Abstract A068: Determinants of efficacy in cancer immunovirotherapy
Notice bibliographique
Résumé
Abstract Replicating oncolytic viruses (OVs) are emerging as a promising therapeutic approach for different tumor entities. Positive data from numerous clinical studies are accumulating and as a first-in-class oncolytic herpes virus encoding GM-CSF, Talimogene Laherparepvec (T-VEC), has been approved for treatment of unresectable melanoma by the U.S. Food and Drug Administration at the end of 2015. Although it has been recognized that combinations of OVs with different immunomodulators can significantly improve therapeutic outcome, understanding of immune effector mechanisms determining success of a particular approach remains limited, restricting the development of rational combination strategies. In this study we aimed to determine the most beneficial immunomodulation strategies for combination with oncolytic measles virus (MeV). Furthermore, we performed a comprehensive analysis of anti-tumor immune effector mechanisms associated with response to pinpoint mechanisms crucial for therapeutic efficacy. We developed MeV Schwarz vaccine strain vectors (MeVac) encoding different immunomodulators to target the main phases in establishment of an anti-tumor immune response: GM-CSF - to enhance maturation of antigen-presenting cells, an IL-12 fusion protein (FmIL-12) and IP-10 - to enhance immune effector cell responses, antibodies against CTLA-4 and PD-L1 and a soluble form of CD80 - to counteract immunosuppression in the tumor microenvironment. Therapeutic efficacy of the novel vectors was evaluated in the fully immunocompetent murine colon adenocarcinoma model MC38cea. MeVac encoding anti-PD-L1 and FmIL-12, respectively, were identified as the most effective therapeutics. Notably, MeVac encoding FmIL-12 showed a superior therapeutic efficacy, achieving 90% complete remissions of established tumors. Animals treated with the immunomodulatory MeVac vectors rejected secondary tumor engraftments, indicating establishment of protective anti-tumor immunity. Higher IFN-γ production upon restimulation of splenocytes with tumor cells in vitro was observed for animals treated with MeVac FmIL-12 in comparison to treatment with MeVac anti-PD-L1 and a control vector encoding constant region of antibody (MeVac IgG1-Fc), indicating establishment of a more potent memory response. Intratumoral cytokine profiling with cytokine bead arrays revealed upregulation of the effector cytokines IFN-γ and TNF-α after treatment with MeVac FmIL-12. A massive decrease in intratumoral natural killer (NK) cell counts and an increase of activation marker CD69 expression on NK cells as well as an increase in T cell amount was observed in flow cytometry analysis one day after treatment with MeVac FmIL-12. This indicates early direct activation of these lymphocyte subsets through direct IL-12 signaling. An increase in intratumoral T cells and a decrease in NK cells and activated cytotoxic T cells (CD8+CD69+) was observed four days after the last treatment with both MeVac anti-PD-L1 and MeVac IgG1-Fc, with slightly more pronounced effects in the MeVac anti-PD-L1 group. This suggests that MeVac vectors per se activate T and NK cell responses, which can further be supported with PD-L1 blockade. This study establishes MeVac encoding FmIL-12 as a potent immunomodulatory oncolytic vector and provides insights into its mechanisms of action, thereby creating a basis for further rational vector modifications to translate immunomodulatory MeV into clinical application. Citation Format: Rūta Veinalde, Christian Grossardt, Marie-Claude Bourgeois-Daigneault, Christof von Kalle, Dirk Jaeger, Guy Ungerechts, Christine E. Engeland. Determinants of efficacy in cancer immunovirotherapy [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A068.
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 | 0,001 | 0,001 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».