Characterization of Antigen-Specific Immune Responses Induced by Canarypox Virus Vaccines
Bibliographic record
Abstract
Avipoxvirus-based vectors, such as recombinant canarypox virus ALVAC, are studied extensively as delivery vehicles for vaccines against cancer and infectious diseases. Effective use of such vaccines is expected to benefit from proper understanding of the interaction between these viral vectors and the host immune system. We performed preclinical vaccination experiments in a murine tumor model to analyze the immunogenic properties of an ALVAC-based vaccine against carcinoembryonic Ag (ALVAC-CEA), a tumor-associated autoantigen commonly overexpressed in colorectal cancers. The protective CEA-specific immunity induced by this vaccine consisted of CD4(+) T cell responses with a mixed Th1/Th2 cytokine profile that were accompanied by potent humoral responses, but not by CEA-specific CD8(+) CTL immunity. In contrast, protective immunity induced by a CEA-specific DNA vaccine (DNA-CEA) consisted of Th1 and CTL responses. Modification of the ALVAC-CEA vaccine through coinjection of DNA-CEA, admixture with CpG oligodeoxynucleotides, or supplementation with additional transgenes encoding a triad of costimulatory molecules (TRICOM) did not result in induction of CEA-specific CTL responses. Even though these results suggested that ALVAC does not elicit Ag-specific CTLs, immunization with ALVAC vaccines against other Ags efficiently induced CTL responses. Our data show that the capacity of ALVAC vaccines to elicit CTL immunity against transgene-encoded Ags critically depends on the presence of highly immunogenic CTL epitopes in these Ags. This consideration needs to be taken into account with respect to the design and evaluation of vaccination strategies that use ALVAC-based vaccine.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".