Genetically modified dendritic cells prime autoreactive T cells through a pathway independent of CD40L and interleukin 12: implications for cancer vaccines.
Bibliographic record
Abstract
Genetic immunization through ex vivo transduction of dendritic cells has been suggested as an effective approach to enhance antitumor immunity by activating both CD4+ and CD8+ T cells. Immunizing mice with dendritic cells transduced with an adenovirus expressing the human melanoma antigen glycoprotein 100 (DCAdhgp100) as a cancer vaccine, we demonstrated complete protective immunity and a potent CTL response against melanomas expressing murine glycoprotein 100 in a CD4+ cell-dependent manner. Surprisingly, however, effective tumor rejection was not the result of cooperation between CD4+ and CD8+ T cells. Protective immunity was completely lost when CD4+ cells were depleted immediately before tumor challenge, whereas it was unaffected by removal of CD8+ cells, establishing a principal role for CD4+ cells in the effector phase of tumor rejection. Neither protective immunity nor CTL generation in this model required interleukin 12, in spite of high levels of IFN-gamma secretion by tumor-reactive T cells. Most notably, the DCAdhgp100 vaccine could elicit protective antitumor CD4+ cells in the absence of CD40 ligand, although it does not bypass the need for CD40-mediated signals to generate melanoma-reactive CTLs. Thus, in contrast to the current thinking that the optimal cancer vaccine should include determinants for both CD4+ and CD8+ cells, the potency of the DCAdhgp100 vaccine appears to be a result of its ability to directly prime autoreactive CD4+ cells through a process that does not require interleukin 12 and CD40 signals.
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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) | 0.000 | 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".