Abstract B016: Cytokines derived from tumor-initiating osteosarcoma cells mediate a novel self-seeding mechanism relevant to growth of primary and metastatic tumors
Notice bibliographique
Résumé
Abstract Osteosarcoma is the most common pediatric bone tumor. Death from osteosarcoma is almost always due to metastatic spread to the lungs, which largely occurs after the primary tumor has been resected and treated with chemotherapy. Others have suggested that the primary tumor elaborates factors that suppress metastasis, though mechanisms explaining this phenomenon have not been well-validated suggested that primary osteosarcoma tumors suppress metastasis by recruiting circulating tumor cells back to the tumor via self-seeding, though the mechanism(s) of recruitment remained poorly defined. We found that osteosarcoma cells induce chemotaxis of other osteosarcoma cells in vitro. We previously demonstrated that osteosarcoma cells produce IL6 and CXCL8. Here, we found that both cytokines induced chemotaxis of osteosarcoma cells. Conversely, inhibition of both cytokines prevented osteosarcoma-induced osteosarcoma chemotaxis. These results suggested a model wherein tumor cells attract other tumor cells via inflammatory cytokine signaling. Within a living organism, such mechanisms might have implications for therapy. We wondered whether resection of a primary osteosarcoma tumor might redirect circulating tumor cells from the primary tumor to the lung (the “next best” site). To test this hypothesis, we generated orthotopic tibial tumors in mice. One cohort of mice underwent amputation of the primary tumor while another retained their primary tumors. At euthanasia, mice that underwent amputation had significantly increased tumor cell burden in the lungs. In separate experiments, lungs from mice with established primary tumors showed significantly less osteosarcoma lung burden than was seen in mice that did not have a primary tumor. Many infiltrating (labeled) tumor cells were subsequently identified within the primary tumor, strongly supporting the self-seeding model. Finally, we asked whether this same self-seeding mechanism might drive events important to lung metastasis. To test this hypothesis, mice were first inoculated with green-labeled osteosarcoma cells to induce lung metastasis. Fourteen days later, the same mice received inoculation with red labeled osteosarcoma cells. Strikingly, we found that lesions contained many more red- than green-labeled osteosarcoma cells. In addition, we have demonstrated that inhibition of IL6/CXCL8 blocks circulating tumor cell recruitment to established lung niches. This suggests circulating tumor cells preferentially target an established niche within the lung in an IL6/CXCL8 dependent manner in the absence of a primary tumor. Collectively, our data suggest that a loss of self-seeding in osteosarcoma on the excision of the primary tumor increases the metastatic burden. We are now exploring ways to leverage this biology in the development of novel therapies that prevent metastatic disease. Citation Format: Ryan D. Roberts, Amy C. Gross, James B Reinecke, Amanda Saraf. Cytokines derived from tumor-initiating osteosarcoma cells mediate a novel self-seeding mechanism relevant to growth of primary and metastatic tumors [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B016.
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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) | 0,001 | 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) | 0,003 | 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 ».