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Record W4220684155 · doi:10.1016/j.omto.2022.03.006

IFNAR blockade synergizes with oncolytic VSV to prevent virus-mediated PD-L1 expression and promote antitumor T cell activity

2022· article· en· W4220684155 on OpenAlexaff
Nader El-Sayes, Scott R. Walsh, Alyssa Vito, Amir Reihani, Kjetil Ask, Yonghong Wan, Karen Mossman

Bibliographic record

VenueMolecular Therapy — Oncolytics · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsOncolytic virusVirotherapyBlockadeImmunotherapyCancer researchMonoclonal antibodyInterferonVirologyImmunityImmunologyImmune systemVirusBiologyAntibodyReceptor

Abstract

fetched live from OpenAlex

Oncolytic virotherapies have shown excellent promise in a variety of cancers by promoting antitumor immunity. However, the effects of oncolytic virus-mediated type I interferon (IFN-I) production on antitumor immunity remain unclear. Recent reports have highlighted immunosuppressive functions of IFN-I in the context of checkpoint inhibitor and cell-based therapies. In this study, we demonstrate that oncolytic virus-induced IFN-I promotes the expression of PD-L1 in tumor cells and leukocytes in a IFN receptor (IFNAR)-dependent manner. Inhibition of IFN-I signaling using a monoclonal IFNAR antibody decreased IFN-I-induced PD-L1 expression and promoted tumor-specific T cell effector responses when combined with oncolytic virotherapy. Furthermore, IFNAR blockade improved therapeutic response to oncolytic virotherapy in a manner comparable with PD-L1 blockade. Our study highlights a critical immunosuppressive role of IFN-I on antitumor immunity and uses a combination strategy that improves the response to oncolytic virotherapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.270
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2022
Admission routes1
Has abstractyes

Explore more

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