Induction of antitumor immunity through xenoplacental immunization
Bibliographic record
Abstract
Historically cancer vaccines have yielded suboptimal clinical results. We have developed a novel strategy for eliciting antitumor immunity based upon homology between neoplastic tissue and the developing placenta. Placenta formation shares several key processes with neoplasia, namely: angiogenesis, activation of matrix metalloproteases, and active suppression of immune function. Immune responses against xenoantigens are well known to break self-tolerance. Utilizing xenogeneic placental protein extracts as a vaccine, we have successfully induced anti-tumor immunity against B16 melanoma in C57/BL6 mice, whereas control xenogeneic extracts and B16 tumor extracts where ineffective, or actually promoted tumor growth, respectively. Furthermore, dendritic cells were able to prime tumor immunity when pulsed with the placental xenoantigens. While vaccination-induced tumor regression was abolished in mice depleted of CD4 T cells, both CD4 and CD8 cells were needed to adoptively transfer immunity to naïve mice. Supporting the role of CD8 cells in controlling tumor growth are findings that only freshly isolated CD8 cells from immunized mice were capable of inducing tumor cell caspases-3 activation ex vivo. These data suggest feasibility of using xenogeneic placental preparations as a multivalent vaccine potently targeting not just tumor antigens, but processes that are essential for tumor maintenance of malignant potential.
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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) | 0.000 | 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 | 0.000 |
| 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 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".