Development and applications of oncolytic Maraba virus vaccines
Bibliographic record
Abstract
Oncolytic activity of the MG1 strain of the Maraba vesiculovirus has proven efficacy in numerous preclinical cancer models, and relied not only on a direct cytotoxicity but also on the induction of both innate and adaptive antitumor immunity. To further expand tumor-specific T-cell effector and long-lasting memory compartments, we introduced the MG1 virus in a prime-boost cancer vaccine strategy. To this aim, a replication-incompetent adenoviral [Ad] vector together with the oncolytic MG1 have each been armed with a transgene expressing a same tumor antigen. Immune priming with the Ad vaccine subsequently boosted with the MG1 vaccine mounted tumor-specific responses of remarkable magnitude, which significantly prolonged survival in various murine cancer models. Based on these promising results, we validated the safety profile of the Ad:MG1 oncolytic vaccination strategy in nonhuman primates and initiated clinical investigations in cancer patients. Two clinical trials are currently under way (NCT02285816; NCT02879760). The present review will recapitulate the discoveries that led to the development of MG1 oncolytic vaccines from bench to bedside.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".