Lack of Functional Selectin Ligand Interactions Compromises Long Term Tumor Protection by CD8+ T Cells
Bibliographic record
Abstract
Central memory CD8(+) T cells expressing the adhesion molecule CD62L (L-selectin) are potent mediators of anti-cancer immunity due to their ability to proliferate extensively upon antigen re-stimulation. The interaction of selectin with its ligands mediates leukocyte rolling along high endothelial venules. Mice deficient in α(1,3) Fucosyltransferase IV and VII (FtDKO) lack functional L, P and E selectin ligands. Thus, we addressed whether the lack of selectin ligand interactions alters tumor protection by CD8(+) T cells in FtDKO mice. Listeria monocytogenes-OVA (LM-OVA) infection evoked potent OVA-specific CD8(+) T cells that proliferated and contracted at similar kinetics and phenotype in FtDKO and wild-type mice. Additionally, OVA-specific CD8(+) T cells in both mouse strains exhibited similar phenotypic differentiation, in vivo cytolytic activity and IFN-γ expression. However, FtDKO mice succumbed to B16-OVA tumors significantly earlier than wild-type mice. In contrast, FtDKO mice evoked strong recall memory CD8(+) T cell responses and protection to systemic LM-OVA re-challenge. The diminished tumor protection in FtDKO mice was not related to defective antigen presentation by dendritic cells or reduced proliferation of antigen-specific CD8(+) T cells. However, WT or FtDKO OVA-specific CD8(+) T cells showed significantly reduced ability to traffic to lymph nodes upon adoptive transfer into naïve FtDKO recipients. Furthermore, FtDKO OVA-specific CD8(+) T cells displayed poor ability to infiltrate tumors growing in WT mice. These results reveal that selectin ligand expression on host endothelium as well CD8(+) T cells may be important for their efficient and continued extravasation into peripheral tumors.
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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".