<i>Porphyromonas gingivalis</i> fuels colorectal cancer through CHI3L1-mediated iNKT cell-driven immune evasion
Bibliographic record
Abstract
The interaction between the gut microbiota and invariant Natural Killer T (iNKT) cells plays a pivotal role in colorectal cancer (CRC). The pathobiont Fusobacterium nucleatum influences the anti-tumor functions of CRC-infiltrating iNKT cells. However, the impact of other bacteria associated with CRC, like Porphyromonas gingivalis, on their activation status remains unexplored. In this study, we demonstrate that mucosa-associated P. gingivalis induces a protumour phenotype in iNKT cells, subsequently influencing the composition of mononuclear-phagocyte cells within the tumor microenvironment. Mechanistically, in vivo and in vitro experiments showed that P. gingivalis reduces the cytotoxic functions of iNKT cells, hampering the iNKT cell lytic machinery through increased expression of chitinase 3-like-1 protein (CHI3L1). Neutralization of CHI3L1 effectively restores iNKT cell cytotoxic functions suggesting a therapeutic potential to reactivate iNKT cell-mediated antitumour immunity. In conclusion, our data demonstrate how P. gingivalis accelerates CRC progression by inducing the upregulation of CHI3L1 in iNKT cells, thus impairing their cytotoxic functions and promoting host tumor immune evasion.
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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) | 0.002 | 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".