Dendritic Cell-Induced Activation of Adaptive and Innate Antitumor Immunity
Bibliographic record
Abstract
While studying Ag-pulsed syngeneic dendritic cell (DC) immunization, we discovered that surprisingly, unpulsed DCs induced protection against tumor lung metastases resulting from i.v. injection of a syngeneic BALB/c colon carcinoma CT26 or a syngeneic C57BL/6 lung carcinoma LL/2. Splenocytes or immature splenic DCs did not protect. The protection was mediated by NK cells, in that it was abrogated by treatment with anti-asialo-GM1 but not anti-CD8, and was induced by CD1(-/-) DCs unable to stimulate NKT cells, but did not occur in beige mice lacking NK cells. Protection correlated with increased NK activity, and increased infiltration of NK but not CD8(+) cells in lungs of tumor-bearing mice. Protection depended on the presence of costimulatory molecules CD80, CD86, and CD40 on the DCs, but surprisingly did not require DCs that could make IL-12 or IL-15. Unexpectedly, protection sensitive to anti-asialo-GM1 and increased NK activity were still present 14 mo after DC injection. As NK cells lack memory, we found by depletion that CD4(+) not CD8(+) T cells were required for induction of the NK antitumor response. The role of DCs and CD4(+) T cells provides a novel mechanism for NK cell induction and innate immunity against cancer that may have potential in preventing clinical metastases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".