Nitric Oxide Sensitizes Tumor Cells to Dendritic Cell–Mediated Apoptosis, Uptake, and Cross-Presentation
Bibliographic record
Abstract
Dendritic cells are professional antigen-presenting cells associated with efficient antigen processing and presentation to T cells. However, recent evidence also suggests that dendritic cells may mediate direct tumoricidal functions. In this study, we investigated the mechanism by which murine dendritic cells mediate the apoptotic death of murine lymphoma cell lines, and whether dendritic cell effector function could be enhanced by preconditioning tumor cells with the protein phosphatase inhibitor nitric oxide (NO) by altering the balance of proapoptotic/antiapoptotic proteins in the treated cells. We observed that NO donor compound sensitized lymphomas to dendritic cell-mediated cytotoxicity in vitro. Both immature and spontaneously matured bone marrow-derived dendritic cells (SM-DC) were capable of inducing tumor cell apoptosis, with SM-DCs serving as comparatively better killers. Fas ligand (FasL)-Fas engagement proved important in this activity because elevated expression of membrane-bound FasL was detected on SM-DCs, and dendritic cells derived from FasL-deficient mice were less capable of killing NO-sensitized tumor cells than wild-type dendritic cells. As FasL-deficient dendritic cells were still capable of mediating a residual degree of tumor killing, this suggests that FasL-independent mechanisms of apoptosis are also involved in dendritic cell-mediated tumor killing. Because NO-treated tumor cells displayed a preferential loss of survivin protein expression via a proteasome-dependent pathway, enhanced tumor sensitivity to dendritic cell-mediated killing may be associated with the accelerated turnover of this critical antiapoptotic gene product. Importantly, NO-treated tumor cells were also engulfed more readily than control tumor cells and this resulted in enhanced cross-presentation of tumor-associated antigens to specific T cells in vitro.
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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 | 0.000 |
| 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".