DNA-based vaccination against carcinoembryonic antigen
Bibliographic record
Abstract
DNA vaccination is based on in vivo delivery of plasmids encoding an antigen, leading to antigen synthesis and specific immunity. This technology is still in its infancy but has advantages over conventional vaccination, such as the stimulation of all arms of the immune response, i.e., humoral immunity, T-helper (17h) cells and cytotoxic T lymphocytes (CTLs). We studied DNA vaccination against human carcinoembryonic antigen (CEA) in mice. Our hypothesis was that codelivery of cytokine- and CEA-encoding plasmids could regulate responses, and allow polarization of Th responses to either type 1 (Th1) or type 2 (Th2). We found that intramuscular injection of the CEA plasmid alone induced antibodies, Th1 cells and CTLs reactive to CEA. These mice had increased immunity against transplanted syngeneic CEA+ stably transfected tumor cell lines, but always developed lethal tumors. Coinjection of the CEA plasmid with a vector encoding either IL-12 or interferon gamma (IFNgamma) markedly enhanced IgG2a production (IFNgamma-dependent), IFNgamma secretion by spleen cells (a Th1 cytokine) and CTL-mediated tumor cell lysis, in a CEA-specific way. Moreover, resistance to a tumor challenge was greatly improved, such that up to 80% of mice survived tumor free. In contrast, coinjection of CEA and IL-4 genes increased CEA-specific IgG1 levels (IL-4-dependent) and IL-4 secretion by lymphocytes (a Th2 cytokine), but decreased both CTL activity and tumor resistance. Thus, we could readily enhance or polarize immunity. The IL-12 cDNA had the strongest adjuvant effect, which was only observed when it was injected at the same site as the CEA gene. To analyze effector components, we studied IL-12-plasmid-enhanced DNA vaccination in gene knockout mice, lacking either CD3, CD4, CD8. IFNgamma, perforin or Fas ligand (FasL). Only mice expressing all of CD3, CD4, IFNgamma, CD8 and perforin, and inoculated with both the CEA and IL-12 genes, could fully resist a tumor challenge. The Fas/FasL lytic
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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 | 0.001 | 0.000 |
| 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".