HER-2/neu is a tumor rejection target in tolerized HER-2/neu transgenic mice.
Bibliographic record
Abstract
HER-2/neu (neu-N) transgenic mice, which express the nontransforming rat proto-oncogene, develop spontaneous focal mammary adenocarcinomas beginning at 5-6 months of age. The development and histology of these tumors bears a striking resemblance to what is seen in patients with breast cancer. We have characterized the immunological responses to HER-2/neu (neu) in this animal model. neu-positive tumor lines, which were derived from spontaneous tumors that formed in neu-N animals, are highly immunogenic in parental, FVB/N mice. In contrast, a 100-fold lower tumor challenge is sufficient for growth in 100% of transgenic animals. Despite significant tolerance to the transgene, neu-specific immune responses similar to those observed in breast cancer patients can be demonstrated in neu-N mice prior to vaccination. Both cellular and humoral neu-specific responses in transgenic mice can be boosted with neu-specific vaccination, although to a significantly lesser degree than what is observed in FVB/N mice, indicating that the T cells involved are less responsive than in the nontoleragenic parental strain. Using irradiated whole-cell and recombinant vaccinia virus vaccinations we are able to protect neu-N mice from a neu-expressing tumor challenge. T-cell depletion experiments demonstrated that the observed protection is T cell dependent. The vaccine-dependent neu-specific immune response is also sufficient to delay the onset of spontaneous tumor formation in these mice. These data suggest that, despite tolerance to neu in this transgenic model, it is possible to immunize neu-specific T cells to achieve neu-specific tumor rejection in vivo. These transgenic mice provide a spontaneous tumor model for identifying vaccine approaches potent enough to overcome mechanisms of immune tolerance that are likely to exist in patients with cancer.
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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) | 0.006 | 0.001 |
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".