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Record W4220720824 · doi:10.1136/jitc-2021-004335

Oncolytic Orf virus licenses NK cells via cDC1 to activate innate and adaptive antitumor mechanisms and extends survival in a murine model of late-stage ovarian cancer

2022· article· en· W4220720824 on OpenAlexafffund
Jacob P. van Vloten, Kathy Matuszewska, Mark A.A. Minow, Jessica A. Minott, Lisa A. Santry, Madison Pereira, Ashley A. Stegelmeier, Thomas M. McAusland, Elaine M. Klafuric, Khalil Karimi, Joseph Colasanti, Dennis McFadden, Jim Petrik, Byram W. Bridle, Sarah K. Wootton

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Veterinary College, University of GuelphTerry Fox Research InstituteCancer Research Society
KeywordsOncolytic virusOvarian cancerCancer researchImmunotherapyBiologyInnate immune systemImmune systemCancerVirotherapyImmunology

Abstract

fetched live from OpenAlex

Background Novel therapies are needed to improve outcomes for women diagnosed with ovarian cancer. Oncolytic viruses are multifunctional immunotherapeutic biologics that preferentially infect cancer cells and stimulate inflammation with the potential to generate antitumor immunity. Herein we describe Parapoxvirus ovis (Orf virus (OrfV)), an oncolytic poxvirus, as a viral immunotherapy for ovarian cancer. Methods The immunotherapeutic potential of OrfV was tested in the ID8 orthotopic mouse model of end-stage epithelial ovarian carcinoma. Immune cell profiling, impact on secondary lesion development and survival were evaluated in OrfV-treated mice as well as in Batf3 knockout, mice depleted of specific immune cell subsets and in mice where the primary tumor was removed. Finally, we interrogated gene expression datasets from primary human ovarian tumors from the International Cancer Genome Consortium database to determine whether the interplay we observed between natural killer (NK) cells, classical type 1 dendritic cells (cDC1s) and T cells exists and influences outcomes in human ovarian cancer. Results OrfV was an effective monotherapy in a murine model of advanced-stage epithelial ovarian cancer. OrfV intervention relied on NK cells, which when depleted abrogated antitumor CD8 + T-cell responses. OrfV therapy was shown to require cDC1s in experiments with BATF3 knockout mice, which do not have mature cDC1s. Furthermore, cDC1s governed antitumor NK and T-cell responses to mediate antitumor efficacy following OrfV. Primary tumor removal, a common treatment option in human patients, was effectively combined with OrfV for optimal therapeutic outcome. Analysis of human RNA sequencing datasets revealed that cDC1s correlate with NK cells in human ovarian cancer and that intratumoral NK cells correlate positively with survival. Conclusions The data herein support the translational potential of OrfV as an NK stimulating immunotherapeutic for the treatment of advanced-stage ovarian cancer.

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 categoriesnone
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 score0.052
Threshold uncertainty score0.746

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 science0.0000.000
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 head0.027
GPT teacher head0.332
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations30
Published2022
Admission routes2
Has abstractyes

Explore more

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