Evaluation of recombinant adenovirus vectors and adjuvanted protein as a heterologous prime-boost strategy using HER2 as a model antigen
Bibliographic record
Abstract
Induction of strong antigen-specific cell-mediated and humoral responses are critical to developing a successful therapeutic vaccine. Herein, using HER2 as a model antigen, we aim to evaluate a therapeutic vaccine protocol that elicits anti-tumor antibody and cytotoxic T cells to HER2/neu antigen. Replication-competent (ΔPS AdV) and non-replicating recombinant adenoviral vectors (AdV) expressing a rat HER2/neu (ErbB2) oncogene, were generated and compared for four different doses and over four time points for their ability to induce antigen-specific T and B cell responses in mice. Although ΔPS AdV:Her2 vector was shown to induce more durable antigen-specific CD8+ T cell responses, overall, the AdV:Her2 vector induced broader T and B cell responses. Hence the AdV:Her2 vector was used to evaluate a heterologous prime-boost vaccination regimen using rat HER2 protein encapsulated in archaeosomes composed of a semi-synthetic glycolipid (sulfated S-lactosylarchaeol, SLA; and lactosylarchaeol, LA) (SLA/LA:HER2enc) or admixed with archaeosomes composed of SLA alone (SLA:HER2adm). We first tested AdV:Her2 using a prime-boost approach with SLA/LA:HER2enc, and thereafter evaluated a sub-optimal AdV:Her2 dose in a heterologous prime-boost approach with SLA:HER2adm. A single administration of AdV:Her2 alone induced strong cell-mediated immune responses, whereas SLA/LA:HER2enc alone induced strong antigen-specific IgG titers. In mice primed with a suboptimal dose of AdV:Her2, strong CD8+ T-cell responses were observed after a single dose which were not further augmented by protein boost. AdV:Her2 induced CD4+ specific T-cell responses were augmented by SLA:HER2adm. Homologous vaccination using SLA:HER2adm induced strong antigen-specific antibody responses. However, the overall magnitude of the responses was similar with three doses of SLA:HER2adm or Ad:HER2 prime followed by two doses of SLA:HER2adm. We demonstrate that AdV:Her2 is capable of inducing strong antigen-specific CD8+ T cell responses, even at a low dose, and that these responses can be broadened to include antigen-specific antibody responses by boosting with SLA adjuvanted proteins without compromising CD8 T cell responses elicited by AdV priming.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.000 | 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".