Tumor-reactive CD4+ T cells develop cytotoxic activity and eradicate large established melanoma after transfer into lymphopenic hosts
Bibliographic record
Abstract
Adoptive transfer of large numbers of tumor-reactive CD8(+) cytotoxic T lymphocytes (CTLs) expanded and differentiated in vitro has shown promising clinical activity against cancer. However, such protocols are complicated by extensive ex vivo manipulations of tumor-reactive cells and have largely focused on CD8(+) CTLs, with much less emphasis on the role and contribution of CD4(+) T cells. Using a mouse model of advanced melanoma, we found that transfer of small numbers of naive tumor-reactive CD4(+) T cells into lymphopenic recipients induces substantial T cell expansion, differentiation, and regression of large established tumors without the need for in vitro manipulation. Surprisingly, CD4(+) T cells developed cytotoxic activity, and tumor rejection was dependent on class II-restricted recognition of tumors by tumor-reactive CD4(+) T cells. Furthermore, blockade of the coinhibitory receptor CTL-associated antigen 4 (CTLA-4) on the transferred CD4(+) T cells resulted in greater expansion of effector T cells, diminished accumulation of tumor-reactive regulatory T cells, and superior antitumor activity capable of inducing regression of spontaneous mouse melanoma. These findings suggest a novel potential therapeutic role for cytotoxic CD4(+) T cells and CTLA-4 blockade in cancer immunotherapy, and demonstrate the potential advantages of differentiating tumor-reactive CD4(+) cells in vivo over current protocols favoring in vitro expansion and differentiation.
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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) | 0.001 | 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 | 0.001 |
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 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".