TNFR2-Deficient Memory CD8 T Cells Provide Superior Protection against Tumor Cell Growth
Bibliographic record
Abstract
TNF receptor-2 (TNFR2) plays a critical role in promoting the activation and survival of naive T cells during the primary response. Interestingly, anti-CD3 plus IL-2 activated TNFR2(-/-) CD8 T cells are highly resistant to activation-induced cell death (AICD), which correlates with high expression levels of prosurvival molecules such as Bcl-2, survivin, and CD127 (IL-7Ralpha). We determined whether the resistance of activated TNFR2(-/-) CD8 T cells to AICD contributes to more effective protection against tumor cell growth. We found that during a primary tumor challenge, despite initial inferiority in controlling tumor cell growth, TNFR2(-/-) mice were able to more effectively control tumor burden over time compared with wild-type (WT) mice. Furthermore, vaccination of TNFR2(-/-) mice with recombinant Listeria monocytogenes that express OVA confers better protection against the growth of OVA-expressing E.G7 tumor cells relative to similarly vaccinated WT mice. The enhanced protection against tumor cell growth was not due to more effective activation of OVA-specific memory CD8 T cells in vaccinated TNFR2(-/-) mice. In vitro studies indicate that optimally activated OVA-specific TNFR2(-/-) CD8 T cells proliferated to the same extent and possess similar cytotoxicity against E.G7 tumor cells as WT CD8 T cells. However, relative to WT cells, activated OVA-specific TNFR2(-/-) CD8 T cells were highly resistant to AICD. Thus, the enhanced protection against E.G7 in TNFR2(-/-) mice is likely due to the recruitment and activation of OVA-specific memory TNFR2(-/-) CD8 T cells and their prolonged survival at the tumor site.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".