Cross-Reactive Antigen Is Required to Prevent Erosion of Established T Cell Memory and Tumor Immunity: A Heterologous Bacterial Model of Attrition
Bibliographic record
Abstract
Induction and maintenance of T cell memory is critical for the control of intracellular pathogens and tumors. Memory T cells seem to require few "maintenance signals," though often such studies are done in the absence of competing immune challenges. Conversely, although attrition of CD8(+) T cell memory has been characterized in heterologous viral models, this is not the case for bacterial infections. In this study, we demonstrate attrition of T cell responses to the intracellular pathogen Listeria monocytogenes (LM) following an immune challenge with a second intracellular bacterium, Mycobacterium bovis (bacillus Calmette-Guérin, BCG). Mice immunized with either LM or recombinant LM (expressing OVA; LM-OVA), develop a potent T cell memory response. This is reflected by peptide-specific CTL, IFN-gamma production, and frequency of IFN-gamma-secreting T cells to native or recombinant LM Ags. However, when the LM-infected mice are subsequently challenged with BCG, there is a marked reduction in the LM-specific T cell responses. These reductions are directly attributable to the effects on CD4(+) and CD8(+) T cells and the data are consistent with a loss of LM-specific T cells, not anergy. Attrition of the Ag (OVA)-specific T cell response is prevented when LM-OVA-immunized mice are challenged with a subsequent heterologous pathogen (BCG) expressing OVA, demonstrating memory T cell dependence on Ag. Although the reduction of the LM-specific T cell response did not impair protection against a subsequent LM rechallenge, for the first time, we show that T cell attrition can result in the reduction of Ag-specific antitumor (B16-OVA) immunity previously established with LM-OVA immunization.
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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 | 0.000 | 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".