Enhanced Tumor Metastasis in Response to Blockade of the Chemokine Receptor CXCR6 Is Overcome by NKT Cell Activation
Bibliographic record
Abstract
Invariant NKT (iNKT) cells can induce potent antitumor responses in vivo. However, the mechanisms that regulate the effects of iNKT cells are unclear. The chemokine receptor CXCR6, and its ligand CXCL16, have been shown to play critical roles in iNKT cell homeostasis and activation. Thus we investigated the role of CXCR6 in protection against experimental metastasis of B16-F10 melanoma (B16) and Lewis lung carcinoma (LLC) cells to the liver and lungs. Wild-type and CXCR6(-/-) mice exhibited no differences in tumor cell metastasis to the lungs. However, metastasis of LLC and B16 tumor cells to the liver was enhanced in CXCR6(-/-) mice. Liver metastasis was also increased in wild-type mice treated with a CXCL16 neutralizing Ab. As Ab treatments did not alter iNKT cell numbers, this implicates a direct role for CXCR6/CXCL16 in regulating antitumor immunity. Cytokine induction was significantly attenuated in CXCR6(-/-) mice upon systemic iNKT cell activation with the glycolipid Ags alpha-galactosylceramide (alpha-GalCer), alpha-C-GalCer (a Th1 polarizing derivative), or OCH (a Th2 polarizing derivative). Despite differences in the levels of cytokine production, liver and lung metastasis were inhibited significantly in both wild-type and CXCR6(-/-) mice treated with glycolipids. Single doses of alpha-GalCer, alpha-C-GalCer, or OCH were sufficient to prevent liver metastasis and subsequent doses failed to elicit optimal cytokine responses. Our findings implicate a role for CXCR6 in natural immunosurveillance against liver metastasis. However, CXCR6 deficiency could be overcome by systemic iNKT cell activation, demonstrating that even suboptimal iNKT cell activation can protect against metastasis.
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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) | 0.001 | 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) | 0.002 | 0.001 |
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".