Antitumor Impact of Interferon-γ Producing CD1d-restricted NKT Cells in Murine Malignant Mesothelioma
Bibliographic record
Abstract
CD1d-restricted natural killer T (iNKT) cells have been shown to provide adjuvant activity against cancer by producing interferon (IFN)-γ. However, the role of invariant NKT (iNKT) cells in the tumor microenvironment has not yet been fully addressed. Our aim is to elucidate the antitumor effect of iNKT cells in the tumor microenvironment by using an intrathoracic murine malignant pleural mesothelioma model that we had previously developed and to provide pleural effusion as a good surrogate of the tumor microenvironment. We found that the number of iNKT cells increased dramatically in the pleural effusion after intrathoracic tumor cell injection at an earlier phase compared with accumulation of CD8 T cells. These iNKT cells showed increased expression of CD25 and increased ratio of cells positive for IFN-γ intracellular staining. iNKT cells sorted from pleural effusion of tumor burden mice produced larger amount of IFN-γ compared with naive mice. Mice pretreated in vivo with anti-CD1d-blocking Ab showed increased amount of pleural effusion and decreased ratio of total and effector-type CD8 T cells as well as decreased intracellular IFN-γ expression of CD8T-cell in the pleural effusion. In vivo administration of α-galactosylceramide (α-GalCer) showed prolonged survival associated with less pleural effusion and increased ratio of IFN-γ-positive iNKT cells and CD8 T cells in the pleural effusion. Therefore, this study suggests that iNKT cells accumulating in the tumor microenvironment play an antitumor effect by producing IFN-γ and enhancing subsequent CD8 T-cell response. Furthermore, in vivo administration of α-GalCer could suppress mesothelioma growth by activating iNKT cells.
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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 | 0.001 |
| 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".