Chimeric MHC class I– and II–restricted non-self epitopes broaden antitumor T cell reactions
Bibliographic record
Abstract
The mechanism by which one non-self antigen augments T cell immune responses to another remains unclear. We found that these expanded immune responses could derive from chimeric non-self peptides. These peptides, which we termed complete T cell antigens (CTAs), must be expressed intracellularly as single-chain chimeras containing both MHC class I- and II-restricted epitopes. CTAs, even unrelated to tumor antigens, when administered as live cell adjuvants or in cDNA-transfected muscle, increased T cell reactivity against tumor neoantigens. Mechanistically, CTA treatment altered dendritic cell phenotype in a CD4+ T cell-dependent manner, suppressing CD8+ T cell exhaustion and generating self-renewing CD8+ T cells in tumors. Cancers predicted to have long non-self peptides resulting from frameshift mutations, which frequently contain CTAs, were associated with a better prognosis or benefit from PD-1 blockade therapy in mouse models and cancer patients. These findings indicate that a subset of cancer cells expressing CTAs is sufficient to evoke overall antitumor immunity by broadening T cell responses to other neoantigens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".