The effects of CCR5 inhibition on regulatory T-cell recruitment to colorectal cancer
Bibliographic record
Abstract
BACKGROUND: Regulatory T cells (Treg) are enriched in human colorectal cancer (CRC) where they suppress anti-tumour immunity. The chemokine receptor CCR5 has been implicated in the recruitment of Treg from blood into CRC and tumour growth is delayed in CCR5-/- mice, associated with reduced tumour Treg infiltration. METHODS: Tissue and blood samples were obtained from patients undergoing resection of CRC. Tumour-infiltrating lymphocytes were phenotyped for chemokine receptors using flow cytometry. The presence of tissue chemokines was assessed. Standard chemotaxis and suppression assays were performed and the effects of CCR5 blockade were tested in murine tumour models. RESULTS: Functional CCR5 was highly expressed by human CRC infiltrating Treg and CCR5(high) Treg were more suppressive than their CCR5(low) Treg counterparts. Human CRC-Treg were more proliferative and activated than other T cells suggesting that local proliferation could provide an alternative explanation for the observed tumour Treg enrichment. Pharmacological inhibition of CCR5 failed to reduce tumour Treg infiltration in murine tumour models although it did result in delayed tumour growth. CONCLUSIONS: CCR5 inhibition does not mediate anti-tumour effects as a consequence of inhibiting Treg recruitment. Other mechanisms must be found to explain this effect. This has important implications for anti-CCR5 therapy in CRC.
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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".