVCAR4, OVCAR8) and new ascites-derived iOvCa cell lines (n=7) were used to generate spheroids in suspension on Ultra-Low Attachment® plates and organoids using modified patient-derived organoid (PDO) culture conditions. Brightfield microscopy with our Incucyte® S3 Organoid Module, immunohistochemistry (IHC), and immunofluorescence (IF) were conducted for morphological comparisons between spheroids and organoids. Immunoblotting was performed to evaluate bioenergetic stress and autophagy, which are both altered processes in spheroids from our previous studies. OVCAR8 CRISPR knockout cell lines (for STK11, CAMKKβ, and ULK1) were also used for a more in depth look at these pathways. Bulk RNA-sequencing was completed on the seven iOvCa cell lines and three recently developed PDOs, with subsequent bioinformatics analyses, to discover new implicated pathways in EOC disease progression. Organoids appeared heterogeneous in morphology with dense, cystic, or mixed phenotypes, whereas spheroids often existed as compact, grape-like clusters, or sparse structures. There were also clear differences in growth dynamics, proliferative capacity based on IHC of Ki67, and fibronectin deposition based on IF staining within each 3D spheroid and organoid structure. Interestingly, established EOC cell lines and patient ascites-derived iOvCa182 and iOvCa246 organoids have higher AMP-activated protein kinase (AMPK) T172 phosphorylation as compared with spheroids, however the remaining iOvCa cell lines exhibited increased AMPK activity in spheroids only. This indicates reliance of bioenergetic stress mainly in our spheroids and increased use of patient-derived samples in current EOC research. Lastly, transcriptomic analyses of our seven iOvCa cell lines showed elevated pathways for G2M checkpoint and E2F targets in organoids compared to spheroids, which could provide a new avenue for targeted therapeutics on EOC cells. The EOC cellular adaptations during disease progression have become more apparent as the phenotypic and molecular differences of spheroids and organoids are uncovered in this study, as well as the patient’s heterogeneity. Our results show that being able to target both proliferative and dormant cells is very important in developing new treatment options. Therefore, parallel assays of spheroid and organoid models will be crucial experimental systems to discover new therapeutic vulnerabilities in advanced EOC disease. Citation Format: Emily Tomas, Yudith Ramos-Valdes, Jennifer Davis, Bartlomiej Kolendowski, Gabriel E. DiMattia, Trevor G. Shepherd. Comparative exploration of cultured spheroids and organoids as models to study epithelial ovarian cancer pathobiology [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr B001.
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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,002 |
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 ».