Abstract B44: Role of EMT transcription factors in the metastatic potential of osteosarcoma
Notice bibliographique
Résumé
Abstract Objective: The main culprit for mortality in osteosarcoma (OS) is metastatic pulmonary disease, which originates from a highly selected group of tumor cells that acquire a heightened ability to migrate from the primary tumor, intravasate, and survive in the bloodstream while circulating to remote sites. The early steps of this process are thought to be regulated by epithelial-to-mesenchymal translation (EMT)-related transcription factors (EMT-TFs), which can surprisingly occur in nonepithelial malignancies such as glioma, leukemia, and sarcoma. To determine how EMT-TFs and other mediators of stemness contribute to the early steps of tumor metastasis, drug resistance, and ultimately to the shedding of circulating tumor cells (CTC), we explored the presence and role of these EMT-TFs such as SNAIL, ZEB1, TWIST, and AXL in OS. Methods: The acellularized rat lung (ACL) model used in our research provided a unique ability to isolate and characterize thousands of lab-derived circulating tumor cells (dCTCs) and compare them to the primary tumors formed in rat lung by injecting OS-D OS cell line. Expression of EMT-TFs (SNAIL, ZEB1, TWIST, AXL) in cells cultured in 2D monolayer, primary tumors (PT) formed in acellularized lung, and the derived CTCs were evaluated by immune-fluorescence (IF) staining using confocal microscopy and quantified by IMARIS software. We also compared the level of expression of EMT-TFs in parental OS cell line MG63, and its derivative metastatic cell lines MG63.2 and MG63.3 by IF and Western blotting. Circulating tumor cells were also isolated from OS patients for IF analysis of EMT-TFs and compared with their paired primary tumor. Results: The dCTCs collected from ACL OS model showed substantially higher expression of SNAIL, TWIST, and AXL, as well as considerably higher expression of ZEB1 compared with cells from 2D culture and PTs. AXL showed significantly increased expression in metastatic cell lines MG63.2 and MG63.3 compared with the parental cell line MG63. ZEB1, TWIST, or SNAIL did not replicate this difference in expression, likely due to the phenotypic changes that cells undergo when grown on the 2D monolayer. Results from the ACL experiments were validated by comparing the expression of AXL, TWIST, and ZEB1 in CTCs collected from patients with a limited set of paired primary patient tumors. Conclusion: An ACL model of the lung microenvironment yielded an opportunity to characterize lab-derived CTCs, using techniques that cannot readily be achieved from clinical specimens. Surprisingly, EMT-TFs were enriched in dCTCs, an important finding that suggests a small subset of OS cells—which are already high grade—can become even more stem-like as they navigate the initial steps required of early metastasis. Though we have just begun to validate this result using paired tumor/CTC clinical samples, early evidence confirms our lab findings. The identification of EMT-TF in OS CTCs suggests that antagonists of AXL, ZEB, or TWIST might impede the earliest steps in the metastatic cascade. Citation Format: Sana Mohiuddin, Salah-Eddine Lamhamedi-Cherradi, Dhruva K. Mishra, Kristi Pence, Sandhya Krishnan, Brian A. Mnegaz, Alejandra Ruiz Velasco, Danh Dinh Troung, Branko Cuglievan, Amelia Vetter, Eric R. Molina, Min P. Kim, Joseph A. Ludwig. Role of EMT transcription factors in the metastatic potential of osteosarcoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B44.
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 | 0,000 |
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 ».