Abstract C225: Differential regulation of simultaneous antitumor and alloreactive CD8+ T cell responses in the same host by rapamycin.
Bibliographic record
Abstract
Abstract Rapamycin is an immunosuppressive agent routinely used in organ transplantation, but also paradoxically, exerts antiviral and anti-tumor activities. Pathogen-specific memory CD8+ T cell (TCD8) responses were recently found to be augmented by rapamycin. However, whether rapamycin influences the magnitude and quality of anticancer TCD8 responses is unknown. Importantly, how rapamycin may regulate simultaneous virus/tumor-specific and alloreactive TCD8 in the same host remains unexplored. To answer these questions, we primed wild-type mice with allogeneic cells concomitantly expressing simian virus 40 large tumor antigen (T Ag), a viral oncoprotein with well-defined epitopes. Rapamycin selectively improved the cross-priming of TCD8 specific for T Ag's most immunodominant epitope called site IV. Rapamycin-treated mice also had a high percentage of splenic CD127highKLRG1low TCD8 as well as an increased frequency of site IV-specific T cells long after the peak of their primary response. When site IV was presented as a cytosolic minigene encoded by a recombinant vaccinia virus, rapamycin failed to enhance the site IV-specific response. Therefore, the nature and presentation mode of antigen determine the susceptibility to the adjuvant effect of rapamycin. Our findings reveal the unexpected benefit of rapamycin treatment in recipients of allografts co-expressing tumor/viral Ags. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr C225.
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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 | 0.000 | 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 | 0.000 |
| 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".