The tumor-derived cytokine Chi3l1 induces neutrophil extracellular traps that promote T cell exclusion in triple-negative breast cancer
Bibliographic record
Abstract
In triple-negative breast cancer (TNBC), stromal restriction of CD8 + T cells associates with poor clinical outcomes and lack of responsiveness to immune-checkpoint blockade (ICB). To identify mediators of T cell stromal restriction, we profiled murine breast tumors lacking the transcription factor Stat3, which is commonly hyperactive in breast cancers and promotes an immunosuppressive tumor microenvironment. Expression of the cytokine Chi3l1 was decreased in Stat3 −/− tumors. CHI3L1 expression was elevated in human TNBCs and other solid tumors exhibiting T cell stromal restriction. Chi3l1 ablation in the polyoma virus middle T (PyMT) breast cancer model generated an anti-tumor immune response and delayed mammary tumor onset. These effects were associated with increased T cell tumor infiltration and improved response to ICB. Mechanistically, Chi3l1 promoted neutrophil recruitment and neutrophil extracellular trap formation, which blocked T cell infiltration. Our findings provide insight into the mechanism underlying stromal restriction of CD8 + T cells and suggest that targeting Chi3l1 may promote anti-tumor immunity in various tumor types.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".