Abstract 958: Myeloid cell populations drive early Vaccinia-induced anti-tumor responses differentially based on tumor cell immunogenicity
Notice bibliographique
Résumé
Abstract Cancer poses an enormous burden on the healthcare system, with approximately 1 in 5 people worldwide expected to develop cancer in their lifetime according to the World Health Organization. Given this, there is a significant need for new therapeutics that are highly selective and evade tumor resistance to therapy. Oncolytic viruses (OVs) have been shown to selectively target and kill cancer cells while simultaneously activating local and systemic immune responses. Among these, Vaccinia (VACV) virus is a potential OV candidate with a high safety profile and a large genome, providing opportunities for genetic modification. However, in clinical trials it has shown to have limited success. To improve its efficacy, we need a more thorough understanding of VACV’s immunomodulatory activity both within and across distinct tumor microenvironments (TME). In these studies, we treated weakly immunogenic (B16-F10) and highly immunogenic (MC38) tumors with a mouse-adapted wild-type VACV (3 intratumoral injections, 48 hours apart). Changes in immune cell infiltration and tumor associated macrophage (TAM) activation were assessed in tissues collected 24 hours after each injection and up to 21 days after completion of the treatment regimen. We found that VACV treatment significantly reduced tumor volume and was associated with an early influx of CD45+ cells across both models. This infiltration occurred earlier, was more pronounced, and lasted longer in MC38 vs. B16-F10 tumors. While both models were associated with a significant decrease in the relative frequency of immunosuppressive TAMs (24 hours after first injection), VACV treatment of MC38 tumors was associated with higher and more sustained levels of newly recruited inflammatory monocytes. Similarly, the MC38 TME maintained higher levels of activated TAMs (↑CD80/CD86 expression) and sustaining this phenotype for a longer period. Importantly, these changes were linked to increased infiltration of CD8 T cells, anti-tumor immune responses and a slower rebound of tumor growth (>2 weeks). Collectively, our results suggest that VACV treatment can help limit tumor growth in both MC38 and B16-F10 models but that the anti-tumor response is more pronounced and sustained in highly vs. weakly immunogenic tumors. This increased activity is not dependent on early loss of immunosuppressive TAMs but is dependent on the increased recruitment of inflammatory monocytes and the maintenance of activated TAMs in the TME. Further studies are required to assess the specific contribution of these cells in driving anti-tumor immune responses and whether sustained viral replication is required for these processes. Citation Format: Duale Ahmed, Robyn Skillings, Omar Abdo, Aroosha Fareghdeli, Zoya Versey, Alicia Boxma, Leila Mostaço-Guidolin, Edana Cassol. Myeloid cell populations drive early Vaccinia-induced anti-tumor responses differentially based on tumor cell immunogenicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 958.
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) | 0,002 | 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 ».