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Enregistrement W2610673450 · doi:10.1182/blood.v128.22.3960.3960

A Novel Oncolytic Reovirus Immune Priming Strategy Dramatically Enhances the Efficacy of Anti-PD-L1 Antibody Therapy Against Multiple Myeloma

2016· article· en· W2610673450 sur OpenAlexaff
Kevin R. Kelly, Claudia M. Espitia, Weiguo Zhao, Valeria Visconte, Matt Coffey, Jennifer S. Carew, Steffan T. Nawrocki

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueVirus-based gene therapy research
Établissements canadiensOncolytics Biotech (Canada)
Organismes subventionnairesnon disponible
Mots-clésOncolytic virusMultiple myelomaBortezomibAntibodyCancerImmunotherapyIn vivoCancer researchImmunologyImmune systemMedicineBiologyVirologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Multiple myeloma (MM) is the second most common adult hematologic malignancy in the United States and is characterized by a unique form of progressive bone destruction. Despite the development of new treatments such as proteasome inhibitors and immunomodulatory agents, patients with high-risk disease have a median survival of only 2-3 years, highlighting the demand for more effective therapeutic strategies. Oncolytic viral formulations represent a promising new class of anticancer agents that may have important applications in precision medicine. Recent studies have demonstrated that reoviruses specifically replicate only in cancer cells and this led to the development of a reovirus-based oncolytic viral therapy called Reolysin. We have demonstrated that reoviruses selectively replicate in MM cells and Reolysin possesses significant activity in preclinical in vitro and in vivo MM models. These findings established the framework for an ongoing investigator-initiated phase 1b clinical study of Reolysin in combination with bortezomib and dexamethasone in patients with relapsed/refractory MM. Recent gene ontology analyses of RPMI-8226 and U266 MM cells treated with Reolysin revealed that reovirus exposure triggers a highly significant transient increase in CD274(programmed death 1 ligand, PD-L1) in MM cell lines. Reolysin-mediated PD-L1 upregulation was confirmed by immunoblotting, qRT-PCR, and flow cytometric analyses in MM cell lines and primary patient specimens treated with Reolysin. Increased PD-L1 expression was also detected by immunohistochemistry in MM tumor samples collected from mice treated with Reolysin. Adaptive resistance mediated by inhibitory ligands such as PD-L1 has emerged as an important mechanism of malignant cell survival and has led to the development of new agents that disrupt the PD-L1/PD-1 immune checkpoint. These agents have exhibited dramatic efficacy in certain forms of cancer including melanoma and lung cancer. Analysis of specimens from patients treated on clinical trials with these agents indicates that high basal expression of PD-L1 on tumor cells may be necessary to elicit significant clinical benefit. Notably, most MM cell lines and primary CD138+ cells from MM patients do not overexpress PD-L1 compared to normal plasma cells and this may preclude patients with MM from optimally benefiting from immune checkpoint therapy. However, novel immune priming strategies that stimulate transient upregulation of PD-L1 on malignant cells could potentially render agents that target the PD-L1/PD-1 axis significantly more effective for a broader range of malignancies including MM. We hypothesized that Reolysin could be used as a precision immune priming agent to potentiate the anti-MM efficacy of PD-L1 targeted therapy by rendering MM cells vulnerable to PD-L1 inhibition through the transient upregulation of target expression. To investigate this therapeutic approach, 5TGM1-luc murine MM cells were injected IV into immunocompetent mice to generate MM bone disease. After disease was established, mice were randomized into groups and treated with vehicle, Reolysin (5 x 108 TCID50, Q7D), murine anti-PD-L1 antibody (200 mg/mouse, Q2D) or the combination for 5 weeks. Mice treated with the combination demonstrated decreased disease burden as measured by bioluminescent imaging and also showed reduced IgG2bk levels (specific IgG secreted by 5TGM1 cells) by ELISA. Importantly, the combination also led to increased overall animal survival compared to vehicle control and either single agent treatment (P<0.01). Analysis of bone marrow specimens from mice in all experimental groups showed that Reolysin stimulated elevated PD-L1 levels in vivo in a manner that was directly linked to the enhanced efficacy of the combination. Our findings demonstrate that Reolysin has dramatic PD-L1-related immune priming effects in clinically relevant models of MM and support its use as a precision agent to sensitize MM cells to immune checkpoint therapy. Based on these promising data, we are currently planning a clinical study of Reolysin in combination with bortezomib and a PD-1 inhibitor in patients with relapsed/refractory MM. Disclosures Kelly: Novartis: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees. Coffey:Oncolytics Biotech: Employment.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,311
Écart entre enseignants0,288 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2016
Routes d'admission1
Résumé présentoui

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