Abstract B101: Novel oncolytic vaccinia virus platform for systemic delivery of immunotherapeutic payloads
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 pro-inflammatory 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 certain oncolytic vaccinia viruses can be delivered systemically and spread within metastatic lesions. These early clinical viruses, however, contain multiple potent immune suppressive genes and are not ideal for the generation of antitumor immune responses “in situ.” 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 optimize the vaccinia virus platform. Initially we developed a fitness assay to identify the vaccinia strain with the best ability to replicate in and kill both established cancer cell lines and cancer patient tumor explants. Next, we used a transposon insertion strategy and deep sequencing of viral populations to systematically examine the role of each vaccinia virus gene in its ability to be an anticancer therapeutic. Ultimately, we identified large regions (25Kb) of the vaccinia genome that when deleted, augment the oncolytic activity of a newly generated vaccinia backbone termed SKV. Our new best-in-class vaccinia, SKV, 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 from the backbone a combination of very potent immune modulators that are safest and most effective when expressed within the TME. These include an immune checkpoint inhibitor, a membrane tethered cytokine and antigen-presenting cell activating ligand in a single virus. Ongoing toxicity and efficacy studies are being carried out to prepare our novel virus construct for clinical launch. Citation Format: John C. Bell, Adrian Pelin, Michael Huh, Matthew Tang, Fabrice Le Boeuf, Brian Keller, Jessie Duong, Katherine Clark-Knowles, Julia Petryk, Victoria A. Jennings, Alan Melcher, Mathieu Crupi, Larissa Pikor, Caroline Breitbach, Steven Bernstein, Michael Burgess. Novel oncolytic vaccinia virus platform for systemic delivery of immunotherapeutic payloads [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B101.
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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) | 0,000 | 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».