Murine Responses to Recombinant MVA Versus ALVAC Vaccines Against Tumor-associated Antigens, gp100 and 5T4
Bibliographic record
Abstract
Virally vectored cancer vaccines comprise a new form of immunotherapy that aim to generate anti-tumor immune responses with potential for tumor clearance and enhanced patient survival. Here, we compared 2 replication-deficient poxviruses modified vaccinia Ankara (MVA) and ALVAC(2) in their ability to induce antigen expression and immunogenicity of the tumor-associated antigens (TAAs) 5T4 and gp100. To facilitate the comparison, recombinant MVA-gp100M and ALVAC(2)-5T4 were constructed to complement existing ALVAC(2)-gp100M and MVA-5T4 vectors. Recombinant TAA expression in chicken embryo fibroblast cells was confirmed by Western blot analysis. 5T4 expression was approximately equal for both viruses, whereas ALVAC-derived gp100 was quickly degraded, at a time point when MVA-derived gp100 was still stable and expressed at high levels. Human leukocyte antigen-A2 transgenic mice were vaccinated with recombinant viruses and the CD8 T-cell responses elicited against each TAA were monitored by interferon-γ enzyme-linked immunospot. No 5T4 peptide responses were detected using splenocytes from mice vaccinated with either vector, whereas vaccination with MVA elicited a significantly higher gp100-specific response than ALVAC(2) at 10 PFU (P<0.001). In CD-1 mice, each vector elicited similar 5T4 antibody responses, whereas MVA was more potent and induced gp100 antibody responses at a lower immunization dose than ALVAC (P<0.001). In this study, immunogenicity varied depending on the viral vector used and reflected vector-associated differences in in vitro TAA expression and stability. These findings suggest that novel vector-transgene combinations must be assessed individually when designing vaccines, and that stability of vector-encoded proteins produced in vitro may be useful as a predictor for in vitro immunogenicity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".