Cigarette Smoke Impairs NK Cell-Dependent Tumor Immune Surveillance
Bibliographic record
Abstract
In this study, we investigated the impact of cigarette smoke on tumor immune surveillance and its consequences to lung tumor burden in a murine lung metastasis model. Cigarette smoke exposure significantly increased the numbers of lung metastases following B16-MO5 melanoma challenge. This effect was reversible; we observed significantly fewer tumor nodules following smoking cessation. Using RAG2(-/-) and RAG2(-/-)gamma(c)(-/-) mice, we provide strong evidence that increased tumor incidence was NK cell dependent. Furthermore, we show that cigarette smoke suppressed NK activation and attenuated NK CTL activity, without apparent effect on activating or inhibitory receptor expression. Finally, activation of NK cells through bone marrow-derived dendritic cells conferred protection against lung metastases in smoke-exposed mice; however, protection was not as efficacious as in sham-exposed mice. To our knowledge, this is the first experimental evidence showing that cigarette smoke impairs NK cell-dependent tumor immune surveillance and that altered immunity is associated with increased tumor burden. Our findings suggest that altered innate immunity may contribute to the increased risk of cancer in smokers.
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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".