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Record W2036869628 · doi:10.1038/mt.2013.249

Maraba Virus as a Potent Oncolytic Vaccine Vector

2013· article· en· W2036869628 on OpenAlexafffund
Jonathan Pol, Liang Zhang, Byram W. Bridle, Kyle B. Stephenson, Julien Rességuier, Stephen J. Hanson, Lan Chen, Natasha Kazdhan, Jonathan L. Bramson, David F. Stojdl, Yonghong Wan, Brian D. Lichty

Bibliographic record

VenueMolecular Therapy · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsChildren's Hospital of Eastern OntarioMcMaster University Medical CentreOttawa HospitalUniversity of GuelphMcMaster University
FundersCanadian Institutes of Health ResearchOntario Institute for Cancer ResearchCancer Research Institute
KeywordsOncolytic virusVirologyAdjuvantAntigenHeterologousImmunotherapyImmune systemImmunityMelanomaVirusCancer immunotherapyVaccinationBiologyVirotherapyCancer vaccineImmunologyViral vectorCancer researchRecombinant DNAGene

Abstract

fetched live from OpenAlex

The rhabdovirus Maraba has recently been characterized as a potent oncolytic virus. In the present study, we engineered an attenuated Maraba strain, defined as MG1, to express a melanoma-associated tumor antigen. Its ability to mount an antitumor immunity was evaluated in tumor-free and melanoma tumor-bearing mice. Alone, the MG1 vaccine appeared insufficient to prime detectable adaptive immunity against the tumor antigen. However, when used as a boosting vector in a heterologous prime-boost regimen, MG1 vaccine rapidly generated strong antigen-specific T-cell immune responses. Once applied for treating syngeneic murine melanoma tumors, our oncolytic prime-boost vaccination protocol involving Maraba MG1 dramatically extended median survival and allowed complete remission in more than 20% of the animals treated. This work describes Maraba virus MG1 as a potent vaccine vector for cancer immunotherapy displaying both oncolytic activity and a remarkable ability to boost adaptive antitumor immunity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.283
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), 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

Citations175
Published2013
Admission routes2
Has abstractno

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