Abstract PR19: Utilizing novel oncolytic vaccinia virus for selective expression of immunotherapeutic payloads in metastatic tumors
Notice bibliographique
Résumé
Abstract The treatment paradigm for patients with metastatic cancer has evolved rapidly with the approval of agents targeting CTLA-4 and the PD-1/L1 immune checkpoint axis. Despite the profound impact these agents have had, they are minimally effective in the majority of cancer patients. Rational combinations of complementary immune-modulating agents have thus far not led to clear patient benefit, and newer technologies that are better able to safely combine multiple modes of action could well prove to be vital. Oncolytic viruses (OVs) have the capacity to be the ideal therapeutic partner for immune checkpoint therapeutics in several ways. First, on their own OVs can “heat up” immunologically “cold” tumors by initiating a proinflammatory infection within the tumor microenvironment (TME). Second, some OVs can be engineered to strategically express one or more immune-modulating molecules. Finally, certain OVs have the capacity to be delivered systemically and thus enhance immune cell recruitment and activation in all metastatic sites. We have selected a novel vaccinia virus as our therapeutic OV platform and are using it to engineer multi-mechanistic cancer therapeutics. Previously it has been demonstrated that oncolytic vaccinia viruses can be delivered systemically and spread within metastatic lesions. These clinical candidates, however, contain multiple potent immune-suppressive genes. Furthermore, in clinical studies some of these therapeutics exhibited off-tumor infections (e.g., pox lesions), which may ultimately limit their ability to be used to deliver potent immune modulators. We used a combination of functional genomics and bio-selection strategies to generate a novel oncolytic vaccinia backbone (termed SKV) containing a large genome deletion that exhibited augmented oncolytic activity and improved tumor selectivity. Our new best-in-class vaccinia robustly stimulates anti-immune responses, rapidly spreads within and between tumors, and has a substantially improved preclinical safety profile when compared to other vaccinia clinical candidates. As predicted, SKV synergizes well with immune checkpoint inhibitor antibodies and potently activates human immune cells. Due to the exquisite tumor selectivity of SKV, we have been able to engineer and express three potent immune modulators that are safest and most effective when expressed within the TME: anti-CTLA4 antibody, membrane tethered IL-12, and the antigen-presenting cell-activating ligand FLT-3L. Tumor-selective transgene expression has been demonstrated in murine tumor models in which therapeutic payload concentrations (e.g., >1 ug/ml IL-12) were achieved within the TME without any detectable transgene product in the systemic circulation (serum). Expression of the therapeutic payloads increased survival versus the SKV backbone control in an immunocompetent, syngeneic tumor model. Ongoing toxicity and efficacy studies are being carried out prior to clinical evaluation of the novel virus construct. This abstract is also being presented as Poster A02. Citation Format: Adrian Pelin, Mike Huh, Matt Tang, Fabrice LeBouef, Brian Keller, Jessie Duong, Katherine Knowles, Julia Petryk, Vicki Jennings, Alan Melcher, Ragunath Singaravelu, Mathieu Crupi, Larissa Pikor, Caroline Breitbach, Steven Bernstein, Michael Burgess, John C. Bell. Utilizing novel oncolytic vaccinia virus for selective expression of immunotherapeutic payloads in metastatic tumors [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr PR19.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».