Tumor-Infiltrating Dendritic Cell Subsets of Progressive or Regressive Tumors Induce Suppressive or Protective Immune Responses
Bibliographic record
Abstract
Tumor-infiltrating dendritic cells (TID) have an ambivalent role in regulation of tumor regression or growth. However, their precise natures and molecular mechanisms have not been elucidated. In this study, we studied TIDs recruited in progressive P815 and regressive P198 tumors of the same origin. Our data showed that P815 tumors contained CD4+ 8+ and CD4- 8- TID815 subsets, whereas P198 tumors contained CD4+ 8+ and CD4+ 8- TID198 subsets. They similarly stimulate allogeneic T cell proliferation and have nitric oxide-mediated cytotoxicity to tumor cells with an exception of CD4- 8- TID815 with less efficiency. The newly identified fourth CD4+ 8+ TID815 or TID198 subset and the CD4+ 8- TID198 all express high levels of IFN-gamma and interleukin (IL)-6, whereas CD4- 8- TID815 secrete a marked level of transforming growth factor-beta. Vaccination of mice with P815 tumor lysate-pulsed CD4+ 8+ TID815 or TID198 and CD4+ 8- TID198 induced IFN-gamma-secreting Th1 and effective CTL responses leading to protective immunity against P815 tumor, whereas CD4- 8- TID815 stimulated IL-10-expressing Tr1 responses leading to immune suppression. Transfer of CD4+ Tr1 cells obtained from CD4- 8- TID815-immunized wild-type, but not IL-10(-/-) mice, into CD4+ 8+ TID815 immunized mice abolished otherwise inevitable development of antitumor immunity. Taken together, our findings provide an important insight into immunologic alterations in progressive and regressive tumors and an implication for dendritic cell-based approaches in the design of cancer vaccines.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".