Abstract B74: Investigating the role of tumor:bone microenvironment crosstalk in Ewing sarcoma progression
Notice bibliographique
Résumé
Abstract Background: Ewing sarcoma is the second most common pediatric bone cancer. Metastatic disease is almost always fatal, and there is currently no method to predict which patients are at risk for metastasis. Better therapies are needed to prevent and treat metastatic disease, which means the mechanisms that drive Ewing sarcoma metastasis must be better elucidated. It is becoming increasingly clear that interactions between tumor cells and the tumor microenvironment (TME) play an essential role in metastasis, but the specific mechanisms through which the TME contributes to Ewing sarcoma progression remain largely unknown. Our previous work has demonstrated that activation of canonical Wnt and TGF-β pathways in a subset of Ewing sarcoma cells induces changes in gene expression and protein secretion that are associated with enhanced metastatic engraftment, changes in the extracellular matrix (ECM), and increased angiogenesis. As bone, the primary site for Ewing sarcoma, is an excellent source of ligands for both pathways, we hypothesize that crosstalk between Wnt/TGF-β-activated tumor cells and the local bone microenvironment contributes to osteolysis and metastatic progression. Methods: Ewing sarcoma cells were treated with control or Wnt3a media +/- recombinant TGF-β1, and then the mRNA levels of target genes were measured by Q-RT-PCR. ELISA and Luminex assays were also performed to determine the levels of secreted proteins. Conditioned media collected from stimulated cells were used to treat osteoblast precursor cells, which were then assayed for effects on differentiation and function. Subcutaneous, femur, and vossicle transplant xenograft models were established in mice and are being validated. Results: We have demonstrated that in response to Wnt3a and TGF-β1, Ewing sarcoma cells upregulate expression of canonical Wnt targets (e.g., LEF1), ECM-associated genes (e.g., TNC, COL1A1, and MMP2), and the pro-osteolytic factor PTHrP. We have also shown that osteoblast precursor cells can be induced to differentiate in the presence of conditioned media from Ewing sarcoma cell lines. Immunohistochemical staining is being used to evaluate Wnt and TGF-β pathway activation, angiogenesis, osteolysis, and the ECM in our bone tumor xenograft models. Conclusions: Wnt3a/TGF-β1-stimulated Ewing sarcoma cells upregulate expression of genes associated with the ECM and osteolysis. We are in the process of demonstrating the functional consequences of those changes using in vitro conditioned media experiments and in vivo transplant models. Understanding the mechanisms by which these pathways contribute to Ewing sarcoma phenotypes is important for the development of new therapeutics for patients with metastatic disease. Citation Format: Kelsey Temprine, Sydney Treichel, Allegra Hawkins, Tahra Suhan, Wei Jiang, Parker Acevedo, Amy Koh, Kurt Hankenson, Laurie K. McCauley, Elizabeth R. Lawlor. Investigating the role of tumor:bone microenvironment crosstalk in Ewing sarcoma progression [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 B74.
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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».