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Record W2020975318 · doi:10.1038/mt.2012.128

Harnessing Oncolytic Virus-mediated Antitumor Immunity in an Infected Cell Vaccine

2012· article· en· W2020975318 on OpenAlexafffund
Chantal G. Lemay, Julia L. Rintoul, Agnieszka Kuś, Jennifer M Paterson, Vanessa da Silva Garcia, Theresa Falls, Lisa Ferreira, Byram W. Bridle, David P. Conrad, Vera A. Tang, Jean‐Simon Diallo, Rozanne Arulanandam, Fabrice Le Bœuf, Kenneth Garson, Barbara C. Vanderhyden, David F. Stojdl, Brian D. Lichty, Harold Atkins, Kelley A. Parato, John C. Bell, Rebecca C. Auer

Bibliographic record

VenueMolecular Therapy · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsMcMaster UniversityUniversity of GuelphOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsOncolytic virusVirologyImmunityVirusBiologyCell mediated immunityImmune systemImmunology

Abstract

fetched live from OpenAlex

Treatment of permissive tumors with the oncolytic virus (OV) VSV-Δ51 leads to a robust antitumor T-cell response, which contributes to efficacy; however, many tumors are not permissive to in vivo treatment with VSV-Δ51. In an attempt to channel the immune stimulatory properties of VSV-Δ51 and broaden the scope of tumors that can be treated by an OV, we have developed a potent oncolytic vaccine platform, consisting of tumor cells infected with VSV-Δ51. We demonstrate that prophylactic immunization with this infected cell vaccine (ICV) protected mice from subsequent tumor challenge, and expression of granulocyte–monocyte colony stimulating factor (GM-CSF) by the virus (VSVgm-ICV) increased efficacy. Immunization with VSVgm-ICV in the VSV-resistant B16-F10 model induced maturation of dendritic and natural killer (NK) cell populations. The challenge tumor is rapidly infiltrated by a large number of interferon γ (IFNγ)-producing T and NK cells. Finally, we demonstrate that this approach is robust enough to control the growth of established tumors. This strategy is broadly applicable because of VSV's extremely broad tropism, allowing nearly all cell types to be infected at high multiplicities of infection in vitro, where the virus replication kinetics outpace the cellular IFN response. It is also personalized to the unique tumor antigen(s) displayed by the cancer cell. Treatment of permissive tumors with the oncolytic virus (OV) VSV-Δ51 leads to a robust antitumor T-cell response, which contributes to efficacy; however, many tumors are not permissive to in vivo treatment with VSV-Δ51. In an attempt to channel the immune stimulatory properties of VSV-Δ51 and broaden the scope of tumors that can be treated by an OV, we have developed a potent oncolytic vaccine platform, consisting of tumor cells infected with VSV-Δ51. We demonstrate that prophylactic immunization with this infected cell vaccine (ICV) protected mice from subsequent tumor challenge, and expression of granulocyte–monocyte colony stimulating factor (GM-CSF) by the virus (VSVgm-ICV) increased efficacy. Immunization with VSVgm-ICV in the VSV-resistant B16-F10 model induced maturation of dendritic and natural killer (NK) cell populations. The challenge tumor is rapidly infiltrated by a large number of interferon γ (IFNγ)-producing T and NK cells. Finally, we demonstrate that this approach is robust enough to control the growth of established tumors. This strategy is broadly applicable because of VSV's extremely broad tropism, allowing nearly all cell types to be infected at high multiplicities of infection in vitro, where the virus replication kinetics outpace the cellular IFN response. It is also personalized to the unique tumor antigen(s) displayed by the cancer cell.

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 score0.005
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 science0.0000.000
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 head0.019
GPT teacher head0.308
Teacher spread0.289 · 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

Citations92
Published2012
Admission routes2
Has abstractyes

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